Flying Blind

Marty Cagan argues that many product teams still fly blind because they do not instrument their products to collect usage analytics, or collect so little that they cannot see how customers actually use features. He notes that strong teams have collected this data for years across web, mobile, desktop, on-premise, and hardware products, often silently and anonymized, and that it is their main tool for making products more valuable and usable. He describes a simple loop: decide what you need to know, instrument the product, then review reports, and he insists that every feature ship with instrumentation to verify it works. Without usage data, teams cannot back up decisions or confidently simplify products, and management rightly pushes back. The core advice is to treat this data as non-negotiable and work backward from that requirement.

01Key takeaways

• Instrument your product so you can see how it is actually used, rather than relying on assumptions.
• Decide what questions you need answered before choosing how to collect the data.
• Ship every feature with the monitoring needed to confirm it works and catch unintended consequences.
• Anonymize usage data so no personally identifiable information is collected.
• Use usage data to justify simplification and decisions to management instead of relying on theories.
• Treat analytics as a requirement from the start, then work backward to the best collection method.

02Key sections

Teams Flying Blind

Cagan observes that many product teams either lack analytics entirely or collect too little to understand real product usage. He contrasts this with strong teams for whom such data has become indispensable.

Collecting Data Across Product Types

Web tools are the easiest route, but good teams also instrument installed apps, on-premise software, and devices that report usage back. Some ask permission first, while many collect data silently.

Privacy and Anonymization

He stresses anonymizing usage data so nothing personally identifiable is captured, noting that companies get in trouble when they send raw data in a rush to market.

The Instrumentation Process

The workflow is to decide what to learn, instrument the product accordingly, then generate reports. Each new feature should ship with monitoring to confirm it works and reveal unintended effects.

Why It Matters for Simplification

Without knowing what is used and how, teams cannot justify removing features or defend decisions to management. Data is what makes simplification feasible.

03From the post

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Summary and takeaways written by PM Atlas; quotes are short excerpts. © the original author.