What problems are encountered in attempting to estimate demand? Carefully reference data and sources used and show clearly any calculations made.
Several reasons may cause that the efforts to estimate demand highly challenging. In this part, the challenge in estimating demand will be separated into two categories, namely, (a) problems faced in estimating current demand, and (b) issues faced in estimating future demand.
Problems Faced in Estimating Current Demand
There problems faced in estimating current demand are outlined as follow:
Data on the population are hardly available. Very often, the complete data on the demand (most probably measured by amount of products transacted at a particular point of time) are hardly available. For example, there is no way to capture the total amount of shirts sold around the world, or in a country at a particular point of time.
Forecasting errors. For large population, sampling techniques will be relied to estimate the demand level. However, such method is subjected to forecast errors (Fildes et. al., 2011). However, there are many issues to be taken care off in the sampling process. For example, researchers must control for possible bias, ensure randomness of the sampling process, obtaining data from the subject and design proper tools, methodologies or instruments to collect, interpret and analyze the data collected.
Existence of black market. Often, the demand for particular products, for example, Nike sport shoes can be hardly estimated, due to existence of black market in many regions around the world. Many of the transactions are done in black market, whereby no records are present to collect the demand related data for analysis purposes. In fact, it is also found that counterfeit products are becoming serious issues in recent years, in many of the merging countries (Norum et. al., 2011). All these will cause the estimation of current demand in the marketplace challenging.
Problems Faced in Estimating Future Demand
There problems faced in estimating future demand are outlined as follow:
Changes in consumer preferences. In the fast changing economy, consumers’ preferences can change very fast (Gwartney et. al., 2003). Trends rise and fade in a fast manner; as evidenced by the shorter and shorter product life cycle in the marketplace. Consumers’ behaviors are largely uncertain, and the consumer decision making process tend to be affected by behavioral or emotional issues. As such, to estimate the demand in the future can be challenging, as it is virtually impossible to know accurately how the consumers’ behaviors might change in the future.
Complicated forces are affecting the demand of goods. Many of the external factors that can affect demand level on the marketplace are hardly predictable. For example, the emergence of new substitute products (i.e., iPhone to replace traditional portable media players), the emergence of new technologies (Yannelis et. al., 2009), or the shift in consumers perceptions on certain products or services (e.g., consumers may demand more environmentally friendly products due to the issue of global warming).
External shocks may affect the demand in the future. In many instances, external shocks, such as natural disasters, accidents or wars can change the demand level for certain products or goods in the future significantly (McGuigan et. al., 2002). All these are hardly predictable, thereby causing the exercise to estimate demand in the future highly challenging.
Advertising and promotional activities will affect the demand level on the marketplace (Gwartney et. al., 2003). It cannot be denied that advertisement can have certain effects towards consumer behaviors in the marketplace. However, such effects are hardly quantified. The issues become more complicated some companies operating in a certain industry may launch new promotional activities (for example, price discount, free gifts, discounting coupon, buy 1 free 1, loyalty cards, loyalty points and many others) to entice customers. All of these are hardly predictable, and the impacts on market demand can be hardly calculated and analyzed. These cause that estimating demand level in the future highly complex and challenging.
References & Bibliography
Fildes, R., & Kingsman, B. (2011). Incorporating demand uncertainty and forecast error in supply chain planning models. The Journal of the Operational Research Society, 62(3), 483-500.
Gwartney, J. D., Stroup, R. L., Sobel, R. S., & Macpherson, D. A. (2003). Economics: private and public choice (10th Edition). Thomson South-Western.
McGuigan, J. R., Moyer, R. C., & Harris, F. H. (2002). Managerial economics: applications, strategy and tactics. Ohio: South-Western Thomson Learning.
Norum, P. S. & Cuno, A. (2011). Analysis of the demand for counterfeit goods. Journal of Fashion Marketing and Management, 15(1), 27-40.
Samuelson, P. A. & Nordhaus, W. D. (2005). Economics (18th Edition). Mc Graw Hill.
Silbiger, S. (2005). The 10-day MBA: a step-by-step guide to mastering the skills taught in top business schools. Piatkus.
Yannelis, D., Christopoulos, A., & Kalantzis, F. (2009). Estimating the demand for ADSL and ISDN services in Greece. Telecommunications Policy, 33(10/11), 621.