Contributed by: Akash Sood
I am Akash Sood working as a Techno-Functional Consultant in the Oil & Gas Domain. While working in my current project which is delivered in Agile methodology, the Scrum Master mentioned that the client has asked to deliver the aging Product Backlogs.
I found an opportunity learning this. There was a case study which was mentioned while learning PCA during our mentor sessions in PGPDSBA program,where IPL teams ranked the players and used PCA to get the most important metrics to judge a player’s performance. I found this analogous to my requirement, the only difference being I already had the KPIs on which to work to calculate rank of a Product Backlog.
The metrics used: Created Date, Priority, and Story Points. I chose to use Fibonacci series to give a higher score to older, higher priority, and higher story points backlog items. Analytics Views from the Azure DevOps was used to fetch data into a Power BI report using their Online Services, which ensures we can get the updated data with a refresh button.
Data transformation was performed to calculate the relevant metrics and put relevant data checks. Finally, a DAX measure was created to calculate the Rank of a Product Backlog. An interesting view I got was that there were a lot of ties after ranking, so the Age of an item in fractions was also included in the Total score to deal with the tie breakers.
IMPACT: The solution is now being used within my project for long term planning in feature deliveries. This is also being shown to the Product Owners to give an overall view of the expected Product Backlogs that will be delivered.
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