Productivity and Forecasting Productivity and Forecasting Productivity refers to “a measure of effective use of resources, usually expressed as the ratio of output to input. ” (Stevenson 56). It is a gauge to determine if a production is efficient and if the company is competitive. High productivity is not only important for the company but for the nation as well. When productivity is high, the productivity growth or the increase in productivity over a certain period will also increase. This in turn produces real income to business organizations that they can utilize in order to meet their commitments to shareholders and employees while being competitive in the market.
Real income also improves the buying power of the public, therefore escalates the living standards of the people and sustains the economic growth of the country (Stevenson 56-57). Service jobs have low productivity than manufacturing jobs because the former possesses a less organized setting and the workers are less skilled compared to the latter. In the manufacturing sector environment, factories produce tangible products then build communities that contribute to economic growth. On the other hand, the service sector gives less value to the economy and is susceptible to distractions, emotions and challenges beyond the superior’s control (Stevenson 60). A company can gain a competitive advantage by having higher productivity than its competitors have because of its lower production cost for its goods and services.
With this advantage, they have the ability to sell their products at lower prices than their competitors or maximize their profits by setting an equivalent price in the market (Stevenson 59). Benefits of Forecasting M&L Manufacturing weekly forecasting: Week Product 1 Moving Average Product 2 Naïve Forecast 1 50 40 2 54 38 40 3 57 41 38 4 60 54 46 41 5 64 57 42 46 6 67 60 41 42 7 90 64 41 41 8 76 74 47 41 9 79 78 42 47 10 82 82 43 42 11 85 79 42 43 12 87 82 49 42 13 92 85 43 49 14 96 88 44 43 15 92 44 Calculations: a.
Computed using Moving Average on Product 1: Get the average of the first 3 weeks’ data to get the following week’s forecast Sample: 50+54+57=161/3=54 (week 4 forecast); 54+57+60=171/3=57 (week 5 forecast); 57+60+64=181/3=60 (week 6 forecast); and so on. . b. Computed using Naïve Forecast on Product 2: Simply copy the previous data into the next week’s forecast Business organizations use various forecasting methods to evaluate potential results of the enterprise. It is responsible for providing important data that can be used in constructing decisions about the organization’s future. Hence, production strategies can be implemented properly when suitable forecasting methods are used to determine the impending outcomes for the business. Forecasting is an essential tool in planning effective strategies of the organization.
With this, managers and production heads can determine the shift of customer demands due to changes in the industry or shift in season among others, and thereby create informed decisions. In addition, it supports the costs and profits brought about by the increase of taxes, freight costs or production supplies. For instance, a formalized forecast can identify when to escalate the degree of production, the best time to propose inventory levels and when to stock up raw materials (Stevenson 112).
The methods used by organizations are influenced by the data presented and the business in which the party operates. It is also imperative that all affected areas or departments of a company come to an agreement on a common forecast to realize its success. Nonetheless, long-range planning in terms of products and services proposals should also include necessary information about production and workforce levels (Stevenson 75). Reference Stevenson, William J. (2012). Operations Management. 11th Ed.
McGraw-Hill: New York.