Rethinking Best Practices
Why “Best Practice” keeps showing up on my list
When I think about the handful of things that most reliably distinguish strong business acumen from superficial competence, it’s a short list. One of the most consequential is the ability to avoid overgeneralization, recognizing when an idea that worked somewhere is being treated as if it should work everywhere.
Overgeneralization is a cognitive shortcut. When leaders face pressure to act, borrowing what appears to have worked elsewhere feels responsible, even prudent. In my experience, this shortcut most often takes the form of best practice.
I have seen this pattern across industries, roles, and levels of seniority. A performance initiative succeeds in one organization. Its visible practices are documented. Those practices are then generalized into a different context with different constraints, histories, and interactions. When results fail to materialize, the diagnosis typically focuses on execution rather than on whether the generalization itself was warranted.
This tendency has been well documented in both cognitive and management research. We are prone to infer causality from success, even when outcomes emerge from complex interactions rather than from isolated practices (Kahneman, 2011; Rosenzweig, 2007).
Understanding when generalization is appropriate and when it is not, is a foundational element of business acumen. And nowhere is the cost of getting it wrong more visible than in the routine application of best practices to complex systems.
– Pamela Ey, 2026
Best Practice
It has become common knowledge that best practices reduce risk. If leaders can identify what worked elsewhere and apply it consistently, performance should improve. That logic works in stable or complicated systems (Snowden & Boone, 2007). It breaks down in complex ones.
A complex system is one in which outcomes emerge from interaction rather than execution. More formally, it is a system in which multiple agents continuously adapt to one another and to changing conditions, such that outcomes cannot be reliably predicted or controlled by applying predefined rules or best practices (Meadows, 2008; Snowden & Boone, 2007). Most organizational work today occurs under these complex system conditions.
The Assumption Hiding in Best Practice
Best practices rest on an unspoken causal assumption: If a practice produced strong results in one context, applying it elsewhere will produce similar results. That assumption fits only when cause–effect relationships are stable, repeatable, and largely independent of local conditions. Those properties describe complicated systems, but not complex ones (Snowden & Boone, 2007; Meadows, 2008).
In complex systems, performance emerges from interactions among people, technologies, incentives, timing, workload, and judgment. The same intervention can improve outcomes in one setting and degrade them in another. When leaders import a best practice into a complex system, they are importing a retrospective story about performance success, detached from the conditions that shaped it.
Performance View from the Cheap Seats of Hindsight
This is why so many performance initiatives are defensible on paper and disappointing in practice. The pattern is familiar. A high-performing organization is identified. Or leaders meet at conferences for sharing ideas from “successful” leaders or organizations. Visible practices are documented. Those practices are standardized and scaled. Results fail to replicate, or performance improves for a time before stalling or reversing. The after-action explanation usually focuses on blaming execution: poor adoption, cultural resistance, insufficient training.
But the deeper failure is the real knowledge problem. Leaders routinely mistake correlation for causation, attributing outcomes to practices rather than recognizing that practices and performance co-evolve within a system. This error is well documented in management research. As Phil Rosenzweig explains, success creates a halo that distorts explanation: when results are good, everything associated with them appears causal; when results change, those same elements are reinterpreted as flaws (Rosenzweig, 2007).
The system itself may be largely unchanged. What changed is the outcome, and the story told about it.
What Complex Systems Actually Do
Complex systems have properties that directly undermine best-practice thinking:
Nonlinearity
Small inputs can produce disproportionate effects
Local Adaptation
People continuously adjust behavior to immediate conditions
Emergence
System performance arises from interactions, not components
Path Dependence
History, timing, & prior adaptations matter (Meadows, 2008)
Standardization can improve reliability in well-understood domains. It cannot replace judgment where conditions vary, and surprise is unavoidable.
Research from Naturalistic Decision Making shows that experts operating in real-world complexity do not rely primarily on abstract rules or generalized procedures. Instead, they recognize patterns, detect anomalies, and adapt actions to fit situational demands (Klein, 1998; Klein et al., 2010). Effective performance in complex environments depends on sensemaking under constraint, not rule compliance detached from context.
Best practices suppress the important signals experienced professionals need so they can adjust when conditions shift.
The Craving for Certainty
Best practices are at the top of everyone’s list because they offer leaders something deeply appealing: certainty.
They suggest complexity can be managed with replication more than interpretation. Or that success can be transferred without deeply understanding the system it comes from. But complexity calls for the ability to recognize what kind of situation one is facing and respond accordingly (Snowden & Boone, 2007; Klein et al., 2010).
When leaders treat complex systems as if they were merely complicated, they do not reduce risk. They create brittleness. Performance appears stable until it suddenly is not.
The Real Cost of Misunderstanding Complexity
– Professionals trained to comply rather than think –
– Organizations optimized for past conditions or conditions of other organizations. –
– Leadership teams surprised by outcomes that were predictable if the system had been understood on its own terms –
Best practices are not inherently wrong. They are context-dependent. They work where conditions are stable and repeatable. They fail where interaction, emergence, uncertainty, and adaptation define the work.
References
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
Klein, G. (1998). Sources of power: How people make decisions. MIT Press.
Klein, G., Moon, B., & Hoffman, R. R. (2010). Making sense of sensemaking 1: Alternative perspectives. IEEE Intelligent Systems, 21(4), 70–73. https://doi.org/10.1109/MIS.2006.75
Meadows, D. H. (2008). Thinking in systems: A primer. Chelsea Green Publishing.
Rosenzweig, P. (2007). The halo effect…and the eight other business delusions that deceive managers. Free Press.
Snowden, D. J., & Boone, M. E. (2007). A leader’s framework for decision making. Harvard Business Review, 85(11), 68–76.