Project Data You Can't Trust Costs Twice

Only 9% of professional services firms say they fully trust their operational data. That finding, from Runn’s 2026 State of Resource Management report, is striking mostly because it isn’t surprising. Most firms already know their project data is unreliable and have decided to live with it.

That decision is more expensive than it looks. Bad project data doesn’t just create one problem. It creates two: every decision takes longer because you have to verify before you act, and margin problems stay hidden until they show up on the final invoice.

The Double Cost of Untrusted Data

When your team doesn’t trust the numbers, they work around them. Project managers build their own tracking spreadsheets. Partners call people directly instead of checking the resource plan. Finance waits until month-end to reconcile because the real-time figures don’t match reality.

Cost one: slower decisions. A staffing question that should take five minutes takes an hour. A scope change that should trigger an immediate margin check gets approved on gut feel. A project review that should surface a problem at week three surfaces it at week ten. Every untrusted data point adds a verification step, and those steps compound.

Cost two: hidden losses. When you expect bad data, you stop looking for signals. The project running 15% over budget doesn’t trigger an alert because the budget figure was wrong to begin with. The consultant logging 30 hours against a 40-hour week doesn’t raise questions because “everyone knows the timesheets aren’t accurate.” According to the SPI Research 2025 PS Maturity Benchmark, average billable utilization dropped to 66.4%, the lowest in the survey’s history and the third consecutive year of decline. Firms can’t fix a utilization problem they can’t measure accurately.

What Does Bad Project Data Actually Look Like?

It’s rarely dramatic. Nobody opens a dashboard and sees obviously wrong numbers. Instead, it’s a collection of small inaccuracies that make the whole picture unreliable.

• Timesheets filled on Friday afternoon from memory. The data exists, but the allocation across projects is approximate. This is the most common source of unreliable project data, and we’ve covered why accuracy matters in detail.
• Project budgets that reflect the original estimate, not the current scope. Scope expanded twice, but nobody updated the budget baseline. Now you’re comparing actual costs against a number that hasn’t been valid for weeks.
• Resource plans that show planned allocation, not actual work. The plan says Maria is 50% on Project A and 50% on Project B. In practice, she spent all week on Project A because it hit a crisis. The plan wasn’t updated.
• Third-party costs entered when the invoice arrives, not when the commitment is made. Your project looks profitable right up until the subcontractor bill shows up in week eight. We’ve explored this blind spot before.

None of these is a system failure. Each is a process gap that widens under pressure, which is when accurate data matters most.

Why Do Services Firms Tolerate Bad Data?

Three reasons come up repeatedly.

The data entry burden feels disproportionate. Consultants see time tracking as administrative overhead that pulls them away from client work. When the tracking system is separate from where actual work happens, they’re right. The friction is real, and it shows up in the non-billable time that fills 30% of a consultant’s week.

Good-enough data worked at smaller scale. When you had five projects and twelve people, the partner knew what was happening from hallway conversations. At twenty projects and forty people, that stops working. But the habits and systems from the five-project era persist. Client onboarding and resource forecasting both break for the same reason.

Fixing data quality feels like an IT project, not an operations win. The conversation about better data usually gets framed as “we need a new system,” which triggers budget discussions and change management fears. Data trust improves when the system where people track time, costs, and progress is the same system where they manage the work. Separate tools for tracking and doing are where data trust breaks down.

Frequently Asked Questions

What project data should services firms track in real time?

At minimum: time logged against each project, third-party costs committed (not just invoiced), resource allocation changes, and budget-to-actual variance. Real-time tracking means capturing these as they happen, not reconstructing them at week’s end.

How does bad project data affect profitability?

Bad data delays intervention. If your budget tracking shows a project is on target but the underlying numbers are stale or approximate, you miss the window to adjust scope, staffing, or client expectations. Most margin erosion happens in the middle of a project, where good data would have flagged the trend early.

What is real-time project visibility?

Real-time visibility means project financials, resource allocation, and delivery status reflect current reality, not a snapshot from last week’s status meeting. It requires capturing data where work happens rather than asking people to report separately.

How Tier2 Keel Closes the Data Trust Gap

The trust problem starts when project management, time tracking, and financials live in separate systems. Each system has its own version of reality, and reconciling them is a manual, error-prone process.

Tier2 Keel keeps the full project lifecycle in one place: from lead capture and scoping through resource allocation, time tracking, cost management, and invoicing. When your team tracks time against the same projects they deliver, and costs flow into the same system that tracks budgets, the data stays trustworthy because it’s generated as a byproduct of work, not a separate reporting task.

See how Keel handles project operations or book a walkthrough with our team.

The firms with the best margins aren’t better at guessing. They built systems where they don’t have to.