The information hidden in data — such as retail sales, industrial production, and transaction data — is imperative to a company’s future. But simply accumulating massive amounts of data is not the answer. Fast analytics systems, correct correlations, and asking the right questions can help generate more value out of this data and ensure companies are using the information to its full potential.
Looking Toward the Future
DSAG’s recent investment survey indicates a significant trend in this direction: 41% of the SAP users surveyed intend to invest in analytics in 2014, specifically in the areas of business intelligence (BI) and business warehouse solutions.1 The planned expenditure on analytics tools is high and it appears that this trend will continue to increase. However, the desire to implement analytics solutions is not, by itself, sufficient. Owning high-quality data sets and establishing new skills within the company are just as important as implementing powerful systems.
Predictive analytics can help a company answer crucial questions: Where do customers intend to invest in the future? How is demand developing right now? Which products must be supplied tomorrow to which markets and in what quantities?
Predictive analytics not only juxtaposes figures, but also combines scientific calculation models with data from the near and distant past. For example, meteorological services now have a worldwide reach with a high degree of precision for weather forecasts. There is no reason why business enterprises should hesitate to take advantage of the same technology, which is already easily available to them.
Owning high-quality data sets and establishing new skills within the company are just as important as implementing powerful systems.
What You Need Now
When using powerful analytics tools, such as SAP Predictive Analysis, you need to ensure three fundamental items are present within your company:
- Preparatory selection and modeling must be performed on the data and the required mathematical procedure must be defined.
- Basic calculation models that provide the best results for their special tasks should be developed and defined. Then they need to be continuously adapted to the requirements of the company.
- A management body is required to implement the results of the analysis in specific business measures.
The areas of supply chain, customer relationship management, risk management, and fraud management are especially ideal for the application of predictive analysis. In each area, minor changes can produce major benefits. For example, a well-known credit card company managed to reduce the time required to check large volumes of transactions for attempted fraud from one hour to a few seconds. Through extremely fast recognition of patterns, the company is able to protect its customers from losing assets.
Once again, it is important to ensure that employees have the appropriate skills and knowledge to use these tools. Many users are less interested in the technical and mathematical intricacies and are more focused on convenient and efficient use of the analysis functions. SAP should continue to keep the user at the forefront when building predictive analytics tools, keeping in mind the importance of user experience and user adoption.
1 DSAG, “DSAG Investment Survey” (February 2014; www.dsag.de/pressemitteilungen/it-budgets-growing-more-slowly-previous-year). [back]