Forecasting

Uncertainty is difficult when making decisions, especially within the complexity of a supply chain or operation of a large warehouse. Reducing a part of this uncertainty by using the most advanced prediction techniques can have a significant impact on the performance. For example, fluctuating demand causes high fluctuations in workload which reduces productivity. Accurately predicting customer’s demand gives the warehouse the opportunity to start processing orders even before orders are being ordered.

Process mining

With only a minimal number of data-points we can get very useful insights in various logistical and organizational processes, for example in picking and invoice processes. Combining activities, timestamps and case id’s, we can create dynamic visual insights in the performance of a process and identify quick wins or risks.

Order batching and order release

A large part of the operational costs for most of the warehouses comes from the picking process. Most of the warehouse management systems (WMS) on the market do include a standard order batching strategy. Pipple has achieved large savings on picking costs by developing and implementing tailor made software solutions that fit perfectly to the operation. We have real time A.I. planners running operational in various warehouses.

Identify and control process dynamics by simulation

Optimization, algorithms and optimized decision making contribute the most to the overall performance when applied to the bottleneck of a process. But it is not always clear what part this is, and it might even change over time. By combining optimization models with simulation techniques, we can finetune the decision making of our algorithms even before they are implemented.

Other solutions we offer within the supply chain:

• Fleet and route optimization
• Inventory management and optimization
• Product storage location (ABC)
• (Multi)resource planning and scheduling