Systems diagnosis tools and techniques – Part One
Systems diagnoses and solutions are both the answer to a lot of what is wrong with corporate performance – and a source of the problem at the same time. Most issues around strategy execution and organizational performance have foundations that spread across different parts of the system. Yet way too often, the solutions that are tried are too narrow and fail to properly address the true root causes and interdependencies that are endemic. Too many approaches to improving performance fail to take enough of a systems view, or apply it in the right way.
When I wrote my book Strategic Analytics eight years ago, this was the fundamental problem I was focused on: how to get people to ask the right questions and apply the right kind of diagnostics to identify the right solutions. I was hardly the first, and certainly won’t be the last, to call out deficiencies with how we approach finding the right solutions to organizational performance.
The history of such tools is long and storied, and includes:
- Deming’s focus on quality and systems tools, which became the foundation for total quality management and the Toyota Way
- Design thinking
- Six Sigma (and Lean Six Sigma)
- Business process reengineering
Comparing and contrasting these different approaches requires an entirely different article, for another time. Here I’m going to address the common threads in these approaches, which span over seven decades of development and implementation.
Systems diagnosis is one of the most important, yet greatly underutilized, tools for improving organizational performance and strategy execution. It is both everywhere – as evidenced by so many tools that have been developed over the years – and glaringly lacking at the same time. Lacking because, despite so many people having been trained in various methods over the years, day in and day out, people in key leadership and project management roles fail to be as comprehensive as they need to be in carrying out their work.
Take a broad and comprehensive view of the issue
Beware the leader who is convinced they know exactly what the solution is to the problem. Watch out for competing objectives and conflicts among leaders in different parts of the system. Zoom in and out. Look left and right, up and down. Be aware of interdependencies among the parts of the system. Focus on perennial problems that never seemed to get solved fully in the past. Check for unintended consequences of what you want to change.
These are some of the coaching guidelines that are common among systems diagnostics. If you do all of them, you will greatly increase the chances you will get to the bottom of what’s challenging your organization’s performance.
In this first installment, I will address the first half of these guidelines.
Beware the leader who is convinced they know exactly what the solution is to the problem. Watch out for competing objectives and conflicts among leaders in different parts of the system. These two points are related. When a leader comes to you and is absolutely sure they know not just the problem to be addressed, but which solution to apply, more often than not, they are at least a little incorrect. They usually have failed to grasp all the potential root causes for the performance problem. So while their identified solution may be appropriate to apply, additional work is almost always needed to make sure that is the correct solution, and whether other changes are needed at the same time to fully address the issue.
Part of the reason why you cannot just trust what the leader tells you is that, unless they are the CEO, they do not have responsibility for the complete end-to-end business processes that cross all departments, functions and business units. Because they are responsible for only a subset, chances are they are looking at the issue with too-narrow a focus that takes into account what they personally are responsible for, and downplays what their peers in other parts of the business are responsible for.
Zoom in and out; look left and right, up and down. The focus here is on the same thing: making sure you are not looking too narrowly or widely when diagnosing the performance problems.
This guidance can be traced back to the work of systems diagnosis pioneer W. Edwards Deming who was trying to solve the problem of how to improve quality in manufacturing. When he was doing his early work in the 1950s, a main challenge was reducing errors in manufacturing assembly lines – the ones that had been created a half century earlier by Henry Ford and Frederick Taylor.
The initial assembly lines created by Ford and Taylor were modern engineering marvels, and they set the industry standard for decades and helped propel the industrial revolution. Yet over time it became apparent that consistent quality was difficult to achieve under that work design. To determine the sources of the quality problems, Deming had to “zoom in” to look at how the work was happening at the job level across all the different jobs on the assembly line. After zooming in to the job level, he then “zoomed out” and asked the question, if the work were reorganized from narrow jobs into self-managing teams responsible for a larger part of the work, would that solve the quality problems? (The answer, as history has demonstrated, was a resounding “yes.”)
Note that zooming in from the product level to the job level is like “looking down” from the product to its subparts. Zooming out from individual jobs to multiple roles that assembled a compete subpart of an automobile, such as the engine, is like “looking up” from individual jobs to groups of jobs. So “zooming in” and “looking down” are the same, just as “zooming out” and “looking up” are.
“Looking left and right” is a way of pointing out that any one job or any one team does not operate in a vacuum. The job/team has to integrate with others: the jobs/teams that do the work immediately before and after. So if you are examining issues that appear to be rooted in one job’s performance, you need to understand how the work of that one job integrates well (or not) with the work that came immediately before and which follows immediately after.
Be aware of interdependencies among the parts of the system. Looking left and right at the workflow addresses interdependencies of the work with adjacent parts of the system that come immediately before and after. Beyond those immediate interdependencies, there are others if you zoom further out to look at the entire end-to-end business process.
Pushing on a balloon. Playing whack-a-mole. These are two metaphors that call out potential interdependencies in the system.
When you push on a balloon, whatever part you are not holding directly will bulge or expand out – you cannot push on all sides of the balloon simultaneously to prevent the bulging. And you can never really accurately forecast which parts will expand. Whack-a-mole has a similar connotation: you never can tell where the next problem will arise.
The power of systems thinking or diagnostics is that you take a step back to consider why things are happening the way they are. And usually there are interdependencies that can help explain which parts of the balloon will bulge out – and where on the playing field the next mole will pop up in the game of whack-a-mole.
For example, the recent supply chain travails created by the Covid-19 pandemic are a classic case requiring systems diagnostics to identify where the bottlenecks and shortages were created, and identify options for overcoming them. One of the first things that many consumer products companies pivoted towards was producing a much smaller number of options for products which, over the years, had grown in scope and complexity. So rather than have, say, 17 different shades of white paint (or variations of shampoo or salty snacks or chocolate), a company might pare the options back to the 3-5 which traditionally were the biggest sellers.
The benefits of paring back product options were many:
- Fewer products options produced, which simplified operations, reducing the number of issues that had to be dealt with internally, in an environment that suddenly had become much more uncertain. This made the jobs of staff simpler, which was important in an environment where employee absence and turnover risks had suddenly increased dramatically.
- The simplified operations included dealing with far fewer external vendors and suppliers of the inputs needed to produce their products, which lowered the complexity of dealing with disruptions that were happening at potentially every point in the supply chain. This included reduced cost of carrying excess inventory of both inputs and finished products, compared to how much extra inventory costs would have been needed to maintain the pre-Covid full lineup of product options.
The system-level interdependencies here included:
- Disruptions in the operations of vendors and suppliers due to their labor shortages
- Disruptions in the distribution system for the inputs from vendors and suppliers, and for the outputs of the company’s own operations
- Internal labor and product disruptions at any point within the internal operations of the company, which would ripple throughout the entire system
The rest of the systems diagnosis coaching guidelines are addressed in part two.
Systems diagnosis tools and techniques – Part Two
In Part One I covered the need to:
- Beware the leader who is convinced they know exactly what the solution is to the problem. Watch out for competing objectives and conflicts among leaders in different parts of the system.
- Zoom in and out; look left and right, up and down.
- Be aware of interdependencies among the parts of the system.
In Part Two here I address the rest of the systems diagnosis coaching guidelines:
- Focus on perennial problems that never seemed to get solved fully.
- Check for unintended consequences of what you want to change.
- Look for root causes, not just behavioral indicators
And I also address cultural resistance to systems solutions.
Focus on perennial problems that never seemed to get solved fully. A good systems diagnosis is neither easy nor quick. It takes time and resources to fully examine all the key parts of the system that combine together to enable organizational performance. So it’s best to focus systems diagnosis on challenges that are larger and have bigger impacts on revenue and profits.
On the plus side, there typically is no shortage of such challenges. Most of the large complex challenges that bedevil strategy execution are perennial ones, meaning they have been around for a while and are likely to persist unless something very different is done about them. The issue could be productivity in operations, customer retention, the speed of innovations, attraction and retention in key roles, or any of a host of other challenges that keep your leaders up at night.
The good news is that because these challenges are at the heart of properly executing your strategy, there is no shortage of things that have been tried before, and thus lots of evidence on what has been attempted. Previous attempts may have included changes to compensation, training, decision making processes (such as RACI), recruiting processes, and more. Each provides a piece of evidence on what is and is not driving behavior and performance, which can help guide you to look at either something entirely different, or a combination of factors that might not have previously been addressed – because there often are multiple things that need to be addressed at the same time.
For example, if motivation and productivity appear to be lagging, leaders often will say that better candidates need to be identified for hiring or internal promotion into the role. Yet a persistent gap, even in the face of trying to find better candidates, usually means that recruiting alone can’t solve the problem. Usually, a combination of different aspects of job (re)design need to be evaluated and potentially applied, including altering the workload, improving compensation, addressing skills gaps, increasing communication and feedback, fostering better teamwork, and more.
The other point about addressing perennial problems is that, because they have been around for a while, it’s easier to take the time that’s needed to thoroughly evaluate the different options. This may not seem to be the case at first, because issues to be addressed usually are presented as so urgent, needing solutions in a short amount of time. The urgency is created by leaders who are trying to improve performance on KPIs and are impatient about waiting for the time needed to do a thorough diagnosis.
The answer is to do whatever you can in the requested urgent time frame, and suggest initial potential improvements with a big caveat. You need to point out that multiple attempts have been made in the past to improve performance, with mixed success. So any decisions made in haste are likely to have the same impact as has historically been the case: there may be some marginal improvements but the root causes almost certainly won’t be addressed, because insufficient time and resources were devoted to the diagnosis.
Laying out all the issues that need to be addressed sets up the work that should immediately follow: taking the time needed to do the full systems diagnosis. This may have to occur a bit “under the radar,” while the leader who raised the issue works through the initial potential improvements you suggested.
Proceeding with doing the full diagnosis after delivering the initial potential improvements is a time-honored way of getting to the root causes. Doing this also positions you to provide better insights the next time that same leader, or a different one, raises the issue again. Given the perennial nature of the issue, it’s virtually guaranteed that whatever is implemented based on the initial potential improvements won’t solve all the underlying challenges. So the performance problems should persist.
By pursuing the full systems diagnosis in the months that follow, you will set yourself up to be perfectly positioned to provide the correct answers when it’s raised the next time by leadership.
Check for unintended consequences of what you want to change. Systems-level challenges almost by definition are never solved by quick assessments the first time through. Even though a potential solution may seem like a good idea – such as the example of choosing better candidate quality which I addressed above – you need to take time to check the robustness of your diagnosis to make sure you didn’t miss anything important.
One important stress test is to examine any recommendation you are thinking of making for unintended consequences. For example, introducing a new compensation-based incentive program will always get people to pay attention and change their behavior. But you have to check to make sure that the actual behavioral changes are consistent with the desired goals – because compensation alone is almost always too blunt an instrument to drive the desired changes. And as Steve Kerr (the management practitioner, not the basketball coach) noted back in 1975, using compensation to try and change behavior usually leads to a large number of unintended consequences because the behaviors we want to change typically are not the ones that can be easily monitored and used to hold people accountable.
There are many cases of unintended consequences we see around us wherever we look.
- A company reorganizes a division to increase performance along a set of KPIs for new customers and markets; only to fall short on meeting those KPIs while losing business from legacy customers who no longer feel the company is meeting their needs.
- A company cuts back on personnel to increase margins and financial leverage, and then finds itself unable to cope effectively with unforeseen macroeconomic shocks (such as Covid-19).
- A company makes a big shift to gig and “on demand” workers to make its labor cost more variable, only to discover that ownership over key tasks and deliverables among frontline employees falls substantially, which increases the time and resources needed to keep key customers happy.
These are all real-world examples of why best intentions in (re)designing a work system are never enough to ensure the right alignment and results are achieved – because of the unintended consequences.
A similar point revolves around the widely known mantra, “Culture eats strategy for breakfast,” which is a classic example of unintended consequences. Even when everyone can see that markets are evolving and therefore a new strategy is needed, the organization today is set up with a highly complex and interdependent system that is optimized to produce the legacy products and services, not the new ones needed for the strategy to succeed. Saying “culture eats strategy” is shorthand for:
- There is an existing, well-designed and integrated set of decision rights, roles and responsibilities, rewards and benefits, business processes, talent management processes, etc.
- If you try to change only one part of the system, the interconnectedness and interdependencies among the system elements will inevitably pull things back to the status quo. New strategies require new capabilities that the organization has not yet successfully built.
And while most people might throw up their hands at the prospects of trying to change the culture – because it can seem so intractable and hard to change – taking a systems approach shows the things that need to be addressed and aligned to produce culture change. Examples of the systems approach include org design models (Galbraith’s Star; McKinsey’s 7S; etc.) and work design models such as the one based on Capability, Opportunity (job design) and Motivation.
The key is to start with comprehensive systems models such as these, work through all the elements that are needed to change to create the new organizational capability, and make sure everything is aligned and consistent following the changes. It takes a lot of time and energy – and diligent follow-up – to make it work. But doing so can actually change the culture, and provide a shining exception to the culture-eats-strategy mantra.
Look for root causes, not just behavioral indicators
Too-quick diagnosis often falls for the trap of focusing on observed behaviors, rather than the potential underlying factors that cause the behaviors.
A simple yet classic version of this is the over-emphasis on leadership competencies, which are usually expressed in terms of observed behaviors. The problem is that most leadership competency models exclude critical skills such as judgement or quality of decision making – because they are not easily observable. Instead, the models emphasize things like communication style, coaching versus micromanaging, openness to new ideas or opposing views, and many more; all of which can be important things we want in our leaders.
So how can we address all the factor that drive good leadership, not just the parts that are more-easily observed and included in competency models? That requires taking more of a systems approach, including looking for indirect evidence of how the leaders perform on their own and working with their peers and other parts of the organization.
The hyper focus on employee engagement is another example of over-emphasizing certain types of observable or measurable behaviors at the expense of looking for root causes with more of a systems approach. Examining employee engagement via surveys is a best-in-class approach that minimized bias in measuring how people feel … yet that approach does nothing to address the two other core contributors to employee performance: their capabilities and the job design. (This is the COM model referenced above: Capability, Opportunity/Job Design, and Motivation.) Organizations everywhere, with the help of an army of survey consultants, spend too much time and energy focusing on measured employee engagement (motivation), and nowhere near enough on how the work design impacts both motivation and performance.
The same can be said for teams and team performance. If there is discord on a team, leadership knows that something needs to be addressed and will (usually) jump to action. Yet outward signs of disharmony are not the right way to diagnose what may be going wrong within a team. The systems approach addresses the factors that have been well documented as impacting team performance, including shared understanding about the teams goals and how to achieve them, integration among the team members in doing the work, trust, cross-functional collaboration, and more. Yet while those are well established drivers of team performance, most organizations and leaders neither fully understand them nor promote measuring and improving them among their teams.
Cultural resistance to systems solutions
The final point I want to address is cultural resistance to adopting systems solutions. Doing a proper systems diagnostic is time consuming first of all because of the work that has to be done – examining many different parts of the system and how they fit together. What further adds to the complexity and time needed to do the work are the many different stakeholders and leaders who are responsible for or deeply involved in the processes that need to be addressed. The more of a systems approach you take, the more decision makers, influencers, and potential road-blockers you have to bring into the process to ensure they won’t derail whatever changes you end up recommending.
Which is why implementing a solid systems diagnostic, even if the evidence is overwhelming, can be challenging to do. The larger the net you cast in working with different parts of the system, to make sure you are being appropriately thorough in your diagnosis, the greater the chances that you will bring in a key leader who will be resistant to the change.
This doesn’t mean any change you recommend will be doomed to fail. To the contrary, the more comprehensive and compelling the diagnosis, the more obvious it may be that big changes have to happen in order for the strategy to succeed. So, by taking a systems approach, you quite likely will increase the chances that one or more senior leaders will see value in your recommended changes and want to (help) make sure they succeed.
Yet that doesn’t mean your job is any easier, since other senior leaders may oppose the change either actively, or passively, or both. Which is why so many people’s knee jerk reaction is to try for diagnoses and changes that are more limited in scope: these are the ones that don’t require so much time and effort to come up with a potential solution, and there are fewer senior leaders that typically have to get on board to make the change happen.
But think about what that means for the opportunities that lie ahead of you. With so many people shying away from doing proper systems diagnosis and solutions, we clearly are in a state of underinvestment in these approaches. Which was my argument at the very beginning of this two-part series: way too often, the solutions that are identified and implemented are too narrow and fail to properly address the true root causes and interdependencies that are at the foundation of faulty strategy execution.
With so much upside potential, how can you not want to try to tackle and solve these fundamental issues that plague organizations everywhere? Especially since we know the tried and true systems tools and techniques that work. I, for one, have spent more than 20 years doing this kind of work, and find that, virtually every time, the insights are extremely valuable to the organization’s leadership. And the changes, when done right, are usually lasting and very impactful for both the business’ bottom line and the people who work hard every day to enable the business to succeed.