David Taylor
Chief Commercial Officer
Jan 13, 2026
In capital projects, “good enough” data has become the industry standard.
Schedules are mostly right. Cost reports are directionally accurate. Dashboards look impressive enough for the executive committee. And when something feels off, someone inevitably says, “We’ll clean it up next month.”
That mindset is quietly costing owners and contractors millions.
The problem isn’t a lack of tools. Most organizations already run best-in-class systems — scheduling, cost, risk, reporting platforms, and a growing list of AI pilots layered on top. The real issue is what happens between those systems. Data is fragmented, duplicated, transformed, and reinterpreted so many times that confidence erodes long before decisions are made.
When data is merely “good enough,” decision-making slows. Teams spend more time validating reports than acting on them. Analysts become full-time translators. Executives stop trusting dashboards and revert to instinct and anecdote — the most expensive analytics tool ever invented.
This is where the hidden cost shows up.
Late signals don’t look late — until they are. Small variances don’t raise alarms — until they compound. Risk isn’t visible early, when it’s manageable; it’s discovered late, when options are limited and expensive. By the time leadership asks the hard questions, the data is already out of date.
AI doesn’t fix this. In fact, it exposes it.
Advanced analytics and AI depend on clean, consistent, governed data. When the underlying foundation is shaky, AI simply produces faster confusion. The algorithms work exactly as designed — on data that was never fit for decision-making in the first place.
What’s missing is not another dashboard or another model. It’s a data foundation built for capital projects — one that treats project data as an enterprise asset, not a byproduct of reporting.
This is the gap the Unified Project Platform (UPP) was designed to close.
UPP doesn’t replace your systems. It connects them. It standardizes how schedule, cost, risk, and performance data are structured, governed, and shared across the portfolio. The result isn’t prettier charts — it’s faster, more confident decisions based on a single, trusted version of project truth.
Organizations that move beyond “good enough” data gain something far more valuable than insights: they gain time. Time to act earlier. Time to manage risk instead of react to it. Time to trust what they see and focus on outcomes, not explanations.
The industry talks a lot about digital transformation and AI. But the real competitive advantage is quieter — and far less glamorous.
It’s data you don’t have to apologize for.
Before investing in the next AI tool or analytics initiative, ask a simpler question: Is your project data merely good enough — or is it actually ready to drive decisions?