In Agile teams, misaligned story point estimates happen frequently.
In a recent sprint planning session for an e-commerce application, my team faced significant estimation differences for a seemingly simple feature:
"As a user, I can filter products by price range."
The developer estimated 3 points, considering it a straightforward implementation using existing components. However, as a QA engineer, I estimated 8 points.
I identified several testing complexities the developer hadn't considered:
This example illustrates why estimation discrepancies are natural and potentially valuable.
In my team’s case, we used this discrepancy as an opportunity to discuss testing requirements thoroughly, ultimately agreeing on 5 points after understanding each other's perspectives.
However, when not managed well, misaligned estimates could lead to missed deadlines, disappointed stakeholders, and team members who lose confidence in the planning process.
So, let’s discuss steps that you can take to align different perspectives on the estimate on your team using a practical example.
To demonstrate how QA engineers can improve estimation accuracy, let's walk through a practical example using a flight sorting feature. We'll apply a structured step-by-step approach to the user story, showing how breaking down testing activities leads to more realistic estimates.
User Story: "As a traveler, I can sort flight prices from low to high."
Acceptance Criteria:
1. Flights should be sorted in ascending order by price
2. If no flights are available, display "Please search using different combinations"
3. If two flights have the same price, sort them alphabetically
First, break the story into discrete testing activities, and don’t assign points immediately. A breakdown could be:
This increases estimation accuracy by reducing the likelihood of missing critical testing activities.
For each activity, evaluate the complexity factors that affect the estimation using questions.
Evaluating complexity factors enables efficient resource allocation by identifying areas that require the most attention and could impact time.
Planning Poker is a collaborative estimation technique used in Agile teams to predict the effort or complexity of user stories. Each team member selects a card (usually from a Fibonacci sequence) to represent their estimate, and all cards are revealed at the same time.
This encourages discussion, uncovers misunderstandings, and helps the team reach a shared understanding of the work involved. It involves:
Silent Assessment: After the story is presented, everyone silently considers their estimate
Simultaneous Reveal: All team members show their estimates at once to avoid anchoring bias
Explain Outliers: Those with the highest and lowest estimates explain their reasoning
QA Perspective Sharing: As a QA engineer, articulate testing considerations.
"I estimated 5 points because we need to verify the sorting algorithm with various price combinations, test the empty state message, validate alphabetical sorting for identical prices, and ensure compatibility across our supported browsers and devices. We'll also need regression testing since the sorting mechanism affects multiple pages."
Convergence Discussion: The team discusses until reaching consensus or a reasonable compromise
While Agile emphasizes story points over hours, stakeholders sometimes need time estimates. Let’s break down the 5-point story into QA activities with time allocations:
Total estimated QA effort: 5 hours
Combining Planning Poker with historical comparison is particularly effective.
When estimating the flight sorting feature, we referenced a previously completed 3-point story for filtering by airlines and a 5-point story for price range filters. This breakdown helps validate that the story point estimate is reasonable based on actual testing work required.
Our comparative approach grounded our estimate in actual delivery history rather than subjective opinions.
The goal isn't perfect estimates, it's making sure your team sees the full scope of work before committing to deliver it.
Estimation accuracy improves when teams understand and value different perspectives, especially the QA viewpoint that often identifies hidden complexities and edge cases.
By breaking down stories into specific testing activities, assessing complexity factors, and using structured estimation techniques like Planning Poker, you can arrive at more realistic estimates that account for both development and testing efforts.
In your next sprint planning, try asking: "What's the riskiest or least understood part of this story from a QA perspective?"
This single question can surface hidden work early and drastically improve estimation accuracy.