Raw spreadsheet data from MyCNBox can be overwhelming. This guide will show you how to transform it into clear, actionable charts to analyze cost efficiency, QC approval rates, and delivery performance.
Step 1: Prepare Your MyCNBox Spreadsheet
Ensure your data is clean and consistent before creating any visuals.
- Verify Data Consistency:Cost (USD),
QC_StatusDelivery_Days- Create a Pivot Table (Optional but Recommended):average cost by suppliertotal orders by month.
Step 2: Choose the Right Chart for Each Metric
1. Analyzing Cost Efficiency
Recommended Chart: Column Chart or Line Chart
Visualize trends and comparisons across suppliers, product categories, or time periods.
- How-to:Clustered Column Chartaverage order cost
- Insight:
Example: X-axis = Month, Y-axis = Average Cost. A rising line indicates cost inflation.
2. Tracking QC Approval Rates
Recommended Chart: Pie Chart or Donut Chart
Get an instant snapshot of your quality control performance.
- How-to:Pie Chart
- Insight:
Example: Chart Segments = "Approved (85%)", "Rejected (15%)". Aim for a larger "Approved" segment.
3. Monitoring Average Delivery Times
Recommended Chart: Bar Chart or Line Chart
Analyze speed and reliability of your supply chain.
- How-to:Horizontal Bar Chartaverage delivery days
- Insight:
Example: X-axis = Average Delivery Days, Y-axis = Carrier Name. Shorter bars represent faster carriers.
Step 3: Implementation Tools & Tips
You can create these visualizations directly in your spreadsheet software or use business intelligence tools.
| Tool | Best For | Action |
|---|---|---|
| Excel / Google Sheets | Quick, simple charts from your existing spreadsheet. | Highlight your data range, navigate to Insert Chart, and select your chart type. |
| Power BI / Tableau | Interactive dashboards combining all three metrics. | Import your MyCNBox spreadsheet, create linked charts, and add filters (e.g., by date range). |
Pro Tip: Create a Combined Dashboard
Place your three key charts (Cost, QC Rate, Delivery Time) on a single dashboard page. This allows for correlation analysis—for instance, does a lower-cost supplier also lead to longer delivery times?