Categories You Will Regret
The category scheme decides what the data can tell you, is almost always chosen too early, and is where most personal tracking becomes unusable.
Categories look like an administrative detail. They are the analysis, decided in advance and usually wrongly. Organisations asking the same question at team level can compare their process with the freelancer resource: define the purpose, make the record visible to the people in it, and interpret time data alongside finished work rather than on its own.
Why choosing early goes wrong
Categories chosen before you have looked encode what you already believe about your week.
Which means the data can only confirm or deny that belief, and cannot show you the thing you had not thought of.
And the awkward entries — the ones that do not fit — are exactly the interesting ones, but a scheme decided in advance forces them into "other" where they disappear.
Record in plain words. Categorise afterwards. This single reversal fixes most of what goes wrong here.
The schemes that fail
Too many categories. Beyond about eight, the decision cost per entry rises and consistency falls. By week two you are guessing.
Categories that overlap. "Email" and "client work" both apply to a client email, and the choice you make varies by mood.
Value-laden categories. "Productive" and "wasted" produce a record that argues rather than describes, and they change meaning as the week goes.
Project-based categories on a week with six projects, which turns every entry into a lookup.
And a category called "admin" that grows until it means nothing — it has its own note because it happens to everybody.
What a workable scheme looks like
Five to eight categories.
Mutually exclusive, with a stated rule for the overlaps: "client email counts as client work" written down once.
Descriptive rather than evaluative.
And at least one deliberately neutral bucket for things you cannot classify, sized so you notice if it grows.
The two-axis alternative
Instead of one list, two simple tags: what it was, and whether it was chosen or arrived.
The second axis — did I decide to do this, or did it come at me — is frequently more informative than any subject category.
A week that is eighty percent arrived-at explains a great deal, and no subject-based scheme reveals it.
Categorising afterwards
Print or export the raw entries. Read them. Group them by what they actually have in common.
You will find three or four groupings you would never have predicted, and that is the exercise working.
Then apply the scheme to the whole record in one pass, which is faster and far more consistent than deciding thirty times a day.
Recategorising later
Keep the original plain-word entries, always.
A record stored only as category totals cannot be re-analysed; a record stored as raw entries can be asked new questions in a year.
This is the single strongest argument for plain text over any tool that only stores categorised data.
What to check
Did you choose categories before or after looking at the data?
How many do you have, and can you state the rule for the overlaps?
Do you still have the raw entries, or only the totals?
And has "other" or "admin" grown past about a tenth of the week — because if so, it is hiding your actual finding.
Keep the raw entries
A record stored only as category totals cannot be re-analysed.
One stored as plain-word entries can be asked new questions in a year, which is the strongest argument for plain text over any tool that discards the original wording.
Worth keeping in mind
Consider two axes rather than one list: what it was, and whether it was chosen or arrived. The second is frequently more informative than any subject category, and a week that is largely arrived-at explains a great deal.
In short
Categories chosen before you have looked encode what you already believe about your week, which means the data can only confirm or deny that belief and cannot show you the thing you had not thought of..
The point
Five to eight categories, mutually exclusive, descriptive rather than evaluative, with the overlap rule written down once.
Beyond that the decision cost rises and consistency falls. For a complementary perspective on work, measurement or planning, consult Google Workspace.