There are complicated problems, and there are complex problems. Complicated problems are technical in nature. They are linear, orderly, and predictable. Complex problems are adaptive challenges. They are messy, unstable, and unpredictable. “Having a wedding is complicated; having a happy marriage is complex.”
If you want to crack a complex problem, you need the code. David Benjamin and David Komlos provide the code in Cracking Complexity.
We can master highly sophisticated technical and technological challenges because we’re quite skilled at making linear connections from one technical feat to the next. But complex, multidimensional challenges are categorically different. They are not linear. They are not solved or even solvable through technical prowess. They don’t stand still. They don’t patiently await solutions. Complexity is a whole different ball game.
The question is, “How can we best deal with something we’ve never dealt with before, without foreknowledge of what’s going to work?” Conventional approaches to problem-solving typically rely on small groups of smart people cloistered away tasked with deciding the best way forward. We need a new approach to complex problems that allow us to cocreate in large groups.
The Complexity Formula
A foundational idea behind the formula is Ashby’s Law or the Law of Requisite Variety which states: Only variety destroys variety. “Ashby’s Law says you need to bring a matching amount of variety to the solving process.” In other words, a high-variety group that can collectively address the variety inherent in the issue to be solved. The Complexity Formula helps you to unlock the skills, knowledge, experience, and expertise of the people around you.
All the steps in the Formula are complementary and build one upon the next to deliver rapid leaps on complex issues.
The first five steps set things up. Steps six through nine are where a requisite-variety of people can spend a short amount of time—typically two days—to sense, absorb, think, decide, and then in Step ten to act on the complex problem.
Listed below are the ten steps with some key thoughts on each:
1. Acknowledge the Complexity
The first step is to determine exactly what kind of problem you are faced with. A complicated problem or a problem that is truly complex. The first step is “recognizing that there are no known answers, that no outsourced provider is going to figure it out for you—at least fast enough—and that the old way of figuring things out isn’t going to work anymore.”
2. Construct A Really, Really Good Question
Frame the issue with a good question. A complex issue needs a question that addresses the complexity. “A good gut check on the question is how people react to it. Are they uncomfortable with it because it challenges the status quo, sets the bar high, or suggests a lot of work needs to be done? Conversely, are they completely comfortable with it because it’s easy to answer? Don’t necessarily retreat from what you think is a good question because people are reacting negatively, and don’t be satisfied if people aren’t pushing back.” Example: “What must we do in the next 12 months to drive necessary changes in mind-set, action, and behavior to fully realize the benefits of…?”
3. Target A Requisite Variety of Solvers
Involve the right people. Identify the requisite variety of people needed to match and absorb the complexity. “Your goal is to include the necessary perspectives, characteristics, roles, functions, hierarchical levels, and so on. If you shortchange requisite variety, you’re setting yourself up for no or partial solution and weak execution.” The authors provide a system to be sure you’re getting the right people together.
4. Localize the Solvers
Get everyone together face-to-face. It allows for neural synchronization. In Google’s team study, they found what distinguished high-performing teams from low-performing teams is not team cohesion, motivation, or average IQ, but rather frequent turn-taking in conversations and high social sensitivity toward what team members are thinking and feeling.
5. Eliminate the Noise
Noise takes all forms: “too much information all at once; too much wrong or inaccurate information; and too much missing, ambiguous, unreliable, or fragmented information.” They recommend that we “Err on the side of too little research, too little data, information, and knowledge—invest the effort instead in the requisite variety of people who carry the tacit data banks and the powerful processors around between their two ears.”
6. Agree on the Right Agenda
Do not preset the agenda. Once you get everyone together, begin by deciding what to talk about. “Let the group decide what they have to talk about in order to answer the question. Their first task together is agreeing on how to deconstruct the question into the right component parts to discuss.”
7. Put people On A Collision Course
A highly engineered conversation—engineered serendipity. “Serendipity often happens where people, domains, and/or systems collide. And collisions can be engineered. When we talk about domains and systems colliding, we mean people from one domain or system bumping into people from another domain or system.”
8. Advance Iteratively and Emergently
You must trust that the answers will emerge. “Your requisite variety group needs to operate with energy and an expectation that the right answers will arise from the right kinds of interactions together.” Also, “Having set their agenda, your group needs to go through that entire agenda once, then again, then again.” Three times is the number—more yields diminishing returns.
9. Change How People Interact
Nothing will happen if the interactions between your group members are not productive ones. To be effective, they need to be “candid, incisive, unconstrained, unguarded, transparent, fierce, and focused.” That requires, “discipline and structure, right-sized teams (no more than 8), effective conversation roles, and environment where productive friction is expected and not frowned upon, and have a neutral note taker.”
10. Translate Clarity and Insights into Action
“The actions that result from the use of the Complexity Formula fall into three categories: Things to do, things to try, and the newly revealed complexities.” The job in step ten is to categorize the solutions in the three categories and then to attack “each pile in the right way to make progress, to continue learning, and to get after the next big challenge.” Sometimes working on one complexity reveal yet another complexity that needs to be resolved.
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