Elite soccer goalkeepers dive left or right on penalty kicks 94% of the time. Statistically, staying in the center of the goal gives a goalkeeper the best chance of making the save. They dive anyway, almost every time.
The behavior has a name: action bias, a documented preference for visible action over a statistically better but passive choice, because standing still feels like failing even when it produces the better outcome. Sales enablement teams run the identical pattern. A CRO flags a problem, and a program gets built and shipped inside days, before anyone diagnoses whether the problem named is the actual cause or just the most visible symptom of something else.
Action bias is a documented preference for visible activity over a statistically better but passive alternative, first measured formally in a study of elite soccer goalkeepers facing penalty kicks. The same bias drives sales enablement teams to build and ship programs in response to a stated problem before diagnosing whether that problem is the real root cause or a symptom sitting on top of one.
What the Goalkeeper Study Found
Michael Bar-Eli and a team of researchers analyzed a large sample of penalty kicks from top leagues and championships, published in the Journal of Economic Psychology in 2007. Given the distribution of where kicks go, the goalkeeper’s statistically best strategy is to stay in the center of the goal. Goalkeepers dive left or right on 94% of kicks regardless.
The explanation the researchers proposed is called norm theory. Diving is the expected, normal action for a goalkeeper facing a penalty kick. A goal scored while the goalkeeper stood still feels worse to that goalkeeper, and looks worse to everyone watching, than a goal scored after a dive in the wrong direction, even though the result on the scoreboard is identical either way. Goalkeepers dive because inaction that fails feels more costly to them than action that fails, even though staying in the center produces more saves over time.
The Same Pattern Inside Sales Enablement
A CRO reports that reps can’t close, and a closing workshop gets built the same week. A VP flags weak objection handling, and an objection-handling module ships. A new product launches, and product training rolls out. A competitor starts winning deals, and a battlecard gets produced. In each case, a request comes in and a program ships in response, and nobody stops to ask whether closing, objection handling, or product knowledge is the real problem or just where the symptom happens to be visible.
The real issue behind a closing problem is often that reps never built a strong enough case earlier in the deal to have anything worth closing. The real issue behind an objection is often that the rep never established enough value early enough for the objection to come up in the first place. Neither of those root causes gets identified by a team that jumps straight to building the response the request implied.
Why Building Feels Safer Than Diagnosing
The cost of not responding to a CRO’s request feels immediate and personal: a program that has not shipped yet looks like inaction, and inaction reads as a team failing to take the problem seriously. Diagnosis takes longer, produces no visible output for the first several days, and might conclude that the original request was aimed at the wrong target entirely, which is an uncomfortable thing to tell the person who made the request. Shipping something, anything, produces an immediate, visible signal of responsiveness, even when what shipped is aimed at a symptom rather than a cause.
The Cost of Diving in the Wrong Direction
McKinsey research estimates that roughly 70% of organizational change initiatives fail, identifying bad problem definition as the leading cause: the initiative solved a problem other than the one driving the outcome. That pattern is not limited to internal programs. A Sales Growth Company’s How Buyers Want to Be Sold research, surveying more than 1,200 B2B buyers, found that 27% do not scope the problem they are trying to solve before they start the buying process, and 48% report having bought the wrong product because they did not understand their own problem well enough. Buyers skip diagnosis. Sales enablement teams, whose entire job is diagnosing and closing performance gaps, frequently skip it too.
Diagnosing Before Building
The alternative to diving first is answering three questions before a single asset gets built: what is broken, what is that problem costing the business, and why does the problem exist in the first place. A program built without a documented answer to the third question, the root cause, is a program aimed at whatever the requester happened to notice, which is rarely the same thing as what is driving the outcome. That three-question discipline, developed at length in Gap Revenue Performance, is what separates a program that fixes the real problem from one that treats a symptom and gets rebuilt again next quarter under a different name.
Running that diagnostic step consistently, on every request, before every build, is a habit an enablement function has to install into its own operating rhythm rather than something it does only when there happens to be time for it.
Building the Habit Into the Operating Rhythm
A team under constant pressure to respond quickly will default back to diving unless diagnosis becomes the standing first step rather than an optional one. That requires the same discipline taught in sales training that gets applied to reps: prescribe only after you diagnose, and build a solution only once you understand what’s broken and why. Enablement teaches that discipline to reps. The same discipline has to apply to enablement’s own work, or the function ends up making the exact mistake it trains the sales organization to avoid.
Frequently Asked Questions
What is action bias?
Action bias is a documented tendency to prefer visible action over a statistically better but passive choice, because standing still and failing feels worse than acting and failing, even when the outcome is identical. It was formally studied in elite soccer goalkeepers, who dive left or right on penalty kicks 94% of the time despite staying in the center of the goal being the statistically better strategy.
What did the goalkeeper penalty-kick study find?
Michael Bar-Eli and colleagues analyzed a large sample of professional penalty kicks and found that goalkeepers dive left or right on 94% of them, even though staying in the center gives the best statistical chance of making a save. The researchers attributed the pattern to norm theory: a goal scored while standing still feels worse than a goal scored after diving the wrong way, so goalkeepers choose the action that protects how the failure feels rather than the action that produces the best outcome.
How does action bias show up in sales enablement specifically?
A CRO or VP flags a problem, such as reps struggling to close or handle objections, and a program gets built and shipped in direct response within days. The problem named in the request rarely gets diagnosed first to confirm whether it’s the real root cause or a visible symptom of something else, such as weak early-stage discovery producing both the closing problem and the objection at the same time.
Why do teams build first instead of diagnosing first?
Because not responding to a request feels like failure immediately, while diagnosis takes time and produces no visible output for several days. A team that ships a program quickly looks responsive. A team that spends a week diagnosing looks slow, even when the diagnosis prevents weeks of wasted work building a solution aimed at the wrong problem.
What does McKinsey’s research say about why change initiatives fail?
McKinsey research estimates that roughly 70% of organizational change initiatives fail, and identifies bad problem definition, not poor execution, as the leading cause. Teams solve a problem that was never the actual problem driving the outcome they were trying to change.
What questions should come before building any sales enablement program?
Three questions, in order: what is broken in the business, what is that problem costing in measurable terms, and why does the problem exist in the first place. Skipping the third question, the root cause, produces a program built for whatever symptom happened to be visible rather than what is driving the outcome.
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