Importance of Demand Forecasting in Todays Business Environment - Coursework Example

DEMAND FORECASTING Introduction Businesses need to predict how the demand for their goods and services is in the market. Demand forecasting enables businesses to obtain valuable information regarding the marketplaces in which they conduct their operations as well as the markets they intend to venture into. Demand forecasting activities are important to businesses because they enable organisations to align their logistics and supply chain management strategies with the changing situations of markets. For instance, by predicting where demand for a particular commodity is, companies can then make plans on how to reach those markets and supply them with the required goods or services. Demand forecasting also enables organisations to have an insight on the changes occurring in the markets in which they operate and thus adjust accordingly as the situation in the market changes. Against this background, this essay will evaluate the significance of demand forecasting in relation to today’s business dynamic environment and supply chain management operations. The essay will also discuss challenges and issues facing demand forecasting and present the benefits associated with the phenomenon. Importance of demand forecasting in today’s business environment The importance of demand forecasting in the present day’s business environment can be seen right from the definition of the concept. Demand forecasting can be defined as the process of predicting the likely demand for a service or a commodity based on past events as well as the current trends in the market (Jain & Khanna 2006, p. 162). This is to say that demand forecasting estimates the expected levels of demand at a given future date by taking into consideration the present and past behaviour sequence of related events. This makes it possible to approximate how, when, where and what quantity of goods or services will be required in the near future. According to Rosenfield (1994, p. 327), demand forecasting deals with projecting the demand of a product or service in the future, which is critical to effective logistics and supply chain management. This is because when the nature of demand for a certain product of service is known, an organisation is able to make arrangements for purchases of raw materials, production and offering of the finished product or service to the market or how to manage inventory. Demand forecasting is particularly important in today’s business environment because the business environment is relatively unpredictable. Since the primary goal of demand forecasting is to ensure that a business has the right product in the right position at the right time (Rosenfield 1994, p. 327), this helps businesses to deal with the issue of uncertainty regarding the demand for goods or services that are offered in the market. In this regard, demand forecasting is important in that it helps remove any inefficiency that may exist in the supply chain by ensuring that services or goods are availed where they are required at the right time. As well, predicting the future demand of a commodity or service involves quantification of the raw materials required, analysis of inventories of finished goods, determining the number of items that need to be transported, identifying the number of personnel to be hired, coming up with the number of plants to be set up, and determining the number of other purchases to be made (Chase, Jr 2013). This enables businesses to have the appropriate quantity of resources at any given time and hence avoid the negative consequences that would result from an oversupply or undersupply of resources. Additionally, in today’s globalised business environment, demand forecasting processes are vital because the operations involving obtaining raw materials or purchases from suppliers to offering the final product to the customer take time (Chase, Jr 2013) and may involve long distances, even across many countries. Thus, predicting when goods and services will be required enables manufacturers to plan their operations and avail the finished items when they are needed. Relevance of demand forecasting to supply chain management According to Knowledge Flow (2015), demand forecasting is an important concept in relation to the management of inventory and the supply chain. This is because as stated earlier, demand forecasts enable firms to estimate the quantity of services or products that customers need at a given time and thus be able to supply them accordingly. Supply chains usually comprise a number of firms with people working from various locations (Oosterhuis, Molleman & van der Vaart 2005, p. 287). The people involved in the supply chains have to make decisions regarding issues such as when to make purchases, the number of suppliers, number of plants to be used, inventory, distribution, transportation, and pricing among others. For any given business, findings of demand forecasts will be used in making decisions on how to deploy resources at various levels of the supply chain. As noted by Öztayşi and Sürer (2014, p. 245), demand forecasting is particularly important for the whole supply chain system since it affects all decisions and plans that are made by each of the firms that are involved in the supply chain. Decisions regarding the supply chain are made at three levels: the strategic level, the tactical level and the operational level. The strategic level involves setting up and managing the various processes in a supply chain (Arlbjørn et al. 2010, p. 33) in accordance with the results of demand forecasting activities. For instance, the purchasing department of an organisation can specify its goals and create differentiated strategies that will have to be met by suppliers. The decisions made at the strategic level are meant for the long-term and touch on issues such as modes of integration, production capacity, location, inventory and transport (Ilyas, Banwet & Shankar 2006, p. 56). It is at this level of decision-making that companies for instance make long-term decisions on when and where to produce their goods or source them depending on how and where they expect the demand for the goods over a period of time. For instance, Toyota adopted the just in time production philosophy to ensure that it produced only what was demanded in the market based on demand forecasts and thus reduced in-process inventory (Malakooti 2014, p. 267). This in turn helped reduce costs on areas such as space and managing workstations (Malakooti 2014, p. 267). The tactical level involves medium term decisions such as week by week or monthly demand forecasts, methods of distribution, production planning, transportation planning, and planning for material requirements (Ilyas et al. 2006, p. 56). For example, Dell makes orders for personal computer components when it anticipates that customers will make orders, and performs assembly of the components when customers make orders (Chopra & Meindl 2007, p. 187). This is an example of a strategy that ensures that products are made available when they are actually needed to guarantee sales. At the operational level, those involved make very short term decisions, generally on a day to day basis (Ilyas et al. 2006, p. 57). For instance, the buying assistant or material planner in an organisation can place orders for specific materials required in the organisation and indicate the delivery times, which in most cases will be short. The operational level basically involves executing processes that have been established at the higher levels of decision-making in accordance with the demand forecasts that are made. Challenges and issues in demand forecasting There are several issues and challenges related to demand forecasting. To start with, the demand for products or services is not at all times constant; it changes as a result of consumer behaviour as well as due to many other factors such as the contemporary fashion, the global and local economy, weather, duration of peak sales, seasons and many others (Rahman 2013, p. 90). Consequently, it is not always easy to match demand and supply in supply chain management (Radhakrishnan 2001, p. 4). For instance, demand variation at the retail store is propagated to the supplier and ultimately to the manufacturer. This implies that the impact of demand changes that occur at the customer level increases sharply towards the wholesaler, distributer, and is highest at the manufacturer facility (Rahman 2013, p. 90). Such an increase in variability in demand is known as the bullwhip effect. Demand forecasting is one of the factors that cause the bullwhip effect, the other factors being batch ordering, lead time, inflated orders and price fluctuation (Radhakrishnan 2001, p. 4). Wisner, Tan and Leong (2012, p. 137) also argue that managing demand is a challenging activity due to the difficulty in predicting future consumer needs correctly. This is despite the fact that in order to have a successful supply chain integration, suppliers need to be in a position to precisely forecast demand so as to produce and provide to the market the appropriate quantities demanded by consumers in a cost-effective and timely manner. What this means is that all players along the supply chain must find ways of matching demand and supply in order to achieve optimal levels of quality, cost as well as customer service and be able to compete effectively with other supply chains. Any problem that affects one party in the supply chain (for instance due to incorrect demand forecasting) is thus likely to be have corollaries all through the supply chain (Wisner et al. 2012, p. 137). Another issue relating to demand forecasting concerns availability of information that can be used for forecasting. According to Srivastava and Mock (2002, p. 286), conventional methods of forecasting – such as econometric modelling and time series analysis – require past data on the market in question or data from a closely related market. Hence, there is a challenge in making demand forecasts for new and innovative products or products whose use changes significantly over a short period of time. For instance, in the electronics industry today, products keep changing as consumers desire to upgrade to the newest and most advanced devices. Thus, many products are becoming obsolete at a fast rate; an example being CD players which have been rapidly replaced by MP3 players. It is generally difficult to precisely forecast how long the demand for such fast changing products will last before the products are replaced by other more ‘convenient’ products. Benefits/advantages of demand forecasting Despite the challenges related to demand forecasting, the phenomenon has several advantages. The first advantage of demand forecasting is that it offers an approximation of future demand and thus forms the foundation of planning and making viable business decisions (Wisner et al. 2012, p. 137). Even though it may not be possible to provide a precise estimate of future demand due to the uncertain nature of the future, demand forecasting helps businesses to obtain some information that is useful for planning and managing their logistics and supply chain operations. This helps improve customer service due to improved management and hence promotes customer retention. Demand forecasting also leads to increased collaboration since the information obtained in demand forecasts needs to be shared among all those involved in a supply chain (Chase, Jr 2013). As a result, managers have a better comprehension of what spurs profitability, resulting in better budget management and more efficient allocation of resources across the supply chain. Collaboration also enhances understanding of customers, products and the market. Another point is that demand forecasting helps align the interests of the internal stakeholders of an organisation as they collaborate and find solutions through marketing, sales, operations planning, finance and interactions with external stakeholders (Chase, Jr 2013). These relationships help foster strong network interaction, which is vital for dealing with the dynamic nature of the market environment. Conclusion In conclusion, demand forecasting helps organisations to plan and manage their logistics and supply chain operations more effectively through better allocation of resources that ensures that goods or services are available where and when they are needed by consumers. This helps businesses to make informed decisions regarding supply chain management at the strategic, tactical and operational levels. Demand forecasting is affected by issues and challenges such as the ever changing consumer demand for products and services, inability to precisely predict future consumer needs, and lack of information that can be used in forecasting the demand for some products and services. In spite of these challenges, the benefits of demand forecasting include helping in planning and making business decisions, increasing collaboration among players in a supply chain, and aligning the interests of internal and external stakeholders of an organisation. References Arlbjørn, JS, de Haas, H, Mikkelseń, OS & Zachariassen, F 2010, Supply chain management: sources for competitive advantages, Academica, Aarhus. Chase, Jr, CW 2013, Demand-driven forecasting: a structured approach to forecasting, 2nd edn, John Wiley & Sons, New York. Chopra, S & Meindl, P 2007, Supply chain management: strategy, planning, and operation, Pearson Prentice Hall, Upper Saddle River, NJ. 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