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Counterfactual analysis and the question of what would have happened anyway
A counterfactual is a statement about a world that did not happen: what sales would have been without the campaign, or how the plan would fare if interest rates had not fallen. Counterfactual analysis uses those other worlds in two ways. It measures the true effect of a choice, and it tests whether a plan survives when a key assumption proves false.
The baseline question
Every claim that an action worked hides a comparison. If sales rose 10 percent after a campaign, the effect of the campaign is 10 percent less whatever sales would have done without it. Economists and statisticians build careful methods around this, such as control groups and comparisons with a similar market that was left alone.
For an ordinary business decision, the habit matters more than the method. Before crediting a choice with a result, ask what would most likely have happened had you done nothing.
Testing a plan's assumptions
The second use looks forward. List the assumptions a plan rests on, then write the false version of each: demand grows 3 percent instead of 10, the new hire leaves within a year, the supplier misses its date.
Score the plan again in each of those worlds. A plan that leads in all of them is sturdy. A plan that leads only where everything goes right is fragile, however fine it looks in the base case.
Keeping the work manageable
There is no need for a counterfactual on every assumption. Rank them by how far the result would move if each were false, and test the top three. Write each alternative world as a short, specific paragraph with numbers, so it can be scored rather than merely discussed.
The common mistake
Imagining the other world without changing the numbers. A team lists five things that could go wrong, nods, and keeps the original forecast. Unless the alternative world is scored, the exercise produces worry rather than information. A second mistake is a flattering baseline, such as comparing a new campaign with the weakest month of the previous year.
How the room tests the other world
In a Decision Room, the Red Teamer runs the stress scenarios in which the plan's key assumption fails, and the engine works the sums again from your own figures in each. The Strategist looks for a materially different path that holds up in more of those worlds. The Judge's Verdict names the conditions that would change the result, so the fragile assumption is written on the record before the Human Decision is made.
A campaign measured against its baseline
A shop ran a $30,000 advertising campaign in May, and May sales reached $410,000 against $360,000 in April, a rise of $50,000. The campaign appears to have paid for itself and more. Yet the same shop's sales rose by about $35,000 from April to May in each of the previous two years, with no campaign at all. Against that baseline, the campaign added roughly $15,000 in sales. At a 40 percent gross margin, that is $6,000 of profit on a $30,000 spend. The counterfactual turns an apparent success into a clear loss, and it changes whether the campaign should run again next spring.
Questions
- How does counterfactual analysis differ from scenario planning?
- Scenario planning describes several possible futures. Counterfactual analysis asks a narrower question: how the result changes if one specific assumption is false, or what would have happened without one specific action.
- How do I estimate what would have happened anyway?
- Look for a comparison the decision did not touch: the same period in earlier years, a similar region or customer group that was left alone, or the trend before the change.
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