Problem 1: You are an operations analyst working for a major movie theater chain. Currently, the company requires all employees in the concession stand to use a technique known as suggestive selling (e.g., "Would you like Red Vines with your order today?"). Employees are not given any guidelines as to what suggestion to make, so they typically pick their favorite food or candy. The company has asked you to come up with a system to find items that a given customer is likely to buy in order to improve the effectiveness of the suggestive selling process and increase profits. Using market basket analysis, you have discovered several associations that you believe will lead to improved suggestive selling accuracy. You are considering two main options for deployment: 1. Work with the point-of-sale software vendor to implement the suggestive selling algorithm into the software used by cashiers. As cashiers enter the customer's order, the algorithm will determine what additional item the customer is likely to buy, based on the items currently ordered. The item will be displayed to the cashier who can then choose to add the item to the current order or dismiss the prompt, depending on the customer's response. Naturally, the software vendor is demanding a hefty fee and promising a 6-12- month timeline for delivery of the software update. Changes to the algorithm down the road will require an additional fee and waiting period. 2. Choose a small number (e.g., 5-10) of the most effective rules and incorporate them into the training protocol. One of these rules would be a catch-all (i.e., "If no other rules apply, suggest Red Vines"). You estimate that it will take 2-4 weeks to decide on rules, develop training collateral (posters for the employee breakroom, reminder cards to stick on each cash register, etc.), and deliver training. Because this is a high turnover industry and training is constantly being delivered, the additional costs of delivering this training are negligible. In 100-250 words, describe what sort of analysis you would need to do to make an informed decision about what plan to implement. What data would you need to acquire? How would you acquire that data? How would you measure the success of the deployment? How would you determine when the model needs to be updated?

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Problem 1: You are an operations analyst working for a major movie theater chain. Currently, the company requires all employees in the concession stand to use a technique known as suggestive selling (e.g., "Would you like Red Vines with your order today?"). Employees are not given any guidelines as to what suggestion t