Vision Supply Chain Intelligence Michael P. Haydock SAS Institute Supply chain intelligence reveals opportunities to reduce costs and units. Managers responsible for the results stimulate revenue growth and it enables companies to understand want control over most, if not all, supply chain functions producing those results. the entire supply chain from the customer’s perspective. Procurement is a good example, where the trend for each division to do its own strate- SAS Supply Chain Intelligence is a new Driving Forces Create the Need gic sourcing began to emerge. Logistics is initiative that provides the capability to For Supply Chain Intelligence another example, where each division extract, sense, and analyze information A prominent management style throughout moved its own goods from manufacturing about a supply chain. It enhances an exec- the 1990s was to drive down into an organ- through to the consumer. To help these utive’s ability to reason through business ization the responsibility and authority to autonomous divisions do their jobs, compa- outcomes and prescribes the best course drive a division’s profits. The smaller the nies purchased enterprise resource planning of action for focusing an organization on division, the further down into the organi- (ERP) systems and supply chain manage- the highest impact activities. Modeling a zation one could drive the responsibility ment systems highly targeted to solve a few supply chain is, at best, a complex for profits. In organizations effective at specific challenges, such as inventory man- endeavor, because in doing so we model using this management style, each agement, materials requirements planning, an organization’s processes, costs, and employee felt responsible for the success invoicing, transportation routing systems, objectives. Global supply chains that cross of his respective division. and shop floor control. Divisions wanted to multiple geographies, cultures, and cur- So far, nothing is wrong with this model. get a handle on their performance as well as rencies add to the challenge. In fact, using this model effectively seems to achieve operational excellence, so they Before examining the supply chain of have been one of the key success norms for installed their own “instance” of these ERP a particular business, it may be advanta- chief executive officers during the decade. and supply chain management systems. geous to understand the motivations CEO portfolios contained assets made up of This management style and strategy behind supply chain improvements. The the divisions within their companies. The worked well until the U.S. economy began confluence of several recent business typical measure of success was whether a to slow down in 2000. It was difficult for and technical developments has made division was No. 1 or No. 2 in its respective corporate chiefs to go back to operating the study of supply chain improvements marketplace. Funding and careers were divisions and try to make them more effi- extremely relevant: made or broken with the ability to generate cient. The operating units had been driven 1. An understanding and an appreciation results. Corporate headquarters were typi- to efficiencies for nearly a decade, and that serving a customer is done by cally run with a minimum of staff; in fact, in there was little to be gained at reasonable many firms in collaboration. the early 1990s companies often moved costs. So they began focusing on “cross- 2. The ability to capture and analyze headquarters personnel out of headquarters organizational” efficiencies – especially in data from enterprise resource and into the operating divisions so they logistics, manufacturing, and strategic planning systems across the firm, could be closer to the firm’s customers and sourcing. Managers began to ask: “Can I combined with business intelligence where their contributions could be solidly take a horizontal look across the operating methods, can reveal opportunities to measured by performance in the market- divisions and gain efficiencies that I can’t take out additional costs previously place. This remains the preferred corporate get by tasking vertical operating companies not recognized. management model, and it may be for quite to be more efficient?” 3. A desire by executives to understand some time – it clearly drives business results. Firms are highly complex organizations the enterprise as a whole. One of the model’s disadvantages is that with multiple divisions, making an “infor- 4. Dramatic improvements in integrating it tends to decentralize some core supply mation slice” across divisions complex and optimization and forecasting software, chain functions into the divisional operating multidimensional. The information systems which have improved the output of computational solutions. Michael P. Haydock is a vice president at SAS Institute, where he serves as the worldwide solutions executive for SAS’ Supply Chain Intelligence initiative. The SAS Supply Chain Intelligence initiative was created to address integration problems linking demand intelligence, logistics intelligence, the alignment of This paper will provide the reader with a supply and demand, production intelligence, and supplier intelligence that exist across complex supply chains. perspective of the elements of supply Through large-scale data mining, statistical forecasting, and mathematical optimization techniques, these chain intelligence through examples. solutions can dramatically improve the business performance of intricate supply chains. ASCET • 15 Vision that collected the data and solved some of our customer base of centralized corporate up the supply chain – from raw materials to the reporting challenges inside individual function beginning to take “horizontal” views ultimate consumers. operating units were not designed to address across operating divisions of the enterprise to The need for response-based supply this multidimensional information slice. look for additional cost efficiencies. chains that can adapt continuously to Addressing this type of information challenge Strategic sourcing is a good example. changes in demand, logistics situations, requires business intelligence methods and Sourcing requires an understanding of the rela- inventory positions, manufacturing backlogs, techniques that look across multiple business tionships a firm has with its many suppliers. and materials acquisition has fueled the trend dimensions and “mine” the data for its infor- The decentralization trend in the 1990s led toward intra-company collaboration. This mational content – turning information into firms to have many relationships across the sensitivity to changing conditions is best insight and, in the case of a supply chain, enterprise with the same supplier. This led to illustrated in event-driven management. The finding opportunities where costs can be instances where the same company – from an motivation is the opportunity to: never miss taken out and top-line revenue can be added. enterprise point of view – paid different prices a sale; take costs out of the system on very Corporations have a lot of experience with in different divisions for the same product and short notice; and look for ways to delight a similar multidimensional problem – cus- did not take advantage of price discounts for existing customers. tomer relationship management (CRM). In high quantity relationships for essentially the In exploring more efficient techniques to the early 1990s, firms learned that they had same item coming from the same supplier. treat customers, companies have learned that multiple relationships (or multiple dimen- One explanation is that different operating the data has to pass through multiple sions) with the same customer, yet they companies were willing to pay a premium for processes in its journey from raw observation would treat that customer, from a sales and certain parts because their use of the part was to business intelligence. Developing one ver- marketing point of view, as if each operating critical in their product, while another operat- sion of the supply chain depends on having unit with part of the relationship “owned” ing company within the enterprise buying the the right set of information technology com- the customer. This not only confused same part did not value that part as much as a petencies to handle large data repositories customers flooded with promotions to cross- critical component and was not willing to pay that allow for complex views of the data, the sell and up-sell into other related divisions, as much. When we inspect our clients’ data, right set of computing technologies that allow but treating that customer in that way typi- we see the range of prices they pay and how for massive amounts of information to be cally costs more than that customer’s profit much inefficiency or “slack” could be elimi- processed quickly and, finally, a business contribution to the firm. To develop a more nated from the system by taking a multidi- intelligence software platform to perform the meaningful relationship with a customer, mensional approach across the enterprise. analysis to gain visibility into optimal supply companies began to collect data across the Another trend motivating the need for chain design and execution configurations. enterprise about the stimulus and response multidimensional views of the supply chain We call this multidimensional capability behavior of customers, segmented those is the drive to look not just at the internal supply chain intelligence.