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The Mercer Human Resource Consulting

Scenario Background:
A marketing company based out of New York City is doing well and is looking to expand internationally. The CEO and VP of Operations decide to enlist the help of a consulting firm that you work for, to help collect data and analyze market trends.

You work for Mercer Human Resources. The Mercer Human Resource Consulting website lists prices of certain items in selected cities around the world. They also report an overall cost-of-living index for each city compared to the costs of hundreds of items in New York City (NYC). For example, London at 88.33 is 11.67% less expensive than NYC.

More specifically, if you choose to explore the website further you will find a lot of fun and interesting data. You can explore the website more on your own after the course concludes.

https://mobilityexchange.mercer.com/Insights/ cost-of-living-rankings#rankings

In the Excel document, you will find the 2018 data for 17 cities in the data set Cost of Living. Included are the 2018 cost of living index, cost of a 3-bedroom apartment (per month), price of monthly transportation pass, price of a mid-range bottle of wine, price of a loaf of bread (1 lb.), the price of a gallon of milk and price for a 12 oz. cup of black coffee. All prices are in U.S. dollars.

You use this information to run a Multiple Linear Regression to predict Cost of living, along with calculating various descriptive statistics. This is given in the Excel output (that is, the MLR has already been calculated. Your task is to interpret the data).

Based on this information, in which city should you open a second office in? You must justify your answer. If you want to recommend 2 or 3 different cities and rank them based on the data and your findings, this is fine as well.

To help you make this decision here are some things to consider:

Based on the MLR output, what variable(s) is/are significant?
From the significant predictors, review the mean, median, min, max, Q1 and Q3 values?
It might be a good idea to compare these values to what the New York value is for that variable. Remember New York is the baseline as that is where headquarters are located.
Based on the descriptive statistics, for the significant predictors, what city has the best potential?
What city or cities fall are below the median?
What city or cities are in the upper 3rd quartile?

Full Answer Section

Analyzing Significant Predictors: We'll compare these significant predictors (apartment rent and transport pass) to New York City's costs (baseline) and analyze other descriptive statistics:

Variable	NYC Cost	Min	Q1 (25th percentile)	Median	Q3 (75th percentile)	Max
Monthly Apartment Rent	?	?	?	?	?	?
Monthly Transportation Pass	?	?	?	?	?	?

drive_spreadsheetExport to Sheets Finding the "Best Potential" City: Since we don't have the specific NYC costs and all the data points, a definitive answer isn't possible. However, we can identify promising cities based on the following criteria:

Cities with Lower Apartment Rent and Transportation Costs: These would likely have a lower overall cost of living based on the significant predictors. Look for cities with medians and Q3 values for rent and transport pass below NYC's values.
Cities Below the Median Cost of Living: Targeting cities below the median overall cost of living (compared to NYC) suggests potentially lower operational costs.

Prioritizing Based on Data:

Top Choices: Cities that meet both criteria 1 (lower rent & transport costs) and 2 (below median cost of living) would be the most attractive options.
Alternative Choices: If no city meets both criteria, consider cities excelling in criteria 1, especially if the cost of living index is still lower than NYC.

Additional Considerations:

Availability and Cost of Qualified Talent: While cost is crucial, factor in the availability and cost of hiring qualified marketing professionals in each location.
Market Potential: Consider the target market size and growth potential in each candidate city.

Conclusion: By analyzing the MLR output (significant predictors) and descriptive statistics (means, medians, quartiles) for key cost factors, you can identify cities with lower operational costs compared to NYC. However, remember to consider talent availability, market potential, and other factors before making a final decision.

Sample Answer

Based on the data provided and the concept of cost optimization for the marketing company, here's an analysis to recommend potential locations for the second office:

Significant Predictors from MLR Output:

Let's assume the MLR analysis reveals the following significant predictors for cost of living:

Cost of 3-bedroom apartment (per month)
Price of monthly transportation pass