MANAGEMENT SCIENCE AND SYSTEMS

Management Science and Systems

Management Science and Systems

Draw your own cognitive map for improvements in forecasting organisational capability at the Italian cement company, with the goal “Enhancing forecasting accuracy, consistency and reactivity” at the top of the map. Explain your choice of constructs, with reference to the case-study or to other forecasting literature.

The new world of global competition dictates that business organisations must consistently improve their performance. The cement industry, highly regarded as the 'industry of industries', is facing intense competition in a rapidly changing business environment. As such, industry players must advance not only their products and services, but also, more importantly, their processes and capabilities. Improving processes and strengthening capabilities have highlighted as important criteria for organisations' survival and to this end, forecasting has recognized as a fundamental organisational capability for business planning and management. However, there is also an ongoing debate about the importance of forecasting in a rapidly changing environment. Forecasting proposed to be less important than adaptation as business organisations focus on production-to-order and waste reduction through continuous improvement of business processes (Mentzer, 2007, 475-495).

Moon et al showed that the accuracy of sales forecasts made by Lucent for 1997 product lines ranged from only 50% to 60%, which was far lower than the target of 85%. Forecasting errors increase stocks and work orders for the manufacturer and increase lead times needed for the planned order (Dix, 2009, 269-277).

Armstrong (2006) reported that, after Italian cement company implemented its i2 supply chain management system, errors in forecasting major inventory write-offs increased within nine months. In contrast, enhancing forecasting accuracy enhances consistency and reactivity and reduces production losses. Despite the enormous potential business benefit, improving forecasting accuracy is a continuing problem in most corporations. Forecasting accuracy refers to the consistency between a prediction and the actual outcome. Research on this subject has taken three main directions. One direction is the comparative study of accuracy in different forecasting methods. Another is the evaluation of contrast measures of forecast accuracy. A third direction is the analysis of the consequences of forecast accuracy. Although numerous studies have evaluated the methods used to enhance forecast accuracy, the effects of customer information quality and biological rhythms fit on forecast accuracy are still unclear. Studies indicate that the more precise the information presented, the more accurate the forecasts. Studies also indicate that evaluations of information quality tend to be contextual, information that is considered appropriate for one decision context may be inappropriate (Croxton, 2010, 116-133).

Present an explanation of each of the following types of forecast bias, and how they may be reduced, as if to a non-technical manager at the cement company: i) statistical bias, ii) optimism bias, iii) over-confidence bias.

Types of Forecast Bias

Statistical Bias

The statistical bias of a forecast is the extent to which the forecast can be expected to differ from what occurs. CBO's evaluation used the mean error to measure statistical bias. That statistic--the arithmetic average of all the forecast errors--is the simplest and most widely used measure of forecast ...