Operation Strategy: The benefits of using a forecasting system

Length: 360 words

With businesses ever more dependent on streamlined and efficient processes for success, the role of forecasting has come to the fore. The first step in developing a forecasting system is Problem Definition. This is the most important step for it sets the agenda for the forecasting system. The scope, range of utility, accessibility and function of the forecasting system is outlined herein. Following this is Information Gathering, whereby the sources of data collection are identified and statistical tools are devised to analyze the data. Rich historical and archival data add credibility and soundness to the eventual forecasts. The next step is making a Preliminary Analysis of the forecasting methods and techniques. This involves experimentation and verification. The next step is Choosing Models, whereby complex mathematical concepts like regressions, exponents and neural networks are integrated into the forecasting system. The final is Evaluating and Fine Tuning the system so that they are aligned to the ultimate business goals of the organization. In the high competition atmosphere of modern businesses a quality forecasting system can make all the difference between success and failure. Through complex and sophisticated forecasting techniques, businesses can gain key strategic advantages in their

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operations.

Reference:

B. Chase, F.R. Jacobs, N.J.Aquilano, Operations Management for Competitive Advantage, 11th ed. McGraw-Hill 2007

With businesses ever more dependent on streamlined and efficient processes for success, the role of forecasting has come to the fore. The first step in developing a forecasting system is Problem Definition. This is the most important step for it sets the agenda for the forecasting system. The scope, range of utility, accessibility and function of the forecasting system is outlined herein. Following this is Information Gathering, whereby the sources of data collection are identified and statistical tools are devised to analyze the data. Rich historical and archival data add credibility and soundness to the eventual forecasts. The next step is making a Preliminary Analysis of the forecasting methods and techniques. This involves experimentation and verification. The next step is Choosing Models, whereby complex mathematical concepts like regressions, exponents and neural networks are integrated into the forecasting system. The final is Evaluating and Fine Tuning the system .

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