Problem

Philips managed over 10 years of legacy backlog data, which resulted in significant systemic inefficiencies for its primary users: Product Managers and Developers. The backlog data was siloed across JIRA, Rally, and Azure DevOps, these users faced a "needle in a haystack" scenario when trying to find related tickets, costing them time and reducing development velocity.

Research Results

By conducting interviews with the engineering and product teams and analyzing real world backlog data, I identified several critical friction points:

• Prioritization Failure: Misaligned prioritization meant Product Managers often pushed critical defects to subsequent releases, causing technical debt to accumulate

• Systemic Fragmentation: Siloed data required Developers to manually jump between platforms, leading to substantial lost efficiency and redundant rework.

• Search Inefficiency: Traditional keyword-based searching was found to be ineffective for users, taking an average of two minutes per query.

Impact

The resulting solution, utilized advanced vector-based search to transform how these teams navigate the backlog:

• Quantifiable Time Savings: The tool is projected to save Product Managers and Developers significantly, reducing search time from minutes to seconds.

• Projected ROI: This transformation is estimated to save light users 55 hours and power users 275 hours annually, delivering a total scaled value of $1.1M–$5.5M in annual savings for a team of 250 users.

• Unified Access: Provided a single dashboard to access conceptually related items across all siloed platforms, enabling faster, data-driven decision-making for the whole team.