Beyond Supply Chain Optimization to Enterprise Optimization


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Beyond Supply Chain Optimization to Enterprise Optimization

  1. 1. Academic Research Enterprise Optimization 4 COLLABORATION Beyond Supply Chain Jeremy F. Shapiro Optimization to MIT and SLIM Technologies, LLC Enterprise Optimization Recognition that strategic supply chain planning should be planning systems, which seek to add analyt- imbedded in larger enterprise planning exercises will serve to ical capability to materials requirements and distribution requirements planning systems. break down barriers to fact-based decision-making. A top-down approach is followed in constructing strategic and tactical planning Introduction continents. The third dimension is inter- systems, which seek to provide holistic, The large and growing interest in Supply temporal integration of strategic, tactical and fact-based insights into the future perform- Chain Management is the result of two over- operational supply chain decisions. Roughly ance of the company’s supply chain. In our lapping motivations: speaking, strategic planning is concerned opinion, a top-down approach is more liable 1) Managers are seeking models and busi- with resource acquisition, tactical planning to produce a coherent suite of modeling ness processes to support fact-based deci- is concerned with resource allocation and systems for integrated strategic, tactical sion making in designing and operating refinement, and operational planning is and operational supply chain planning their supply chains. concerned with business execution. in the firm. Fact-based decision making refers to the Models imbedded in easy-to-use model- In the following discussion, we begin by development, validation and application of ing systems are critically needed to support reviewing the purpose and form of supply data-driven models to analyze supply chain integrated decision making. These systems chain network optimization models to sup- planning problems. Due to advances in IT, employ descriptive models and optimization port strategic supply chain planning. After fact-based decision making has become models. Descriptive models, such as those that, we present extensions of such models possible and necessary. It is possible that forecast future demand or compute that incorporate decision regarding demand because enterprise databases finally exist in direct and indirect manufacturing costs, are management. Similarly, we discuss exten- many companies, although improvements in used to create supply chain decision data- sions that incorporate corporate financial their flexibility and functionality are still bases, which are the inputs to optimization decisions. An enterprise optimization model being sought. It is necessary because firms models. Optimization models allow man- combining the three types of models is then that fail to exploit their enterprise databases agers to explore the space of decision presented. The paper concludes with a brief by creating and using models will find options and constraints to identify effective discussion of the outlook for enterprise opti- themselves at a serious competitive plans. Rigorous optimization models based mization models that integrate these three disadvantage. New business processes are on linear and mixed integer programming central areas of decision making in the firm. needed to fully explore and exploit insights are the only analytical tools capable of fully provided by models. unraveling the complex interactions and rip- Strategic Supply Chain 2) Managers are seeking to integrate deci- ple effects that make Supply Chain Network Optimization sions across supply chain functions, across Management difficult and important. As A growing number of companies are using geographically dispersed facilities, and shown in Figure 1, a suite of interconnected optimization models to help senior across time. modeling systems is needed to analyze sup- management explore the space of strategic The essence of fact-based Supply Chain ply chain problems at all levels of planning. supply chain options. They are often called Management is integrated planning, which Two distinct approaches have emerged for supply chain network optimization models has three important dimensions. The first developing the modeling systems displayed because they explicitly account for activities, dimension is functional integration in Figure 1. A bottom-up approach is costs and capacities across the geographic involving decisions about purchasing, followed in constructing operational network of facilities owned and operated by manufacturing and distribution activities within the company and between the Jeremy Shapiro is Professor of Operations Research and Management in the Sloan School of Management at MIT. For nine years he served as Co-Director of MIT’s Operations Research Center. Previously, he was company and its suppliers and customers. employed by Procter and Gamble, Hughes Aircraft Company, and the Port of New York Authority. Dr. The second dimension is geographical Shapiro is also President of SLIM Technologies, LLC, a Boston-based firm that develops and applies modeling integration of these functions across systems for supply chain management. He is the author of Modeling the Supply Chain, a book published in physical facilities located in one or several 2001 by Duxbury Press.
  2. 2. Academic Research Enterprise Optimization the company, plus those owned and 4 operated by the company’s suppliers and Demand Forecasting and Order customers. Typical decisions analyzed by Management System such models include: • How should the company consolidate its manufacturing capacities following an acquisition or a merger? Analytical IT Scope 10 • Where should the company’s distribu- Strategic tion centers be re-located? Optimization Strategic Modeling System • Should the company introduce a new Analysis product line, and if so, in what facili- ties should its parts, components and final assemblies be manufactured? 9 Tactical Optimization Long-term In most instances, the objective driving Modeling System Tactical analysis is minimizing the total supply chain Analysis cost of meeting fixed and given demand. Many scenarios reflecting variations in 7 8 Production Logistics demand and other planning parameters will Planning Optimization Optimization Short-term be optimized before senior managers, using a Modeling Systems Modeling System Tactical combination of model results and judgment, Analysis commit to important strategic decisions. Our contention is that a cost minimizing objective is timid and short-sighted for the 5 6 Production Distribution purposes of strategic planning. Instead, we Scheduling Optimization Scheduling Optimization Operational believe that supply chain network optimiza- Modeling Systems Modeling Systems Analysis tion models should seek to maximize net revenues by incorporating demand manage- ment decision options. Related objectives, such as to maximize return on assets, might Transactional IT also be of interest to senior management. 2 3 Concepts for carrying out such model exten- Materials Distributions Requirements Requirements sions are the next topic to be discussed. Planning Systems Planning Systems Integrating Supply Chain and Demand Management 1 Enterprise A supply chain network optimization model Resource Planning that minimizes the total supply cost of meet- System ing fixed and given demands provides an estimate of profit margin for each combina- tion of product and markets. Specifically, an External Data optimization algorithm produces a shadow Management Systems price or marginal cost of supplying an addi- tional unit of a product to a market. By com- Figure 1 – Interconnected modeling systems are needed to analyze supply chain problems at all levels of the paring shadow prices against unit sales planning process. prices, the company can identify those prod- ucts and markets with the highest margins. The company should strive to increase sales allowable sales, with gross sales revenues supply chain network optimization model of those products in the indicated markets. reflecting decreasing marginal prices needed can maximize net revenues, which equals Similarly, sales of products in markets with to stimulate increasing sales. In other words, gross revenues minus supply chain cost, by negative margins should be reduced. a gross revenue curve for each product in determining optimal sales of each product in A natural extension based on this obser- each market price can be generated using each market. vation is to let the model select sales for each the price elasticity relating product sales to The extension just described may be dif- product in each market from a range of its price. Given such curves, the extended ficult to achieve from an organizational per-
  3. 3. Academic Research Enterprise Optimization spective, although it is easy to implement in Still, marketing science models describing network model would then select the a model. The marketing department, not the the relationship between sales volume and demand profile and associated supply chain supply chain department, is responsible for marketing control variables have been pro- strategy such that net revenue would be setting prices and sales targets. They may posed and occasionally implemented. maximized. Moreover, information from the feel uncomfortable with quantitative meth- Assuming for the moment that such a model optimal solution to the extended supply ods (i.e., fact-based decision making), were available for a consumer package goods chain network optimization model could be which in this instance involves statistical company, extension of a supply chain net- used to identify new strategies for the estimation of elasticities. Although the work optimization model to incorporate it marketing control variables and thus marketing science literature describing such would be straightforward. As shown in new demand profiles to be added to the estimation methods is extensive, managerial Figure 2, the marketing manager would posit extended model. reluctance in many companies to using them a possible strategy for advertising, promo- Another perspective on the model exten- is still high. tion, pricing and salesforce activities for the sion just discussed is that it relies on Moreover, once we contemplate market- coming year. Given these, the marketing demand profiles and net marketing revenue ing and sales plans allowing price and vol- science model computes sales responses by that we assumed were computed by a ume to vary, we are naturally drawn into month that must be met by the company’s model. If no such model was available or wider issues of demand management. supply chain. We assume sales will equal acceptable, the extended supply chain net- Depending on the industry in which the firm demand since it is a waste of marketing work optimization model for maximizing Marketing Strategy Advertising Promotions Pricing Sales Force Activities Months 1 2 3 4 5 6 7 8 9 10 11 12 Sales Sales Sales Gross Gross Gross Gross Revenue Revenue Revenue Revenue gross revenue marketing costs net marketing revenue – = for the year for the year for the year Figure 2 – A potential strategy for advertising, promotion, pricing, and salesforce activities competes, price may be only one of several expense to generate unsatisfied demand. The net revenues could still be constructed and marketing control variables affecting model also computes associated net market- optimized using data based solely on quali- demand. For a company that manufactures ing revenue, which equals gross revenue tative judgments by the marketing manager. consumer package goods, for example, mar- received from sales minus marketing costs. Such an approach puts into focus the need ket share and volume depend on advertis- Each demand profile and associated mar- for the marketing manager to develop ing, promotion, sales force effort, as well as keting net revenue computed by the market- alternate demand profiles, with or without a price. The reluctance of marketing personnel ing science model would be added to the model, if integration of supply chain and in such companies to a holistic approach for supply chain model with a zero-one decision demand management is to be achieved. modeling these dependencies will be even variable where zero means “reject the pro- Given the importance of demand profiles to greater than their reluctance to estimating file” and one means “accept the profile.” A the company’s future performance, price elasticities. It may also reflect the com- constraint stating that exactly one profile however, it seems compelling that marketing partmentalized approach to decisions mak- should be selected would also be added. science models should be employed as aides ing taken by many marketing departments. Optimization of the extended supply chain in predicting them.
  4. 4. Academic Research Enterprise Optimization Integrating Supply Chain and financial control variables. An important optimization model and a supply chain net- Corporate Financial link to Supply Chain Management is through work optimization model are effected Management ∆Equity for each year, which we express as: through the funds flow equation for each The issues that arise when we wish to inte- ∆Equity = f (Earnings Before Interest and year. The supply chain network optimiza- grate supply chain and corporate financial Taxes during the year, cumulative values tion model, perhaps extended to incorporate decisions are different than those just dis- of ∆Long-term Debt from the beginning of demand management decisions, would cussed regarding supply chain and demand the planning horizon through the end of compute the earnings before interest and management decisions. As with Supply the year, Dividends paid during the year) taxes in each year of the planning horizon. Chain Management, corporate financial The notation f ( ) means “function of.” As (We assume that the company’s earnings management involves numerical data and is stated, it assumes that the company will not from other sources, such as investments, are therefore an excellent candidate for fact- issue new stock. Details of f ( ) have been negligible.) In making multiple year deci- based decision-making. Unlike supply chain omitted, but it is mathematically tractable sions, the supply chain model would evalu- managers, however, corporate financial allowing us to substitute for ∆Equity in ate the portfolio of possible capital invest- managers have not yet recognized the the balance sheet change equation. The ments (or divestments) in the company’s importance of integrated, or holistic, deci- result is the funds flow equation, which supply chain; that is, supply chain improve- sion making based on analysis with opti- is the cornerstone underlying construction ments resulting from possible changes in mization models. of optimization models for corporate fixed assets. On a yearly basis, improve- As we saw for Supply Chain Management, financial planning. ments in inventory management would optimization models can provide valuable In a practical application, each of the cause reductions in the class of current insights into the complex interactions and change variables in the funds flow equation assets yielding no return. Many other con- ripple effects among financial decisions. would correspond to several categories of nections describe the integration of supply Such models, which use linear and mixed variables. For example, the change in cur- chain and corporate financial management integer programming, have long been pro- rent assets would include changes in several models, but space limitations prevent us posed by academics, although widespread classes of short-term investments, changes from further discussions. interest in their application has not yet in inventories, changes in several classes of emerged. They can also be seamlessly inte- accounts receivable, and so on. An opti- Enterprise Optimization grated with supply chain network optimiza- mization model for corporate finance would The supply chain network optimization tion models. Because integration emphasizes also contain constraints on the change vari- model extensions discussed above are sum- the important role played by the company’s ables, such as those corresponding to upper marized in Figure 3. In the middle and right supply chain in determining the financial bounds on the ratio of debt-to-equity in each hand blocks, we display extension of the performance of the firm, it can accelerate year. Lenders to the corporation might model to incorporate a marketing science recognition by senior financial managers that impose these constraints or financial man- model describing demand management. Supply Chain Management involves much agers might view them as performance met- This extended model analyzes decisions more than operational activities such as vehi- rics that the company must impose to sus- about supply chain costs and capacities with cle routing or machine scheduling. tain or improve the value of the firm’s stock. decisions about sales and net marketing rev- The construction of an optimization model Corporate financial planners will typically enues to produce a maximal stream of earn- for corporate financial management begins seek to impose multiple objectives on the ings before interest and taxes for each year with the firm’s balance sheet equation: optimization of their strategic plans. They of the planning horizon. Fixed Assets + Current Assets – Current may seek to maximize the discounted sum The extended supply chain and demand Liabilities – Long-term Debt – Equity = 0 of after-tax profits or return on fixed assets management optimization model is itself This equation holds at all times but, over a multiple year planning horizon, or to extended to include the corporate financial for planning purposes, we consider it at the maximize equity at the end of the planning optimization model that analyzes decisions end of each year of a multiple year planning horizon. Methods of multi-objective opti- across the three areas of strategic planning. horizon. Specifically, corporate financial mization are available for exploring the Specifically, information from the supply planning involves yearly changes in these tradeoffs among such objectives. Such meth- chain and demand management optimization variables. ods produce strategic financial plans that lie model regarding achievable earnings before If we let ∆ denote such a change, we on the efficient frontier of undominated interest and taxes in each year, plus implied have the balance sheet change equation for plans. Using managerial judgment, a specific changes in more on the web each year: plan would be selected from a set of efficient current assets Supplystream’s John Grabski ∆Fixed Assets + ∆Current Assets – solutions generated by a model, possibly by and current discusses the finer points of ∆Current Liabilities – ∆Long-term Debt – taking into account how these plans might liabilities due optimization in his white paper ∆Equity = 0 maximize shareholder value. to operations at The “∆” variables for each year are the Linkages between a corporate financial in each year,
  5. 5. Academic Research Enterprise Optimization are passed to the corporate financial model. scope and meaning of the strategic decisions tion. In any business planning situation, Conversely, the financial model determines identified by a model. however, it pays to follow a problem-solv- budgets for investments in supply chain and 2) The growing success of fact-based deci- ing or inductive approach. This means that other fixed assets over the planning horizon. sion making in Supply Chain the modeling system developers will use This enterprise optimization model is driven Management can and should be used to only those new concepts with significant by the goal of maximizing measures of the promote fact-based decision making in relevance to the planning problems at firm’s economic performance, such as the other areas of strategic planning. hand. Building on existing supply chain present value of revenues or returns on assets The commitment by an increasing number network optimization models, model devel- Earnings Before Interest and Taxes Market Sourcing Strategy Yearly Changes in Supply and Cost Demand Corporate Management Current Assets Chain Financial Model Network Management (Marketing Yearly Changes in Optimization Model Science) Current Liabilities Model Demand and Net Marketing Revenue Investments in Fixed Assets Figure 3 – The supply chain network optimization model extensions generated for each year of the planning hori- of supply chain managers to the application opers could, in many cases, readily add zon. Methods of multi-objective of modeling systems is already influencing selected demand or corporate financial optimization may be used to explore the open-minded marketing and corporate management variables and constraints to efficient frontier of solutions to the enterprise financial managers. A related development the model. optimization model. is the balanced scorecard methodology that 4) The major barriers to extended fact- has found favor in many companies. This based decision making in the firm are Conclusions methodology provides managers with a organizational, not technical. Relative to the current state of supply chain comprehensive range of internal and exter- Organizational barriers include: Myopic network optimization modeling, claims that nal measures and metrics describing the managerial incentives that do not support widespread application of enterprise opti- company’s performance. Specifically, the integrated planning; lack of new business mization models is just over the horizon may balanced scorecard links performance meas- processes to support ongoing, fact-based be unrealistic. Nevertheless, for the following ures in four key areas: financial perspective, decision making at the strategic and tacti- reasons, we believe there is considerable customer perspective (marketing), internal cal levels; poorly defined identities and merit in contemplating such extensions. perspective (supply chain), and learning and career paths for analysts who use data and 1) Supply chain cost minimization is a growth (human resources). We believe the models to evaluate strategic and tactical timid and short-sighted approach to strate- enterprise optimization models discussed planning problems; and, legacy thinking by gic planning. here would add an important dimension to managers that precludes the development Although this point was made during our the balanced scorecard approach because and application of modeling systems. discussion of supply chain network opti- the models would allow senior managers to Because supply chain decision making in mization models, it deserves further empha- more fully explore the space of strategic many companies is performed after sis. Senior managers using models to ana- decisions options. important financial and demand manage- lyze strategic supply chain plans can and 3) Taken one at a time, the supply chain ment decisions have been made, there is should incorporate demand and corporate modeling extensions outlined above are reason to hope that these organizational financial decision options, resources and technically feasible and not difficult barriers will be more rapidly overcome constraints in their evaluations. Even if the to implement, implying that models when supply chain models are extended to extended fact-based analysis is informal, customized to specific enterprise planning other areas of strategic planning. In other such as the specification of “what if” problems could be rapidly developed words, recognition that strategic supply scenarios describing alternate borrowing and applied. chain planning should be imbedded in limits on long-term debt, or alternate We applied a comprehensive, or deductive, larger enterprise planning exercises will demand patterns and their net marketing approach in our discussions of new model- serve to break down barriers to fact-based s revenues, it can add significantly to the ing methodologies for enterprise optimiza- decision making in the firm.