01 · Problem
Manual reporting across dozens of retail sources
Category Leadership teams relied on fragmented sales data from IRI, NPD, internal reports, and retailer POS systems. Pulling and harmonizing performance across 30+ sources was manual, slow, and inconsistent, costing analysts significant time each month before insights could reach brand managers and sales directors.
Stakeholders needed a single, reliable view of KPIs without waiting on repetitive Excel work or one-off exports. The existing workflow made it hard to standardize metrics, compare periods quickly, or deliver real-time visibility to decision makers.
02 · Solution
An automated dashboard with Python, Excel, and Circana Unify+
I built an automated analytics dashboard that integrated Python scripting, Excel workflows, and Circana Unify+ (IRI and NPD) to streamline sales tracking across the full data ecosystem. The system reduced manual data entry, standardized how sources were combined, and produced dynamic views tailored to category leadership needs.
The dashboard harmonized disparate datasets into one reporting layer, with user-friendly visualizations designed for brand managers, category leaders, and sales directors. Python and Excel automation handled recurring pulls and transformations so the team could focus on interpretation instead of assembly.
03 · Impact
Faster reporting and stronger retail analytics fluency
The project cut reporting time by 20 hours per month while giving stakeholders a consistent, real-time window into sales performance. Teams gained a repeatable workflow for CPG analytics, from POS trends to category leadership metrics.
Beyond efficiency, the work deepened my skills in data integration, retail analytics, visualization, and cross-functional collaboration, aligning technical automation with how Ferrara's sales organization actually makes decisions.
