There are many reasons why someone might want to gain an overview of a warehouse or logistics operation: a new job, new responsibilities, a project, or simply a desire to better understand the operation. Sometimes, the need to look beyond one’s immediate area of work arises from daily involvement in a subprocess. However, inquiries and discussions with process participants often quickly delve into details without providing the desired overview.
Many readers can probably relate to this situation and might have even experienced something similar. A comprehensive overview might seem straightforward at first—it’s about the processes, the efforts, and the material flow. And this is exactly where the explorative approach, the journey of discovery with the flumiq 3P model, begins.
The journey starts with examining individual completed orders. One can trace the paths taken on the floor plan or follow the sequence of activities on a timeline. Detailed information is available for each activity, including data about the items, quantities, loading units, personnel involved, timestamps, order data, and much more. This data makes the information tangible and allows to connect to the reality in the warehouse. Dialogues with employees can be conducted based on a concrete example.
In the next step, the focus shifts from individual orders to analyzing the overall process through “process mining“. Here, activities are aggregated; it’s no longer about a single picking step, but rather all 103,530 steps from the past month. 76,989 times a picking step is followed by another, and 26,541 times the list is completed at the pack table (red and green arrows indicate order and employee perspectives). The material flow (blue arrow) is straightforward in this case, as it always moves from the pick bin to the pack table. Using the complete picture, the various process routes are developed from order creation through pallet picking, piece picking, packaging, and loading, to order completion. System integrations and document printing, as well as any other activities, can be included.
A summary of employee activities and efforts is already visible. Typical process metrics, such as Dock-To-Stock or here Wave-To-Pack, can be easily accessed by simply connecting the start and end activities with an arrow. If an activity appears too generalized, it can be easily subdivided according to its underlying properties. For instance, instead of having a single “Document Printing” activity linked with various process steps, differentiating between packing slip and shipping label printing can provide more clarity.
Since the structure emerges from the reality of the stored data, discussions with process participants focus on the reasons behind certain actions, the “why.” This approach quickly leads to a profound understanding of the processes involved.
At the conclusion of the process mining, the results can be visualized as a flowchart using BPMN (Business Process Model Notation). This method allows for the creation of a process documentation from existing operational data that is both current and valid. It provides the highest level of overview—knowledge and understanding of the interconnections within the processes.
PS: Traditional volume statistics and performance metrics can also be calculated and included in this analysis.