Project Overview

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Business Context (Why is this project?)

The warehouse team struggled with inefficient pick routes and missed KPIs due to a poor layout and lack of visibility into real-time operations. High-frequency items were scattered, causing staff to zigzag through long routes, wasting time and labour.

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Objective (What is it for?)

This project aimed to build a visual, data-driven dashboard that would:

• Provide spatial visibility into warehouse activity and layout.
• Track order-picking frequency by location.
• Support strategic stock placement (e.g., moving fast-moving items to floor-level shelves).
• Optimize pick routes to reduce travel time and increase labour efficiency. </aside>

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Key Insights Delivered (What does data tell?)

• Identified high-activity zones within the warehouse based on picking frequency - darker red areas on the heatmap indicate busier locations.

• Highlighted inefficient pick paths that caused excessive walking time for staff.
• Showed temporal peaks in activity, enabling better labour planning.

• Visualized opportunities to:

  • Relocate frequently picked items to floor-level, high-access zones.

  

  • Store similar items near each other to minimize walking time.
  • Reorganize picking sequences and optimize routes to meet KPIs.

  

  • Managed inventory and optimized storage by grouping items for the same customer together to reduce operational time.

  

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Business Impact (So What?)

• Enabled warehouse managers to redesign stock placement based on actual usage patterns—not assumptions.
• Reduced picker travel distance and time, directly supporting improved labour productivity and order fulfilment KPIs.
• Informed staffing decisions by visualizing activity trends over time. </aside>

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Scalability & Future Use (What Else?)

This approach is scalable across warehouse networks by replicating the mapping methodology and plugging in different activity datasets, such as:

• Warehouse capacity planning
• Inventory control efforts
• Cycle count accuracy analysis
• Physical stock monitoring and reconciliation </aside>

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Tools & Approach (How was it done?)

• Excel (Layout Mapping): Drafted a digital map of the warehouse using X and Y coordinates to represent bin/rack locations.

• Excel (Operational Data): Compiled daily operational reports, including order number, item, quantity, time stamps, and storage locations.

• Tableau:
  • Mapped the physical layout of the warehouse using the coordinates.
  • Visualized pick frequency heatmaps across different storage zones.
  • Created time-series dashboards to analyse activity by day, week, and month.

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🔗 Deliverables

Excel files used for layout mapping and data aggregation.

Notes on layout design, mapping methodology, and business logic.

WH Layout Sample.xlsx

Warehouse Operation.twbx