Pre-sales and bid response
More bids, better written — without degrading technical accuracy
A 12-person team handling 200 bids a year. The gain comes as much from bid volume as from time saved. The documented risk here is the most serious of the five.
- Modelled yearly gain
- €161k – €304k
- Payback
- 3.0 to 5.6 months
- Over 3 years
- €338k to €767k net over 3 years
modelled yearly gain
A twelve-person pre-sales team — bid managers, account engineers, technical experts — handles around 200 bids a year at 25 hours each. The reference study covers 758 consultants at a major strategy firm, randomly assigned between equipped and control groups. It measures the gain, but also — more rarely — the cost of poorly bounded use.
- Automatic parsing of tender documents, extracting requirements and evaluation criteria
- First drafts of standard responses from a library of internal references
- Completeness checking: is every requirement in the tender addressed in the submission?
- Consistency review across technical, schedule and commercial volumes
Everything on the table
- Pre-sales team
- 12 people
- Volume handled
- 200 bids/year × 25 h = 5,000 h
- Loaded hourly cost
- €70/h
- Average win rate
- 20%
- Average margin per win
- €45,000
- Year 1 investment (reference library, integration, use-case boundaries, training)
- €75,000
- Annual running cost in later years
- €35,000/year
Three scenarios, not one number
| Parameter | Conservative | Central | High |
|---|---|---|---|
| Time reduction per bid applied | −15% | −20% | −25% |
| Hours saved (valued) | 750 h → €53k | 1,000 h → €70k | 1,250 h → €88k |
| Additional bids at constant headcount | +12 | +18 | +24 |
| Expected additional margin (20% win rate) | €108k | €162k | €216k |
| Total yearly gain | €161k | €232k | €304k |
| Payback period | 5.6 months | 3.9 months | 3.0 months |
| Net cumulative gain over 3 years | €338k | €551k | €767k |
- The risk here is documented and quantified: on tasks outside the tool's competence frontier, equipped users produced 19 percentage points fewer correct answers than the control group. On a technical submission, that reads as fluent, well-written — and wrong.
- The volume half of the gain assumes a market with extra bids to chase and downstream capacity to deliver them. Without that, only the time gain remains — about a third of the model.
- The 20% win rate and €45k margin per win are working assumptions. They are the two heaviest parameters: replace them with yours before any decision.
- A technical submission is contractually binding. Nothing ships without validation by a named expert.
- An explicit map of what the tool handles and what it does not — the direct counter-measure to the risk the study quantifies.
- A clean, current library of internal references, or the tool will recycle your past mistakes.
- Named expert sign-off on every technical volume, traced in the review workflow.
- Before/after win-rate tracking: it is the only indicator that settles the question, and it needs at least two quarters.
What these scenarios are, and what they are not
These are models, built for illustration on public sector benchmarks. They are not results observed at Cardan-AI clients, and they constitute no commitment as to outcome. The improvement rates come from the studies cited; the choice of assumptions, the scope haircuts and the arithmetic are Cardan-AI's, and are shown in full so they can be challenged. Transposed to your organisation, these orders of magnitude can vary widely — in both directions.
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