Your team just completed a promising A/B test. The results show a 15% improvement in your key metric with 95% statistical confidence. The sample size was robust, the methodology sound, and the data looks compelling.
Then comes the inevitable question:
"So what do we do now?"
What follows is a familiar dance. Marketing wants to roll it out immediately. Product requests more testing. Engineering worries about technical implementation challenges. Leadership asks for ROI projections. Two weeks pass. Then four. Then six.
By the time a decision is made, the market conditions have changed, a competitor has shipped something similar, and the original hypothesis feels stale.
This disconnect between experimental results and business decisions is what I call the Trust Gap: the space where any experiment outcome, regardless of statistical significance, fails to translate into clear strategic action.
Some organizations approach experimentation with a fundamental flaw: post-hoc decision making.
When teams wait until after seeing results to decide what they mean and what actions to take, they have already compromised the integrity of their decision-making process. Post-hoc decisions are inherently unreliable because they are made in the emotional and political context of known outcomes.
Consider what happens in your mind when you see different results:
With strong positive results, suddenly small concerns get dismissed and implementation seems urgent. With negative results, you start questioning the methodology or finding reasons why the test "was not really fair." With inconclusive results, everyone becomes an expert on why the results do not matter or need extending.
This is not poor judgment. It is human nature. But it is exactly why post-hoc decision making undermines even the most rigorously designed experiments.
Three forces make post-hoc decisions unreliable:
Emotional contamination. Once results are visible, rational evaluation becomes nearly impossible. A 3% improvement becomes "clearly significant" if you needed good news, or "barely meaningful" if you were hoping for dramatic results.
Retrospective rationalization. Business contexts and priorities inevitably shift during experiment cycles. What seemed strategically vital six weeks ago gets reframed as "not that important" if results are disappointing, or suddenly becomes "critical to implement immediately" if results exceed expectations.
Stakeholder politics. When decisions wait until after results, they become political rather than scientific. Each stakeholder advocates for interpretations that support their departmental goals. The experiment becomes secondary to the organizational dynamics.
A decision protocol is a pre-commitment device. It eliminates post-hoc decision making by requiring teams to agree on what they will do for every possible outcome before they see any results, when their judgment is unclouded by emotional investment or political pressure.
The concept comes from behavioral economics. Just as Odysseus had himself tied to the mast to resist the sirens, decision protocols tie your team to rational decision-making before the emotional pull of results can influence judgment.
Decision protocols require teams to establish three elements before any experiment launches: