01
Customer & Use Case Orientation
Who do we produce for, and what decisions do they make?
Define target groups, map their use cases, and understand the workflows that data must serve. The supreme discipline of data production.
→ Article 1The Data Production Framework
Five dimensions for data production strategy, whether you're running a traditional data company or building data operations at an AI lab.
02
Data Portfolio
What should we produce, and what should we stop?
Evaluate data types across strategic, financial, and production attractiveness. Manage the portfolio as a disciplined allocation, not a backlog.
03
Production Engine
How do we organize and produce at scale?
Team structure, production means, methods, AI-enabled tooling, content steering. Building the factory and running it.
04
Quality & Customer Signal
How do we measure quality and stay close to customers?
Quality frameworks, feedback loops, customer signal collection. Why you can't QA your way out of a production design problem.
05
Commercial Connection
What do we sell, and how do we get it to market?
Data vs. insights vs. software. Products, pricing, packaging, and the Sales collaboration.