Reinventing logistics through data mining with SAP S/4HANA

The logistics transactions offered by the ECC 6 generation of SAP resolutely focused on data entry. Little recourse was given to the analysis or application of this data.

Materials Managers had to use predefined analyses, which were limited to exploring certain axes, in a predefined way. Also, the user interface (SAP-GUI) dated back about 20 years and was based on a thick client that was not available on mobile terminals.

This was one of the main shortcomings in the logistics functionalities of the previous generation of SAP software. Users had to struggle to benefit from their data.

When migrating to SAP S/4HANA, logistics managers were immersed in a completely different software universe and a completely redesigned interface (Fiori). Data analysis was now the heart of the application.

SAP S/4HANA and the use of an In-Memory database – SAP HANA – made it possible to work directly on raw data. This gave users complete freedom in terms of analysis. The axes of exploration became an open-world environment.

Somewhat surprisingly, the switch from SAP-GUI to the Fiori user interface did not immediately result in productivity gains. In fact, whilst SAP GUI was initially difficult to master, trained users then found it quite effective, and it’s taken Fiori a few years to deliver on the promise to increase user productivity.

Benefiting from productivity gains

These productivity gains start with the use of the Fiori launchpad, a personalized cockpit of Fiori tiles. Each of these tiles displays the result of a specific analysis run dynamically, allowing an MRP (Material Requirement Planning) manager to identify at first glance the issues to solve during his working day. With the traditional SAP-GUI interface, this would require at least an hour of work.

Better still: Fiori, coupled with the computing power of HANA, will offer suggestions for the resolution of these issues, as well as an evaluation of the effectiveness of these solutions thanks to the integration of Machine Learning functions at the heart of SAP S/4HANA. And this extends beyond MRP to inventory management. For example, where the integration of pivot tables in the application allows users to save a lot of time by avoiding imports into Excel.

These major changes have a profound impact on the daily lives of the users

When looking at the example of an MRP manager, there are two tasks that occupy their time every day. These are dealing with the exceptions that the MRP has not been able to manage (delays, special cases) and maintaining products’ MRP data (lead times, lot sizes, safety stocks, etc.).

The latter is substantive work that will improve the performance of the MRP in the long run. However, with ECC 6, two-thirds of MRP managers’ time was occupied by processing exceptions. By switching to SAP S/4HANA, and thanks to personalized cockpits, this time can be cut by around half.

Reducing the time to manage exceptions creates a virtuous circle in which data is increasingly complete and clean. This reduces the number of exceptions that the manager will have to deal with.

In addition, the structure of SAP S/4HANA also makes it easier for a materials manager to take charge of a new materials class. A few hours of investigation are enough. This facilitates mobility for MRP managers within companies.

Machine Learning can anticipate delivery delays

These advances are supported by the integration of machine learning functions. Machine learning can be used to increase user productivity and improve the quality of logistics management across the process.

Let’s look at a specific example. When managing supplies, the delivery date will often be critical. The ability to anticipate delays is an invaluable asset to an MRP manager.

Machine Learning is basically the only effective and consistent way to predict possible delays based on historical data. Identifying the probability of delays is far too complex to be done manually, even for a seasoned user.

SAP S/4HANA provides these forecasts directly in the order tracking tool, which makes it easy to intervene to anticipate difficulties. The software calculates the same type of probabilities for shipping delays for products, which be essential for the MRP manager.

Continuously adding functionalities for smoother logistics

Since the release of the first version of SAP S/4HANA in 2015, SAP has continued to enrich it adding new functionalities, such as Extended Warehouse Management, Transport Management, Demand Driven MRP, or even Predictive MRP. Some of these modules were not new, but most have been redeveloped specifically for SAP S/4HANA.

SAP also regularly delivers new Fiori tiles that reimagine entire processes. Taking advantage of access to raw data and tools such as machine learning and pivot tables, these tiles will deliver ready-to-use KPIs and appropriate solutions to logistical problems.

Take for example transaction MD04 (Display Stock/Requirements Situation): it has been redesigned within several tiles for greater productivity. The same applies to sales orders. New tiles allow you to classify the reasons for the non-completeness of an order, then dig into each problem identified to provide an appropriate solution.

These new FIORI applications almost always follow the same logic. They start from an aggregated dashboard, then allow users to drill down with a few clicks to a single operation or issue, presented with remediation proposals.

This use of data and the increasing integration of machine learning functions is helping reinvent logistics within SAP. The scope covered by these functions now covers virtually all areas of the software package and helps unlock the productivity gains SAP S/4HANA provides in logistics and within the wider operation of the company.