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How to Accurately Estimate Story Points

πŸ“ Context: In software development, story points play a pivotal role in managing workload, planning, and predicting product delivery. These abstract units help teams estimate the effort and complexity involved in completing a user story. However, determining their accuracy can be challenging.

πŸ€” User Problem: Teams need a way to accurately estimate the effort and complexity of user stories using story points. However, understanding the accuracy of these estimates and identifying issues in task estimation can be challenging. The Time in Status add-on can provide valuable insights into how time is spent during sprints, helping agile teams improve their estimation processes.

When estimating work using story points, it can be helpful to consider the following factors:

   πŸ‹οΈ Effort: This includes all the work required to complete the task, including Quality Assurance (QA) as defined in your Definition of Done.

   πŸ•ΈοΈ Complexity: Consider the number of elements involved, their interdependence, and the need for research.

   βš οΈ Risk: Estimate how much of the task is unknown or risky at the moment of estimating.

   πŸ’‘ Experience: Consider the team's previous experience in completing similar tasks.

   πŸ€ Collaboration: Estimate the amount of cooperation required for the task within the team or with other parties.

If Story Points are not related to time, how can Time in Status be useful for Sprints?

Even though story points do not directly correspond to specific amounts of time (as they represent complexity, effort, and risk rather than hours or days), understanding how time is spent during sprints can provide crucial insights for agile teams. The Time in Status add-on becomes particularly useful in this context by offering detailed analytics on the status of each issue within a sprint.

Let's analyze a real case study of a scrum master and how he found a problem in task estimation.

We generate a Pivot table that will calculate how much time each Assignee takes to complete a task for each story point.

image-20240821-080137.png

After setting up the calculation, we get the following report:

image-20240821-080240.png

Let's look at the table, namely at the problem with the tasks that were estimated as 3 story points. Completing 3 different tasks of 3 story points of the point took 1 hour, 22 hours and 46 hours.

image-20240821-080300.png

We can conclude that such an assessment does not make practical sense and is a marker that the developers do not have an understanding of what to do in this task.

Usually, in such tasks, either 

  • the size of the task is too large, or 

  • there are unclear risks during the planning of the task.

That is, the score in the third quarter of the point in this team is given when they do not understand what to do.

πŸ“ˆ Outcomes:

  • Improve Estimation Accuracy: Identify discrepancies in task estimation and improve the accuracy of story points.

  • Understand Time Spent: Gain insights into how time is spent on tasks during sprints.

  • Identify Bottlenecks: Pinpoint where tasks are getting stuck in the workflow.

  • Optimize Workflows: Make data-driven decisions to optimize workflows and improve team productivity.

If you need help or want to ask questions, please contact SaaSJet Support or email us at support@saasjet.atlassian.net

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