Value Added Analysis, Essay Example

A common issue in business is that it is difficult to predict the future demand of a product or service, which is necessary because the supply produced will have a direct impact on the profitability of the good or service. Therefore, it is important for the industry to take advantage of forecasting to predict supply and demand trends as relevant (Gilliland, 2011). A simple way that this could be done is by observing previous trends. If the demand for the product has been consistent for several years, there’s reasonable probability that this trend will continue. Likewise, if the product demand has been increasing steadily over the past several years, it will likely continue, and forecasting models can determine the extent of this growth. The type of data that would need to be collected in order to solve this problem includes the amount of products sold over time, profit over time, and the distribution of these sales. It may be the case that there are only positive demand trends in some localities, and this data would be able to pinpoint this to maximize profit.

In a journal article entitled “Statistical Quality Control and Routine Data Processing for Radioimmunoassays and Immunoradiometric Assays”, statistical quality control is described as a method that is useful for analyzing information from biological testing, although this has applications in many areas of industry as well (Rodbard, 1974). Statistical models are often used to fit biological data and the author describes quality control analysis as a necessary component of this approach. He compares multiple methods for graphical display and concludes that the degree of statistical quality control to analyze data is dependent on the particular application, but is nonetheless important.

References

Gilliland, M. (2011). Value Added Analysis. Analytics Magazine. Retrieved from http://www.analytics-magazine.org/july-august-2011/361-value-added-analysis-business-orecasting-effectiveness

Rodbard, D. (1974). Statistical Quality Control and Routine Data Processing for Radioimmunoassays and Immunoradiometric Assays. Clinical Chemistry, 20(10): 1255-1270.