What Time Data Must Never Be Used For

There is one mechanism behind everything in this article. Data collected for one stated purpose and used for another stops being accurate, and it does not recover.

People are not being difficult. They are responding rationally to finding out that the thing they were told was for estimating is being used to judge them.

For a vendor-side perspective on employee PC activity tracking, see this guide from Monitask.

The uses to rule out

Ranking individuals

Two people's hours are not comparable unless the work is comparable, which it almost never is.

The person doing difficult, uncertain work posts worse numbers than the one doing routine work. A ranking rewards taking easy work.

And once a leaderboard exists, the data describes competition for the leaderboard.

Performance conversations

Especially if you said the data was for something else.

A single use is enough. Word travels within a day, and every record afterwards is defensive.

If time data must inform performance discussions, say so from the beginning and accept that the accuracy will be lower. What you cannot do is say one thing and do another.

Disciplinary action

Time records are frequently poor evidence — reconstructed, rounded, missing categories, with known biases. Using them to establish that someone underperformed rests a serious decision on approximate data.

And it converts the entire system into a surveillance instrument for everyone who hears about it.

Setting targets from the baseline

"Last quarter averaged 6.2 billable hours a day, so the target is 7."

This guarantees the honest baseline was the last one you will see. The next quarter reports 7.1 and means less.

Baselines are for understanding, not for target-setting. See why time tracking fails.

Comparing teams or sites

Same problem as ranking individuals, scaled. Different work, different clients, different constraints, one number.

And it pushes recording practices apart — the site that records honestly looks worse than the one that does not.

Justifying a decision already made

Redundancies, restructuring, dropping a client. If the decision is made, the data is not informing it.

People recognise this, and it costs the credibility of every future use.

Proving remote workers are working

The most common motivation and the weakest.

Time data does not measure work; it records what someone said they did. Using it as attendance evidence produces attendance-shaped records.

If the question is whether remote people are productive, the answer is in outcomes, not hours. See the line between timekeeping and surveillance.

What it is legitimately for

Worth stating alongside, so the article is not only prohibition.

Understanding where effort goes, at the level of work.

Pricing and estimating. See estimating from your own data.

Finding organisational friction — waiting, approvals, rework, meetings.

Capacity planning, in aggregate.

Billing, where work is billed by time.

And protecting people. Records showing consistent overwork are evidence, usually in the worker's favour.

Notice what these have in common: the subject is the work or the organisation. Where the subject becomes the individual, you have crossed over.

Saying it credibly

A statement of purpose is only worth what your behaviour makes it worth.

Write it down. What the data is for, who sees it, what it will not be used for.

Repeat it whenever the data is used, not only at rollout.

Report at the level of work — project, client, task type. Reporting structure signals purpose more loudly than any statement. For broader independent background, see ICO guidance on monitoring workers.

Give people their own data, which signals that it is not being held over them.

And handle the first hard case correctly. There will be a moment when someone senior wants a per-person report. What happens then determines whether anyone believes the policy. If you concede, say so openly rather than doing it quietly — the quiet version is worse.

Where it gets genuinely difficult

Not everything is clear-cut.

Someone is clearly not working, and the time data shows it. Use the data as a prompt to look properly, not as the evidence. The conversation should rest on outcomes.

A client disputes an invoice. Legitimate, and it is what billing records are for — and it means people knew the records were billing records.

Aggregate reporting where the team is three people. Aggregate is individual at that size. Be honest about it rather than pretending otherwise.

Capacity planning that implies individual capacity. Real, and manageable if the output is a team number.

The test for each: would you be comfortable telling the people recording exactly how this data is being used? If not, that is the answer.

The one-way door

Honest records can become defensive. Defensive records do not become honest again just because you change the policy.

Rebuilding requires visible change over months, and frequently it does not work at all — because the people who learned the lesson are still there.

Which is why the purpose statement is the most consequential decision in the system, and why holding to it matters more than any feature.

The short version

One mechanism: data used for a purpose other than the stated one stops being accurate, and does not recover.

Do not rank individuals, set targets from the baseline, or use it in performance or disciplinary decisions — especially not after saying it was for something else.

Where the subject becomes the individual rather than the work, you have crossed over.

Report at the level of work, because reporting structure signals purpose louder than any statement.

And the first time someone senior asks for a per-person report is the test everyone is watching.