Why Agile Teams Use Story Points Instead of Hours for Estimation

Critical problems with time estimates

Problem 1: Uncertainty not actively tracked

When team members discuss a story and how they will get it done, they base their estimate on what they know. Some overlook what they can't see and give a best-case estimate. Some will assess uncertainty and include additional time to account for it. The big challenge is deciding how much time to account for the uncertainty. Because you only know how long it takes when the work is complete.

So while uncertainty isn't being assessed, measured, and used to forecast progress, your team will struggle with estimates.

Problem 2: It depends on who does the work, how long it will take

You will find experienced team members and less experienced members in any team. It will take less time for a team member to implement changes on a well-known codebase. Similarly, it will take more time to implement changes that depend on an unfamiliar API. Each team member has a different level of knowledge and experience. So when team members discuss time estimates, they struggle to agree on an estimate when each member is thinking

'how long will it take 'me' to implement this story?'

We need a way to move away from this line of thinking because team members' knowledge and experience are different.

Problem 3: No feedback loop keeping track of team’s capacity and historical performance

This part of the post was inspired by a thoughtful comment from a Reddit user, highlighting the importance of establishing a feedback loop between capacity forecasting and a team’s historical performance.

One of the issues with estimating stories using hours is the lack of an effective feedback loop between what the team is planning and actual performance. When teams rely on time-based estimates, they often overlook the importance of tracking their progress and adjusting future estimates based on historical data.

Without a feedback loop, the team’s capacity forecast is based purely on isolated guesses rather than informed forecasts based on actual performance. This makes it difficult to assess whether the team is improving, stagnating, or struggling.

There is a solution to these problems. The answer is to use story points, relative estimates, and the team's Velocity. Let's discuss how it works.

How do story points, relative estimates, and team's velocity solve these problems?

Let’s explore how Story Points and Relative Estimates help teams manage uncertainty and improve estimation accuracy.

Solving 1: Uncertainty not actively tracked

Using Story Points and Velocity is an effective way to address uncertainty in estimation. It relies on three foundations: assessment, measurement, and forecasting progress using real data.

1. Assessing Uncertainty When Assigning Story Points

• We assess Uncertainty When Assigning Story Points
• For example, if two stories initially appear similar in size but one involves an unfamiliar API, it receives a higher story point estimate to reflect the additional risk

2. Measuring Uncertainty Through Velocity Tracking

• By tracking Velocity every sprint, teams collect data on their speed, i.e. completed backlog items, involing every uncertainity that came up
• Knowing your teams approximate Velocity and what uncertainity surfaced allows teams to identify improvements that eliminate or reduce uncertainity in future sprints
• Knowing your Velocity helps prevent overcommitment, which can significantly reduce your team's throughput

3. Forecasting Progress Using Past Velocity

• By tracking average velocity over past sprints, teams can predict how much work they are likely to complete in future sprints using real performance data

This is allows teams to answer key planning questions, such as, (More on this here)

• When can Feature A be delivered?
• Should we spend time and implement A1 rather than the cheaper version A2?
• What can we complete before the end of the next quarter?
• Can we finish Feature A before the next quarter ends?

Solving 2: It depends on who does the work, how long it will take

Relative estimates address this issue by shifting the focus from “How long will this story take me?” to “How does this story compare in effort to others?” Instead of assigning a fixed time estimate, teams categorize stories based on their relative effort:

• Does this story match the effort of a one-story point task?
• Is it more similar to a two-story point task?
• Or does it require the effort of a three-story point task?

…and so on.

Research shows that teams are more accurate when estimating effort relatively rather than in absolute time. Using the Fibonacci sequence (e.g., 1, 2, 3, 5, 8) as a scale instead of a continuous time-based scale helps because the increasing gaps between numbers make it easier to distinguish differences in effort between stories.

Solving 3: No feedback loop keeping track of your team’s capacity and historical performance

By using story points and tracking velocity, how many story points your team completes per sprint, Agile teams can establish a reliable feedback loop. This ongoing comparison between expected and actual performance helps teams gradually refine their estimation process, making their forecast more accurate over time. It also helps identify when teams are overcommitting or underestimating their capacity, allowing them to adjust their forecasts.

Furthermore, a team’s velocity is not a constant value; it can improve, stagnate, or even decline depending on various factors within the working environment. Elements such as status of technical dept, team morale,management pressure to meet unrealistic deadlines, and external disruptions all impact the team’s velocity.

By using a feedback loop an tracking your team’s velocity continuously, you gain valuable insights into whether the team’s efficiency is improving, remaining steady, or deteriorating. This data-driven approach allows you to identify trends, detect underlying issues early, and make adjustments to optimize performance. Additionally, it fosters a culture of continuous improvement by providing clear evidence of progress or areas that require attention.

Frequently Asked Questions about Story Point Estimates

What are Limitations of Velocity-Based Forecasting

While past Velocity is a strong predictor of future progress, your forecast will break if what happens in one sprint it totally different from what happened during the sprints you base your Velocity on. So while Black Swan events are not common, your forecast doesn't and shouldn't account for them.

How do you convert story points to hours or time on the calendar?

At the end of each sprint, teams track the total number of story points completed—this is known as the team’s velocity. Velocity tends to remain fairly consistent from sprint to sprint, as long as team capacity stays the same and the level of uncertainty in stories remains similar. Since each sprint has a fixed duration, teams can use velocity to convert story points to delivery time when needed.

Wrapping Up: Why Agile Teams Choose Story Points

In Agile development, estimating effort using story points rather than time-based units allows teams to account for complexity and uncertainty more effectively. This approach leads to more accurate planning and improved project outcomes. By focusing on relative effort instead of absolute time, teams can better manage their workload and deliver value more consistently.

Moreover, tracking velocity over time establishes a critical feedback loop between estimation, capacity forecasting, and actual performance. This feedback loop allows teams to continuously refine their estimation process, detect inefficiencies, and adapt to changing conditions. The result is not just better planning accuracy but also a framework for continuous improvement.

Adopting story points over hours isn’t just about estimating effort; it’s about creating a system that evolves and grows with your team. With the right tools and mindset, this approach becomes a powerful mechanism for delivering projects with greater consistency and predictability.

About Smart Guess

We help teams educate stakeholders by providing actionable answers to common misconceptions about estimates. So more teams can use estimates to their advantage, and fewer are held accountable for delivering on impossible deadlines.

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