We capture what manuals can’t
The most important knowledge in your organization has never been written down. We have a method for making that knowledge visible. And codable.
Built on 40 years of decision science
Our methodology builds on Cognitive Task Analysis (CTA) — a family of interview and analysis techniques developed by Gary Klein, Beth Crandall, Robert Hoffman, and Laura Militello over four decades of research into expert decision-making.
CTA was originally designed to understand how fighter pilots, surgeons, firefighters, and nuclear power operators make critical decisions under uncertainty. Not through rules or checklists — through pattern recognition, situational awareness, and experience-based intuition.
We apply the same rigor to a new domain: how organizations make decisions — and how to code that decision-making into AI.
How we extract what can’t be Googled
1. Critical Decision Method Interviews
We don’t ask people what they think they do. We ask them to walk us through specific moments — actual decisions, real situations — step by step. This surfaces the invisible: the cues experts notice that novices miss, the mental models that guide judgment, the unwritten rules that actually govern behavior.
2. Scenario-Based Elicitation
We present realistic situations — drawn from your organization’s actual context — and ask how different people would handle them. The variations reveal where alignment exists, where it breaks down, and where tacit knowledge makes the difference.
3. Cross-Validation
We don’t take one person’s perspective as truth. Every insight is validated across multiple sources: other interviews, documented processes, observed behavior.
4. Narrative Coding
Instead of coding knowledge into databases, taxonomies, or rule sets, we code it into narrative — specifically, into a Living Book. Why? Because AI responds to narrative differently than it responds to rules. Rules create boundaries. Narrative creates understanding.
Our Living Books have been validated across logistics, education, public sector, and regulated industries. The format works because it captures how people think — not just what they decide.
Why rules don’t work — and narrative does
Values in context. “We put the customer first” means entirely different things at different organizations. Statistical models can’t distinguish between your “customer first” and Amazon’s.
Judgment under uncertainty. No amount of training data captures “we usually say yes to this, except when it involves that type of client in that phase of the project.”
Narrative reasoning. People think in stories, not rules. This type of reasoning is invisible to statistical models but central to human decision-making.
Our method captures all three. And our coding format — the Living Book — preserves the narrative logic that makes the knowledge usable.
Who does this work
Ola Hedin leads the knowledge extraction process. His background — sociologist, journalist, three decades of digitalization work — is uniquely suited: he understands how people talk about their work, how to extract the essential from complex narratives, and how technology transforms organizations.
Peter Yngen brings operational leadership and market perspective. He ensures that what we capture isn’t just academically interesting but operationally useful.
Together, they combine the human extraction capability that no AI platform can replicate with the business judgment to know what matters.
