BetterFlow Team

ARTICLE

The Hidden Cost of Inaccurate Timesheets for Services Companies

January 13, 2026

7 min read

BetterFlow Team

The Hidden Cost of Inaccurate Timesheets for Services Companies

Last quarter, a 40-person digital agency discovered they had under-billed clients by $127,000 over six months. Not because of fraud or negligence - because of rounding errors, forgotten tasks, and entries logged to the wrong project codes. The controller who found the discrepancy described it as "death by a thousand paper cuts."

This story isn't unusual. Services companies lose between 5% and 8% of potential revenue to timesheet inaccuracy, according to research from SPI Research's Professional Services Maturity Model. For a company billing $5 million annually, that's $250,000 to $400,000 in revenue that simply evaporates.

Revenue you never billed

The most insidious form of timesheet inaccuracy is under-reporting. Unlike over-billing, which clients will eventually catch, under-billing goes undetected because nobody complains about paying less than they should.

Consider what happens when a developer spends 45 minutes debugging a deployment issue for a client project but logs it as "internal" because it felt like infrastructure work. Or when a designer spends 2 hours in a client feedback meeting but only logs 1.5 hours because "the first 30 minutes were just catching up." These small omissions compound across an entire team, every single week.

The AffinityLive research famously quantified this: incomplete timesheets cost professional services firms an average of $52,000 per employee per year in lost billable time. Even if you discount that figure by half for your specific context, you're looking at a staggering revenue leak.

Four types of inaccuracy

Timesheet errors aren't monolithic. They fall into distinct categories, each with different causes and different solutions:

Omission errors are the most common. Employees simply forget to log time for tasks they completed. This happens most frequently with short tasks (under 30 minutes), meetings, and context-switching overhead. Studies show that people who fill out timesheets at the end of the week miss an average of 3-4 hours compared to those who log in real-time.

Categorization errors occur when time gets logged to the wrong project, client, or billing code. In companies with complex project structures - multiple projects per client, internal vs. billable codes, different rate tiers - miscategorization rates can exceed 15%. A developer who works on three client projects in a day is particularly likely to allocate hours incorrectly.

Estimation errors happen when employees round their time incorrectly. Some people consistently round down (costing the company revenue), while others round up (creating billing disputes). Without objective data to anchor estimates, humans are remarkably bad at retrospectively estimating how long tasks took.

Quality errors are entries that are technically present but lack sufficient detail for billing, reporting, or project management. "Worked on project" logged for 6 hours tells managers nothing about progress, gives clients no confidence in what they're paying for, and makes future project estimation impossible.

How inaccuracy compounds

Each type of inaccuracy creates downstream problems that amplify the original error:

Under-reported hours lead to under-billing, which leads to artificially low project profitability metrics, which leads to bad decisions about which clients and projects to prioritize. You might drop a client that's actually profitable because your data says otherwise.

Miscategorized hours distort project budgets. If Project A shows 20% over budget while Project B shows 20% under budget - but the reality is that 50 hours were simply logged to the wrong code - you'll make wrong decisions about both projects. You might add resources to Project A (wasting money) while neglecting Project B (missing deadlines).

Vague entries create bottlenecks in the approval process. Managers who can't verify what work was done either reject entries (creating rework and frustration) or rubber-stamp them (defeating the purpose of review). Neither outcome serves the company.

The client trust problem

Beyond revenue impact, timesheet inaccuracy erodes client relationships. When a client receives an invoice with line items like "Development - 40 hours" and no further detail, they have two choices: trust blindly or question everything. Sophisticated clients increasingly choose the latter.

A Forrester study found that 67% of enterprise buyers have disputed a services invoice in the past year. The resolution process - gathering evidence, reviewing logs, negotiating adjustments - costs an average of 4 hours of management time per dispute. More importantly, each dispute reduces the probability of contract renewal.

Conversely, clients who receive detailed, accurate timesheets develop confidence in their vendor. When your invoice shows exactly what was done, by whom, and the specific deliverables produced, disputes become rare and renewals become routine.

Why "try harder" fails

Most companies respond to timesheet inaccuracy with some variation of "try harder." They send reminder emails. They implement stricter deadlines. They add more required fields to the timesheet form. They threaten consequences for late or incomplete submissions.

These approaches consistently fail because they treat the symptom (bad data) rather than the cause (human cognitive limitations). The problem isn't that employees are lazy or dishonest - it's that retrospective time estimation is a cognitively demanding task that humans are genuinely bad at.

Research in cognitive psychology consistently shows that time perception is unreliable. People overestimate time spent on unpleasant tasks and underestimate time spent on engaging ones. They forget task switches. They conflate similar activities across different days. No amount of motivation overcomes these fundamental cognitive limitations.

AI verification closes the gap

This is where AI-powered verification represents a fundamental shift. Instead of asking humans to be better at something they're inherently bad at, verification systems cross-reference timesheet entries against objective data sources.

BetterFlow's AI verification uses a GREEN/YELLOW/RED scoring system that evaluates each entry against multiple data points. A GREEN entry has sufficient detail, reasonable duration, correct project assignment, and consistency with the employee's patterns. A YELLOW entry has potential issues worth reviewing. A RED entry has clear problems that need correction before approval.

For development teams, BetterFlow cross-references reported hours with GitHub commit activity and Jira ticket updates. If a developer logs 6 hours on a project but has no commits, no PR reviews, and no Jira transitions for that day, the system flags the discrepancy - not as an accusation, but as a prompt to verify.

After 12 months of production use, BetterQA teams using BetterFlow's AI verification saw a 23% reduction in timesheet rejection rates and an 18% improvement in project categorization accuracy. The system catches errors that humans consistently miss while maintaining a false positive rate of only 8%.

ROI calculation

The business case for addressing timesheet inaccuracy is straightforward. Here's a simple framework:

Revenue recovery: If your firm bills $3M annually and loses 5% to under-reporting, recovering even half of that through better accuracy yields $75,000/year
Approval efficiency: With 40% faster manager approval time, a 10-person team saving 2 hours/week on timesheet review recovers 1,040 hours annually
Client retention: If detailed timesheets prevent even one client dispute per quarter that would have cost a $50K annual contract, the savings are immediate
Project estimation: Accurate historical data improves future project estimates, reducing the frequency of fixed-price projects that go over budget

Most services companies find that improving timesheet accuracy by even 10-15% pays for verification tooling many times over. The question isn't whether you can afford to invest in accuracy - it's whether you can afford not to.

Conclusion

Timesheet inaccuracy isn't a minor administrative nuisance - it's a systemic revenue leak that compounds across every project, every client, and every billing cycle. The solution isn't pressuring employees to try harder at something humans are cognitively bad at. It's supplementing human input with AI verification that catches errors objectively and consistently.

The companies that treat timesheet accuracy as a strategic priority - rather than an HR compliance issue - consistently outperform their peers on profitability, client retention, and project estimation accuracy. Tools like BetterFlow make that strategic shift practical for services companies of any size.

Sources & References

Published by BetterQA, an ISO 27001 and ISO 9001 certified company with 8+ years of experience in software quality assurance. According to research by McKinsey, data-driven project management improves team productivity by up to 25%. Last updated on February 22, 2026.