Scrum Master Best Practices to Accelerate Data Projects

Often, data-reliant organizations focus their data strategy more on technical aspects, such as data warehouse architecture and technology selection, than on non-technical factors such as processes, procedures, and documentation.

Creating documentation associated with a data warehouse build including Source to Target Mappings (STM), business requirements (BRD), and the business or technical glossaries are often overlooked. However, in some respects, the non-technical aspects of a data initiative are just as vital to the organization’s data transformation as the technical side.

One of those non-technical aspects is known as Scrum. Scrum is a Delivery Framework, under the Agile umbrella, that can accelerate initiatives, break down data silos, and bring organizations together as a team to progress any project. Individuals certified in Scrum are known as Scrum Masters.

The main principles behind this practice are:

  • Transparency – Often projects fail to meet deadlines due to foggy communication or unclear direction. Therefore, it’s important to be transparent with stakeholders.
  • Inspection – A continuous inspection of the product helps identify bugs sooner and avoids the accumulation of technical debt.
  • Adoption – Project demands can be fluid so it's necessary to remain agile and adaptive to any project changes.

And while these are considered the foundation of a Scrum Master-led project, our experience has helped us identify a few additional Scrum best practices that will help advance your projects and produce optimal outcomes.

Teamwork and Meetings

Quick question: How many projects achieve success without a collaborative effort?

The answer is zero (or very little).

Scrum Masters are the linchpin of any agile team. They have insight into all aspects of the project and the ability to identify and include all pertinent stakeholders in the process.

This is accomplished by promoting peer-to-peer collaboration as well as creating a detailed backlog of all changes required for the project (we’ll get into more detail about this in a bit). Empowering a project team with information and knowledge allows for thoughtful reflection of retrospectives during Lessons Learned meetings.

Planning and Estimates

With any Scrum Master-led project, planning and estimates are vital to helping keep project momentum on a forward trajectory.

It’s important that clear goals and timetables are set. A big part of keeping those goals and time estimates as realistic as possible goes back to keeping stakeholders involved.

With an informed and transparent project, Scrum Masters collaborate with both IT and business stakeholders to identify and break down barriers before they become a problem. This is all made possible by sprint ceremonies and planning sessions.

Managing Backlogs

Earlier we mentioned that promoting a collaborative project environment would enable the creation of backlogs as a reference to all changes made. Well, creating the backlog is only half the battle.

A project team must also learn to manage its backlogs to realize its full value.

A Scrum Master can accomplish this in several ways. By utilizing task prioritization techniques, the project team can set up tasks according to relevance. Next, mapping functional and technical dependencies will help highlight technical debt discrepancies. And finally, embracing iterative development as a way to design, develop, and test in a repeated cycle.

Scrum Master Best Practices Summary

In conclusion, for optimal project results a Scrum Master must apply the foundational elements of Scrum mentioned above: Transparency, Inspection, and Adoption.

Additionally, the best practices we’ve outlined will accelerate project progression and help identify roadblocks before they become a problem.

It’s important to note that these best practices are based on our professional experiences and a big part of the Agile Scrum process is to remain flexible. To that end, deciding which of these Scrum best practices to apply to your next Agile project are dependent on its scope, scale, and team dynamics.

At Data Ideology, we believe a combination of Agile and Scrum is the best fit for accelerated data and analytics projects when compared to traditional Project Management, primarily because an Agile Scrum approach allows teams to test and deploy parts of the project as they become available instead of waiting until the entire project is complete.

Additional advantages of an Agile Scrum approach include early identification and remediation of bugs and errors, accelerated timelines, and with both the business and IT groups working collaboratively throughout the project lifecycle, a sense of ownership is created for all parties involved.

With this shared ownership, user testing and adoption happen organically allowing the business to keep pace or, hopefully, surpass competitors and market threats. By utilizing our certified Scrum Masters, we help organizations progress toward their future state in a more accelerated manner.

Contact us here to schedule a quick discovery call.

Written by Tyler Onusko

Senior Consultant at Data Ideology

Written by Shelley Nolte

Consultant at Data Ideology


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