example of cost analysis in research

Research Methodology: Cost Benefit Analysis

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About Cost Benefit Analysis

Cost benefit analysis is a systematic process for calculating and comparing benefits and costs of a project. A cost benefit analysis finds, quantifies, and adds all the positive factors (the benefits). Then it identifies, quantifies, and subtracts all the negatives (the costs). The difference between the two indicates whether the planned action is advisable. The real trick to doing a cost benefit analysis well is making sure you include all the costs and all the benefits and properly quantify them.

• An Introduction to Cost Benefit Analysis San José State University Department of Economics
• Cost Benefit Analysis Examples of techniques designed to determine the feasibility of a project or plan by quantifying costs and benefits, including external costs and benefits.
• Benefit-Cost Analysis FEMA

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" cost benefit analysis " OR " benefit cost analysis " OR " costs and cost analysis " OR " cost effectiveness " AND " research methodologies "

Method Demonstrated by IQPs

• A Cost-Benefit Analysis of a Geothermal Power Plant and Spa Baird, Timothy Brian;Chan, Chun-shek Charles;Kast, Peter Gregory
• Energy Efficiency in Water Infrastructure Marinelli, Andy; Patenaude, Rachel Lynn; Toomey, Mary Kate
• Leicester Energy Study Gabrielson, Christopher Daniel; Hanly, Stephen William; Montville, Laura Elizabeth

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An Expert Guide to Cost Benefit Analysis

By Joe Weller | December 8, 2016

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In business today, it’s essential to get the most out of every idea, option, and investment. To accomplish this, many organizations - from large enterprises to startups and small businesses -  use cost benefit analyses to help make important decisions. Using a cost benefit analysis can help teams identify the highest and best return on an investment based on the cost, resources, and risk involved.   In this article, we’ll walk you through the process of cost benefit analysis, and offer insight and tips from industry experts. They’ll shine a light on the risks and uncertainties you should be aware of as you work, and provide real-world examples to show cost benefit analysis in action.

Cost benefit analysis: What is it?

A cost benefit analysis (also known as a benefit cost analysis) is a process by which organizations can analyze decisions, systems or projects, or determine a value for intangibles. The model is built by identifying the benefits of an action as well as the associated costs, and subtracting the costs from benefits. When completed, a cost benefit analysis will yield concrete results that can be used to develop reasonable conclusions around the feasibility and/or advisability of a decision or situation.   Why Use Cost Benefit Analysis? Organizations rely on cost benefit analysis to support decision making because it provides an agnostic, evidence-based view of the issue being evaluated—without the influences of opinion, politics, or bias. By providing an unclouded view of the consequences of a decision, cost benefit analysis is an invaluable tool in developing business strategy, evaluating a new hire, or making resource allocation or purchase decisions.   Origins of Cost Benefit Analysis The earliest evidence of the use of cost benefit analysis in business is associated with a French engineer, Jules Dupuit, who was also a self-taught economist. In the mid-19th century, Dupuit used basic concepts of what later became known as cost benefit analysis in determining tolls for a bridge project on which he was working. Dupuit outlined the principles of his evaluation process in an article written in 1848, and the process was further refined and popularized in the late 1800s by British economist Alfred Marshall, author of the landmark text, Principles of Economics (1890).

Scenarios Utilizing Cost Benefit Analysis

As mentioned previously, cost benefit analysis is the foundation of the decision-making process across a wide variety of disciplines. In business, government, finance, and even the nonprofit world, cost benefit analysis offers unique and valuable insight when:

• Developing benchmarks for comparing projects
• Deciding whether to pursue a proposed project
• Evaluating new hires
• Weighing investment opportunities
• Measuring social benefits
• Appraising the desirability of suggested policies
• Assessing change initiatives
• Quantifying effects on stakeholders and participants

How to Do a Cost Benefit Analysis

While there is no “standard” format for performing a cost benefit analysis, there are certain core elements that will be present across almost all analyses. Use the structure that works best for your situation or industry, or try one of the resources and tools listed at the end of this article. We’ll go through the five basic steps to performing a cost benefit analysis in the sections below, but first, here’s a high-level of overview:  

• Establish a framework to outline the parameters of the analysis
• Identify costs and benefits so they can be categorized by type, and intent
• Calculate costs and benefits across the assumed life of a project or initiative
• Compare cost and benefits using aggregate information
• Analyze results and make an informed, final recommendation

  As with any process, it’s important to work through all the steps thoroughly and not give in to the temptation to cut corners or base assumptions on opinion or “best guesses.” According to a paper from Dr. Josiah Kaplan, former Research Associate at the University of Oxford, it’s important to ensure that your analysis is as comprehensive as possible:   “The best cost-benefit analyses take a broad view of costs and benefits, including indirect and longer-term effects, reflecting the interests of all stakeholders who will be affected by the program.”

How to Establish a Framework

In establishing the framework of your cost benefit analysis, first outline the proposed program or policy change in detail. Look carefully at how you position what exactly is being evaluated in relationship to the problem being solved. For example, the analysis associated with the question, “should we add a new professor to our staff?” will be much more straightforward than a broader programmatic question, such as, “how should we resolve the gaps in our educational offering?”   Example:

Once your program or policy change is clearly outlined, you’ll need to build out a situational overview to examine the existing state of affairs including background, current performance, any opportunities it has brought to the table, and its projected performance in the future. Also make sure to factor in an objective look at any risks involved in maintaining the status quo moving forward.   Now decide on how you will approach cost benefits. Which cost benefits should be included in your analysis? Include the basics, but also do a bit of thinking outside the box to come up with any unforeseen costs that could impact the initiative in both the short and long term.   In some cases geography could play a role in determining feasibility of a project or initiative. If geographically dispersed stakeholders or groups will be affected by the decision being analyzed, make sure to build that into the framework upfront, to avoid surprises down the road. Conversely, if the scope of the project or initiative may scale beyond the intended geographic parameters, that should be taken into consideration as well.

Identify and Categorize Costs and Benefits

Now that your framework is in place, it’s time to sort your costs and benefits into buckets by type. The primary categories that costs and benefits fall into are direct/indirect , tangible/intangible , and real :  

• Direct costs are often associated with production of a cost object (product, service, customer, project, or activity)
• Indirect costs are usually fixed in nature, and may come from overhead of a department or cost center
• Tangible costs are easy to measure and quantify, and are usually related to an identifiable source or asset, like payroll, rent, and purchasing tools
• Intangible cost s are difficult to identify and measure, like shifts in customer satisfaction, and productivity levels
• Real costs are expenses associated with producing an offering, such as labor costs and raw materials

  Now that you’ve developed the categories into which you’ll sort your costs and benefits, it’s time to start crunching numbers.

How to Calculate Costs and Benefits

With the framework and categories in place, you can start outlining overall costs and benefits. As mentioned earlier, it’s important to take both the short and long term into consideration, so ensure that you make your projections based on the life of the program or initiative, and look at how both costs and benefits will evolve over time.

TIP: People often make the mistake of monetizing incorrectly when projecting costs and benefits, and therefore end up with flawed results. When factoring in future costs and benefits, always be sure to adjust the figures and convert them into present value.

Compare Aggregate Costs and Benefits

Here we’ll determine net present values by subtracting costs from benefits, and project the timeframe required for benefits to repay costs, also known as return on investment (ROI).   Example:

The process doesn’t end there. In certain situations, it’s important to address any serious concerns that could impact feasibility from a legal or social justice standpoint. In cases like these, it can be helpful to incorporate a “with/without” comparison to identify areas of potential concern.   With/Without Comparison The impact of an initiative can be brought into sharp focus through a basic “with/without” comparison. In other words, this is where we look at what the impact would be—on organizations, stakeholders, or users—both with, and without, this initiative.   Thayer Watkins, who taught a course on cost benefit analysis during his 30-year career as a professor in the San Jose State University Department of Economics, offers this example of a “with/without” comparison:   “The impact of a project is the difference between what the situation in the study area would be with and without the project. So that when a project is being evaluated the analysis must estimate not only what the situation would be with the project but also what it would be without the project. For example, in determining the impact of a fixed guideway rapid transit system such as the Bay Area Rapid Transit (BART) in the San Francisco Bay Area the number of rides that would have been taken on an expansion of the bus system should be deducted from the rides provided by BART and likewise the additional costs of such an expanded bus system would be deducted from the costs of BART. In other words, the alternative to the project must be explicitly specified and considered in the evaluation of the project.”   TIP: Never confuse with/without with a before-and-after comparison.

3 Steps for Analyzing the Results and Make a Recommendation

In the home stretch of the cost benefit analysis, you’ll be looking at the results of your work and forming the basis to make your decision.   1. Perform Sensitivity Analysis Dr. Kaplan recommends performing a sensitivity analysis (also known as a “what-if”) to predict outcomes and check accuracy in the face of a collection of variables. “Information on costs, benefits, and risks is rarely known with certainty, especially when one looks to the future,” Dr. Kaplan says. “This makes it essential that sensitivity analysis is carried out, testing the robustness of the CBA result to changes in some of the key numbers.”   EXAMPLE of Sensitivity Analysis In trying to understand how customer traffic impacts sales in Bob’s Pie Shop, in which sales are a function of both price and volume of transactions, let’s look at some sales figures:

Bob has determined that a 10% increase in store traffic will boost his pie sales by 5%. This allows Bob to build the following sensitivity analysis, based upon his sales of 400 pies last year, that demonstrates that his pie sales are significantly impacted by fluctuations or growth in store traffic:

2. Consider Discount Rates When evaluating your findings, it’s important to take discount rates into consideration when determining project feasibility.  

• Social discount rates – Used to determine the value to funds spent on government projects (education, transportation, etc.)
• Hurdle rates – The minimum return on investment required by investors or stakeholders
• Annual effective discount rates – Based on a percentage of the end-of-year balance, the amount of interest paid or earned

Here is a template where you can make your Cost Benefit Analysis

Download Simple Cost Benefit Analysis Template

Microsoft Excel | Smartsheet

3. Use Discount Rates to Determine Course of Action After determining the appropriate discount rate, look at the change in results as you both increase and decrease the rate:  

• Positive - If both increasing and decreasing the rate yields a positive result, the policy or initiative is financially viable.
• Negative - If both increasing and decreasing the rate yields a negative result, revisit your calculations based upon adjusting to a zero-balance point, and evaluate using the new findings.

  Based upon these results, you will now be able to make a clear recommendation, grounded in realistic data projections.

The Risks and Uncertainties of Cost Benefit Analysis

Despite its usefulness, cost benefit analysis has several associated risks and uncertainties that are important to note. These risks and uncertainties can result from human agendas, inaccuracies around data utilized, and the use of heuristics to reach conclusions.   Know the Risks Much of the risk involved with cost benefit analysis can be correlated to the human elements involved. Stakeholders or interested parties may try to influence results by over- or understating costs. In some cases, supporters of a project may insert a personal or organizational bias into the analysis.   On the data side, there can be a tendency to rely too much on data compiled from previous projects. This may inadvertently yield results that don’t directly apply to the situation being considered. Since data leveraged from an earlier analysis may not directly apply to the circumstances at hand, this may yield results that are not consistent with the requirements of the situation being considered. Using heuristics to assess the dollar value of intangibles may provide quick, “ballpark-type” information, but it can also result in errors that produce an inaccurate picture of costs that can invalidate findings.   In addressing risk, it’s sometimes helpful to utilize probability theory to identify and examine key patterns that can influence the outcome.   Uncertainties There are several “wild-card” issues that can influence the results of any cost benefit analysis, and while they won’t apply in every situation, it’s important to keep them in mind as you work:  

• Accuracy affects value – Inaccurate cost and benefit information can diminish findings around value.
• Don’t rely on intuition – Always research benefits and costs thoroughly to gather concrete data—regardless of your level of expertise with the subject at hand.
• Cash is unpredictable – Revenue and cash flow are moving targets, experiencing peaks and valleys, and translating them into meaningful data for analysis can be challenging.
• Income influences decisions – Income level can drive a customer’s ability or willingness to make purchases.
• Money isn’t everything – Some benefits cannot be directly reflected in dollar amounts.
• Value is subjective – The value of intangibles can always be subject to interpretation.
• Don’t automatically double up – When measuring a project in multiple ways, be mindful that doubling benefits or costs can results in inconsistent results.

  Controversial Aspects When thinking about the most controversial aspects of cost benefit analysis, all paths seem to lead to intangibles. Concepts and things that are difficult to quantify, such as human life, brand equity, the environment, and customer loyalty can be difficult to map directly to costs or value.    With respect to intangibles, Dr. Kaplan suggests that using the cost benefit analysis process to drive more critical thinking around all aspects of value—perceived and concrete—can be beneficial outcomes. “[Cost benefit analysis] assumes that a monetary value can be placed on all the costs and benefits of a program, including tangible and intangible returns. ...As such, a major advantage of cost-benefit analysis lies in forcing people to explicitly and systematically consider the various factors which should influence strategic choice,” he says.

Cost Benefit Analysis in the Real World

Extending Transport Options in Seattle  

Originally built for the 1962 World’s Fair, the Seattle monorail runs between the Seattle Center and the city’s downtown area. Several times over the past 50+ years, the city has considered extending monorail service to key areas in order to provide more transport options for residents. The following is an excerpt from a cost benefit analysis performed by DJM Consulting and ECONorthwest on behalf of the Elevated Transportation Company to assess an expansion project.   Costs The estimated costs for constructing and operating the monorail are $1.68 billion (in 2002 dollars). This includes a total capital cost of $1.26 billion and a total discounted stream of operating costs of $420 million (at approximately $29 million a year), using the same discount rate (7.95%). Operating costs were discounted over a span of 22 years, from 2008 through 2029.   Benefits

Benefit type                                                     Benefit value (millions, 2002$) Value of travel time savings                           $77.1 Parking savings                                               28.7 Reduced auto operating/ownership costs       11.2 Reliability                                                         7.7 Road capacity for drivers                                 4.6 Reduction in bus-related accidents                 3.7 Reduction in auto-related accidents                2.6 2020 Benefits                                                  $135.6

Benefits accrue for 23 years from 2007 through 2029. A discount rate of 7.95% was used to estimate the total benefits, in 2002 dollars. The net benefits were evaluated to be $2,067,263,000.   Analysis

• Net present value B-C = $390,164,000
• Benefit-cost ratio B/C = 1.23
• Nominal rate of return = 7.95%

  Sensitivity Analysis A team of outside engineers and contractors determined that there is a 60% chance the monorail project would come in at or under budget and a 90% chance the project will come in under 1.15 times the budget. The travel demand forecasters included a 10% range around their estimate of future monorail ridership. For the case where the costs are low and the benefits are high, a 9.9% return is expected. For the case where the costs are higher than expected and the benefits are lower, a 5.2% return is expected.   Read the full analysis here .   Solid Waste Reduction in California California's Department of Resources Recycling and Recovery’s mission is to help state residents achieve the highest waste reduction, recycling and reuse goals in the U.S. The following is an excerpt from a cost benefit analysis performed in 1997 to compare the costs of Cardiovascular Group’s (CVG) solid waste reduction program to its economic benefits.   Costs According to the Environmental Manager, one employee spends eight hours per day on recycling duties. This employee is paid an average of $5.50 per hour. The Environmental Manager spends an estimated 5% of his time ($100,000/per year compensation) directing the solid waste reduction program. Utilizing this cost data, the calculations below demonstrate that CVG spent an estimated $16,440 in 1997 on its solid waste reduction program:   (1 Employee) X ($5.50/hr.) X (8 hrs./day) X (260 work days/year) = $11,440 per year + 5%(100,000) = $16,440 per year   Benefits 1995 Disposal cost reductions (1989 Baseline disposal costs – 1995 disposal costs) = $99,190 - $26,800 = $72,390   1996 Disposal cost reductions (1989 Baseline disposal costs – 1996 disposal costs) = $99,190 - $33,850 = $65,340   Average Annual Disposal Cost Reduction (DCR) (1995 DCR + 1996 DCR)/ 2 = ($72,390 + $65,340)/2 = $68,865   Analysis

• Nominal Rate of Return = 7.95%

  From these data, it is clear that CVG has benefited economically from its solid waste reduction programs. Average annual costs amounted to $16,440 per year, while benefits equaled $1,308,865 per year. Therefore, net savings from CVG’s solid waste reduction program amounted to $1,292,425 per year.

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• Systematic review
• Open access
• Published: 12 March 2021

Cost analysis in implementation studies of evidence-based practices for mental health and substance use disorders: a systematic review

• Diana M. Bowser 1 ,
• Brandy F. Henry   ORCID: orcid.org/0000-0002-0667-9283 1 , 2 &
• Kathryn E. McCollister 3  

Implementation Science volume  16 , Article number:  26 ( 2021 ) Cite this article

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This study is a systematic literature review of cost analyses conducted within implementation studies on behavioral health services. Cost analysis of implementing evidence-based practices (EBP) has become important within implementation science and is critical for bridging the research to practice gap to improve access to quality healthcare services. Costing studies in this area are rare but necessary since cost can be a barrier to implementation and sustainment of EBP.

We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology and applied the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Key search terms included: (1) economics, (2) implementation, (3) EBP, and (4) behavioral health. Terms were searched within article title and abstracts in: EconLit, SocINDEX, Medline, and PsychINFO. A total of 464 abstracts were screened independently by two authors and reduced to 37 articles using inclusion and exclusion criteria. After a full-text review, 18 articles were included.

Findings were used to classify costs into direct implementation, direct services, and indirect implementation. While all studies included phases of implementation as part of their design, only five studies examined resources across multiple phases of an implementation framework. Most studies reported direct service costs associated with adopting a new practice, usually summarized as total EBP cost, cost per client, cost per clinician, and/or cost per agency. For studies with detailed analysis, there were eleven direct cost categories represented. For five studies that reported costs per child served, direct implementation costs varied from $886 to $9470 per child, while indirect implementation costs ranged from $897 to $3805 per child.

Conclusions

This is the first systematic literature review to examine costs of implementing EBP in behavioral healthcare settings. Since 2000, 18 studies were identified that included a cost analysis. Given a wide variation in the study designs and economic methods, comparison across studies was challenging, which is a major limitation in the field, as it becomes difficult to replicate studies or to estimate future costs to inform policy decisions related to budgeting. We recommend future economic implementation studies to consider standard economic costing methods capturing costs across implementation framework phases to support comparisons and replicability.

Peer Review reports

Contributions to the literature

Implementation research of evidence-based behavioral health interventions has grown dramatically in the past 10 years; however, costing methods and types are still not standardized which makes cost comparisons across studies difficult.

We describe the types of costs and costing methods which have been used to date in implementation research of evidence-based behavioral health interventions.

Results of this analysis inform future studies in identifying appropriate costs and methods to include in research which will improve rigor and replicability.

Introduction

Cost analysis is broadly applied through economic evaluations of treatment interventions and related programs for mental health/substance use disorders (SUD), often as part of an effectiveness/cost-effectiveness study. Recently, cost analysis has become an important area within the implementation science field, which focuses on the translation of research into practice and disseminating methods and applications of evidence-based practices (EBP) on a broader scale [ 1 ]. Implementation science has developed to understand the factors that facilitate the adoption of EBP to assist in bridging the research to practice gap, and to improve the accessibility and quality of health services [ 2 ]. Health services focused on mental health and SUD, across the lifespan, fall under the broader area of behavioral health. Research and evaluation of the implementation of EBP in behavioral healthcare is a rapidly expanding area of importance, particularly since EBP adoption in this area has lagged behind that in traditional healthcare settings. Economic studies in this area are especially important since costs can be a barrier to implementation of EBPs in behavioral healthcare agencies [ 3 ], and funding/payment for behavioral health services are often separate from other health services.

In their seminal article, Proctor et al. specifically called for implementation research to include costs as an outcome [ 4 ]. The inclusion of costs in implementation research is important because the costs of implementing EBP can drive decision-making by service providers. Such decision-making impacts whether an EBP will be adopted or sustained, which ultimately impacts service quality and patient outcomes [ 5 ]. However, despite the importance of including costs, a systematic review of implementation research on practice guidelines found that only about a quarter of implementation studies include costs [ 6 ]. This is relevant because the bulk of costing studies in implementation research focuses on practice guidelines [ 5 ].

Implementation studies within the broader health service delivery field that included economic evaluations were summarized in a recent systematic literature review by Roberts et al. [ 7 ]. This review identified 30 studies, most of which were hospital-based. More than half of the included studies used cost-effectiveness analyses, while smaller proportions used cost utility analyses or cost-consequence analyses. Measured costs included staff training, development of new care processes/pathways, and patient/caregiver-related costs. While this study provided a useful overview of the economic tools used in implementation research, it did not specify how these tools have been used in the area of nonhospital-based behavioral health services or how costs are collected across implementation phases.

The extent to which researchers have included costs in their implementation studies of EBP in behavioral health services is not known. Additionally, the costing methods applied in these studies have not been systematically described. We address this gap by conducting a systematic review of the literature to understand the types of costs and costing methods which have been used to date in implementation research of evidence-based behavioral health interventions in the USA and Canada. We focus on these two countries due to their similarities in the epidemiology of behavioral health disorders, overlapping related health policies [ 8 ], and flow of both patients and programs across the border [ 9 ]. We exclude other countries due to the unique nature of the US healthcare financing [ 10 ]. Addressing these issues can elucidate areas of potential growth in how implementation researchers incorporate cost analysis as a core measure. While costs are an important driver, they certainly do not overshadow the importance of patient outcomes, which is why we focus only on the implementation of EBP, which have already been linked to quality services.

Identification of studies

We conducted an initial systematic review (February 2019) and updated the search prior to submission (April 2020). We investigated costing studies in behavioral health implementation research using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology [ 11 ] and checklist [ 12 ]. We developed key search terms through reviewing search terms in MeSH® [ 13 ]. Key search terms included four areas: (1) economics, (2) implementation, (3) EBP, and (4) behavioral health. Included articles contained at least one key term from each area. Specific key terms were economic, cost, implementation, evidence-based practice, behavioral health, mental health, mental illness, mental disorder, psychiatric, addiction, drug abuse, substance use, and drug use. Key words related to specific types of substances (e.g., opioids) were not included to reduce complexity.

We based our search strategy on suggestions from psychology and economics published best practices for systematic literature reviews [ 14 , 15 ]. Terms were searched within article title and abstracts in the following databases: EconLit, SocINDEX, Medline, and PsychINFO. We did not include Embase, as we were not interested in biomedically or pharmaceutically related research, and excluded studies focused only on drugs. Included articles contained at least one key term from each area. Abstracts were downloaded into Excel and independently screened by two of the authors to determine if they met inclusion and exclusion criteria. Full-text screening was conducted for all articles meeting inclusion criteria. Full-text screening was also conducted for articles where insufficient information was provided in the abstract to determine if criteria were met. The Boolean search and selection criteria are listed below. There is no published review protocol.

((TI economic) OR (TI cost) OR (AB economic) OR (AB cost)) AND ((TI implementation) OR (AB implementation)) AND ((TI evidence based practice) OR (AB evidence based practice)) AND ((TI behavioral health) OR (AB behavioral health) OR (TI mental health) OR (AB mental health) OR (TI mental illness) OR (AB mental illness) OR (TI mental disorder) OR (AB mental disorder) OR (TI psychiatric) OR (AB psychiatric) OR (TI addiction) OR (AB addiction) OR (TI drug abuse) OR (AB drug abuse) OR (TI substance use) OR (AB substance use) OR (TI drug use) OR (AB drug use))

Inclusion criteria

The following are the inclusion criteria:

Articles that address implementation studies of behavioral health services which incorporate costing (formal economic analysis was not required for inclusion)

Studies published after 2000

Studies only if original research is presented (quantitative or qualitative data)

Community-based studies (outpatient level of care or services provided to people residing in the community, rather than a hospital)

Peer-reviewed articles

Published in English

Research was conducted in the USA or Canada

Studies providing services to people of any age

Exclusion criteria

The following are excluded in the study:

Published before 2000

Editorials, newspapers, and other pieces of popular media

Dissertations or theses

Book chapters, book reviews, proceedings, government and/or organization reports, and other publications from the gray literature

Systematic reviews

Protocols without preliminary data

Non-implementation-based studies

Published in a language other than English.

Studying a system outside the USA or Canada

Studies based in hospitals

Did not include costing data

Focusing solely on comparing medications

Data extraction and analysis

As shown in Fig. 1 , the initial abstract search returned 636 articles (four from EconLit, 33 from SocIndex, 335 from Medline, and 264 from PsychINFO). Seven articles were added based on review of references during full text review. After excluding articles based on date of publication and those that were duplicates, a total of 464 unique abstracts were screened independently by two authors. Authors also screened articles individually for risk of bias, but did not exclude any articles based on this issue. This was reduced to 37 articles after applying inclusion/exclusion criteria to abstracts. The final number of included articles after full-text reviews was 18.

Search results using PRISMA

The following characteristics were extracted from all included studies: authors, year published, journal, area of behavioral health, type of EBP, sample size, implementation framework, economic methodology, costing approach, costing perspective(s), cost categories and specific resources, cost analysis results, and economic study design. Thematic analysis was conducted to summarize similarities and differences across studies. Content analysis was used to identify how these characteristics overlapped within included studies, such as identifying costing perspectives and resource categories that overlapped across studies. Content analysis classified three categories of costs for the purpose of the study: direct implementation, direct service, and indirect implementation. For a subset of studies, direct and indirect implementation cost results were extracted and reported. In studies where summary cost estimates were not provided, we used the aggregated cost results (as presented) combined with patient/family/client sample sizes provided within the articles to approximate summary costs (i.e., cost per child served) to support comparisons across studies.

The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist [ 16 ] was used to assess the quality of the articles. This checklist was designed to provide a standardized reporting system for economic evaluations of health interventions. Since we included other implementation studies with costing components, in addition to economic evaluations, we reported the overall percent of included items on the checklist (removing not applicable items from the denominator, rather than a score). We eliminated several checklist items that were not relevant for costing studies that did not also include an economic evaluation. We converted CHEERS checklist quality scores used in previous research [ 17 , 18 ] to a percentage. Previous studies applied the following scoring categories: excellent (24 out of 24 points or 100%), good (at least 18 out of 24 points or 75-99%), average (at least 12 out of 24 points or 50-74%), and poor (11 or fewer out of 24 points or 0-49%).

Table 1 provides the list of included studies with details on study design, type of EBP, target population, implementation framework, and economic methodology. Only one of the included articles was published before 2010 [ 19 ]. Most articles (12 articles) were published in specialty journals focusing on behavioral health. The remainder were published in specialty journals related to public health (four articles [ 20 , 21 , 22 , 23 ]), children’s services (one article [ 19 ]), or implementation science (one article [ 24 ]). Several studies focused on specific demographic groups [children with substance use disorders, mental health disorders, or trauma (six articles [ 19 , 23 , 24 , 25 , 26 , 27 ]), adolescents/youth with mental health disorders (two articles [ 21 , 28 ]), justice-involved youth (two articles [ 29 , 30 ]), geriatric mental health (one article [ 20 ]), and veteran’s mental health (one article [ 31 ]). Studies focusing on specific diagnoses included: alcohol use (one article [ 32 ]), addiction (one article [ 33 ]), co-occurring disorders (one article [ 34 ]), mental health disorders (two articles [ 22 , 35 ]), and serious mental illness (one article [ 36 ]).

Most articles (15 articles) investigated the implementation of a single EBP. However, some studies (three articles) considered implementation of multiple practices [ 21 , 33 , 36 ]. EBPs delivered to patients included multisystemic therapy, screening and brief intervention for alcohol use, trauma-focused cognitive behavioral therapy, gender-responsive trauma-informed care, assertive community treatment, integrated treatment, family psychoeducation, integrated dual disorders treatment, illness management/recovery, and supported employment. EBPs that were delivered to providers focused on remote learning and mentoring, improved practice guidelines, quality measures, and enhanced interagency collaboration.

Studies varied in sample size and unit of analysis. Four studies measured EBP adoption on individual patient outcomes. The sample size in these studies ranged from 72-1,869 people; however, three of the studies had a sample size between 72-155 [ 23 , 25 , 34 ]. One study measured the impact on families (N=45) [ 19 ]. Another study measured outcomes for patients (N=1,410) and clinicians (N=574) [ 28 ]. Yet another study measured outcomes for clinicians only (N=154) [ 20 ]. Three studies focused on management staff and/or teams, with sample sizes ranging from 32 (teams) to 75 (staff) [ 21 , 31 , 35 ]. Eight studies measured EBP impact on the organization/agency or system and had sample sizes ranging from 3-307 organizations [ 22 , 24 , 26 , 27 , 30 , 32 , 33 , 36 ].

Implementation frameworks and costing approaches

Most articles (11 articles [ 21 , 24 , 26 , 27 , 28 , 29 , 31 , 32 , 33 , 34 , 35 ],) reported using an implementation framework, although there were no studies that reported using the same framework. This is indicative of the broad set of implementation frameworks that exist within the field, and the complexity of internal and external factors that must be considered in evaluating an implementation process based on type of EBP, setting, and target population. The Consolidated Framework for Implementation Research (CFIR) provides a point of reference as it includes a comprehensive list of constructs (intervention characteristics, agency/staff characteristics, outer and inner contexts within which the agency operates, and the implementation process itself) [ 37 ]. In this framework, cost is mentioned as a key measure of the implementation process, but no details are provided as to recommended approaches, measures, or data sources for estimating implementation costs. In this review, about half (five articles) of the included studies were developing a framework, or specific tools, for understanding implementation processes and/or phases. These tools/frameworks focused on costs (two articles [ 26 , 33 ]), EBP sustainability (two articles [ 27 , 32 ]), and implementation stages and fidelity (one article [ 24 ]). The remaining studies adopted existing implementation frameworks to conceptually guide their research.

Most implementation frameworks follow a phased structure, generally including pre-implementation, implementation, and sustainment activities and corresponding evaluation metrics. Cost analyses must define an analytic perspective, and in implementation research, two key perspectives are the agency/provider/organization that would be deciding to adopt an EBP and the payer, sometimes the agency itself, health insurance plan, or Medicaid/Medicare. In cost-effectiveness research, the Second Panel on Cost-Effectiveness in Health and Medicine recommends adopting the healthcare sector and societal perspectives, both of which are broader than a provider or payer perspective. The societal perspective includes costs to the healthcare system, other systems (e.g., justice, education, social services), and patient/caregivers. The cost analysis perspective defines the relevant resources and monetary conversion factors for estimating costs across implementation phases. General categories of implementation costs include direct labor costs, indirect labor costs, and nonlabor costs [ 5 ]. Direct labor costs reflect personnel time spent implementing an EBP, including time spent training and delivering services to clients. Indirect labor costs refer to personnel time outside of clinical services, such as time spent recording case notes or administrative duties. Nonlabor costs essentially cover all other resources required for implementation such as contracted services, equipment, supplies, licensing, building/space costs, and administrative overhead. Studies use other many terms to characterize costs such as direct implementation costs, direct service costs, opportunity costs, accounting costs, as well as fixed costs and variable costs. All implementation phases (pre-implementation, implementation, and sustainment) have some combination of these costs. Pre-implementation costs would typically include labor costs associated with meetings and trainings during preparation and planning phases, as well as one-time expenditures on equipment or supplies to prepare for the implementation phase. Implementation costs would include labor costs for those delivering services or performing administrative roles, and recurring expenditures on supplies, equipment, space, communications. Sustainment costs would include the cost of implementation resources that are required to continuously support the EBP.

For the purposes of this review, we classify three categories of costs guided by the presentation of costs in the included studies: direct implementation costs, direct service costs, and indirect implementation costs (Table 2 ). As shown in Table 2 , direct implementation costs capture the actual expenditures incurred by agencies/providers implementing the EBP for pre-implementation and implementation activities such as meetings, trainings, purchasing training manuals, and travel. Direct implementation costs were calculated mainly through activity-based costing, tallying the time spent on implementation activities and applying reported or imputed salary data to estimate the direct labor costs for implementation activities. Direct service costs are those costs associated with billable healthcare and other services resulting from the implementation process or specific EBP activities. About half of the included studies calculated direct service costs using Medicaid or other claims data [ 19 , 20 , 22 , 23 , 24 , 25 , 26 , 29 , 30 , 34 ].

Indirect implementation costs capture the opportunity cost for agencies due to lost revenues and/or time spent on implementation activities rather than standard (pre-implementation) clinical activities that could be billed and reimbursed. Indirect costs were estimated using the amount of time that a clinician reported spending on implementation activities, multiplied by the reimbursement rate for their billable activities [ 27 , 28 ]. Two of the 18 studies measured the indirect costs associated with implementation of EBPs [ 19 , 24 ]. Seven studies do not report cost figures, but rather used primary data collection and qualitative methods to summarize specific examples of both direct and indirect implementation costs incurred at the agency during the implementation process [ 21 , 22 , 24 , 32 , 33 , 35 , 36 ]. Almost all studies (sixteen) applied direct costing, although one study used cost-benefit analysis [ 29 ], and another used cost-effectiveness analysis [ 28 ]. Different costing perspectives were represented across the 18 studies. Eleven studies described using a provider (i.e., organizational) perspective, with one other study also including costs incurred by organization staff (but not reimbursed directly) [ 31 ] and another including costs incurred by staff as well as consumers [ 21 ]. One study applied a facility perspective (one location of a multi-location organization) [ 30 ], one reported an interagency perspective (e.g., representing costs incurred across collaborating agencies) [ 19 ], and one reported a taxpayer perspective [ 29 ]. Two studies did not fully describe their perspective but provided enough detail to infer that they used a societal perspective [ 22 , 23 ].

Using the cost categories defined in Table 2 , we noted five studies examining costs within all phases of implementation (including sustainment) based on the adopted framework [ 19 , 21 , 24 , 33 , 35 ]. Three studies examined only pre-implementation and implementation phases, all of which focused on trauma-focused cognitive behavioral therapy. These studies measured either direct implementation costs, direct services costs, and/or indirect implementation costs [ 26 , 27 , 28 ]. Eight studies included costs aligned only with the implementation phase [ 20 , 22 , 23 , 25 , 29 , 30 , 31 , 34 ]. All of these studies measured direct services costs, except one study, which measured direct implementation costs [ 31 ]. The remaining two studies were focused on the sustainability phase, and provided qualitative measurement of direct implementation costs [ 32 , 36 ].

As shown in Table 3 , there was a wide variation in the types of direct cost categories in the implementation costing studies. We identified eleven distinct categories of direct implementation costs captured across these five studies. Eight of these categories captured direct costs attributable to staff time spent in implementation activities such as trainings, meetings, on-site consultations, follow-up calls, supervision, project management, and preparation time. While the actual name of the cost categories differed slightly across the studies, the objective of including these eight direct cost categories was similar. For example, on-site meetings are called “learning sessions” [ 28 ] in the study of community-based implementation of trauma-focused cognitive behavioral therapy, and “on-site assessor reviews” in another study [ 31 ]. The purpose of including this cost category is to understand how much time is devoted to learning how to appropriately implement the EBP. The three final cost categories captured time devoted to data activities required of implementation studies or the actual purchase of data equipment as well as transportation expenses and training materials purchased. No single study included all 11 cost categories. One study of the implementation of a trauma-focused cognitive behavioral therapy program for youth included nine of the eleven cost categories [ 26 ]. Another study examining three specific methods for assessing implementation activities (on-site, phone, and self-report), included four cost categories only [ 31 ]. One article focused implementation costing on training and travel expenses only [ 19 ].

Studies reporting quantitative cost results across the highlighted costing categories are summarized in Table 4 . Since it was difficult to compare cost results between studies given the variation in the type of EBP implemented and the number of cost categories included, the results were summarized by type of cost (direct versus indirect), type of EBP, and average costs (per child, per clinician, per collaborative). The results show that even within similar cost categories and types of costs, there was still considerable variation. For example, among the five studies that reported direct implementation costs [ 19 , 26 , 27 , 28 , 31 ], four reported direct implementation costs per child, which ranged from $886 per child to $9470 per child. For the three studies that implemented the same EBP (trauma-focused cognitive behavioral therapy for children), direct implementation cost per child varied between $886 and $2742 [ 26 , 27 , 28 ]. Two studies reported indirect implementation costs ranging from $897 per child to $3805 per child [ 27 , 28 ].

Three studies examined costs across phases of implementation: pre-implementation, implementation, and sustainment. All three of these studies also reported average per-child costs. One study combined pre-implementation and implementation direct costs totaling $886 per child [ 28 ]. A second study reported average direct implementation costs per child of $1,000 and indirect implementation costs per child of $897 per year during the sustainment period [ 27 ]. In another study, while the authors reported staff costs separately for pre-implementation and implementation, they report an aggregate summary of the average direct implementation costs ($2,742 per child) for both phases together [ 26 ].

Results from the CHEERS checklist (Table 5 ) indicate that, on average, studies included 87% of applicable items from the CHEERS checklist, which corresponds to good quality. The highest quality (excellent) studies include all applicable items [ 32 , 33 , 35 , 36 ]. All studies, except one, included at least 75% of applicable items (good quality), with the one exception including only 65% (average quality) [ 23 ]. The most common item that was not included was the discount rate, with only 8% of studies including that item. Several other items from the CHEERS checklist related to cost-effectiveness analysis and were largely not applicable. These items included measurement of effectiveness, measurement of valuation, and characterizing uncertainty/heterogeneity.

Overview of the field

This is the first systematic literature review to examine cost analyses within implementation studies of EBP for behavioral health services. The literature review identified 18 studies published since 2000 that included a formal cost analysis. Most of this work has been published in recent years (16 articles since 2013). Given the increase in cost analyses within implementation research of behavioral health EBPs, this study provides important context for the current state of the field, including a summary of findings, and we offer suggestions for how the field might standardize economic concepts and measures to increase translatability and support data harmonization going forward. In particular, the large number of not applicable categories from the CHEERS checklist may indicate a need for a new checklist of costing as part of implementation research.

Review of results

We found several studies proposing the development of an implementation research framework, but no studies using a previously published framework. This finding resonates with a recent study by Wensing and Grol (2019) that identified a large number of implementation frameworks within the field, but very little consistency across contextual determinants [ 38 ]. Our findings describe and categorize existing methodologies for calculating direct costs of EBP implementation, direct costs of healthcare services, and indirect costs of EBP implementation. These three categories of cost most closely align with how cost results were presented in the included studies, but they diverge slightly from standard cost categories in the economic evaluation literature. For instance, economic analyses of treatment interventions typically include start-up costs (aligned with pre-implementation costs) and intervention management/operational costs (aligned with implementation and sustainment costs). Within these categories, resources are typically characterized as sunk costs (e.g., start-up), variable costs (dependent on number of patients or clients), time-dependent (recurring costs during the year to support implementation), and societal costs (e.g., opportunity costs of subsidized/donated resources, staff and participant’s time and travel costs).

We identified a wide variation in study type and costing methods, thus limiting the comparability across cost analysis results. Further complicating comparability is the possibility that there could be some double counting in the direct implementation and direct service cost categories if staff time is being reported as a provider expense as well as a billable service cost. Only one study included both of these categories [ 19 ], and the methods and results were not detailed enough to determine the magnitude of double counting. However, this limitation is important for future comparisons of implementation costs. Despite these challenges, we were able to highlight 11 distinct categories of direct implementation costs that are captured in sufficient detail across five of the studies. This review also highlights the importance of estimating the indirect implementation costs—or opportunity costs—in both seeking and providing services. Opportunity cost in this context refers to the lost revenue from billable clinical services due to implementation activities. Several of the implementation studies calculated opportunity costs. These calculations are extremely important from the provider perspective as they represent the large monetary investment that is made in implementing EBPs and other programs at the expense of direct billing for providing healthcare services.

Regarding the presentation of summary cost estimates, three studies examined the same EBP (trauma-focused cognitive behavioral therapy), which facilitated comparison. However, even among these studies there was wide variation in reported costs, which may suggest that costs are substantially impacted by factors outside of the implementation process. Some of the reported costs were also relatively high (as much as $3,805 per child), and may be inflated due to the inclusion of fixed startup costs (i.e., pre-implementation costs that would not vary with the number of children served) and smaller caseloads. In fact, one of the included studies highlights this in reporting that per child and per session incremental implementation costs are highest in the start-up phase and decrease over time as more children are served [ 26 ]. However, as is known, the cost of healthcare in the United States is highest in the world, and this includes the costs of behavioral healthcare. As pharmacotherapy is a large component to behavioral healthcare, relatively high drug prices in the United States could be an important driver. For example, one study reported the annual per capita cost of treating an adult for a behavioral health disorder to be $2,745 [ 39 ]. Other research has identified that factors outside implementation can impact costs. For example, behavioral health patient caseloads and state level Medicaid and Child Health Insurance Program (CHIP) funding may be associated with lower implementation costs and better retention in behavioral health services programs for justice-involved youth [ 40 ].

Implications for future research

Given the wide variation in the types of factors included in implementation research it is difficult to make comparisons across studies. This is a major limitation of implementation research focusing on behavioral health services, as it becomes difficult to replicate studies or use studies to estimate future costs to inform policy decisions related to budgeting. With increasing emphasis on the economics of implementation science [ 38 ], the field could benefit from adopting standardized guidelines, especially for costing perspectives, approaches (e.g., activity-based costing), instrumentation, and categorization of cost components. In the broader economic evaluation literature, standard methods for cost analysis are established [ 41 , 42 ]. Recently, standardized approaches for economic analysis in behavioral health were also described [ 43 ]. As implementation science grows, similar guidelines need to be developed. Without standardization and harmonization of data across studies, it is difficult to fully assess how the evidence of effectiveness and economic impact generalizes from one study to a broad area of practice or research.

Based on our findings, we recommend that future studies include more details about the specific activities and resources associated with an implementation process, so that other researchers and policy makers can anticipate what costs will be incurred in changing existing or adopting new practices. We also recommend that studies include measures of environmental context such as treatment capacity, available funding (i.e.: block grants) and urbanicity, all available from public sources, to better capture how outside factors may impact the costs of implementing EBPs [ 44 ]. As shown in two studies, urbanicity was related to behavioral health EBP delivery [ 45 , 46 ]. Beyond impacting the effectiveness of the EBP, contextual factors impact costs directly. For example, salaries may be impacted by geography due to higher costs of living in certain areas.

Limitations and strengths

While this study adds substantially to the literature by describing the state of the field to date, there are still several limitations. For example, since there was very little overlap between studies in the types of EBP being implemented or outcome measures, we were unable to conduct a meta-analysis. Our findings were also focused on implementation studies of evidence-based behavioral health services, and therefore do not extend to other health-related services. Further, only one included study reported both direct implementation costs and direct service costs [ 19 ], which limited our ability to estimate the ratio of implementation to service costs. Concerns about double counting staff time or other resources across direct implementation and direct service cost categories could not be explored in this study given the level of detail provided. Additionally, we also focused only on nonhospital-based services within the United States and Canada, therefore excluding hospital-based services. Since healthcare systems and behavioral health epidemiology in countries outside the United States and Canada are quite different, this decision likely improved the specificity of our findings. However, we are unable to generalize outside of this geographical area. Additional research focused on single-payer healthcare systems, like in the United Kingdom, that would illuminate the role of costing in both policy decisions and implementation of services. While these choices likely improve selection process, there are likely other important areas of research conducted outside the scope of this work. Future studies should aim to describe findings in these areas. Had we included hospital-based services and health services more broadly, it is likely that there would have been greater variation in costing approaches and results.

Implementation research on EBPs in behavioral health has grown significantly in the last several years. However, the field has not yet standardized the use of economic methods or measures. Recommendations based on our findings include moving toward standard cost measures to facilitate cross study comparisons and the potential for results to drive policy decisions.

Availability of data and materials

Data can be obtained by replicating the key search terms in the listed academic databases.

Abbreviations

• Evidence-based practices

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Consolidated Health Economic Evaluation Reporting Standards

Substance use disorders

Consolidated Framework for Implementation Research

Child Health Insurance Program

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Acknowledgements

This study was funded by the National Institute on Drug Abuse (NIDA), and the National Institute on Alcohol Abuse and Alcoholism (NIAAA) both at the National Institutes of Health (NIH) (T32AA007567, T32DA37801, R21DA044378, P30 DA040500, R01DA035808). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIAAA, NIDA, NIH, or the participating universities.

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Bowser, D.M., Henry, B.F. & McCollister, K.E. Cost analysis in implementation studies of evidence-based practices for mental health and substance use disorders: a systematic review. Implementation Sci 16 , 26 (2021). https://doi.org/10.1186/s13012-021-01094-3

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• 7 Department of Surgery, Harvard Medical School, Boston, Massachusetts
• Editorial Maximizing the Impact of Surgical Health Services Research Amir A. Ghaferi, MD, MS; Adil H. Haider, MD, MPH; Melina R. Kibbe, MD JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Qualitative Analysis Margaret L. Schwarze, MD, MPP; Amy H. Kaji, MD, PhD; Amir A. Ghaferi, MD, MS JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Mixed Methods Lesly A. Dossett, MD, MPH; Amy H. Kaji, MD, PhD; Justin B. Dimick, MD, MPH JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Comparative Effectiveness Research Using Observational Data Ryan P. Merkow, MD, MS; Todd A. Schwartz, DrPH; Avery B. Nathens, MD, MPH, PhD JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Health Policy Evaluation Using Observational Data John W. Scott, MD, MPH; Todd A. Schwartz, DrPH; Justin B. Dimick, MD, MPH JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Survey Research Karen Brasel, MD, MPH; Adil Haider, MD, MPH; Jason Haukoos, MD, MSc JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Meta-analysis Shipra Arya, MD, SM; Todd A. Schwartz, DrPH; Amir A. Ghaferi, MD, MS JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Assessment of Patient-Reported Outcomes Giana H. Davidson, MD, MPH; Jason S. Haukoos, MD, MSc; Liane S. Feldman, MD JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Implementation Science Heather B. Neuman, MD, MS; Amy H. Kaji, MD, PhD; Elliott R. Haut, MD, PhD JAMA Surgery
• Guide to Statistics and Methods Practical Guide to Decision Analysis Dorry L. Segev, MD, PhD; Jason S. Haukoos, MD, MSc; Timothy M. Pawlik, MD, MPH, PhD JAMA Surgery

Constraints on US health care resources provide incentives to maximize outcomes among surgical patients while limiting the costs of providing care. Cost-effectiveness analysis (CEA) is a statistical method that allows researchers to simultaneously compare the trade-offs between costs and health effects of different surgical interventions. The resultant metrics can help inform decisions about adopting new or existing interventions, particularly when many surgical procedures are expensive and benefits are uncertain over time. For example, the results of CEA have been used to help surgeons choose between alternative techniques for creating arteriovenous fistulas for hemodialysis in patients with end-stage renal disease. 1 Similarly, a recent study published in JAMA Surgery applied CEA methods to assess the relative value of bariatric surgery (compared with no surgery) over time among adolescent patients with severe obesity. 2

• Editorial Maximizing the Impact of Surgical Health Services Research JAMA Surgery

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Brooke BS , Kaji AH , Itani KMF. Practical Guide to Cost-effectiveness Analysis. JAMA Surg. 2020;155(3):250–251. doi:10.1001/jamasurg.2019.4392

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How to Do a Cost-Benefit Analysis & Why It’s Important

• 05 Sep 2019

Are you unsure whether a particular decision is the best one for your business? Are you questioning whether a proposed project will be worth the effort and resources that will go into making it a success? Are you considering making a change to your business, marketing, or sales strategy, knowing that it might have repercussions throughout your organization?

The way that many businesses, organizations, and entrepreneurs answer these, and other, questions is through business analytics —specifically, by conducting a cost-benefit analysis.

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What Is A Cost-Benefit Analysis?

A cost-benefit analysis is the process of comparing the projected or estimated costs and benefits (or opportunities) associated with a project decision to determine whether it makes sense from a business perspective.

Generally speaking, cost-benefit analysis involves tallying up all costs of a project or decision and subtracting that amount from the total projected benefits of the project or decision. (Sometimes, this value is represented as a ratio.)

If the projected benefits outweigh the costs, you could argue that the decision is a good one to make. If, on the other hand, the costs outweigh the benefits, then a company may want to rethink the decision or project.

There are enormous economic benefits to running these kinds of analyses before making significant organizational decisions. By doing analyses, you can parse out critical information, such as your organization’s value chain or a project’s ROI .

Cost-benefit analysis is a form of data-driven decision-making most often utilized in business, both at established companies and startups . The basic principles and framework can be applied to virtually any decision-making process, whether business-related or otherwise.

Related: 5 Business Analytics Skills for Professionals

Steps of a Cost-Benefit Analysis

1. establish a framework for your analysis.

For your analysis to be as accurate as possible, you must first establish the framework within which you’re conducting it. What, exactly, this framework looks like will depend on the specifics of your organization.

Identify the goals and objectives you’re trying to address with the proposal. What do you need to accomplish to consider the endeavor a success? This can help you identify and understand your costs and benefits, and will be critical in interpreting the results of your analysis.

Similarly, decide what metric you’ll be using to measure and compare the benefits and costs. To accurately compare the two, both your costs and benefits should be measured in the same “common currency.” This doesn’t need to be an actual currency, but it does frequently involve assigning a dollar amount to each potential cost and benefit.

2. Identify Your Costs and Benefits

Your next step is to sit down and compile two separate lists: One of all of the projected costs, and the other of the expected benefits of the proposed project or action.

When tallying costs, you’ll likely begin with direct costs , which include expenses directly related to the production or development of a product or service (or the implementation of a project or business decision). Labor costs, manufacturing costs, materials costs, and inventory costs are all examples of direct costs.

But it’s also important to go beyond the obvious. There are a few additional costs you must account for:

• Indirect costs: These are typically fixed expenses, such as utilities and rent, that contribute to the overhead of conducting business.
• Intangible costs: These are any current and future costs that are difficult to measure and quantify. Examples may include decreases in productivity levels while a new business process is rolled out, or reduced customer satisfaction after a change in customer service processes that leads to fewer repeat buys.
• Opportunity costs: This refers to lost benefits, or opportunities, that arise when a business pursues one product or strategy over another.

Once those individual costs are identified, it’s equally important to understand the possible benefits of the proposed decision or project. Some of those benefits include:

• Direct: Increased revenue and sales generated from a new product
• Indirect: Increased customer interest in your business or brand
• Intangible: Improved employee morale
• Competitive: Being a first-mover within an industry or vertical

3. Assign a Dollar Amount or Value to Each Cost and Benefit

Once you’ve compiled exhaustive lists of all costs and benefits, you must establish the appropriate monetary units by assigning a dollar amount to each one. If you don’t give all the costs and benefits a value, then it will be difficult to compare them accurately.

Direct costs and benefits will be the easiest to assign a dollar amount to. Indirect and intangible costs and benefits, on the other hand, can be challenging to quantify. That does not mean you shouldn’t try, though; there are many software options and methodologies available for assigning these less-than-obvious values.

4. Tally the Total Value of Benefits and Costs and Compare

Once every cost and benefit has a dollar amount next to it, you can tally up each list and compare the two.

If total benefits outnumber total costs, then there is a business case for you to proceed with the project or decision. If total costs outnumber total benefits, then you may want to reconsider the proposal.

Beyond simply looking at how the total costs and benefits compare, you should also return to the framework established in step one. Does the analysis show you reaching the goals you’ve identified as markers for success, or does it show you falling short?

If the costs outweigh the benefits, ask yourself if there are alternatives to the proposal you haven’t considered. Additionally, you may be able to identify cost reductions that will allow you to reach your goals more affordably while still being effective.

Related: Finance vs. Accounting: What's the Difference?

Pros and Cons of Cost-Benefit Analysis

There are many positive reasons a business or organization might choose to leverage cost-benefit analysis as a part of their decision-making process. There are also several potential disadvantages and limitations that should be considered before relying entirely on a cost-benefit analysis.

Advantages of Cost-Benefit Analysis

A data-driven approach.

Cost-benefit analysis allows an individual or organization to evaluate a decision or potential project free of biases. As such, it offers an agnostic and evidence-based evaluation of your options, which can help your business become more data-driven and logical.

Makes Decisions Simpler

Business decisions are often complex by nature. By reducing a decision to costs versus benefits, the cost-benefit analysis can make this dilemma less complex.

Uncovers Hidden Costs and Benefits

Cost-benefit analysis forces you to outline every potential cost and benefit associated with a project, which can uncover less-than-obvious factors like indirect or intangible costs.

Limitations of Cost-Benefit Analysis

Difficult to predict all variables.

While cost-benefit analysis can help you outline the projected costs and benefits associated with a business decision, it’s challenging to predict all the factors that may impact the outcome. Changes in market demand, material costs, and the global business environment are unpredictable—especially in the long term.

Incorrect Data Can Skew Results

If you’re relying on incomplete or inaccurate data to finish your cost-benefit analysis, the results of the analysis will follow suit.

Better Suited to Short- and Mid-Length Projects

For projects or business decisions that involve longer timeframes, cost-benefit analysis has a greater potential of missing the mark for several reasons. For one, it’s typically more difficult to make accurate predictions the further into the future you go. It’s also possible that long-term forecasts won’t accurately account for variables such as inflation, which can impact the overall accuracy of the analysis.

Removes the Human Element

While a desire to make a profit drives most companies, there are other, non-monetary reasons an organization might decide to pursue a project or decision. In these cases, it can be difficult to reconcile moral or “human” perspectives with the business case.

In the end, cost-benefit analysis shouldn't be the only business analytics tool or strategy you use in determining how to move your organization into the future. Cost-benefit analysis isn’t the only type of economic analysis you can do to assess your business’s economic state, but a single option at your disposal.

Do you want to take your career to the next level? Download our free Guide to Advancing Your Career with Essential Business Skills to learn how enhancing your business knowledge can help you make an impact on your organization and be competitive in the job market.

This post was updated on July 12, 2022. It was originally published on September 5, 2019.

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What is Cost-Benefit Analysis? Definition, Examples

Appinio Research · 21.12.2023 · 41min read

Are you faced with critical decisions that demand a thorough assessment of costs and benefits? Understanding the art of cost-benefit analysis (CBA) is your key to informed and strategic decision-making.

In this guide, we will demystify the intricacies of CBA, equipping you with the tools and insights to evaluate projects, investments, and initiatives from a financial perspective. Whether you're a business leader, policymaker, or researcher, join us in unlocking the power of CBA and transforming complex choices into clear, data-driven solutions.

What is Cost-Benefit Analysis?

Cost-benefit analysis (CBA) is a systematic and quantitative approach used to evaluate the financial implications of decisions, projects, or policies. At its core, CBA seeks to answer a fundamental question: "Is the expected benefit of an action greater than its expected cost?" By comparing the costs and benefits of different options, CBA provides a structured framework for decision-makers to make informed choices that maximize value.

Importance of Cost-Benefit Analysis in Decision-Making

Cost-benefit analysis plays a pivotal role in informed decision-making across various domains. Its importance lies in the multitude of benefits it offers:

• Objective Evaluation:  CBA provides an objective and structured framework for evaluating decisions, reducing the influence of personal biases and preferences.
• Resource Allocation:  It helps allocate limited resources efficiently by identifying projects or initiatives that yield the greatest net benefit, enhancing overall economic performance.
• Accountability:  CBA fosters accountability in both the public and private sectors, as decisions are based on quantifiable data and analysis, making it easier to justify choices to stakeholders.
• Risk Management:  CBA allows decision-makers to assess the financial implications of various risks and uncertainties, enabling proactive risk management and mitigation.
• Policy Design:  In public policy, CBA aids in designing policies that optimize societal welfare and achieve specific objectives, such as environmental protection or public health.
• Project Prioritization:  In project management, CBA assists in prioritizing projects by quantifying their potential returns and aligning them with organizational goals.
• Environmental and Social Impact:  CBA extends beyond financial metrics to consider broader environmental and social impacts , promoting sustainability and responsible decision-making.
• Informed Choices:  Ultimately, CBA empowers decision-makers with the knowledge and tools to make choices that maximize benefits, enhance efficiency, and lead to better outcomes.

How to Conduct Cost-Benefit Analysis?

Now, let's delve deeper into the key steps of conducting a cost-benefit analysis, providing you with a more comprehensive understanding of each crucial element in this process.

1. Identify and Define the Project or Decision

Before embarking on a CBA journey , you must have a crystal-clear vision of the project or decision at hand. Take the time to thoroughly identify and define the scope, objectives, and boundaries of the undertaking. Here's how:

• Scope Definition:  Clearly outline what the project aims to achieve. Identify its goals, intended outcomes, and the problems or opportunities it addresses.
• Objective Clarity:  Define the specific objectives you intend to accomplish with the project. Ensure that these objectives are quantifiable and align with the project's scope.
• Boundary Establishment:  Determine the project's boundaries by specifying what it includes and excludes. This step helps avoid scope creep and ensures a focused analysis.

2. Identify Stakeholders and Their Interests

Understanding who the key stakeholders are and what interests they hold in the project is vital for a comprehensive CBA. Here's how to go about it:

• Stakeholder Identification:   Identify all parties that have a stake in the project. This includes individuals, groups, or organizations that may be impacted by the project or have influence over it.
• Interest Assessment:  For each stakeholder, assess their interests, concerns, and expectations regarding the project. Recognize potential conflicts or overlaps in interests.
• Prioritization:  Prioritize stakeholders based on their level of influence and interest. This will guide your engagement efforts and ensure you address the concerns of those with the most significant impact on the project.

3. Establish the Timeframe for Analysis

The timeframe you choose for your CBA can significantly affect the results. Consider the following when determining the analysis period:

• Project Duration:  Understand the expected duration of the project. Is it a short-term initiative, a multi-year project, or an ongoing decision?
• Long-Term Impacts:  Recognize that some projects may have long-term impacts that extend beyond the immediate timeframe. Ensure your analysis captures these extended effects.
• Time Units:  Determine the time units you'll use for analysis (e.g., months, years) and the granularity of your assessment.

4. Identify Costs

Identifying and categorizing costs accurately is fundamental to a reliable CBA. Here's how to do it effectively:

• Cost Categories:  Break down the project's costs into categories such as initial investment costs, operating and maintenance costs, and any recurring expenses.
• Cost Sources:  Seek out the sources of cost data, which may include quotes from suppliers, historical records, and expert opinions.
• Hidden Costs:  Be vigilant in uncovering hidden or indirect costs that might not be immediately apparent but are essential for a comprehensive analysis.

5. Identify Benefits

Just as with costs, identifying and categorizing benefits is a critical step. Here's how to go about it:

• Benefit Categories:  Distinguish between various categories of benefits, including financial gains, improvements in quality of life, environmental benefits, and any other positive outcomes.
• Benefit Sources:  Collect data and information from sources that can help estimate the potential benefits of the project. This may involve surveys, market research, or expert insights.
• Intangible Benefits:  Don't overlook intangible benefits such as improved reputation, enhanced employee morale, or community goodwill. These can have significant value.

6. Quantify Costs and Benefits

Quantifying costs and benefits involves attaching specific numerical values to each item. Here's how to approach this quantitative aspect:

• Measurement Units:  Define the measurement units for costs and benefits. For instance, use dollars for financial values and relevant units (e.g., quality-of-life score) for non-monetary benefits.
• Data Precision:  Strive for data precision by using accurate and up-to-date information. Avoid rough estimates whenever possible.
• Consistency:  Ensure consistency in how you measure costs and benefits across the entire analysis. Use a common currency and time units.

7. Assign Monetary Values to Costs and Benefits

To make an apples-to-apples comparison, you'll need to bring all costs and benefits to a common monetary basis. Here's how to do it:

• Discount Rate Selection:  Choose an appropriate discount rate that reflects the time value of money. The discount rate accounts for the fact that future cash flows are worth less than present ones.
• Discounting Formula: Calculate the present value (PV) of future costs or benefits. We'll discuss how to calculate it more in detail.

8. Discounting Future Costs and Benefits

Applying the discount rate to future costs and benefits is essential for fair and accurate comparisons. Here's how to discount future values:

• Applying the Formula:  Use the present value formula mentioned earlier to discount each future cost and benefit back to its equivalent present value.
• Time-Dependent Analysis:  Recognize that the further into the future a cost or benefit occurs, the more it diminishes in present value terms. Ensure that your analysis accounts for this temporal effect.

9. Sensitivity Analysis

Sensitivity analysis is a valuable tool for understanding the robustness of your CBA results in the face of uncertainty. Here's how to conduct it:

• Parameter Variation:  Identify key assumptions, parameters, or variables in your analysis that are subject to uncertainty.
• Scenario Testing:   Create multiple scenarios by varying these uncertain factors. Assess the impact of different scenarios on the project's net present value (NPV) or other relevant metrics.
• Risk Assessment:  Use sensitivity analysis to identify potential risks and opportunities associated with your project. This helps decision-makers understand the range of possible outcomes and make informed choices.

By thoroughly understanding and applying each of these steps, you'll be well-equipped to conduct a robust cost-benefit analysis for any project or decision you encounter. These steps lay the foundation for a comprehensive assessment that can guide your decision-making process effectively.

Types of Costs and Benefits

Cost-benefit analysis involves assessing a wide array of costs and benefits, each falling into distinct categories. Understanding these categories is crucial for a comprehensive analysis. Here, we explore the various types of costs and benefits in detail.

Direct Costs

Direct costs  are the expenses directly attributable to a project or decision. These costs are explicit and easily traceable to the project's activities. Examples of direct costs include:

• Labor Costs:  The wages and salaries paid to employees directly involved in the project, such as project managers, engineers, or construction workers.
• Material Costs:  Expenses related to the purchase of raw materials, supplies, and equipment essential for the project's execution.
• Equipment Costs:  Costs associated with the acquisition or rental of machinery and tools necessary for the project.
• Travel and Transportation Costs:  Expenses incurred for travel , accommodation, and transportation directly linked to project activities.
• Contractor Fees:  Fees paid to external contractors or consultants for their services on the project.

Direct costs are typically straightforward to identify and quantify, making them a fundamental component of any CBA.

Indirect Costs

In contrast to direct costs,  indirect costs  are not directly tied to the project but are essential for its execution. These costs are often shared among multiple projects or activities within an organization. Identifying and allocating indirect costs accurately is necessary for an accurate CBA. Examples of indirect costs include:

• Administrative Overhead:  Costs associated with general administrative functions, such as office rent, utilities, office supplies, and administrative staff salaries.
• General Maintenance Costs:  Expenses for the upkeep and maintenance of facilities and equipment that serve multiple projects.
• Insurance Costs:  Costs related to insuring project assets and liabilities against potential risks and accidents.
• Indirect Labor Costs:  Wages and benefits paid to employees not directly involved in the project but who contribute indirectly to its success, such as administrative staff or support personnel.

Indirect costs can sometimes be challenging to allocate accurately to specific projects, requiring careful consideration in the CBA.

Tangible Benefits

Tangible benefits  are the measurable and quantifiable outcomes that result from a project or decision. These benefits are often expressed in monetary terms, making them relatively straightforward to evaluate. Examples of tangible benefits include:

• Increased Revenue:  A direct boost in income or sales resulting from the project. For instance, the launch of a new product can lead to increased sales revenue.
• Cost Savings:  Reductions in operational costs due to project implementation, such as energy savings from energy-efficient equipment.
• Profit Margins:  Improvements in profit margins, which can result from increased efficiency or reduced production costs.
• Market Share Growth:   Expansion of market share due to successful project outcomes.

Tangible benefits are critical for demonstrating the financial viability of a project, as they contribute directly to the project's return on investment.

Intangible Benefits

While  intangible benefits  may be challenging to measure in monetary terms, they hold significant value. These benefits are not easily quantifiable but are essential for a comprehensive CBA. Examples of intangible benefits include:

• Enhanced Reputation:  A positive impact on the organization's reputation or brand image , which can lead to increased customer trust and loyalty.
• Employee Morale:  Improved job satisfaction and motivation among employees, potentially resulting in higher productivity and reduced turnover.
• Environmental Preservation:  Benefits related to environmental conservation, such as reduced pollution or biodiversity preservation.
• Community Well-being:  Positive effects on the overall quality of life and well-being of the community in which the project operates.

Intangible benefits may not appear on the balance sheet, but they can contribute significantly to the overall success and sustainability of a project.

Social Costs and Benefits

In some instances, the impacts of a project extend beyond financial considerations and delve into broader societal consequences.  Social costs and benefits  encompass these effects on the community, environment, or society at large. Examples include:

• Environmental Impact:  Costs associated with pollution, habitat destruction, or resource depletion, as well as benefits from reduced emissions or conservation efforts.
• Healthcare Costs:  Costs related to increased healthcare demands or benefits from improved public health outcomes resulting from a project.
• Community Development:  Costs associated with disruptions to local communities or benefits from increased employment opportunities and infrastructure development.

Assessing social costs and benefits requires a holistic perspective, as their effects can be far-reaching and have significant societal implications.

Private Costs and Benefits

Private costs and benefits pertain specifically to individuals or entities directly involved in the project or decision. Distinguishing between private and social costs and benefits is crucial for understanding the broader impact of a project. Examples include:

• Private Financial Costs:  Costs borne by individual stakeholders, such as project investors or employees.
• Private Financial Benefits:   Financial gains accrued by individuals or organizations directly associated with the project, such as suppliers or contractors.
• Private Non-Financial Costs:  Non-monetary burdens experienced by individuals involved in the project, such as increased workload or stress.
• Private Non-Financial Benefits:  Non-monetary advantages received by project participants, like skill development or networking opportunities.

Understanding the distinction between private and social costs and benefits helps ensure that your CBA comprehensively captures the implications of the project for all stakeholders involved.

By recognizing and categorizing these various types of costs and benefits, you can conduct a more thorough and insightful cost-benefit analysis that accounts for both the financial and non-financial aspects of your decision or project. This holistic approach enables you to make more informed choices and understand the full impact of your actions.

Cost-Benefit Analysis Data Collection and Analysis

To conduct a robust cost-benefit analysis, you must pay careful attention to data collection and analysis. This phase is critical for obtaining accurate and reliable information to support your decision-making process. Here, we delve into the intricacies of gathering data for cost estimation, collecting data for benefit estimation, ensuring data quality and reliability, and analyzing data effectively.

Gathering Data for Cost Estimation

Before you can estimate costs accurately, you need to gather relevant data related to the project's expenses. This step involves a systematic approach to ensure that you capture all cost elements. Here's how to do it effectively:

• Quotes and Estimates:  Reach out to suppliers, contractors, and vendors to obtain detailed quotes and estimates for materials, labor, equipment, and services required for the project. These quotes serve as valuable benchmarks.
• Historical Data:  Review historical cost data from similar projects within your organization or industry. This can provide insights into cost patterns and trends that are likely to apply to your project.
• Expert Input:  Consult with subject matter experts within your organization or industry. Their expertise can help identify potential cost drivers and nuances specific to the project.
• Contingency Planning:  Account for contingencies by considering unforeseen costs that may arise during the project's execution. A contingency budget can help mitigate unexpected financial setbacks.
• Detailed Documentation:  Maintain meticulous records of all cost-related data, including invoices, receipts, and cost breakdowns. This documentation will be essential for transparency and accountability.

Gathering Data for Benefit Estimation

Estimating benefits accurately is equally crucial to the success of your CBA. Benefits can take various forms, so a comprehensive data collection approach is necessary:

• Market Research:   Conduct market research to understand customer demand and potential revenue streams. Surveys, focus groups, and customer feedback can provide valuable insights.
• Benchmarking:  Compare your project's potential benefits to industry benchmarks and standards. This can help you set realistic expectations and identify areas for improvement.
• Environmental Studies:  For projects with environmental impacts, gather data from environmental assessments and studies. This may include data on emissions reductions, energy savings, or ecosystem restoration.
• Economic Models:  Employ economic models and analysis techniques to project potential benefits accurately. These models can simulate various scenarios and their corresponding outcomes.
• Scenario Analysis:  Consider multiple scenarios for benefit estimation, ranging from optimistic to pessimistic. This approach allows you to assess the range of potential outcomes and their associated probabilities.

Data Quality and Reliability

Ensuring the quality and reliability of the data you collect is paramount. Inaccurate or unreliable data can lead to flawed conclusions. Here's how to maintain data integrity:

• Source Verification:  Verify the credibility and trustworthiness of data sources. Use reputable sources, official records, and reliable industry databases.
• Data Consistency:  Ensure consistency in data units and formats. Use standardized metrics and measurement units to prevent data discrepancies.
• Data Validation:  Cross-check data for accuracy and completeness. Look for inconsistencies, outliers, or missing information that may need validation or correction.
• Sampling Techniques:  If you cannot collect data from an entire population, use appropriate sampling techniques to ensure representativeness and reduce sampling bias .
• Peer Review:  Engage experts or colleagues to review and validate your data collection methods and assumptions. External validation can help identify potential blind spots.

Analyzing Data for Decision-Making

Analyzing data effectively is the cornerstone of a successful CBA. It involves crunching numbers, identifying patterns, and drawing meaningful insights from the collected data.

• Data Segmentation:  Segment data into relevant categories or variables to gain a deeper understanding of cost and benefit components. This segmentation can reveal insights into different aspects of the project.
• Statistical Tools:  Utilize statistical tools and software to perform quantitative analysis. Statistical techniques can help identify trends, correlations, and potential outliers.
• Sensitivity Analysis:  Incorporate sensitivity analysis into your data analysis process. This involves varying key parameters or assumptions to assess the impact on outcomes, helping you understand the robustness of your results.
• Comparative Analysis :  Compare different scenarios, projects, or alternatives to evaluate their relative merits. Comparative analysis can assist in choosing the most favorable course of action.
• Visualization:  Present your data using visual aids such as charts, graphs, and tables. Visual representations can make complex data more accessible and facilitate communication with stakeholders.
• Interpretation:  Interpret the data findings in the context of the project's objectives and goals. What do the numbers mean for the project's feasibility and desirability?
• Risk Assessment:  Consider the inherent risks associated with the data and analysis. Identify potential sources of error or uncertainty and communicate these risks transparently.

Effective data collection and analysis are the backbone of a sound CBA. By adhering to best practices and maintaining data integrity, you can enhance the accuracy and reliability of your analysis, ultimately leading to more informed and confident decision-making.

Discounting and Present Value

Understanding the concept of discounting and calculating present value is a pivotal aspect of cost-benefit analysis. We will explore the principles of the time value of money, the factors involved in discount rate selection, and the methods for calculating present value.

What is TVM (Time Value of Money)?

The  time value of money (TVM)  is a fundamental financial principle that underpins CBA. It recognizes that the value of money changes over time due to factors such as inflation, opportunity cost, and risk. To grasp this concept fully, consider the following:

• Inflation:  Inflation erodes the purchasing power of money over time. A dollar today is worth more than a dollar in the future because you can buy more with it now.
• Opportunity Cost:  Money invested or used for one purpose cannot be used for another. The opportunity to earn a return on investment is an essential consideration in CBA.
• Risk:  The future is uncertain, and investments or benefits expected in the future are riskier than those received today. Risk must be factored into discounting.

Discount Rate Selection

Selecting an appropriate  discount rate  is critical for discounting future costs and benefits to their present value. The discount rate reflects the rate of return that could be earned on alternative investments with similar risk profiles. Here's how to approach discount rate selection:

• Risk Assessment:  Assess the risk associated with the project or decision. Projects with higher risk typically require a higher discount rate to account for the added uncertainty.
• Opportunity Cost:  Consider the opportunity cost of capital. This is the return you could earn by investing the money elsewhere. Your discount rate should at least match this opportunity cost.
• Market Rates:  Examine market interest rates for investments with similar risk characteristics. These rates can serve as a benchmark for your discount rate.
• Timeframe:  The discount rate should match the duration of the analysis. Short-term projects may use short-term interest rates, while long-term projects require long-term rates.
• Public vs. Private Projects:  In public projects, discount rates may be determined by government guidelines or policies. For private projects, market-based rates are often used.
• Sensitivity Analysis:  Consider conducting sensitivity analysis with varying discount rates to understand how changes in this key parameter impact your results.

How to Calculate Present Value?

Calculating present value (PV) involves converting future costs and benefits into today's monetary terms. The formula for calculating the present value is:

PV = FV / (1 + r)^n 

• PV  is the Present Value
• FV  is the Future Value
• r  is the Discount Rate
• n  is the Number of Time Periods

Here's how you can apply this formula:

• Single Future Value:  When you have a single future cash flow (e.g., a future benefit or cost), plug in the values for FV, r, and n to calculate the present value.
• Multiple Future Values:  For projects with numerous future cash flows occurring at different time periods, calculate the present value of each cash flow separately and sum them to get the total present value.
• Excel or Financial Calculators:  Excel and financial calculators often have built-in functions for present value calculations. Utilize these tools for efficiency and accuracy.
• Continuous Cash Flows:  For projects with continuous cash flows (e.g., annual benefits or costs), use annuity formulas or financial software to calculate the present value.

By calculating present value accurately, you ensure that all costs and benefits are expressed in terms of today's dollars, allowing for meaningful comparisons and informed decision-making in your cost-benefit analysis. Understanding the time value of money and selecting an appropriate discount rate are crucial components of this process.

Cost-Benefit Analysis Tools and Software

Utilizing the right tools and software is essential for streamlining the cost-benefit analysis process, enhancing accuracy, and facilitating decision-making.

What is CBA Software?

Cost-benefit analysis software plays a pivotal role in simplifying complex calculations, automating data processing, and generating insightful reports. Here's why CBA software is an invaluable asset:

• Efficiency:  CBA software significantly reduces the time and effort required for complex calculations. It automates many of the mathematical tasks, allowing analysts to focus on interpretation and decision-making.
• Accuracy:  Automation reduces the risk of human error in calculations, ensuring that your CBA results are more accurate and reliable.
• Scenario Analysis:  CBA software often allows you to conduct scenario analysis with ease. You can explore different assumptions and scenarios, providing decision-makers with a range of possible outcomes.
• Visualization:  Many CBA tools offer visualization features, such as charts and graphs, making it easier to present data in a comprehensible and engaging manner.
• Consistency:  CBA software enforces consistency in calculations and data management, reducing the likelihood of inconsistencies or discrepancies.
• Documentation:  These tools often provide built-in documentation capabilities, allowing you to maintain comprehensive records of your analysis.

Popular CBA Tools and their Features

Several CBA tools and software applications are available, each offering unique features and capabilities. Understanding their strengths and functionalities is essential for choosing the right tool for your specific needs. Here's an overview of some popular CBA tools:

Microsoft Excel

• Features:  Excel is a versatile spreadsheet software that can handle various financial calculations and data management tasks.
• Strengths:  Widely accessible and familiar to many analysts. Offers a wide range of financial functions and the ability to create customized templates.
• Limitations:  May require advanced knowledge to set up complex CBA models.
• Features: Appinio  is a real-time market research platform that simplifies data collection for CBA. It provides lightning-fast insights, democratized research capabilities, global reach, precise targeting, and guidance from dedicated research consultants.
• Strengths:  Real-time insights, user-friendly interface, global reach, and expert guidance make it an invaluable tool for efficient and informed decision-making.
• Limitations:  Not a dedicated CBA tool, but its real-time insights can complement CBA analysis for well-informed decision-making.

Crystal Ball

• Features:  Crystal Ball is specialized software for risk analysis and Monte Carlo simulation, making it valuable for sensitivity analysis in CBA.
• Strengths:  Allows for comprehensive risk assessment and modeling of uncertain variables. Offers advanced simulation capabilities.
• Limitations:  May have a steeper learning curve, and licensing costs can be substantial.

Online CBA Calculators

• Features:  Numerous free and paid online CBA calculators are available, offering basic CBA functionalities through web-based platforms.
• Strengths:  Accessibility, ease of use, and cost-effectiveness. Suitable for simple CBA calculations.
• Limitations:  Limited in terms of advanced features and customization options.

Dedicated CBA Software

• Features:  Specialized CBA software solutions are designed for in-depth analysis, offering comprehensive modeling and reporting capabilities.
• Strengths:  Tailored specifically for CBA tasks, allowing for sophisticated modeling, extensive scenario analysis, and in-depth reporting.
• Limitations: May require specific training, and some solutions can be costly.

Best Practices for Using CBA Software

To make the most of CBA software, make sure to follow these best practices:

• Training:  Invest in training for your team to ensure they are proficient in using the chosen CBA software effectively.
• Standardization:  Establish standardized templates and procedures for conducting CBA within your organization to promote consistency.
• Data Quality:  Ensure that the data input into the software is accurate, reliable, and up to date. Garbage in, garbage out applies to CBA software.
• Documentation:  Maintain thorough documentation of your CBA process, including assumptions, data sources, and model configurations.
• Validation:  Validate your software-generated results manually to verify their accuracy and ensure they align with your project's objectives.
• Sensitivity Analysis:  Leverage the software's capabilities for sensitivity analysis to explore the impact of varying assumptions on your results.
• Collaboration:  Encourage collaboration among team members by using collaborative features offered by some CBA software.

By selecting the right CBA software, adhering to best practices, and leveraging the tools effectively, you can enhance the efficiency and accuracy of your cost-benefit analysis, ultimately aiding decision-makers in making informed choices.

How to Interpret Cost-Benefit Analysis Results?

After conducting a thorough cost-benefit analysis, effectively interpreting and communicating the results is crucial. Let's see how you can present CBA findings, interpret the Net Present Value (NPV), and communicate uncertainty and risks associated with your analysis.

Presenting Cost-Benefit Analysis Findings

Presenting CBA findings in a clear and concise manner is essential for decision-makers to grasp the implications of your analysis.

• Executive Summary:  Begin with an executive summary that provides a high-level overview of the project, its objectives, and the key findings of the CBA. This summary should be accessible to non-experts.
• Visual Aids:  Utilize charts, graphs, and tables to visually represent your data. Visual aids make complex information more digestible and engaging.
• Narrative Explanation:  Accompany visual aids with a narrative explanation of the results. Explain the methodology, assumptions, and any notable trends or patterns in the data.
• Key Metrics:  Highlight key metrics such as the Net Present Value (NPV), Benefit-Cost Ratio (BCR), and Internal Rate of Return (IRR). These metrics provide a brief summary of the project's financial viability.
• Sensitivity Analysis:  If you conducted a sensitivity analysis, communicate the range of possible outcomes and their associated probabilities. This helps decision-makers understand the level of uncertainty.
• Recommendations:  Conclude with clear and actionable recommendations based on your analysis. Discuss the implications of your findings and offer guidance on whether the project should proceed.

Interpreting the Net Present Value (NPV)

The  Net Present Value (NPV)  is a pivotal metric in CBA, representing the difference between the present value of benefits and the present value of costs. Interpreting NPV correctly is essential for decision-making:

• Positive NPV:  A positive NPV indicates that the project is expected to generate more benefits than costs. This suggests that the project is financially viable and likely to be a favorable investment.
• Negative NPV:  A negative NPV indicates that the project is expected to incur more costs than benefits. In such cases, the project may not be economically viable from a financial perspective.
• Zero NPV:  A zero NPV signifies that the benefits and costs are expected to be equal over time. This implies that the project is expected to break even but may not generate a surplus.
• Magnitude of NPV:  The magnitude of the NPV indicates the magnitude of the project's net benefit. A higher positive NPV suggests a more financially attractive project, while a lower positive NPV may be less appealing.
• NPV and Decision-Making: The decision to proceed with a project often hinges on its NPV. A positive NPV generally supports project approval, while a negative NPV may warrant reconsideration or project modification.

By effectively presenting your CBA findings, interpreting the NPV, and communicating uncertainty and risks, you provide decision-makers with the necessary information to make informed choices. Transparency and clarity in your communication are vital to ensuring that the implications of your analysis are well understood and can guide effective decision-making.

Cost-Benefit Analysis Examples

Cost-benefit analysis is a versatile tool that can be applied to various scenarios across various industries.

Example #1: Investment in Energy-Efficient Equipment

Scenario:  A manufacturing company is considering investing in energy-efficient equipment to replace its outdated machinery. The new equipment is expected to reduce energy consumption and maintenance costs. The project's lifespan is 10 years.

• Initial Investment (Cost): $500,000
• Annual Energy Savings: $60,000
• Annual Maintenance Savings: $20,000
• Annual Operating Cost Increase: $5,000 (due to new equipment)
• Discount Rate (r): 5% (representing the company's cost of capital)

Calculation:

• Calculate the Net Cash Flow (NCF) for each year: NCF = Annual Energy Savings + Annual Maintenance Savings - Annual Operating Cost Increase
• Calculate the Net Present Value (NPV) of the project: NPV = Σ [NCF / (1 + r)^t], where t represents the year.
• Determine the Benefit-Cost Ratio (BCR): BCR = Σ [NCF / (1 + r)^t] / Initial Investment
• Calculate the Internal Rate of Return (IRR) using trial and error or financial software.
• NPV = $117,512.56 (positive NPV indicates a favorable investment)
• BCR = 1.235 (BCR > 1 signifies a beneficial project)
• IRR ≈ 10.18% (IRR > Discount Rate indicates a financially attractive project)

Example #2: Launching a New Product

Scenario:  A consumer goods company is considering launching a new product line. Market research indicates potential annual revenues and costs associated with the new product.

• Initial Investment (Cost): $1,000,000
• Expected Annual Revenue: $400,000
• Annual Variable Costs: $150,000
• Annual Fixed Costs: $50,000
• Project Lifespan: 5 years
• Discount Rate (r): 8% (representing the company's cost of capital)
• Calculate the Net Cash Flow (NCF) for each year: NCF = Expected Annual Revenue - Annual Variable Costs - Annual Fixed Costs
• NPV = -$231,366.78 (negative NPV indicates a less favorable investment)
• BCR = 0.769 (BCR < 1 suggests a less beneficial project)
• IRR ≈ 4.91% (IRR < Discount Rate indicates a less attractive project)

Interpretation:

In the first example, the investment in energy-efficient equipment yields a positive NPV, BCR greater than 1, and an IRR exceeding the discount rate, indicating that it is a financially attractive project . It is expected to generate net positive cash flows over its lifespan.

In the second example, launching the new product line results in a negative NPV, a BCR less than 1, and an IRR lower than the discount rate, suggesting that it may not be a financially viable project . The company should carefully reconsider this investment or explore alternative strategies.

These examples illustrate how CBA can quantitatively assess the financial viability of projects, guiding decision-makers in choosing the most economically advantageous options.

Cost-benefit analysis (CBA) serves as a powerful compass in the realm of decision-making. It empowers individuals and organizations to weigh the financial pros and cons of various choices, enabling sound investments, effective policies, and informed strategies. By mastering CBA, you can navigate the complex landscape of costs and benefits with confidence, ensuring that your decisions are grounded in data, logic, and the pursuit of maximum value.

Remember, CBA is not just a calculation; it's a mindset that fosters better choices. It encourages us to consider not only the immediate gains and losses but also the long-term impacts on society, the environment, and our future.

How to Conduct Cost-Benefit Analysis in Minutes?

In cost-benefit analysis (CBA), timing is everything, and Appinio , the real-time market research platform, understands the need for swift and data-driven decision-making. With Appinio, you can conduct your own market research in minutes, revolutionizing how you approach CBA. Appinio redefines market research, making it exciting, intuitive, and seamlessly integrated into your daily decision-making.

Here's why Appinio is your gateway to more informed choices:

• Lightning-Fast Insights:  Say goodbye to lengthy research processes. Appinio's platform delivers insights in real-time, allowing you to make decisions swiftly and stay ahead in the competitive landscape.
• Democratized Research:  You don't need a Ph.D. in research to use our platform. It's designed to be intuitive and user-friendly, empowering anyone to harness the power of market research.
• Global Reach, Precise Targeting:  With access to over 90 countries and the ability to define target groups based on 1,200+ characteristics, Appinio ensures your data collection is both expansive and precise.

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Introduction to Economic Evaluation in Oral Health Care pp 115–125 Cite as

Worked Example in Cost-Benefit Analysis

• Rodrigo Mariño 3  
• First Online: 29 May 2022

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This chapter builds upon the previous ones and provides a detailed description of the individual steps in designing a protocol for a cost-benefit analysis (CBA). The chapter starts with a definition of CBA and outlines problems and pitfalls with CBAs. To facilitate the understanding and the practical application of CBA principles and methods, a second part presents a case study of a CBA in oral health. The case study’s methodological framework is structured following a checklist proposed by Splett (The practitioner’s guide to cost-effectiveness analysis of nutrition interventions. https://www.ncemch.org/NCEMCH-publications/NtrnCstEff_Anl.pdf: 1996). Thus, although it is based on a published project, it has been simplified to fit this chapter’s objectives; as such, it may not reflect the complexities of a “real-life” CBA.

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Mariño, R. (2022). Worked Example in Cost-Benefit Analysis. In: Zaror, C., Mariño, R. (eds) Introduction to Economic Evaluation in Oral Health Care. Springer, Cham. https://doi.org/10.1007/978-3-030-96289-0_8

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How to Do a Cost Analysis

Last Updated: October 8, 2023 Approved

This article was co-authored by Dave Labowitz and by wikiHow staff writer, Jennifer Mueller, JD . Dave Labowitz is a Business Coach who helps pre-entrepreneurs, solopreneurs/entrepreneurs, and team leaders start, scale, and lead their businesses and teams. Before beginning his coaching career, Dave was a startup executive who spent over a decade building high-growth companies. Dave’s “path less traveled” life includes adventures such as dropping out of high school, co-authoring a book in the Smithsonian Institute, and getting his MBA at Pepperdine’s Graziadio Business School. There are 9 references cited in this article, which can be found at the bottom of the page. wikiHow marks an article as reader-approved once it receives enough positive feedback. This article has 22 testimonials from our readers, earning it our reader-approved status. This article has been viewed 743,527 times.

Cost analysis is one of four types of economic evaluation (the other three being cost-benefit analysis, cost-effectiveness analysis, and cost-utility analysis). Conducting a cost analysis, as the name implies, focuses on the costs of implementing a program without regard to the ultimate outcome. A cost analysis is an important first step before you engage in other types of economic evaluation to determine the suitability or feasibility of a potential project. [1] X Trustworthy Source Centers for Disease Control and Prevention Main public health institute for the US, run by the Dept. of Health and Human Services Go to source

Defining Your Purpose and Scope

• Programs that overlap to a significant degree may be lumped together, rather than evaluated separately. Go with what makes the most sense for the operations of your organization, avoiding duplication of efforts wherever possible.
• To determine whether programs should be separated, look at the services offered by each program, the resources needed to provide those services, and who those services are provided to. If two programs are the same in 2 out of 3 of those dimensions, they probably should be treated as one for the purposes of cost analysis.

• For example, if you're trying to decide whether to charge for a specific service, you would first determine how much that service costs you to provide. You would then do a longer term cost analysis to determine whether your organization can sustain a loss for providing that service.
• It's generally best to choose a time period for which you can acquire accurate revenue data, rather than estimates. This will help if you plan to use your cost analysis as a basis for further economic evaluation. [4] X Research source

• If you are conducting a cost analysis merely to set a budget or plan strategically for the future, you would typically conduct a cost analysis that extended organization-wide.
• On the other hand, a narrower or more specific purpose, such as determining whether to bill for a particular service (and how much), might require a narrower cost analysis that only addressed the costs of that particular service.

• For example, you may be interested in the cost to your clients of offering a particular service. You would look at costs from their perspective, taking into account the amount you bill (or plan to bill) for the service, transportation to your location, and other costs.
• If you're simply looking at the cost of the program to your organization, you'll look at your organizational expenses generally. You might also look at opportunity costs, such as whether offering one program means you will be unable to offer other programs.

Categorizing Costs

• You might also look at cost analyses conducted by similar organizations implementing similar programs or providing similar services.

• Direct costs are specific to the program or service you're evaluating in your cost analysis – they are not shared with any other programs.
• Overhead costs, such as utilities or rent, may be a direct cost if the program or service has its own location.

• Ultimately, when you calculate the costs of an individual program or service, you'll need to allocate these indirect costs

• Standard categories may include personnel costs, operational costs, and start-up costs. Within each category, identify which costs are direct and which are indirect.

Calculating Costs

• Use actual cost information as much as possible. It will increase the utility and reliability of your ultimate cost analysis. [11] X Trustworthy Source Centers for Disease Control and Prevention Main public health institute for the US, run by the Dept. of Health and Human Services Go to source
• For estimates, seek out reliable sources that can be applied as narrowly as possible. For example, if you need to estimate pay, use average rates for employees locally, not nationally.

• If you're doing a longer term cost analysis, compute direct costs first on a weekly or monthly basis, and then extend them out.
• When computing personnel costs, be sure to include the cost (or value) of any benefits offered to employees working on the program.

• For example, suppose you're allocating the salary of the director of human resources. Since they are responsible for personnel, it makes sense to divide their salary by the number of people on staff. If you have 10 employees total, 2 of whom are dedicated to the program or service you're evaluating, you can allocate 20 percent of the director's salary to the program for the purposes of your cost analysis.

• Calculating depreciation can be a complicated endeavor. If you don't have experience doing it, consider hiring an accountant. [14] X Research source

• For example, if you're doing the cost analysis of a program for a non-profit, hidden costs might include the estimated value of volunteer hours, donated materials, or donated space.
• Hidden costs might also include opportunity costs. For example, launching one program may affect your organization's ability to offer other programs.

• At a minimum, your cost analysis should provide your organization with the true cost of running a program or providing a particular service.
• Your cost analysis may also raise additional questions, indicating further analysis is necessary before an ultimate decision can be made.

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• ↑ https://www.cdc.gov/dhdsp/pubs/docs/CB_January_2013.pdf
• ↑ https://www.bridgespan.org/insights/library/pay-what-it-takes/nonprofit-cost-analysis-introduction
• ↑ https://www.universalclass.com/articles/business/basic-methods-and-calculations-of-financial-and-cost-analysis.htm
• ↑ https://www.bridgespan.org/insights/library/pay-what-it-takes/nonprofit-cost-analysis-introduction/step-3-allocate-indirect-costs
• ↑ https://www.bridgespan.org/insights/library/pay-what-it-takes/nonprofit-cost-analysis-introduction/step-4-allocate-indirect-costs
• ↑ https://www.bridgespan.org/insights/library/pay-what-it-takes/nonprofit-cost-analysis-introduction/step-2-gather-financial-data
• ↑ https://2012-2017.usaid.gov/sites/default/files/documents/1868/300mad.pdf
• ↑ https://www.investopedia.com/ask/answers/021815/what-are-different-ways-calculate-depreciation.asp
• ↑ https://www.bridgespan.org/insights/library/pay-what-it-takes/nonprofit-cost-analysis-introduction/step-6-apply-this-knowledge

About This Article

To do a cost analysis, start by calculating the direct costs for your program, which include things like salaries, supplies, and materials. If you're doing a long-term cost analysis, break the costs up into weeks or months. Next, calculate the indirect costs, which are costs that are shared across multiple programs or services. You'll also want to include the depreciation of your company's assets that will be used, as well as any hidden costs that may appear. To learn how to calculate direct and indirect costs, keep reading! Did this summary help you? Yes No

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What Is a Cost-Benefit Analysis?

• Understanding CBA
• The Process
• Limitations
• Cost-Benefit Analysis FAQs

The Bottom Line

• Business Essentials

What Is Cost-Benefit Analysis, How Is it Used, What Are its Pros and Cons?

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and behavioral finance. Adam received his master's in economics from The New School for Social Research and his Ph.D. from the University of Wisconsin-Madison in sociology. He is a CFA charterholder as well as holding FINRA Series 7, 55 & 63 licenses. He currently researches and teaches economic sociology and the social studies of finance at the Hebrew University in Jerusalem.

Pete Rathburn is a copy editor and fact-checker with expertise in economics and personal finance and over twenty years of experience in the classroom.

A cost-benefit analysis is a systematic process that businesses use to analyze which decisions to make and which to forgo. The cost-benefit analyst sums the potential rewards expected from a situation or action and then subtracts the total costs associated with taking that action. Some consultants or analysts also build models to assign a dollar value on intangible items, such as the benefits and costs associated with living in a certain town.

Key Takeaways

• A cost-benefit analysis is the process used to measure the benefits of a decision or taking action minus the costs associated with taking that action.
• A cost-benefit analysis involves measurable financial metrics such as revenue earned or costs saved as a result of the decision to pursue a project.
• A cost-benefit analysis can also include intangible benefits and costs or effects from a decision such as employees morale and customer satisfaction.
• More complex cost-benefit analysis may incorporate sensitivity analysis, discounting of cashflows, and what-if scenario analysis for multiple options.
• All else being equal, an analysis that results in more benefits than costs will generally be a favorable project for the company to undertake.

Michela Buttignol / Investopedia

Understanding Cost-Benefit Analysis

Before building a new plant or taking on a new project, prudent managers conduct a cost-benefit analysis to evaluate all the potential costs and revenues that a company might generate from the project. The outcome of the analysis will determine whether the project is financially feasible or if the company should pursue another project.

In many models, a cost-benefit analysis will also factor the opportunity cost into the decision-making process. Opportunity costs are alternative benefits that could have been realized when choosing one alternative over another. In other words, the opportunity cost is the forgone or missed opportunity as a result of a choice or decision.

Factoring in opportunity costs allows project managers to weigh the benefits from alternative courses of action and not merely the current path or choice being considered in the cost-benefit analysis. By considering all options and the potential missed opportunities, the cost-benefit analysis is more thorough and allows for better decision-making.

Finally, the results of the aggregate costs and benefits should be compared quantitatively to determine if the benefits outweigh the costs. If so, then the rational decision is to go forward with the project. If not, the business should review the project to see if it can make adjustments to either increase benefits or decrease costs to make the project viable. Otherwise, the company should likely avoid the project.

With cost-benefit analysis, there are a number of forecasts built into the process, and if any of the forecasts are inaccurate, the results may be called into question.

The Cost-Benefit Analysis Process

There is no single universally accepted method of performing a cost-benefit analysis. However, every process usually has some variation of the following five steps.

Identify Project Scope

The first step of a cost-benefit analysis is to understand your situation, identify your goals, and create a framework to mold your scope. The project scope is kicked off by identifying the purpose of the cost-benefit analysis. An example of a cost-benefit analysis purpose could be "to determine whether to expand to increase market share " or "to decide whether to renovate a company's website".

This initial stage is where the project planning takes place, including the timeline, resources needed, constraints, personnel required, or evaluation techniques. It is at this point that a company should assess whether it is equipped to perform the analysis. For example, a company may realize it does not have the technical staff required to perform an adequate analysis.

During the project scope development phase, key stakeholders should be identified, notified, and given a chance to provide their input along the process. It may be wise to include those most impacted by the outcome of the analysis depending on the findings (i.e. if the outcome is to renovate a company's website, IT may be required to hire multiple additional staff and should be consulted).

Determine the Costs

With the framework behind us, it's time to start looking at numbers. The second step of a cost-benefit analysis is to determine the project costs. Costs may include the following.

• Direct costs would be direct labor involved in manufacturing, inventory, raw materials , manufacturing expenses.
• Indirect costs might include electricity, overhead costs from management, rent, utilities.
• Intangible costs of a decision, such as the impact on customers, employees, or delivery times.
• Opportunity costs such as alternative investments, or buying a plant versus building one.
• Cost of potential risks such as regulatory risks, competition, and environmental impacts.

When determining costs, it's important to consider whether the expenses are reoccurring or a one-time cost. It's also important to evaluate whether costs are variable or fixed; if they are fixed, consider what step costs and relevant range will impact those costs.

"Costs" can be financial (i.e. expenses recorded on an income statement) or non-financial (i.e. negative repercussions on the community).

Determine the Benefits

Every project will have different underlying principles; benefits might include the following:

• Higher revenue and sales from increased production or new product.
• Intangible benefits, such as improved employee safety and morale, as well as customer satisfaction due to enhanced product offerings or faster delivery.
• Competitive advantage or market share gained as a result of the decision.

An analyst or project manager should apply a monetary measurement to all of the items on the cost-benefit list, taking special care not to underestimate costs or overestimate benefits. A conservative approach with a conscious effort to avoid any subjective tendencies when calculating estimates is best suited when assigning a value to both costs and benefits for a cost-benefit analysis.

Analysts should also be aware of the challenges in determining both explicit and implicit benefits. Explicit benefits require future assumptions about market conditions, sales quantities, customer demands, and product expectations. Implicit costs, on the other hand, may be difficult to calculate as there may be no simple formula. For example, consider the example above about increasing employee satisfaction; there is no formula to calculate the financial impact of happier workers.

Compute Analysis Calculations

With the cost and benefit figures in hand, it's time to perform the analysis. Depending on the timeframe of the project, this may be as simple as subtracting one from another; if the benefits are higher than the cost, the project has a net benefit to the company.

Some cost-benefit analysis require more in-depth critiquing. This may include:

• Applying discount rates to determine the net present value of cashflows.
• Utilizing various discount rates depending on various situations.
• Calculating cost-benefit analysis for multiple options. Each option may have a different cost and different benefit.
• Level-setting different options by calculating the cost-benefit ratio.
• Performing sensitivity analysis to understand how slight changes in estimates may impact outcomes.

Make Recommendation and Implement

The analyst that performs the cost-benefit analysis must often then synthesize findings to present to management. This includes concisely summarizes the costs, benefits, net impact, and how the finding ultimately support the original purpose of the analysis.

Broadly speaking, if a cost-benefit analysis is positive, the project has more benefits than costs. A company must be mindful of limited resources that might result in mutually-exclusive decisions. For example, a company may have a limited amount of capital to invest; although a cost-benefit analysis of an upgrade to its warehouse, website, and equipment are all positive, the company may not have enough money for all three.

Not all cost-benefit analysis that result in net benefit should be accepted. For example, a company must consider the project's risk, coherence to its company imagine, or capital limitations,

Advantages of Cost-Benefit Analysis

There's plenty of reasons to perform cost-benefit analysis. The technique relies on data-driven decision-making; any outcome that is recommended relies on quantifiable information that has been gathered specific to a single problem.

A cost-benefit analysis requires substantial research across all types of costs. This means considering unpredictable costs and understanding expense types and characteristics. This level of analysis only strengthens the findings as more research is performed on the state of outcome for the project that provides better support for strategic planning endeavors.

A cost-benefit analysis also requires quantifying non-financial metrics (i.e. what is the financial benefit of increased employee satisfaction?). Although this may be difficult to assess, it forces the analyst to consider aspects of the project that are more difficult to measure. The ultimate result of a cost-benefit analysis is to deliver a simple report that makes it easier to make decisions.

Limitations of the Cost-Benefit Analysis

For projects that involve small- to mid-level capital expenditures and are short to intermediate in terms of time to completion, an in-depth cost-benefit analysis may be sufficient enough to make a well-informed, rational decision. For very large projects with a long-term time horizon, a cost-benefit analysis might fail to account for important financial concerns such as inflation, interest rates, varying cash flows, and the present value of money.

One of the benefits of using the net present value for deciding on a project is that it uses an alternative rate of return that could be earned if the project had never been done. That return is discounted from the results. In other words, the project needs to earn at least more than the rate of return that could be earned elsewhere or the discount rate.

However, with any type of model used in performing a cost-benefit analysis, there are a significant amount of forecasts built into the models. The forecasts used in any cost-benefit analysis might include future revenue or sales, alternative rates of return, expected costs, and expected future cash flows. If one or two of the forecasts are off, the cost-benefit analysis results would likely be thrown into question, thus highlighting the limitations in performing a cost-benefit analysis.

Cost-Benefit Analysis

Requires data-driven analysis

Limits analysis to only the purpose determined in the initial step of the process

Results in deeper, potentially more reliable findings

Delivers insights to financial and non-financial outcomes

May be unnecessary for smaller projects

Requires capital and resources to gather data and make analysis

Relies heavily on forecasted figures; if any single critical forecast is off, estimated findings will likely be wrong.

What Are the 5 Steps of Cost-Benefit Analysis?

The broad process for a cost-benefit analysis is to set the analysis plan, determine your costs, determine your benefits, perform analysis of both costs and benefits, and to make a final recommendation. These steps may vary from one process to another.

What Is the Main Goal of Using a Cost-Benefit Analysis?

The main goal of cost-benefit analysis is to determine whether it is worth undertaking a project or task. This decision is made by gathering information on the costs and benefits of that project. Management leverages the findings of a cost-benefit analysis to support whether there are more benefits to a project or if it is more detrimental to a company.

How Do You Weigh Costs vs. Benefits?

Cost-benefit analysis is a systematic method for quantifying and then comparing the total costs to the total expected rewards of undertaking a project or making an investment. If the benefits greatly outweigh the costs, the decision should go ahead; otherwise, it should probably not. Cost-benefit analysis will also include the opportunity costs of missed or skipped projects.

What Are Some Tools or Methods Used in Cost-Benefit Analysis?

Depending on the specific investment or project being evaluated, one may need to discount the time value of cash flows using net present value calculations. A benefit-cost ratio (BCR) may also be computed to summarize the overall relationship between the relative costs and benefits of a proposed project. Other tools may include regression modeling, valuation, and forecasting techniques.

What Are the Costs and Benefits of Doing a Cost-Benefit Analysis?

The process of doing a cost-benefit analysis itself has its own inherent costs and benefits. The costs involve the time needed to carefully understand and estimate all of the potential rewards and costs. This may also involve money paid to an analyst or consultant to carry out the work. One other potential downside is that various estimates and forecasts are required to build the cost-benefit analysis, and these assumptions may prove to be wrong or even biased.

The benefits of a cost-benefit analysis, if done correctly and with accurate assumptions, are to provide a good guide for decision-making that can be standardized and quantified. If the cost-benefit analysis of doing a cost-benefit analysis is positive, you should do it!

Some complex problems require deeper analysis, and a company can use cost-benefit analysis when it isn't abundantly clear whether or not to pursue an undertaking. By determining the expenses and identifying what will be favorable, a company can simplify the decision-making process by synthesizing a cost-benefit analysis.

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Benefit–Cost Analysis of Undergraduate Education Programs: An Example Analysis of the Freshman Research Initiative

• Rebecca L. Walcott
• Phaedra S. Corso
• Stacia E. Rodenbusch
• Erin L. Dolan

Department of Health Policy and Management, University of Georgia, Athens, GA 30602

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Texas Institute for Discovery Education in Science, College of Natural Sciences, University of Texas at Austin, Austin, TX 78712

*Address correspondence to: Erin L. Dolan ( E-mail Address: [email protected] ).

Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602

Institutions and administrators regularly have to make difficult choices about how best to invest resources to serve students. Yet economic evaluation, or the systematic analysis of the relationship between costs and outcomes of a program or policy, is relatively uncommon in higher education. This type of evaluation can be an important tool for decision makers considering questions of resource allocation. Our purpose with this essay is to describe methods for conducting one type of economic evaluation, a benefit–cost analysis (BCA), using an example of an existing undergraduate education program, the Freshman Research Initiative (FRI) at the University of Texas Austin. Our aim is twofold: to demonstrate how to apply BCA methodologies to evaluate an education program and to conduct an economic evaluation of FRI in particular. We explain the steps of BCA, including assessment of costs and benefits, estimation of the benefit–cost ratio, and analysis of uncertainty. We conclude that the university’s investment in FRI generates a positive return for students in the form of increased future earning potential.

INTRODUCTION

According to the National Center for Education Statistics, postsecondary institutions in the United States spend ∼$150 billion annually on instruction ( National Center for Education Statistics, 2016 ). Grants from federal, state, and philanthropic agencies provide additional funds for the development, testing, and evaluation of innovative undergraduate education programs, which, if demonstrated to be effective, often are expected to be sustained from other sources when grant funding ends. Yet the changing landscape in postsecondary education, including increasing enrollment, expanding access, and decreasing state-level investment, is putting added pressure on postsecondary education budgets ( Pew Charitable Trusts, 2015 ). How can administrators make informed decisions about how to invest limited funds? How can the directors of undergraduate education programs determine whether their initiatives yield sufficient benefits to be worth the cost, and how can they provide such evidence to administrators? Of course, many factors must be considered when making decisions about how to invest funds, including alignment of particular initiatives with institutional missions, priorities, and strategic plans. This Research Methods essay aims to add an additional tool to the decision-making toolbox: benefit–cost analysis.

Benefit–cost analysis (BCA) is one method of economic evaluation, or the systematic analysis of the relationship between costs and outcomes for a given program or policy. The purpose of economic evaluation is to provide stakeholders with information for making decisions about how to allocate resources, such as whether the benefits of the program outweigh its costs and whether returns on investments are sufficient to justify continued or even expanded funding for a program. The National Academies of Sciences, Engineering, and Medicine recently released a consensus study designed to improve the use of economic evidence to inform investments in children, youth, and families ( Steuerle et al. , 2016 ). Here, we offer a general guide for researchers and practitioners looking to conduct BCA to yield such evidence.

Two main types of economic evaluation are cost-effectiveness analysis (CEA) and BCA. CEA compares the costs of a program with its impacts measured in natural units, or units that occur in real life, such as college attrition rates. For example, CEA might yield information about the percentage by which college attrition rates are reduced per dollar spent on a program aimed at retaining students in college (i.e., $X spent results in Y% reduction in attrition). BCA compares program costs with program outcomes or impacts that have been monetized, or expressed in dollars. For instance, BCA could provide information about the extent to which a program increases a college student’s future earning potential for every dollar spent on the program (i.e., $X spent results in $Y increase in future earning potential). BCA produces several summary measures, including the ratio of benefits to costs (i.e., benefit–cost ratio [BCR]) and benefits minus costs, or net benefits, both of which are presented in net present dollars; that is, dollars expressed at a current value as opposed to a past or future value. Return on investment (ROI) analysis is a subset of BCA, in which results are presented as the percentage of the program cost that is returned as a program net benefit. For example, ROI might provide information about the benefit of an educational institution’s recruitment campaign in terms of increased tuition income for the institution ($X spent on recruitment yields $3X in tuition income, or an ROI of 200%). Table 1 presents the key features of CEA, BCA, and ROI for a hypothetical disease vaccination program. The hypothetical program costs $5000 and averts 50 cases of the disease. The cost of disease treatment is assumed to be $250. Therefore, the benefits of the program are $12,500 (50 cases averted * $250 per case) and the net benefits are $7500 ($12,500 − $5000).

Although economic evaluation is commonly used to evaluate healthcare and public health interventions ( Haddix et al ., 2003 ; Drummond et al ., 2015 ; Neumann et al ., 2016 ), regular application of economic evaluation in the field of education has primarily focused on early childhood educational programs ( Barnett, 1985 ; Lee et al ., 2012 ; Karoly, 2016 ). The application of economic evaluation to postsecondary education programs and policies is more nascent, as evaluations in these contexts face increased study design challenges as well as a lack of standardized outcome measures ( Hummel-Rossi and Ashdown, 2002 ). Our purpose with this essay is to describe methods for conducting a BCA as one approach to economic evaluation, using an example of an existing undergraduate research experience (URE) program, the Freshman Research Initiative (FRI) at the University of Texas Austin (UT Austin). We hope this example will be useful for demonstrating how to apply economic methodologies to evaluate an undergraduate education program and also for evaluating the costs and benefits of FRI in particular.

FRI was developed at UT Austin to engage students in multiple semesters of course-based undergraduate research experience (CURE) early in their college careers, with the goal of increasing students’ persistence in scientific degree programs and careers. FRI makes use of an expanded apprenticeship model, integrating large numbers of undergraduate students into research groups, called “research streams,” as an alternative to entry-level laboratory courses. The program comprises a three-course sequence taken within the first 2 years of undergraduate study. In each stream, groups of 35–40 undergraduate students work on a common research problem with mentorship and guidance from a PhD-trained research educator (RE) and a tenure-track/tenured principal investigator. The RE role is unique and essential to FRI, because each RE mentors 35+ students in his or her stream, which would not be practical in a more traditional research group structure. REs are immersed in the cognitive apprenticeship model of interaction with the students ( Ritchie and Rigano, 1996 ), creating and implementing a research program designed to support students in learning core science concepts and research skills while making meaningful scientific contributions (e.g., authorships on peer-reviewed publications). FRI capitalizes on the power of research experiences as a science, technology, engineering, and mathematics (STEM) recruitment and retention tool, integrating a combination of experiences that contribute to student success: mentoring ( Coppola, 2001 ), tutoring ( Topping, 1996 ), research experiences ( Lopatto, 2007 ; Russell et al ., 2007 ; Hurtado et al ., 2009 ), and learning communities ( Springer et al ., 1999 ).

A recent consensus study from the National Academy of Sciences highlights the need for more research evaluating the benefits and costs of UREs, particularly for students majoring in STEM fields ( National Academies of Sciences, Engineering, and Medicine, 2017 ). Several existing studies discuss the benefits and costs of UREs but do not attach a monetary value to program benefits and costs, which precludes economic evaluation ( Pennebaker, 1991 ; Hoffman, 2009 ; Lei and Chuang, 2009 ). These studies are undoubtedly helpful in providing information about the supports and constraints of implementing a program. Yet there is a clear gap in knowledge regarding the potential returns of allocating resources to UREs.

Here we focus on BCA, the first step of which is to clearly define the program of interest and to identify the program’s alternative, or the “status quo” experience ( Karoly, 2016 ; Steuerle et al. , 2016 ). The status quo experience refers to the program or intervention that the study population would receive if they were not participating in the program being evaluated. In many cases, the status quo refers to a “do-nothing” approach. This alternative experience serves as the baseline for comparison to most accurately capture the costs and benefits attributable to the program. For our example, FRI is the program of interest and STEM majors who do not participate in FRI take comparable non-CURE science courses (i.e., the status quo experience), referred to hereafter as the comparison program.

After the program and the alternative have been clearly defined, it is necessary to have demonstrated evidence of program effectiveness, or the impact of the program compared with the alternative. An important point to remember is that the usefulness of an economic evaluation rests on the robustness of the underlying effectiveness study. The effectiveness study should be conducted with a comparable population, should incorporate valid methodology, and should produce outcomes amenable to economic analysis. FRI is a good candidate for BCA, because it is an example of a large-scale URE program for which effectiveness has been demonstrated ( Rodenbusch et al ., 2016 ). Participation in FRI has been shown to increase overall graduation rates from 66% for comparison students to 83% for FRI students, after carefully controlling for other factors that affect graduation rates using propensity score matching. FRI has also been shown to increase the percentage of students graduating with a STEM major (instead of transferring to a non-STEM major) from 71% for comparison students to 94% for FRI students. See work from Beckham, Rodenbusch, and colleagues for more details about FRI and its effects ( Beckham et al ., 2015 ; Rodenbusch et al. , 2016 ). These results, along with data on the costs of FRI and the comparison experience, allow for a BCA of the program to be conducted, which we describe in the following section.

To conduct a BCA of FRI, we estimated all costs incurred by UT Austin for both FRI and the comparison program. We conceptualized program benefits as the estimated future potential earnings of FRI students relative to comparison program students. We used a BCR as the summary measure, estimating the ratio of benefits to costs for FRI in relation to the comparison program. We illustrate this process in Figure 1 and describe each step in the following sections.

FIGURE 1. Flowchart for BCA outlining the steps necessary to conduct and interpret a BCA for a program.

Estimating Costs

We started by conducting a programmatic cost analysis, which is the standard first step in economic evaluation including BCA and refers to the collection, valuation, and analysis of all resources required to implement a program or policy. We first determined the perspective of the analysis (i.e., who bears the costs), as the perspective will drive which cost data we choose to collect. For example, if we analyze the program from an organizational perspective—in the case of FRI this would be UT Austin—we would only collect data on costs paid by the organization. Alternatively, we could frame the analysis from a societal perspective and include costs to participants as well as the organization, such as time and travel costs. Best practices for economic evaluation indicate using the societal perspective in order to provide the most comprehensive picture of benefits and costs ( Steuerle et al. , 2016 ). However, recommendations for education studies emphasize the importance of matching the study perspective to the goals of the evaluation, especially in cases when a societal perspective would unnecessarily complicate the interpretation of the study findings ( Barnett, 1993 ; Hummel-Rossi and Ashdown, 2002 ). Here, we analyzed costs from the university’s perspective and did not consider the costs to students to participate in FRI, because we did not anticipate that costs to FRI versus comparison students would differ (i.e., students do not pay extra costs to participate in the program). We also did not include an estimate of any potential cost differences in terms of the time or effort students spent in FRI versus the comparison experience. We could not reliably estimate these values and did not expect them to differ appreciably between the two experiences, although this should be tested more directly in future studies.

Once an analytic perspective is selected, costs are collected prospectively or retrospectively , using a microcosting or gross-estimation approach. Prospective cost collection refers to the ongoing recording of program costs as they accrue, such as through activity logs, project invoices, and travel logs. Retrospective cost collection involves estimating expenditures after program implementation. Microcosting involves collecting costs by identifying individual resources, while gross estimation uses total program expenditures as costs (e.g., from budgets). Prospective microcosting for both preimplementation (i.e., planning and development) and implementation phases is preferred, because it provides the most detail about the resources required to implement a program and therefore is the most useful for program implementers ( Steuerle et al. , 2016 ). However, this method requires the most evaluator effort and is not always feasible.

For our BCA of FRI, we used a retrospective microcosting approach from the university perspective. We obtained itemized expenditure data from the FRI program, including the individual personnel costs (salary plus fringe for instructors/REs and graduate/undergraduate assistants) and materials costs for each FRI course and for each comparison course. Regarding indirect costs, the FRI program was found to use more building resources than the comparison experience due to students spending more time in campus labs for assignments: FRI courses 1 and 2 used ∼75% more building resources than their comparators, and FRI course 3 was set equal to FRI course 2, while comparison course 3, an independent study, used no building resources. Indirect (or overhead) costs can be allocated several different ways depending on the information available, but it is generally recommended that allocation be tied to resource use, such as total direct costs or total personnel costs ( Drummond et al. , 2015 ; Steuerle et al. , 2016 ). We estimated building resource costs as a proportion of total personnel costs based on the allocation found in the University of Texas system’s annual financial report. In other words, we set building resource costs at 2.8% of total personnel costs for comparison courses 1 and 2 ( University of Texas System, 2016 ). There was no marginal difference in administrative costs and institutional support costs between the FRI program and the comparison experience, as both course sequences require similar levels of administration and coordination. Therefore, these costs were not included.

We focused our cost collection on implementation costs, because planning and development costs were not available and may also differ significantly between institutions planning FRI-like programs. We provide a summary of the costs of FRI and the comparison experience in Table 2 . Because different courses had different levels of enrollment, we present costs at the per student level. On average, FRI costs $2875 per student, while the comparison program costs $1820 per student.

a Owing to rounding, there may be slight discrepancies in sums.

Estimating Benefits

Before a BCA can be conducted, the benefits of the education program of interest must be identified and monetized. Benefits can be multiple and far-reaching, accruing to students in the form of higher grade point averages and to institutions in the form of reputation. Rodenbusch and colleagues (2016) identified benefits of FRI by comparing outcomes of students who participated in FRI versus a propensity score–matched group of students who participated in the comparison experience. They found that FRI participation led to significant increases in likelihood of graduating from college (from 66 to 83%) and significant improvements in rates of STEM retention (from 71 to 94%) ( Rodenbusch et al. , 2016 ). STEM retention refers to the sample of students who entered college with a declared STEM major and graduated from college with a STEM major. Because FRI had demonstrated effectiveness for these two outcomes, we used college graduation and STEM major to define our study benefits. Attrition from college (i.e., not graduating) represents a third, complementary outcome for our study population.

The outcome must be monetized to turn a study outcome into a benefit for BCA. Future earning potential is a common outcome measure for BCAs in education ( Stem et al ., 1989 ; Hummel-Rossi and Ashdown, 2002 ; Karoly, 2016 ), and we chose to use future earning potential as a monetization for each of the three outcomes. Data provided by the Hamilton Project at the Brookings Institution show career earnings by educational attainment and by college major, both as median annual earnings over a career and as median lifetime earnings ( Hershbein and Kearney, 2014 ). The earning potentials generated by the Hamilton Project are comparable to other estimates when adjusted for discounting and inflation ( Carnevale et al ., 2013 ). By categorizing the majors into two groups, STEM and non-STEM, we were able to estimate a median potential earnings value for each group. We defined our study benefits in terms of median initial annual earning potential and median lifetime earning potential for each of our three study outcomes: college attrition, graduation with a STEM degree, or graduation with a non-STEM degree. College graduates have a much higher earning potential than those who leave college without graduating, and STEM graduates have a higher earning potential than graduates with majors in non-STEM fields. We summarize the benefits for this analysis in Table 3 .

a Lifetime earnings are discounted annually at a rate of 3%.

It should be noted that, instead of directly comparing institutional costs to institutional benefits, we are chose to measure benefits exclusively from the student perspective. Many additional benefits of FRI could also be monetized and analyzed, such as the tuition dollars gained and reduced recruitment costs from increased student retention, as well as benefits to the reputation of UT Austin ( Heldman, 2008 ; Raisman, 2013 ). Increased retention is also likely to save state and federal governments money in the form of publicly funded scholarships and grants provided to students who end up dropping out ( Schneider, 2010 ). Finally, from a societal perspective, increased graduation rates and increased STEM graduation rates in particular are likely to produce societal benefits in the form of technological progress and increased economic productivity ( Krueger and Lindahl, 2001 ). Including additional benefits in our analysis may have resulted in a more comprehensive BCA, but the challenges inherent in monetizing more abstract and distal benefits, such as quantifying reduced recruitment costs in terms of FRI effectiveness and how to value increased university reputation, would likely have weakened the overall usefulness of the study. We opted not to monetize these additional benefits in order to maintain a simplified focus on the organizational and student perspectives and in an effort to prioritize the explanation of the BCA process for this essay.

For making fair cost comparisons, it is important to ensure costs and benefits are adjusted for inflation and for time preference (i.e., discounting), especially for cases in which the benefits occur in the future. The value of a dollar 5 years ago does not equal the value of a dollar today, and adjusting for inflation mitigates this difference in purchasing power. For this study, we collected FRI costs for 1 year of operation in 2015 and obtained benefits data presented in 2014 U.S. dollars. To adjust for inflation, we used the All Items Index of the Consumer Price Index to adjust all costs to the base year of 2014, so that all dollar values of costs and benefits possess equal purchasing power ( Bureau of Labor Statistics, 2014 ). Discounting is separate from inflation and can be defined as the reduced valuation of costs and benefits that occur in the future due to the concept of time preference. Time preference refers to the advantage of obtaining a benefit now instead of in the future, and this preference holds true even in a scenario in which inflation does not exist. The costs of FRI do not need to be discounted, as they occur in a single year; however, the benefits of FRI accumulate over the course of the student’s career, and this differential timing of costs and benefits necessitates discounting. Therefore, the future earning benefits obtained from the Hamilton Project were discounted at a 3% annual rate (a common discount rate for social programs) and are reported as present values in order to be fairly compared with the program costs ( Hershbein and Kearney, 2014 ). Additional adjustments for monetized benefits may be necessary to ensure that the transfer of benefits from one source accurately applies to the population under consideration. For example, a geographic cost of living adjustment may be required if benefits estimates derived from a Los Angeles population are applied to participants of a program implemented in the Midwest. Because the future earning potential estimates used in this study were derived from a nationally representative sample and we have no reason to believe that UT graduates significantly over- or underearn when compared with the national average, no further adjustments are necessary.

Modeling Costs and Benefits

The decision tree is among the most common methods for modeling economic evaluations ( Drummond et al. , 2015 ). A decision tree ( Figure 2 ) functions like a flowchart, with a hypothetical population beginning at a decision node (rectangle) and then proceeding through the tree sequentially until arriving at a final outcome represented by a terminal node (triangle). Along the route are chance nodes (circles) at each bifurcation in the tree, which represent the probability of a given event occurring along the pathway. At the end of the tree, each terminal node represents a final outcome associated with the pathway of events. The probability of each final outcome occurring can be calculated by multiplying the probabilities at each chance node along a particular path through the tree. The average projected cost and benefit of each path can then be calculated and compared.

FIGURE 2. Decision tree model for the costs and benefits of FRI vs. the comparison program. The potential population of FRI is STEM majors at a decision node (rectangle on left), who either become part of the FRI or comparison group. Chance nodes (circles) are points where the population has different likelihoods of pursuing different paths on the way to realizing different outcomes (triangles). The percentages of the population that proceed on each path are noted next to the path. The probability of each outcome occurring is calculated by multiplying the probabilities at each chance node (i.e., the percentages) associated with that path. The average cost and benefit of each path can then be calculated and compared (on right).

Figure 2 depicts a decision tree for estimating the projected costs and benefits of FRI versus the comparison program. The hypothetical population consists of STEM majors who participate or not in FRI (the decision node). For simplicity’s sake, we assume a population of 200 STEM majors, with 100 in the FRI path and 100 in the comparison path. Following the two populations sequentially through the tree, the evidence from Rodenbusch et al. (2016) suggests that one would expect 17% of the FRI students to leave college and 34% of comparison students to leave college. Of the 83 FRI students who graduate college, 94% (i.e., 78 students) go on to graduate with a STEM degree, while the remaining five graduates do not. Similarly, 71% of the 66 comparison students who graduate (i.e., 47 students) do so with a STEM degree, while the remaining 19 comparison students graduate in a non-STEM field.

The right side of the decision tree ( Figure 2 ) shows the expected probability for each group (FRI vs. comparison) of achieving each of the three outcomes and the associated potential earnings. Probabilities are rounded to the nearest hundredth in this example. Because average costs do not vary among outcomes within each study group, they are shown only at the decision node. Average potential earnings for each study group are estimated with the expected outcome probabilities as weights. On the basis of this model, we estimate that the expected average median initial annual earning potential for FRI students is $27,658, while the expected average median initial annual earning potential for comparison program students is $23,305. The expected average median lifetime earning potential for FRI students is $1,284,400, while the average median lifetime earning potential for comparison students is $1,106,450.

Benefit–Cost Analysis

The next step in a BCA is to directly compare the program’s costs with its benefits. It is common for BCAs to compare a program with a scenario in which there is no program in place, referred to as a “do-nothing” scenario. A do-nothing scenario has a cost of $0, making the calculation of the BCR relatively straightforward: the benefits of the new program are compared with the costs of the new program. For example, BCAs of early childhood education programs often compare a preschool population with a population that did not attend preschool. The benefits are estimated from the improved performance of the preschool graduates compared with children who did not attend preschool, and the BCR reflects these benefits compared with total program costs. However, when the comparison experience is not a do-nothing scenario but instead refers to a basic program or the status quo, which the program of interest is enhancing, it is more appropriate to compare the incremental costs and benefits in a BCR ( Karoly, 2016 ).

In this study, we compare FRI with a traditional college course sequence, the status quo in this case, instead of a do-nothing scenario; therefore, we estimated the incremental, or additional, costs and benefits of FRI relative to the costs and benefits of the status quo. The microcosting data indicate that FRI costs an average of $1055 more per student than the comparison program. The projected benefits indicate that participation in FRI produces an average increase of $4353 per student in potential initial annual earnings and $177,950 per student in potential lifetime earnings. Thus, FRI participants are estimated to earn almost 19% more in initial annual earnings upon graduation and 16% more in lifetime earnings when compared with the comparison group. Calculating an incremental ratio of benefits to costs reveals a 4.13:1 ratio for initial annual earning potential and a 169:1 ratio for lifetime earning potential. Any ratio greater than 1:1 indicates a positive return on the university’s investment. Thus, we estimate that FRI generates a return of more than $4 in students’ initial earning potential and a return of $169 in students’ lifetime earning potential for every $1 that the university invests when compared with the earning potential of students in the comparison program.

The final step of an economic evaluation, including BCA, is to conduct a sensitivity analysis ( Drummond et al. , 2015 ; Steuerle et al. , 2016 ). Costs and benefits of a program may vary among participants, and a sensitivity analysis is conducted to reflect this uncertainty. For this study, we conducted a two-way sensitivity analysis, in which we varied two key parameters both individually and simultaneously in order to present potential scenarios producing lower- and upper-bound estimates to supplement our baseline estimate of the BCR.

The first key parameter we varied for the sensitivity analysis was the average cost per student of the FRI course sequence, as this cost depends on the resource intensity of the research undertaken in each course. For example, computer science courses required far fewer resources than wet-lab science courses. Our data showed that total FRI program costs ranged from $2137 to $3785 per student for the three courses; therefore, we assumed FRI costs of $2137 per student in a low-cost scenario and a cost of $3785 per student in a high-cost scenario. A more robust sensitivity analysis would also include the associated differences in effectiveness by course type, but these data were not available in the effectiveness study.

The second key parameter we varied was the graduation rate of students in the hypothetical cohort. Our baseline scenario assumed that students who left UT Austin did not finish college elsewhere and accrued the future earning potential of students who never finish college. For the sensitivity analysis, we add a scenario in which 10% of students who leave UT Austin enroll in and graduate from a different college ( Schneider, 2010 ) and thus accrue the future earning potential of a non-STEM graduate.

Table 4 presents the results of a two-way sensitivity analysis. The estimates of FRI costs are given in the first column, followed by the BCRs for the baseline graduation assumptions and then the ratios for the increased graduation rates. The lowest BCR scenario (the costliest FRI course sequence and the increased graduation rate) reduced the incremental BCR to 2.12:1 for initial annual earnings and 88:1 for lifetime earnings, while the highest BCR scenario (the least costly FRI courses and the baseline graduation rate) increased the BCR to 13.7:1 for initial annual earnings and 561:1 for lifetime earnings. Therefore, every additional dollar that UT Austin invests in FRI when compared with a traditional program of study generates $2 to $14 in returns for students in increased potential initial annual earnings and $88 to $561 in returns for students in increased potential lifetime earnings. In all scenarios, even the most costly FRI courses generate a positive return for students.

a Increased graduation rate assumes that 10% of those who leave college go on to graduate from a different institution and thus gain the earning potential of a college graduate.

LIMITATIONS

There are several limitations to our FRI analysis that should be considered in any economic evaluation. First, best practices for economic evaluation recommend a societal rather than organizational perspective in order to provide the most comprehensive economic estimates ( Steuerle et al. , 2016 ). Such a perspective would account for any marginal differences in student costs between the two programs, including marginal differences in time spent on course work. However, a comprehensive societal perspective requires more extensive data collection and does not always have a straightforward and applicable interpretation. In our example analysis of FRI, we made use of multiple perspectives in an effort to most clearly and succinctly illustrate how the university’s investment can benefit FRI students. Specifically, we estimated costs from an organizational perspective, as UT Austin (the organization) funds the extra programmatic costs of FRI (students do not pay extra fees to participate in the program). We estimated benefits as future earning potential from a student perspective, because improving student retention in college and in STEM were primary objectives of the program. Multiple perspectives are not uncommon in BCA; BCAs of government programs often incorporate multiple perspectives, as costs are typically estimated from the government’s perspective, while benefits accrue to vulnerable populations who may not contribute to the tax base for the program. Public education funding serves as a useful example, because property taxes fund a large proportion of public education, but not all who pay property taxes have children using public education and not all who benefit from public education pay property taxes. Such a multiperspective approach does, however, preclude a traditional ROI analysis, as the student benefits do not necessarily return to the investor (the university). An analysis that estimated benefits in terms of increased tuition dollars or attributable alumni donations would allow for an estimation of ROI.

Second, there are limitations in our assumptions of costs and benefits. We did not include preimplementation costs, such as planning costs, in our estimate of FRI costs. Including these costs would decrease the BCR, although over time this impact would lessen as these costs were spread over more FRI participants. Further, we obtained effectiveness data at the aggregate level only and therefore were unable to analyze costs and outcomes more precisely at the major level, which would have enabled BCR estimates by major. In our estimation of benefits, we did not have data on the actual earnings of FRI graduates and instead used existing national estimates to project the earning potential of STEM versus non-STEM graduates. We used median estimates instead of average earnings to mitigate the skewedness of the data, but variances in earning were unequal between STEM and non-STEM majors, with non-STEM majors realizing higher variance. Additionally, median earnings data were reported at the major level, and in order to report group-level earnings potential of STEM and non-STEM majors, we used the median earnings of the median major for each group. These are not the true median earnings of STEM and non-STEM majors, as those data were unavailable.

Finally, we presented a simple two-way sensitivity analysis, which introduced the concept of uncertainty, to encourage readers to consider how variability in assumptions may affect the evaluation’s conclusions. However, per guidance on how to conduct sensitivity analyses from the National Academies and others, a more robust sensitivity analysis should include varying all parameters in the model, uniquely and simultaneously ( Drummond et al. , 2015 ; Steuerle et al. , 2016 ). In our sensitivity analysis, there are no analyses of uncertainty around the benefit estimates of future earning potential or around the effectiveness of FRI, and a robust multiway analysis incorporating these parameters would be appropriate. The use of more sophisticated modeling techniques, such as probabilistic sensitivity analysis, would also strengthen the study.

A recent consensus study calls for research that evaluates the benefits and costs of UREs, particularly for students in STEM majors ( National Academies of Sciences, Engineering, and Medicine, 2017 ). Here, we aimed to provide more general guidance on how to conduct economic evaluations of undergraduate education programs by explaining the basic methods used to assess a program’s benefits and costs in a BCA. To illustrate how BCA can be used in practice, we conducted a BCA using a large-scale URE program, the FRI at UT Austin, the results of which can be used to inform decisions about the program. We conclude that the university’s investment in FRI is likely to generate a positive return for students in the form of increased future earning potential.

ACKNOWLEDGMENTS

We thank Lauren Crowe, Cassandra Delgado-Reyes, and Marty Mass for providing cost information. Support for FRI was provided by a grant from the Howard Hughes Medical Institute (#52006958). The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of HHMI.

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Submitted: 11 July 2017 Revised: 8 December 2017 Accepted: 11 December 2017

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10 Cost-Benefit Analysis Examples

Cost-benefit analysis refers to an assessment of the benefits of a particular course of action, weighed against the costs incurred.

This type of analysis is useful for identifying the best path forward among a range of possible options, each with their own pros and cons. It is most commonly used in economics.

Cost-benefit analysis has two main applications: 

• Determining the soundness of a decision.
• Providing a basis for comparing alternative decisions (see: opportunity cost analysis ). 

A simple example of a cost-benefit analysis would involve an investor weighing up whether to buy real estate or stocks. Each has its own strengths and weaknesses, and they would need to consider their own context to determine which has the greatest cost-benefit (i.e. benefits per dollar).

Definition of Cost Benefit Analysis

Cost-benefit analysis (or benefit-cost analysis) is a systematic approach to deciding between alternatives based on their costs and benefits.

It may be used to compare completed or potential courses of action. It is often used to evaluate business or policy decisions, economic transactions, project investments, and so on. 

Cost-benefit analysis identifies and places monetary values on the costs of programs.

Furthermore, it requires weighing those costs against the monetary value of program benefits (Riegg Cellini & Edwin Kee, 2015).

Often, this is achieved through calculating the benefit-cost ratio of a particular course of action, calculated as follows:

Benefit-Cost Ratio (BCR) = Present Value of Expected Benefits / Present Value of Expected Costs

This formula helps to determine whether the benefits outweigh the costs. A BCR greater than 1 indicates that the project’s benefits are expected to be greater than its costs, and vice versa.

Cost-benefit analysis proceeds by a ten-step process (Boardman et al., 2011; Riegg Cellini & Edwin Kee, 2015):

• Analysis Framework Setting: Decide on the type of analysis to be undertaken, such as a cost-benefit analysis or a cost-effectiveness analysis.
• Stakeholder Identification: Recognize whose costs and benefits should be accounted for. Considerations include which stakeholders are affected and who should have standing in the program or policy.
• Costs and Benefits Categorization: Identify and categorize all costs and benefits associated with the program or policy.
• Lifetime Costs and Benefits Projection: Project how costs and benefits will evolve over the lifespan of the program, if applicable.
• Cost Monetization: Assign a monetary value to all or most costs to facilitate comparisons.
• Benefit Quantification: Quantify benefits in terms of monetary units. The goal is to assign a dollar value to every major output or benefit, taking into consideration varying beneficiary groups and program objectives.
• Discounting Costs and Benefits: Discount future costs and benefits to their present values to account for the time value of money.
• Net Present Value Calculation: Compute the net present value (NPV) which represents the difference between the present value of cash inflows and the present value of cash outflows.
• Sensitivity Analysis: Test the sensitivity of the analysis to specific assumptions, determining how different values of an independent variable impact the particular dependent variable under consideration.
• Recommendation Generation: Based on the results of the cost-benefit analysis, make a suitable recommendation. If the program has a positive net present value, especially after a worst-case sensitivity analysis, the policy should be implemented as it would increase social welfare. Conversely, a program with a negative net present value should be rejected (Riegg Cellini & Edwin Kee, 2015).

The concept of cost-benefit analysis and its fundamental formulas are quite simple, but actually carrying out a cost-benefit analysis can be extremely challenging. 

10 Examples of Cost Benefit Analysis

1. investment decisions.

A company is trying to decide between two alternative investments, so it decides to conduct a cost-benefit analysis to compare the two.

• Total costs of the first alternative: $100,000
• Total benefits of the first alternative: $120,000
• Total costs of the second alternative: $150,000
• Total benefits of the second alternative: $200,000

The basic formula to use to decide between the two alternatives is the following:

Benefit-Cost Ratio = Expected Benefits / Total Costs

• Benefit-Cost Ratio of the first alternative: 120,000/100,000=6/5
• Benefit-Cost Ratio of the second alternative: 200,000/150,000=4/3

The Benefit-Cost Ratio of the second alternative is larger than that of the first, so the second investment will be more profitable for the company. 

2. Real Estate Development Options

A construction company needs to compare two potential real estate development projects. The company doesn’t have the resources to engage in both, so it has to choose. 

Each project has a different number of housing units that need to be constructed, how many of those will be sold and how many will be rented also differs. The rental prices, construction costs, sale prices, personnel costs, durations, and financing costs of each project also differ. 

A cost-benefit analysis will have to take account of each relevant parameter to estimate how much each project will cost in total and how profitable each will be. The two projects can then be compared based on the cost-benefit ratio of each (Castle, 2018). 

3. Weighing whether to Buy new Equipment

A company wants to decide whether to make a new equipment purchase. The company wants to know whether this new purchase might save money in the long term, so it conducts a cost-benefit analysis. 

• Total costs of the new equipment: $100,000
• Annual benefits of the new equipment: $25,000

So the company will make a profit after the fourth year. The company then has to decide whether this is worth it. 

4. Whether to Hire more Workers

A company decides to conduct a cost-benefit analysis of hiring 10 new workers. 

• Total costs: $200,000
• Total benefits: $250,000

The company can generate an extra $50,000 each year, so they should go through with the decision and hire 10 new workers.

5. Public Infrastructure Decisions

A city council is deciding between building a new public park or a community center. A cost-benefit analysis is carried out for each option:

• Total costs of the public park: $500,000 Estimated societal benefits of the park (increased property value, improved health, etc.): $700,000
• Total costs of the community center: $750,000 Estimated societal benefits of the community center (education, community cohesion, etc.): $900,000
• Benefit-Cost Ratio of the public park: 700,000/500,000=7/5 Benefit-Cost Ratio of the community center: 900,000/750,000=6/5

The public park has a higher Benefit-Cost Ratio and could therefore be a more favorable option, despite the community center having higher absolute benefits.

6. Healthcare Investment

A hospital is considering investing in new MRI technology or in a specialized heart disease treatment program.

• Total costs of the MRI technology: $2,000,000 Estimated patient benefits of MRI technology: $2,500,000
• Total costs of the heart disease program: $1,500,000 Estimated patient benefits of heart disease program: $2,200,000
• Benefit-Cost Ratio of MRI technology: 2,500,000/2,000,000=5/4 Benefit-Cost Ratio of the heart disease program: 2,200,000/1,500,000=44/30

Despite the heart disease program having a lower absolute benefit, it has a higher Benefit-Cost Ratio and might be a better investment for the hospital.

7. Education Policy Choices

A school district is deciding between implementing a new online learning system or hiring additional teaching staff. A cost-benefit analysis helps in decision making:

• Total costs of online learning system: $300,000 Estimated benefits of online learning system (increased learning efficiency , accessibility, etc.): $450,000
• Total costs of hiring additional staff: $400,000 Estimated benefits of additional staff (improved student-teacher ratio, individual attention, etc.): $550,000
• Benefit-Cost Ratio of online learning system: 450,000/300,000=3/2 Benefit-Cost Ratio of additional staff: 550,000/400,000=11/8

Despite the additional staff providing higher absolute benefits, the online learning system has a higher Benefit-Cost Ratio, making it a more efficient investment.

8. Software Upgrade Decision

A tech company is weighing the costs and benefits of upgrading their existing software versus purchasing a new one.

• Total costs of upgrading existing software: $10,000 Estimated benefits of upgrading existing software: $20,000
• Total costs of purchasing new software: $25,000 Estimated benefits of new software: $40,000
• Benefit-Cost Ratio of upgrading existing software: 20,000/10,000=2/1 Benefit-Cost Ratio of new software: 40,000/25,000=8/5

Upgrading the existing software has a higher Benefit-Cost Ratio, indicating it might be a more cost-effective choice for the company.

9. Environmental Policy

A government is considering investing in a renewable energy project or continuing to support fossil fuel-based energy production. A cost-benefit analysis is needed:

• Total costs of renewable energy project: $1,000,000
• Estimated societal benefits of renewable energy (lower pollution, sustainability, etc.): $1,300,000

Total costs of fossil fuel support: $800,000 Estimated societal benefits of fossil fuel support (job retention, immediate energy supply): $900

10. Whether to add a New Service

A software company is planning to speed up its delivery dates. But doing so would require hiring three additional coders, which requires investments like buying new furniture, and computers, and leasing additional workspace (Castle, 2018). 

• Assume that the yearly revenue is $100,000 but it will increase by 50% as the capacity increases. 
• Assume that each coder earns $10 per hour. 

A cost-benefit analysis will have to take the following costs and benefits into account:

• Rental cost per year: $15,000
• Furniture costs: $10,000
• Hiring costs per year: $23,040
• Hardware & software costs: $10,000
• Downtime costs: $10,000
• 10% annual revenue increase: $50,000

Summing up the costs, we can see that they amount to more than $68,000, so the costs of the project would be larger than their benefits. 

Cost-Benefit Analysis vs Cost-Effectiveness Analysis

In economics, cost-benefit analysis is related to cost-effectiveness analysis:

• Cost-effectiveness analysis: this compares the relative costs and outcomes (instead of benefits) of different decisions. It aims to be more holistic. 
• Cost-benefit analysis: this tends to assign a monetary value to a course of action to identify the best course to pursue (Bleichrodt & Quiggin, 1999). 

Riegg Cellini and Edwin Kee (2015) define the two as follows:

“Cost-effectiveness analysis is a technique that relates the costs of a program to its key outcomes or benefits. Cost-benefit analysis takes that process one step further, attempting to compare costs with the dollar value of all (or most) of a program’s many benefits. These seemingly straightforward analyses can be applied anytime before, after, or during a program implementation, and they can greatly assist decision makers in assessing a program’s efficiency.

For a General List of Analysis Examples, See Here

Cost-benefit analysis is an essential part of doing business as it helps businesses to identify the most efficient and productive ways to dedicate resources and time in order to achieve optimal outcomes for both the company and the client. By calculating the benefit-cost ratio, we can directly compare two options.

However, it’s important to note that a cost-effectiveness analysis may provide a more holistic overview that considers outcomes (such as human impact) rather than just costs.

Bleichrodt, H., & Quiggin, J. (1999). Life-cycle preferences over consumption and health: When is cost-effectiveness analysis equivalent to cost–benefit analysis? Journal of Health Economics , 18 (6), 681–708. https://doi.org/10.1016/S0167-6296(99)00014-4

Boardman, A., Greenberg, D., Vining, A., & Weimer, D. (2011). Cost-Benefit Analysis: Concepts and Practice, 4th edition .

Castle, K. (2018, February 13). Cost Benefit Analysis Example and Steps (CBA Example). Projectcubicle . https://www.projectcubicle.com/cost-benefit-analysis-example/

Riegg Cellini, S., & Edwin Kee, J. (2015). Cost-Effectiveness and Cost-Benefit Analysis. In Handbook of Practical Program Evaluation (pp. 636–672). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781119171386.ch24

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Cost Effectiveness Analysis for Nursing Research

With ever increasing pressure to reduce costs and increase quality, nurses are faced with the challenge of producing evidence that their interventions and care provide value. Cost effectiveness analysis (CEA) is a tool that can be used to provide this evidence by comparative evaluation of the costs and consequences of two or more alternatives.

The aim of this article is to introduce the essential components of CEA to nurses and nurse researchers with the protocol of a recently funded cluster randomized controlled trial as an example.

This article provides: (a) a description of the main concepts and key steps in CEA, and (b) a summary of the background and objectives of a CEA designed to evaluate a nursing led pain and symptom management intervention in rural communities compared to current usual care.

As the example highlights, incorporating CEA into nursing research studies is feasible. The burden of the additional data collection required is off-set by quantitative evidence of the given intervention's cost and impact using humanistic and economic outcomes. At a time when US health care is moving toward accountable care, the information provided by CEA will be an important additional component of the evidence produced by nursing research.

The rising cost of U.S. health care has been a political issue for almost 40 years ( McMahon & Chopra, 2012 ). Many attempts have been made to mitigate health care costs while ensuring that the quality of patient care does not suffer in the process. Over the last 40 years managed care, as well as hospital and physician payment reforms, has come and gone without success ( Berenson & Rich, 2010 ). The Patient Protection and Affordable Care Act (P-PACA) (2010) represents the latest national effort to improve quality and reduce health care costs.

A key component of P-P ACA is the development of health care systems innovations, such as Accountable Care Organizations (ACOs), that aim to meet the P-PACA goal of ensuring accessible, high-quality, and affordable health care for all Americans ( U.S. Department of Health and Human Services, 2011 ). ACOs move beyond the expansion of health care insurance coverage to also include shift in payment incentives from volume (as seen in a fee-for-service model) to quality and outcomes ( Fisher, Bynum, & Skinner, 2009 ; Goroll & Schoenbaum, 2012 ; Sommers & Bindman, 2012 ).

This shift has created an increasingly competitive environment. Nurses, as health care providers, leaders, and advocates of high-quality, patient-centered, and cost effective health care ( Hart, 2012 ), will need to provide evidence of the value they provide. Cost effectiveness analysis (CEA) is a tool that can provide this evidence by evaluating both the costs and effectiveness of nursing interventions. While evidence of clinical effectiveness is essential for health care decision makers, the results of well-designed cost effectiveness studies provides important additional information on costs and effectiveness for policy makers, payers, and consumers. The aim of this article is to introduce the essential components of CEA to nurses and nurse researchers. The protocol of a recently funded cluster randomized controlled trial “Symptom Management in Rural Communities” will be used as an example.

Main Concepts and Key Steps

Scarcity of resources creates the need to make choices about how available resources will be used. Not all needs or wants can be met. Some interventions are not feasible, and the resultant benefits unattainable, because their costs exceed available resources ( Rhodes, Battin, & Silvers, 2012 ). It is thus important to maximize return from the resources that are available.

CEA is a tool used for comparative analysis of different ways of using scarce health care resources. This involves comparing current “usual care” to one or more alternatives in terms of both the costs and effectiveness involved. CEA provides a systematic approach for balancing resource implications (cost) against results (effectiveness) of alternatives and is preferable to other approaches such as “gut feelings”, “what we have always done”, or “educated guesses” ( Drummond, Sculpher, Torrance, O'Brien, & Stoddart, 2005 ). The results of CEA provide decision makers with information on costs, effectiveness, and the relationship between the two (i.e., the value attained).

Conducting a CEA is a complex and multifaceted undertaking. The process can be broken into five key steps ( Bensink, Scuffham,& Smith 2012 ): (a) formulate the research question to be answered, (b) define and measure the resources used and consumed, and then assign costs, (c) define and measure effectiveness, (d) complete incremental analysis including estimates of uncertainty, and (e) present and interpret results.

Formulate the research question

This first step is critical because it determines the foundation of the methods to be used in the analysis and the resulting evidence provided. The patient, intervention, comparator, and outcome (PICO) structure ( Centre for Evidence-Based Medicine, 2009 ), with important information relating specifically to economic evaluation added to the clinical research question, provides a single comprehensive statement that captures the key components of the analysis ( Bensink et al., 2012 ). Economic information added to the clinical research question includes: (a) the economic perspective of the analysis, (b) the economic decision maker that the evidence is directed toward, and (c) the explicit focus on cost effectiveness versus clinical effectiveness as the outcome of interest.

Define and measure resources used/consumed and assign costs

Including the economic perspective and information on the economic decision maker in the research question has important implications for the scope of the data collection required. As recommended by the United States Preventive Services Task Force (USPSTF) Panel on Cost Effectiveness in Health and Medicine ( Gold, Siegel, Russell, & Weinstein, 1996 ), a broad societal perspective should be used to capture all of the anticipated and unanticipated impacts of the intervention(s) under evaluation. The USPSTF outlines four specific areas: (a) the health care resources used and/or consumed, including those required to provide the intervention; (b) the non-health care resources used and/or consumed by patients to receive care; (c) patient time to access care, and (d) the resources provided by family caregivers. Measuring the use of these resources should be undertaken using a combination of patient interviews, chart reviews, tracking logs and potentially hospital bills or claims data (depending on availability) ( Ramsey et al., 2005 ).

Once the relevant resources have been identified, they need to be valued based on credible sources. For health care resources used and/or consumed, credible sources in the United States include the Healthcare Cost and Utilization Project ( Steiner, Elixhauser, & Schnaier, 2002 ) and the Diagnosis Related Group Weights and Physician Fee Schedules ( Centers for Medicare and Medicaid Services, 2012 ). For context specific resources, additional information from secondary hospital and clinic financial systems can be used where available ( Ramsey et al., 2005 ). For items like patient and caregiver time, age- and sex-adjusted national wage rates can be used ( Weinstein, Siegel, Gold, Kamlet, & Russell, 1996 ).

It is essential to provide the decision maker specified in the research question with information relevant to their specific decision-making context, measuring the disaggregate components of the resources involved, so results from alternate perspectives, such as health care system and patient/family perspectives, can be presented in the analysis ( Drummond et al., 2005 ).

Define and measure effectiveness

Because CEA provides evidence to decision makers who are most likely considering the impact of a wide range of alternative uses of scarce health care resources, CEA requires looking at effectiveness in a way that can be compared across many different diseases, patient groups, interventions, therapies, and approaches. Disease specific measures cannot be used to compare the effectiveness of all possible uses of the resources available to decision makers. Although not a perfect measure ( Nord, Daniels, & Kamlet, 2009 ), quality-adjusted life years (QALYs) is the currently accepted measure of effectiveness for CEAs ( Drummond, et al., 2005 ; Gold, et al., 1996 ; Weinstein, Torrance, & McGuire, 2009 ). The QALYs variable combines both quality and quantity of life information into one common measure that can be used to compare very different interventions.

While there are a number of ways to obtain information for the calculation of QALYs, the use of multiattribute health status classification systems with preference scores has gained increasing popularity with researchers over time. Ease of use and the minimization of participant burden are some of the key factors in this trend. For example, the Health Utilities Index Version 3 (HUI 3) asks patients to rate their current health status across eight attributes: vision, hearing, speech, ambulation, dexterity, emotion, cognition, and pain ( Feeny, Furlong, Boyle, & Torrance, 1995 ; Furlong, Feeny, Torrance, & Barr, 2001 ). Responses are then valued using a scoring and health state preferences algorithm. The resulting utility scores reflect the quality of life of patients on a scale from 0 = dead to 1 = perfect health and can be used to calculate QALYs.

Complete incremental analysis including estimates of uncertainty

After the collection and valuation of cost and effectiveness data, the next step in a CEA is analysis. The arithmetic mean cost for patients in intervention and control groups is estimated followed by an incremental analysis of the arithmetic mean difference in cost between groups. From a societal perspective, this provides a summary estimate of the average net impact of the intervention on total per patient cost. An indication of the uncertainty surrounding these estimates is provided by reporting means with 95% confidence intervals. A p -value should also be reported for the incremental analysis in trial-based evaluations ( Glick, Doshi, Sonnad, & Polsky, 2007 ).

While other statistical measures can be used to characterize these estimates, the arithmetic mean is the important statistic in CEA. This is due to CEA's unique budgetary and societal perspectives ( Thompson & Barber, 2000 ). This can present analytic challenges as cost data are generally skewed with a long right tail. Guidance recommends completing simple univariate analysis first (e.g., independent samples t -tests when a new treatment is compared with usual care), followed by multivariable analysis using techniques such as the generalized linear model if the distributional properties of the data are an issue ( Glick et al., 2007 ). Similarly, information from the QALY information collected from patients is used to estimate the arithmetic mean for patients in each group along with the difference between means and the probability associated with this difference compared to a hypothesis of no difference.

Estimates of the arithmetic mean differences in cost (Δ c ), relative to the arithmetic mean difference in QALY effectiveness (Δ e ), are then compared to produce an incremental cost effectiveness ratio (ICER) such that ICER = Δ c / Δ e . The ICER provides information on the value provided by the new intervention compared to current usual care. The metric of value is the average cost needed to produce an average gain of one quality-adjusted life year ($ / QALY).

As with the analysis of cost and effectiveness, the uncertainty associated with the ICER (the joint distribution of uncertainty surrounding cost and QALY estimates) is also included using a 95% confidence interval. A number of analytic techniques that can be used, including the commonly implemented bootstrap percentile method ( Briggs, Wonderling, & Mooney, 1997 ; Polsky, Glick, Willke, & Schulman, 1997 ).

Present and interpret results

Results are presented on the cost effectiveness plane ( Black, 1990 ) to provide a graphical summary of the joint distribution of costs and effectiveness along with associated uncertainty in estimates ( Figure 1 ). Uncertainty in ICER results should also be characterized using willingness-to-pay (WTP) thresholds and cost effectiveness acceptability curves (CEACs) ( Fenwick & Byford, 2005 ). This approach uses a pre-defined definition of value, the WTP threshold (e.g., $50,000 or $100,000 per QALY), to guide decision making ( Figure 2 ). Alternatives that cost less than the threshold are considered cost effective; those over the threshold are not. A CEAC provides information on the probability that the alternative under evaluation is cost effective given the underlying uncertainty in ICER estimates.

The four quadrants of the cost effectiveness plane. The four quadrants of the cost effectiveness plane provide information on the joint distribution of costs and effects. Quadrant III results show a new option that should be adopted as it is less costly and more effective than usual care. Quadrant II results below the cost effectiveness threshold should be adopted; those above should not as they exceed the predefined threshold (e.g., $50,000 or $100,000 per QALY). Results in quadrant IV could theoretically have a similar threshold if there is a willingness to accept decreased effectiveness to reduce cost, but in practice, a less effective option is not adopted. Adapted from “The CE Plane: A graphic Representation of Cost-Effectiveness” by W.C. Black, 1990 , Medical Decision Making, 10 , 212–214. Copyright 1990, Sage Publications. Used with permission.

Cost effectiveness acceptability curve. This simulated cost effectiveness acceptability curve shows that the probability that the new option is cost-effective, compared to the comparator, is .819 at a willingness-to-pay threshold of $50,000/QALY. The probability at $100,000/QALY is slightly higher, at .832.

Example CEA: Symptom Management Study

The following illustrates the application of these methodological aspects of CEA. The “Symptom Management in Rural Communities” cluster randomized trial currently underway is used as an example.

Study background and objectives

The Office of Rural Health Policy accepts all non-metro counties as rural areas in the United States ( Health Resources and Services Administration, 2013 ). Yet rural residents are more likely than their urban counterparts to be: older; in poorer overall health; suffering from more chronic or serious illnesses and disabilities; uninsured or under-insured; and living in poverty ( Rosenthal & Fox, 2000 ). Although telehealth (the use of information and communication technologies to deliver health care at a distance) is an emerging method of health care delivery that has been found useful and effective in many clinical settings and specialties ( Hersh, Helfand et al., 2002 ; Hersh, Hickam et al. 2006 ), its effectiveness and the associated resource implications for symptom management have yet to be explored. Thus, the basis of the study described here is the evaluation of the effectiveness of a telehealth-enhanced symptom-management intervention among rural health care providers and the patients they care for. Correspondingly, the study is designed to answer the question: for rural-dwelling patients, does a telehealth-enhanced symptom-management intervention provide better pain management than current usual care?

Study design

The study is designed as a cluster randomized trial with a wait-list control group and is conducted with rural providers in the Washington, Wyoming, Alaska, Montana, and Idaho (WWAMI) region. (The study is approved by the institutional review board of the University of Washington.) Eligible providers in each site are those responsible for direct patient care including: physicians, physician assistants, and nurse practitioners. Consenting providers are asked to identify patients under their care who are being seen for chronic pain. Patients who agree to participate in the study are then contacted by phone and provided a description of the study. Two additional inclusion criteria are assessed at this time: those patients score a 3 or higher on a 10-point pain scale and are functionally fluent in English. Eligible patients are then asked to consent to participate in the study before being assigned to the same group as their provider.

Providers randomized to the “integrated symptom management intervention group”, have access to weekly videoconferences with other community providers and university-based pain and symptom management experts to manage cases, engage in evidence-based practice activities, and receive peer support. Providers randomized to the wait-list control group, provide usual care to patients at their specific site (i.e., without evidence-based videoconferencing or peer support activities) until week 12, when they are also given access to the intervention.

The primary outcome measure for the study is pain severity assessed using PainTracker, a web-based patient-reported pain outcomes measurement tool. PainTracker is also used to collect secondary outcome measures including anxiety and depression ( Spitzer, Kroenke, & Williams, 1999 ; Spitzer, Kroenke, Williams, & Lowe, 2006 ), overall quality-of-life (HUI3), as well as fatigue, dyspnea, and constipation. To account for nesting of patients within providers, and providers within study sites, the impact of the intervention on the primary outcome of patient-reported pain management outcomes will be analyzed using a hierarchical linear model (HLM) ( Raudenbush, Bryk, Cheong, & Congdon, 2004 ). The results of this analysis will provide an answer to the study's primary research question.

Integrated cost effectiveness analysis

Given the resource constraints experienced by rural communities ( Baldwin et al., 2006 ; Jukkala, Henly, & Lindeke, 2008 ), the completion of an economic evaluation alongside the primary comparative effectiveness study is particularly compelling. Aligned with the primary study's research question, the economic research question is: from a societal perspective, should rural health care organizations caring for adult patients, invest in telehealth-enhanced symptom management as a cost effective alternative to current usual care?

A societal perspective is taken for the CEA. This includes the resources that will be used/consumed in the four specific areas recommended by the USPSTF ( Table 1 ). The study is also placed in a particular decision-making context, that of the rural health care organizations responsible for the care of adult patients.

Cost components to be included in a societal perspective cost effectiveness analysis

For effectiveness, the HUI 3 was selected due to its: (a) credibility as an established instrument with demonstrated feasibility, reliability, validity, and responsiveness ( Horsman, Furlong, Feeney, & Torrance, 2003 ); (b) coverage of the health attributes likely to be important to the patient population under study (ambulation, emotion, cognition, and pain); and (c) prior use in similar patient populations ( Franks, Hanmer, & Fryback, 2006 ; Lubetkin & Gold, 2002 ; Räsänen et al., 2006 ).

As an adaptation to the multivariate techniques recommended, analysis of differences between cost and effectiveness will use the same multivariate HLM technique being used for the primary study question to account for both the correlation between costs and outcomes and the potential dependence of these data on clustering under the enrolled clinician ( Gomes, Grieve, Nixon, & Edmunds, 2012 ). Numeric results will be presented aggregated and disaggregated from societal, rural health care organization, and patient/family perspectives. Overall results of cost effectiveness will be presented using the cost effectiveness plane and as a cost effectiveness acceptability curve.

Incorporating an analysis of cost effectiveness alongside a comparative effectiveness study adds specific data collection requirements and analytic activities to the primary study. This includes the collection, valuation, and analysis of comprehensive information on the resources used from the recommended societal perspective, as well as information from patients that allows the recommended measure of effectiveness, the QALY, to be calculated. Although these additions, as presented here, may seem relatively straightforward, there are many important decisions to be made and many different facets of any analysis that need to be considered. Including a health economist to study personnel from the beginning and maintaining their involvement throughout a study is essential.

The inclusion of CEA as part of a comparative effectiveness evaluation provides a number of benefits. These include: comprehensive information on the cost of implementing an intervention, the resulting impact of this investment on the total cost of patient care, the cost to patients, the cost to informal caregivers, the effectiveness of the intervention as a means of improving the overall health of the patient population under study, and the value provided by using the new alternative over the currently accepted usual care.

The plan to conduct a comprehensive economic evaluation of a telehealth-enhanced symptom-management intervention among rural patients, from the recommended societal perspective and the composite perspectives this involves, will be valuable to rural provider organizations, patients, their families, and the clinicians, including nurses who care for them. It will also provide important information to decision makers working for public and private health insurance plans especially when considerations of cost effectiveness are increasingly used in the private sector to make coverage and reimbursement policies ( Malone, 2005 ; Neumann, 2004 ; Trice, Devine, Mistry, Moore, & Linton, 2009 ; Weart & Bauman, 2007 ).

Despite the value of this information, it is important to highlight that CEA evidence is not the only information that can or should be used for decision making. CEA provides additional evidence to supplement rather than replace the comparative-effectiveness evidence produced by analysis of primary clinical outcomes. Decision makers also consider other issues such as availability, access and equity. At a time when U.S. health care is moving toward accountable care, the information provided by CEA will be an important additional component of the evidence produced by nursing research.

Acknowledgments

This work was supported by a grant from the National Institutes of Health/National Institute of Nursing Research (R01 NR012450) and the University of Washington Palliative Care Center of Excellence.

The authors have no conflicts of interest to declare.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Cost-Benefit Analysis: A Quick Guide with Examples and Templates

When managing a project, many key decisions are required. Project managers strive to control costs while getting the highest return on investment and other benefits for their business or organization. A cost-benefit analysis (CBA) is just what they need to help them do that. Before we explain how to do a cost-benefit analysis, let’s briefly define what it is.

What Is a Cost-Benefit Analysis?

A cost-benefit analysis (CBA) is a process that’s used to estimate the costs and benefits of projects or investments to determine their profitability for an organization. A CBA is a versatile method that’s often used for business administration, project management and public policy decisions. An effective CBA evaluates the following costs and benefits:

• Direct costs
• Indirect costs
• Intangible costs
• Opportunity costs
• Costs of potential risks
• Total benefits
• Net benefits

These project costs and benefits are then assigned a monetary value and used to determine the cost-benefit ratio. However, a cost-benefit analysis might also involve other calculations such as return on investment (ROI), internal rate of return (IRR), net present value (NPV) and the payback period (PBP).

The Purpose of Cost-Benefit Analysis

The purpose of cost-benefit analysis is to have a systemic approach to figure out the pluses and minuses of various business or project proposals. The cost-benefit analysis gives you options and offers the best project budgeting approach to achieve your goal while saving on investment costs.

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Cost Benefit Analysis Template

Use this free Cost Benefit Analysis Template for Excel to manage your projects better.

When to Do a Cost-Benefit Analysis

Cost-benefit analysis is a technique that helps decision-makers choose the best investment opportunities in different scenarios. Here are some of the most common applications for a cost-benefit analysis in project management.

Cost Benefit Analysis & Feasibility Studies

A feasibility study determines whether a project or business initiative is feasible by determining whether it meets technical, economic, legal and market criteria.

Cost Benefit Analysis & Business Requirements Documents

A cost-benefit analysis should be included in a business requirements document , a document that explains what a project entails and what it requires for its successful completion.

Cost Benefit Analysis & Government Projects

Government projects also require conducting a cost-benefit analysis. However, in these types of projects, decision-makers must not only focus on financial gain, but rather think about the impact projects have on the communities and external stakeholders who might benefit from them.

Keeping track of project costs is easier with project management software. For example, ProjectManager has a sheet view, which is exactly like a Gantt but without a visual timeline. You can switch back and forth from the Gantt to the sheet view when you want to just look at your costs in a spreadsheet. You can add as many columns as you like and filter the sheet to capture only the relevant data. Keeping track of your costs and benefits is what makes a successful project. Get started for free today.

How to Do a Cost-Benefit Analysis

According to the Economist , CBA has been around for a long time. In 1772, Benjamin Franklin wrote of its use. But the concept of CBA as we know it dates to Jules Dupuit, a French engineer, who outlined the process in an article in 1848.

Since then, the CBA process has greatly evolved. Let’s go through this checklist to learn how to do a basic cost-benefit analysis using the cost-benefit ratio and present value formulas:

1. What Are the Project Goals and Objectives?

Create a business case for your project and state its goals and objectives.

2. Review Historical Data

Before you can know if a project proposal might be valuable, you need to compare it to similar past projects to see which is the best path forward. Check their success metrics such as their return on investment, internal rate of return, payback period and benefit-cost ratio.

3. Who Are the Stakeholders?

List all stakeholders in the project. They’re the ones affected by the costs and benefits. Describe which of them are decision-makers.

4. What Are the Project Costs and Benefits?

Estimate the future value of your project costs and benefits and think about all the non-financial benefits that a project proposal might bring

The process can be greatly improved with project management software. ProjectManager has one-click reporting that lets you can create eight different project reports. Get data on project status, variance and more. Reports can be easily shared as PDFs or printed out for stakeholders. Filter any report to display only the data you need at the time.

5. Define a Project Timeframe

Look over the costs and benefits of the project, assign them a monetary value and map them over a relevant time period. It’s important to understand that the cost-benefit ratio formula factors in the number of periods in which the project is expected to generate benefits.

6. What Is the Rate of Return?

As explained above, the rate of return is used to calculate the present values of your project’s costs and benefits, which are needed to find the cost-benefit ratio.

Free Cost-Benefit Analysis Template

Use this Excel template to put what you’ve learned into practice. This free cost-benefit analysis template helps you identify quanitative costs and benefits, as well as qualitative costs and benefits, so you can appreciate the full impact of your project. Download yours today.

What Is the Cost-Benefit Ratio?

The cost-benefit ratio, or benefit-cost ratio, is the mathematical relation between the costs and financial benefits of a project. The cost-benefit ratio compares the present value of the estimated costs and benefits of a project or investment.

Cost-Benefit Ratio Formula

This is a simplified version of the cost-benefit ratio formula.

Cost-Benefit Ratio= Sum of Present Value Benefits / Sum of Present Value Costs

Here’s how you should interpret the result of the cost-benefit ratio formula.

• If the result is less than 1: The benefit-cost ratio is negative, therefore the project isn’t a good investment as its expected costs exceed the benefits.
• If the result is greater than 1: The cost-benefit ratio is positive, which means the project will generate financial benefits for the organization and it’s a good investment. The larger the number, the most benefits it’ll generate.

Present Value Formula

The present value of a project’s benefits and costs is calculated with the present value formula (PV).

PV = FV/(1+r)^n

• FV: Future value
• r= Rate of return
• n= Number of periods

We’ll apply these formulas in the cost-benefit analysis example below. Our free cost-benefit analysis template can help you gather the information you need for the cost-benefit ratio analysis.

Cost-Benefit Analysis Example

Now let’s put the formulas reviewed above into practice. For our cost-benefit analysis example, we’ll think about a residential construction project, the renovation of an apartment complex. After using project cost estimation methods and evaluating past-project data, the apartment management company concludes that:

• The project costs are $65,000. They’re paid upfront, so it’s not necessary to calculate their present value
• The project is expected to generate $100,000 in profit for the next 3 years
• The rate of return based on inflation data is 2%

Next, we’ll need to calculate the present value of the benefits expected to be earned in the future using the present value formula:

PV= ($100,000 / (1 + 0.02)^1) + ($100,000 / (1 + 0.02)^2) + ($100,000 / (1 + 0.02)^3)=$288,000

Now we need to use this cost value to find the cost-benefit ratio. Here’s how it would be calculated in this case:

Cost-Benefit Ratio: 288,000/65,000= 4.43

Since we obtained a positive benefit-cost ratio, we can conclude that the project will be profitable for this company. This result implies that the project will generate about $4,43 dollars per each $1 spent to cover expenses .

This is a simple cost-benefit analysis that relies on the cost-benefit ratio to establish the profitability of this project. In other scenarios, you might also need to calculate the return on investment (ROI), internal rate of return (IRR), net present value (NPV) and the payback period (PBP). In addition, it’s advisable to conduct a sensitivity analysis to evaluate different scenarios and how those affect your cost-benefit analysis.

Capture all the costs and benefits with project management software. But unlike many apps with inferior to-do lists, ProjectManager has a list view that is dynamic. It adds priority and customized tags you can assign team members to own each item. Our online tool automatically tracks the percentage complete for each item in real time. All the data you collect in our list view is visible throughout the tool. Regardless of the view, they all update live and they’re ready for you to utilize.

How Accurate Is Cost-Benefit Analysis?

How accurate is CBA? The short answer is it’s as accurate as the data you put into the process. The more accurate your estimates, the more accurate your results.

Some inaccuracies are caused by the following:

• Relying too heavily on data collected from past projects, especially when those projects differ in function, size, etc., from the one you’re working on
• Using subjective impressions when you’re making your assessment
• Improperly using heuristics (problem-solving employing a practical method that is not guaranteed) to get the cost of intangibles
• Confirmation bias or only using data that backs up what you want to find

Cost-Benefit Analysis Limitations

Cost-benefit analysis is best suited to smaller to mid-sized projects that don’t take too long to complete. In these cases, the analysis can help decision-makers optimize the benefit-cost ratio of their projects.

However, large projects that go on for a long time can be problematic in terms of CBA. There are outside factors, such as inflation, interest rates, etc., that impact the accuracy of the analysis. In those cases, calculating the net present value, time value of money, discount rates and other metrics can be complicated for most project managers .

There are other methods that complement CBA in assessing larger projects, such as NPV and IRR. Overall, though, the use of CBA is a crucial step in determining if any project is worth pursuing.

Templates to Help With Your Cost-Benefit Analysis

As you work to calculate the cost-benefit analysis of your project, you can get help from some of the free project management templates we offer on our site. We have dozens of free templates that assist every phase of the project life cycle. For cost-benefit analysis, use these three.

RACI Matrix Template

One of the steps when executing a cost-benefit analysis includes identifying project stakeholders. You need to list those stakeholders, but our free RACI matrix template takes that one step further by outlining who needs to know what. RACI is an acronym for responsible, accountable, consulted and informed. By filling out this template, you’ll organize your team and stakeholders and keep everyone on the same page.

Project Budget Template

You can’t do a cost-benefit analysis without outlining all your expenses first. That’s where our free project budget template comes in. It helps you capture all the expenses related to your project from labor costs, consultant fees, the price of raw materials, software licenses and travel. There’s even space to capture other line items, such as telephone charges, rental space, office equipment, admin and insurance. A thorough budget makes for a more accurate cost analysis.

Project Risk Register Template

You have your stakeholders identified and your budget outlined, but there’s always the unknown to consider. You can’t leave that up to chance: you must manage risk, which is why our free project risk register is so essential. Use it to outline inherent project risks. There are places to list the description of the risk, its impact, the level of risk and who’s responsible for it. By maintaining a risk register, you can control the project variables and make a better cost-benefit analysis.

Make Any Project Profitable With ProjectManager

No matter how great your return on investment might be on paper, a lot of that value can evaporate with poor execution of your project. ProjectManager is award-winning project management software with the tools you need to realize the potential of your project. First, you need an airtight plan.

Planning on Gantt Charts

Our online Gantt charts have features to plan your projects and organize your tasks, so they lead to a successful final deliverable. If things change, and they will, the Gantt is easy to edit, so you can pivot quickly.

Resource Management Tools

Another snag that can waylay a project is your resources. ProjectManager has resource management tools that track your materials, supplies and your most valuable resource: the project team. If they’re overworked, morale erodes and production suffers.

The workload page on ProjectManager is color-coded to show who is working on what and gives you the tools to reassign to keep the workload balanced and the team productive.

Real-Time Cost Tracking

The surest way to kill any project is for it to bleed money. ProjectManager lets you set a budget for your project from the start. This figure is then reflected in reports and in the charts and graphs of the real-time dashboard , so you’re always aware of how costs are impacting your project. ProjectManager has the features you need to lead your project to profitability.

Cost benefits analysis is a data-driven process and requires project management software robust enough to digest and distribute the information. ProjectManager is online project management software with tools, such as a real-time dashboard, that can collect, filter and share your results in easy-to-understand graphs and charts. Try it today with this free 30-day trial.

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Cost-Benefit Analysis Research Paper

View sample economics research paper on cost-benefit analysis. Browse economics research paper topics for more inspiration. If you need a thorough research paper written according to all the academic standards, you can always turn to our experienced writers for help. This is how your paper can get an A! Feel free to contact our writing service for professional assistance. We offer high-quality assignments for reasonable rates.

Infrastructure, education, environmental protection, and health care are examples of goods and services that in many circumstances are not produced by competitive private companies. Instead, decision making regarding investments and regulations is often made by politicians or public sector officials. For these decisions to be consistent, rational, and increase welfare, a systematic approach to evaluating policy proposals is necessary. Cost-benefit analysis is such a tool to guide decision making in evaluation of public projects and regulations. Cost-benefit analysis is a procedure where all the relevant consequences associated with a policy are converted into a monetary metric. In that sense, it can be thought of as a scale of balance, where the policy is said to increase welfare if the benefits outweigh the costs. Cost-benefit analysis of a proposed policy may be structured along the following lines:

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• Identify the relevant population of the project. For a cost-benefit analysis of a single individual or for a firm, this is not a problem. But in a societal cost-benefit analysis, we need to consider how to define society. A common approach is to consider the whole country as the relevant population. This is reasonable given that most public policies are financed at the national level. Another approach is to conduct a cost-benefit analysis specifying costs and benefits using different definitions of the relevant population—for example, including benefits and costs of a neighboring country in the analysis.
• Specify all the relevant benefits and costs associated with the policy. The aim with a cost-benefit analysis is to include all relevant costs and benefits with a policy. Based on the definition of the population (Step 1), every aspect that individuals in this population count as a benefit or a cost should be included in the analysis. For some benefits and costs of a policy, this may be an easy task—for example, 2,000 hours of labor input are required next year to build a road. But there are also more difficult phases in this step of a cost-benefit analysis; some examples include (a) a new infrastructure investment may have ecological consequences that are difficult to estimate and (b) regulating speed limits in a major city may have beneficial health effects due to decreases in small hazardous particles. For the economist or analyst, this step often consists of asking the right questions and gathering the necessary information from the literature, professionals, or both.
• Translate all the benefits and costs into a monetary metric. A cost-benefit analysis requires that the different consequences are expressed in an identical metric. For simplicity, we use a monetary metric ($ or €, etc.). Consider the example of an investment in a new road. The costs for the labor input can be valued by the wages (plus social fees, etc.), and the use of equipment may be estimated by the machine-hour cost. For benefits of, for example, increased road safety, decreased travel time, and decreased pollution level, there are no market prices to use; instead, weights and estimates are necessary to translate these benefits into a monetary metric. If this would not be possible with all relevant consequences, they should at least be included as qualitative terms in the evaluation. In the Valuation of Nonmarket Goods section, giving nonmarket goods a monetary estimate is discussed.
• If benefits and costs arise at different times, convert them into present value using an appropriate social discount rate. Most people prefer a benefit today to a benefit in one year. There are several reasons for this, one being that no one knows for sure whether he or she will be alive in a year. Another reason may be that, over a longer time horizon, people expect their incomes to increase in the future. If an extra dollar has a larger utility benefit to a less rich individual, that individual would prefer to consume when he or she has less money (today) rather than when he or she has more (e.g., in 5 years). Also, from an opportunity-cost approach, $100 that is not consumed today can be invested in a bond, and in a year from now, it may be worth $105, implying higher consumption in one year. In a cost-benefit analysis, economists therefore (generally) do not treat benefits and costs that occur at different times as equal; rather, they translate all benefits and costs into a present value. Choosing an appropriate social discount rate is, however, a complicated task and will often have major effects on the results of the evaluation. In the Discounting section, this is discussed in more detail.
• Compare the net present value of benefits and costs. When the present value of benefits (PVB) and costs (PVC) has been calculated, what remains is to calculate the net present value (NPV). The policy is said to increase social welfare if the net present value is positive—that is, PVB- PVC> 0. It is also common to express the comparison as the benefit-cost ratio—that is, PVB / PVC, which gives the relative return of the investment. If the ratio is greater than 1, the policy increases social welfare.
• Perform a sensitivity analysis to see how uncertain the benefit-cost calculation may be and give a policy recommendation. A cost-benefit analysis will have several uncertainties regarding the outcome. It is most often not reasonable to show only one point estimate of the evaluation. There are often uncertainties regarding both parameter values (such as the monetary estimates of, e.g., increased safety or environmental pollution) and more technical issues, such as the economic lifetime of a new road, which is the period during which it retains its function. These uncertainties need to be explicitly modeled. The final step in a cost-benefit analysis is to give a policy recommendation based on the result of the evaluation as well as the uncertainties associated with the result.

What Do We Mean by Social Welfare?

The aim with a cost-benefit analysis is to evaluate the welfare effect of a policy. This requires a definition of what is meant by social welfare in an economic framework. The meaning of a welfare improvement is, in its most restricted view, formulated in the Pareto criterion. The Pareto criterion states that a policy that makes at least one individual better off without making any other individual worse off is a Pareto-efficient improvement and increases welfare. However, the Pareto criterion is generally useless as a definition for welfare improvements in a real-world application, because more or less all policies make at least someone worse off. It may also be criticized on ethical grounds; consider a vaccine that would save 1 million lives in sub-Saharan Africa but required a €1 tax on someone (a nonaltruistic individual) in Europe or the United States. According to the Pareto criterion, this policy could not be said to increase welfare, but this conclusion would violate the moral values of most individuals.

As a development to the Pareto criterion, the Kaldor-Hicks criterion was formulated, and it may be seen as the foundation of practical cost-benefit analysis. The Kaldor-Hicks criterion is less restrictive than the Pareto criterion and may be interpreted such that a policy is considered to increase welfare if the winners from a policy are made so much better off that they can fully (hypothetically) compensate the losers and still gain from the policy (potential Pareto improvement). This implies that every Pareto improvement is a Kaldor-Hicks improvement, but the reverse is not necessarily true. The compensation from the winners to the losers is a hypothetical test, and the compensation does not need to be enforced in reality (which distinguishes it from the Pareto criterion). In the example above, the vaccine to save 1 million lives would pass the Kaldor-Hicks criterion, if those who were saved would be hypothetically willing to compensate the European taxpayer with a payment of at least €1. Cost-benefit analysis is a test of the Kaldor-Hicks criterion, translating all the benefits and the costs into a monetary metric. The Kaldor-Hicks criterion also implies that we need to collect information only on aggregate benefits and costs of a policy; we do not need to bother ourselves determining which individuals are actually winning or losing from a policy.

Valuing Benefits and Costs

Performing a cost-benefit analysis of a policy requires that all benefits and costs of the policy be summed up in monetary terms. There are two principal ways of measuring the sum of benefits in a cost-benefit analysis: willingness to pay (WTP) and willingness to accept (WTA). Both WTP and WTA are meant to value how much a certain policy is worth to an individual in monetary terms. The WTP of a policy may be characterized as an individual’s maximum willingness to pay, such that he or she is indifferent to whether the policy is implemented— that is, if it is implemented, utility is the same after the policy as before the policy. The WTA of a policy may instead be characterized as the lowest monetary sum that an individual accepts instead of having the investment implemented—that is, utility is the same when receiving the money as it would have been if the investment had been implemented. WTP and WTA for a policy are expected to differ (WTP < WTA) because of the income effect. Robert D. Willig (1976) shows, using plausible assumptions, that WTP and WTA should not differ from each other by more than a few percentage points. But a lot of research has documented that WTP and WTA usually differ a lot for the same policy, with WTA being significantly higher than WTP. Several hypotheses have been put forward trying to explain this discrepancy, one frequent hypothesis being the existence of an endowment effect (Kahneman, Knetsch, & Thaler, 1990). An endowment effect states that individuals value a good significantly more once they own it, which would create a gap between WTP and WTA for an identical good. In several circumstances, it is often more problematic to estimate WTA for a good, especially in valuation of nonmarket goods, implying that it is more common to use the concept of WTP in cost-benefit analyses.

The cost of a certain policy is based on the opportunity cost concept—that is, the value of the best alternative option that the resources could be devoted to instead. The opportunity cost is derived based on companies’ marginal cost curve—that is, the cost that is associated with increasing output with one unit. This should not be equalized to accounting costs, which do not necessarily tell us the economic cost of an activity. As an example, going to a 2-year MBA program has some direct costs (accounting costs), such as tuition fees, books, and travel costs to attend lectures, but also indirect costs, such as the money that one could earn in a job if not attending the MBA program. The economic cost of an activity is the sum of direct and indirect costs.

Valuation of Market Goods

To estimate benefits and costs of a policy, the natural starting point is to examine whether market prices exist that may be used. If the market is characterized by perfect competition, or a reasonable approximation of perfect competition, and no external effects exist, the market price can give us information about the willingness to pay for a marginal change of a good. For example, if we need to use production factor X for a certain investment and our demand for X will not affect the market price, we can use the market price as a cost measure. The total cost of the production factor in the cost-benefit analysis is, then, the market price multiplied by the number of units used. However, if the policy will also affect the market equilibrium, we cannot simply use the market price in our analysis. Figure 1 shows the difference.

Initial market equilibrium is at price P0 and quantity Q0. Imagine that a new policy will lead to a decrease in the market price to P1, which increases quantity consumed to Q1. The total benefits of this policy include the increased consumer surplus for the original consumers (rectangular area P0P,AC) as well as the benefit of the new consumers (triangle area ABC). Hence, the total benefit may be represented by the area P0P,AB, which shows that when a policy has a nonmarginal effect on the market price, we cannot simply use the prepolicy market price in a cost-benefit analysis.

Figure 1.   Measuring Benefits and Costs for Nonmarginal Changes in Quantity

Other problems to note when using market data as information on prices in a cost-benefit analysis include market imperfections, such as tax distortions and externalities. The existence of taxes implies that there are several market prices, including or excluding taxes. An easy rule of thumb is to calculate prices including taxes, which implies that prices are expressed as consumer prices rather than producer prices. This implies that, for example, labor costs should be calculated as gross wages plus other social benefits or taxes that the consumer (or employer) has to pay. There is also another important effect of taxes that needs to be considered. Usually, cost-benefit analyses are performed for public projects, which often are paid for by taxes that lead to distortions in the economy. Distortions are created because not all activities are taxed, such as leisure. This implies that taxes on labor incomes change the relative prices between labor and leisure and lead to economic inefficiency. The distortion should normally be included in a cost-benefit analysis. As an example, in Swedish cost-benefit analysis, the recommendation is to include a distortion cost of 30% of direct costs (including taxes).

A final complicating note is that theoretically it may be that the correct benefit measure is the option price of a policy, which consists of the expected surplus (as outlined above) as well as the option value of a policy. Option value is the value that individuals are willing to pay, above the expected value of actually consuming the good, to have the option of consuming the good at some point in time (Weisbrod, 1964). For example, investing in a new national park includes the expected surplus of actually going to the park for the visitors. But it may also include a willingness to pay reflecting that the national park provides an option to go there, even if an individual will never actually go. In practical applications, it is common to exclude option value in the benefit calculations. There are several arguments for this; for example, it is difficult to measure and separate option values from other types of values or attitudes that may not be relevant, such as non-use values (non-use value refers to value an individual may place on, e.g., saving the rain forest in a specific region in South America, even if the individual knows that he or she will never go there—an intrinsic value). In addition to option value, sometimes it is also argued that a quasi-option value (sometimes referred to as real option) should be included in a project evaluation. The quasioption value refers to the willingness to pay to avoid an irreversible commitment to the project right now, given expectations of future growth in knowledge relevant to the consequences of the project. It is not particularly common to include quasi-option value in cost-benefit analyses.

Valuation of Nonmarket Goods

A common difficulty with a cost-benefit analysis is the fact that the policy to be evaluated includes a nonmarket good that is publicly provided. This implies that there are no market data to use. Examples of nonmarket goods that are common in cost-benefit analyses of public policy are values of safety, time, environmental goods, and pollution. Generally, there are two main approaches available for estimating monetary values of nonmarket goods: (1) revealed preference (RP) methods and (2) stated preference (SP) methods. RP methods use actual behavior and try to estimate implicit values of WTP or WTA. SP methods use surveys and experiments where individuals are asked to make hypothetical choices between different policy alternatives. Based on these choices, the researcher can estimate WTP or WTA.

Revealed Preference Method

Revealed preference techniques can be used to elicit willingness to pay when there is market information about behavior that at least indirectly includes the good that the analyst is interested in evaluating.

One revealed preference approach is hedonic pricing (Rosen, 1974). Imagine that we would like to estimate the willingness to pay to avoid traffic noise; we may be able look at the housing market in a city to accomplish this. The price of a house depends on many different characteristics: size, neighborhood, number of bedrooms and bathrooms, construction year, and so on. But another important determinant may be the level of noise—that is, a house located close to a heavily trafficked highway will generally be less expensive than an identical house located in a noise-free environment. The hedonic pricing approach uses this intuition and performs a regression analysis where the outcome is the market value of a house including several relevant characteristics as determinants of the house price (including the noise level, measured in decibels). The results from such a statistical analysis can in a second step tell us the impact of the noise level on the market price, holding other important factors constant. For example, Nils Soguel (1994) uses data on monthly rent for housing in the city of Neuchatel in Switzerland and included factors measuring the structure and condition of the building, several apartment-specific factors, and the location of the property. Based on a hedonic pricing approach, it shows that a one-unit increase in decibel led to a reduction in rents by 0.91%. Hence, using this approach, it is possible to estimate the economic value of noise.

Another revealed preference approach is the travel-cost method (see, e.g., Cicchetti, Freeman, Haveman, & Knetsch, 1971). This method uses the fact that individuals can reveal the value of a good by the amount of time they are willing to devote to its consumption. For example, if an individual pays $10 for a train ride that takes 30 minutes to visit a national park, we can use this information to indirectly estimate the lower bound of the value that the individual assigns the park. If the value of time for the individual is $20/hour, the individual is at least willing to spend the train fare of $10 plus $20 for the pure time cost (60 minutes back and forth) to visit the park—that is, a total sum of $30. Using this approach on a large set of individuals (or based on average data from different cities or regions), it is possible to estimate the total consumer surplus associated with the national park.

Stated Preference Method

In many cases, it may not be possible to use revealed preference methods. Further, it should be noted that revealed preference methods assume that individuals (on average) have reasonable knowledge of different product characteristics for a hedonic pricing approach to give reliable estimates. In many cases, this condition may not be fulfilled. A possible option is then to turn to stated preference methods, which are based on hypothetical questions designed such that individuals should reveal the value they would assign to a good if it were implemented in the real world (Bateman et al., 2004). There are two common approaches in the stated preference literature: (1) contingent valuation (CV) and (2) choice modeling (CM). A CV survey describes a scenario to the respondent—for example, a proposed policy of investing in a new railway line— and asks the individual about his or her willingness to pay. A common recommendation is to use a single dichotomous-choice question—that is, respondents are asked whether they would be willing to pay $X for a project—and use a coercive payment mechanism (e.g., a tax raise) for the new public good (Carson & Groves, 2007). The cost of the project is varied in different subsamples of the study, which makes it possible to estimate the willingness to pay (demand curve) for the project using econometric analysis.

In a CM framework, a single respondent is asked to choose between different alternatives where different characteristics of a specific good are altered. For example, the respondent may choose between Project A, Project B, and status quo. Project A and Project B may be two different railway line investments that differ with respect to commute time, safety, environmental pollution, and cost. Using econometric techniques, it is possible to estimate the marginal willingness to pay for all these different attributes using the choices made by the respondents.

Stated preference methods have the advantage that it is possible to directly value all types of nonmarket goods, but the reliability of willingness to pay estimates is also questioned by many economists. Problems include individuals’ tendency to overestimate their willingness to pay in a hypothetical scenario compared to a real market scenario, referred to as hypothetical bias (Harrison & Rutstrom, 2008). There are also many studies that highlight the problem of scope bias (Fischhoff & Frederick, 1998), which refers to the fact that willingness to pay is often insensitive to the amount of goods being valued—for example, willingness to pay is the same for saving one whale as for saving one whale and one panda.

Application: The Value of a Statistical Life

Many cost-benefit analyses concern public policies with effects on health risks (mortality and morbidity risks). Environmental regulation and infrastructure investment are two examples where policies often have direct impacts on mortality risks, morbidity risks, or both. Hence, we need some approach to monetize health risks. In the United States, an illustrative example can be found in the evaluation of the American Clean Air Act by the Environmental Protection Agency, where 80% of the benefits were made up of the value of reduced mortality risks (Krupnick et al., 2002). In a European example (from Sweden), cost-bene-fit analyses of road investments show that approximately 50% of the benefits consist of mortality and morbidity risk reductions (Persson & Lindqvist, 2003).

In the literature of the last 20 to 30 years, the concept used to monetize the benefit of reduced mortality risk is the value of a statistical life (VSL). It may be described in the following way:

Suppose that you were faced with a 1/10,000 risk of death. This is a one-time-only risk that will not be repeated. The death is immediate and painless. The magnitude of this probability is comparable to the annual occupational fatality risk facing a typical American worker and about half the annual risk of being killed in a motor vehicle accident. If you faced such a risk, how much would you pay to eliminate it? (Viscusi, 1998, p. 45)

Let us assume that a certain individual is willing to pay $100 to eliminate this risk. Using this information on WTP, the value of a statistical life is then based on the concept of adding up this total willingness to pay for a risk reduction of 1 in 10,000 to 1. Hence, in this example, it implies that the estimate for the value of a statistical life is equal to $100 x 10,000 = $1 million (VSL = WTP / A risk). This implies that a policy that prevents one premature fatality increases social welfare as long as the cost is less than $1 million.

What value should be used in a cost-benefit analysis? There is no market where we explicitly trade with small changes in mortality risks. Rather, researchers have been forced to turn to RP and SP methods to estimate VSL. The most common RP approach has been to use labor market data to estimate the wage premium demanded for accepting a riskier job (hedonic pricing). The idea behind these studies is that a more dangerous job will have to be more attractive in other dimensions to attract competent workers, and one such dimension is higher pay. Hence, by controlling for other important determinants of the wage, it is possible to separate the effect that is due to a higher on-the-job fatality risk. This approach has been particularly popular in the United States; see W. Kip Viscusi and Joseph Aldy (2003) for a survey of several papers using this approach.

SP approaches to estimate VSL are also frequent. Primarily, they have been performed using the contingent valuation approach. For example, a survey might begin with a description of the current state of the world regarding traffic accidents in a certain municipality, region, or country. The respondent might be told that in a population of 100,000 individuals, on average, 5 people will die in a traffic accident the next year. After this description, the respondent might be asked to consider a road safety investment that would, on average, reduce this mortality risk from 5 in 100,000 to 4 in 100,000—that is, 1 fewer individual killed per 100,000 individuals. To elicit the preferences of the respondent, the following question may be asked: Would you be willing to pay $500 in a tax raise to have this traffic safety program implemented? The respondent then ticks a box indicating yes or no. Other respondents are given other costs of the project, which gives the researcher the possibility of estimating a demand curve for the mortality risk reduction.

In the United States, the Environmental Protection Agency recommends a VSL estimate of €6.9 million for cost-benefit analyses in the environmental sector. In Europe, for the Clean Air for Europe (CAFE) program, a VSL (mean) of €2 million (approx. $2.7 million) is suggested (Hurley et al., 2005). Theoretically, higher income and higher baseline risk should be associated with a higher VSL (although this can hardly explain the large differences between the estimates used by the United States and the European Union). In the transport sector, there are also international differences. Among European countries, Norway recommends a VSL estimate for infrastructure investments of approximately €2.9 million; the United Kingdom, €1.8 million; Germany, €1.6 million; Italy, €1.4 million; and Spain, €1.1 million (HEATCO, 2006).

For many individuals, it is offensive to suggest that the value of life should be assigned a monetary value, and there is some critique from the research community (Broome, 1978). However, it needs to be acknowledged that in estimating WTP for small mortality risk reductions for each individual (hence the term statistical life), no one is trying to value the life of an identified individual. Moreover, these decisions have to be made, and we make them daily on an individual basis. Public policy decision making on topics that have impacts on mortality risks will always implicitly value a prevented fatality. Using the concept VSL in cost-benefit analysis, economists are merely trying to make these decisions explicit and base them on a rational decision principle.

Discounting

As stated in the introduction, benefits and costs associated with a policy that occur at different times need to be expressed in a common metric. This metric is the present value of benefits and the present value of costs. Practically, discounting into present value is calculated as PV = Bt / (1 + SDR)t, where PV is the present value of a benefit (Bt) occurring in year t in the future. SDR is the social discount rate. For example, with a social discount rate of 3%, a benefit of $100 occurring in 5 years has a present value of $100 / (1 + 0.03)5 = $86.26. Traditionally, there have been two main approaches to choosing an appropriate social discount rate: (1) the social opportunity rate cost of capital, and (2) social time preference rate. The former can be seen as the opportunity cost of capital used for a certain policy. Imagine that a road safety investment has a cost of $100; this money could instead be placed in a (more or less) risk-free government bond at a real interest rate of perhaps 5%. This would be the opportunity cost of the capital used for the public policy. The social time preference rate approach can be formulated as in the optimal growth model (Ramsey, 1928) outlining the long-run equilibrium return of capital: SDR = p + m x g, where p is the pure time preference of individuals, p is the income elasticity, and g is the growth rate of the economy. This captures both that individuals tend to receive $1 today rather than in a year (p), and it reflects that as individuals grow richer, each additional $1 is worth less to them (m).

The actual discount rate used in economic evaluation often has a major impact on the result. Consider Table 1, which shows the present value of $1 million in 10, 30, 50, and 100 years in the future with discount rates of 1%, 3%, 5%, and 10%. As an example, with a discount rate of 1%, the present value of $1,000,000 occurring in 10 years is $905,287. The present value if using a discount rate of 5% is instead $613,913.

Table 1 can be used to show how important the discount rate is for the discussion regarding what to do about global warming. The predicted costs of global warming are assumed to lie quite distantly in the future. The effect of different discount rates will be relatively larger the more distant in the future the benefit or cost will take place. An environmental cost of $1 million occurring in 100 years is equal to only $7,604 in present value if using a discount rate of 5%. If using a discount rate of 1%, it is $369,711. A policy that would be paid for today to eliminate this cost in 100 years would be increasing social welfare if it cost less than $7,604 using the higher discount rate (5%) or would be increasing social welfare if it cost less than $369,711 using the lower discount rate (1%). Hence, it is obvious that the conclusion on how much of current GDP we should spend to decrease costs of global warming occurring in the distant future will be highly dependent on the chosen discount rate used in the cost-benefit analysis.

In 2006, a comprehensive study on the economics of climate change was presented by the British government: the Stern Review (Stern, 2007). The review argues that the appropriate discount rate for climate policy is 1.4%. Stern argues that because global warming is an issue affecting many generations, the pure time preference (p) should be very low (0.1), and he assumes an income elasticity (m) of 1 and a growth rate (g) of 1.3; this implies SDR = 0.1 + 1 x 1.3 = 1.4. This is a relatively low discount rate compared to what most governments recommend for standard cost-benefit analyses around the world for projects with shorter life spans than policies to combat global warming. The Stern Review has also been criticized by other economists, who argue that such a low discount rate is not ethically defensible and has no connection to market data or behavior (Nordhaus, 2007). Weitzman (2007) argues that a more appropriate assumption is that p=2, m = 2, and g = 2, which would give a social discount rate of 6%. The debate about the correct social discount rate has been a very public question in discussions about global warming policy—that is, how much, how fast, and how costly should measures taken today to reduce carbon emissions be?

Table 1.   Present Value of $1 Million Under Different Time Horizons and Discount Rates

There really exists no consensus regarding the correct discount rate, and there probably never will. Different government authorities around the world propose different social discount rates. The European Union demands that cost-benefit analyses be conducted for projects that imply important budget consumption, and the European Commission proposes a social discount rate of 5%. In the so-called Green Book in the United Kingdom, a social discount rate of 3.5% is proposed. In France, the Commisariat Général du Plan proposes a discount rate of 4%. In the United States, there are somewhat different proposals for different sectors, but the Office of Management and Budget recommends a social discount rate of 7% (Rambaud & Torrecillas, 2006). Several of the recommendations are also indicating that the social discount rate should be dependent on the time horizon of the project; in the United Kingdom, the social discount rate is proposed to be 3.5% for year 0 to 30, 3% for year 31 to 75, and decreasing down to 1% for policies with a life span of more than 301 years.

Sensitivity Analysis

There are often large uncertainties in a cost-benefit analysis, regarding parameter estimates of benefits and costs. It has been shown that, especially for large projects, costs are often underestimated and benefits are sometimes exaggerated, making projects look more beneficial than they actually are (Flyvbjerg, Holm, & Buhl, 2002, 2005). These types of uncertainties need to be explicitly discussed and evaluated in the analysis. One common approach to deal with uncertainty in a cost-benefit analysis is to perform sensitivity analyses. There are different approaches regarding how to conduct a sensitivity analysis. Partial sensitivity analysis involves changing different parameter estimates and examines how it affects the net present value of the policy. Examples include using different discount rates and different parameter values of the value of a statistical life. Another approach is the so-called worst- and best-case analysis. Imagine that the benefits are uncertain but that an interval can be roughly estimated—for example, the benefit of improving environmental quality will be in the interval $100,000 to $150,000. A worst-case analysis implies taking the lowest bound of all beneficial parameter estimates. A best-case analysis implies the opposite. These types of sensitivity analyses may be interesting for a risk-averse decision maker and also give information about the lowest benefit (or largest loss) for a given project.

The downside to partial sensitivity analysis and worst-and best-case scenarios is that they do not take all available information about the parameters into consideration. Further, they do not give any information about the variance of the net present value of a project. For example, if two projects give similar net present value, decision makers may be more interested in the project with the lowest variance around the outcome. This requires the use of Monte Carlo sensitivity analysis. This is based on simulations where economists make assumptions about the statistical distribution of different parameters and perform repeated draws of different parameter values, each leading to a different net present value. This can give an overview of the distribution of the uncertainty of the project. A standard approach to visually describe the results from a Monte Carlo sensitivity analysis is to display the results in a histogram that shows mean net present value, sample variance, and standard error.

An Application

To end this overview, a cost-benefit analysis of the Stockholm congestion charging policy is described (Eliasson, 2009). The Stockholm road congestion charging system is based on a cordon around central parts of Stockholm (capital of Sweden), with a road toll between 6:30 a.m. and 6:30 p.m. weekdays (higher charge during peak hours). The aim with the charging system is to reduce congestion and increase the reliability of travel times. Positive effects on safety and the environment are also expected. The cost-benefit analysis has the particular advantage of being based on observed traffic behavior, rather than simulations and forecasts (this is possible because the charging system was introduced during a trial period of 6 months). Using the six steps in a cost-benefit analysis as outlined in the introduction:

• The first step involves defining the relevant population. The Stockholm congestion charging policy is mainly relevant for the population in the region of Stockholm, but because the cost-benefit analysis is based on actual behavior and data, it will therefore include benefits and costs of users of the roads in Stockholm, which will include various types of visitors as well. Hence, the relevant population is all the users of the roads.
• The second step in a cost-benefit analysis is to identify the relevant consequences associated with the policy. The following main benefits are associated with the policy:

(a) reduction in travel times due to decreased congestion, (b) increased reliability in travel times, (c) reductions of carbon dioxide and health-related emissions due to the decrease in traffic volume, and (d) increased road safety due to decrease in traffic volume. It could be hypothesized that the system would have effects on decisions where to locate, the regional economy, and retail sales, but it has been judged that these effects will be very small. Negative effects are (a) investment and startup costs, and (b) yearly operation costs.

• The third step in the cost-benefit analysis is to monetize all the benefits and costs associated with the policy. Table 2 summarizes the consequences and shows their monetary benefits and costs. Some of the smaller benefits and costs in the analysis are not described here; refer to the reference for a more detailed description.

Table 2.   Annual Benefits and Costs of the Stockholm Road Charging System

Table 2 shows the annual benefits and costs of the system. The magnitude of the effects on travel time, standard deviation of travel time, and so on is based on large computer estimations of the traffic measurements on 189 links to calibrate origin-destination (OD) matrices for the case with and without the charging system. The investment cost is not listed in Table 2 but was estimated at 1.9 million SEK.

• The next step consists of calculating the net present value of all benefits and costs based on the annual estimates. It is not obvious which time horizon should be used for the project, but technical data and past experience indicated that it was reasonable to make a conservative assumption that the system would have an economic life span of 20 years. Hence, the benefits and operating costs in year 2, 3, … , 20 have to be discounted to a present value. The Swedish National Road Administration argues that the social discount rate should be 4%. Hence, the present value of the net social benefits in year 20 is 654 / (1.04)20 = 298 million SEK. These calculations are performed for benefits and costs in years 1 through 20.
• Discount all annual benefits and costs to present values, as in Step 4, showing that the total social surplus (after deducting the investment costs) is approximately

6.3 billion SEK (approx. $800 million). Expressing it as a payback estimate, this means that the policy will take 4 years before the investment costs are fully repaid. It is also explicitly discussed that some consequences were deemed too difficult to include in the calculations, such as the effects on noise, labor market, time costs for users, quicker bus journeys, and so on.

• The sixth step in a cost-benefit analysis is to perform a sensitivity analysis. In this aspect, there is little done in the described analysis. One reason for this is that the actual estimates of the consequences as performed using OD matrices are very time consuming, which more or less implies that because of practical limitations, only one main estimation can be performed. A simple sensitivity analysis is performed assuming increasing benefits over the time horizon. But if any improvement to the cost-benefit analysis should be suggested, it would be to conduct a more detailed sensitivity analysis. The quite straightforward conclusion of the cost-benefit analysis, even though it should have included sensitivity analyses to satisfy our full requirements, is that social welfare will increase because of the charging system.

How should we evaluate a proposed public policy or regulation? A cost-benefit analysis is an approach that includes all relevant consequences of a policy and compares, in monetary units, benefits with costs. If benefits outweigh the costs, the policy is said to increase social welfare. Social welfare is defined using the Hicks-Kaldor criterion, which states that a policy increases welfare if the winners from the policy can compensate the losers from the policy and still be better off than if the policy is not implemented.

To conduct a cost-benefit analysis, one must identify consequences and express them in a monetary metric so that all consequences can be compared in the same unit of measurement. If benefits and costs arise in the future, they should be discounted to present value using a social discount rate. Finally, given the uncertainties involved with estimating consequences of a policy or regulation as well as uncertainties with the monetary estimates of the consequences, a proper cost-benefit analysis should include sensitivity analyses to show how robust the result is.

Finally, considering the definition of social welfare as usually applied in cost-benefit analysis (Hicks-Kaldor criterion), the typical cost-benefit analysis of a project or regulation estimates the effect on economic efficiency. Therefore, even though a very important guide to decision making, in most applications, cost-benefit analysis is often seen as one of several guides to the decision making process. Especially in political decision making, there will be other effects of interest, such as effects on income distribution and geographical distribution of benefits.

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Estimating workforce costs in economic evaluations of genomic testing: Towards a standardised Australian health workforce costing model for comparative health systems research

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Introduction Labour costs are a key driver of healthcare costs and a key component of economic evaluations in healthcare. We undertook the current study to collect information about workforce costs related to clinical genomic testing in Australia, identifying key components of pay scales and contracts, and incorporating these into a matrix to enable modelling of disaggregated costs.

Methods We undertook a microcosting study of health workforce labour costs in Australia, from a health services perspective. We mapped the genomic testing processes, identifying the relevant workforce. Data was collected on the identified workforce from publicly available pay scales. Estimates were used to model the total cost from a public health services employer perspective, undertaking deterministic and probabilistic sensitivity analyses.

Results We identified significant variability in the way in which pay scales and related conditions are both structured and the levels between jurisdictions. The total costs (2023-24 AUD $) ranged from 160,794 (113,848 - 233,350) for administrative staff to 703,206 (548,011 - 923,661) for pathology staff (full-time equivalent). Deterministic sensitivity analysis identified that the base salary accounts for the greatest source of uncertainty, from 24.8% (20.0% - 32.9%) for laboratory technicians to 53.6% (52.8% - 54.4%) for medical scientists.

Conclusion Variations in remuneration levels and conditions between Australian jurisdictions account for considerable variation in the estimated cost of labour and may contribute significantly to the uncertainty of economic assessments of genomic testing and other labour-intensive health technologies. We outline an approach to standardise the collection and estimation of uncertainty for Australian health workforce costs and provide current estimates for labour costs.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study did not receive any funding

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

zornitza.stark{at}vcgs.org.au

ilias.goranitis{at}unimelb.edu.au

kim.dalziel{at}unimelb.edu.au

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