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Product and Topic Expert
Product and Topic Expert
Welcome back to our well-known use case series. It is designed to offer a closer look at business value acceleration – driven by the design principles of SAP S/4HANA. The technology-induced implications of the digital economy are huge, though the technology itself is only a catalyst to achieve a fundamentally different business outcome.

The selected use cases, related to SAP S/4HANA Release 1709 are designed to emphasize and visualize the value behind this technological shift, that can be activated by you.

In this blog, we want to focus on one of our major innovations for our 1709 release, which includes predictive analytics and especially the business benefits derived from this capability.

A logical consequence of the digital economy is the Segment of ONE. Customers want to be treated as individuals, not in a segment with others any more. This triggers an average invoice value decrease while the number of invoices is exploding, similar impact you will have in your enterprise logistics, the average value and size of lots is going down while the number of lots is going significantly up. The direct consequence of this "UNIT of ONE driven order size" seeps throughout the entire organization.

How can I keep my corporate functions working at scale in such an environment?

The Big Data challenge becomes reality, but how much has changed in the individual workplace of your employees since this term is socialized? How many better decisions have your employees made, because of smart insights?

Finally, I would argue that “Big Data” is not the problem, the focus needs to be the "right" data, leveraged in context of the adequate business process and brought to the attention of an end-user exactly in the moment a business decision needs to be taken.

The secret sauce of winning in the digital economy is a truly intelligent ERP. One of the ingrediencies of this intelligence is embedded analytics, natively build into the digital core.

With the 1709 release, we go the next step and provide an even more intelligent ERP, as we ship predictive capabilities, ready deployed within the application. Based on this machine learning functionality, this is SAP´s first on premise shipment for predictive analytics in SAP S/4HANA. The first area coming with predictive capability is “Sourcing & Procurement”.


Based on machine learning algorithm, the full contract consumption of a purchase contract is predicted, before it happens. This plays in the value lever category of increase effectiveness, driven by 2 value levers:

  • Speed up signal to action and

  • Raise process intelligence

We shipped this functionality in the Cloud with our SAP S/4HANA Cloud 1705 release and now made it available also for our on-premise customers, derived from the same single code line as already known.

To predict a purchase consumption, the predictive analytics algorithm set up in the SAP S/4HANA system today basically leverage historical data to calculate an estimated consumption date and will be further detailed out with situational and contextual awareness capabilities going forward.

The predictive analytics functionality has been integrated with embedded analytics in the SAP Fiori “Quantity Contract Consumption” app. Before 1709, this app already provided a comprehensive overview of your company`s purchase contracts and all relevant data related to them, such as the validity time frame, material group, target amount as well as the current released amount. This has now been extended, with forecasted purchase contract consumption data. The estimated consumption date for a purchase contract is displayed in the “Quantity Contract Consumption” app, both graphically and numerically.

You can access the “Quantity Contract Consumption” app with the SAP Fiori role “Buyer”.

Using this app, purchasers can intuitively and closely analyze and predict existing purchase contracts, evaluate the situation. With this information on hand, purchasers can take immediate action and renegotiate purchasing contracts before due time, considering consumed and predicted information together.

Having an extended or new purchase contract in place, before being close to or overspending on the original contract will provide you a significantly improved situation.

Without the predictive analytics functionality, buyers had to know their contracts, the intelligence of insights and action was mainly in front of the screen. Contracts were followed actively and closely, trying to manually predict spending patterns related to each contract.

A purchase contract might be already consumed by 75%, but upcoming spending behavior is quite low in the upcoming months. Vis versa, a purchase contract that is only consumed by 40% might be expired within only one month, since the demand for the underlying goods has risen tremendously over the last weeks.

Now with the predictive analytics functionality and the underlying machine learning algorithm, buyers do not need to rely on human investigations, as the system can provide the expiration date and a recommended renewal automatically.

The new predictive analytics for contract consumption functionality is a powerful tool that enables companies to change basic processes and focus on exceptions to increase effectiveness.

Stay tuned when we explore the technical aspects of this use case and illustrate our upcoming use case blogs following over the next few weeks!

All blog posts of this series can be found here

For more information on SAP S/4HANA, check out the following links:

SAP S/4HANA release info: www.sap.com/s4hana

And follow us via @SAP and #S4HANA or myself via @BeSchulze