In presales and bidding, testing estimation is one of the most challenging and most misunderstood activities. Testing teams are expected to provide accurate effort estimates under tight timelines, limited requirements, and strong commercial pressure to stay competitive. Too often, testing estimates are reduced to simple numbers: test cases, person-days, or percentages of development effort.
Yet many projects fail not because the numbers were wrong, but because the assumptions behind those numbers were never made explicit.
This blog explains why risk-based testing estimation, combined with clear and well-defined assumptions, is essential for successful testing bids and why assumptions matter more than the estimate itself.
1. Why Testing Estimation Is Especially Difficult in Bidding
Bidding environments are inherently uncertain. Common constraints include:
- High-level or incomplete requirements
- Unclear or evolving system architecture
- Unknown data volumes and usage patterns
- Limited visibility into integrations and non-functional requirements
- Short turnaround times for proposals
Despite this uncertainty, testing teams are still expected to provide firm estimates and delivery commitments. Without a risk-based approach, these estimates quickly become optimistic guesses rather than realistic plans. In this context, precision is less important than transparency.
2. The Problem with Traditional Testing Estimation
Traditional testing estimation methods often focus on:
- Number of test cases
- Number of test cycles
- Percentage-based effort allocation
While these approaches provide structure, they assume stability where none exists and treat all features as equal. This limitation becomes especially dangerous in presales, where uncertainty is highest.
As a result, teams often face:
- Underestimated testing scope
- Missing non-functional coverage
- Hidden dependencies
- Delivery teams absorbing unplanned effort after project award
The outcome is familiar: budget overruns, delivery delays, and growing friction between presales and delivery teams.
3. What Is Risk-Based Testing Estimation?
Risk-based testing estimation shifts the focus from “how much testing” to “where testing effort matters most.”
Instead of estimating all areas equally, testing teams evaluate risk factors such as:
- Business criticality
- Technical complexity
- Integration dependencies
- Data sensitivity
- Performance and security exposure
Testing effort is then weighed toward high-risk areas, while lower-risk areas receive proportionate attention.
In bidding, this approach answers two critical questions:
- Where should testing effort be prioritized?
- What risks are we explicitly accepting or deferring?
4. Why Assumptions Are the Most Important Part of a Tester’s Bid
In presales, assumptions are unavoidable. The real difference lies in whether they are explicit or implicit.
Well-defined assumptions:
- Enable estimation despite incomplete information
- Create transparency with stakeholders
- Protect delivery teams after project award
- Provide a clear mechanism for scope adjustment
Estimates describe effort. Assumptions describe risk.
Without documented assumptions, estimates become disconnected from reality.
5. Common Testing Assumptions That Directly Impact Estimation
Typical assumptions in testing bids include:
- Stability and completeness of requirements
- Number and complexity of integrations
- Availability and quality of test data
- Supported devices, browsers, and environments
- Expected user load and performance thresholds
- Scope of security, accessibility, and compliance requirements
Each assumption directly influences:
- Test scope
- Resource allocation
- Timelines
- Overall delivery risk
Documenting these assumptions is not optional, it is essential.
6. How Risk-Based Estimation and Assumptions Work Together
A practical presales approach combines both risk-based estimation and explicit assumptions:
- Identify high-risk functional and non-functional areas
- Estimate testing effort based on those risks
- Document assumptions for all unknowns
- Define the impact if assumptions change
Example: Performance testing effort assumes a maximum of X concurrent users. Any increase beyond this threshold will require scope and effort re-alignment.
This approach allows teams to proceed confidently while remaining protected.
7. What Happens When Assumptions Are Missing
When assumptions are not documented:
- Scope creep is labeled as “expected work”
- Testing teams are blamed for delays
- Budgets are exceeded silently
- Tension arises between presales and delivery
In reality, most testing delivery failures are not caused by poor estimation but by unstated or ignored assumptions.
8. Best Practices for Managing Assumptions in Testing Bids
| Best Practices | Examples |
| Make assumptions explicit and visible | Test data availability is assumed by Sprint 2; delays may impact regression execution. |
| Link each assumption to scope and effort impact | Performance testing effort assumes ≤ 5,000 concurrent users. Higher load requires re-estimation. |
| Avoid overly optimistic assumptions | Bad assumption: Test data will be sufficient Good assumption: Estimation assumes representative test data is available for key scenarios; additional effort may be required if data must be created or masked |
| Categorize assumptions by risk level | Low risk: Test environment setup Medium risk: API integration availability High risk: Third-party payment gateway stability |
| Use phased or optional testing for high uncertainty | Accessibility Testing is proposed as an optional phase once architecture is finalized. |
| Define clear triggers for scope re-alignment | Any addition of supported devices beyond the agreed matrix will require scope adjustment. |
| Validate assumptions with bid teams/delivery team (if any) before submission | Tester and Solution Architecture jointly reviewed the non-functional testing scope and agreed that performance testing is out of scope. This decision is based on the project scope covering frontend development only, with no backend services included, and the absence of any heavy-load or performance-critical features in the application. |
| Use assumptions as risk control, not disclaimers | Assumptions are reviewed at project kickoff and used to confirm or re-baseline testing scope. |
9. Leadership Takeaway
Winning a bid with minimal testing effort is easy. Delivering successfully without clear assumptions is not.
Strong bids balance:
- Competitive pricing
- Risk-based testing focus
- Transparent assumptions
This balance protects delivery teams, reduces surprises, and strengthens long-term client trust.
10. Conclusion
In presales and bidding, risk-based testing estimation and clear assumptions are inseparable. Estimates provide structure, but assumptions provide protection.
When test leaders make risks visible and assumptions explicit, they don’t just improve estimation, they enable realistic delivery and sustainable success.
In the end, the goal is not just to win the bid, but to deliver it well.