Controllable Inputs Review
Judge execution by controllable inputs, then learn from changing outcomes
- Difficulty
- Moderate
- Time to result
- ~weeks to results
- Steps
- 5
- Confidence
- 98%
The Controllable Inputs Review evaluates performance in two layers. First, define the actions, quality standards, decisions, and operating practices the team can directly control. Second, record environmental assumptions such as market conditions, platform rules, or competitor behavior. After the result arrives, assess whether the controllable work met a world-class standard and whether external parameters changed. This protects teams from having months of strong execution dismissed by a single chart while preserving accountability: excellent inputs do not eliminate the need to learn when outcomes disappoint. The review ends by updating assumptions and changing the next set of inputs. Over time, the process produces fairer leadership judgments, better morale, and faster adaptation without abandoning ambitious results.
Origin
Extracted from Marketing Against The Grain during Kieran Flanagan and Kip Bodner’s debate about obsessing over the process rather than the win.
Core principles
- 01Teams control inputs more reliably than outputs
- 02External conditions can change the result despite strong execution
- 03Poor outcomes still require learning and adaptation
- 04Effort should be evaluated without excusing weak execution
How to run it
- 1
Define the Inputs
Before execution, list the actions, decisions, and quality standards the team can directly control. Connect each to the expected outcome.
Pro tip Use observable inputs rather than vague intentions such as trying hard.
Watch out Do not define inputs after seeing the result.
- 2
Record External Assumptions
Document platform behavior, market conditions, dependencies, and other parameters outside the team’s control. State what must remain true for the plan to work.
Pro tip Assign an owner to monitor each major assumption.
Watch out Unrecorded assumptions are easy to rewrite retrospectively.
- 3
Evaluate Execution
Compare the work performed with the agreed input standard. Identify where execution was excellent, adequate, or deficient.
Pro tip Use artifacts and metrics rather than relying on memory.
Watch out A changed environment does not excuse preventable execution errors.
- 4
Explain the Outcome
Determine how execution quality and changed conditions each contributed to the result. Avoid reducing the review to a binary win or loss.
Pro tip Consider counterfactuals: what result might the same work have produced under the original assumptions?
Watch out Do not manufacture external explanations to protect the team.
- 5
Revise and Iterate
Preserve strong practices, repair weak inputs, and update the plan for the new environment. Define the next review cycle.
Pro tip Translate every lesson into a changed action or assumption.
Watch out Celebrating process without adapting to repeated bad outcomes becomes complacency.
In the wild
An experienced search team loses traffic despite maintaining its prior execution standard. The review confirms that publishing, technical quality, and optimization met expectations, but Google changed the parameters of the game. The team preserves strong practices while redesigning its strategy for the new environment.
→ Leadership avoids unfairly labeling the team incompetent and still initiates necessary adaptation.
A campaign underperforms. The retrospective finds both an external competitor launch and an internal delay that reduced distribution time. The team documents both causes, fixes the approval process, and adjusts future launch monitoring.
→ The review produces accountability without pretending the result had only one cause.
Common mistakes
Using Process to Excuse Failure
Strong effort does not remove the obligation to adapt when results remain poor.
Discounting Months of Work
Judging solely from the final chart can erase useful execution evidence and lessons.
Ignoring Changed Parameters
A process that worked previously may stop producing the same outcome when the surrounding system changes.
Is it for you?
Best for
It is best for performance reviews and retrospectives in volatile markets, platforms, algorithms, or competitive environments.
Not ideal for
It is not ideal when used to rationalize consistently poor results without changing the strategy or process.
From the transcript
“Another great insight um was to obsess about the process not the results.”
“you care about the inputs because you can't control the output all the time”
“have we executed to a work class level on the inputs and have the parameters changed in some way that has caused us to have…”
From the episode
Leadership Lessons, Needing to Win, and Cards Against Humanity