problem solving maturity model

Are You Ready? How to Conduct a Maturity Assessment

Published: June 23, 2011 by Afsar Choudhury

When an organization begins a Lean Six Sigma deployment, what is the first step that the leadership team should take? Should they start executing Kaizen events to demonstrate the impact of quick process improvement? Or should they kick-off with Six Sigma projects, using the DMAIC or DFSS roadmap, with a deep dive into sophisticated statistics?

While these two efforts can bring value in time, ideally leaders should start with a Lean Six Sigma maturity assessment – a self-evaluation of where the organization stands. The key to successful implementation of Lean Six Sigma lies in knowing where the organization needs to be in the future. At the same time, it is equally important that leaders know the current state of their business. A Lean Six Sigma maturity assessment shows leaders how advanced their organization is in terms of Lean Six Sigma perspective, its strengths, weakness and improvement opportunities.

The assessment enables detailed, step-by-step, quantitative scoring to diagnose the current state. The rigorous nature of this exercise ensures that the journey going forward will lead the organization toward a future state of satisfying customer needs, improving internal processes, motivating employees and keeping the balance sheet strong.

The 3A Approach: Assess, Analyze and Address

A Lean Six Sigma maturity assessment should follow a three-phase approach: 1) assess, 2) analyze and 3) address. The tasks within each phase are described below.

The assess phase involves the use of a scorecard of Lean Six Sigma parameters and a radar chart, also known as a web chart or spider chart. The scorecard should be completed by both the leaders of the Lean Six Sigma deployment and the department heads for each of the individual verticals within the organization. The scorecard (seen in the table below) should address at these 12 Lean Six Sigma parameters:

• Leadership alignment
• Leadership approach toward Lean Six Sigma
• Employee involvement
• Process capability
• Approach to errors
• Data-driven problem solving
• Continuous improvement methodologies
• Standard work
• Value stream mapping
• Accounting support to Lean Six Sigma
• 5S/housekeeping

A 1-to-5 rating scale is used to assess the selected Lean Six Sigma parameters, where 1 represents the lowest level of maturity and 5 is best in class. The scorecard contains detailed guidelines for scoring criteria.

Sample Lean Maturity Assessment Scorecard

To aid in completing the scorecard, leaders should conduct interviews and audits, walk the shop floor, and do all other necessary data gathering. Once the scores are complete, they can be transferred to a radar chart, which helps leaders see the current state in a graphic form. The chart illustrates the 1 through 5 rankings for the different Lean Six Sigma parameters; the lower the Lean Six Sigma maturity level, the closer the scores are toward the center of the chart.

Once the Lean Six Sigma deployment leader receives the completed scorecards and linked radar charts from the leaders of the various verticals in the organization, the analyze phase can begin. The goal of the analyze phase is to identify the most important parameters on which to start working.

To do this, the deployment leader can start by creating a graph comparing the scores for the individual parameters to the organization’s Lean Six Sigma maturity index (the average of all those scores).

The bars on the left side of the graph represent the weaknesses of the organization. Because these parameters achieved lower scores they are a matter of concern and need immediate attention. The parameters on the right-hand side are those with the highest scores, making them strengths. The difference between the Lean Six Sigma maturity index and the desired score of 5 is known as the maturity gap.

Once the key parameters for improvement are agreed upon, based on this gap analysis, the second phase is complete.

In this last phase, leaders from the various departments and functions within the organization should meet to begin addressing the weaknesses. One way to collect ideas for making improvements in these areas is to use the brainwriting technique . This technique is different from traditional brainstorming in that participants write down their ideas rather than immediately share them aloud. After the broad action ideas are compiled, the group can drill them down using a decision tree diagram. All attainable action items should be slotted into a Gantt chart to form the improvement roadmap.

Once the whole cycle of asess, analyze and address is completed, leaders can look back on lessons learned and prepare for the next cycle of the continuous improvement journey.

About the Author

Afsar Choudhury

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THE LEADERSHIP MATURITY MODEL

Alone we can do so little; together we can do so much. Helen keller

Dysfunctional leadership teams are more the norm than the exception. At the top of many companies is a lack of trust fueled by politics, power dynamics, selfish mindsets , and a toxic culture . Often, they aren't really a team as much as a collection of individuals pursuing their own agendas for more power and budget. The dysfunctions of the leadership team permeate and infect the rest of the organization , ultimately leading to poor performance and often the never-ending revolving door of new leadership every 12-24 months. The cycle stops once a CEO with the right experience, perspective, and skillset finally cleans up the team and the mess. But, in the meantime, the market and competition have evolved, and whatever advantages the business had have disappeared.

Here is the thing: with focus and hard work, leadership teams (often with some help) can systematically address their dysfunctions in a relatively short amount of time. The transformation of a leadership team from dysfunctional to high-performing doesn't have to wait for the "savior" CEO to swoop in. Most CEOs and leadership teams have the right ingredients to become high-performing; they just need the proper focus, a robust approach, and often a coach to mature and refine their behaviors to that of a high-performing team.

High-performing leadership teams don't create mediocre or average companies. They create market leaders. Their performance is measured by how efficiently and effectively they can mature the business model into a market leader. Put another way, a high-performing leadership team creates a high-performing business model in which the organization efficiently and effectively develops and delivers the customer value proposition and go-to-market to fulfill the target customers' needs better than the competitors, all to achieve the vision and mission .

• LEADERSHIP MATURITY MODEL
• Communication
• Collaboration
• The Author - Joe Newsum

There is much to unpack in the previous statement, which I detail in many sections of Stratechi.com. The takeaway for us right now is that high-performing leadership teams create high-performing business models . So, if you want to mature into a high-performing leadership team, the team's ultimate goal is to create a market-leading business model.

High-performing leadership teams aren't about big personalities, inspiring speeches, and natural ability; instead, high performance comes down to the little fundamental things the leadership team learns to do consistently every day to ensure a group of people achieves a set of goals efficiently and effectively. Maturing a leadership team involves doing more and more of the little things, the fundamentals, that, over time, compound to create incredible improvement in the business and the organization. It comes down to having a leadership team with the right people and mindsets. A team that infuses strong collaboration and communication skills and norms through themselves and the entire organization. A team that can strategically plan its way, solve the problems, and make the stream of decisions to become a market leader. And, of course, a team with the leadership skills to drive efficient and effective organizational execution to realize the vision to become a market leader.

The path to becoming a high-performing leadership team is through maturing the fundamentals within the five leadership competencies:

• People & Mindsets
• Collaboration & Communication
• Problem Solving & Decision Making
• Leadership & Execution

We'll go deep into the details of the what, why, and how of these five competencies, but be assured that if your leadership team works diligently on maturing these competencies, performance will follow.

WHY I CREATED THE LEADERSHIP MATURITY MODEL

As an executive, consultant , and coach, I've worked with many leadership teams over my 25+ year career. They've all had the potential to do great things with their businesses. And while some accomplished great things, the majority never reached their potential simply because they would consistently get in their own way. Some just weren't very strategic, others myopic, valuing short-term gains over long-term strategy; others were terrible at communication and collaboration; some consistently made poor decisions; others weren't good at problem solving and prioritizing or didn't have the right people and mindsets, or had toxic team dynamics, or couldn't execute. While the leaders were always different, the stories were eerily the same. The leadership teams consistently underperformed to their potential and typically found themselves in a stew of politics and ineffectiveness.

Early in my career, I focused primarily on strategy, but about ten years ago, I realized strategy isn't the hard part of business. The most challenging and rewarding part, financially and personally, is elevating the performance and alignment of a leadership team so they can collectively develop and execute strong strategies to become the leader in their market. The whole performance game became much easier once I began focusing on helping teams become high-performing leadership teams. Developing collaborative strategies and visions became easier for the teams. Their team dynamics would often take a 180 in a short amount of time. The pace of positive change accelerated as the organization had focus, clarity, and motivation. And, it always came down to the same playbook, which became the Leadership Maturity Model. We would work on the fundamentals of strategy & planning , people & mindsets, collaboration & communication, problem-solving & decision-making, and leadership & execution. Over time, I knew I was onto something, and I took some time off to codify all of my learnings over my career to develop the Leadership Maturity Model.

Another reason I created the LMM is the need for more prescriptive and helpful advice on becoming a high-performing leadership team. Most of the existing content is too simple, generalized, and without much depth. There isn't a comprehensive playbook for leadership teams to become high-performing and lead their organization to market leadership. None of what is in the Leadership Maturity Model is rocket science; just a lot of fundamentals wrapped up in a practical framework of competencies, which leadership teams can rally around in their pursuit of becoming a market leader and a high-performing team.

WHY THE LEADERSHIP MATURITY MODEL WORKS

There is a tremendous lift to the leadership team's performance as they mature in the fundamentals of strategy & planning, people & mindsets, collaborating & communicating, problem-solving & decision-making, and leading & executing. The beauty is that little investment is needed to transform not only the leadership team but the entire organization and trajectory of the business. No capital investment is required to mature all the competencies of the leadership maturity model. Instead, it's just a lot of hard work and focus to drive the individual and collective change to do the basics better, evolve fundamental behaviors, norms, and mindsets, and think and act a bit differently and more strategically. In addition, there are also three other big-picture reasons why the leadership maturity model playbook works and is one of the most, if not the most, fruitful, journeys a leadership team can take to transform themselves, their organizations, and their business.  

THE FOCUS ON BECOMING A MARKET LEADER

Most leadership teams don't aim high enough. Executives focus on their KPIs , hitting the quarterly and annual financial goals, getting their initiatives approved, and moving them along. The game changes dramatically when leadership teams change their orientation towards evolving their business model into a market leader. When this happens, the leadership team finally has a goal they can all get behind instead of the piecemeal KPIs and OKRs they are focused on in the hope of progress. Leadership teams broaden their time horizon, elevate their strategic game, and start collectively focusing on the real chess game of how they will win and dominate. It may initially seem delusional for some teams to aim so high. Still, there is no downside for a leadership team to aim high, as long as they back it up by maturing their leadership competencies of strategy & planning, people & mindsets, collaborating & communicating, problem solving & decision making , and leading & executing. Ultimately, nothing stops a leadership team from being the best except for the leadership team.

THE EXPECTATION OF BECOMING A HIGH-PERFORMING TEAM

The simple act of a leadership team committing to the pursuit of excellence in becoming a top high-performing team is one the most significant boosts to the potential performance of the team. When every leadership team executive truly commits to the hard work and challenge to develop into a high-performing team, many historical team dysfunctions of politics and toxicity quickly fade away, replaced by positive team dynamics, trust, and a collective desire to improve as a team. Once the team decides to be a team, any holdouts that continue to prioritize their individual orientation stick out like sore thumbs and typically fall into place. The collective commitment to becoming a high-performing team is one of the most significant boosts to team growth . As expectations of what the leadership team can become elevate, the art of the possible opens up to the team. Belief is a potent, if not the most potent motivator. And once the leadership team truly "believes" they can be great, they will constantly be pulled toward greatness.

TRANSFORM THE LEADERSHIP TEAM TO TRANSFORM THE ENTIRE ORGANIZATION

A toxic leadership team creates a toxic organizational culture, while a high-performing team creates a high-performing culture. People primarily learn through mimicry and modeling of behaviors. As leadership teams mature in competencies, the leaders become role models, taking those learned norms and behaviors, and infusing them into their teams, creating a positive chain reaction throughout the organization. In essence, culture is simply employees' collective norms and behaviors. There isn't a better way to create a high-performing culture than first to elevate the performance of the leadership team, who will, in turn, cascade winning norms and behaviors to their teams, who will cascade them to their teams, and so on. As the leadership team goes, so does the rest of the organization.

A COACH TO ACCELERATE THE JOURNEY

Every major professional sports team has a coach, yet few leadership teams have one. They often try to rely on the CEO to be the coach, yet that is like depending on the quarterback of a football team to be the coach. Some CEOs are highly gifted and talented and can play both roles . Still, leadership teams can significantly accelerate their transformation with a strong leadership coach to bring an objective perspective to what good is, what the gaps are, how best to evolve the dynamics and skill sets of the leadership team, while also holding them accountable. Having specialized coaches for specific competencies can further accelerate the leadership team's maturity, just like every professional sports team has a bevy of coaches to work with players on various skills.

The absence of team-oriented coaches is one of the most significant gaps in modern executive leadership. While most executives have individual coaches, the advice they get can often exacerbate specific team dysfunctions since the orientation is usually around the best strategy for individual executives rather than the best collective path for the team and organization. Imagine a professional sports team where everyone has their own personal coach they meet with once a week, who never sees the players in action in practice or games, and no coaches are overseeing the team. That experiment would go poorly, but that experiment is the reality of most leadership teams in business.

There are a million and one reasons why leadership teams may be dysfunctional, but in my experience, all the reasons leading to the dysfunctions are irrelevant. What matters is what the leadership team will do differently today, tomorrow, and over the next month to mature in specific competencies. How will they change their collective beliefs, mindsets, actions, and behaviors to try to move forward and, with it, the business model? So, let's dig into the five management competencies of the Leadership Maturity Model to get your team started on their journey today.

THE FIVE COMPETENCIES OF THE LEADERSHIP MATURITY MODEL

The five competencies of the leadership maturity model are:

• Strategy & Planning
• Accountability & Execution

Within these competencies are dimensions that further define the competencies to a specificity that leadership teams can tactically improve. Below are the competencies and their dimensions, which I will review in the following sections.

Leadership teams who take on the challenge of maturing across these leadership competencies create positive systemic change across their organization to accelerate their journey to market leadership. They’ll get people working on the right things and less on the things that don’t matter.

From here, you can navigate the Leadership Maturity Model sequentially, which will maximize your understanding, or jump to a section that interests you.

Learn what it takes for a leadership team to mature strategically by mastering the big picture, using a common strategic language, managing a balanced portfolio of strategic initiatives, driving functional excellence, and developing and executing well-crafted objectives and key results (OKRs). 

Explore how high-performing leadership teams are stacked with high-will and high-skill people with a complementary composition, and the right mindsets oriented around team, growth, value , and the company's core values .

High-performing teams drive incredible productivity and creativity through strong communication and collaboration. They focus on creating a culture of trust and strong networks of connection. They establish and nurture collective norms around purpose, quality, and efficiency. And, they fully utilize technology.

Problem solving and decision-making are how leadership teams create the strategies to become a leading business model. High-performing teams are strong problem-solvers and decision-makers. They focus on the right problems, correctly frame them, collaboratively solve them with solid logic and analytics , ideate creative and elegant solutions, and make good decisions that propel the business model forward.

The realization of a leadership team's good decisions and strategy comes down to the organization's ability to execute them. A team with strong leadership and accountability creates a performance culture. Efficient and effective execution are the last critical pieces of the puzzle.

BECOME A HIGH-PERFORMING TEAM WITH PERSONAL COACHING

I hope you are enjoying the leadership maturity model. Seeing the rapid improvements leadership teams have realized using the model has been rewarding. As an executive,  consultant , and coach, I've worked with many leadership teams over my 25+ year career. If you want to take your leadership team to the next level, I encourage you to learn more about my background and reach out or set up some time if you think there is a fit. We'll work together to develop your team into a high-performing leadership team and your business into a market leader. 

How to master the seven-step problem-solving process

In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.

Podcast transcript

Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.

Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].

Charles and Hugo, welcome to the podcast. Thank you for being here.

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?

Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”

You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”

I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.

I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.

Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.

Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.

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Simon London: So this is a concise problem statement.

Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.

Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.

How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?

Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.

What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.

Simon London: What’s a good example of a logic tree on a sort of ratable problem?

Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.

If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.

When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.

Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.

Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.

People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.

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Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?

Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.

Simon London: Not going to have a lot of depth to it.

Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.

Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.

Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.

Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.

Both: Yeah.

Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.

Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.

Simon London: Right. Right.

Hugo Sarrazin: So it’s the same thing in problem solving.

Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.

Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?

Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.

Simon London: Would you agree with that?

Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.

You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.

Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?

Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.

Simon London: Step six. You’ve done your analysis.

Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”

Simon London: But, again, these final steps are about motivating people to action, right?

Charles Conn: Yeah.

Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.

Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.

Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.

Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.

Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?

Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.

You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.

Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.

Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”

Hugo Sarrazin: Every step of the process.

Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?

Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.

Simon London: Problem definition, but out in the world.

Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.

Simon London: So, Charles, are these complements or are these alternatives?

Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.

Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?

Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.

The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.

Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.

Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.

Hugo Sarrazin: Absolutely.

Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.

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Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.

Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.

Charles Conn: It was a pleasure to be here, Simon.

Hugo Sarrazin: It was a pleasure. Thank you.

Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.

Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.

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Practical IT Maturity Models and Assessment Tools for Today’s Modern Business

By Kate Eby | March 9, 2022

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We have compiled the most comprehensive IT maturity information and tools for organizations of all sizes. Plus, find an IT maturity starter kit for assessing, analyzing, and planning.

On this page, you’ll find an IT maturity assessment scorecard , a presentation to share IT maturity data and progress trajectory with stakeholders , expert tips on improving IT maturity , and industry-relevant IT maturity models .

What Is the Maturity Model for IT?

An IT maturity model is a tool that indicates the current development of an IT organization. IT maturity models measure the progress of people, processes, and technology. Maturity may range from low-level chaos to high-level strategic partnership.

Maturity models are common across all business disciplines. Businesses will use IT maturity models to compare where IT is today to where IT wants to be in the future. This comparison helps companies identify gaps between the current and future desired state. 

Several consulting companies utilize maturity models to help IT organizations find ways to improve. The organization’s internal resource availability and budget help determine what a company uses to map current maturity and track progress. A small company may rely on surveying employees to identify IT gaps and a standard project plan to prioritize improvements. In contrast, a large enterprise may hire a consulting firm specializing in IT maturity to assess, analyze, and plan IT maturity growth. 

​​​​​​​Types of IT Maturity Models

Below are a few IT maturity models that you can use to familiarize yourself with how evaluating and scoring IT maturity works

Gartner IT Score for CIOs

Gartner’s IT Score for CIOs is one of the most popular models. This maturity model measures the maturity of key IT activities. It helps prioritize improvements and plan a path to progress. 

The Gartner IT Score framework looks at functional areas, including how IT engages with leadership, strategy, innovation, IT governance, IT finance, and talent, as well as its overall performance. Each of these categories is given a high- to low-maturity rank based on how advanced the organization is in that area. Priorities are then identified based on both maturity and importance.

Forrester’s DEX Maturity Model

Forrester Consulting recently introduced the DEX maturity model , commissioned by 1E. This model evaluates the state of remote and hybrid work. The goal is to help IT improve the work experience of the digital employee.  

The model contains 15 assessment questions. The questions analyze your organization’s DEX practices across four key disciplines: monitoring, security and compliance, remediation and automation, and operating model and integration.

Capability Maturity Model Integration (CMMI)

The Capability Maturity Model Integration helps a company improve its  processes and behaviors. The model applies to hardware, software, and service development in any industry. The primary goal is to ensure organizations have everything necessary to develop reliable products and services. 

Carnegie Mellon University in conjunction with the Department of Defense and the U.S. government developed CMMI. The model is owned by the Information Systems Audit and Control Association (ISACA) and administered by the CMMI Institute. CMMI was originally a software-specific model. Over time, it became applicable to hardware, service, and software development.

Why is IT Maturity Important?

Organizational performance depends on IT effectiveness. In turn, business excellence improves when IT can deliver good outcomes. By understanding maturity, the IT department can progress from its current state to a future desired state.

“To have a successful business, you have to secure some level of IT maturity,” says Viachaslau Matsukevich , IT Solutions Architect with CTDev. “It doesn't matter the type of company; confidence in IT is essential. A mature IT department will provide stable continuous benefits that lead to a competitive advantage, customer satisfaction, and sales growth. Neglecting IT maturity will lead to the unreliability of your services, a bad customer experience, loss of customers, and potential income.” 

The capabilities that make up IT maturity for each organization will differ. Maturity is all about whether the IT department can provide the people, processes, and technology that enable a business to perform efficiently. “Highly mature organizations are less likely to have end-user disruptions. They are more likely to increase employee retention and have higher employee satisfaction. Plus, Forrester research shows that more mature organizations will have fewer security incidents and breaches,” according to Erik Jost, Chief Strategy Officer at 1E .

The IT Maturity Curve

Many IT maturity models refer to the stages of maturity as a curve. Level one is at the bottom, and level five is at the top. As IT organizations adopt people, processes, and technology improvements, they scale up the maturity curve.

What Are the Different Levels of IT Maturity?

IT maturity characterizes performance through levels or stages. Each model has its own terminology for the levels, but they all follow a similar structure. Level one is the least mature, while level five is the most mature. 

Below we will define the five levels of IT maturity and what they mean for an organization.

Level 1: Chaos

Level one maturity is where an organization usually begins its IT journey. There are no processes in place. Activities, technology, and personnel are inconsistent or non-existent. The overall IT support structure is not very useful. 

Level 2: Committed

Level two maturity is a bit more organized, but not enough to be proactive. The IT team still does not have processes in place. They react to issues and are always fighting fires. 

Level 3: Proactive

Level three has made significant progress in maturity. Processes are in place, and documentation exists. The IT staff know their roles. The IT team can predict problems before they occur, working proactively to keep the entire organization productive. 

Level 4: Integrated and Aligned 

Level four IT maturity is difficult to achieve. The IT organization is beyond documenting processes and proactive problem-solving. IT and business goals are aligned. The IT organization is indispensable.

Level 5: Strategic Business Partner 

In level five, IT is central to business strategy. Getting a seat at the executive table is not easy for IT because it has often been considered a cost center. Teams that reach level five receive investments for their efforts to ensure outcomes strategically align with business goals.

How to Assess IT Maturity

Assessing IT maturity involves evaluating IT's performance across all functions. You can use any model appropriate for your business. Making an assessment is not a one-time activity. It’s essential to reassess maturity to monitor progress and continually improve.

An IT maturity assessment may follow a three-step approach: assess, analyze, address. The phases are as follows:

• Assess: The assessment phase involves a series of questions or evaluators to determine the current state of a company’s IT maturity. Organizations may complete the assessment independently or with a consultant who specializes in maturity assessments. Below is an IT maturity assessment scorecard that contains guidelines for scoring IT maturity.
• Analyze: Once the assessment scorecard is complete, the results will be analyzed and will determine which IT areas require attention. 
• Address: Weaknesses found during the analysis will become addressable action items. Add the action items to improve IT maturity to a project plan to create an IT improvement roadmap. 

Assessing IT maturity does not need to be complex. “You can start by asking questions like: ‘What are your developers’ or operators’ level of experience? How fast can you deliver new features? What is your time to market?’ Or even questions like: ‘Can I rely on my IT department? Can I achieve the business goals using IT in a reliable and timely manner?’ Check the downtime and outages of your IT services and get feedback from within your IT department to provide visibility into pain points that could be improved,” suggests Matsukevich.

How to Improve IT Maturity

To improve IT maturity, a company must first know its current level of maturity regarding people, technology, processes, and management. Create a roadmap that takes IT from today's maturity state to the desired level and use it to guide your improvement.

It is only natural for an organization with inefficient, poor-quality IT operations to desire consistent output, standard processes, and agility. With maturity comes the ability to adjust as a business grows. The process starts with an IT maturity assessment. Once the analysis is complete, the IT team can prioritize action items for improvement. Below are tips and best practices for improving IT maturity:

• Processes: It is essential to focus on IT processes as part of your improvement strategy. “Focus on your internal processes and implement a proven best practice, such as ITIL , Scrum , or Kanban ,” says Matsukevich. Process automation is a key strategy to progressing up the maturity curve. Self-service, specifically, eases frustration and promotes business productivity. Jost shares that the legacy dependence of waiting for a service desk technician to call and conduct an intrusive screen share to resolve an issue is time-consuming and disruptive. ”The availability of self-service tools and chatbots that allow workers to circumvent the service desk admin and IT bureaucracy entirely, while resolving issues on their own time, are game changers. On the other hand, for issues that unavoidably require human assistance, service desks need to be able to act in real time with automation-driven resolution,” he says.
• People: Data is key to understanding employee satisfaction (and dissatisfaction). Jost suggests gathering sentiment-driven data that paints a holistic, context-based picture of the employee experience and what matters most. “Qualitative surveys that uncover nuances between individuals can help leaders tap into employee sentiment and enact meaningful change. Change cannot occur without data and measurement," he adds. The data you collect can feed into where to prioritize improvements. IT employees must receive training and access professional-level certifications to mature your IT organization. It is essential to create a culture where you keep your most talented IT professionals and attract new talent that will improve IT operations. “If you are having trouble hiring seasoned professionals, you can focus on growing your team internally,” says Matsukevich. “Hire fresh graduates and run them through a series of internal bootcamp training sessions that will get them up to speed quickly.”
• Technology: For employees across the entire organization to perform at their optimum capacity, they require the necessary tools and the right environment to succeed. “Much like the growing demand for choice from consumers, employees want more options when it comes to workplace technology,” suggests Jost. “Employees are far more effective when they have the technology, devices, and tools that suit their preferred ways of working. Plus, IT organizations will benefit from significant cost savings by eliminating unused software and hardware.”

Download an IT Maturity Starter Kit

Get everything you need to assess your IT maturity in our IT maturity starter kit. You’ll find an IT maturity assessment scorecard and a presentation template in one easy-to-download file.

Download IT Maturity Starter Kit

IT Maturity Assessment Scorecard Template

Download IT Maturity Assessment Scorecard Template Microsoft Excel | Google Sheets

The IT maturity assessment scorecard template allows you to evaluate the maturity of your IT organization. Score maturity across user experience, strategy, business relationship, and performance. Note your target maturity level and prioritize areas where gaps exist in this easy-to-use worksheet.

IT Maturity Presentation Template

Download IT Maturity Presentation Template — Microsoft PowerPoint

Use this IT maturity presentation template to provide sponsors, stakeholders, and team members with an overview of IT maturity and your team’s progress. Include criteria for each stage of IT maturity and what your team must do to achieve the desired state.

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When teams have clarity into the work getting done, there’s no telling how much more they can accomplish in the same amount of time.  Try Smartsheet for free, today.

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• Lean , Lean Wiki , Six Sigma

DMAIC Model | The 5 Phase DMAIC Process to Problem-Solving

• 5 mins to read
• July 1, 2020
• By Reagan Pannell

Summary: An Introduction to DMAIC

Dmaic – the dmaic model.

The 6 Sigma DMAIC model remains the core roadmap for almost all Lean Six Sigma problem-solving approaches that drive quality improvement projects. It is used to ensure a robust problem-solving process is followed to give the best chance of the best solution being found.

A note about the structure and the approach used in this article.

Our approach to DMAIC follows Quentin Brook’s book “Lean Six Sigma & Minitab” which for anyone wishing to study Lean Six Sigma is a must for the  Green Belt Course  and the  Black Belt Course .

What is the DMAIC Model?

DMAIC is short for: Define, Measure, Analyse, Improve and Control. These are the key phases that each project must go through to find the right solution. This flow is the concept behind DMAIC Analysis of an issue and its the DMAIC cycle all projects must go through.

As you can quickly see from the 5 DMAIC phases they follow a logical sequence as we will go through in more detail below. But they also make sure you do not try to jump to implementing a solution before you have properly, defined and measured what you are going to be an improvement.

We all love to jump to solutions, but the DMAIC problem-solving structure helps us have a more rigorous approach so that we do not short cut the process and perhaps miss the best solution or perhaps implement the wrong solution as well. It can help companies better structure their problem-solving approaches and be more robust in their approach. 

DMAIC – The 5 DMAIC Process Phases

The phases throughout the DMAIC model have and can be broken down in many different ways. One of the best approaches we have found is from Opex Resources which shows how to examine the existing processes, and with a project team, and the sigma improvement process, we can solve complex issues.

DMAIC Define Phase

The purpose of the Define phase is ultimately to describe the problems that need to be solved and for the key business decision-makers to be aligned on the goal of the project. Its about creating and agreeing the project charter .

All too often, teams have identified solutions without actually defining what it is they will actually be trying to do or perhaps not do. This can lead to internal confusion and often solutions which completely miss the business requirements and needs.

• Define the Business Case
• Understand the Consumer
• Define The Process
• Manage the Project
• Gain Project Approval

We can’t solve problems by using the same kind of thinking we used when we created them” Albert Einstein Tweet

DMAIC Analyse Phase

The goal of the DMAIC Analyse phase with the lean six sigma improvement process is to identify which process inputs or parameters have the most critical effect on the outputs. In other words, we want to identify the root cause(s) so that we know what critical elements we need to fix.

During this phase, the teams need to explore all potential root causes using both analytical approaches, statistical approaches or even graphical tools such as VSM’s and Process maps to uncover the most important elements which need to be changed/fixed.

The Analyse phase can be broken down into:

• Analyse the Process
• Develop Theories and Ideas
• Analyse the Data
• and finally, Verify Root Causes 

DMAIC Improve Phase

The goal of the improvement phase is to identify a wide range of potential solutions before identifying the critical solutions which will give us the maximum return for our investment and directly fix the root cause we identified.

During this phase, the team brainstorm, pilot, test and validate potential improvement ideas before finally implementing the right solutions. With each pilot, the team can validate how well it improves the key measures they identified back in Define and Measure. When the team finally roll out the solution, the results should be seen if the right solution has been found and implemented correctly.

The Improve phase can be broken down into:

• Generate Potential Solutions
• Select the Best Solution
• Assess the Risks
• Pilot and Implement

DMAIC Control Phase

The final part of the DMAIC Model is the Control phase where we need to ensure that the new changes become business as normal and we do not revert to the same way of working as before.

During this phase, we want to ensure that we close the project off by validating the project savings and ensuring the new process is correctly documented. We also need to make sure that new measures and process KPI’s are in place and, finally that we get the business champion to sign off on both the project and the savings. We may need to redesign the workplace following the 5S principles .

The Control phase can be broken down into:

• Implement Ongoing Measurements
• Standardise Solutions
• Quantify the Improvement
• Close The Project

The key closing documents of the Control Phase is a Control Plan that documents all the changes and process steps with key risks, standard work instructions and the Project Close-Out document signed by the business owners to accept the change and the validated benefits.

Our approach to DMAIC follows Quentin Brook’s book “Lean Six Sigma & Minitab” which for anyone wishing to study Lean Six Sigma is a must for the  Green Belt Course  and the  Black Belt Course .

The dmaic model vs. a3 management vs. 8d problem solving.

The DMAIC model is not the only project management roadmap. Two others which are important is the A3 format which originally comes from Toyota and is very Lean focused and the 8D which draws more of the DMAIC structure but with the 1-page idea of the A3.

Everyone has their own preference but each method is interchangeable. The DMAIC Structure lends its self naturally to a multi-slide Powerpoint presentation. Whereas the A3 is a single-page document which is perfect for internal communication and adding into War Rooms and Control Towers.

What’s important is that every problem-solving approach follows the PDCA (Plan, Do, Check and Act) Scientific Problem Solving format. The reset is just a preference or using the right tool in the right circumstances.

Reagan Pannell

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The four levels of Lean Maturity

As a real lean enthusiast, I am stunned how many people introduce lean tools in their processes without success. How can you spend time on implementing a tool without making sure that it helps you achieve your goals?

I have written a book about it, lean Transformations, and in this book, I discuss a LEAN MATURITY MODEL (shown in figure 1) that should help you break the cycle of actions that do not lead to measurable improvement.

Figure 1: The four levels of lean maturity ( Panneman, 2017 )

Level 1 describes the first level of lean maturity: Setting Standards .  It includes the tools 5S and standard work, which are necessary to implement in any company, just to keep the lines running (Panneman, 2017). The problem with level 1 organizations is, that they have an event and they think of something great, but they do not have a system in place to sustain these implementations . This means the organization lean organizations are stressed when an external party announces an audit because they are not sure everything is documented properly, let alone that all standards are adhered to. The weeks before the audit, management does as many quick fixes as possible to prevent the auditor from finding inconsistencies, after which the organization moves back into its old habits until the next audit is announced.

Level 2 describes the second level of maturity which is called checking the Standards . This is where team boards and kamishibai audits are described as tools to help steer conversations in the organization about how we are performing compared to the standards (Panneman, 2017). A level-two lean organization is therefore an organization in which people discuss performance regularly and check whether the standards are still kept, but nothing happens with the information they gather (Panneman, 2017). One possibility is that targets are met every time, and the daily performance meeting does not change anything in the way that the team works in the future. At this level of maturity, both kamishibai and the team board are used on a push basis. Even though the structure of lean tools is in place, it is not used to its full potential, namely finding the next improvement opportunity, which brings us to level three.

Level 3 is called improving the standards and describes kaizen, A3 problem solving, and D2MAIC projects as possible ways of using the audits and daily meetings to improve the standards (Panneman, 2017). These are the organizations which use visual management as input for their problem solving processes. Teams are taught to use the tools kaizen, A3 and maybe even D2MAIC project and start improving. However, even though the organization has different forms of problem solving in place, they have difficulties measuring the impact of these improvements on organizational goals. This is the power of level-four organizations.

The fourth level of lean maturity is about Linking Improvements to company goals . Meaning, that all departments have to improve in the same direction: the number one KPI that is most important for the organization to achieve its vision (Panneman, 2017). The daily management system and hoshin kanri are the tools that organizations in this maturity level use. Level four organizations make sure that all improvement initiatives in the organization directly influence bottom-line results. Having a clear link between management levels and each of the individual teams creates a situation in which management will pull improvement ideas from the organization. Their KPI depends on the KPIs on each team board, so they will offer their support when a team misses its targets.

In a true lean organization, everyone is working with the system of continuous improvement. Processes are standardized, performance is visualized, and people are trained in problem solving based on their KPI that are directly derived from organizational goals. Only when all these elements are in place, your organization will use the lean tools the way they were designed: gain measurable results.

Continue to:

Lean basics – 5 lean principles

Panneman, T, 2017, Lean Transformations - when and how to climb the four steps of Lean maturity, Maarssen (NL): panview ( summary / order this book )

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Six Sigma DMAIC - T.Panneman & D.Stemann (summary)

5s in practice - sustain, 5s in practice - sweep and standardize, 5s in practice - sort and straighten.

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Blog - IT CSI

How to improve it problem solving maturity levels.

Oct 6, 2017 11:46:52 PM

I am a professional problem solver. When I started applying my skills set as an Industrial Engineer to the IT environment, I was astonished at the maturity level of troubleshooting skills, specifically Root Cause Analysis, in this sector. I became aware of a whole generation of IT Professionals who have never been taught the fundamentals of deductive reasoning, problem solving, or critical thinking skills. There was (mis)use of the  “5 Whys”  technique and attempts to clone branded solutions to in-house situations, but little else in RCA. That has changed gradually over the last 10 years, but there are still some very basic problems and obstacles in getting RCA properly embedded into the Service Management environment.

As a company specializing in solution applications, we were at the forefront of this evolution. We have detected the following trends that will continue to shape RCA evolution in 2017 and beyond. We want to comment on six specific TRENDS and will continue this series of blogs by discussing each trend in more detail over the next few months. Here are the six most significant trends taking place within RCA methodologies as they apply to the IT sector:

• Understanding the real meaning of a Root Cause   – Most IT Professionals do not make the distinction between the Technical Cause of a problem and its Root Cause. These terms are often used inter-changeably or worse case, there is no distinction made between them at all. The IT Professional who “gets this” distinction has a major advantage over his/her colleagues in determining a Root Cause quicker, cheaper and permanently. The trend of recognizing this distinction will grow in the years to come.
• Aligning the “handover” practices between IM and PM  – Last year I worked with a significant number of clients who were adamant in wanting to improve the handover between IM and PM in the following ways:
• Having a seamless process between IM and PM.
• Improving the quality of data and ensuring no loss of data with this handover.
• Having templates that could be added to as the incident investigation moves from one area to the other area.
• Having a common incident investigation approach and language to eliminate any misunderstanding along the way.
• IT divisions are starting to adopt the rigor and discipline of a structured approach to incident investigations  – The benefits of arriving at an effective and correct restoration plus an accurate root cause analysis is getting management’s attention. Too many outstanding incident tickets with too slow restoration times is becoming just too expensive for IT Divisions to reason away. Many of our clients would like to see how they are doing and are starting to employ templates and techniques with the appropriate metrics in the analysis process. They want the incident analysis data to be visible, which would make it easier for them to identify areas of improvement.
• The importance of a robust Knowledge Management Practice  – This area has been overlooked for far too long. Management is realizing that having the correct knowledge, skills and expertise available will make a significant difference in becoming more effective in incident investigations. In 2016, we experienced a major increase in requests to help our clients establish a worthwhile knowledge data base on the 20% of incidents (objects and types of faults) that account for 80% of their incidents. In many cases, this exercise alone produced a major reduction in down time and level of incidents.
• C-Level managers starting to understand and embrace the potential benefits of Problem Management – We are still struggling to see a significant change in attitude towards a full commitment to establishing a highly skilled Problem Management practice. Unless you are an expert in the many ways causes, effects and consequences interact with each other, it is difficult to understand the exponential potential benefits. In 2016, our senior consultants made it their mission to sit down with C-Level Managers and rationally explain these benefits (with graphics), to improve their understanding of the opportunities. We estimated that a good problem investigation with a verified root cause will not only eliminate the recurrence of that particular incident, but would also prevent at least 6-8 other potential incidents.
• A major push towards standardizing incident investigation methodologies, processes, templates and techniques  – Everyone knows that a common investigation approach with a common language makes a world of difference in how a company resolves its incidents. However, if you add to this common approach some simple-to-apply processes, templates with “worked questions”, additional benefits such as cross-silo collaboration, confidence in the approach, building on each other’s’ ideas and positive impact on attaining consensus can be easily realized.

Topics: Blogs - IT CSI IT Problem Solving ITRCA

Written by Mat-thys Fourie

Washington, DC, United States | Founder & Chairman of Thinking Dimensions Global Mr. Fourie is a thought leader on how IT professionals apply Incident Investigation techniques on a repeatable and sustainable basis within their organizations. His strength lies in customizing and embedding the various techniques within existing CSI, Incident and Problem Management practices.

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The Five Stages of DEI Maturity

• Ella F. Washington

Many organizations take big actions in the realm of DEI because of something they see another company do—such as publicly declaring themselves champions of people of color or setting an ambitious top-down DEI strategy across the firm. However, these grand stances usually fizzle out, leaving leaders frustrated and saying, “DEI work is too hard. It takes too long to see results.”

The fact is, DEI isn’t a short-term project, and a company making big moves before it has the right culture and structures in place is likely to fail, leaving marginalized employees and customers no better off and giving companies a reputation for hollow promises.

Academic research and the author’s experience working with firms on DEI strategy suggest that companies tend to follow predictable stages on their DEI journey. In this article, Georgetown professor and organizational psychologist Ella F. Washington describes the five stages: aware, compliant, tactical, integrated, and sustainable. She also includes questions for leadership teams to ask themselves. Understanding what stage your company is in can help you decide where to focus your energies most effectively and keep you from getting stuck.

How to move from promises to results

Idea in Brief

The problem.

Companies looking to make progress on diversity, equity, and inclusion goals often make big declarations or try to implement ambitious top-down strategies before they have the right culture and structures in place. Such efforts often fail, leaving marginalized employees and customers no better off and giving companies a reputation for hollow promises.

Academic research and the author’s experience working with firms on DEI strategy suggest that companies typically move through five stages: aware, compliant, tactical, integrated, and sustainable.

How to Use It

Knowing what stage your firm is in can help you decide where to focus your DEI energies most effectively and what questions your leadership team should be asking to keep you from getting stuck.

Since the murder of George Floyd, in 2020, I’ve spoken with countless CEOs and chief human resources officers as they responded to the racial violence they witnessed that summer. And I’ve noticed a pattern: Leaders first tend to express deep concern and then ask if their company is instituting all the best diversity, equity, and inclusion (DEI) programs. They are eager to know what other companies are doing and how their own efforts stack up. Many firms take action because of something they see another company do—such as publicly declaring itself a champion of people of color or setting a top-down DEI strategy across the organization. But these grand stances usually fizzle out, leaving leaders throwing up their hands and saying, “DEI work is too hard. It takes too long to see results.”

The fact is, DEI isn’t a short-term project, and a company making big moves before it’s ready will most likely fail to meet its objectives, leaving minority employees and community members continually marginalized. Moreover, doing so can give the organization a reputation for hollow, performative promises. Many companies that rushed to meet the moment in 2020, for example, pledged thousands of dollars to build racial equity but did not have a structure in place to support the implementation of new initiatives. As a result, they still haven’t made any progress in improving their employees’ and communities’ lived experiences.

There is good news, however. More than 40 years of academic research and my experience helping hundreds of companies on their DEI journeys have shown me that companies tend to follow predictable stages on the DEI journey in sequence. When they understand which stage they’re in, they can focus their energies on the right activities, making their DEI efforts more successful and making it more likely that they’ll keep progressing.

In this article I describe the five stages: aware, compliant, tactical, integrated, and sustainable. For each one, I include questions for leadership teams to ask themselves to focus their efforts and keep moving forward. Although there’s no one-size-fits-all DEI solution, a typical journey through these stages includes connecting top-down strategy and bottom-up initiatives around DEI, developing an organization-wide culture of inclusion, and, ultimately, creating equity in both policy and practice.

[   Stage One   ] Aware

For many companies, the process of being intentional about DEI begins with a trigger—for example, a lawsuit, being called out by investors, or a traumatic experience such as George Floyd’s murder. That gut punch of awareness can prompt soul-searching and a genuine desire to change course.

Companies entering the aware stage generally fall into one of two camps: successful older organizations that have never prioritized DEI or start-ups so deeply focused on survival that they’ve neglected to create strong human-capital practices. After a wake-up call, both camps often make high-minded public statements about their attitudes and intentions toward DEI. But what’s really needed at this point is for them to be honest internally—especially within the leadership team. Leaders should ask themselves:

Why does DEI matter to us personally? Understanding colleagues’ personal experiences of diversity or discrimination inside and outside the organization builds a necessary foundation of shared understanding and trust for further strategy work and for speaking with the broader organization about these topics.

Where do we want to go? Setting a collective internal vision for the company’s DEI work will help point you in the right direction as you get started. Leaders will have differing ideas of what DEI should look like, especially when they come from a broad range of backgrounds. So they must first agree on a vision of where to focus: Diversity of employees, having a better relationship with the community, building a more inclusive culture, and fixing the brand’s reputation are all appropriate goals. Ultimately, companies should be doing all these things, but when they are just starting out, they need a specific target.

A company making big DEI moves before it’s ready will most likely fail to meet its objectives, leaving minority employees and community members continually marginalized.

When setting goals, companies should take particular care to avoid benchmarking themselves against companies that may be at a later stage of DEI maturity. For example, the ice cream maker Ben & Jerry’s, whose cofounders are the longtime social-justice activists Ben Cohen and Jerry Greenfield, boldly stated, “We must dismantle white supremacy” on its corporate web page and social media accounts in 2020. That is laudable, but if a company hasn’t already built the structures and culture to act on such a stand—as Ben & Jerry’s had—it will appear performative. Instead of making sweeping statements, companies in the aware stage should choose a narrower, more tactical goal.

Iora Health, whose mission is to “restore humanity to health care,” is working to transform primary care. Since its founding in 2011, the Boston-based organization has opened 48 practices in 10 states and reduced hospitalizations of its patients by more than 40%. (It has since been acquired by One Medical, which Amazon recently announced plans to buy.)

In June of 2020 Iora’s cofounder Alexander Packard was shaken by the news of George Floyd’s murder, and he knew that it was affecting his teams as well. He spoke candidly with four Black leaders in the organization, asking questions about race and racism, subjects he had never broached with them before. He was surprised to learn that many Black and Brown employees had never felt supported at the company. He had always assumed that Iora’s mission—which led it to serve many people in marginalized groups—meant that it didn’t need an intentional approach to DEI, but he realized that wasn’t the case.

I led Iora’s full leadership team in a two-part conversation about its DEI vision. During the first part, leaders spoke of their experiences with race. Some acknowledged that they had been largely unaware of issues of race and privilege; others shared deeply personal experiences from their childhood and professional life. The second part of the conversation built on the emotional momentum of the first. The leaders admitted that they weren’t sure they were all aligned on the kind of diversity efforts they were looking for. They shared their own visions of what DEI should mean for the organization and then worked together to define what DEI would look like at Iora. They determined that for them, it meant serving a diverse patient population—including patients who might harbor racial biases—as well as supporting their Black and Brown team members. Navigating that tension has formed the basis of their DEI policies ever since.

[   Stage Two   ] Compliant

Companies need to meet many industry and government requirements for diversity, such as EEOC laws in the United States. Additionally, businesses that have been subject to DEI lawsuits may have agreed to certain settlement terms. Some companies might pursue voluntary compliance and compare their DEI goals with those of competitors. At the compliant stage the thinking is typically, We do DEI because we have to. It’s worth noting that a company could be compliant without ever going through the aware stage, but it would be ill-equipped to proceed any further without the foundational work done there.

Nearly a third of companies today find themselves in the compliant phase, according to a study of more than 10,000 knowledge workers in the United States, Australia, France, Germany, Japan, and the United Kingdom (see the exhibit “A Snapshot of Companies’ DEI Progress”). This is partly good news: There is certainly a benefit to compliance. Regulations and requirements can spark meaningful changes in organizations because their terms and goals are so concrete. Whether it’s talent selection, performance reviews, or diversity training and mentorship programs, companies are given specific direction on change. They often set up scorecards and use performance scores to determine leaders’ bonus compensation. And doing the work to fulfill the specific terms of a compliance settlement can help an organization rebuild a reputation tarnished by poor DEI practices.

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Still, it’s notable—and concerning—that many companies become stuck in this stage. Just because a company is compliant doesn’t mean its diversity initiatives are mature or connected with the organization’s overall strategy. Many leaders of firms in this stage have not done the soul-searching needed to make real changes to their cultures. And although their diversity numbers may be good at the frontline level, employees from minority groups may still feel unsupported or unable to advance. Furthermore, research has shown that without an inclusive culture, a diverse workforce will not yield the tangible benefits of teamwork, creativity, better problem-solving, and so on. To go beyond the compliant phase, leaders should ask:

Where can we set goals that are bigger than our compliance targets? Companies that have managed to move past this stage have used the requirements imposed by regulations not as end goals but as springboards for further efforts. For example, they push themselves to exceed their metrics for success or keep incentives in place long after regulatory requirements expire.

How can DEI help us to meet our other goals? Moving on from the compliant stage can be challenging because it requires the wholehearted buy-in of senior executives and managers who may never have experienced the kinds of discrimination you’re trying to fight. To get them on board, show them how DEI efforts can help your organization achieve its specific mission, values, and goals. While there is a risk that highlighting the business case for DEI obscures the ultimate ethical point that everyone should be treated with respect and have an opportunity to succeed, history has shown us the limits of moral conviction around DEI in the workplace.

In the 1990s the Denny’s chain of fast-food restaurants was mired in numerous racial-bias lawsuits and scandals. After first contesting the suits, Denny’s eventually settled with a large payout and a consent decree, which required the company to create written antidiscrimination policies, inform the public of those policies, provide training to all employees, and monitor and report any future incidents.

In 1994 Denny’s hired April Kelly-Drummond to lead its diversity initiatives; under her guidance the company surpassed the terms of its consent decree. For example, the settlement mandated that all employees attend diversity training within 90 days of joining Denny’s and attend a second session within 270 days; Denny’s tightened those requirements to 75 days and 225 days. In fact, the company’s strong performance led to its release from oversight by the Office of the Civil Rights Monitor a year early. After its release, Denny’s didn’t let up: It even placed a toll-free number in every restaurant to encourage others to help identify problems. The company also tackled bias in hiring beyond the scope of the original decree, broadened its recruitment efforts, and built a promotion pipeline. Further, it instituted an incentive structure around DEI goals. For example, 25% of senior management’s incentive bonus was tied to the advancement of women and minorities.

In the 30 years since the lawsuits, Denny’s has gone above and beyond the consent decree’s original mandate, and its whole culture has changed. The chain has recaptured sales, repaired its reputation in local communities, and been named one of Newsweek ’s best places to work.

[   Stage Three   ] Tactical

Organizations in the tactical stage have moved beyond meeting the rules imposed on them and are fully engaged in executing their own DEI initiatives, which tend to be bottom-up. These companies might have flourishing grassroots efforts such as employee resource groups (ERGs) and teams that institute their own DEI processes—perhaps community guidelines for handling microaggressions or appointed devil’s advocates in meetings to make sure diverse opinions are heard. There may be some top-down strategy or programming, such as a celebration of Pride month, but it is largely executed independently by individual managers. Companies at the tactical stage are on their way to changing their cultures: Employees at all levels may engage in tough conversations about bias and give one another feedback; groups may take care to improve diversity of thought in their decision-making.

Yet companies in this stage typically still lack a strategic DEI approach that drives the entire business. Uncoordinated efforts mean that one area of the organization may champion DEI efforts while other areas ignore them. Consider Nike: Its 1988 “Just do it” campaign famously featured commercials for all customers regardless of age, gender, or physical fitness level, and the company publicly supported Colin Kaepernick in 2018 after his protests against racial inequality and police brutality. But Nike also has a troubling history of DEI offenses. In 2003 the company settled a racial-discrimination lawsuit filed by 400 employees, and in 2018 it faced a gender discrimination lawsuit alleging unequal pay for women and a hostile work environment. As we might expect with a company in the tactical stage, Nike’s DEI efforts have been uneven, excelling in some customer-facing units but proving woefully inadequate in other areas. To better align their organizations, leaders should ask:

What’s our strategy? You need to start defining an overarching DEI strategy that brings all your company’s efforts together. Still, don’t shoot too high: Companies that are most successful in implementing a new DEI strategy home in on a short list of priorities that can be connected to short- and long-term goals and metrics.

Where do we need to standardize? Do different units approach basic practices such as hiring differently? If some departments have made progress in creating an inclusive culture, learn from them and replicate their policies.

How can we connect DEI work up and down the organization? A feedback loop between team members, managers, and senior leaders is critical to the success of a DEI strategy. Executive buy-in can help clear cultural obstacles within a company and build a communal sense of responsibility for programs. Holding regular meetings between senior leaders and the leaders of grassroots efforts like ERGs can give you a good sense of whether your DEI efforts are improving corporate culture.

What is our full sphere of influence? Your company touches people beyond its employees: Take a close look at the impacts of discrimination or inequity across internal and external stakeholders, including employees, customers, partners, suppliers, shareholders, competitors, and your community. Look for ways to reduce existing inequities and build inclusion with those stakeholders as well.

The productivity-software firm Slack, which is in the tactical stage, has taken a decentralized and often employee-led approach to its DEI efforts. The company has encouraged employees to create an array of identity-based communities, and thus its DEI efforts are in large part the work of ERGs.

The work of DEI is never done. Without continued vigilance, even organizations in the sustainable stage can slide backward.

To ensure that these groups are more than social venues or places for commiseration, company leaders have made a concerted effort to regularly connect with them. Their monthly meetings uncover employee concerns and give ERGs early insight into the direction of the company and an opportunity to influence that path. ERGs also serve as a testing ground for new process ideas. ERG sponsors, meanwhile, are better able to understand the needs of employees and can give the groups greater exposure across the organization.

Slack has now begun to standardize some DEI processes. After the company created guidelines for interview questions to ensure that each candidate was treated similarly, regardless of the interviewer, the number of women in technical roles grew by almost 5% in a year. And Slack has brought its DEI gains to its larger sphere of influence with the introduction of Slack for Good, an initiative that aims to increase the number of people from historically underrepresented communities in the technology industry.

[   Stage Four   ] Integrated

Once an organization has aligned internal and external efforts and connected top-down and bottom-up efforts, it has reached the integrated stage. An integrated organization has defined its DEI strategy, developed a culture of inclusion, and taken a close look at the impacts of discrimination and inequity across its internal and external stakeholders, seeking to address those challenges. Companies in this stage can truly say, “DEI is part of everything we do.”

Despite this achievement, humility is the most common attribute of companies in this stage. For most, reaching this level has required experimentation to learn what works and what doesn’t. Leaders of companies with long-standing and celebrated DEI programs must be modest enough to change course if what they are doing isn’t working.

Leaders also worry that their success or even their efforts may be short-lived. DEI advances can often be linked to a particular event, to favorable market conditions, or to a particular leader’s passion. To move on from the integrated stage, leaders must ask:

What systems and structures do we need to create? The current passion for and attention to DEI needs to be encoded in the way that the company works so that it persists beyond one leader’s tenure or the current market cycle. The company needs to build programming that removes the burden of continuing the drumbeat for DEI from the shoulders of people in underrepresented communities themselves.

Why not? To move into the sustainable stage, companies must challenge the status quo and do things that simply weren’t done before. They must also regularly evaluate the effectiveness of what they are doing for its impact on people and the business.

A common assumption I encounter in my work is that minority-owned businesses don’t need to put as much effort into DEI. This assumption couldn’t be more wrong, for many reasons. DEI goes beyond representation alone. Every organization, no matter its demographic makeup, must be intentional about the equitable nature of its systemic structures, such as hiring and promotion, and must focus on making the culture diverse, equitable, and inclusive.

Uncle Nearest is a whiskey distillery founded by Fawn Weaver, a Black woman who was inspired when she read the story of Nathan “Nearest” Green, an enslaved man in Tennessee who applied water-filtering techniques he had learned in West Africa to whiskey and became the first master distiller for Jack Daniels. Weaver launched a new distillery to honor his name; in a few short years it became the fastest-growing whiskey brand in the country and is now the best-selling African American–owned and African American–founded spirit brand of all time. Weaver built the company from the start with a clear DEI strategy, a goal to change her larger industry, a culture of confidence and self-expression, and a requirement for diversity in hiring.

But when Weaver tried to fulfill her vision for diverse recruitment, she couldn’t find enough Black talent to hire. “One of the things I realized was that if I wasn’t getting résumés of African Americans, then nobody in the industry was,” she explains. “So the question became ‘How do we get more African Americans interested in the spirit business? How can we be creative about building this longer-term pipeline?’” Weaver broke traditional hiring rules to achieve her goals: For example, she left positions open longer than her competitors did—up to two years—to maintain demographic diversity on her teams. Her willingness to challenge the status quo and think big has helped her to establish Uncle Nearest and ensure that its mission and commitment to DEI will outlive her tenure at the company. Uncle Nearest, founded in 2017, is still a new company, so it’s hard to say it has reached the sustainable stage yet, but it is on its way.

[   Stage Five   ] Sustainable

Organizations whose DEI efforts are deeply embedded in their corporate DNA have entered the sustainable stage. Their DEI efforts pass stress tests such as economic challenges and changes in leadership, and their leaders have a mindset of continuous improvement.

Take the technology giant Intel. In 2015 then-CEO Brian Krzanich announced a $300 million five-year plan to bring the company’s workforce to “full representation” by 2020, initiating programs such as a $4,000 bonus for employees who successfully referred candidates from marginalized groups and a $5 million partnership to develop a high school computer-science curriculum for the Oakland Unified School District. In just six months the number of female and minority hires had surpassed the initial 40% goal for the year. Over the course of Krzanich’s tenure hires from underrepresented communities increased by 31%, and Intel’s female workforce increased by almost 43%.

But in 2018 Krzanich resigned after violating a non-fraternization policy with a colleague. Such a charged change in leadership could have meant an end to the policies championed by the outgoing leader. But Intel’s next CEO, Robert (Bob) Swan, continued to set ambitious DEI goals. For example, in 2020 Intel pledged to increase the number of women in technical roles to 40% and to double the number of women and underrepresented minorities in senior roles by 2030. Swan left Intel in 2021, but that hasn’t slowed Intel’s commitment to DEI. According to its Corporate Sustainability Report 2021–2022, the company extended its Inclusive Leaders program and integrated the inclusion content into its Manager Academy training, which it began rolling out to its 13,000 managers. In 2021 it required all hiring managers to receive training in inclusive hiring practices. Further, it has initiatives in place to “increase the number of women hired for technician, engineering hardware and software roles” and has tied increased representation of women in technical roles to an annual performance bonus goal for all employees in 2022. DEI has become integral to its culture.

The work of DEI is never done. Without continued vigilance, even an organization that has designed systems and structures to remain sustainable through change can easily slide backward. True commitment to DEI requires continuous improvement by reassessing strategies and initiatives as the organization grows and as the world changes. For example, if you open your first-ever office in India, you will have new DEI challenges to solve. The same is true if some event in the world shines a bright light on inequity that you hadn’t known was there.

Regardless of which stage you’re in, knowing where you are on your DEI journey can help you focus on the right questions to keep moving forward.

Ella F. Washington is the author of The Necessary Journey: Making Real Progress on Equity and Inclusion (HBR Press, November 2022), from which this article is adapted.

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• Ella F. Washington is an organizational psychologist; the founder and CEO of Ellavate Solutions, a DEI strategy firm; a professor of practice at Georgetown University’s McDonough School of Business; and a cohost of Gallup’s Center of Black Voices Cultural Competence podcast. She is the author of The Necessary Journey: Making Real Progress on Equity and Inclusion (HBR Press, November 2022).

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CSOC 2021: Software Engineering and Algorithms pp 110–118 Cite as

Maturity Models, Challenges and Open Issues

• Tumisang Akinpelu   ORCID: orcid.org/0000-0001-5081-9901 10 ,
• Rene van Eck   ORCID: orcid.org/0000-0001-8683-4396 10 &
• Tranos Zuva   ORCID: orcid.org/0000-0001-9579-3899 10  
• Conference paper
• First Online: 20 July 2021

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 230))

Maturity models enable evaluation of the business process management maturity in organizations and assist to benchmark by revealing the opportunities to improve business processes. A very large number of academics have researched the maturity models but there is a need to correlate the challenges and open issues. The maturity models have challenges that need to be explored in detail in order for organizations to be able to properly implement the models properly to enjoy the benefits thereof. This paper reviews the maturity models in literature and highlights the challenges . The research found that the use of different models produce different results in the same organization and some of the existing maturity models are complicated and require specialized skills. It has been found that it is imperative to standardize the models so that they are able to measure the maturity of organizations in an understandable and reliable way. Despite the challenges that may exist in using maturity models, the organizations can still measure the maturity levels of their organization using the models available.

• Maturity models
• Maturity model challenges
• Maturity model open ıssues
• Maturity model challenges and open issues

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Tumisang Akinpelu, Rene van Eck & Tranos Zuva

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Akinpelu, T., van Eck, R., Zuva, T. (2021). Maturity Models, Challenges and Open Issues. In: Silhavy, R. (eds) Software Engineering and Algorithms. CSOC 2021. Lecture Notes in Networks and Systems, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-030-77442-4_9

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The Data Maturity Model: Master Your Data in 5 Easy Stages

When organizations fail to utilize their data fully, they overlook business-critical insights, resulting in less informed decisions and missed opportunities.

With data maturity, you can transform every click, view, and interaction into important insights that inform your marketing strategies.

This article looks into the data maturity model’s various stages, offering insights to help businesses transition from data novices to experts.

⚡ The majority of marketers feel like they either have a novice or intermediate understanding of how to connect their data sources across customer journeys.

What is Data Maturity?

Data maturity measures the sophistication and effectiveness of how a company collects, manages, analyzes, and uses data to guide decisions and strategies.

💡 Research from Heap revealed that data-mature companies achieve 2.5x better business outcomes across the board for revenues and profits, NPS (Net Promoter Score), lifetime customer value (LCV), and overall operational efficiency.

Rather than relying on gut decisions or defaulting to traditional strategies, data-mature companies use qualitative and quantitative data to make decisions about their business.

Example: Netflix collects viewing data from its subscribers using sophisticated algorithms to recommend shows and movies tailored to individual preferences.

Using data maturity in programmatic advertising, your company could analyze the purchasing behaviors of your high-spending customers and then target lookalike audiences with personalized ads. This optimizes ad spend and increases your potential conversion rate as you’re targeting not just any audience but the right one.

The 5 Stages of Data Maturity

A company’s data maturity is characterized by five stages: initial, managed, defined, measured, and optimized. These stages help organizations assess where they stand in their data journey and the steps needed to progress further. 

Let’s examine the typical stages of data maturity:

1. Initial Stage

The first stage centers on discovering the customer data at your disposal, also called First-Party data . Data is collected and stored, but you may not understand its potential and have no standardized processes in place for data management.

Within many organizations, silos between teams and functions blur the road toward a unified approach to data maturity. Consequently, each team operates with its interpretation of data best practices, leading to disparities in the way different teams analyze disparate data points using various tools.

At this initial stage of data maturity, decisions are often made without data support, and initiatives lack proper measurement for assessing their impact.

What’s one of the biggest challenges companies have with their data?

“When data is scattered across departments, from marketing to web development, gaining approval and access becomes cumbersome. This misalignment is why many companies don’t utilize their internal data optimally.

For instance, when we need to get a tracking pixel placed on a website for our tool, Axon, and the Media Planner informs us that it’s owned by the Web Dev team, we could end up communicating with multiple stakeholders before we even begin implementing the task.”

2. Managed Stage

As your data maturity journey progresses, you’ll establish basic data management practices. These processes include data collection, storage, and basic reporting. However, there might not be a comprehensive strategy for data utilization, and data remains primarily descriptive.

Your leadership recognizes the value of exploring data-driven tools, improving data utilization, and identifying existing data gaps. Leaders prioritize investments in data collection and management, establishing best practices for roadmap planning and post-launch analysis. 

Success metrics are integrated into project briefs and campaigns, and post-mortem analyses become standard. Team members receive fundamental analytics training and access to self-service tools for real-time problem-solving.

3. Defined Stage

You’ll formalize your data strategies during this phase, emphasizing data quality and governance. This involves establishing transparent data management processes and defined roles within the organization, with a central goal of enhancing the reliability and accessibility of your data.

Data takes center stage, driving the core of your strategies and operations. Each initiative is powered by a shared ambition to realize tangible business impact through the prism of data-driven decision-making. Teams are increasingly skilled at harmonizing digital experiences with critical business KPIs, ensuring data is pivotal in every facet of your organization’s endeavors.

Collecting, analyzing and understanding your marketing data is critically important so that you can make data-driven decisions. If structured properly, your data will allow you to start focusing on bottom funnel conversion activities to gauge your ROI and CPA rather than focusing on top funnel metrics like CTR and Viewability. It also lays the groundwork for more advanced analysis like Marketing Mix Modeling and creating a single holistic attribution model that attributes credit for each final conversion event or dollar of revenue to the appropriate marketing efforts. By analyzing this data, you can make informed decisions about where to allocate your marketing budget, which channels to focus on, and which strategies are most effective.

4. Measured Stage

The emphasis shifts from data collection to meticulous performance metrics tracking and optimization. It’s about making every piece of data count and extracting maximum value from your information resources.

You’re not just accumulating data; you’re harnessing its potential to unearth valuable insights. These insights become the cornerstone of your strategies, enabling you to make well-informed decisions that drive growth and innovation. 

5. Optimized Stage

You’ve reached the pinnacle of data maturity when data becomes a strategic asset driving innovation, customer experiences, and business growth. Advanced analytics and machine learning extract deeper insights, leveraging data to make real-time decisions.

Everyone across your teams looks at the same numbers and dashboards. At this point, your focus shifts to fine-tuning your data strategy.

The Types of Data Collected for Data Maturity

Organizations gather rich, direct, and valuable First-Party data from their audiences throughout their data maturity journey. Using this data is pivotal for successful data maturity.

Some common First-Party data types include:

• Customer Relationship Management (CRM): Contains customer interactions, preferences, and contact details.
• Transactional Data: Records business transactions like purchases, sales, and product and inventory levels.
• Web Analytics: Tracks website traffic, user behavior, and engagement, aiding online optimization.
• Email Campaigns: Measures open rates, click-through rates, and conversions.
• Social Media Data: Involves user interactions, comments, shares, and sentiments for brand monitoring.
• Survey/Feedback Data: Offers insights into customer satisfaction, product feedback, and improvement areas.
• Loyalty Programs: Tracks customer loyalty and rewards program engagement.
• Customer Support Data: Records interactions, identifying customer issues and service improvements.
• App Analytics: Monitors user behavior within mobile apps.
• In-Store Metrics: Analyzes foot traffic, sales patterns, and retailer store performance.

Incorporating First-Party data into your data maturity journey ensures compliance with evolving data privacy norms and offers unparalleled insights into your customer base.

📚 Related Article: What Is First-Party (1P) Data? A Guide to Data-Driven Marketing : First-Party data collection can be overwhelming, so we made this guide to make it easier for you.

Your First-Party Data Should Help You, Not Frustrate You.

Don’t let overwhelming or disorganized data stand in your way. At KORTX, we make it simple. We help businesses like yours uncover valuable insights from their data, leading to smarter strategies and better results. 

The Importance of Organization & Cleansing Data

Data organization and cleansing are pivotal to accurate, reliable, and actionable data throughout the data maturity journey.

Let’s explore how these aspects relate to key areas within an organization:

1. Decision-Making

Clean and organized data gives decision-makers the confidence that their choices are based on accurate information.

Example: A programmatic advertising agency utilizes clean data to make real-time decisions on ad placements. Accurate data ensures their bids are strategically placed, maximizing their client’s return on investment (ROI).

2. Personalization and Segmentation

For marketing personalization segmentation and customer engagement, data must be organized to send the right message to the right audience.

Example: An e-commerce platform uses clean customer data to segment users based on their purchase history. This allows them to send personalized product recommendations and tailored ads, increasing customer engagement and sales.

3. Customer Journey Analysis

A well-structured dataset allows organizations to track and analyze the entire customer journey, identifying pain points and opportunities for improvement.

Example: A travel booking platform uses programmatic advertising to re-engage users who abandoned the booking process. Clean data helps track user interactions across devices, allowing them to retarget potential customers with tailored ads and incentives.

4. Compliance

Data cleansing ensures that sensitive customer information is handled in compliance with data protection regulations, reducing the risk of legal and financial repercussions.

Example: An ad tech company ensures that user data used for programmatic advertising complies with GDPR regulations. Clean data practices help them avoid legal issues and fines while maintaining user trust.

5. Efficiency

Clean data streamlines processes and reduces the time and effort required to access and analyze information.

Example: A manufacturing company centralizes its product data in a clean and structured database. This simplifies product information retrieval, streamlines production processes, and accelerates time-to-market.

6. Monetization

Data accuracy and quality are paramount for organizations aiming to monetize their data.

Example: A media publisher leverages programmatic advertising to monetize its website traffic. Clean data on user demographics and behavior allows them to offer highly targeted ad inventory to advertisers, resulting in increased CPM rates and revenue.

Why is data maturity important for companies wanting to run advertising campaigns?

“Data maturity is extremely critical for companies aiming to run successful advertising campaigns. Just having data isn’t enough. Companies have to understand, process, and employ their data in an organized way to target the right audience, craft compelling messages, and allocate budgets efficiently. 

A mature data approach makes sure that advertising decisions are rooted in insights rather than assumptions, leading to campaigns that resonate deeply and offer a tangible return on investment.”

Where Will Your Data Go?

The destination of the data maturity journey typically involves aggregating your data back into a centralized system, such as a Customer Relationship Management (CRM) platform or a dedicated database for easy organization. This aggregation is the foundation for further data analysis, visualization, and decision-making. 

However, choosing between a CRM and a dedicated database depends on the organization’s complexity, expertise, and specific needs.

1. CRM Aggregation

Aggregating data into a CRM system offers a comprehensive perspective on customer interactions and relationships. This approach is beneficial for organizations prioritizing customer engagement and relationship management.

CRM systems often feature integrated visualization and reporting tools, facilitating easier insight derivation.

Some Examples of CRMs:

• Salesforce: A widely-used cloud-based CRM platform that offers tools for sales, service, marketing, and more.
• HubSpot: Known for its inbound marketing tools, it also offers comprehensive sales and customer service functionalities.
• Zoho CRM: Offers sales automation, marketing automation, analytics, and multichannel communication tools.
• Pipedrive: Focuses on sales management and pipeline management.

2. Database Aggregation

Database aggregation is most suitable for organizations with intricate data demands or those desiring custom analytics. Dedicated databases support advanced analytics, machine learning, and bespoke visualization tools.

These databases allow for enhanced flexibility in terms of data storage and retrieval.

Some Examples of Databases:

• MySQL: An open-source relational database system.
• PostgreSQL: A powerful, open source object-relational database system.
• Redis: An in-memory data structure store used as a database, cache, and message broker.
• Elasticsearch: An open-source search and analytics engine designed for horizontal scalability, reliability, and real-time capabilities.
• Snowflake: A cloud-based data warehousing solution that separates storage and compute resources for scalable and concurrent data operations.

Why is data maturity important for businesses of all sizes?

“The most persistent problem in using data, really for any purpose, is being able to trust that it accurately and reliably represents phenomena that the data is supposed to be capturing. In my experience, the only way to have that trust is to have a program where you understand where you company sits on a data maturity program. You want the maturity of the data program to match the potential value of the data. Otherwise, you run a very real risk of not understanding the risks associated with any given application of the data.

Each company has to do a risk assessment to understand where their particular weaknesses and exposure lies. And then assess if moving up the maturity curve in a particular area is going to mitigate that risk. In the end, I think of it as a cost/benefit thing. If there is substantial financial or reputational risk (or other kinds of risk) that can be mitigated by improving your data maturity, you should do it.”

CRM vs. Database Aggregation

Businesses often choose between CRM systems and dedicated databases, each presenting unique advantages and challenges. 

Here’s how the two compare:

Complexity:

• CRM: Typically more user-friendly and ideal for organizations with limited technical expertise or smaller scale.
• Dedicated Databases: Require more technical knowledge but promise increased flexibility.

Scalability:

• CRM: Might encounter challenges handling extensive data volumes.
• Dedicated Databases: Better scalability to cater to growing data needs.

Customization:

• CRM: May face restrictions adapting to distinct data needs.
• Dedicated Databases: Offer broad customization and system integration opportunities.

How to Determine Your Organization’s Data Maturity Stage

Understanding your current position on the data proficiency spectrum is crucial for charting the next steps in your data journey. 

To gain clarity, engage with your team with these probing questions:

• Where is your data currently stored for each team?
• What metrics or KPIs do you use to gauge the success of marketing initiatives?
• Is your team able to seamlessly access and analyze data? 
• How promptly can they derive insights regarding initiative success?
• Is your team adept at integrating qualitative and quantitative data into their analyses?

Reflecting on these questions will pinpoint your organization’s data maturity and foster a culture of continuous improvement and data-driven decision-making. Remember, the journey to data maturity is iterative and requires regular introspection.

Navigating the Complexity of Data Maturity

Collecting, managing, and successfully using First-Party data can be a challenge for many organizations. 

At KORTX, we can assist you in your data maturity journey. We offer a range of services and solutions to help you with your data needs, like helping assess your current data maturity, setting future data-driven goals, and helping bring together different data streams.

With Axon Audience Manager , our advanced customer data platform (CDP), we make it easier for you. Axon combines varied data sources into one cohesive dashboard, enabling you to maximize the full potential of your First-Party data easily.

🔍 Case Study: Trustmark Bank : Discover how the KORTX team leveraged Axon Audience Manager’s First-Party data to identify prime leads, achieving a staggering 98% video completion rate, 90% listen-through rate, and a 0.2% click-through rate.

Data That Works For You

As evidenced by leading companies, high data maturity translates to more informed decisions, heightened business outcomes, and a competitive edge in the market. 

Therefore, businesses must assess, nurture, and optimize their data management practices to truly realize the immense data potential and confidently navigate the future. The journey from initial data collection to optimized utilization might be complex, but the rewards are undoubtedly transformative.

Don’t Let Your Data Hold You Back

At KORTX, we’re experts in turning your data into business decisions that matter. If you want to get more from your data without getting lost in the technical details, we’re here to help.

Eric Lee is the Co-Founder and COO at KORTX.

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