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Organizations would like to get a prognosis of the outcome when making decisions. Having a sense of how events will unfold allows the organization to make plans and required preparations for the future. The ability of forecasting creates the expectation. Forecasts are a key element of the decision-making process in organizations. A forecast analysis includes all important facts that must be considered. As a result, the company can rely on these forecasts when establishing strategy.
Once the forecast has been created, precision is critical. Accuracy aids the organization in obtaining dependable information. One of the measures taken to make sure accuracy and reliability of the prediction are by establishing the mean absolute deviation. According to Wallström (2009), the role of measuring deviation from the various possible outcomes cannot be downplayed because it helps reduce the occurrence of errors. It is a risk mitigating factor that organizations take to secure their investments from effects of poor outcomes. The mean absolute deviation aims at establishing the size and impact of the differences expected for the forecast.
According to Krajewski and Ritzman (1993), this method helps calculate the average values which could be used for comparison of movements over a period of time. It is a crucial tool in analyzing the impact of errors in specific individual items, but it does not work well with many items. Of the various methods available, mean absolute deviation is considered the most suitable method due to its ability to be easily understood and applied. As such, an organization will maximize mean absolute deviation by establishing errors in forecasts with few items or items spreading over a small period of time.
Krajewski, Lee &Ritzman, Larry. (1993). Operations management, strategy and analysis, Addison-Wesley, Reading, MA, 1993
Wallström, P. (2009). Evaluation of forecasting techniques and forecast errors: with focus on intermittent demand (Doctoral dissertation, Luleåtekniskauniversitet).
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