Selecting computers for a company
Suppose you're trying to help a company (with hundreds of employees) determine which computers to purchase. The company has been able to pull utilization data by employee that classifies users into 3 bins, depending on how much they use their computer in their work:
- Low usage - spends a lot of time in meetings, checking email, doing people management
- Average usage - requires some compute power, with balanced mix of heads down/technical work along with a good amount of meetings/email writing
- High usage - power user, relies heavily on computer performance
Additionally, they've surveyed employees to collect the relative importance of the following variables describing a computer's performance:
- Price inverse - this metric was given to you by the company, with the directive that price should have a 25% weight in the purchase decision.
The results of the survey data can be found here.
Lastly, the company is looking to purchase a maximum of 3 different computer models, and have compiled the following list scoring their memory, processing, storage, and relative price. Each dimension is scored from 0-10, with 10 being the best.
Given this information, provide the company with a recommendation on which computers to purchase. Be sure to lay out the logic behind your recommendation and the assumptions/steps you took to arrive there. You can consider this more of an open-ended/case study question.
To help get you started, below is code (Python) to import the referenced datasets:
# Import libraries %matplotlib inline import pandas as pd import matplotlib.pyplot as plt import numpy as np # Import data employee_utilization = pd.read_csv('https://raw.githubusercontent.com/erood/interviewqs.com_code_snippets/master/Datasets/computer_case/employee_utilization.csv') computer_options = pd.read_csv('https://raw.githubusercontent.com/erood/interviewqs.com_code_snippets/master/Datasets/computer_case/computer_options.csv') survey_results = pd.read_csv('https://raw.githubusercontent.com/erood/interviewqs.com_code_snippets/master/Datasets/computer_case/survey_results.csv')
Our solution will lay out our assumptions/logic behind our recommendation as we would to a stakeholder at the company.
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