The iceberg metaphor is one of business’s greatest hits, a classic analogy used to remind us that what we see is rarely what we get. Across psychology, systems thinking, and now Generative AI (GenAI), it perfectly illustrates that valuable outcomes—the visible 10% tip—are utterly dependent on a vast, invisible foundation—the 90% mass below the waterline.
But when you’re a leader in an enterprise software business, the iceberg is no longer just a reminder; it’s the structure of your greatest risk. The visible business problem, the smooth-running Large Language Model (LLM), or the flash of insight on a dashboard? That’s the tip. The policies, the data systems, the culture, and the sheer volume of underlying data? That’s the mountain of ice that can sink your most ambitious projects.
From Freud’s Couch to the Data Lake
The metaphor’s journey is fascinating, proving its enduring relevance. Its origins lie not in data but in the human mind, in Sigmund Freud’s Model of the Psyche , representing the small, visible portion of consciousness versus the enormous repository of the unconscious—the buried emotions and instincts.
From there, it sailed into Systems Thinking, where it became a tool for problem-solving. Here, the visible business problem and observable patterns/trends are the tip, but solving them requires analysing the hidden foundation: the policies, processes, data systems, and underlying beliefs/culture. This holistic approach was a critical step in reminding managers that data-driven reports have fundamental limitations.
The adoption into the world of IT and data was a natural fit:
- Business Intelligence (2000s): The data warehouse of numerical data was the iceberg; the dashboards and reports were the tip.
- Big Data: The data lake, with its unstructured data, was the iceberg; the data science outcomes were the tip.
- GenAI Today: The LLM is the visible, seemingly intelligent tip, with the vast amounts of structured and unstructured data it was trained on serving as the immense, crucial, and often murky iceberg.
The Iceberg’s Perpetual Growth Spurt
The evolution of the metaphor in the context of analytics has two critical, and often overlooked, aspects that keep us on our toes:
1. The Iceberg is Always Getting Bigger: We’ve gone from the data used for a specific, narrow report to “all of the internet”. This sheer, exponential growth in the volume of foundational data introduces complexity and risk that dwarf the initial, simple data warehouse challenges.
2. We’re Extracting More Complex Ice: Historically, only simple numerical data was used. This evolved to include complex analytics on unstructured data. Now, with GenAI’s sophisticated processing, we are extracting complex relations, sentiment, and various sorts of bias —elements far closer to Freud’s original, hidden “unconscious” than any spreadsheet.
This brings us full circle. A model intended for psychology adapted to the objective field of IT, and now it’s becoming deeply relevant to psychology again. Why? Because GenAI’s quest is the imitation of the human brain —an AI-driven echo of the very mind the iceberg was first used to describe.
A Final Thought for Enterprise Leaders
In the race for a competitive edge, the focus is almost always on the shiny tip: the revolutionary new application, the AI-generated insight, or the cutting-edge dashboard. We, as leaders in the Go-To-Market and Professional Services space, must be the ones to anchor the conversation in the 90% below the surface.
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