Chapter 1: The Challenges of Task Estimation

Task estimation presents a significant challenge for developers. Accurately predicting the time needed to complete tasks can be a daunting endeavor. As a developer myself, I have often found myself either overestimating or underestimating the time required for various assignments.

A seemingly straightforward task, which I initially believed would take four hours, can quickly evolve into a more complex endeavor with unexpected features and dependencies. Consequently, what was meant to be a four-hour job ended up taking eight hours. In the process, I improved the structure of related code, identified areas for optimization, and completed the task—but I ultimately spent double the anticipated time.

Does this mean I'm a poor programmer? I don't think so. However, repeated experiences like this can lead to my manager observing a pattern of missed deadlines.

While clear communication and early identification of potential obstacles can help mitigate this issue, the reality remains: developers often miscalculate task estimates.

To simplify the estimation of intricate projects, breaking them down into smaller components can be beneficial. However, even with this approach, errors in estimation are still possible.

Why is estimating tasks crucial in the first place? In a collaborative environment, it's essential to gauge how much time will be required to accomplish specific tasks. Development processes are frequently organized into iterations. Within the Scrum framework, these iterations—known as sprints—typically last around two weeks. Before embarking on a new sprint, it’s vital to ascertain how many tasks will be tackled during that time.

How can we determine the number of tasks manageable within a two-week timeframe? The answer lies in estimating tasks in hours and calculating how many can fit into that period. It’s a straightforward process.

What are the benefits of estimating tasks in hours? For clients, this approach is transparent; they pay for development hours and receive task estimates expressed in hours. It also facilitates easy calculations for task allocation in upcoming iterations.

However, there are notable drawbacks. Developers can easily misjudge their estimates. Each time a developer exceeds their projected time, it can feel like a failure, even if the work produced is of high quality. This method of assessment tends to yield limited statistics, as we often only track a developer's 40-hour workweek—a statistic that lacks depth.

As is the case with any method, there are alternatives worth exploring.

Chapter 2: What Are Story Points?

The concept of "story points" often comes up in discussions about task estimation. You might hear them referred to by various names—parrots, shirt sizes, etc. But fundamentally, story points are units used to measure the complexity of a task rather than the time needed to complete it.

So, how do we determine the value of a task in story points? The simplest task is typically assigned a value of one story point. For instance, "changing the color of a button" is a basic task that can be designated as one story point.

Many teams utilize the Fibonacci sequence to create a common scale of complexity, allowing tasks to be rated as 1, 2, 3, 5, 8, or 13 story points. If a task's complexity exceeds the highest value, it should be broken down into smaller tasks.

Teams often employ techniques like scrum poker for estimating tasks in story points. In this approach, the manager announces a task, and each team member votes on its difficulty level. If there's a significant disparity in scores, the team engages in discussion before voting again.

What advantages do story points offer? They enable the collection of detailed statistics regarding a team's performance. Over multiple sprints, managers can calculate the average number of story points completed per iteration. This number might fluctuate, but it tends to stabilize over time.

Developers begin to focus on complexity rather than time, shifting their mindset from completing a task within a set number of hours to understanding its complexity and executing it efficiently. This encourages team discussions about task complexity, providing valuable insights into the codebase.

However, there are drawbacks to using story points. For one, communicating story points to clients can be problematic, especially in outsourcing scenarios. Clients typically pay for developer hours, while story points are less tangible.

To accurately gauge story points, teams need to undergo several iterations. The initial iterations may yield imprecise estimates, requiring adjustments from management. Additionally, if the team feels pressured to expedite task completion, they may inflate estimates into higher story points. It's crucial to maintain a balance to ensure that the value of story points remains stable.

A common mistake when using story points is equating them to hours.

NEVER equate the number of hours with a single story point. Why? Because doing so is fundamentally flawed. A junior developer might complete ten story points in two weeks, while a senior developer could finish 24. The time it takes to complete a story point can vary widely among developers.

It’s akin to tracking how many cookies I consume on a train journey: I might eat one cookie for every mile traveled, but that doesn't really convey anything meaningful.

While discussions about hours and story points can be productive for analysis and forecasting between a manager and a supervisor, team members should never correlate story points with hours. Such comparisons undermine the essence of the method.

In Conclusion

Throughout my experience on various teams, I've seen both the correct and incorrect application of story points. In some instances, they were impractical due to business constraints. However, I thrived on teams where story points were effectively implemented. This method of task estimation is both engaging and beneficial.

If you decide to experiment with story points, ensure that your team fully understands the approach. By avoiding common pitfalls, you can have a rewarding experience.

What estimation methods do you employ for tasks? Have you tried using story points? I would love to hear about your experiences in the comments.

The first video highlights the argument against using story points in Scrum teams, emphasizing the need for a more effective estimation approach.

The second video explores the historical challenges of using story points in Agile, shedding light on common pitfalls and misconceptions.