Experimentation programs lack a fundamental governance tool: an objective experiment scorecard that measures quality and reliability, not just statistical outcomes. Without such a scorecard, your experimentation program is flying blind, mistaking statistical significance for strategic value.
Most organizations approach hiring experimentation leaders the same way they’d hire senior practitioners—looking for deeper technical skills, more testing experience, and better optimization results. This approach virtually guarantees you’ll hire someone who will build a bigger testing factory when what you need is strategic decision-making infrastructure.
The way most companies approach experimentation documentation isn’t just inefficient—it’s a governance crisis that undermines the entire value of your experimentation program.
Your board expects results, your teams need direction, and most critically, you need to prove that experimentation deserves a seat at the strategic planning table. The difference between programs that influence strategy and those that merely execute tests comes down to one crucial element: governance.
If you’re running an experimentation program, you probably have your own system for tracking tests, documenting results, and managing implementation. Maybe it’s a collection of Airtable bases connected to Jira tickets, with results in Google Sheets and insights captured in Notion. Perhaps you’ve created impressive dashboards in Tableau pulling from multiple sources, or built custom workflows connecting various tools.
Congratulations! You have created what we call a “Frankenstack.”
Organizations have invested heavily in testing tools, built dedicated teams, and run hundreds of experiments annually. Yet despite this significant investment, many still struggle to connect promising test results to reliable business outcomes. This disconnect is what we call the “Trust Gap” – the critical space between experimental findings and strategic decision confidence.
