The new SAP Predictive Analytics integrator makes it easier for companies to integrate and use their own data models in SAP software solutions.

Within an intelligent enterprise, all business departments should be able use predictive analytics. Its deployment scenarios range from inventory and contract management to the early detection of fraud.

Capgemini’s 2018 study on IT trends shows that predictive analytics is steadily gaining in importance. Ranked third in this year’s study, it is a high priority for more than half of those surveyed, topped only by privacy by design and security automation.

It is no surprise that predictive analytics is receiving a lot of interest. The technology enables companies to use historical data to identify, for example, the customers or employees it is in danger of losing – before it is too late. They can then reach out to these customers or employees and take appropriate action to retain them. The technology can also forecast product sales in selected countries, assess credit risk, and enable predictive machine maintenance.

The IT structure of an intelligent enterprise. Predictive analytics belongs in the business intelligence category; SAP Leonardo Machine Learning is one of the underlying technologies.

How Does Predictive Analytics Work?

First, the data manager component in SAP Predictive Analytics prepares vast amounts of data. Then, based on this data, users configure their own basic predictive models, select training datasets and filters, and train the algorithm within the application. Automating the creation of models means that users no longer need to write their own algorithms, which makes deploying the technology to business departments significantly easier. It is also possible to run a large array of models at optimal performance levels.

Leveraging machine learning capabilities, the models constantly and automatically adapt to new data, therefore ensuring that the outcomes remain reliable. The results are integrated directly into familiar applications so that all users — from board members to plant managers — can access the outcomes and instigate action accordingly. And crucially, the software presents the data in an intuitive format that is easy to understand.

This smart approach makes it easier for business departments to adopt predictive analytics. As such, nothing stands in the way of using this technology – in almost all SAP applications.

“Thanks to our automated forecasting functions, companies can very quickly create forecast models and integrate them into their business processes,” says Dr. Sarah Detzler, a data scientist at SAP. “The ability to identify patterns and complex connections within their data gives them new insight and predictive information that they can use to improve their processes.”

Predictive Analytics in Action

Predictive analytics is no longer just a distant dream. A host of other examples show just what is achievable.

German bookstore chain Thalia deploys a platform solution combining SAP HANA and SAP Predictive Analytics to create analyses and forecasts that help the company offer as pleasant a customer experience as possible. The process covers more than 250 stores with varying requirements, e-readers, thousands of inventory items, and more than 18 million master data entries. Customers identified as being at risk of churn receive personalized product recommendations and exclusive offers. Thalia uses these and other functions to retain profitable customers and increase customer value.

Cisco Systems and mBank also use predictive analytics to anticipate customer behaviors and, as such, positively influence the consumer buying process.

“No one doubts anymore that predictive analytics adds value. Demand for it is burgeoning and business departments’ interest in embracing predictive methods is strong,” says Detzler.

Predictive inventory management and contract management are two of the scenarios that are already easy to integrate into business processes today. Inventory management is vital to companies that deliver goods or receive stock from their plants and suppliers. To help ensure just-in-time manufacturing, these companies must constantly monitor their stock so that they can react before production comes to a standstill. One tool that helps them do this is the Materials Overdue – Stock in Transit app from SAP, which by forecasting stock delivery times and more, makes requirements planning vastly simpler.

Covering contract creation, execution, and monitoring, contract management enables companies to maximize their operational and financial performance. As such, it is an area where businesses hope to gain practical help from the digital transformation. Predictive analytics technology can foresee every event that may occur throughout the lifetime of a contract — including termination, renewal, orders, and amendments to master agreements with suppliers — so that a company can take appropriate action. SAP Predictive Analytics provides end-to-end workflows to match.

There are plans to include other scenarios, such as fraud detection, as standard in SAP applications; SAP Fraud Management identifies potentially fraudulent activity using historical data.

Predictive analytics could also be used to forecast how likely it is that a business deal will be closed. If sales teams focus on high-potential deals, they stand a better chance of achieving their targets, and they would save time into the bargain. Management would also benefit from being able to forecast revenue more accurately and thus plan more effectively.

Ready to Achieve Remarkable Things

Thanks to SAP Predictive Analytics integrator, fully configured tools for predictive analytics like those described here, are already included as standard in a variety of SAP applications, including SAP S/4HANA, SAP Business Integrity Screening, and SAP Hybris Cloud.

“Business departments can now leverage the data available in SAP solutions such as SAP S/4HANA to train their own models and integrate the outcomes into their business processes,” says Detzler.

Using predictive analytics for specific business processes increases the value of the digital core because the ability to rapidly build and deploy predictive models enables companies to use their data to its full potential. And SAP customers benefit from the best of worlds, since they have the flexibility to either use the standard scenarios or, with the help of SAP Predictive Analytics, to create scenarios that more accurately address their specific business requirements.

SAP Predictive Analytics integrator represents a significant step for SAP. By allowing business departments to adopt pre-programmed algorithms or easily build their own, it gives them access to the valuable world of predictive analytics. Indeed, some customers are already savoring the benefits of being able to identify and promptly react to fraudulent activity or delayed deliveries.