All warehouses, large or small, are complex environments where it can be difficult to spot possible improvements. Our experience shows that, with the right tools and knowledge, there are considerable efficiencies to be made. Traditionally, planners and operational managers have developed models that simulate warehouse activity across a number of days or even weeks, grouping activities and using ‘averages’ in order to develop an overview of requirements. These models cope well with the many warehouse activities but don’t provide the level of detail required to improve real operations. Simulate Warehouse Operations Davies & Robson has developed a DITLO (Day in The Life Of) model that simulates hundreds of activities and fixed resources throughout the day.  Each activity is planned across every hour and associated with the relevant resources and throughput. It allows traditional synthetic productivity rates to be developed and added to the simulation or for actual operational performance information to be used. At Davies & Robson, our team of warehouse consultants use DITLO modelling to:

• ASSESS shift patterns and match workforce to workload
• ENABLES detailed cost analysis to be use to assess options
• REVISE working practices
• PINPOINT bottlenecks and simulate operating practices to relieve them
• ELIMINATE congestion points and improve warehouse flows
• IMPROVE the perceived throughput capacity of an existing operation
• IMPROVE productivity
• DEVELOP a detailed business case to support discussions about change with workforce or trade unions
• ENSURE planned performance targets are met
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Benefits of DITLO Modelling   The simulation allows us to match manpower to work flows, ensuring shift patterns are suitable and the workload is appropriate for the resources.  [Example 1 v4] Example 1 demonstrates an incidence where shift patterns and breaks did not support the workload resulting in over-resourcing at certain times of the day. [Example 2 v4] Example 2 shows how modelling can pinpoint potential bottlenecks and backlogs. Here we see that the available workforce does not match the increase in the Goods-In rate during the afternoon.  When goods are not processed at the same rate they are received, congestion occurs causing products to become unavailable for picking and slowing the operation. Modelling can pinpoint potential bottlenecks and backlogs, rebalancing the workflow would improve the overall productivity of the warehouse. [Example 3 v4] Example 3 shows how the use of doors varies across a 24-hour period. A shortage of loading doors could be considered a bottleneck and peak loading times may stretch operational requirements beyond the capacity of a building.  Peak use, as expected, is during the morning and mid-afternoon despatches. The current number of entry points can cope with planned volumes and, by realigning picking patterns and preloading of vehicles, additional capacity could be enabled. DITLO Modelling is often overlooked by planners and operations teams but the examples above illustrate the value of a deeper understanding of workflow variance.