You work for Pergamon Alarm Ltd. (PAL), a manufacturer of commercial alarm systems that has recently expanded into the residential market. As an analyst in the controllers office, one of your responsibilities is to provide a supported estimate of the expected warranty costs for its new residential product AbodeShield. Sales of AbodeShield began in early 2019, and so experience data is now available across all PALs markets where customers have been using it for at least a year.

AbodeShield comes with a two year warranty. PALs warranty history with the commercial market suggest that the following factors will likely affect the warranty costs for AbodeShield:

• Costs of repairs to date (averaged for each region)
• Expected increases in repair costs:
  • based on component and labour cost trends provided by the trade association
  • based on PAL technician estimates of costs in the second year of the warranty
• Environmental factors such as average temperature and humidity, which can accelerate the normal wear-and-tear processes for the outdoor components of AbodeShield
• Regional crime statistics
• Customer ratings of product performance

You want to impress your boss by taking a big data approach to this project. You plan use predictive analytics to estimate the provision needed for the second year of the AbodeShield warranty. Youve talked this through with your sister, Stephanie, who is a bit of a computer geek, and sketched out an approach. Youve now gathered the data you and your sister discussed, and youre ready to create your model (see the attached excel document).

When you approached your boss with this idea, he was interested, but a bit skeptical. He suggested that you bring your model, some background information on Data analytics, and yourself to the senior management meeting on June 26. He wants you there to walk the senior management team through your approach. This is a great opportunity to make yourself visible to the senior team beyond the controller.

You decide to prepare for the meeting by doing the following:

Part A: Refresh/extend your knowledge of Data Analytics by completing the Data Analytics module including all embedded quizzes.

Part B: Use the information youve gathered and the approach you decided on with your sister (included in the attached 3340 DA Assignment Part B.xlsm file) to create your warranty cost prediction model and calculate the provision you estimate is required for the second year of the warranty.

Part C: Write a brief memo that describes three key challenges associated with using big data in general, and separately, the limitations of your warranty cost prediction model. There is no need to explain the model itself in your memo as you will be there to walk through the details verbally. [Please ensure your memo is organized and makes good use of subtitles.]

Required:

1. Complete the Wiley Plus quizzes through the link on the Data Analytics page of the course website.
2. Submit the following documents to the Dropbox:

• Excel document: your completed model and provision estimate per Part B
• Word document: your Part C memo