Every organization sits atop a mountain of information. Yet, in the crunch moments that decide new markets, major deals, or operational breakthroughs, only a rare sliver of expertise truly moves the revenue needle. Most of what we circulate inside a business is “stuff people know” but not the judgments or working methods that define outcomes.
We call that decisive slice “revenue-moving knowledge.” It’s not the full corpus of what your company knows. It’s the engine behind decisive management, a skilled sales force, building the right distribution channels, or knowing when and how to acquire a competitor. Each of these revenue-moving feats isn’t accidental; they’re governed by the subtle, expert knowledge embedded in your organization’s best minds and operational DNA.
The future belongs to organizations that can surface, circulate, and activate their unique, revenue-driving knowledge. The new mission is to engineer how knowledge gets codified and put to work at scale.
It’s easy to confuse three distinct abstractions: data, information, and knowledge. A classic paper, “Data, Information and Knowledge: Have We Got it Right?” (Boisot & Canals), explains:
You don’t win by having more data. You don’t even win by having more information. You win by surfacing the knowledge that actually drives competitive results.
This is why the distinction is critical. Business intelligence isn’t passive. Without activation, knowledge sits idle while the crucial insight that could have shifted outcomes never reaches the people or processes that need it.
Organizations often mistake “knowledge” for whatever they could write down and store. In reality, only about ~30% of what a company knows is explicit: documented, easily explained, and simple to transfer. But it’s the hidden ~70% – the tacit knowledge embedded in muscle memory and gut instinct – that sets top performers and transformative decisions apart.
“Experts are so automated and unconscious about what they do they can’t remember to tell you, even if they want to.”
—Dr. Richard Clark, Professor Emeritus, University of Southern California.
Standard training misses the critical diagnostic moves and pattern-matching that drives outsized business results. Cognitive Task Analysis (CTA) was long the gold standard but required heavy investment and facilitation out of reach for most organizations.
AI is closing this gap. Forbes reports Generative AI can automate roughly 60% of the cognitive task analysis cycle, scaling capture and transfer of the “hidden 70%” at a fraction of the cost and speed of old approaches. But that only works if the AI is engineered to surface, represent, and update living knowledge, not just churn out documents.
Unless organizations treat expert know-how as a critical asset, actively codifying and activating what now passes largely unwritten, they risk quietly bleeding competitive advantage each time an expert leaves or retires.
At Innovation Algebra, we engineer knowledge as a living, operational asset using a fundamentally different approach. We encode critical know-how using neurosymbolic, recursive AI. This lets us represent knowledge as modular, auditable building blocks, not just as static text or frozen processes.
Each block of knowledge in our system carries transparent, editable logic. Because our approach is symbolic and programmable (not locked up in the hidden weights of a large language model) it can be inspected and adjusted in real time. This brings two transformative advantages:
Because knowledge is modular, new expertise and best practices can be composed, remixed, and surfaced wherever the business needs them. When embedded into workflows, either human-led or fully autonomous, these living knowledge assets dissolve complexity. Orchestration that used to require teams of specialists becomes structured and even self-improving. The gap between vision and delivery narrows; applied know-how moves at the pace of change.
How do organizations turn living knowledge into measurable results? The answer is codifying, activating, and cycling critical know-how so that it shapes real decisions and drives outcomes. Consider the story of Bayer scaling field wisdom for a billion dollar business line.
What sets Bayer apart isn’t just amassing 117 billion data points, but translating years of expert know-how, field test results, and even failed experiments into an evolving knowledge moat. The platform they built on this foundation delivers a 60% productivity boost for over 1,500 agronomists and saves each of them four hours a week, according to CIO Amanda McClerren. These reclaimed hours translate directly to more time with customers and more revenue-moving action.
“Our field-facing agronomists are seeing about a 60% increase in productivity… saving about four hours a week that they don’t have to spend searching for all of this knowledge.”
—Amanda McClerren, CIO, Bayer Crop Science
By embedding living, expert knowledge in operations, Bayer reimagined the very nature of work turning lessons learned into a system that drives a $32 billion product pipeline and consistently accelerates new product delivery by up to two years. In knowledge work, it’s not about what you’ve collected; it’s about what you’ve made alive and available for action.
The organizations winning today aren’t those with the biggest data lakes or the most elaborate dashboards. They’re the ones that activate the knowledge that actually drives results. Revenue-moving knowledge is dynamic and essential; far more than trivia or reference material. It’s what makes your next deal possible, your team more adaptive, and your business fundamentally smarter, year after year.
At Innovation Algebra, we believe critical knowledge is a living asset. It isn’t something to be shelved or locked away. It must be surfaced, continually refined, and wired directly into the way people make decisions and take action. That’s knowledge engineering.
The pragmatic takeaway is: stop measuring organizational progress by how much you’ve stored; start measuring it by how rapidly and reliably your revenue-moving knowledge gets into play. Find it. Engineer it. Activate it. Because in the end, it’s not what you know; it’s what you know how to use that moves the business forward.
