Turning Competing Priorities Into Defensible Funding Decisions
Built DecisionLens, an AI-enabled decision surface that reduces every initiative to return per dollar at risk and ranks the whole portfolio, so funding follows impact instead of persuasion.
The Challenge
Every prioritization meeting wastes capital twice. A strong initiative loses to a weaker one because someone had a sharper deck or a bigger title, and a doomed project limps along for another year, quietly eating budget and engineering capacity, before everyone admits what half the room already knew. The problem is rarely a lack of ideas. It is that most organizations have no honest, shared way to compare them. Scorecards rate everything one to five on impact, effort, and strategic fit, then everyone quietly tunes the weights until their own project lands on top. The comparison gets faked, and capital gets allocated by persuasion instead of impact.
Our Approach
We built a framework that makes tradeoffs visible, structured, and defensible, and turned it into an AI-enabled tool: DecisionLens. The idea is simple. Reduce every initiative to one number, return per dollar at risk, read over a fixed window such as three years: Priority (EV per $) = [ Annual benefit × Value years × Probability of Success − Risk × Exposure ] ÷ Cost Above 1.0, an initiative returns more than it cost. Below 1.0, it does not. Everything sits in real dollars, so there are no fake weights to tune. The output is a ranked decision surface, best return first, with the reasoning behind each rank, the assumptions it depends on, and the watch-outs a click away on every row.
The Result
Prioritization shifts from persuasion to evidence. Leaders get a single ranked list with a clear funding line, so it is obvious what gets the green light, what waits, and what gets stopped, and every decision is defensible in real dollars. The debate becomes concrete, testable, and harder to game. Instead of arguing over whose deck is sharper, teams argue about assumptions that are visible on the surface, where they can actually be checked. DecisionLens is live at decisionlens.space.