Software estimation can be a real challenge. Have you ever tried to predict how long a task would take, only for it to end up taking twice as long? This happens all the time in software development. But the good news is that there are ways to improve this and make software estimates more reliable.
The goal here isn’t to achieve absolute precision (because that’s impossible) but rather to find a balance that allows for better planning, fewer unpleasant surprises, and better alignment of expectations with the team and stakeholders.
Best Practices for Software Estimation
1. Everything Starts with a Clear Scope
If you’ve ever started a project without fully understanding what needed to be done, you know how it can lead to poor estimates. Clearly defining requirements, functionalities, and objectives prevents misunderstandings and gives the team a solid foundation for making more accurate estimates.
💡 Tip: Whenever possible, document the scope objectively and share it with everyone involved. Clarity prevents incorrect assumptions.
2. Estimates Should Be Iterative
Estimates are not unbreakable contracts. As the project evolves, new information arises, and the initial numbers can (and should) be adjusted. This flexibility allows the team to handle unexpected changes without compromising delivery quality.
3. Techniques to Improve Your Software Estimation
If you rely solely on intuition, the chances of error are high. Some software estimation techniques can help bring more structure to the process:
- T-Shirt Sizing
Simple and fast, this technique categorizes tasks into T-shirt sizes: Small (S), Medium (M), Large (L), and Extra Large (XL). It works well when you need a high-level view without spending too much time on details. - Planning Poker
Planning Poker is a collaborative technique that involves all team members. Each person receives a set of cards with numerical values (usually a Fibonacci sequence). The team discusses a task, and then each member selects a card representing their effort estimate. The cards are revealed simultaneously, and discrepancies are discussed until a consensus is reached. This method helps avoid individual biases and fosters agreement. - Three-Point Estimation
This method uses three values to define an estimate:- Optimistic (best-case scenario)
- Pessimistic (worst-case scenario)
- Most likely (realistic scenario)
The final estimate is calculated as a weighted average, giving more weight to the most likely scenario. For example, if a task is estimated at 2 days in the optimistic case, 5 days in the most likely case, and 10 days in the pessimistic case, the final estimate would be just over 5 days.
Which Technique to Choose?
✔ Need a quick, high-level estimate? → T-Shirt Sizing
✔ Want to involve the team and ensure alignment? → Planning Poker
✔ Need to consider uncertainties and risks? → Three-Point Estimation
4. Don’t Forget About External Factors
External factors such as holidays, resource availability, and external dependencies can impact project timelines. Microsoft, for instance, adjusts project estimates to account for vacation periods and peak workloads, ensuring a more realistic and achievable schedule.
Considering external factors in planning creates a more realistic timeline. This helps avoid unpleasant surprises and ensures the team is prepared to handle potential obstacles. A Forrester study found that 60% of projects that considered external factors from the start were completed on time and within budget.
5. Testing and Debugging Must Be Included
Many teams underestimate the time needed for testing and bug fixing, focusing only on feature development. However, poorly tested software can lead to rework, user dissatisfaction, and even damage the product’s credibility.
When estimating testing time, it’s essential to consider different validation layers:
✔ Unit tests
✔ Integration tests
✔ Regression tests
✔ Acceptance tests
Each has its role and impact on the development cycle. Ignoring any of them can lead to unexpected project delays.
Additionally, debugging doesn’t always follow a predictable flow. A bug may seem simple at first but, upon investigation, may reveal deeper issues that require extra time to fix. Setting aside a buffer for this phase ensures product quality isn’t compromised just to meet a tight deadline.
Read Also: Types of software testing and how AI is helping
6. Historical Data Is Your Friend
If your team has worked on similar tasks before, why not use that history to support your estimates? Comparing actual time spent on past projects with new forecasts helps fine-tune estimates and reduce uncertainties.
Beyond just looking at execution times, it’s helpful to analyze broader patterns:
- What were the biggest challenges?
- Where did estimates go off track?
- How did the team handle unexpected changes?
Another key point is adapting lessons learned to new contexts. Different projects have unique variables, such as technology stacks, team members, and requirement complexities. Historical data should be used as a reference but always adjusted for the current scenario.
7. Involve the Team in Software Estimation
The development team should be involved in the estimation process since they have the technical knowledge to assess task complexity more accurately. A Harvard Business Review study found that including the team in estimates can increase accuracy by up to 20%.
When the team participates in estimation, they feel more motivated and committed to the project. This sense of ownership boosts productivity and work quality, as everyone is engaged in achieving the established goals.
8. Include a Buffer for the Unexpected
Unexpected things always happen, and underestimating uncertainty can derail an entire project. To avoid this, it’s essential to add a safety buffer to estimates. Generally, increasing the estimated time by 20% can help cover unexpected blockers, last-minute revisions, and requirement changes.
However, this buffer shouldn’t be arbitrary. Base it on the project’s nature and the team’s experience. Projects with many unknown variables may require a larger buffer.
9. Measure and Adjust Constantly
Initial estimates should be compared against actual time spent. This helps the team learn from past mistakes and improve future forecasts. Implementing continuous feedback loops makes the estimation process more efficient over time.
Conclusion
Estimates will never be perfect, but that doesn’t mean they can’t be improved. By applying these best practices, your team can reduce uncertainties, plan better, and deliver software with greater predictability.
