TL;DR
- Standard change management relies on big bang, single-threaded predictions that ignore the complexity of human behavior; durable value is found through iterative, Bayesian-style methods.
- Humans are biologically wired to resist change due to loss aversion and status quo bias, but we are evolutionarily primed for trying and exploration.
- Long-term impact is achieved by setting a clear ambitious identity while remaining intentionally blurred on the methods of achievement, allowing feedback loops to dictate the path forward.
The Tetris Effect of Modern Leadership
Leaders today are playing a high-stakes game of Tetris, but they’re starting with half the screen already filled with geopolitical shifts and macro-economic noise. On a micro-level, the attention tax is mounting; research suggests every single smartphone notification can costs us seven seconds of deep focus.
In this state of cognitive depletion, most organizations still attempt big bang change. They blast an email to 50,000 diverse humans and expect immediate alignment. It is a formula for expensive failure. When we force change on a stressed system, we don’t get progress, we get increased change fatigue, a sense of helplessness that transcends the office and bleeds into every facet of a team member’s life.
Organizational effectiveness (value to customers) is found in the gap between how we lead, operate, and use information.
1. The Bayesian Leader: Why Predictions Fail
Why do our leadership development programs or structural pivots so often miss the mark? It’s not a lack of expertise; it’s the narrowly informed prediction. We make a massive assumption of value, launch a new forever initiative, and then, often fearful of looking misguided, we stop (or never start) measuring the actual desired outcome.
The Shift: Adopting a mindset of Ongoing Experimentation.
Think of this as a Bayesian approach to leadership and operations: you start with a prior belief (your prediction), but you constantly update that belief as new data from the diverse and variable environment hits the system. You aren’t pivoting (which implies failure); you are proactively refining.
2. The Psychology of Try vs. Change
There is a profound psychological delta between being told something is changing and being asked to try something new. As in any real change, accounting for human behavioral tendencies is necessary.
Most organizations focus heavily on SWB/REV (Salaries with Benefits as a % of Revenue). While important for operations, this narrow focus creates unseen opportunities and problems.
- Status Quo Bias: Humans like things the way they are, change feels like a substitution or a loss. Trying feels like an addition.
- Loss Aversion: The pain of losing our current routine is twice as powerful as the joy of a potential gain, so the potential loss in a change far outweighs any potential benefits at first.
- Endowment Effect: We overvalue the current way simply because we own it making change even harder but creating space for a potentially owned benefit with little to no risk.
We rarely mind downloading and trying a new app, but we are outraged when our favorite app changes its visual workflow without our consent. One is an exploration; the other is a violation of our owned space.
By framing organizational shifts as experiments, try before you buy, you bypass the brain’s threat detection system. You reduce the cognitive tax and allow for genuine adoption. This approach is useful well beyond a larger operational architecture. Being open to trying new ideas also builds on psychologically safe environments where unique ideas can be brought to life with little risk but significant return in team member innovation and alignment.
3. The Engine of Progress: Feedback as a Ritual
Feedback loops are not just data collection; they are signals of collaboration, co-creation, and shared ownership. When focus groups, listening tours, and behavioral data are synthesized through an anthropological lens, a multi-perspective painting of the organization emerges, one that describes humans, context, and environment in real-time.
Experimentation is a muscle and a strong feedback loop is the consistent habit of protein intake. You want a culture enacting experiments big and small and the desire for consistently improved results and decisions. Feeding that desire is the rigor of measurement, the self-propelling wheel of momentum and collaboration, and new perspectives achieved through intentionally built feedback loop operations.
As these ongoing experiences become a cultural ritual trust is reinforced. People stop fearing the next idea factory blast because they know they are the primary sensors in the experiment. They are no longer the subjects of change; they are the scientists.
A Blurred Vision of the Future
How do we change behavior at scale? We look at the individual. Consider someone fighting the pull toward obesity-driven-disease. The why (Health) is important, but the Identity (who they want to be) is tactile.
The Strategy: The Blurred Horizon. Wading through countless experts and their advice we synthesize what works. Holding the long-term destination in your peripheral vision to inform the short-term without being too rigorous on the methods of achievement.
- Identity over destination: Personify the end state, who will you be?
- Obscure the perspective: Clarity of the goal but blurred on the path.
- Launch the flywheel: Build momentum with iterative measured actions.
This creates an internal feedback loop where the individual (or the 50,000-person org) learns while making progress to that future identity.
Perspective
I have lived every side of this equation. I’ve been the team member drowning in the idea factory, never making progress. I’ve been the executive driving a big bang change that fell flat. And I’ve been the leader who finally learned to say, “Can we try this?”.
In my 20+ years, the iterative, measurable-experiment-driven approach is the only one that has created durable value. Without any startup investment, it only costs the ego required to admit we don’t have all the answers upfront.
I use this same blurred vision for myself. By focusing on my future identity and running small, daily experiments, I keep churning out positive changes on the path to the legacy I want to leave. Whether it’s your life or your labor expense, the answer isn’t a better prediction, it’s a better experiment.
About the research
This article explores the Operations Ridge through the Behavioral, Structure, and Temporal Views. Ridgeline Research Graph: A Blurred Vision Category for the methodology of long-term change. Component-Dominant Thinking (Dave Hodges): Exploring ecological psychology and why HR’s standard interventions are often too expensive and too rigid. Handbook of Regression Models in People Analytics: Bayesian Inference (Keith McNulty): Applying statistical probability to human prediction updates and Systems Thinking (Dave Cabrera): On using feedback loops to inform ongoing organizational predictions in complex systems.
