Course Summary

Characterization of the operations in contemporary SC’s and the area of SC management A SC chain consists of all the required stages for fulfilling customer demand, and it involves the transfer of materials, information and funds. The various operations involved are organized in a number of cycles, with the typical cycles being customer order, replenishment, manufacturing and procurement. Setting up and operating these cycles for any particular supply chain boils down to a number of problems / issues that can be characterized as strategic, tactical and operational. The field of SC management deals with the systematic study of these problems.

The role of Corporate Strategy and its connection to SC Management Any well-run contemporary organization is expected to have a well-defined (and stated) corporate mission, defining its role with respect to society, its employees and its investors. In addition, the organization’s corporate strategy seeks to continually (re- )define the competitive advantages that must be sought by the organization in order to succeed in its mission. These competitive advantages are determined on the basis of –the evolving strengths and weaknesses of the organization and its (key) competitors; –the prevailing political and economic conditions; –the phase of the product/industry life cycle; and they seek to regulate attributes like the organization responsiveness, cost efficiency and product quality / differentiation, in order to build and sustain the company’s market share.

The role of Corporate Strategy and its connection to SC Management (cont.) The various departmental / functional (including the SC) strategies must be aligned to and support the corporate strategy. The key levers used by SC management in its effort to support corporate strategy are: –Facilities –Inventory –Transportation –Information –Market Segmentation

Market Characterization and the role of Information Management in Contemporary SC’s To the extent that the customer demand is the main input signal that drives the entire set of operations in any SC, it is imperative that this input is properly understood, characterized and appropriately disseminated to the various interested parties. Understanding and characterizing the expected demand and the arising customer needs is primarily the task of the marketing department, and the relevant function is known as forecasting. The ability for effective forecasting depends on a number of factors like –the availability of relevant data, –the forecasting horizon, –the stability of the forecasting quantity and any inherent trends in it over time, –etc. As a result, forecasting can be based on either qualitative or quantitative techniques, with quantitative techniques being more demanding in their applicability requirements.

Market Characterization and the role of Information Management in Contemporary SC’s (cont.) Furthermore, quantitative techniques can be discriminated to –causal models, that seek to characterize functional dependencies between the forecasted quantity and other relevant indicator variables, and –time series-based models, that essentially seek to systematically extrapolate any detected trends in past observations of the forecasted quantity, into the future. Causal models can be built using techniques from (linear) regression. Time-series based models essentially use some sort of weighted average in order to compute an estimate of the mean value of the forecasted quantity from its part observations. The implementational details depend on the type of trends identified / expected in the data (level, linear growth, seasonalities, etc.) In addition, it is pertinent to characterize the variability in the forecasted quantity, by obtaining an estimate of the standard deviation of the relevant distribution(s). All of the aforementioned models provide formulae for obtaining (approximating) an estimate of this std. dev., by using the forecast errors.

Market Characterization and the role of Information Management in Contemporary SC’s (cont.) While the last (retailing) stages in a SC have direct experience of the market demand, more upstream stages in the SC must frequently rely on the information provided to them from the downstream stages in order to predict the expected demand and plan their activity appropriately. This type of interaction tends to distort the information provided to the upstream stages of the SC, since it tends to integrate in it the effects of erratic or intentional behavior from the downstream stages. In particular, upstream stages tend to observe a much more variable demand than the actual demand generated by the market; this effect is known as the “bullwhip effect”. Currently, there is a systematic effort among leading companies to identify and eliminate the reasons that tend to result in lack of coordination and the bullwhip effect in SC’s. At the same time, information technology is explored and promoted as an enabler of new business practices that can lead to enhanced SC coordination and efficiency.

Designing SC networks The problem of SC network design seeks to determine the number and configuration of the various facilities in any particular supply chain, in terms of their capacities and capabilities, and also their interaction in terms of material and information flow. The involved decisions are characterized as strategic, since they commit the organization for a substantial period of time (typically measured in years) while at the same time they define the organizational capability with respect to production and distribution. Typical characterizations of this class of problems seek to maximize profit or control total deployment and operational costs while ensuring some target service level(s), which quantify the organization responsiveness. The typical costs involved relate to facilities, inventories, transportation, and maybe other administrative costs like IT-infrastructure, etc. The detailed characterization of these problems is affected by a number of qualitative factors, including attributes of regional demand, production technologies and economies of scale and scope, tarrifs and tax incentives, available infrastructure, risks associated with economic (e.g., exchange rates), political and demand-influencing factors, the behavior of the competitors, etc.

Designing SC networks (cont.) From a mathematical / analytical standpoint, many of these problems can be represented as minimum cost network flow problems, and eventually characterized and solved (at a certain level of approximation) through linear and mixed integer programming formulations. Additional optimization models and techniques have been developed for particular problems, addressed under certain conditions/assumptions (e.g., the “center of gravity” model). Furthermore, there is a developing effort that seeks to systematically address and factor in the relevant decision making, the impact of the uncertainty underlying the various parameters of the considered problems. A popular approach tries to characterize the potential evolution of the system operation under the aforementioned uncertainties in a number of scenarios, compactly expressed in a decision tree, and use this representation for systematically evaluating the expected Net Present Value for various proposed solutions.

Transportation-related Concepts and Problems Transportation-related costs are one of the major types of cost experienced by contemporary SC’s. In general, there is a trade-off between transportation and facilities and inventory-related costs. This cost can be controlled by pertinently choosing the transportation mode, types and frequency of service, service providers, etc. From the transportation service provider’s standpoint, the quest is to maximize the potential profit through the effective utilization of the available resources / assets. Some typical problems underlying the effective deployment and operation of transportation services are as follows: –Shortest Path: Finding the minimum length / cost route between two points –Minimum Spanning Tree: Establish connectivity between a number of locations while minimizing the total cost. –Min-Max Path: Finding a route between two locations that minimizes the length of the involved route legs. –Traveling Salesman Tour: Find the minimum length tour visiting a number of locations. –Bin Packing: Minimize the number of (finite-capacity) containers required to ship a number of indivisible loads to a certain destination. –Vehicle Routing: Minimize the total travel cost for shipping a number of loads to a number of destinations, utilizing finite capacity vehicles.