You paid for a project management platform. Your team is logging updates. The dashboard shows green.

Then you walk the site and something is clearly wrong.

The data existed. It just never connected to a decision.

The real shortage isn’t information

Your project generates data constantly. RFIs, submittals, schedules, change orders, inspection reports, photos, cost curves. If you printed it all out, you’d need a warehouse.

None of it matters if your team is treating data capture as an administrative task rather than a decision-making input.

This is the gap that costs owners money. Not the absence of information, the failure to turn information into action before problems compound.

Frank Thalakotur spent years in HVAC engineering, moved through startup life, and landed in owner’s representation. In every role, he hit the same wall: teams adopting tools and collecting data without understanding what problem they were actually trying to solve. The data sat there. The issues showed up anyway. The change orders came in. The schedule slipped.

His conclusion after all of it: the AEC industry isn’t short on innovation. It’s short on alignment.

What “alignment” actually means on your project

Consider a straightforward framing. You care about three things: budget, schedule, and what the building will cost to operate after you open it.

Your architect cares about design quality and professional liability.

Your GC cares about margin protection and getting paid.

Your engineers care about code compliance and coordination.

None of those incentives are wrong. But they’re not the same as yours. And when the contracts don’t create alignment between your outcome and their behavior, the data your team is collecting is optimized for their interests, not your visibility.

That’s the structural problem. The data exists. The reports get written. The dashboards turn green. And you still get surprised by a scope change on month eight because the information your team was organizing was oriented around their priorities, not yours.

CapEx is the easy part

At a recent executive event, an owner said something that stuck: “I know my CapEx. What I need is clarity on OpEx.”

Your construction budget gets scrutinized line by line. You know the structural steel cost. You know the mechanical package. You can argue the GC’s fee.

What you often don’t know is what the decisions baked into that budget will cost you to operate for the next twenty years. The cheaper HVAC system that requires specialized maintenance. The building envelope detail that looks fine in the drawings and creates an energy performance problem in practice. The lighting control system that your facilities team doesn’t know how to run.

These trade-offs get made in design and construction, usually in value engineering sessions where your operational costs are abstract and the construction savings are concrete. Lifecycle numbers rarely get run in real time. The design decision rarely gets connected to the operational consequence.

That’s a data alignment failure. The information to make better decisions exists. It just doesn’t flow to the right people at the right time.

The questions that should drive your data strategy

Most project owners think about data as reporting: what happened, what it cost, what the current status is. That’s backward-looking and it’s rarely actionable fast enough to matter.

The useful questions are forward-looking. What’s at risk of slipping in the next thirty days? What decisions are pending that will affect budget if they’re not made this week? What are the three things most likely to generate a change order in the next phase?

If your project reporting can’t answer those questions, you have a data problem. Not a lack of data, a lack of data organized around your decisions.

This requires starting with your outcome and building the information architecture backward from there. What do you need to know, and when do you need to know it, to protect your budget and schedule? Build the reporting around that. Stop accepting reports built around what’s easy for your team to generate.

Where AI fits, and where it doesn’t

AI tools are genuinely useful for analyzing large volumes of project data, pulling patterns from inspection reports, flagging schedule risks based on historical performance, summarizing RFI trends before they become change order clusters.

But AI doesn’t solve alignment. You can have the best analysis tools in the world and still get surprised if the data being fed into them doesn’t reflect your project’s real status.

The foundation has to be right first. That means clear definitions of what success looks like, contracts that tie accountability to your outcomes, and a project team with the discipline to report actual status rather than optimistic status.

Get the alignment right, and AI makes your visibility dramatically sharper. Skip the alignment work and add AI, and you’ll get faster reports on the wrong things.

Start with the problem, not the solution

The most expensive mistakes owners make with project data aren’t technology failures. They’re alignment failures. Tools get adopted because the software vendor did a good demo. Reports get generated because someone had to fill out a template. Data gets collected because it was on the list.

None of that is organized around what you need to make better decisions.

Before your next project kicks off, define the three decisions you most need to make in real time to protect your budget and schedule. Then design your reporting around those decisions. Make your team build you the visibility you need, not the visibility that’s convenient for them to produce.

Data is only as useful as the decisions it enables. Make sure yours is pointed at the right problems.