How Bid Qualification Scoring (BQS) works
The full mechanics behind the Bid Qualification Score (BQS): category weights, the Pwin formula, scoring scales, gate rules, constraints, and penalties. This is the reference for anyone who wants to understand exactly how the number is produced.
Start free1. Category structure and weights
A BQS is a weighted score across eight categories. The weights (Balanced profile) sum to 100%.
| # | Category | Weight |
|---|---|---|
| 1 | Customer Relationship | 20% |
| 2 | Competitive Position | 17% |
| 3 | Solution Fit | 17% |
| 4 | Business Case | 12% |
| 5 | Resource Availability | 9% |
| 6 | Risk Factors | 8% |
| 7 | Opportunity Cost & Trade-offs | 9% |
| 8 | Reputational Risk | 8% |
2. Scoring mechanics
Each category produces a normalised score between 0 and 1. Its contribution to Pwin is that score multiplied by the category weight. The final Pwin is the sum of all eight contributions, expressed as a percentage:
Pwin = Σ ( category score × category weight )
| Tier | Per-category input | Resolution |
|---|---|---|
| Rapid Assessment | One binary Yes/No per category | A fast go/no-bid signal |
| Deep Analysis | Multiple questions scored 0–10 per category | A precise, dependency-aware score |
3. Deep Analysis scoring scale
In Deep Analysis every question is answered on a 0–10 scale, anchored into five bands.
| Score | Band | Meaning |
|---|---|---|
| 9–10 | Exceptional | A decisive strength; a genuine, defensible advantage. |
| 7–8 | Strong | Clearly favorable, with only minor gaps. |
| 5–6 | Moderate | Balanced — real strengths offset by real weaknesses. |
| 3–4 | Weak | A material disadvantage that needs a plan to address. |
| 0–2 | Very Weak | A serious problem; likely fatal to the pursuit if unresolved. |
4. Go/No-Bid recommendations
The final Pwin maps to a recommendation. These are the Balanced profile defaults.
| Pwin | Recommendation |
|---|---|
| 60% and above | Go |
| 35% – 59% | Conditional |
| Below 35% | No-Bid |
| Any no-bid gate triggered | No-Bid (overrides the score) |
5. Gate rules
Some findings are decisive regardless of the weighted score. A gate rule forces a No-Bid recommendation when a category reveals a disqualifying condition — for example, no realistic access to the decision maker, or a requirement the organization fundamentally cannot meet. A triggered gate overrides the numeric Pwin so a fatal flaw is never averaged away by strength elsewhere.
6. Within-category constraint chains
Inside a category, answers are not always independent. A within-category constraint chain caps one question's effective score based on another in the same category — so a pursuit cannot claim a strong overall category position while a foundational question within it is weak. This keeps a category score honest to its weakest load-bearing element.
7. Cross-category constraints
Constraints also run between categories. A cross-category constraint caps or flags one category based on the state of another — for instance, a strong Solution Fit is worth less when Customer Relationship is weak, because a great answer to a question nobody trusted you to hear rarely wins. Cross-category constraints keep the model from rewarding strengths that cannot actually be realised.
8. Silo Penalties
In a multi-perspective Deep Analysis, different roles score the same pursuit independently. When those perspectives diverge sharply — sales sees a certain win, delivery sees a disaster — that divergence is itself a risk signal. A silo penalty reduces the weighted contribution of a category in proportion to how far the role perspectives diverge on it.
The effect is deliberate: a category where the team strongly disagrees cannot quietly prop up the overall Pwin. The penalty surfaces the disagreement, quantifies its drag on the score, and points the team at exactly the conversation they most need to have before committing to the bid.
9. Scoring polarity
Every question is written so that high is always good — a higher score always means a stronger position on that factor, and a lower score always means a weaker one. Consistent polarity means a category score, and the Pwin built from it, can be read at a glance without checking which way each question runs.
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