Warehouse Activity Heatmap

The Warehouse Activity Heatmap visualises how intensively different parts of your warehouse are used over time. By colour-coding activity levels across time periods and storage zones, it helps you identify peak hours, bottleneck areas, and opportunities to improve your warehouse layout and staffing.

Accessing the heatmap

To open the heatmap, navigate to Warehouse > Reports > Activity Heatmap. The heatmap requires the can_view_warehouse_reports permission. If the menu item is not visible, ask your CoreAdmin to assign this permission to your role under Configuration > Users & Roles.

What the heatmap shows

The heatmap displays the frequency and volume of warehouse operations across two dimensions:

• Time-based heatmap — Shows activity intensity by hour of day (vertical axis) and day of week (horizontal axis). Each cell represents a specific time slot (e.g., Tuesday 10:00–11:00) and is coloured according to how many operations occurred during that period.
• Zone-based heatmap — Shows activity intensity by storage zone. Zones with more operations appear in hotter colours, making it immediately obvious which areas of the warehouse see the most traffic.

Colour intensity ranges from cool (light blue or grey, indicating low activity) to hot (deep red, indicating very high activity). The legend at the bottom of the heatmap shows the exact colour scale and the operation counts each colour represents.

Operations tracked

The heatmap aggregates data from all standard warehouse operations:

• Check-in — Equipment returned to the warehouse
• Check-out — Equipment dispatched from the warehouse
• Stock movements — Items moved between storage zones within the warehouse
• Picking — Items picked from zones for packing lists
• Put-away — Items placed into storage zones after receipt or return
• Stock adjustments — Corrections, damage records, and inventory count entries

Filtering the heatmap

Use the filter panel above the heatmap to refine the data displayed:

Date range

Select a start and end date to focus on a specific period. Useful for comparing activity patterns across different seasons, event periods, or before and after a layout change. Common presets include Last 7 days, Last 30 days, Last quarter, and Custom range.

Operation type

Filter by one or more operation types (check-in, check-out, movement, picking, put-away, adjustment). For example, filtering to Picking only reveals which zones are most frequently picked from and at what times, helping you position popular items closer to the packing area.

Storage zone

Filter to a specific zone or group of zones to drill into activity for a particular area of the warehouse. This is especially useful in large warehouses where overall heatmap data can be too broad to act on.

Use cases

Optimise staffing schedules

The time-based heatmap reveals your peak warehouse hours. If Monday and Tuesday mornings consistently show the highest activity, you can schedule more warehouse staff during those periods and reduce headcount during quieter times such as Friday afternoons.

Identify high-traffic zones

The zone-based heatmap shows which storage areas are accessed most frequently. High-traffic zones should be positioned close to the packing area and main aisle to minimise walking distance. If a zone deep in the warehouse consistently shows high activity, consider relocating its contents to a more accessible position.

Detect workflow bottlenecks

If a single zone or time slot shows disproportionately high activity compared to surrounding cells, it may indicate a bottleneck. For example, if all check-outs happen between 07:00 and 08:00, the loading dock may be overwhelmed during that window. Staggering dispatch times or adding a second loading point can relieve the pressure.

Plan warehouse layout improvements

Before reorganising your warehouse, use the heatmap to understand current usage patterns. Place frequently accessed items in the most accessible zones. After making changes, compare the new heatmap against historical data to verify that the layout change improved efficiency.

Evaluate seasonal patterns

Compare heatmap data across different months or quarters to identify seasonal trends. Rental businesses often see spikes during summer festival season or the Christmas period. Understanding these patterns helps you plan temporary staffing, overflow storage, and pre-staging of popular equipment.

Reading the heatmap effectively

• Look for clusters — Groups of hot cells indicate sustained busy periods. A single hot cell surrounded by cool cells is likely a one-off event rather than a pattern.
• Compare weekdays to weekends — Many rental warehouses are busiest on Thursday and Friday (pre-weekend dispatch) and Monday (post-weekend returns). Confirm whether your data matches this expectation.
• Use longer date ranges for reliable patterns — A 7-day heatmap may be skewed by a single large project. Use 30 days or a full quarter to identify genuine recurring patterns.
• Filter by operation type for targeted insights — An overall heatmap shows general activity. Filtering to a single operation type (e.g., picking) provides actionable data for a specific workflow step.

Tips

• Review the heatmap monthly — Regular review ensures you catch changes in warehouse activity patterns early, before they become problems.
• Combine with inventory count data — If a zone shows low heatmap activity but high stock levels, the items stored there may be slow-moving and could be relocated to free up prime space.
• Share heatmap insights with management — Use heatmap data to support requests for additional staff, layout changes, or new equipment. Visual data is more compelling than anecdotal evidence.
• Use zone filtering for large warehouses — In warehouses with dozens of zones, the overall heatmap can be overwhelming. Filter to one area at a time for clearer insights.

Next steps

Continue to the next article for Troubleshooting Warehouse, which covers common issues and their solutions for scanning, stock levels, packing lists, transfers, and permissions.