Business Decision Making


1008GBS Business Decision Making

T1 2021



ASSIGNMENT Assignment 2 – Data Analysis Portfolio
DUE DATE Week 9 – 9am Friday 14/05/21
SUBMISSION via Learning@Griffith (as a PDF, using the template provided)
WEIGHTING This assignment is worth 40% of overall grade
FORMATTING Complete the assignment template provided, with 12pt font

Please convert your document to a PDF file before submitting to ensure the formatting does not change



For this assignment, you will analyse an organisation’s operational data, to provide insights that will inform future decisions.



  • Read the case study below.
  • Download the associated excel file containing case study data
  • Analyse the data
  • Using the assignment template, answer the questions at the end of the brief

CASE STUDY – Harley Davidson New York

Who wants to ride a Harley Davidson? 

It was winter in New York City and Asaf Jacobi’s Harley-Davidson dealership was selling an average of two motorcycles a week. It wasn’t enough.


Jacobi went for a long walk in Riverside Park and happened to bump into Or Shani, CEO of an AI (Artificial Intelligence) firm, Adgorithms. After discussing Jacobi’s sales woes, Shani suggested he try out Albert, Adgorithm’s AI-driven marketing platform. It works across digital channels like Facebook and Google to measure and autonomously optimise the outcomes of marketing campaigns. Jacobi decided he’d give Albert a one-weekend audition. That weekend Jacobi sold 15 motorcycles. It was almost twice his all-time summer weekend sales record of eight.


Naturally, Jacobi decided to trial Albert for three months to determine future growth opportunities and strategy. In addition, previously Jacobi’s dealership had only offered motorcycles for sale. So, at the start of the Albert trial, Jacobi introduced motorcycle gear (helmets, gloves, protective clothing & footwear) as an additional offering.


The impact on sales

The use of Albert had an immediate impact on operations. The dealership went from getting one qualified lead per day to 40. In the first month, 15% of those new leads were “lookalikes,” meaning that the people calling the dealership to set up a visit resembled previous high-value customers and therefore were more likely to make a purchase. By the third month, the dealership’s leads had increased 2930%, 50% of them lookalikes.


1008GBS Business Decision Making

T1 2021

Effectively, Jacobi had estimated that only 2% of New York City’s population were potential buyers, Albert revealed that his target market was larger – much larger – and began finding customers Jacobi didn’t even know existed. These included out-of-state buyers who were willing to purchase a motorcycle – and associated gear – through the dealer’s online shopping channel. This was an interesting development for Jacobi, given net margin (profit) on motorcycles is 15.7%, while net margin on gear is 57.5%.


What does the future hold?

At the end of the three-month trial, Jacobi had some major decisions to make. He has already set up a small call centre – with three employees – to handle all new business. He now has $100K to invest back into the business and wants to know whether he should use that to include a new product in his range. Jacobi decided to analyse the relevant data to guide his decision.




You have been hired by Jacobi to analyse the data and provide the necessary reports to help him decide which option will be best for the dealership. He has set out some key information that he requires:

  1. Over the three months, what is the total sales for the dealership, and how is this broken down across in-store and online sales? Provide a relevant chart with your answer clearly detailing the necessary information.
  2. What are the in-store and online customers spending, on average, for motorcycles? Choose a different chart (to that used in Q1) to visualise this information.
  3. What are the in-store and online customers spending, on average, for gear? Choose the best chart to visualise this information.
  4. With the extra profits generated from the new customers, Jacobi is considering expanding his product range. He is interested in stocking a new type of motorcycle headset camera. To fit with current business plans, the new product would have to generate a minimum of 37.5% margin to be worthwhile. With that in mind, he hypothesises that customers will be willing to pay at least $350 for this product, which is the minimum sale price for it to be viable at the specified margin.


To test if his belief is true, Jacobi hires a market researcher (you) to determine how much customers may be willing to pay for this product. You collect data from a sample of 100 motorcycle enthusiasts, all of whom resemble Jacobi’s usual clientele, and determine that the average amount people are willing to pay is $364, with a standard deviation of $35.


Using this information, you conduct a hypothesis test at a 5% level of significance to check whether Jacobi’s belief is justified and to help him decide whether to stock this product. In your answer, include the relevant table from the hypothesis testing input-output excel file in module 7.2 and state clearly what process and evidence you are using from the data to support your suggestion.

(Note: you do not need to do manual formula calculations, please use the excel worksheet provided in the modules)