Data Analysis for Business Decision Making - Assignment Example

Topic: Data Analysis for Business Decision Making Task a. The contribution of the company will obtained from the calculations below. Contribution will be determined by subtracting total variable cost from the selling price. b) Definition of decision variables. One of the decision variables we will use will be contribution margin; contribution margin is difference between the selling price per unit and the total variable costs. The second decision variable will be the labor cost where in this case we have a limiting factor the test devices hours. The objective function will be to maximize the contribution per unit obtained from the overall production, this leads to optimization of the firm profits. Therefore, the contribution which is equal to selling price less the total variable costs of each peripheral will be multiplied by optimal number that will maximize the firm profit. Therefore, the objective function will be; Maxmize; 156.82A + 156.10B + 250.87C + 167.60D + 290.78E + 274.22F Where, A- Number of Internal modem B- Number of External modem C- Number of Circuit board D- Number of CD drive E- Number of Hard disk drive F- Number of Memory board The constrains in this case refers to the limiting factor where the test devices hours available for every peripheral in this case there are only 150 hours available for test device one, 130 hours for test device two, 110 hours for test device three, 102 hours for test device four in one week. The constrains in this case limit the number or peripheral that can be produced. The constrains in this case will be, 150 =224. After using the excel solver the following constrains were found to be binding chocolate, sugar and fat. While calorie was not binding, thus this constrain has a zero shadow since there is no additional contribution derived from application of the resources since these resource is available in abundant. For the other three constrain if the management decides to engage more resources then this would imply, if the management seeks additional resources then these action would result to an decrease in contribution by 0.0039 for any additional resource of chocolate engaged, 0.0067 for sugar, 0.028 for fat. From the sensitivity analysis it can be observed that the level of sugar, chocolate, calorie and fat can be reduced by 79.82,165, 1x1030,68.49 respectively without affecting the objection function. While constrain R.H side that is 550, 165,280 and 224 for daily calorie intake, daily chocolate, daily sugar intake and daily fat intake respectively represent the limiting value of the constrain. Works Cited Jensen, P., & Bard, J. (2003). Operations research:models and methods, Volume 1. New Jersey: Wiley. Read More