Decision Analysis

Decision Analysis

Introduction

This paper will be discussing and providing recommendations to decision analysis for the Shuzworld Company. As the operations consultant for Shuzworld, I will provide recommendations after analyzing the problems given in the task prompts, applying the appropriate decision analysis tool.

Task 1

In this task I will be recommending which method (i.e., using reconditioned equipment, purchasing new equipment in its Shanghai plant, or outsourcing to another manufacturing operation) Shuzworld should use for the manufacturing of its sneakers. For this task I will be using

Table for the Cost Volume Analysis

Cost Type

Recondition existing Equipment

New Equipment

Outsource to Other Company

Cost 1

Fixed

50000

200000

0

Cost 2

Variable

1000

500

3000



BREAKEVEN POINTS

Units

Dollars

Recondition existing Equipment

300

350000

Recondition existing Equipment

25

75000

new equipment vs. Outsource production

80

240000



Volume analysis @

1000

Total Fixed Costs

50000

200000

0

Total Variable Costs

1000000

500000

3000000

Total Costs

1050000

700000

3000000

The above table states that it will cost company $ 1,050,000 if they will produce their sneakers shoes with reconditioned existing equipment. It will cost them $ 3,000,000. Lastly it will cost them $ 700,000 if they use a new production machine. The table is also stating break even points with the comparison to other options that were available to the company.

Graph of Cost Volume Analysis

This graph states all the three possible options analysis. This analysis is done on the basis of cost volume analysis. Shuzworld for their sneakers product should

Recommendation

Analyzing the position of the company in all the three cases I will recommend Shuzworld to buy the new machine for the production of their new Sneakers product. It is because after analyzing the position it can be clearly stated that the by using new machine the company can produce its product in $ 700,000. This is the lowest cost for the production.

Task 2

In this task we will be developing a sales volume forecast using the least squares method and one other forecasting method.

Table for Smoothing Forecast Sales Analysis

Measure

Value

Error Measures

Bias (Mean Error)

8668.7

MAD (Mean Absolute Deviation)

8668.7

MSE (Mean Squared Error)

119379600

Standard Error (denom=n-2=6)

12616.37

MAPE (Mean Absolute Percent Error)

0.08

Forecast

next period

110804.9

This above table states forecasting of sales for the next period that is $ 110,804.9. Bias Mean error is $ 8,668.7. The smoothing exponential for this part of analysis used was 0.3. Following is the graph present which provides data and forecasted lines. There is little variability present in forecasting and real data.

Measure

Value

Error Measures

Bias (Mean Error)

7494.87

MAD (Mean Absolute Deviation)

7494.87

MSE (Mean Squared Error)

98544600

Standard Error (denom=n-2=6)

11462.67

MAPE (Mean Absolute Percent Error)

0.07

Forecast

next period

113983.6

This above table states forecasting of sales for the next period that is $ 113,983.6. Bias Mean error is $ 7,494.87. The smoothing exponential for this part of analysis used was 0.4. Following is the graph present which provides data and forecasted lines. There is little variability present in forecasting and real data.

Recommendations

From the above analysis it can be seen clearly that exponential smoothing 0.4 is providing more forecast for the sales. The error present is also less and it provides authentic results.

The emphasis or sales analysis in most supply chain management systems is more on operational reporting and management or sales, rather than on aiding sales ...