Using both high-low and regression

Reference no: EM131130017

Using Both High-Low and Regression

John Meeks Company is a medium-size manufacturing company with plants in three small mid-Atlantic towns. The company makes plastic parts for automobiles and trucks, primarily door panels, exterior trim, and related items. The parts have an average cost of $5 to $20. The company has a steady demand for its products from both domestic and foreign automakers and has experienced growth in sales averaging between 10 and 20 percent over the last 8 to 10 years.

Currently, management is reviewing the incidence of scrap and waste in the manufacturing process at one of its plants. Meeks defines scrap and waste as any defective unit that is rejected for lack of functionality or another aspect of quality. The plants have a number of different inspection points, and failure or rejection can occur at any inspection point. The number of defective units is listed in the following table; management estimates the cost of this waste in labor and materials is approximately $10 per unit.

An unfavorable trend appears to exist with regard to defects, and management has asked you to investi- gate and estimate the defective units in the coming months. A first step in your investigation is to identify the cost drivers of defective parts, to understand what causes them, and to provide a basis on which to esti- mate future defects. For this purpose, you have obtained these recent data on the units produced, the units shipped, and the cost of sales since these numbers are easily available and relatively reliable on a monthly basis:

	Units Produced(000s)	Cost of Sales(000s)	Units Shipped(000s)	DefectiveUnits
Jan 2009	55	$ 689	50	856
Feb	58	737	53	1,335
Mar	69	886	64	1,610
Apr	61	768	56	1,405
May	65	828	60	1,511
Jun	69	878	64	1,600
Jul	75	962	70	1,570
Aug	81	1,052	76	1,910
Sep	70	1,104	80	2,011
Oct	79	1,224	89	2,230
Nov	82	1,261	92	2,300
Dec	70	1,020	74	1,849
Jan 2010	67	850	62	1,549
Feb	72	916	67	1,669
Mar	85	1,107	80	2,012
Apr	75	968	70	1,756
May	81	1,037	76	1,889
Jun	85	1,103	80	1,650
Jul	92	1,208	87	2,187
Aug	100	1,310	95	2,387
Sep	91	1,380	101	2,514
Oct	101	1,536	111	2,787
Nov	105	1,580	115	2,310
Dec	88	1,270	92	2,311

Required Use the high-low method and regression analysis to estimate the defective units in the coming months and to determine which method provides the best fit for this purpose.

Reference no: EM131130017

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