What if we could simulate emotion?
Not in a hypothetical way. Not in a philosophical way. But in the real, physical world the world of boardrooms, shop floors, team huddles, late-night deadlines, and customer interactions.
What if we could finally see how trust flows through a team?
How burnout builds beneath the surface?
How motivation spreads or doesn’t through a department?
That is the core promise of the Business Physics Lab.
We are here to bring structure to what has always felt unstructured: We Research
Emotion in business.
From Invisible to Visible: Mapping Emotional Dynamics
The Business Physics Lab is built around 20 core principles that help us make emotional systems visible inside organizations.
We simulate:
- Where motivation builds or fades.
- Where trust is stable and where it is breaking down.
- How collaboration moves or stalls across departments.
- How stress accumulates in specific roles, spaces, or moments.
We also use synthetic agents—human-like models of employees, customers, or partners—to test emotional interactions inside simulated business environments.
These tools help leaders explore scenarios in advance, much like a wind tunnel test. The difference is that we are testing not a product, but a culture.
At the Lab, we take a different approach.
We do not treat emotion as something soft or abstract. We treat it as systemic, observable, and designable using a physics-inspired framework rooted in the real environments where business happens.
In our work, concepts like:
- Motivation become force, the energy that moves people forward.
- Trust becomes structure, the integrity that holds everything together.
- Friction becomes misalignment, the source of wasted effort and conflict.
- Momentum becomes progress that sustains itself through resistance.
- Empathy becomes resonance, the pattern that creates meaningful connection.
These are not metaphors. These are working principles that we apply to meetings, customer journeys, team dynamics, and organizational strategy.
20 Business Physics-Inspired Principles
1. Force (Motivation)
Represents the driving factors influencing actions and behaviors.
2. Energy (Effort)
Measures the resources expended to achieve outcomes.
3. Momentum (Progress)
Represents sustained performance over time.
4. Friction (Obstacles)
Symbolizes inefficiencies or barriers in processes.
5. Equilibrium (Stability)
Represents the balance between workload and capacity.
6. Adaptability (Elasticity)
Reflects the ability to adjust to changing conditions or demands.
7. Feedback Loops (Self-Regulation)
Captures how systems improve through iterative feedback.
8. Optimization (Leverage)
Focuses on achieving maximum results with minimal input.
9. Distributed Intelligence (Collaboration)
Represents the collective problem-solving capability of human and synthetic agents.
10. Trust as Stability
Highlights the importance of trust in maintaining system reliability.
11. Wave Cycles (Behavioral Patterns)
Reflects recurring patterns in performance or demand.
12. Entropy and Renewal (System Longevity)
Represents system degradation and the need for updates.
13. Alignment (Resonance)
Ensures goals and actions are synchronized across systems.
14. Velocity (Speed of Execution)
Reflects how quickly tasks are completed.
15. Persona-Driven Interactions
Synthetic agents embody distinct personas tailored to roles.
16. Cognitive Load (Effort Balancing)
Represents the management of task complexity.
17. Redundancy (System Resilience)
Ensures backup systems are available for continuity.
18. Bias and Ethics (Decision Quality)
Ensures decisions are fair, unbiased, and aligned with ethical standards.
19. Interference (Unintended Consequences)
Represents disruptions caused by conflicting actions or inefficiencies.
20. Emergence (Complex Systems Behavior)
Captures new patterns or behaviors arising from system interactions.
These principles guide modelling, decision-making, and optimization across business contexts in the Business Physics AI Lab.
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