Estimating the Cost of Street View Data Collection in Manhattan

Introduction

Preparing for FAANG product management interviews can be a daunting task. Aspiring product managers need to be equipped with the right frameworks and strategies to tackle the myriad of questions that can come their way. One particularly relevant aspect is being able to reason through data-driven questions efficiently. This blog post will focus on how to navigate a product interview question using a structured framework, as outlined in ‘Decode and Conquer: Answers to Product Management Interviews.’ The question we’ll explore is: How much would it cost for Google Maps to gather Street View data for all of Manhattan?

Detailed Guide on Framework Application

To approach this question, we can utilize the Cost-Based Pricing framework. This framework takes into account all direct and indirect costs associated with a project to determine a price point that ensures profitability while reflecting the value provided.

Step-by-Step Guide on Framework Application:

1. Break Down the Problem: Begin by segmenting the task into smaller, more manageable components. For Street View data collection, this includes the geographic area of Manhattan, equipment required, personnel, transportation, and data processing time.
2. Quantity Estimations: Research and estimate the length of roads in Manhattan, the number of cameras and vehicles needed, and the number of personnel to operate them.
3. Cost Estimations: Gather data on the cost of purchasing or leasing the required equipment, wages for personnel, vehicle operating costs, and overhead costs for data storage and processing.
4. Gather Comparative Costs: If possible, find out the costs incurred in previous similar projects or other cities to corroborate your estimates.
5. Include a Contingency: Factor in unexpected costs and overheads to make sure the estimate is realistic.

Assume we have the following hypothetical statistics:

• Manhattan has about 6,000 city blocks, translating to roughly 280 miles of road.
• Each Street View car equipped with a camera system can cover about 40 miles per day.
• Operating costs, including fuel, maintenance, and depreciation, average $100 per day per vehicle.
• Personnel costs (driver and data operator): $300 per day per vehicle.
• Data processing costs come to $500 per mile of road.

Based on these figures:

1. Total days required: 280 miles / 40 miles per day = 7 days
2. Vehicle operating costs: 7 days * $100/day = $700 per vehicle
3. Personnel costs: 7 days * $300/day = $2,100 per vehicle
4. Data processing costs: $500/mile * 280 miles = $140,000
5. Total costs per vehicle (without overhead): $700 + $2,100 = $2,800
6. Assuming one vehicle, total cost estimate (without overhead): $2,800 + $140,000 = $142,800

To finesse your figures, consider scalability discounts, the possibility of using multiple vehicles to reduce time, and fluctuating fuel costs.

Tips on Communicating Effectively:

• Be clear, concise, and logical in your explanation of the framework and its application.
• Maintain a confident demeanor even when approximating figures, but be open to feedback from the interviewer.
• Ensure that you walk through your calculations step by step and verify that the interviewer is following along.
• Summarize your findings and explain their implications for the business question at hand.

Conclusion

In summary, the Cost-Based Pricing framework allows you to dissect complex problems and generate comprehensive cost estimates. Applying a structured approach not only impresses interviewers with your analytical abilities but also demonstrates a thoughtful consideration of business operations. Remember to practice different scenarios and integrate real-world data when possible to strengthen your estimating skills. Good luck, and happy calculating!