BACKYARD PIZZA OVENS: MANUFACTURE OR OUTSOURCE?

According to Business Insider, May 6, 2023, "The trendiest thing that adds value to your home - and livens up your summer BBQ: a pizza oven." Thanks to rapid cooking, versatility, and ease, backyard pizza ovens are a growing trend with a twist on the classic barbecue experience.

Fresco produces large outdoor home pizza ovens (p-ovens) designed for the high-end backyard kitchens included as an alternate or addition to the traditional BBQ grill. For the past ten years, Fresco outsourced their manufacturing process to a manufacturer in China. Despite the global supply chain that Fresco has developed, they are considering if they should vertically integrate into manufacturing and produce the p-ovens themselves.

In the p-oven industry, most manufacturing has been taking place in Asian countries, where there is significant low-cost labor available to produce the products. However, many of these companies are looking to relocate to the Western hemisphere. As a result, Fresco is considering setting up their own in-house production facility in Mexico. However, they are not ruling out the option to continue to outsource manufacturing (in China).

Given their current supplier in China, they would not need to pay any fixed cost but would have to guarantee to purchase 35K units for $840 each.

If they decided to produce the p-ovens themselves in Mexico, they would have an estimated fixed cost of approximately $11 million dollars including mortgage, machinery, overhead and fixed labor costs. The unit cost to manufacture each p-oven would be $625.

The selling price of the Fresco p-ovens would be $1345 each. One of their main concerns is regarding demand. If demand is strong, the number of p-ovens they can sell is uniformly distributed between 25K and 55K. If demand is weak, the number of p-ovens they can sell is uniformly distributed between 10K and 30K. There is a 70% chance that demand will be strong.

If Fresco chooses to continue to outsource and the demand is greater than the 35K, they can only sell the 35K p-ovens that they purchased. If demand is less than the 35K p-ovens, they will only earn revenue on the amount demanded even though they must purchase the full 35K p-ovens from their vendor.

If Fresco chooses to manufacture the p-ovens themselves, they can produce an initial 15K p-ovens and then will have the option to run a second production run of anywhere between 0 and 40K additional p-ovens in response to market conditions. The timing of the second production run would be shortly after Fresco learns if the market will be weak or strong. Thus, the total quantity that Fresco can produce will vary between 15K and 55K p-ovens - that's a 15K minimum from the first production run plus anywhere from 0 to 40K units for the second run.

Once again, given that demand varies, if Fresco produces more p-ovens than the demand, it will only be able to collect revenue from the p-ovens sold and if the demand is greater than the number of p-ovens produced (after the second production run), Fresco can only sell the number of p-ovens produced.

Use this information, to advise Fresco on their decision. Prepare an Executive Summary report with appendices and include the following sections) that summarizes your findings and recommendations. Be sure to include the following in your report:

1. Case Synopsis (include a brief summary of the case and the business issue(s)being studied)
2. Methodology (including a discussion of what information was provided and how you used this information to analyze the problem)
   1. Organize the available data on cost, revenue, and probability estimates in a table.
   2. Set up a decision tree to model the scenario presented to Fresco. I want to see two versions of your decision tree.
      1. First, show the tree with the algebraic formulations as your payoffs before you run the simulations - see the examples in the lecture notes (e.g. from FOOZ lecture example = $250*MIN(D, Q) - $150000 - $130Q)
      2. Second (completed after step (c)), after running simulations and optimization, show the decision tree with your payoffs (average profit calculated from the four simulations). Show your solved decision tree.
   3. Use simulation to estimate the expected profit generated for each option under both weak and strong demand scenarios. HINT: for the simulations, use 600 samples each. You will have four worksheets with simulations - OUTSOURCE-WEAK; OUTSOURCE-STRONG; MANUFACTURE-WEAK; MANUFACTURE-STRONG) For the manufacturing option, use Optimization to calculate the optimal number of p-ovens to produce for both the weak and strong demand scenarios.

IMPORTANT NOTES: (1) You may either draw out the decision trees using the drawing tools in Word/PPT or you may use SilverDecisions. Be sure to differentiate between Decision Nodes and Chance (event) nodes and label all branches.

(2) Each of your simulations should be on separate Excel worksheets. All worksheets should be in one Excel file with clearly labeled tabs. To generate your simulations, use the Random Number Generator (instead of the RAND() function). Please use 2127 as the random seed. Please indicate the random seed used in both the comments for submission and your write-up.

1. Findings and Conclusions (include a summary of analysis results) Based on your analysis, respond to the following:
   1. Provide a recommendation for Fresco, including their decision to continue to outsource or vertically integrate the manufacturing. Included the expected return/cost for the decision based on your decision tree (and simulation and optimization values).
   2. SENSITIVITY ANALYSIS (Note: for each of these scenarios, you only need to show your revised solved decision trees - see (ii) above - or summarize the revised expected values in a Payoff Table.
      1. Scenario 1: Given the strong trend to date on the growth of backyard pizza ovens, there is a concern that there may be a slowdown in demand as more households may be reducing their discretionary spending so the likelihood of a strong market may be reduced to 40%, would this change your decision to OUTSOURCE or MANUFACTURE? If so, how?
      2. Scenario 2: On the other hand, with remote work families are able to spend more family time outdoors, the demand for backyard pizza ovens may continue to soar making the likelihood of a strong market 85%. Would this change your decision to OUTSOURCE or MANUFACTURE? If so, how?
2. Recommendations. For your management perspective, what other factors (not included in the model) need to be considered in making the recommendations? Do you agree with the decisions from your quantitative analysis? Why or why not? You could include a concise summary based on research on current trends with demand for outdoor backyard pizza ovens