What Leaders/Managers Can Learn from Calling Bullshit
Marcus stood before his leadership team with a slide showing a dramatic jump in customer satisfaction after a new process rolled out. A junior analyst had built the chart, and Marcus liked what it told him, so he had not looked closely at how it was built. Later that week, a direct report asked quietly why the axis started well above zero and why the survey sample seemed to include only customers who had already responded. Marcus felt a flash of defensiveness, then recognized the instinct he warned his team against: liking a number too much to question it. He asked for the raw data before the next meeting. The real picture was less dramatic, showing exactly where the process was actually failing rather than confirming everything was fine.
The whole book, compressed
This edition works through 4 core lessons — take them one at a time, not all at once.
What's different for your conditions
Tap whichever ones sound like you. Nothing here is sent or saved — it's just for your own noticing.
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The core lessons, applied to you
Requesting the number behind the number
Marcus's satisfaction chart is a common leadership trap: a subordinate presents a polished figure, and the temptation is to accept it because pushing back feels like distrust rather than ordinary diligence. The habit worth building is treating every dashboard as a claim to be checked, not a fact to be repeated.
Constantly demanding raw data for every routine update can slow a team down and read as micromanagement rather than diligence. Practice: before repeating any number in a meeting above you, ask once where it came from and what was left out of the sample.
Before repeating any number in a meeting above you, ask once where it came from and what was left out of the sample.
Reading the deck your own team hands you
Charts built to please a leader share the same flaws: truncated axes, a favorable date range, or a scale chosen to make a result look bigger than it is. Marcus's willingness to ask about the sample, rather than admiring the shape of the line, uncovered a real problem the chart had been quietly hiding.
Some genuinely strong results really do look dramatic on an honest chart, and reflexive suspicion of every steep line can demoralize a team that did good work. Practice: ask whoever built a chart to redraw it once with a full axis and the complete, unfiltered sample before you present it further.
Ask whoever built a chart to redraw it once with a full axis and the complete, unfiltered sample before you present it further.
Separating what changed from what merely coincided
When a new process launches alongside an improving result, it is tempting to credit the process for everything that followed, ignoring seasonality or other initiatives running at the same time. A causal claim worth acting on should be specific enough that a disappointing quarter could contradict it, not vague enough to survive any outcome.
Organizations rarely run controlled comparisons, so some causal judgment calls are unavoidable even with good intentions. Practice: before crediting one initiative for a result, name one other explanation and check whether it fits the timing as well.
Before crediting one initiative for a result, name one other explanation and check whether it fits the timing as well.
Modeling honest doubt as a leadership habit
How a leader treats an inconvenient number teaches an entire organization what honesty is actually worth there, more than any values statement on a wall ever could. Marcus's decision to question his own favorite result, rather than only the numbers he already disliked, signals that scrutiny is not punishment but respect for the people whose work the data represents and for every decision the organization will make from it.
The hardest tension for leaders is between moving decisively on numbers and pausing to verify them first, since organizations rarely reward a leader who visibly slows down. Marcus cannot re-derive every report from raw data, so the workable approach is reserving real scrutiny for results that shape a resourcing or strategy decision, letting routine updates pass with a lighter check.
Name one thing, honestly
- Which recent number did you repeat upward without checking where it came from? - Whose report do you trust so completely that you have stopped questioning it? - What would change in your team's culture if scrutiny of numbers were routine rather than suspicious?
Good. Now look back at the "Try this" line under whichever lesson feels most connected to what you just wrote, and treat that as this week's actual assignment — not all 4 at once.
The practices from this edition
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Run this for seven days
Before crediting one initiative for a result, name one other explanation and check whether it fits the timing as well.