In complex systems, it’s tempting to fight complex problems with complex solutions. But building complicated models with detailed multi-factor analysis driven by expert-laden opinions… layers of complexity are not going to move the system forward. Complex systems defy that kind of approach.
The alternative is to fight complexity with simplicity. Sounds compelling, right?
Simple Rules is a term used for a technique used to drive behavior and decision making in complex systems. In “Simple Rules: How to Thrive in a Complex World” by Kathleen Eisenhardt and Donald Sull, they describe how simple rules seek to distill strategic aims into “a handful of guidelines, tailored to the user and the task at hand, which balance concrete guidance with the freedom to exercise judgment.”
It recognizes that in complex systems, the decision architecture should emphasize flexibility more than consistency. Simple rules work best in unstructured decision making environments, where alignment across the organization can be a challenge. At the other end of the spectrum is the use of automated rules in highly structured decision making environments.
Eisenhardt and Sull teach Simple Rules using four simple rules (because, of course…)
- Keep the set of rules small, so it’s easy to remember
- Tailor them to the context; let the people or teams make their own rules
- Apply them to a well-defined activity; aim for meaningful, not general
- Treat them as guidance, not prescriptive; leave latitude to exercise discretion
Strategic decision makers can distill their strategic direction or path into simple rules to guide the transition to action. The rules can support the transition from a strategic choice to the guiding policies for action that follow.
Simple rules are especially powerful when applied to a known bottleneck in the flow of value in an organization.
They add, “People are more likely to use rules devised by themselves, reflecting their own values, rather than those imposed on them by someone else.”
They categorize types of simple rules, to help people get started:
Decision Rules - provide guidelines on “what to do”
- Boundary Rules - cover what is acceptable for specific people or teams to do (or not within their decision authority)
- Prioritizing Rules - cover what is more important to do (e.g. Even-Over Statements)
- Stopping Rules - cover what to stop doing and when
Process Rules - provide guidelines on “how to do it”
- How-To Rules - covers basics of specific activities or making certain kinds of decisions
- Coordinating Rules - covers getting things done when multiple actors have to work together
- Timing Rules - covers getting things done when rhythms (cadences), sequences, or deadlines are relevant
Of all the categories, they note that it is especially difficult to define and follow simple rules for stopping things. Stopping work and pivoting away from failed experiments form the linchpin of agility, yet most organizations struggle with these kinds of decisions.
The concept of Simple Rules can also be found in descriptions of Complex Adaptive Systems. Common examples of CAS found in nature show how simple rules can describe the flocking of birds and the behavior of ant colonies.
The Human Systems Dynamic Institute adds, “Simple Rules are the agreed-upon guides that inform behavior and interactions among members of a Complex Adaptive System. Whether by conscious agreement or by unspoken assent, members of a CAS appear to engage with each other according to a short list of simple rules. Those Simple Rules shape the conditions that characterize the dominant patterns of the system.”
They offer another set of characteristics for sets of Simple Rules:
- Few - “never more than 7, 5 is ideal”
- Generalizable - “general statements that apply in any situation to anyone in the system. [Note: This differs with Eisenhardt and Sull’s view, who say a rule should be specific to a well-defined activity.]
- Positive - focus on what to do, not what “not to do”
- Active - emphasize the doing; name should lead with an action verb
In this telling, the rules are emergent. Choices made by agents in the CAS drive system behaviors, which can be distilled into patterns, and which, when described as rules, express the culture of a complex system. These rules are explored as people come together to look retroactively at these system behaviors, and agree on the shape of the patterns. From there, they can possibly tweak the rules, to improve the coherence across the organization.
Another proponent of simple rules to support decentralized decision making is Donald Reinersten, author of “The Principles of Product Development Flow”. He stresses the importance of finding simple rules that navigate the economic constraints present in design and development organizations.
Reinertsen reminds us that decentralizing authority requires us to “provide high-quality decision support information to this level of the organization.”
He coined the First Decision Rule Principle that advises leaders to “Use decision rules to decentralize economic control.” These are good examples of prioritizing rules, as categorized by Eisenhardt and Sull.
He lists four advantages to simple, economics-based, decision rules. When crafted well, decision rules can:
- Align the independent choices that get made with the rules
- Insure that the choices are optimum at the system level
- Reduce the risk of decentralizing the decision making control
- Streamline the process of making the decisions
He gives a great example from Boeing from the development of the Boeing 777. He explains that in the design of an aircraft, there is always a tradeoff between minimizing the overall weight and minimizing the overall cost. That is, design ideas that could reduce weight usually drive higher costs.
After trying one approach that allocated weight and cost constraints to subsystems (oops, not great to optimize parts in complex systems) and another that created a central expert for make all tradeoff decisions (oops, creates a bottleneck), they settled on a simple economic rule:
“Any designer was authorized to increase unit cost by up to $300, by making design changes or material substitutions, to save one pound of weight.”
Adding, “As a result, Boeing had 5000 engineers making system-level optimum tradeoffs without the need to ask for permission from their superiors.”
Simple rules serve as guidelines for making optimized decisions. This is in contrast to the concept of default rules, heuristics, and habits.
Heuristics are mental shortcuts that ease the cognitive load of making a decision. Heuristics are part of how the human brain evolved and is wired, allowing individuals to quickly reach reasonable (but often not optimal) conclusions or solutions to complex problems. You fall back on heuristics when you “decide not to decide” and stop seeking an optimal solution and settle for a “good enough” solution.
In “Power and Prediction” by Ajay Agarwal, Joshua Gans, and Avi Goldfarb, the authors explain that default rules and habits get formed when the costs of optimization are too high to make individual decisions every time.
They ask, “What determines when a particular problem will be put in the default rule rather than the active decision basket?”
Their answer: Problems are handled with default rules when they have:
- Consequences are low (i.e. low stakes)
- Information is expensive (or time-consuming)
A default rule like wearing the same clothes every day (see: Steve Jobs, Mark Zuckerburg, and Barack Obama), might be a good way to reduce cognitive load and decision fatigue, but these are not examples of Simple Rules that would guide an organization.
Even though "simple" does not mean "easy", it is still worth exploring how simple rules can help manage complexity by supporting economic-based decentralized decision making.