Case Study: Yummy Pizza

Yummy Pizza Inc. is a small pizza chain in Southwestern Ontario. The company started with one shop in London and now has several stores in London and area (London, Woodstock, Tillsonburg, Ingersoll), Kitchener-Waterloo region (Kitchener, Waterloo, Cambridge and Guelph), and Hamilton area (Hamilton, Burlington, Oakville). Last year they introduced a Mediterranean Pizza that has had relative success in the market, particularly for its medium size. Because of its specialty ingredients this specialty pizza needs to stay in oven longer than the conventional pizzas do a nd ends up with less crunchy crust. The company has been evaluating the options for improving the quality of this pizza which is known in the market as Mid-Med.
On January 2, 2020 Kiyan Andalibi, the president of Yummy Pizza called his regional managers to his office to discuss the changes he had been considering in production of a specialty medium sized pizza the company had introduced to the market. “We can have our Mid-Med pizza made faster and crunchier if we buy this new oven. The problem is that the cost of acquiring this oven can only be justified if we sell more than 46,500 pizza a month! I am not sure if we should commit to this change, especially since we cannot increase the price!” said Kiyan. He asked his managers to review their operations and get back to him within a week because he has to finalize the purchase of the new ovens by January 15, 2020.
Sohila Louti, the manager of London and Area operations, delved into the sales numbers of the three regions in 2018 and summarized the regional sales by month as shown in Appendix A. Then she held meetings with the other two managers to examine their sales before reporting back to Kiyan. She also has called upon your group as consultant to help her analyze the sales data she has gathered.
Your group should submit an analytic report in Word format that includes the following:
1- A time series analysis that shows how the overall demand (for all three groups) changed over time during 2019.
2- Interpretation of the above time Series (what can be concluded from the above time series analysis).
3- Comparison of the time series of the three groups (where there differences in time series of the groups? If so how? What can be concluded?)
4- Estimate of January demand for each area using simple moving average method of the last three months.

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