A Fashion company prepares its forecast by taking into account data about past sales, feedback from distribution channels, qualitative assessments from field sales managers, and macroeconomic data. Theres been incredible pressure on managers to keep financial performance up and to increase the sales revenues. This pressure, among other reasons, may cause manufacturing company executives to make bold projections about future sales without using the demand forecast generated from the bottom up. When the company realizes this disparity between the initial projection and the forecast, the forecast is changed to reflect the projections made by the companys officers, negating its accuracy. You have been hired to help in correcting the situation. The following data are collected to assist your team in the project and the objective of the project is to figure the following:

REQ 1:Forecasted demand for 3 types of products the company sell and use for month 13.

The company has 3 types of products in warehouses related to the production line under analysis. 1. Fabrics (the raw material for producing the skirts) 2. Skirts (the final product) 3. Belts (purchased from the supplier directly to be used in styling the skirts) You are given the actual quantities for each product. Months Actual data for Actual data for Skirts Actual data for Fabrics used sold purchase belts 1 15,000 50,000 30,000 15,200 50,100 29,000 16,000 60,070 29,500 16,500 60,100 31,000 16,200 60,000 27,000 16,700 71,000 28,000 17,550 60,900 30,000 8 18,000 50,500 30,300 9 17,700 60,110 26,400 10 18,800 70,500 25,700 11 17,650 50,450 24,800 12 18,220 70,000 26,000 **Based on the past accuracy, the company has an error fraction of 0.60 and in smoothing technique you can use 1st month only predicted sales as 1st actual sales data. Weeks Company's Sales forecast 1 13,000 13,000 14,000 15,000 18,000 13,000 13,000 13,000 2 3456700 23456700 8 The company has 3 types of products in warehouses related to the production line under analysis. 1. Fabrics (the raw material for producing the skirts) 2. Skirts (the final product) 3. Belts (purchased from the supplier directly to be used in styling the skirts) You are given the actual quantities for each product. Months Actual data for Actual data for Skirts Actual data for Fabrics used sold purchase belts 1 15,000 50,000 30,000 15,200 50,100 29,000 16,000 60,070 29,500 16,500 60,100 31,000 16,200 60,000 27,000 16,700 71,000 28,000 17,550 60,900 30,000 8 18,000 50,500 30,300 9 17,700 60,110 26,400 10 18,800 70,500 25,700 11 17,650 50,450 24,800 12 18,220 70,000 26,000 **Based on the past accuracy, the company has an error fraction of 0.60 and in smoothing technique you can use 1st month only predicted sales as 1st actual sales data. Weeks Company's Sales forecast 1 13,000 13,000 14,000 15,000 18,000 13,000 13,000 13,000 2 3456700 23456700 8