QUESTION 7 (13 Marks)

Gunther Company Ltd. produces two types of machinery parts, W and G, both of which require the same raw material in their respective production processes. The following are the budgeted standard unit contribution margins for the two parts for the next production period of April 1 to June 30:

	Part W	Part G
Selling price	$72	$96
Raw materials @$16/kg.	$32	$16
Labour @ $5/hr.	5	15
Variable overhead @ $7/labour hr.	7	21
Total variable costs	$44	$52
Unit contribution margin	$28	$44

Mr. Gunther, the owner of the company, feels that only 1,500 kg. of raw material will be available for the next production period. He knows that the labour union will allow the Gunther Companys employees to work a total of 3,000 hours on these two processes during a three month production period before overtime rates must be paid. Also, Mr. Gunther has promised to produce and deliver 100 units of part G to one of its major customers by June 30.

Mr. Gunther has asked the company accountant to find the optimum production mix for the next production period given the material and part G production constraints. Overtime is to be avoided. The results calculated by the accountant, using linear programming techniques, are as follows:

Intersecting Constraints	Production Mix		Total Contribution
Part G and Material	700 W,	100 G	$24,000
Material and Labour	300 W,	900 G	48,000
Part W and Labour	0 W,	1,000 G	44,000
Part W and Part G	0 W,	100 G	4,000

Based on this analysis, the accountant has advised Mr. Gunther to produce 300 units of part W and 900 units of part G during the April 1 to June 30 production period.

REQUIRED:

1. Assuming that the accountants calculations are correct and that the labour unions prescribed overtime premium is $3 per hour, determine the marginal value of an additional labour hour. Is overtime advisable? Explain.

2. The actual results for the April 1 to June 20 production period were as follows:

	Part W	Part G
Units produced	280	960
Unit contribution margin	$23	$39

Calculate the contribution margin variances in as much detail as the data permit.