# Bay Area Bakery Company Case Study EMIS 7300 February 24, 2006 - PowerPoint PPT Presentation

Bay Area Bakery Company Case Study EMIS 7300 February 24, 2006

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Bay Area Bakery Company Case Study EMIS 7300 February 24, 2006

## Bay Area Bakery Company Case Study EMIS 7300 February 24, 2006

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1. Bay Area Bakery Company Case Study EMIS 7300 February 24, 2006 Nancy Anderson Bill Holladay Jeanna Roti Alice D. Walker

2. Question 1 • As a manager of transportation and customer service for Bay Area Bakery Company, should you agree with the proposal to build a new baking facility in San Jose?

3. Formulation • Variables • Let Xij represent the Major Market Area i (i= 1-11) and the Bakery Plant Locations j (j=1-7)

4. Formulation cont. • Minimize Total Costs = Production Costs + Baking Costs + Transportation Costs Model 1 – Without San Jose

5. Formulation cont. Model 1 – Without San Jose

6. Formulation cont. • Minimize Total Costs = Production Costs + Baking Costs + Transportation Costs Model 2 – With San Jose

7. Formulation cont. Model 2 – With San Jose

8. Solution • No. We do not agree to the proposal to build a new baking facility in San Jose. • Optimal solution with San Jose is \$99,108/day. • Optimal solution without San Jose is \$99,770/day. • The company only saves \$662/day if the new San Jose plant is built. (\$241,630 a year). • It would take the company approximately 16.5 years to pay off the \$4 million it costs to build the San Jose plant not including interest.

9. Solution cont. • Production costs are included after all other costs have been considered. • Inflation is not considered. • Future building costs may be considered if a new San Jose facility is built.

10. Question 2 • If you do not agree with the proposal, what action would you recommend for consideration by other members of the company’s top management group? • Is the current distribution pattern optimal?

11. Solution • We do not agree with the proposal, since the current distribution is not optimal. Without the new San Jose facility, the optimal solution is \$99,770. • Currently, the company is spending a total of \$103,270 in daily costs (\$95,700 in production costs and \$7,570 in transportation costs). • If the company restructures the transportation and production system, they can save \$3,500 per day. (Difference between \$103,270 and \$99,770).

12. Question 3 • If we project similar market growth for 10 years, what effect will this have on the decision about whether and when to build a new plant?

13. Market Growth *Assumes Linear Growth

14. Formulation • Using the demand forecasted in the previous table, we substituted it in the demand constraint in LINDO for each of the 10 years to determine whether / when it would be feasible to build a new plant

15. 10 Year Output

16. 10 Year Delta

17. Solution • We find these numbers using the growth rates in the previous table. • Analyzing the chart found on the previous slide, it appears that a new plant should be built in the year 2011 to satisfy the company’s demand. • It will take the company approximately 5.68 years to recover the total cost to build the San Jose plant.

18. Question 4 • What additional factors would have to be taken into consideration before reaching a final decision in this matter?

19. Solution • Additional factors to consider: • Maintenance Costs • Land Costs • Construction Costs • Labor Costs • Equipment Costs • Property Taxes