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WHITE PAPER Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Analytics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Forecast Cycle Efficiencies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Business Intelligence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 New Product Forecasting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Microsoft Office Integration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Communication. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Collaboration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Jack Hymanson, Solutions Architect in SAS Global Professional Services, provided content for this paper, Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence. Hymanson supports pre-sales forecasting engagements with domain- and industry- specific expertise in sales and operations Planning and SAS ® Forecast Server. With 20 years of experience in demand planning and supply chain management, he has implemented a range of forecasting software and developed a comprehensive sales and operations planning process.

Introduction Sales and operations planning (S&OP) can be described as a consensus-based communication process that provides insight and control over an organization’s supply chain decisions. Executing an S&OP process is dependent on many factors. An organization can have an S&OP process in place and still have difficulty aligning demand and supply effectively. Developing advanced forecasting technology and processes within an enterprise can enhance sales and operations planning and significantly improve demand and supply alignment. This paper will explore technology that can be leveraged, along with better communications and collaboration, to benefit an organization’s S&OP process. Analytics A demand forecast is a fundamental component of an organization’s S&OP process. Its value is demonstrated by its ability to predict future requirements with a reasonable degree of accuracy. Seasonality, promotions and unexpected spikes in demand are difficult to forecast accurately using judgmental input or a jury of executive opinion exclusively. Even when historical patterns are consistent, forecasts created by opinion can be inaccurate. The creation of the unconstrained demand forecast should be based on a statistical analysis of time series historical data. Predictive analytics establishes a forecast baseline that provides the necessary means to initiate fact-based discussions that can drive better supply chain decisions. Taking into consideration the multitude of forecasting software on the market, selection of a package should be made by paying careful attention to components that enhance the effectiveness and maximize the impact of sales and operations planning. The S&OP process can benefit from a software solution that incorporates the following characteristics: • Advanced analytics with optimized model selection. • Scalability. • Reduced forecast cycle times. • Exception forecasting. • The ability to support collaborative planning. Although the art of business forecasting continues to evolve and develop, the importance of predictive analytics is often understated. There is clear evidence in the form of case studies and customer success stories that support the concept of improved forecasts through analytics. As referenced in the Harvard Business Review article “Competing on Analytics” by Thomas H. Davenport, organizations have successfully leveraged analytics to drive business processes. He recognizes analytics as a competitive advantage and states, “Organizations are competing on analytics not just because they can, but also because they should.” Thomas Davenport, “Competing on Analytics,” Harvard Business Review (January 2006).

Not all forecasting software tools are alike and many provide less than acceptable results. SAS ® Forecast Server is a strong analytical forecasting tool that can automatically generate millions of statistically based forecasts without the need for human intervention unless desired. SAS Forecast Server is capable of selecting forecasting parameters that are optimized based on an organization’s unique historical data. Optimized model parameters are selected automatically so users do not have to manually derive them to achieve improved forecasts. As a result, more appropriate models and better-fitting forecasts are generated, which are more accurate and responsive to demand volatility. The benefit to an organization’s S&OP process can be seen in its ability to react to changes in demand more effectively. Changes can be detected and acted on quickly, so inventory exposure can be minimized, and material and capacity alignment can be improved. Advanced analytics within SAS Forecast Server also accommodates flexibility – an important factor since business models change over time and the amount of data that is available today could be very different from what is available in the future. A typical S&OP process may evolve over time to include additional product lines or geographical areas. Existing hierarchy levels may need to be realigned to reflect changes in organizational structure (such as the realignment of sales territories). Being able to create hierarchies easily using SAS Forecast Server is a valuable functionality. Forecasts with their associated hierarchies can be developed and compared to provide a more accurate depiction of demand patterns. The “standard” corporate hierarchy may not always fit the data being forecasted. Because customers don’t always buy products or services in a way that is easy to detect, the ability to make sense of demand by slicing and dicing data into unique hierarchies provides forecasters with a better understanding of demand segregation. When selecting a forecasting solution, take note of how easy or difficult it is to build hierarchies as required. It’s a good idea to avoid forecasting tools that don’t have a flexible hierarchical design. Many ERP systems are not flexible when it comes to an organization’s hierarchy and can require extensive redesign to support a hierarchy change. SAS Forecast Server combines advanced analytics and an intuitive graphical user interface (GUI) to support an organization’s S&OP process by giving better control of the forecast to users who are directly responsible for supply chain management. This is accomplished by addressing the needs of both novice forecasters as well as more experienced analysts. A forecasting software solution should not hinder an S&OP process with interfaces that are difficult to use or by providing less than desirable forecasts. It should incorporate features such as econometric modeling into each forecast to provide a greater understanding of the effects of holidays, marketing events, sales promotions and many other factors. The ability to model external events more effectively can have a direct impact on S&OP by better predicting volatility in demand patterns. Not all forecasting software tools are alike and many provide less than acceptable results. SAS ® Forecast Server is a strong analytical forecasting tool that can automatically generate millions of statistically based forecasts without the need for human intervention unless desired. When selecting a forecasting solution, take note of how easy or difficult it is to build hierarchies as required.