Improve execution with better planning

Intro

Modern engineering practices generally utilize some agile methodologies to deliver software. During my time as a Product Manager at Microsoft and UiPath, I was part of a platform team where there tended to be a lot of dependencies. To manage these dependencies, our team aligned towards the utilization of a longer 3-6 month plan with 1-2 week sprint planning cycles. This ensured that we were incrementally delivering value towards our goals and were agile enough to adjust as needed.

However, during this process, I noticed that poor execution was often caused by poor planning. For example:

• If teams overestimated the amount of work they can complete in a sprint, it would delay planned tasks for the following sprint, ultimately having a trickle-down effect.

• If PMs, like myself, introduced new requirements, it would lead to scope creep, which in turn would affect our ability to deliver features on the desired timeline.

• If there were tasks with large dependency chains within the same sprint or on other teams and they went unfinished, it could cause delays in features across the organization.

It is important to note that planning and execution are two crucial components of any project, and they are closely interrelated. A well-thought-out plan can help ensure that the project is completed on time, within budget, and to the desired level of quality. However, a poorly-planned project can lead to delays, overruns, and a lack of direction for the team.

So how do we get better at planning?

Just like building a better product, you start by measuring it! We already measure our product for daily active users, support tickets, errors, etc. By making data-driven decisions, it will be easier to understand how planning is impacting execution. Historically, it has been difficult to measure how planning has been. You would have to compile data from different tools you use, clean up the schema to make it usable, and set up and maintain an entire modern data stack just for this effort. But there are tools like Intuned that handles all the tedious work for you and allows you to start exploring the rich data you have access to.

With Intuned, you can start to get deep insights on your planning cycles sprint over sprint. Here is an example of the level of insights you can get with Intuned:

• Sprint summary chart: Shows you the breakdown of planned work and unplanned work that was completed in the most recent sprints

• Velocity chart: Shows you the story point delivery sprint over sprint

• Sprint summary metrics table: Shows you metrics around the planned and unplanned work that was completed

• Merge requests by sprint table: Shows you metrics on the merge requests tied to the work items in the sprint

• DORA metrics by sprint table: Shows you the most common software delivery metrics to help you understand if there are bottlenecks in some part of the SDLC

This is just the start, as we work together to develop your dashboards and metrics you can use Intuned to get alerted if there is anything out of the ordinary.

Summary

In conclusion, by using data-driven agile planning practices, organizations can reduce risk and create more successful products in a shorter period of time. With Intuned, it becomes much easier to identify and address bottlenecks in execution, which can help teams improve their practices over time.

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Zawad

Intuned, Co-founder