Spark is one of AFS’ enterprise analytics platforms designed to deliver rapid, accurate, and actionable insights. Built to eliminate traditional bottlenecks in reporting and data discovery, Spark centralizes key datasets, accelerates analysis, and strengthens collaboration through shared dashboards and AI driven interpretations. As an evolving solution, Spark continues to expand its capabilities, contributing to a more integrated and driven interpretations. As an evolving solution, Spark continues to expand its capabilities, contributing to a more integrated and ‑driven interpretations. As an evolving solution, Spark continues to expand its capabilities, contributing to a more integrated and data‑empowered culture within AFS.
This initiative has been guided by Mindy Miller, vice president of analytics, whose leadership has shaped both the system’s current strengths and its long-term vision. Mindy emphasized that Spark’s adoption reflected a growing desire among team members and retailers for the ability to access answers independently rather than relying on lengthy request pipelines.
Spark’s most immediate value lies in its speed. The system renders data with near instant responsiveness, even when users adjust timeframes‑instant responsiveness, even when users adjust timeframes or refine filters. Mindy noted that Spark “updated in seconds rather than waiting minutes or sometimes having the tool time out,” highlighting the platform’s significant improvement over alternative analytical workflows.
The incorporation of large language models (LLMS)—particularly Claude—help enable this speed. As Mindy explained, these models “return answers fast and eliminate the data mining side of things,” enabling staff members with access to focus on interpretation and strategy rather than manual data extraction. They also allow relative newcomers to data analytics to query the system without extensive training.
Spark’s roadmap positions it for continued growth. Upcoming enhancements include the integration of all promotional data types executed by AFS, offering broader visibility into execution and performance. Supply chain data, also in development, will provide new layers of insight and support more comprehensive cross-departmental‑departmental analysis.
These advancements underscore why Spark is an expanding ecosystem designed to streamline operations and support evidence-based‑based decisions at every level of the organization.
Spark also strengthens communication and collaboration across AFS. Its customizable dashboards allow users to build views tailored to their needs, save them privately, and share them directly with colleagues who also hold licenses. Mindy noted that this design made collaboration significantly easier because “rather than describing information or sharing key metrics, the entire view transfers”.
Mindy also acknowledged that adopting a new system requires an organizational shift. “Change is hard. Learning something new is hard… But once you learn it, you’re able to move much faster and the effort pays off.”