Overview
At ADP, I partnered closely with our data science team to automate a time-consuming client reporting process. Previously, they manually exported large datasets into Excel, performed complex calculations, and delivered static reports to clients. This workflow took 6–10 days per report and severely limited client access to fresh data.
Approach
- Requirements Gathering: Consulted with the data science team to fully understand their 20+ page methodology, including formulas, weighting, and edge-case handling.
- Data Architecture: Built a custom calculation engine that split heavy computations between MySQL (for set-based operations) and PHP (for more specialized logic), minimizing memory usage and speeding up processing.
- Admin Interface: Created a secure web portal where clients could log in, customize reports, apply filters, and pick date ranges—eliminating the need for one-off Excel exports.
- Performance Optimization: Iteratively refined queries, caching strategies, and code to reduce overall report generation time from 2 minutes down to ~10 seconds.
Results
- Massive Time Savings: Slashed report generation from 6–10 days to just seconds, enabling data scientists to focus on deeper research rather than repetitive tasks.
- Improved Client Satisfaction: Clients could now access real-time data on demand, boosting trust in ADP’s analytics capabilities and overall user experience.
- Enhanced Scalability: By automating complex calculations and distributing them efficiently, the system seamlessly handled growing data volumes without performance bottlenecks.
- Greater Team Collaboration: Freed up the data science team to innovate further and empowered stakeholders with instant insights.