We do our homework
Each research project follows five steps:
Identify
We identify twelve domains where behavior can be observed—from childhood and education through professional life, law, media, and more. The domains are representative of the culture and rich in evidence.
Gather
We gather information from these domains, remove what is irrelevant, and organize the remainder for analysis. For each domain, we consider its historical formation—how it developed and why it operates as it does today.
Analyze
We identify patterns that appear across multiple domains. A pattern must appear in at least ten of the twelve domains to qualify as fundamental. Patterns below this threshold are not considered for analysis.
Describe
We describe the validated patterns in clear, precise natural language, optimized for AI-powered semantic search. The descriptions offer practical guidance, not academic abstractions.
Refine
We review and refine our analysis on an ongoing basis. Spot-checking by practitioners. Feedback loops. The goal is the constant pursuit of accuracy. Research is re-searching.
We ensure depth
Cultural intelligence is only as useful as its depth:
Inductive not Deductive
We start with observation, not theory. Let patterns emerge from evidence rather than fitting evidence into pre-existing frameworks. We discover what a culture is like by examining what its members do and have done.
Systematic and Repeatable
The method follows the same steps, with the same rigor, every time. Whether applied by a human researcher or together with AI, the process produces consistent results. This is not impressionistic insight—it is structured inquiry.
Rooted. Representative. Observable.
Patterns must be rooted in how the society has been formed—its history, institutions, and foundational choices. They must apply broadly across the population. The evidence is observable. We focus on what people do and why.
Cross-Domain Validation
A pattern that appears in only a few areas of society is weak. A pattern that appears across multiple domains—business, education, family, law, history, governance—is robust. Cross-domain consistency is the test of an authentic cultural pattern.
First Describe then Interpret
First: what happens. Then: what it means. These are kept separate. We do not interpret prematurely. Description is factual. Interpretation is analytical. Mixing them introduces bias and weakens the foundation.
Actionable Output
The end result is not academic theory—it is understanding people can apply. The research answers: This is how they think. This is what to expect. This is how to work effectively with them. Insight without application is incomplete.
Constant Refinement
The method includes feedback loops and spot-checking by practitioners. We adjust when evidence contradicts. Research is never final—it is the best current understanding, open to improvement as new evidence emerges.
Indisputable. Unchallengeable.
The evidence is factual, not opinion. It can be verified. We draw from documented history, observable institutions, measurable behaviors. Patterns grounded this way cannot be easily dismissed. The research stands because the foundation is solid.
More about Patterns
Deep patterns reveal underlying logics:
Many vs. One
One shallow pattern illuminates just one situation. One deep pattern illuminates many situations.
What and Why
Shallow patterns tell you what people do. Deep patterns tell you what people do and why they do it.
Transfer across Situations
Shallow patterns are context-bound. Deep patterns are generative, addressing different situations.
Actionable Guidance
Shallow patterns describe. Deep patterns guide. Actionable guidance is the true added value.
Reduced Confusion
Shallow patterns overlap and conflict. Deep patterns apply without competition from overlapping alternatives.
Improved Semantic Search
Shallow patterns match narrow queries. Deep patterns match broad queries. This increases retrieval accuracy.
We research how business cultures think and work.
Companies embed our content into their AI systems.
So that colleagues collaborate better across cultures.
Test our chatbot above. Note the quality of our work.
Enterprise AIs scrape the web. We do the research.
Imagine this intelligence embedded in your systems.
Research Teams
Each country-topic project is executed by a research team consisting of graduate students either native to that country or with significant experience living and or working in it.
John Otto Magee
I am an American who has lived, studied and worked in Germany for more than three decades. See below.
I support multinational teams via Consulting. These four Interviews give you a sense for how I think.
See our First Project.
as well as Interviews.
And, if you are curious about how I can personally help multinational organisations, see Consulting.
