Agile with Analytics Projects: How to Ensure Success

Maximizing Data Insights: Implementing Agile for Successful Analytics Projects

Many companies adopt the Agile methodology to improve the efficiency of their software development process. Notably, some businesses are also beginning to use Agile on other technology projects, including those focused on data analytics. It requires an effort that relies on collaboration and teamwork, ensuring all project stakeholders contribute to its ultimate success.

Let’s examine how to best take advantage of the Agile approach for analytics projects. This effort helps your company enjoy the highest ROI on projects aimed at gleaning actionable information from data. Use these insights to ensure you deliver the valuable analytics necessary to power effective data-driven decision making.

A Quick Overview of the Agile Methodology

Agile provides a more flexible software development approach compared to traditional methodologies like the Waterfall. As a result, software gets delivered faster, while being able to react to changes in a more cost-effective manner. Responding to any issues subsequently becomes easier when a project is broken-down into smaller sections, known as sprints. Project communication flows seamlessly, with transparent interaction being one of the most important aspects of any Agile initiative.

Breaking Down the Structure of the Sprint

Understanding the structure of the sprint provides a useful overview of the Agile approach. Here is an overview of its components:

• Planning and Retrospective: This initial part of each sprint serves to plan the upcoming sprint as well as provide a retrospective of the previous one’s results. For an analytics project, providing insights on the quality of the delivered data analysis and subsequent reporting definitely helps.
• Daily Scrum: A daily meeting known as a scrum serves as a conduit for reporting progress on the sprint. The scrum master (an Agile project manager) leads the meeting with attendees including the technical team and available business stakeholders.
• Review: This meeting is held after the end of the sprint. It typically includes a demo of the latest version of the project’s ultimate deliverable. For an analytics project, this might include new reports or data from a new algorithm. Feedback from this step informs the planning and retrospective for the next sprint.

An Agile project includes any number of sprints depending on the scope of the overall initiative. The scrum master typically works with business stakeholders and the tech lead to determine the right amount. Of course, expect this scope to likely change on an Agile project!

If your business needs IT professionals experienced with Agile or related methodologies, connect with Technology Partners. As one of the top technical staffing agencies in St. Louis, we provide candidates with the right expertise. Schedule a meeting with us to discuss your current hiring plans.