Evidence before intuition.
The Counter Case brings together different ways of thinking to study business decision-making — from human behavior to numbers, from institutions to strategy. One standard, one question: what does the evidence actually say?
Matanat Talibzada
Conceived, architected, and built The Counter Case from the ground up — spanning product, UI/UX, full-stack engineering, research methodology, and production infrastructure.
Senior Vice President of Moving It Three Pixels to the Left.
Six people, one evidence standard.
From policy to psychology to raw numbers — every case gets looked at from more than one angle before it's published.
Researches regulatory and governance dimensions of business decisions, analyzing primary sources, competing perspectives, and institutional constraints for evidence-based case studies.
Examines the quantitative foundations of Counter Cases, verifying statistical reasoning, numerical claims, and analytical models to ensure evidence is interpreted accurately.
Works with quantitative evidence and datasets to uncover patterns behind business outcomes, supporting cases through data analysis, visualization, and empirical research.
Examines the psychological mechanisms behind business decision-making, drawing on research in human judgment, cognitive bias, social influence, and consumer behavior.
Reviews the evidentiary foundations of Counter Cases, examining source accuracy, competing interpretations, and the strength of claims before publication.
Researches how firms make strategic decisions across pricing, growth, positioning, and competition, contributing business analysis and case development.
What we hold ourselves to.
The short version of how a Counter Case earns its place here.
Evidence before surprise
A case starts with what the evidence supports, not with how counterintuitive the story sounds. We prefer the closest credible source to the claim and reject a good story when the evidence can't carry it.
Know what you're looking at
Every case is clearly identified as a Real Case or Research Simulation before you predict. Documented outcomes and teaching models are never presented as the same thing.
Fact, interpretation, and simulation stay separate
We distinguish what a source directly supports, what we think it may mean, and what has been constructed for experimentation. Interpretation never gets disguised as evidence.
Prediction comes before hindsight
You commit to a prediction and confidence level before seeing the outcome. Once submitted, they lock — because judgment is much easier to rewrite after you already know what happened.
Limitations belong beside the conclusion
A real finding isn't automatically a universal one. Alternative explanations, uncertainty, context, and limits to generalization stay visible rather than being cleaned away for a stronger story.
Make the work inspectable
Sources show what they support, important numbers should be traceable, and every case can be challenged through a correction report. We don't claim more certainty, causality, or independent review than actually exists.