Data reveals patterns. This guide demonstrates a systematic approach to tracking average Quality Control (QC) performance by seller category, empowering you to identify consistent high performers within your ACBuy spreadsheet.
1. Data Preparation: Structuring Your Analysis
Begin by ensuring your ACBuy spreadsheet data is clean and consistently formatted. Essential columns should include:
- Seller ID/Name
- Seller Category
- QC Result
- Order Date
- QC Result
Create a pivot table or set up a dedicated analysis area. This is your foundation for spotting trends.
2. Calculating Average QC Performance by Category
The core of the analysis is aggregating performance. For each Seller Category, calculate:
- QC Pass Rate:
- Average QC Score:
- Trend Over Time:
- Average QC Score:
Use spreadsheet functions like AVERAGEIFS, COUNTIFS, and pivot tables to automate these calculations.
3. Identifying Patterns and Consistent High Performers
With averages calculated, look for these critical patterns:
- Category Outliers:
- Stability:
- Individual Standouts:which specific sellers
- Stability:
Visualize this data using line charts (for trends over time) and bar charts (for category comparisons).
4. Actionable Insights for Sourcing Decisions
Transform analysis into strategy:
- Tier Your Sellers:
- Investigate Deviations:
- Refine Categories:
- Investigate Deviations:
Turning Data into a Competitive Advantage
Regular analysis of seller QC trends in your ACBuy spreadsheet moves sourcing from reactive to proactive. By systematically tracking average performance by seller category, you build a data-driven foundation
Start with a monthly review cycle. Consistent tracking is key to revealing the most valuable long-term trends and partnerships.