NOTE: Free essay sample provided on this page should be used for references or sample purposes only. The sample essay is available to anyone, so any direct quoting without mentioning the source will be considered plagiarism by schools, colleges and universities that use plagiarism detection software. To get a completely brand-new, plagiarism-free essay, please use our essay writing service.
One click instant price quote
Problems and Issues in Forecasting Forecasting has attract tremendous attention in business circle, and for very good reasons. Of, accurate forecasting directly translate into significant increase in run, decreases in expenses, or both. Costly mismatches of capacity to demand can often be avoided through dependable forecasting. Fortunately, a systematic approach to forecasting can be easily learned. Situations that depend upon a novel or dynamic factor such as new technology lend themselves well to qualitative forecasting. Qualitative forecasting methods include expert opinions and opinion polls.
More stable situations with established inputs and outputs are generally approached with quantitative forecasting techniques. Quantitative techniques include causal models and time series models. Causal models are based upon multiple regression or other econometric analyses. These are commonly used by economists but may be difficult and costly to apply. Time series models are often easier to use. They are very helpful when future patterns will probably be affected by the same factors that have applied in the past.
A time series is a set of numerical values collected over equally spaced time intervals. An example would be a record of the number of LASIK procedures performed each month for a series of 24 consecutive months. The multiplicative time series model can be used to create forecasts from time series data. In this model, a time series is assumed to be the product of four components. These components are trend (T), season (S), cycle (C), and irregular/ random (I). In equation form, the variable of interest Y = T S C I.
Trend is the general, steady tendency of the data to move up or down over time. Seasonality is the fluctuation of data in concert with a time horizon (this could be quarterly, monthly, or even -- as in the case of restaurant customers -- hourly). Cyclicality is the oscillation around the trend, often tied to economic expansion and recession. Stock prices cycle around their general upward trend over time. Irregularities are random events that cannot be predicted. It is simple to determine trend (T) after the depersonalized data set has been generated.
Graphically, trend (technically, linear trend) is the straight line that best matches the points in the depersonalized data set. Cycle and irregular effects are notoriously difficult to quantify. These effects can be estimated, if necessary, by dividing the depersonalized data (T C I) by the values shown on the trend line (T). In our example, the depersonalized values are close to the trend line and vary around the trend line without obvious cyclical ity. It is therefore safe in our example to ignore cycle. Irregular effects, because they cannot be predicted, are left out of the forecast as well.
We are now ready to make a forecast for a period, say middle 2003. Extension of the trend line to this period yields a value of 283 (see Figure 1). This value must then be multiplied by the seasonal index for middle season ([S. sub. middle] = 0. 69), yielding a forecast of 283 0. 69 = 195. To balance the customers' demands with the need for profitable growth, many companies have moved aggressively to improve supply chain management.
Their efforts reflect what are the seven most important steps in supply chain management. These steps can enhance revenue, control costs and asset utilization as well as customer satisfaction. The first step is to segment customers based on the service needs of distinct groups and adapt the supply chain to serve these segments profitably. Segmenting customers by their particular needs equips a company to develop a portfolio of services tailored to various segments. Surveys, interviews, and industry research have been the traditional tools for defining key segmentation criteria. Most companies have a significant untapped opportunity to better align their investment in a particular customer relationship with the return that customer generates.
To do so, companies must analyze the profitability of segments, plus the costs and benefits of alternate service packages, to ensure a reasonable return on their investment and the most profitable allocation of resources. To strike and sustain the appropriate balance between service and profitability, most companies will need to set priorities, sequencing the rollout of tailored programs to capitalize on existing capabilities and maximize customer impact For the second step one must customize the logistics network to properly serve your customer and remain profitable across your customer segments. In many industries, especially such commodity industries as fine paper, tailoring distribution assets to meet individual logistics requirements is a greater source of differentiation for a manufacturer than the actual products, which are largely undifferentiated. International Paper Co.
found radically different customer service demands in two key segments; large publishers with long lead times and small regional printers needing delivery within 24 hours. To serve both segments well and achieve profitable growth, the manufacturer designed a multi-level logistics network with three full-stocking distribution centers and 46 quick-response cross-docks, stocking only fast-moving items, located near the regional printers. (Kuglin) Return on assets and revenues improved substantially thanks to the new inventory deployment strategy, supported by outsourcing of management of the quick response centers and the transportation activities. The third step is to understand market signals and align demand planning accordingly across the supply chain, ensuring consistent forecasts and optimal resource allocation. Forecasting has historically proceeded very redundantly with multiple departments independently creating forecasts for the same products. Everyone using their own assumptions, measures, and level of detail. Many consult the marketplace only informally, and few involve their major suppliers in the process.
The functional orientation of many companies has just made things worse, allowing sales forecasts to envision growing demand while manufacturing second-guesses how much product the market actually wants. Excellent supply chain management calls for sales and operations planning that transcends company boundaries to involve every link of the supply chain from the supplier's supplier to the customer's customer in developing forecasts collaboratively and then maintaining the required capacity across the operations. (Riggs) Channel-wide S&OP can detect early warning signals of demand lurking in customer promotions, ordering patterns, and restocking algorithms and takes into account vendor and carrier capabilities, capacity, and constraints. The fourth step is to differentiate the product closer to the customer and speed conversion across the supply chain. Manufacturers have traditionally based production goals on projections of the demand for finished goods and have stockpiled inventory to offset forecasting errors. These manufacturers tend to view lead times in the system as fixed, with only a finite window of time in which to convert materials into products that meet customer requirements. While even such traditionalists can make progress in cutting costs through set-up reduction, cellular manufacturing, and just-in-time inventory methods, great potential remains in less traditional strategies such as mass customization.
For example, manufacturers striving to meet individual customer needs efficiently through strategies such as mass customization are discovering the value of postponement. By delaying product differentiation to the last possible moment and thus overcoming the problem The fifth step is to manage sources of supply strategically to reduce the total cost of owning materials and services. Determined to pay as low a price as possible for materials, manufacturers have not traditionally cultivated warm relationships with suppliers. Excellent supply chain management requires a more enlightened mindset While manufacturers should place high demands on suppliers, they should also realize that partners must share the goal of reducing costs across the supply chain in order to lower prices in the marketplace and enhance margins. This fact-based knowledge is the essential foundation for determining the best way of acquiring every kind of material and service the company buys. These managers need to build an information technology system that integrates capabilities of three essential terms.
For the short term, the system must be able to handle day-to-day transactions and electronic commerce across the supply chain and thus help align supply and demand by sharing information on orders and daily scheduling. From a mid-term perspective, the system must facilitate planning and decision-making, supporting the demand and shipment planning and master production scheduling needed to allocate resources efficiently. To add long-term value, the system must enable strategic analysis by providing tools, such as an integrated network model, that synthesize data for use in high-level "what-if" scenario planning to help managers evaluate plants, distribution centers, suppliers, and third-party service alternatives. Despite making huge investments in technology, few companies are acquiring this full complement of capabilities.
Today's enterprise wide systems remain enterprise-bound, unable to share across the supply chain the information that channel partners must have to achieve mutual success. The seventh step is to adopt channel-spanning performance measures to gauge collective success in reaching the customer effectively and efficiently. To answer the question, How are we doing? most companies look inward and apply any number of functionally oriented measures.
But excellent supply chain managers take a broader view, adopting measures that apply to every link in the supply chain and include both service and financial metrics. First, they measure service in terms of the perfect order; the order that arrives when promised, complete, priced and billed correctly, and undamaged. The perfect order not only spans the supply chain, as a progressive performance measure should, but also views performance from the proper perspective, that of the customer. Second, excellent supply chain managers determine their true profitability of service by identifying the actual costs and revenues of the activities required to serve an account, especially a key account.
For many, this amounts to a revelation, since traditional cost measures rely on corporate accounting systems that allocate overhead evenly across accounts. Such measures do not differentiate, for example, an account that requires a multi-functional account team, small daily shipments, or special packaging. Traditional accounting tends to mask the real costs of the supply chain focusing on cost type rather than the cost of activities and ignoring the degree of control anyone has over the cost drivers. The complexity of the supply chain can make it difficult to envision the whole, from end to end. But successful supply chain managers realize the need to invest time and effort up front in developing this total perspective and using it to inform a blueprint for change that maps linkages among initiatives and a well-thought-out implementation sequence.
This blueprint also must coordinate the change initiatives with ongoing day-to-day operations and must cross company boundaries. The blueprint requires rigorous assessment of the entire supply chain, from supplier relationships to internal operations to the marketplace, including customers, competitors, and the industry as a whole. Current practices must be ruthlessly weighed against best practices to determine the size of the gap to close. Thorough cost / benefit analysis lays the essential foundation for prioritizing and sequencing initiatives, establishing capital and people requirements, and getting a complete financial picture of the company's supply chain before, during, and after implementation. By simultaneously enhancing customer satisfaction and profitability, these seven steps of supply chain management can turn these once warring objectives into a formula for sustainable competitive advantage and the company will be able to reap the full rewards of an excellent supply chain management system. Bibliography: Armstrong, Scott.
Principles of Forecasting: A Handbook for Researchers and Practitioners. Boston, MA: Kluwer Academic Publishers. Lawrence D. Fredendall. Basics of supply chain management. St.
Lucie Press, Alexandria, Va. Boca Raton, FL: 2001. Fred A. Kuglin. Customer-centered supply chain management: a link-by-link guide. New York, 1998.
David A. Riggs. The executive's guide to supply management strategies: building supply chain thinking into all business processes. New York: 1998. David Frederick Ross. Competing through supply chain management: creating market-winning strategies through supply chain partnerships.
New York NY Chapman & Hall 1998. L. A. Smith, M.
Roulston and J. von Hardenberg, End-to-end ensemble forecasting: towards evaluating the economic value of an ensemble prediction system. In Nonlinear Dynamics and Statistics, ed. Alistair I. Mees, Boston: Birkhauser, 31 - 64 (2000).
D. Orwell, L. A. Smith, J. Barkmeijer and T. Palmer, Model error in forecasting.
Nonlinear Processes in Geophysics, preprint, 40 pp. (2001).
Free research essays on topics related to: end to end, mass customization, distribution centers, supply chain management, day to day
Research essay sample on Supply Chain Management End To End
