Efficient System Optimisation with Analytics
What we regard as “normal” efficiency and speed of logistics is increasing day by day. Transport paths are regulated, packaging is standardised and warehouses are automated. But what happens when we (yet again) fail to fulfil the current needs with the existing infrastructure?
“A few years ago, we completed a large investment in an automated warehouse that raised our efficiency to a higher level for that time. Today, this is already inadequate. We don’t have many options, or do we?” a client complained to us.
There are in fact several options for solutions. You can build another warehouse, a faster one next to the old warehouse, for instance. However, the investment is huge, and you may not even have enough space for it from the start. Alternatively, the existing system can be replaced by a newer and faster one. This means that for several months your operation will be effectively “paralysed”, which you probably cannot afford. Finally, you can replace the software. The actual replacement only takes a few days, and the cost amounts to only 10% of the investment in the whole system. What do you gain by doing this? A modern IT system that not only includes “support for the work process”, but also data capture, analytical capabilities and optimisation.
How can the operation of the existing system be improved?
If we focus on the existing logistics system and do not have any means for changing the warehouse technology, set-up, etc., the system’s operation can be enhanced by improving the following areas:
- stock distribution and stock levels;
- the sequence of the preparation of individual orders and lines of orders;
- the sequence of processing orders and lines;
- the pre-preparation of order execution (supplementation, consolidation, marking, unpacking/packing).
The key issue in any kind of optimisation is the best possible knowledge of the future. We acquire this knowledge from known orders (e.g., for a day or two in advance), from analysing past events, from business information (seasonal nature, promotion, discontinuation of products, introduction of new products, etc.). From this multitude of data (according to the principle ‘more is better’) the key information needs to be obtained (holding to the principle ‘less is better’). On the basis of this key information, we can then plan the optimisation and changes in the IT system.
Improvements with a measurable effect
Whenever the problem is clear, we can use the Atlas WMS logistics IT system for the collection and analysis of data. However, for research and learning purposes, as well as for determining solution options, it is better to use a dedicated system for business analytics or data visualisation that enables an easy changing of views, diverse scenarios and the drafting of an appropriate report that clearly shows where potential improvement is possible.
If the testing shows that the improvement can be implemented and that it is effective, we further enhance the logistics IT system targeting two goals:
- Implementation of the improvement;
- Enabling measurement of the improvement effect.
In this way, we will know exactly what we have achieved.
Such an approach is a reliable path to an improvement that can even be 100% or more.