ROI Calculator
| Benefit | Formula |
|---|---|
| Estimator time recovered | bids/month x hours saved/bid x loaded hourly cost |
| Scope-gap avoidance | missed exclusions/year x average cost impact x preventable share |
| Faster bid response | additional bids submitted x win rate x gross profit/project |
| Rework reduction | clarification cycles avoided x hours/cycle x loaded hourly cost |
| Net ROI | (annual benefit - annual tool or implementation cost) / annual cost |
Inputs to Collect
Pull a trailing 90-day sample of bid packages. For each package, capture the number of subcontractor bids received, hours spent leveling, number of clarifications issued, exclusions found late, and bid-decision outcome. This gives you a defensible baseline before introducing AI.
- Monthly bid volume by project type and trade.
- Estimator hours spent comparing inclusions, exclusions, alternates, and assumptions.
- Late-discovered scope gaps and their cost impact.
- Clarification cycles per trade package.
- Bid turnaround time from package receipt to internal recommendation.
- Win rate and gross profit on bids submitted before deadline.
Example Scenario
| Bids leveled per month | 24 |
| Hours saved per bid | 2.5 |
| Loaded estimator cost | $85/hour |
| Preventable scope misses per year | 3 |
| Average scope miss impact | $18,000 |
| Annual platform and implementation cost | $42,000 |
Illustrative result
Time savings: 24 x 2.5 x $85 x 12 = $61,200/year. Preventable scope misses: 3 x $18,000 x 60% = $32,400/year. Total annual benefit before faster-bid upside: $93,600. Against a $42,000 annual cost, that is a 123% simple ROI.
Decision Rule
A bid-leveling automation project is worth prioritizing when it can pay back from time savings alone or when one avoided scope miss covers most of the implementation cost. If the ROI only works after assuming a higher win rate, treat it as a sales-cycle improvement hypothesis and measure it separately.
For the workflow-level guide, read Construction Sub Bid Comparison.
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