The comparison between moving average and exponential smoothing methods: the role of forecasting in increasing profits in a manufacturing company
The primary purpose of this thesis is to compare the efficiency between the moving average and exponential smoothing methods. A further purpose is to investigate how forecasting affects productivity of business. The methodology is to collect the real secondary data from a specific industry operating in food industry. This data, will, then be analyzed using both methods above to compare the efficiency of each method through their accurateness. There are three findings. First of all, it is very risky for business to wait to see what happens and then take their chances without effective planning. Secondly, effective planning in both the short and long run helps business meet the demand for the company's products. Thirdly, good forecasts are an essential part of efficient manufacturing operations. In conclusion, effective forecasting will help the company increase its productivity.
B00077 | (wh) | Available |
No other version available