Briefing #27: The New Way to Think About "Big Data"
Just collecting massive amounts of data is no longer enough.
Note: This briefing was originally published on LinkedIn on February 6, 2026. It has been migrated to our new home on Substack to create a complete archive. Multi-format features like video and audio commentary are available for all new briefings published from April 2026 onwards.
For the past decade, one of the most powerful concepts in business strategy has been the “Data Flywheel.” Pioneered by companies like Amazon, the logic was simple and powerful: a better product attracts more users, who generate more data, which is used to make the product even better. The company with the most data wins.
That era is over.
In the age of generative AI, the value of raw data is collapsing. The Internet is being flooded with low-quality, unreliable, AI-generated “slop.” AI models trained on this contaminated data are beginning to degrade, a process researchers call “model collapse.”
Simply having “more” data is no longer an advantage. In fact, it can be a liability if the quality is poor. The strategic high ground has shifted. The new moat isn’t built on having the most data. It’s being built on having the best process for creating proprietary data.
The last generation of “Big Data”and the “Data Flywheel” is giving rise to a new, more powerful model: the Judgment Flywheel.
If the old Data Flywheel was a giant vacuum cleaner, sucking up all available data, the Judgment Flywheel is a refinery. It takes crude, generic inputs (like an AI’s first-pass analysis) and uses a deliberate, human-centric process to refine them into high-grade, high-signal intelligence.
Here’s how it works:
AI Output: An AI agent makes a first-pass decision (e.g., flags a transaction). This is the crude input.
Human Judgment: A human expert reviews the decision and, if they override it, provides the critical “why.” This is the refining process.
Captured Insight: That “why” — the expert’s judgment — is captured as a structured, proprietary data point. This is the high-grade fuel.
Smarter AI: This new, high-quality data is fed back into your AI models, making them smarter and more contextually aware than any generic system.
The cycle repeats, with each turn making your entire system more intelligent and more aligned with the unique realities of your business. This is what creates a true, unassailable competitive advantage. The winner is no longer the company with the biggest data lake, but the one with the most effective intelligence refinery.