Project Estimates: Why Services Firms Get Them Wrong

You quoted 400 hours. The team logged 580. The client is happy, the deliverable is strong, and your margin just dropped from 35% to 14%. Nobody made a mistake. Nobody slacked off. The estimate was simply wrong.

This happens on every second or third project in most professional services firms, and yet few firms treat estimation as a problem worth solving. They chalk each overrun up to scope changes or unusual complexity, then move on. The pattern repeats.

The cost isn’t just the overrun on any one project. It’s what happens when inaccurate project estimates compound across dozens of engagements a year, turning a healthy-looking pipeline into a quiet margin problem.

Why Project Estimates Fail Systematically

Bad estimates aren’t random. They follow predictable patterns that repeat across firms, industries, and project types.

The optimism bias

Behavioral economics research has documented this extensively. People underestimate how long tasks will take, even when they have direct experience with similar work. Daniel Kahneman’s work on the “planning fallacy” showed that this isn’t an experience problem. Experts are often more optimistic than novices because they mentally simulate the best-case scenario and anchor on it.

In a services context, your most senior people, the ones doing the estimating, are often the most likely to underestimate. They remember how long the work took them, not how long it takes the team that actually delivers.

Anchoring to the sale

Estimates in professional services rarely happen in a vacuum. They happen in a sales context, where the estimator knows (consciously or not) that a lower number is more likely to win the deal. According to the SPI Research 2026 Professional Services Maturity Benchmark, even top-performing firms see a gap between quoted and delivered margins, with industry EBITDA averaging just 9.9% against project-level margins of 37.2%.

That gap is partly structural, but anchoring plays a real role. When a partner knows the client’s budget is $120,000, the estimate tends to land at $115,000 rather than the $145,000 the work actually requires.

Missing the non-billable work

Most estimates cover the visible deliverables: the code, the report, the design, the training sessions. What they consistently miss is the invisible work surrounding every engagement:

• Internal coordination. Standups, status meetings, slack threads, email chains between team members
• Client management. Check-in calls, requirement clarification, review rounds, ad-hoc questions
• Ramp-up time. Learning the client’s systems, reading documentation, getting access to environments
• Quality assurance. Internal reviews, testing, rework after feedback
• Administrative overhead. Time entry, progress reports, invoice preparation

In our experience working with mid-size services firms, this invisible work accounts for 15 to 25% of total effort on a typical engagement. If your estimate only covers deliverable work, you start every project underwater.

Treating projects as unique when they’re not

Services firms pride themselves on bespoke work. But most projects share structural similarities with past engagements. The database migration for Client B has different specifics than the one for Client A, but the effort profile, the phases, the risks, and the typical overrun points are remarkably similar.

Most firms don’t capture this pattern data in a way that’s accessible when the next estimate happens. The knowledge lives in people’s heads, and those people are usually too busy delivering work to sit in on every scoping call.

What Bad Estimates Actually Cost

The direct cost of a bad estimate is obvious: you deliver more work than you priced. But the downstream costs are often larger.

Margin erosion across the portfolio. If your average estimate misses by 20%, and you run 50 projects a year, you’re not dealing with 50 isolated overruns. You’re dealing with a margin deficit that no amount of project-level optimization can fix. The average professional services firm captures only 72% of billable hours worked, and poor estimation is a root cause.

Resource planning failure. When projects run longer than estimated, they consume resources allocated to the next engagement. This creates a cascade: the next project starts late, its team is stretched, and it too runs over. Capacity planning becomes guesswork because the inputs are wrong.

Team burnout. When every project runs hot, the team absorbs the difference. They work longer hours, skip breaks, rush through quality checks. The overrun isn’t free. It comes out of people’s energy and commitment, and over time, your best people leave.

Pricing dysfunction. If you can’t trust your estimates, you can’t trust your pricing. Some firms respond by padding everything by 30%, which makes them uncompetitive on deals they’d have won at an accurate price. Others hold the line and absorb the margin hit. Neither approach works long-term.

How Do Services Firms Build Better Estimates?

Better estimation isn’t about guessing more carefully. It’s about building a feedback loop between delivery data and future estimates. Firms that estimate well do it on evidence, not instinct.

Step 1: Capture actual vs. estimated on every project

Most firms track time for billing purposes, but they don’t compare actual hours by phase, role, and task type against the original estimate. Without that comparison, there’s no data to learn from.

The comparison needs to happen at a granular level. Knowing that “the project went 40% over” isn’t actionable. Knowing that “requirements gathering took 3x the estimate, development was accurate, and testing took 1.5x” gives you something to fix.

Step 2: Categorize your projects

Not all projects are the same, but they’re not all different either. Create categories based on the factors that drive effort: project type (implementation, assessment, migration, development), complexity (small, medium, large), client maturity (first engagement, established relationship), and domain.

With even 10 to 15 completed projects per category, patterns emerge. You’ll see that migrations always take 20% longer than you think, that first-time clients add 15% overhead, and that your internal review process consistently adds a phase nobody estimates for.

Step 3: Build reference ranges, not single-point estimates

A single-point estimate (“this will take 400 hours”) is a bet. A range (“this will take 350 to 500 hours based on similar projects, with a most-likely scenario of 420”) is a conversation.

Reference ranges grounded in historical data change the estimation dynamic. The estimator isn’t guessing anymore. They’re positioning the current project within a known distribution, and when they diverge from the range, they need to articulate why this project is different. That’s the critical thinking single-point estimates skip entirely.

Step 4: Separate estimation from selling

The person who builds the estimate should not be the person whose commission depends on winning the deal. This is a real problem in many firms, where partners both estimate and sell, and the conflict of interest is built in.

If full separation isn’t possible, at least introduce a review step. Have someone outside the sales side check the estimate against historical benchmarks before it goes to the client. That single check catches the worst anchoring-driven underestimates.

Step 5: Update estimates during delivery

An estimate made at the start of a project is based on the least information you’ll ever have. As the project progresses, you learn things that change the picture. Requirements are more complex than expected. The client’s data is messier. A key team member gets pulled to another engagement.

Good estimation practice means updating the forecast at regular intervals, not just at kickoff. Compare the forecast-to-complete against the budget-remaining at every milestone. If the numbers diverge early, you have options: renegotiate scope, adjust resourcing, or reset client expectations. If you wait until the end, you have a write-off.

The Role of Systems in Estimation Accuracy

Spreadsheets can track estimates for a while. They break down when you need to actually do what improves estimation: compare patterns across projects, roles, and time periods.

A firm that keeps estimates in a partner’s notebook, actuals in a time-tracking tool, and project details in a separate PM tool has three data sources that never talk to each other. Building a reference class means manually pulling from all three, which happens once a year at best, if at all.

When the estimate, the staffing plan, the time entries, and the project financials live in one place, estimation feedback becomes automatic. When a project closes, the system already knows the estimate, the actual, and the variance by phase. That data is available the next time someone estimates a similar engagement, without anyone having to chase it down.

One firm learns from every project. The other repeats the same estimation mistakes for years. The data exists in both places. Whether it’s accessible when it matters is what separates them.

Why Top-Down and Bottom-Up Estimates Disagree

Most services firms use one of two approaches, and rarely reconcile them.

Top-down estimation starts from the outcome. “Projects like this usually cost $150,000.” It’s fast, it leverages experience, and it’s directionally right. But it hides assumptions. Why $150,000? What’s included? What’s not? If the scope differs from the reference project by 20%, does the estimate adjust by 20%? Usually not.

Bottom-up estimation starts from the work breakdown. “We need 40 hours of discovery, 120 hours of development, 60 hours of testing…” It’s detailed, forces you to think through the work, and feels rigorous. But it misses coordination overhead, management time, and the scope creep that happens between defined phases.

The firms with the best estimation track records use both approaches and compare. If the top-down says $150,000 and the bottom-up says $120,000, that $30,000 gap demands investigation. Usually, the bottom-up estimate is missing something the top-down estimate has absorbed intuitively but hasn’t named.

From Anecdote to Evidence

Moving from gut-feel to evidence-based estimation is a culture change more than a technology change. It requires a few things most firms haven’t formalized:

• No blame for accurate reporting. If project managers are penalized for surfacing overruns early, they’ll hide them until it’s too late. The data you need for better estimates comes from honest delivery tracking.
• Estimation as a skill, not a talent. Some people are naturally better estimators. But estimation can be taught, practiced, and improved. Firms that treat it as a learnable discipline, with reviews, feedback, and coaching, improve faster than those that leave it to individual judgment.
• Closing the loop. After every project, spend 30 minutes comparing the estimate to the actual. Not to assign blame, but to update your model and your data. What did you miss? What was accurate? What would you change next time? Most services firms skip this, and it’s the single highest-ROI activity they’re not doing.

According to Hinge Research Institute, high-growth professional services firms invest 8 to 12% of revenue in business development activities. A portion of that goes to proposals and estimates. More accurate estimates don’t just protect margins. They make the sales process more honest, which builds the kind of client trust that drives repeat business.

Frequently Asked Questions

Why are project estimates so often wrong in professional services?

Project estimates fail for structural reasons, not random ones. Optimism bias causes estimators to anchor on best-case scenarios. Sales pressure pushes estimates down. And most firms don’t account for invisible effort like internal coordination, client management, and ramp-up time, which typically adds 15 to 25% to total project cost.

How can a services firm improve project estimation accuracy?

Build a feedback loop: capture estimated vs. actual hours on every project at a granular level, categorize projects by type and complexity, and create reference ranges from historical data. Separate the estimation role from the sales role where possible, and review estimates against benchmarks before they go to clients.

What is reference class forecasting for professional services?

Reference class forecasting means estimating a new project by looking at actual outcomes from similar past projects, rather than building the estimate from scratch. You identify comparable engagements, look at their effort profiles, and use that distribution to set expectations. It counteracts optimism bias by anchoring estimates to real data instead of assumptions.

How much do bad project estimates cost a services firm?

The average professional services firm captures only 72% of billable hours worked, and poor estimation is a primary driver. Beyond direct margin loss, bad estimates cause resource planning failures, team burnout, and pricing dysfunction. A firm running 50 projects per year with a systematic 20% estimation miss is leaving significant margin on the table across every engagement.

Should services firms use top-down or bottom-up estimation?

Use both and compare. Top-down estimates leverage pattern recognition and catch the big picture but hide assumptions. Bottom-up estimates force detailed work breakdowns but consistently miss coordination overhead and scope changes. When the two approaches disagree, the gap points to risks or hidden work that needs investigation before the estimate goes to the client.

How Tier2 Keel Connects Estimates to Outcomes

The estimation feedback loop described above only works when estimate data, time entries, and project financials live in the same system. Tier2 Keel tracks the full project lifecycle from lead to delivery to invoicing, which means the variance between quoted effort and actual effort is visible on every closed engagement.

When your next estimate starts, the historical data is already there: how long similar projects took, where the overruns happened, and which project categories consistently outrun their budgets. Instead of starting from a blank spreadsheet and a partner’s memory, you’re starting from the actual delivery record.

Keel’s project management also surfaces in-progress variance during delivery, not just at project close. If a project is trending over budget at the halfway mark, you see it early enough to act.

See how Keel works for services firms or book a walkthrough with our team.

The firms that estimate well in five years aren’t the ones that hire better estimators. They’re the ones that build systems to capture what actually happened and feed it back into the next estimate. Every closed project is a data point. The question is whether you’re using it.