Not long ago, the average executive’s idea of a business forecast was a simple, spreadsheet-based extrapolation of previous performance. Today, however, business executives are recognizing the need for more advanced analytics. These executives want to use the billions of data records stored within their company’s IT systems to visualize and assess future performance, establish sound strategies, and better manage their business.
This article explores two business drivers for leveraging advanced analytics (using two industry examples) and explains the benefits of implementing and managing advanced analytics through specialized services, such as SAP’s new performance and insight optimization services.
Analytics Driver #1: The Business Demands It
Let’s consider the challenges facing an executive at a major international retail organization: “How do I balance the need to give shoppers what they want and the need to grow revenues and profits?” (see Figure 1). Simply cutting prices could be disastrous. Will shoppers notice or care about any price reductions? Certainly, margin will be affected, and it is likely that there will be little positive movement on units sold for low elasticity items. Can the organization even afford the cuts?
Previously, it was near-impossible for a business executive to run through all of the possible “what-if” scenarios due to the overwhelming combinations and permutations to consider (dozens of competitors, hundreds of stores, thousands of products, millions of shoppers, and billions of data records). But now, advanced analytics can mathematically model local shopper demand from historical point of sale (POS) data so that retailers can predict unit sales for each product at each store. They can also measure local sensitivities to price and other key drivers — such as time of year and promotional activity. The shopper concept of “value for money” can also be defined and measured dynamically so that optimization algorithms will directly guide the retailer on where to invest and how to balance investments with efforts to grow revenues and profits.
Because demand modeling and advanced analytics provide a focus on the end customer, business executives are empowered to increase customer loyalty and satisfaction and, in turn, increase revenues and profits.
||Advanced analytics can help retail companies balance growing sales and profits with customer loyalty and satisfaction
Analytics Driver #2: Technology Must Be Intuitive
Consider a banking executive who is managing interest rates for existing savings products while also introducing a new product. He wonders: “How can I grow business volume without paying excessive interest? And will the new product cannibalize existing business?”
What the executive needs is decision support to simulate alternatives and help him make informed decisions quickly. Figure 2 illustrates SAP’s performance and insight optimization simulator solution, in which the executive visualizes alternative scenarios and assesses their likely impact. The back end comprises performance and insight optimization science, while instant visualization of the results via the SAP BusinessObjects front end makes the process intuitive. The complex relationships, driven by billions of data records, are made manageable and understandable.
Mathematical models do the heavy lifting on the numbers, while the executive focuses on rapidly assessing trade-offs for true decision support.
||SAP’s performance and insight optimization services’ forecast simulator for banking
Overcoming the Mistrust of the “Black Box”: Why a Services-Led Approach Is Key
While generalized predictive analytics tools provide reliable data mining capabilities, there are several drivers of accurate forecasts that these tools cannot adequately address: “How do we process volumes of data efficiently? How do we deal with missing data? What happens when our competition reacts, or when the economic climate changes? How do we interpret the results?”
To answer such questions, you need professional expertise at hand. That’s why the best approach is to combine advanced analytics with trained services resources, especially for:
A high-quality services team, such as that of SAP’s performance and insight optimization services (see sidebar), is trained to provide the requisite ramp-up to ensure that all technical aspects of the forecasts are aligned with business needs.
2. Ongoing Maintenance
A services team can also manage models very efficiently (ensuring that they are tuned, for example) in a hosted environment. It can quickly and seamlessly apply model improvements and updates without disruption to the organization.
3. Eliminating Fear of Risk or Failure
A services-led approach that identifies an easily manageable, short-term project opportunity with large ROI and minimal risk or business disruption can drive long-term transformation. Once companies establish the short-term value of leveraging advanced analytics, they can unlock the broader, long-term value without fear of risk or failure.
Extending the Value of Your Software Investments
SAP views advanced analytics as a combination of software, mathematical models, algorithms, and business knowledge to help organizations visualize insights, simulate scenarios for decision support, and maximize business performance. Particularly when combined with trained services resources, advanced analytics are an opportunity for organizations to not only optimize business performance and insight, but also extend the value of their software investments.
Dr. David Ginsberg (firstname.lastname@example.org) is the global co-head and vice president of performance and insight optimization services at SAP. With over 20 years of experience in merging science and business in the areas of advanced analytics, business planning, and strategy, David currently focuses on optimization for the retail, CPG, financial services, and utilities industries. He holds a PhD, MSc, BSc, and P.Eng in electrical engineering.