Data analysis for the purpose of system optimization or green field planning, whether with automation technology or not, is one of our specialties. We help you understand what conclusions can be drawn from your data for optimal planning and operation of your logistics system. Any process analysis and concept development should be preceded by a thorough data analysis. We will be happy to perform these for you. Our customers for data analysis and system planning include well-known logistics automation companies, national supermarket chains, international logistics service providers and consulting firms.

A complete data analysis includes at least the analysis of the

Each of these analyses contributes significantly to the understanding of the logistical processes in your warehouse or production operation and thus also provides essential information for the evaluation of existing processes as well as for the creation of new concepts.

What is the point of logistics data analysis?

Data analysis is an essential component of both process analysis and system planning. Key insights can be gained and decisions derived from the information obtained from data analysis. Do you know, for example, whether the arrangement of your products to be picked in the warehouse layout is optimal or whether there are unnecessary walking times? Do you have the right inventory level of your products in stock or are you losing money and space due to overstocking? Would a small parts warehouse instead of a pallet warehouse possibly make more sense for many of your products? How many orders should you pick simultaneously to achieve the highest possible pick rate? With the help of our data analysis, we can help you answer these and many other questions and increase the efficiency of your warehouse and picking processes. When you are planning a new system, whether it is an automated pallet high-bay warehouse, a highly dynamic system for goods-to-man picking of small parts or a system for mixed case picking, data analysis is of great importance to understand which (sub-) systems should be used and to what extent.

What can’t data analysis do?

Data analytics can support a wide range of decisions. It becomes difficult when data is only generated and available at runtime and decisions are to be made in real time. This requires a more extensive substructure of software and possibly sensor technology. The relevant buzz words in this context are Logistics 4.0, Artificial Intelligence, Smart Systems. The substance behind offers on these topics is usually thin; solutions are often offered for problems that can also be solved by conventional means (such as just classic process and data analysis). Please have a look at our small lexicon of nonsensical terms!

In our opinion, all major problems and issues in intralogistics can currently be solved or answered with the help of ordinary process and data analysis. We can also process large amounts of data without any problems.

What does data analysis cost?

The costs to be estimated for a data analysis depend strongly on the scope of the questions to be answered and (significantly) on the quality of the available data. A standardized data analysis for the initial conceptual design of a new automated logistics system can usually be fully completed in two to three days. Questions that require a high level of analysis and are aimed at detailed optimization can require some more effort.

In all cases, however, the following applies: Data analysis is much less expensive than maintaining inefficient processes and structures or choosing inappropriate technology!


As an aid for the collection of data for later data analysis for the conceptual design of new systems, we have compiled a short (English-language) PDF with explanations for you, which you can download here (click).

Data Analysis Training

Do you want to learn how to perform logistics data analysis independently in your company? We got you covered!