The Importance of Forecasting on Sales Management Decision Making

The Importance of Forecasting on Sales Management Decision Making Introduction In recent times, the business environment has increasingly become more unpredictable. This has made it very important for organizations across the globe to become vigilant when it comes to the issue of forecasting. In fact, for any organization to be successful in today’s business world, its methods of predicting the future in the key areas of its main business has to be improved continually. Otherwise, it faces the threat of becoming obsolete. Forecasting is therefore, a tool to be highly appreciated by the businesspersons of this century.Advertising We will write a custom term paper sample on The Importance of Forecasting on Sales Management Decision Making specifically for you for only $16.05 $11/page Learn More Forecasting is therefore the process of estimating or predicting the future outcome of different business aspects by use of historical data. These business aspects include; sales, revenue, market share, profits, expenses and ma ny more. Forecasting is formed from two words, â€Å"fore†: Al Etisal distribution co. is one of the famous food and consumer goods Distribution Company in Baghdad. They have a wider range of products. Prince ice cream is one of their products that they start selling since 2009. Sales have a steady growth and its seasons have a significant impact on the ice cream sales. Management expects total sales for 2012 to be 3200.Advertising Looking for term paper on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Price ice cream sales unit management is required to set their forecast for 2012. They should find the best way in estimating the demand for the ice cream. Below are the historical sales data for Prince ice cream for the last three years The above example is highly affected by seasons and therefore the sales forecasts have to incorporate the seasons in their formulation. It is also an example of a quantitative problem. Therefore, time series is applicable in this problem specifically trend projection and by use of a seasonality index (Agee,258). Month Sales by Case 2009 Sales by Case 2010 Sales by Case 2011 average sale for the three years average monthly demand seasonal index sales forecasts2012 Jan 30 33 42 35 186 0.188 50 Feb 28 32 49 36 186 0.196 52 Mar 35 47 55 46 186 0.246 66 Apr 55 67 90 71 186 0.380 101 May 194 180 209 194 186 1.046 279 Jun 290 280 376 315 186 1.698 453 Jul 459 504 703 555 186 2.990 797 Aug 350 490 543 461 186 2.482 662 Sep 189 227 290 2 35 186 1.267 338 Oct 76 142 188 135 186 0.729 194 Nov 62 109 97 89 186 0.481 128 Dec 42 56 68 55 186 0.298 79 total average sales 2229 total expected sales= 3200 Average monthly sales = total average sales/ 12 months= 2229/12 =186 Seasonal index = average 3 years sales/ average monthly sales Causal models These models employ the use regression models to forecast sales. They come up with a list of variables that have effect on the sales of the product in question and through regression; they plot the various possibilities and therefore come up with reliable forecasts. Qualitative models Delphi method uses the views of various professionals or experts in the field who analyse the situation and provide their professional views. Normally, the group of experts includes; key decision makers, staff, and the respondents. The staff and respondents provide assistance based on their areas of expertise to the decision makers, who in turn come up with the forecas ts. Jury of executive methods uses the opinions of a jury made up of high-level managers and key decision makers to make forecasts. The group may however receive support from other technical professionals who provide background information to assist in decision-making. Other qualitative methods include; sales force composite and consumer market survey. The latter uses consumer opinions while the former employs the opinions of the salespersons to come up with sales forecasts (Pinney,56). Conclusion In summary, sales forecasting is an important ingredient to success in the current and future business world. Therefore, management has to put emphasis on it to reap the benefits tied to the application of these tools. Management has to keep improving their approach to this process to remain relevant. Agee, Marvin H. Quantitative Analysis for Management Decisions. London: Prentice Hall, 2001. Anderson, David R and Dennis Sweeny. Quantitative Methods for Business. Chicago: South-Western Co llege, 2009. Hiller, Fredrick S and Mark S Hiller. Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets. London: McGraw-Hill Higher Education, 2010. Pinney, William E. Management Science: An Introduction to Quantitative Analysis for Management. Toronto: Harpercollins College , 2000. Render, Barry, Ralph M Stair and Michael E Hanna. Quantitative Analysis for Management. London: Prentice Hall, 2011. Taylor, Bernard R. Introduction to Management Science. London: Prentice Hall, 2009.