sysqtools

🛠️ SysQ Toolkit — Overview

The SysQ AIM (Mindset) and SysQ APTITUDE (Thinking Skills) guide us in seeing the world and analyzing complex challenges, but it’s the Tools that make our thinking visible, shareable, and actionable. These tools aren’t just ideas; they’re practical instruments that help us map, understand, and improve the systems that shape our lives. From simple SysQ Questions that can be used in any meeting to sophisticated simulation models that predict system behavior, each tool has a specific purpose in turning complex challenges into manageable opportunities.

Think of these tools as different lenses through which we can examine reality — each one revealing different aspects of the same system. Just as a carpenter wouldn’t use only a hammer for every job, systemic intelligence practitioners need multiple tools to effectively understand and influence complex systems. The key is knowing which tool to use when and how to combine them for maximum impact. In the following sections, we’ll explore each tool in detail, showing you not just how to use them, but when and why they’re most effective.
IT’S EASY TO FOCUS ON THE TOOLS FIRST

During the 1990s, organizational learning became the leadership fad du jour, with “systems thinking” becoming one of the biggest buzzwords of the decade. Everyone wanted to be systems thinkers. The Fifth Discipline, The Fifth Discipline Fieldbook, and The Systems Thinker1 accelerated a broad diffusion of systems thinking tools and techniques that were adopted by private sector organizations, NGOs, schools, and communities.

accelerated a broad diffusion of systems thinking tools and techniques that were adopted by private sector organizations, NGOs, schools, and communities.

Systems archetypes were the most popular tools. These are recurring behavior patterns found in various systems. For instance, one archetype is called Shifting the Burden to the Intervenor.

This is when a company relies too heavily on external consultants to solve problems they could solve themselves. It’s also when someone becomes overly dependent on coffee to boost energy instead of getting enough sleep, eating well, and exercising; with changes to a few words it also applies to using alcohol to address anxiety.Archetype here from The Waters Center for Systems Thinking

After studying many different systems, from businesses to ecosystems (even families), experts in the field identified a few common behaviors. Eventually, the systems thinking field settled on nine archetypes (like Fixes that Backfire,Shifting the Burden to the Intervenor, and Success to the Successful).

Fixes That Backfire, sometimes referred to as Fixes That Fail, is shown above. Besides using this substack, you can learn more about Fixes That Fail and the other archetypes from the Waters Center for Systems Thinking.2

These archetypes were helpful and easy to understand, so many people who wanted to use systems thinking got excited about them and only used these tools.

But there are many other tools and techniques that should be part of the SysQ toolbox. Some are easier to learn and apply than the archetypes. Others take years to master, but the insights and learning they offer are worth it.

ARTIFACTS (APPLICATIONS and TOOLS)

There are myriad tools — of varying complexity — you should put in your SysQ Toolkit. They include:

SysQ Questions

a set of carefully crafted inquiries that can be used in any conversation to quickly surface systemic patterns and relationships, making them perfect for meetings and initial problem exploration

Behavior Over Time Graphs

help visualize how key variables change through time, revealing patterns and trends that might otherwise remain hidden in the complexity of data and stories

Multi-solving Tools

tools like FLOWER,3 guide us in finding solutions that address multiple challenges simultaneously, maximizing the impact of our interventions while minimizing unintended consequences

Systems Archetypes

recurring patterns of behavior found across different contexts and industries, serving as diagnostic tools to identify common systemic structures that often lead to problematic outcomes

Causal Loop Diagrams (CLDs)

map the circular nature of cause and effect in systems, helping us visualize how different variables influence each other and create feedback loops that drive system behavior

Stock and Flow Main Chains

identify the core structure of systems by tracking the accumulation (stocks) and movement (flows) of resources, information, or other variables that are central to the system's behavior

Stock, Flow and Feedback Maps

combine the power of stocks, flows, and feedback loops to create comprehensive visual representations of complex systems, revealing both structure and behavior

System Dynamics Models

computer simulations that bring these maps to life, allowing us to test different scenarios and policies before implementing them in the real world, providing the highest level of confidence in our understanding of system behavior
OPTIMAL TOOL? USES MINIMUM EFFORT / RESOURCES TO ACHIEVE REQUIRED CONFIDENCE

Each of these tools is like a special tool in our toolbox for understanding and changing complex systems. Some are easy to learn and use right away, while others take a bit more time and effort, but they give us deeper insights. The key is to know which tool to use when and how to mix them together to solve the problems we’re facing.

Many of these SysQ tools have been around for a while, and my colleagues and I have come up with some new ones to make it easier to use SysQ. For example, the SysQ Questions were created when I was teaching public health practitioners how to quickly improve the level of systemic rigor in conversations without having to use some of the more time-consuming visual tools.

There are at least two ways to figure out if these tools are worth using. One way is to think about what you want to achieve with them. The main goal of all these tools and techniques is to make your mental model (the way you understand the world) better, more accurate, and more reliable. In other words, the tool should make you feel more confident that you understand the underlying forces (the basic things that make things happen) that are causing the performance you want to change or improve.

Building simulation models, if done well, creates the most confidence — because they must be internally consistent and use quantifiable data. Creating stock and flow maps can also give you a lot of confidence because they’re the foundation of simulation models and could be simulated if you added data to them. But since we can’t always predict how things will change without a computer, we don’t have as much confidence in our ideas as if we had a simulation model. The chart below isn’t based on any research or has any exact numbers.
Another thing to consider is how much time it takes to learn and use each tool. SysQ says that tools that are easy to learn usually take less time to apply and use. For example, people can learn the SysQ Questions in a few hours and immediately apply them in meetings. But the skills of a good simulation modeler take months or even years to learn, and it can take several months working with an organization to develop a simulation model that gives you confidence in your insights.

Skilled SysQ practitioners are like tool experts who introduce and teach specific tools at the perfect moment. They help clients apply the tools in the right order based on their learning goals and what they want to achieve.
A VISION FOR CAPACITY BUILDING

Barry Richmond vision was everyone could learn systems thinking — at some level. It’s an innate intelligence that can be increased.4 Barry, when teaching system dynamics modeling to various multinational organizations, would show a Venn diagram (below) that suggests everyone should be able to read system maps, many should be able to draw simple maps, and a few should be able to build good simulation models. I’ve updated his original diagram to include additional tools used by other practitioners.Based on my experience teaching many of the SysQ tools above, I believe an ideal distribution of competency would see everyone using the mindset and SysQ Questions. Most would be able to read and apply archetypes, a few would be able to draw useful system maps, and a small percent would be able to develop simulation models. Such a distribution would create an ecosystem of creators, curators, and consumers of SysQ artifacts and insights.

The time it takes to learn and apply the tools and techniques increases exponentially the further right in the diagram. It takes a lot more time and skill to develop a map than to draw a behavior over time graph. And it takes exponentially more to develop a simulation model with dynamic questions and data. However, the amount of confidence in the insight generated from using tools on the right goes up. The type of insight and amount of time available are major factors in deciding which tool(s) would be most appropriate for your work.

“The framework, tools, and language of system dynamics should be accessible to all. Anyone can do this at some level, and everyone should try!”

–Barry Richmond
A WORD OF CAUTION ABOUT TOOLS: SOMETIMES WE CLING TO THEM AT OUR PERIL

We tend to cling to our tools — even when they’re not the best fit for the situation. Remember the saying, ‘a hammer looks like a nail’? Firefighters risk their lives by not putting down their tools when they need to run away from a wildfire.

“In Montana’s 1949 Mann Gulch fire, made famous in Norman Maclean’s Young Men and Fire, smokejumpers parachuted in expecting to face a “ten o’clock fire,” meaning they would have it contained by 10 a.m. the next morning. Until the fire jumped across the gulch from one forested hill slope to the steep slope where the firefighters were, and chased them uphill through dry grass at eleven feet per second. Crew foreman Wagner Dodge yelled at the men to drop their tools. Two did so immediately and sprinted over the ridge to safety. Others ran with their tools and were caught by the flames. One firefighter stopped fleeing and sat down, exhausted, never having removed his heavy pack. Thirteen firefighters died. The Mann Gulch tragedy led to reforms in safety training, but wildland firefighters continued to lose races with fires when they did not drop their tools.”5

Although the failure to set aside our favorite tools may not often have as deadly a consequence as firefighters who fail to do so, we can still be led astray. One common practice is to only apply systems archetypes to an organization’s problems. Newly minted “systems thinkers” may acquire a laminated chart of all the archetypes and scan it to understand all problems. Often an archetype doesn’t apply, so any insight from the chart is most likely unfounded — sometimes it could lead to a bad strategy.

In the case of the Challenger disaster, the standard tool was a having a “solid quantitative case” that the o-rings would be unable to withstand the unusually cold Florida temperatures. The Thiokol engineers who cautioned against giving the mission the green light couldn’t provide the rigorous analysis the managers at NASA required — their standard for the go/no go decision.

“NASA’s Mulloy [one of their senior managers] later argued that he “would’ve felt naked” taking Thiokol’s argument up the chain of command. Without a solid quantitative case, “I couldn’t have defended it.”

The very tool that had helped make NASA so consistently successful, what Diane Vaughan called “the original technical culture” in the agency’s DNA, suddenly worked perversely in a situation where the familiar brand of data did not exist. Reason without numbers was not accepted. In the face of an unfamiliar challenge, NASA managers failed to drop their familiar tools.”6
SUBSTACK MISSION: TEACH WHEN AND HOW TO USE EACH TOOL

Systemic intelligence is all about having the right tools at the right time to understand and influence our complex world. Imagine a master craftsperson’s toolkit, each SysQ tool has a specific purpose. From the quick-to-learn SysQ Questions that can transform any conversation, to the more sophisticated simulation models that can predict system behavior with amazing accuracy. The cool part is that this toolkit is scalable, so everyone can learn to use basic tools to improve their understanding, while those who invest more time can develop deeper capabilities to tackle more complex challenges.

What makes these tools truly powerful is how they work together to build our systemic intelligence. Whether you’re trying to improve organizational performance, address environmental challenges, or solve community issues, these tools provide a structured way to see beyond surface-level symptoms to understand and influence the underlying patterns and relationships that drive system behavior. By mastering these tools, you’ll develop the essential capacity needed to navigate and succeed in today’s interconnected world.

By exploring this substack, you’ll be able to answer:

Why should you use each tool and under what circumstances?

How does that tool work? When applied by an individual? When applied by a team or an organization?

How do you build and deepen proficiency to use each tool?

How do you teach the tools others?

How do you use to facilitate team learning?

“Man must shape his tools lest they shape him.”

—Arthur Miller

🧠 DYNAMIC Thinking

"We count by years, but we live by days. Rightfully, we should do both by seasons." — Ivan Doig, Dancing at the Rascal Fair

YOU’RE ON A COMPANY’S EXECUTIVE TEAM

Imagine you’re on the senior executive team of a multimillion-dollar company. Last quarter’s financial statement just came out, and it’s a doozy. Your company lost several million dollars. How do you feel?Bad, right? Worried?

What ideas / actions do you think the executive team would discuss and probably implement? If like most companies, you’d consider:

Lay offs?
Travel restrictions?
Training reductions?
Several other cost cutting strategies?

Now suppose you were shown the graph drawn below. Profit has plummeted over the past six months.
How do you feel now?

Even worse!

Why? Because it looks like things are getting worse–and rapidly!

What ideas or actions do you think the executive team would discuss and likely implement? If you’re like most companies, you might consider:

Hiring a consulting firm?
Closing part of the business?
Ending a product line?

And as an individual on the team you are concerned about a few things. There is probably going to be some personnel changes on the leadership team. The CEO might be let go. The board will certainly be looking for someone to blame.

You? You are most likely improving your resume, contacting friends and colleagues in your network–spending a lot of time on LinkedIn.

Now, suppose you’re shown this graph.Now how do you feel?

Relieved, right? You may notice even a slight relaxing in the body now (if you were reacting at all to the exercise).

Why relieved?

Because, when viewed over a longer time horizon, the plummeting profits are part of a larger, predictable pattern.

If I asked you what type of business you’re running, you might say it’s a commodity business or more likely a seasonal business (since it has the same fluctuations at the same time each year). Maybe you’re a winter sports chain in New England, selling mostly skis and snowboards.

If it’s a seasonal business (like the winter sports chain) what solutions might you suggest?

You might suggest the following:

Closing the business in the summer months

Diversifying (sell golf clubs!)

Investing during the summer months to boost sales in the winter

Compare the solutions you would propose when analyzing the broader pattern to those you would suggest based solely on quarterly results (an event) or just a half-year’s worth of data (a small window).

The newer solutions are proactive, giving you more control and often revealing opportunities to generate additional revenue. In contrast, the reactive solutions focus on cutting costs.

The key difference between reactive and proactive solutions lies in your understanding of the business’s nature. It’s like seeing the slinky. You grasp the business’s structure, which is seasonal. Once you understand this structure, you can develop a much more effective solution tailored to your business.
EVENT THINKING VS. DYNAMIC THINKING

From a young age, our minds naturally focus on events and behaviors that occur right in front of us, both in space and time. This is not surprising, as humans are hardwired to prioritize the immediate and the present. The ability to hyper-focus on a predator that suddenly leaps from the bushes and react swiftly has proven beneficial to our species. There’s no need to meticulously chart the long-term history of predators leaping from bushes and consuming humans; the immediate response is sufficient: run!

What sets humans apart from other animals is an additional skill: the ability to discern patterns and make predictions. This higher level of consciousness, our meta-level thinking, is essential for addressing adaptive challenges. Our mental models must also include the capacity to represent patterns and make predictions.

In the context of terrorism, it is common in the United States to focus on a single event like 9/11, while overlooking the long history of observable behaviors that could have predicted it. There had been escalating tensions, punctuated by events such as the bombing of the USS Cole and the subsequent US response, as well as actions by the US that supported those considered enemies of terrorist organizations. Adopting a broader, longer-term perspective enhances the quality of any mental model attempting to understand the expansion of terrorism—it helps us identify the causal structures driving it.

Organizations often focus on recent events, such as the last quarter’s profit margin, this week’s layoffs, or current scandals. For instance, the 2008 mortgage crisis in the US (and globally) is a notable example. Initially, in mid-2008, people believed it was a recent phenomenon, likely due to poor management decisions by a few. However, a longer-term perspective reveals that the US economy since the 2000 “sell-off” was stimulated by lower interest rates set by the Federal Reserve. Additionally, granting subprime loans increased at a much faster rate than disposable incomes could sustain. In response, the Federal Reserve resorted to lowering interest rates once again to address the crisis.

The power of an event is undeniable, but unfortunately, we often react impulsively to it. Layoffs, reassignments, extra bureaucratic oversight, and even military invasions are common knee-jerk responses. However, understanding the world and its causes requires the ability to identify patterns of behavior.
REDUCING YOUR STATE’S MEDICAL COSTS

You’re working on your state’s initiative to reverse the rising medical costs. You’ve selected two states to benchmark, and based on their performance, you’ll contact your counterpart in each state to learn from their strategies.

Here are the per capita medical costs for two states. Which one, based solely on this data, would you choose as your benchmark for “best practices”?

he obvious answer is State B.

However, before you draft an email to your counterpart in State B, your assistant bursts into the room with this chart. Now, which state should you contact to learn from their successful practices?
This time the answer is State A.

This illustrates why it’s often beneficial to analyze metrics through the DYNAMIC Thinking lens. First, relying solely on “point in time” data can lead to incorrect conclusions. We frequently make decisions based on narrow time slices of data, which could be detrimental.

Second, comparisons between similar entities, such as states vs. states, cities vs. cities, or countries vs. countries, that only use single numbers can be misleading. Even if two states have the same per capita medical costs, if their trends are similar to those observed here, one may be experiencing rapid deterioration. They are not comparable at all.

Trend lines, on the other hand, often trigger deeper, more rigorous mental models. They provide an operational narrative that enhances our thinking, decisions, and strategies. In this case, observing the trends revealed a story about the direction of performance and clarified the clear winner.

So a good SysQ tenet is:

When something’s important, look at it as a trend over time.
TIME DELAYS: ANOTHER REASON WE NEED DYNAMIC THINKING

In many cases, decisions made today may not have a desired impact on the organization for years. For instance, the Beer Game, a popular learning tool, illustrates our inability to comprehend time delays. Thousands of executives, MBA students, engineers, and others who have played this game have struggled to manage their inventories, even when the retail demand is linear and predictable. Anyone who has played this game understands how inherent time delays in a system’s structure contribute to its performance.

This common limitation also affects our understanding of climate change. John Sterman and Linda Booth-Sweeney have shown that a majority of their subjects (MIT students) cannot predict how long it will take a decrease in carbon emissions rates to impact global climate temperatures, even when the assumptions are clearly stated.1

Ignoring time delays is a major contributor to the planning fallacy. This fallacy occurs when our predictions about the time required to complete a future task are overly optimistic, leading us to underestimate the actual time needed.

Overlooking time delays often results in the common “worse before better” dynamic when implementing public policies or organizational improvements. Public sector managers, rightly so given the public’s understanding of dynamics, avoid policies that may eventually improve situations in the long run but may worsen conditions in the short term.2
THE SHAPE OF A MOVIE

In 2017, we witnessed a plethora of extraordinary yet peculiar movies. Among them, The Shape of Water emerged as the most peculiar of all, potentially claiming the coveted Academy Award for Best Picture.

Its premise, centered around a mute woman named Elisa’s profound love for a creature that resembles a fish more than a human, may initially appear absurd or even laughable. However, this film achieved remarkable success, garnering numerous accolades and captivating audiences.

The trend line for her love of the water man is shown here.

The Shape of Water’s success lies in its ability to gradually reveal credible reasons for Elisa’s growing affection for the water-dwelling entity. This gradual progression allows viewers to comprehend and even predict her actions throughout the movie. If you were to watch only the last third of the film, you might find the scenes so absurd that they would be difficult to take seriously, potentially leading you to leave the theater.

However, by watching the entire movie from the beginning, you are presented with a rational, rigorous, and dynamic mental model that enables you to grasp and even anticipate the protagonist’s actions.
STARTING A SYSQ ANALYSIS? FIND THE PLOT FIRST!

At the outset of every SysQ initiative, establish a clear purpose. Collaborate with your team members and stakeholders who need to be involved. Ensure that everyone is aligned in understanding the purpose of the mapping, modeling, or SysQ analysis.

The purpose is to comprehend the underlying causal factors that contribute to . This knowledge will enable us to develop more effective strategies, policies, or levers to influence in the future.

While verbal descriptions can suffice, visualizing trends over time through a trend graph can significantly enhance the impact and utility of the analysis, particularly in collaborative settings.
OPERATIONAL THINKING — FOCUSING ON THE PHYSICS — REQUIRES CLARITY ON THE TRENDS

OPERATIONAL Thinking — focusing on the physics — is fundamental to high SysQ and applying it involves gaining a comprehensive understanding of the systemic structure that generates the desired behavior. Clarity on the behavior is not merely a desirable outcome but a prerequisite for effective SysQ application.

The process of clarifying the trends, drawing and agreeing on these trends, aligns everyone on the same page regarding their underlying reasons for working together. It provides a clear vision, fostering strong motivation for collaboration. Therefore, I allocate significant time early in any consulting engagement to assist my clients in achieving vivid and rigorous clarity on the purpose: the trends they intend to influence.
ADDITIONAL BENEFITS OF DRAWING TRENDS OF INTEREST

Gaining clarity on trends helps focus effort and develop a vision of success. But it offers many other benefits as well.
Benefit 1

It automatically shifts collaborators into a generative process. Seeing a trend line prompts the mind to seek understanding. Why does this happen? This prompts us to delve into our mental model database, searching for past experiences that might explain it. We transition from reactive thinking—“How do I react to this?”—to becoming more inquisitive and reflective. We seek causality and explore what generates the behavior or enter a generative process.4
Benefit 2

It helps identify faulty thinking by comparing our perceived trends to what others believe or know. Sometimes, our assumptions are incorrect.

Let’s say I believe that our projects are taking increasingly longer to complete, perhaps because my last two actually did. I might suggest to colleagues we need to invest in some improvement, perhaps upgrade the IT system. Instead of promoting a solution to a nonexistent problem, if I drew a trend line similar to the one shown below, I could share with others, including those who have the data.

I’d then have the opportunity to learn why my assessment of reality was so far off. Yes, I’d have a learning moment. In this case I’d learn that I was still holding onto the increase in project time that happened late 2016 when several employees left. And even though project times had steadily improved since then, my confirmation bias kept me looking for the trend to go the other way. In this case, I learned something about myself.

I’ve seen the process of drawing trends help legislators who are normally disagreeable with one another become collaborative because they had some inaccurate understanding corrected. If seen engineers show trend lines to management to help them become more concerned about where a staffing issue was likely trending in the not too far future.
Benefit 3

Asking others you wish to be part of the effort to draw trends they are most concerned with–trends that may not be ones you initially used in trying to motivate their involvement–may help you find common ground. It may also help you expand your field of vision.
TO LEARN MORE ABOUT USING TREND GRAPHS

Check out this substack’s resources section to learn about several trend graph types you’ll find useful across a diverse range of purposes and activities.
1

J. Sterman and L. Booth Sweeney, Understanding public complacency about climate change: adults’ mental models of climate change violate conservation of matter, Springer Netherlands, Vol. 80, Numbers 3-4
2

Soderquist, C. Facilitative Modeling: Using Small Models to Generate Big Insights, The Systems Thinker, Pegasus Communications, December, 2003
3

Forbes, 'The Shape Of Water' 4K Blu-ray Review: The Ultimate Wet Dream, Mar 19, 2018, https://www.forbes.com/sites/johnarcher/2018/03/19/the-shape-of-water-4k-blu-ray-review-the-ultimate-wet-dream/
4

Calancie L, Anderson S, Branscomb J, Apostolico AA, Lich KH. Using Behavior Over Time Graphs to Spur Systems Thinking Among Public Health Practitioners. Prev Chronic Dis 2018;15:170254. DOI: http://dx.doi.org/10.5888/pcd15.170254.

The authors used trend graphs with teams in maternal and child health. 86% of participants found the technique improved their thinking and engagement enough to indicate they would use these tools after the workshop.

By • 7 months ago

🧠 Building SysQ Capacity: Strengthening a Suite of Thinking Skills

By • 7 months ago

🛣️ The Process Redux: The Learning Journey Takes the High Road

“Two roads diverged in a wood, and I — I took the one less traveled by, And that has made all the difference.” — Robert Frost

We tend to focus on the present moment. Most PhDs are awarded for studying a single weed in a field and analyzing it in great detail.

Good systems models, on the other hand, take a broader perspective.

They look at the big picture, analyzing long-term patterns and trends to find ways to improve things over time.

Most mental models are confined to a narrow window of time and space. We usually focus on a few days or weeks, while the system operates over years. Similarly, we usually concentrate on our department or division, but to effectively manage the system, we need to consider multiple organizations, agencies, groups, and stakeholders.

HOW DEEP (DETAILED)?

You may have heard that adaptive leaders should step back from the action and take a look at the big picture. It can feel like we’re stuck in the weeds, and it’s hard to see the shared values and beliefs that guide our interactions with others. Instead of focusing on individual differences, it’s helpful to apply a broader context (FOREST Thinking) — see how forces and conditions in the ecosystem shape our actions. Public health professionals deal with large numbers of people, while marketing departments manage diverse customer groups.

HOW TO BUILD GOOD SYSTEMS MODELS

Good systems models are in the upper right. They see broadly to understand the forces across the full ecosystem responsible for the performance issues you want to improve. The goal is to generate good systems models. The challenge? How to get there!

There are two roads we could take to reach the destination of a useful systems model.

Road 1: Representing the System

Road 1 is the most popular path. It tries to make a complete map of everything from the start. Teams of experts with specific knowledge often try to put all their knowledge together into a detailed picture. But this can make the map too complicated — like the Afghanistan Counterinsurgency map — with too much detail. This pursuit of a complete system map puts us on the Low Road (Road 1).

The Low Road starts with myopic perspectives and ideas and tries to put them together into a coherent whole. Since we have so much detail and the task is so big, this process only makes things more complicated. If we’re lucky, the mapping project ends up with a map as complex as the counterinsurgency map — a tangled web of information. More likely, the mapping effort stops, leaving us lacking comprehension and insight.

The problem is trying to map the whole system instead of just understanding the cause of the behavior (performance measure) we want to improve. Remember the slinky. If our performance goal is to significantly reduce the Slinky’s oscillation, we only need to focus on the physics of the spring. We can leave out colors and shapes — in fact, we must exclude them to reduce complexity. For usability, we must eliminate parts of the full system that don’t contribute to the performance we want to improve.

“Details are confusing.

It is only by selection, by elimination, by emphasis, that we get at the real meaning of things.”

—Georgia O’Keefe

Road 2: Get Up Out of the Weeds

Road 2 is the wisest path. It is the High Road path.1

The High Road starts by setting the big picture vision for system performance. Then, you can decide what you want to see improve. Next, you can build a simple causal map, pick and change a system archetype, or make a simulation model. These tools help you understand what causes that behavior.
The High Road process involves sharing the initial “starter map” or “starter model” with others. Does it provide a clear explanation of why the performance issue is occurring? What changes or additions are needed? Make small adjustments and share the updated model for testing.

Keep adding more details a little at a time. This is the gradual descent in the diagram labeled “and add breadth and a bit more detail — slowly”.

Apply OPERATIONAL Thinking when adding more elements. Answer the question: “Does this contribute to the physics of the challenge — does it explain how the performance is generated?”

When you can finally answer the question “Does this describe the essential drivers of the performance issue?” with “Yes!”, it’s time to stop mapping (or whatever SysQ analysis process you’re applying.

Then use the map or analysis to start exploring ways to improve performance. You can look for solutions to close the future performance gap — you can find interventions to achieve your vision.

“A model should be as simple as possible, but no simpler.”

—Albert Einstein

The concept of two roads, and especially the High Road, was first developed by Barry Richmond while teaching system dynamics to his undergraduate class. The concept was so memorable that one of his students years later asked me if I had a Powerpoint slide with the roads on it.

By • 7 months ago

🛣️ SysQ Process — Overview

“Nothing is as practical as a good theory” — Kurt Lewin

We’ve talked about how the SysQ Mindset (AIM) helps us deal with complexity instead of just making things simpler, and how the SysQ Thinking Skill Set (APTITUDE) helps us figure out how our challenges are connected. Now, we’ll show you how to use these skills to put them into action in a three-step process: Sensemaking, Solving, and Implementing & Learning. These are the things we need to do to move from a problem to a solution in a way that helps us learn the most.

This process isn't just another framework - when infused with the SysQ Mindset and Thinking Skills, it becomes a powerful, yet practical, approach helping us find genuine leverage points in complex systems while avoiding the common pitfalls of rushed solutions and unintended consequences.

This process isn’t just another way to do things — when we use the SysQ Mindset and Thinking Skills, it becomes a powerful and practical way to find real opportunities in complex systems. We can avoid the common mistakes of rushing to solutions and making things worse.

Think of this process as the guide that shows us how to use the SysQ AIM and APTITUDE. While the steps seem simple, they challenge our natural tendency to jump to solutions before we really understand the problem. By following this process, we can move beyond just fixing things to make real, lasting changes in our organizations and communities. This process helps us answer three important questions: Are we working on the right problems? Do we really understand what’s driving them? And are we creating solutions that work?hoosing solutions that will create sustainable improvement rather than temporary relief?

The SysQ Process has three steps that are like a loop. These steps are called phases in the “finding leverage” process:

1. Sensemaking

2. Solving

3. Implementing & Learning

A. SENSEMAKING

To truly improve a situation, we need to understand the underlying forces driving the problem. Often, we jump straight into solutions without fully grasping the root cause. A common mistake is assuming we know what’s causing a problem and moving on to the next step.

The real issue with ineffective strategies is often that we choose the wrong problems to work on. We’ve poorly framed the problem, and that’s why our efforts aren’t making a difference.

Let’s say I want to improve my child’s grades. I might think the problem is their focus and persistence in studying. So, I’ll give them money as a reward. This might work in the short term, but the real problem is likely their intrinsic motivation. And the cause of that might be low self-worth or self-efficacy. If that’s the case, then the reward solution was the wrong approach for the right problem.

This is like building a great ladder and then leaning it against the wrong wall. To make sense and build a successful strategy, we first need to choose the right performance issue to improve. We need to pick the right wall.

Even if we take the time to frame the right issues, we still often just jump to solution mode. We start building our favorite ladder without thinking about the bigger picture.

In the example of my child’s grades, we might react by giving them words of encouragement. You’re smart. You can do it. But then, our child might reject those words and even argue with us. We might get frustrated, and the wall might include a fixed or stuck mindset: I’m bad at math.

To climb the right wall, we need to identify the fixed mindset. Instead of labeling our child as “good at math,” let’s focus on learning. “Yes, you might not be as good at math as you’d like, but you can learn. Even though you still got a C on the latest test, it’s several points higher than the last.” By internalizing the message that we’re learning, we’ll create a lifelong learner who accepts and embraces challenges in productive ways.

Successful sensemaking starts by framing the right performance issues to improve and then building a systemic picture of the structural forces driving performance. We often avoid or don’t apply either step. We tend to say, “Don’t just sit there, do something.” But, the right frame of the issue and a rigorous operational picture of structure must come first. Next, you can generate higher leverage solutions…and then act.

“If you can define the problem differently than everybody else in the industry, you can generate alternatives that others aren’t thinking about.”

—Roger Martin

So, we’ve picked the right performance issue to fix, we’ve figured out the root causes, and now we can find ways to make a real difference.

If we’re using high SysQ, we’ll look for places to make a big impact. We’ll try to make the most of our resources and avoid any surprises.

When startups enter the market, they often follow a simple strategy: they lower their prices to boost sales. But this can backfire. It can create demand that’s too high for our current capacity, leading to delays, defects, and unhappy customers. And that can hurt our sales in the long run.

Instead, we should try a different approach. We should keep our prices high enough to meet the demand of early adopters who want new features and services, but not so high that we lose customers who are looking for something easier to use. We can use our profits to improve our capacity and then slowly lower our prices so that demand and capacity stay balanced.

But here’s the thing: most of the time, we choose solutions that we’ve already tried or even thought of before. We’re not very creative, and we tend to get stuck in a rut. We end up with slightly better or worse customer satisfaction, a little less or more unemployment, or a small decrease or increase in carbon emissions. But we don’t get close to our goals.

SysQ can help us break free from this cycle. It can help us generate solutions that are truly innovative and effective. SysQ-generated solutions are often:

1. Innovative and Overlooked

2. Counterintuitive

3. High-leverage

Innovative and Overlooked

Focusing on interrupting the madrassas pipeline training new terrorists is an overlooked strategy — it’s far more innovative and outside the box than typical anti-terrorism strategies.

When a metro region decided to boost its arts and culture scene to address workforce shortages, that was a smart economic move.

Another innovative idea? Redefining internal customers as ‘On the Fence,’ ‘Advocates,’ and ‘Haters’ and implementing a strategy to reduce early ‘Haters’ instead of the usual focus on building early ‘Advocates.’ This approach saved the aerospace company millions.

We can come up with all these innovative, outside-the-box strategies because we’ve set up the right issues and developed the right mental model of structural drivers. We see things more broadly and understand them more operationally.

Counterintuitive

We often focus on the right levers to make positive changes, but sometimes, the results are unexpected. For example, lowering prices might seem like a good idea, but it can actually lead to lower sales in the long run. Similarly, building only low-income housing can create neighborhoods that become poverty pockets. It’s counterintuitive to remove low-income housing and replace it with mixed-use and mixed-income housing, which includes a range of low to high-income housing. The amount of solely low-income housing is a lever, and our emotional reactions to poverty often lead us to pull the right lever in the wrong direction.1

High-leverage

Have you noticed how often we have planning meetings where we adjust last year’s strategy or budget a bit? We might allocate slightly more resources here and less there. This tweaking approach could be called the Buckshot Strategy Planning Process. We believe that we need to use our scarce resources wisely, so we take a broad approach.

Suburbanites are often surprised when building new roads and adding more lanes to reduce traffic congestion only ends up causing more congestion a few years later. Reducing congestion encourages more development, which then increases congestion. Instead of trying to eliminate congestion, it’s better to accept road congestion and use that pressure to stimulate jobs closer to where people live or public transportation.

One insurance provider faced a challenge in maintaining enough claims processing staff. New hires quickly burned out dealing with stressed-out customers who wanted their claims processed quickly. The typical approach is to increase the number of people involved; we need more of them! So, the company hired more, only to find burnout and turnover continued to accelerate. They discovered a high-impact strategy. Develop the emotional intelligence (EQ) of the department, especially its senior leaders. This allowed the staff to interact with customers with greater empathy and reduced burnout. Additionally, senior leaders could support their staff by focusing on their well-being, which reduced turnover more.2

Our strategies often involve multiple physical aspects of the ecosystem. We increase inventory and buffers, build new facilities and infrastructure, and hire more staff. But it’s often more effective to focus on the less physical aspects: building skills, changing decision rules, reducing burnout, improving information flows, increasing incentives or penalties, and ultimately transforming the mindsets we use to make all decisions.

These high-leverage interventions, though rare in typical planning frameworks, become clear when we apply the skills of SysQ.

“It’s not that I’m so smart, it’s just that I stay with problems longer.”

— Albert Einstein

C. IMPLEMENTING & LEARNING

We start by defining a performance issue and building a model to understand it. Then, we come up with a hypothesis for how to improve it, which we call decisions, plans, or strategies. But even though we’ve tested our hypothesis using SysQ skills and tools, we still need to build confidence in it. And that confidence is best built as we implement the strategy.

Kurt Lewin said that to understand something, we should try to change it. As we learn from implementation, we can see what works and what doesn’t. This helps us figure out if we have the wrong strategy, if it needs to be changed a little, or if it needs to be changed a lot. A higher-leverage learning happens when we realize we’ve made a mistake in our thinking. Maybe we don’t fully understand the causes of the problem or we’ve chosen the wrong performance issues. We’re building ladders for the wrong wall.

Sometimes, we review and revise our sensemaking, which is called double-loop learning. Single-loop learning happens when we think we’ve figured everything out and only change our tactics to solve problems. Double-loop learning happens when we hold our beliefs as hypotheses and are willing to question them. We’re willing to change our thinking before we change our actions.

In the Implementation and Learning phase of the iterative learning process, our goal is to gather as much useful information as possible to confirm or disprove our strategy. We’ll look for leading indicators, keep an eye on them, analyze the data, and decide if we have the wrong strategy. If we do, we can try adjusting it using the same thinking we used to develop it. Or, we might realize we have a wrong understanding of the ecosystem or the performance issues we want to improve. In that case, we’ll double-loop and make any necessary changes to our assumptions. Then, we’ll go back through the process again.

If you want to truly understand something, try to change it.

— Kurt Lewin

SUMMARY

The SysQ Process is a super-powerful tool to tackle tricky problems in our crazy, interconnected world. Instead of jumping to solutions, it guides us through three main steps: first, we figure out what’s really going on and why; second, we come up with creative, unexpected, and super-effective solutions; and finally, we put those solutions into action while staying open to learning and changing our approach as needed.

At its heart, this process helps us avoid common pitfalls like building solutions for the wrong problems or fixing things that just make things worse. Instead, it helps us understand the real issues, see how they’re connected, and come up with truly transformative solutions. By doing double-loop learning, we can keep improving not just our actions, but also our understanding of the challenges we face. This iterative approach means our solutions get better and better over time, leading to lasting positive change instead of just temporary fixes.

The SysQ Process is actually pretty simple, and we all know the steps. But we often don’t spend enough time figuring out what’s really going on or challenging our thinking in ways that support double-loop learning. That’s why this substack is here! We’ll share examples, practical tools, and tips to help us use the SysQ Process more effectively and learn more by doing.
1

Meadows, D. H. (2015). Thinking in Systems. Chelsea Green Publishing.
2

Clark, K. et al. (July 2015). Using Systems Thinking to Shift Mindsets. [white paper]. International System Dynamics Conference, Boston, MA, USA

By • 7 months ago

By exploring this substack, you’ll be able to answer:

Why should you use each tool and under what circumstances?

How does that tool work? When applied by an individual? When applied by a team or an organization?

How do you build and deepen proficiency to use each tool?

How do you teach the tools others?

How do you use to facilitate team learning?

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