Production Forecasting Gregory C. Sause OPS71 March 11, 2013 Todd Myers Production Forecasting Riordan Manufacturing uses a just in time production method. This system suits their needs and allows the company to save money and regulate the production process. One mistake that can be costly in production is a stock out (Chase, Jacobs , & Aquilano, 2006); this affects the ability to meet demand and re-starting the production for a stock out can wind up costing more to manufacture per unit hurting profits.
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Similarly over-producing items can produce warehousing fees and cause instability in the factories workforce if the factory needs to shut down production for longer periods of time than planned. To avoid all of these issues accurate forecasting is essential to the future of the company. Riordan uses a time series analysis to forecast production needs. This theory holds that past production trends can be used to predict what will be needed in the future (Chase, Jacobs , & Aquilano, 2006).
While this is a proven method and can be reliable to make production leaner and more accurate the fluctuations in demand throughout the year must be accounted for. The need for fans can be constant in some regions but can be highly irregular in others due to seasonal needs. To keep the production forecasts in line with demand adding an adaptive exponential smoothing approach to production forecasts should increase the reliability of forecasts.
Using a smoothing approach with a Kalman filter has proven to be far more accurate than other conventional forecasting methodology (LEUNG, 2007). Creating a better knowledge of what the market will demand will be key to establishing a lean production system. Choosing the system for their non-customizable fan production is only the first step in creating a better more streamlined production process. Riordan must also choose the time period to study each year, collect reports on any production issues, and closely follow market trends (Lorette, 2013).
The market is a volatile place and with the proper involvement in sales and keeping demand at high levels the company should study only the past two fiscal years in the current forecast. This should also be the case with production issues. Delving any further into the past could invalidate the information collected by including data that is no longer relevant. With improved forecasting in place the next phases of improvement can be implemented. References Chase, R. B. , Jacobs , F. R. , & Aquilano, N.
J. (2006). Operations Management for Competitive Advantage. New York, NY: McGraw-Hill/Irwin. LEUNG, R. Q. (2007). Adaptive exponential smoothing versus conventional approaches for lumpy demand forecasting: case of production planning for a manufacturing line. International Journal of Production Research, 4937–4957. Lorette, K. (2013, March 2). Forecasting Tools Used for Production Planning. Retrieved from Chron. com: http://smallbusiness. chron. com/forecasting-tools-used-production-planning-4096. html
