Food Truck Forecaster Case Solution And Analysis, HBR Case Study Solution & Analysis of Harvard Case Studies

Question 1

What is the issue or core problem in the case?

Sally Fry, who is the owner of the Hamilton, Ontario based food truck, had just completed her first year of operations of her business. She had started the business in the year 2013 and it was now November 2014. The business had been profitable for the entire year and she had maximized her revenues by charging different prices per burger and driving to the various cities. The fresh ingredient prices also differed with respect to each of the city and so did the travel costs, as the distance in kilometres was different for each city.

Sally was not pondering that whether any sort of statistical analysis and analytics of the data would help her to maximize her revenues and optimize the profitability. She wanted a quantitative model that would help her to decide where to sell and what price to charge for her burgers in each city, that are London, Waterloo, Toronto and Hamilton. Therefore, the main issue in this case is to develop an automotive model for daily decision making of Sally. The data has been collected for the past entire year and now we need to formulate a quantitative model using the collected data.
Food Truck Forecaster Harvard Case Solution & Analysis

Question 2

Discuss what factors of the food truck industry make quantitative analysis valuable.

There are a number of the factors of the food truck industry that make quantitative analysis more valuable. First, the food costs for beef, buns etc different across the cities. For instance, Toronto had the highest food costs and London had the lowest food costs per burger. The travelling distance from Hamilton to each of the other three cities was also different with the highest time being taken to reach at the chosen point in London. However, Sally had to cover only 5 KM to reach at her lucrative spot in downtown Hamilton.

The parking rate also different in each of the city, while the parking rate was $ 0 in London as Sally got a free parking spot at Richmond Row with the help of her good friend. The prices also impacted on the profitability of the food truck business as high demand meant charging lower prices and low demand meant charging higher prices. Certain cities like Toronto had high demand for burgers as compared to other cities. The particular day of the week, whether it was a weekday or weekend also impacted on food truck business. Lastly, whether also impacted on the business and made quantitative analysis more valuable. The demand decreased as the precipitation and temperature increased. On the contrary, the demand increased if there was any foodie festival in any of the cities. Therefore, all of these factors made quantitative analysis valuable..............................

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