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Data Management	Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the information needs of an enterprise. Companies often keep raw information in online transaction processing (OLTP) systems, which track day-to-day operations. But OLTP systems aren’t well suited for answering strategic questions for a business. To answer those kinds of questions, a company needs an analysis system with the ability to perform ad hoc queries and create specialized reports. A data warehouse provides business users with a multidimensional view of the data they need to analyze business conditions. It is a database that collects business information from many sources in the enterprise, covering all aspects of the company’s processes, products and customers. The software designed for organizing data and providing the mechanism for storing, maintaining, and retrieving that data in a database is called a database management system (DBMS). The large amount of stored data has to be mined in order to find underlying relationships and patterns. The process is called data mining. Sources: http://www.dama.org/ http://www.computerworld.com/itresources/rchome/0,4167,KEY241,00.html http://www.apics.org/ (10th ed.) See: Information Technology
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Demand Management	The function of recognizing all demands for goods and services to support the market place. It involves prioritizing demand when supply is lacking. Proper demand management facilitates the planning and use of resources for profitable business results. Source: http://www.apics.org/ (10th ed.)
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Distribution Channel	The distribution route, from raw materials through consumption, along which products travel.
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Distribution Channel Design	The planned channels of inventory disbursement from one or more sources to field warehouses and ultimately to the customer. There are several levels in the distribution network structure. Source: APICS (8th edition)
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Facility Location	Location decisions are a basic determinant of profitability in international logistics. Decisions on where to manufacture, to assemble, to store, to transship and to consolidate can make the difference between profit and loss. Because of international differences in basic factor costs and because of exchange rate movements, location decisions are very important. Also, these decisions involve substantial involvement in fixed assets in the form of facilities and equipment. Location decisions, therefore, can have a continuing impact over time on the company’s financial and competitive position. As movement towards global manufacturing increases, organizations should consider location decisions through total cost analysis which includes activity related costs such as manufacturing, transportation and handling as well as inventory holding costs, tariffs, and taxes. Source: Christopher, M. (1998). Logistics and Supply Chain Management: Strategies for reducing cost and improving service, (2nd Ed.). New York: Prentice Hall.
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Forecasting	The business function that attempts to predict sales and use of products so they can be purchased or manufactured in appropriate quantities in advance. Source: http://www.apics.org/ (10th ed.)
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Forecast Error	The difference between actual demand and forecast demand, stated as an absolute value or as a percentage. E.g., average forecast error, forecast accuracy, mean absolute deviation, tracking signal. There are three ways to accommodate forecasting errors: One is to try to reduce the error through better forecasting. The second is to build more visibility and flexibility into the supply chain. And the third is to reduce the lead time over which forecasts are required. Source: http://www.apics.org/ (10th ed.)
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Forecasting Methods	Qualitative forecasting techniques An approach to forecasting that is based on intuitive or judgmental evaluation. It is used generally when data are scarce, not available, or no longer relevant. Common types of qualitative techniques include: personal insight, sales force estimates, panel consensus, market research, visionary forecasting, and the Delphi method. Examples include developing long-range projections and new product introduction. Quantitative forecasting technique An approach to forecasting where historical demand data is used to project future demand. Extrinsic and intrinsic techniques are typically used. Graphical forecasting methods The use of visual information to predict sales patterns typically involves plotting information in a graphical form. It is relatively easy to convert a spreadsheet into a graph that conveys the information visually. Trends and patterns of data are easier to spot, and extrapolation of previous demand can be used to predict future demands. Trend forecasting models Methods for forecasting sales data when a definite upward or downward pattern exists. Models include double exponential smoothing, regression, and triple smoothing. Source: http://www.apics.org/ (10th ed.)
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Forecast Sharing	A supply partnership between a buyer and supplier is based on mutual interdependency and respect and calls for information sharing between the involved parties. By sharing its demand forecast with the supplier, the buyer benefits in two ways: 1) the partner becomes familiar with the buyer’s needs, and 2) the buyer develops a dependable supply source. Forecast sharing allows the supplier to plan for and schedule production efficiently. Source: Dobler, D.W., & Burt, D.N. (1996). Purchasing and supply management. (6th ed.). New York: McGraw Hill.
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