Week 11 Day 4: Your Team Cannot Prioritize What They Do Not Understand

When your team argues about what to work on next, the problem is rarely disagreement about effort or importance. The problem is that they are using different mental models of value. One person thinks performance matters most because they deal with customer complaints. Another thinks new features matter most because they see competitor releases. Without a shared understanding of how the business makes money, every prioritization conversation is just opinion trading.

Here is how information gaps create prioritization dysfunction. Engineer A thinks the login page redesign is critical because three customers complained this week. Engineer B thinks the API performance issue is critical because it showed up in their monitoring dashboard. Product manager C thinks the new integration is critical because sales asked for it. All three are right within their information bubble. None of them know that customer churn is running at 8% monthly and exit surveys point to a confusing onboarding experience -- which means the login redesign is actually the highest-value work by a factor of ten. But nobody shared the churn data with the team. When I started putting the core business metrics on the wall -- literally, printed and taped to the wall -- the prioritization arguments dropped by half. Not because people agreed more, but because they were finally arguing from the same set of facts.

The relationship between information access and decision quality is well-established in organizational theory. Simon's (1947) concept of 'bounded rationality' argues that decision-makers optimize within the bounds of available information rather than globally. Galbraith (1974) formalized this in his Information Processing Theory of Organization, demonstrating that organizational effectiveness depends on matching information processing capacity to task uncertainty. When business metrics are unavailable to the team, they experience what Galbraith calls 'information deficiency' -- and they compensate with local optimization, prioritizing based on their personal exposure to problems rather than organizational priorities. Hackman and Oldham's (1976) Job Characteristics Model identifies 'task significance' as one of five core dimensions of meaningful work. Teams that understand business context rate their work as more significant, which Hackman's research links to higher motivation, quality, and satisfaction. The wall-of-metrics approach aligns with what Womack (1990) calls 'visual management' in Lean manufacturing -- making process information visible to all participants to enable distributed decision-making.