The jobs you win are the ones that hurt
Your estimators price jobs from experience: look at the drawings or the brief, think about similar work, add a margin, send the quote. Some jobs come in on budget. Others overrun badly. When you look at the year, a pattern appears that nobody likes: the jobs you win most easily tend to be the ones that lose money.
It makes sense once you see it. If your price is too low, the customer says yes quickly. If it is right or high, they shop around. Gut-feel pricing does not just produce errors; it selects the worst ones for you to carry out.
Why estimates drift
Estimators remember the jobs that stood out, not the typical ones. They rarely see the final cost of a job they priced, because by the time it closes they are on to the next quote. Material prices move, labour rates change, and certain types of job keep overrunning for reasons nobody has analysed, such as access difficulties, particular customer types or small jobs that carry fixed overheads.
Most businesses have the data to fix this. Job costing, timesheets and invoices hold what every job actually cost. It is just never joined back to the original quote.
What gut-feel pricing costs
| Pattern | Consequence |
|---|---|
| Underpriced jobs won easily | Margin lost on the work you take |
| Overpriced jobs lost | Good, profitable work goes to competitors |
| Inconsistent quotes | Two estimators price the same job differently |
| No feedback loop | The same errors repeat every year |
| Knowledge in one head | Pricing quality depends on who is in the office |
The effect is often invisible in any single job. It shows up as a business that is busy all year and has less profit than it should at the end.
How we predict job cost from your own history
- We join quotes to actual outcomes by bringing together your quoting system or spreadsheets, job costing, timesheets and invoices, so every past job has a quoted figure and a real cost.
- We work with your estimators to list what drives cost in their view, such as job size, type, location, access, materials, customer and season, and turn those into model inputs.
- We train a model that predicts the likely true cost of a job from those inputs, with a range, and test it on past jobs it has not seen.
- We add a check at quoting time: the estimator enters the job details as usual, and the tool shows the predicted cost range next to their price and flags quotes that fall below it.
- Where you have enough data on won and lost quotes, we add a second view showing how price relates to win rate for similar jobs, so pricing decisions weigh margin against the chance of winning.
- We feed each finished job back into the data so the model keeps up with material prices, labour rates and new types of work.
The estimator still sets the price. The model is a second opinion that has seen every job you have done, not just the memorable ones.
What changes for the estimators
Before a quote goes out, the estimator can see what similar jobs actually cost and whether this price is in the danger zone. A flagged quote prompts a second look, not an automatic change. Over time, recurring overruns become visible by type, so you can fix the cause, such as a missing line item or an access allowance, rather than absorb it.
New estimators learn faster, because the tool shows them what the business's own history says rather than relying only on shadowing.
Managers get a view they did not have before: quotes that went out below the predicted cost, and what happened to them. That turns pricing from a private judgement into something the team can review together, without it becoming personal.
Is this your situation?
- Jobs are priced from experience rather than a costed model.
- Some types of job regularly overrun and nobody is sure why.
- You win work easily but margins are lower than expected.
- Quoted prices are never compared with final job costs.
- Different estimators price the same work differently.