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.

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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. customers into like clusters of behavior and workings of a single firm, but to look at the then treated those customers most efficiently performance of the supply chain across mul- Supply Chain Intelligence relative to their ability to return profit. tiple firms that comprise the entire end-to- A supply chain could have many definitions There are still a lot of efficiencies to be end supply chain. The inspection of both depending on the industry, but most indus- gained in the efficient treatment of cus- process and cost structure from the supplier’s tries include a supply chain made up of a tomers, and CRM professionals admit they supplier to the firm’s supplier to the firm to set of geographically dispersed facilities are somewhere in the middle of their journey the firm’s customers and to their customer’s where raw materials, intermediate products, in solving this problem. But in the few years customer through to the end user is key in or finished goods are sourced, manufac- that this methodology has become a corpo- taking out redundancy not valued by the con- tured, stored, transported, and sold. A sup- rate staple, companies have made impressive sumer. Examining supply chains and how ply chain network represents the flows of gains in both adding top-line revenue and they compete against other supply chains goods and services through these five gen- cutting the cost to treat. The breakthrough redefines corporate competition. eral activities, but equally important, the was using business intelligence methods to Collaboration between trading partners, supply chain network represents the infor- better understand the customer’s needs – using business intelligence methods, and mation flow through these same activities. taking information slices through the enter- seeking efficiencies become core competi- Executives today are faced with a tough prise to develop customer intelligence. tive skills throughout the supply chain. So economy, increased competition, fickle con- Supply chain practitioners consider that the drive for efficiencies is a battle on two sumers and a shrinking product lifecycle, the intelligence required to efficiently source, fronts: to get the firm’s internal house in requiring smarter, more strategic decisions make, store, ship, and ultimately sell and order and reduce costs in the supply chain along the supply chain. Supply chain intelli- deliver the product or service to a customer is by looking across multiple internal divi- gence reveals opportunities to reduce costs an area of opportunity not well-leveraged in sions; and to reduce supply chain costs by and to stimulate revenue growth. This abil- most companies. We are seeing evidence in looking across all the elements that make ity to add top-line growth, combined with

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Operational Excellence and Tactical Execution to Reduce Costs

Product Information Flow

Optimal Supply Strategy Demand Information Flow

Source Make Store Ship Sell

Supply Information Flow Optimal Demand Strategy

Customer Information and Funds Flow

Unique Understanding and Insight Lead to Top-Line Growth

Figure 1 Supply Chain Intelligence, Breadth, and Objectives the capability to take a multidimensional the management of the sourcing process developing an accurate supply chain intelli- view across the enterprise to remove ineffi- and the relationship with key suppliers. gence capability. Demand intelligence can be cient costs, distinguishes supply chain broken out into three areas that provide intelligence systems from either ERP or Elements of Supply Chain insight into the customer: SCM systems. Supply chain intelligence Intelligence • Demand management takes a broad view of the entire supply Webster’s Dictionary defines “intelli- •Pricing optimization chain to reveal the processes that truly gence” as “the capacity to apprehend • Inventory replenishment add value from the customer’s perspective facts and propositions and their relations throughout the product lifecycle. and to reason about them.” Combining Demand management for a consumer prod- The need for both descriptive and pre- this definition with that of a supply chain ucts company would include those functions scriptive supply chain models that extract presented previously describes a capabil- that help the firm develop effective trade information from ERP systems and other ity requiring insight and understanding promotions with its retail trading partners supply chain transactional systems has of some complex processes linking and develop a forecast of demand and prod- never been greater. Traditional supply chain demand, logistics, storage, manufactur- uct or service usage for replenishment. This management solutions reflect the way most ing, and sourcing. The words “insight” can be done by accumulating point-of-sale organizations currently think of supply and “understanding” are necessary and other sales factor data and using vari- chain functions: make, store, and ship. because it is not enough for executives ous computational techniques such as time- Supply chain executives understand all too to get answers from a computer system series analysis or causal methods such as well that their solutions must include an on what their positions are along a supply regression analysis. accurate interpretation of demand across all chain; the information needs to contain An additional degree of complexity sets in product lines, and that an important source an explanation of how to harmonize the when multiple products need to be forecast of cost control comes from the strategic main interacting elements of supply chain within multiple product families in multiple sourcing process. Once demand is added to design and supply chain execution. geographic locations for multiple time peri- traditional supply chain functionality, Following are brief descriptions of core ods within multiple market segments. In demand management becomes paramount. supply chain intelligence components: companies with large numbers of products in This demand intelligence capability lies the marketplace, this multiplicity can make at the intersection of CRM and the supply Demand Intelligence accurate forecasting formidable. Having an chain that serves that customer and is a The optimal supply chain is built around the automatic high-performance forecasting capa- core component of supply chain intelli- needs of the end customer. The perfect sup- bility that feeds an accurate interpretation of gence. Similar logic applies to strategic ply chain would include only those activities future sales into replenishment systems that sourcing and procurement: By adding sup- that the end customer values and is willing to help set inventory policies is a vital compo- plier intelligence to supply chain intelli- pay for. Therefore, a keen understanding of nent in maintaining customer satisfaction gence, we immediately begin to think about the customer’s behavior is the first step in and stocking properly.

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Pricing optimization relies on accurate duce policies that will drive inventory This process takes into account existing and demand forecasts and observations of cus- stocking rates, lead times from manufactur- potential suppliers, facilities, their capacities, tomer behavior. Pricing optimization seeks ing and what gets manufactured when, the location and buying patterns of markets, to set a price for a product that is accept- product quality, and order completeness. the products that flow though the network, able to the customer that also maximizes Figure 2 illustrates the cost advantages of the raw materials used to make the product, the firm’s profits. Pricing optimization having a better forecast versus achieving a the steps in the product assembly process, variables include demand, the cost of the certain level of customer service. The goal the resources used to produce, store, and product or service, available inventory, is to achieve a desired customer service rate transport the product from a cost basis across the velocity of recent sales of the product at a lower cost. each activity, and the transportation network or service, and the profits or revenues the and the alternatives. firm requires. As these elements adjust Logistics Intelligence The model’s outputs are in the form of over time, the pricing optimization func- Logistics intelligence takes the changing an optimal scenario for a time frame and tionality should allow prices to adjust “landscape” in demand intelligence and would include the optimal quantity of accordingly. The dimensions described in determines the optimal response, maximizing raw materials required as input into the demand management are the same dimen- customer value and how it affects manufac- sourcing strategy; the optimal levels of sions that must be computed for price opti- turing production capacity and schedules, manufacturing activity and resource con- mization applications. the logistics network, and inventory policy. sumption for each facility as input into Inventory replenishment planning takes Logistics intelligence in this description con- the production strategy; the optimal move- the information contained in demand man- sists of two functional areas: ment of intermediate and finished product agement and pricing optimization to deter- • Supply chain network optimization from manufacturing facility to distribution mine the optimal inventory position. This • Maintenance and spare parts logistics center to final customer markets; and the inventory position is a trade-off between optimal configuration of facility location. capacity utilization objectives and customer Supply chain network optimization looks at The supply chain network optimization service. An accurate demand forecast can most, if not all, of the components of the models form the basis for strategic and dramatically lower the cost to serve. The supply chain of a firm at one time and deter- tactical supply chain design across most optimal inventory decision will take into mines the optimal resource allocation across industries. Figure 3 is a typical graphical account this stochastic information and pro- the enterprise for a given demand pattern. representation of an efficiently designed

50% Forecast accuracy

70% Accuracy

Forecast accuracy and the resulting effect on inventory levels and customer service 90% Accuracy

much inventory Optimal balance of Too High customer service and inventory cost Forecast accuracy distribution Balance “tranche”

Increase in customer service levels Not enough inventory Customer Service ROI

Lost sales due to Reduced overall being out of stock inventory cost Low

Low Sum of All Inventory Costs Across Time High

Figure 2 The Value of Achieving a Better Forecast

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Supply Chain Network Optimization

Packaging Plant Distribution Centers Warehouse Customers

Figure 3 Output From a Supply Chain Network Optimization Model supply chain resulting from a single sce- life. With this information, corrective mainte- Activity-based costing assigns cost to an nario of a supply chain network optimiza- nance can be scheduled rather than waiting activity as it utilizes resources within the tion model. for a system failure to occur. The intelligence supply chain. A capability that combines the Maintenance and spare-parts logistics procedures for condition-based maintenance cost to serve on an activity basis and the is a wide topical area of which this paper use trend analysis and expert recommenda- ability to develop complex supply chains in will only touch on a specific aspect of the tion software to drive predictions of failure a graphical and logical manner would lie at overall function. A brief description of what and to recommend alternative courses of the intersection of supply chain design and the U.S. government is doing relative to action and maintenance activities. supply chain collaboration. an initiative entitled “condition-based main- The measurement of the effectiveness of tenance” illustrates some of the modern Supply-and-Demand Alignment supply-and-demand balance within a firm thinking in this area. In our supply chain intelligence model, sup- is probably best represented by the supply Conditioned-based maintenance is a form ply-and-demand alignment will refer to the chain operations reference model (SCOR). of proactive equipment maintenance that ability to understand two sets of metrics: The scope of the SCOR model includes all forecasts incipient failures. Maintenance • The cost to serve across the supply chain processes from the initial demand signal (an actions are based on real-time or near-real- • The performance management metrics order) to the final signal that demand has time assessments of equipment condition that measure best practices across the been satisfied (the payment). The SCOR obtained from embedded sensors. It con- supply chain model is specific to a product or a family of trasts with reactive (run to failure) and products and is a measure of performance preventative (scheduled) maintenance con- In the previous description of supply chain and process effectiveness. One of the tenets cepts. The goal is to improve the military’s network optimization, the cost structure of the SCOR model is that a supply chain operational readiness and mission reliability along all aspects of the supply chain was a must be measured and described in multiple while reducing costs. significant consideration. Laying end to end dimensions. These dimensions include Condition-based maintenance capabilities all the processes contained in a supply chain reliability, responsiveness, flexibility, cost, allow the detection of changes in the operat- and assigning a cost to each of the tasks or and efficiency of asset utilization. ing parameters of a piece of equipment that activities as a product moves through each The SCOR model is a cross-industry model will allow the prediction of an impending fail- process would provide the total cost to serve that decomposes the processes within a sup- ure to a part or predict the part’s operational a single customer using that supply chain. ply chain and provides a best-practice view of

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supply chain processes. The model is typi- requirement for validated cleaning and relationship management as a prime cally implemented in most organizations by changeovers result in long downtimes source for reducing costs and take-out developing a geographic representation of between product manufacturing. All within the supply chain. Spend analysis their supply chain (similar to Figure 2) and of these tasks must be documented for includes an intelligence capability to then converting the geographic view into a compliance with Food and Drug understand buying patterns and their process-flow view with specific measures Administration guidelines. All of the trends, usage patterns for particular for each process component. The model data, which comes from a multitude of products, and how supplier dependencies becomes potent when used as a collaboration sources across the enterprise, must be have changed over time. tool to improve supply chain processes collected and tracked for each step of The intelligence surrounding risk between trading partners that comprise the the processes described above. The management has great opportunity for cost end-to-end supply chain. compliance requirements track the manu- efficiencies. Risk management in this con- facturing processes at each step from text is an ability to lock in the price of a Production and Process Intelligence molecule to retail shelf for quality. highly valuable raw material or component. This addresses the key manufacturing If production and process intelligence A candidate component is somewhat scarce, concern – quality. This quality issue is provides the view of quality from manu- essential to the product or service, and has manifest in the increasing complexity facturers’ perspective, the warranty guar- experienced considerable price volatility of industrial processes. Early risk assess- antee provides the view of quality from recently. The ability to lock in the price ment of process abnormal deviations consumers’ perspective. Looking at the of this precious material could be the differ- by having the data to determine the consumer products industry, we find that ence in most cases between profitability or root cause of failure analysis is a vital a product warranty has substantial value loss in that product line. component of quality and has enormous to the consumer. In effect, it provides an potential for savings and higher overall “insurance policy” that dissipates the “One Version” of the Supply Chain plant efficiencies. risks in purchasing the product. The elements of supply chain intelligence Higher quality products usually lead to From the consumer goods manufactur- have been articulated in this paper and significant increases in market share. The ing perspective, the intelligence gathered have a dual use. Some firms will want to supply chain intelligence core compo- from warranty data can help deal with execute around individual applications that nents to achieve quality are: issues such as which warranty claims are can handle pinpointed and targeted tasks •Production or process intelligence fraudulent, what are the new issues of without wanting to implement an entire •Product warranty quality facing product returns, how much system. Other firms will need and want to To illustrate the benefits of production or money should be set aside for claims and do more. Underlying all of the applications process intelligence, the lifecycle of a whether failures can be predicted before described in the prior section is the data drug offers a pertinent example. The they occur. architecture that will be referred to as the lifecycle of a drug is somewhat different Intelligence Architecture. from that of other process industry prod- Supplier Intelligence Figure 4 represents an example of an ucts. It typically takes 10 years to turn Supplier intelligence is the ability to under- Intelligence Architecture. This architecture out a potential new drug after testing stand the relationships between the firm draws from such data sources as: thousands of new compounds. The and its major suppliers. This article began • Enterprise resource planning systems potential new drug must be tested for by articulating how getting a true under- • Supply chain management systems both safety and efficacy. This involves standing of supplier relationships across • CRM systems a variety of trials for toxicity and to the enterprise is one of the best ways to • The corporate data warehouse alleviate disease. Finally, the process- take costs out of the supply chain. But this • Purchased and syndicated data development activity produces a chemical understanding requires using business •Corporate legacy systems or biochemical to manufacture. intelligence methods to take a multidimen- The manufacturing process produces sional view of the data across the enter- Conclusions the active ingredient, which normally prise. Supplier intelligence is comprised of Modeling physical systems has kept involves chemical synthesis and separa- two major functions: scientists and mathematicians busy for tion to yield a complex molecule or, in • Supplier relationship management hundreds of years. Modeling the physical the case of a biochemical, fermentation • Materials and cost risk management structure of a complex supply chain with and purification. Material from the the characteristics of supply variability, process must pass quality control checks Getting an accurate picture of total demand uncertainty, and distinct differ- prior to being used downstream in the purchasing spend is difficult at best, and ences by industry is never going to be final set of processes. The need to avoid in a large enterprise it is formidable. easy. In the description of the elements of cross-contamination of products and the Industry analysts have identified supplier supply chain intelligence, many applica-

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Supply Chain Metrics

Demand Logistics Demand/Supply Production Supplier

Intelligence Intelligence Intelligence Alignment Intelligence Intelligence

Demand Side: Products, Time Supply Side: Parts, Components, Time Alignment: Processes, Costs

Extract, Data Store Transform, (“One Version” of the Supply Chain) Administration One Version and Load and Configuration (ETL) Data Synchonization (UCCNET)

Enterprise Resource Customer Relationship Purchased Data Planning Management

SCM DW External Legacy ERP CRM

Operational Data Supply Chain Corporate Data Legacy System Management Warehouse Data

Figure 4 Business Dimensions of the SCOR Model tions are required to accurately describe designs can be understood and considered. understood from the customer’s perspec- a supply chain. Considering that the You can’t optimize what you can’t “see.” tive. Supply chain intelligence provides supply chain ties together all the unique Service quality is an expectation that capability. ■ aspects and sources of competitive that transcends a single transaction; advantage of a company’s products, the it is an expectation that the customer References company’s business processes, the can count on the supply chain to deliver Aberdeen Group. “Strategic e-Sourcing: A Framework behavior of its customers, as well as the a quality experience over multiple trans- for Negotiating Competitive Advantage.” April 2001. behavior of the company’s suppliers, it actions. Keeping promises, developing is no wonder that systems representation consumers into loyal customers, and Aberdeen Group. “What’s Really Worrying Supply Chain Managers.” December 2002. is going to be intricate. offering high-quality products at fair Effective modeling applications will prices are the real motivations for Bowersox, Donald J., Closs, David J., Cooper, M. Bixby. “Supply Chain Logistics Management.” McGraw- require synchronized and up-to-date developing a supply chain intelligence Hill Press. 2002. operational data, not only across a single capability. To ensure that a customer Butcher, Stephen W. “Assessment of Conditioned- divisional supply chain, but also across has a successful experience, the firm Based Maintenance in the Defense Department.” multiple supply chains, inter-enterprise, and may have to re-engineer or reinvent the Logistics Management Institute. August 2000. intra-enterprise. The data store that allows way raw materials are sourced, the Shapiro, Jeremy F. “Modeling and IT Perspectives on for the intelligence methodology is referred way the product is produced, the way Supply Chain Integration.” Information Systems to as “one version.” Business intelligence the product is stored, the way the Frontiers. Vol. 3, No. 4. December 2001. techniques are necessary to take “horizon- product is delivered, and the way it Shapiro, Jeremy F. “Modeling the Supply Chain.” tal” views across an enterprise so less-costly is priced, promoted, and sold. Done Massachusetts Institute of Technology. Duxbury and more-profitable new supply chain well, the entire supply chain must be Press. 2001.

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