Introduction
This blog post targets a technical yet practical question that might arise during product management interviews, particularly at a company like Google. With the explosive growth of digital content, managing storage efficiently is a significant challenge. We will address the question of how to reduce the total storage required by Google Photos, a popular image and video storage service offered by Google.
Detailed Guide on Framework Application
Picking the Right Framework
For tackling this question, we’ll employ the AARM (Assumptions, Analysis, Recommendations, Metrics) framework, also featured in ‘Decode and Conquer.’ This framework helps manage and present solutions to problems that are data-heavy and require analytical problem-solving.
Assumptions
Initiate with assumptions about user behavior and data usage. Hypothetically, let’s assume an average user saves 1,000 photos per year with an average photo size of 3MB.
Analysis
Analyze the current system and identify major contributors to storage bloat. These could be redundant backups, inefficient image compression, or unused media lurking in the users’ storage.
Recommendations
Suggest actionable solutions like:
– Advanced image and video compression algorithms to reduce file sizes without compromising quality.
– Introducing features that identify and suggest the removal of duplicate or blurry photos.
– Offering incentives to users who streamline their storage, such as additional features for active curation of their media.
– Implementing machine learning models to predict and recommend archival of seldom-accessed content.
Metrics
Define metrics to measure the success of the implemented changes. For storage, metrics could include average storage used per user, percentage reduction in duplicate files, or engagement with storage management features.
Fact-checks and Approximations
Use industry benchmarks for photo and video file sizes, average user behavior, and storage costs. While specifics may not be known, approximations based on typical usage patterns can inform potential strategies.
Tips for Effective Communication
In your interview answer, frame each solution with its impact on the user experience and potential cost savings. Also, indicate possible technical challenges and how they might be mitigated. Communication should be clear, and your reasoning backed by logical thought processes.
Conclusion
The AARM framework suits questions that depend on data analysis and offer candidates a structured methodology to propose well-thought-out solutions. Candidates should practice this analytical framework to become adept at handling technology-centric interview prompts and bolster their chances for success in a PM interview.