Quantum Mechanics, Schrödinger Equation and Organizational Behavior: What Business Leaders Need to Know
Post proposes a data-driven framework for modeling organizational behaviour with concepts in quantum mechanics. It is targeted at business leaders, IT Leaders, Managers or anyone tasked with developing strategies to boost organizational performance. Advanced knowledge of Math or Physics is not required.
As leaders and managers, it is easy think that quantum mechanics has much to do with organizational behavior. After all, quantum mechanics is a complex field of physics that deals with subatomic particles and quantum states, while organizational behavior deals with the behavior of people and groups within an organization. For most leaders with STEM background, anything “quantum” was theoretical and abstract, and left in university classroom or . However, I, not being a Math guru nor interested in Physics, learned recently that there are some interesting analogies that can be drawn between these two seemingly disparate fields. Before we go into analogies, let’s begin by defining both fields according to Wikipedia:
Quantum mechanics is a fundamental theory in physics that provides a description of the physical properties of nature at the scale of atoms and subatomic particles.
The Schrödinger equation is the name of basic non-relativistic wave equation used in one version of quantum mechanics to describe the behaviour of a particle in a field of force. It essentially describes the form of the probability waves that govern the behaviour of small particles (individuals), and it specifies how these waves (collection of individuals — organization) by external influences (leadership, strategy, culture, market, investors, etc).
Organizational behavior (OB) is the: “study of human behavior in organizational settings, the interface between human behavior and the organization, and the organization itself”.
Simply reading these definitions, we begin to see how these two seemingly disparate fields have similar analogies:
One way to think about the analogy between quantum mechanics and organizational behavior is to consider the concept of “quantum organization.” This concept, made popular by economist Brian Arthur and physicist Geoffrey West, proposes that organizations can be thought of as complex systems that exhibit behaviors similar to those of quantum particles. Like quantum particles, organizations are dynamic, constantly changing, and subject to unpredictable fluctuations.
What does this mean for me as a leader?
- Organizations are complex systems: Just as quantum systems are complex and difficult to predict, organizations are also complex systems that are influenced by many different factors. This means that it can be challenging to predict the behavior of an organization, and that small changes can sometimes have large effects, both positive and negative.
- Collective behavior is important: In quantum mechanics, particles can exhibit both wave-like and particle-like behavior, depending on how they are observed or measured. Similarly, organizations can exhibit both individual behavior and collective behavior, depending on the context. Understanding and managing collective behavior within an organization can be critical for achieving desired outcomes.
- Leadership, culture, and strategy matter: In the Schrödinger equation, the Hamiltonian operator represents the factors that influence the behavior of a quantum system, such as the energy and potential of the system. Similarly, leadership, culture, and strategy can influence the behavior of an organization. As business leaders, it is important to understand how these factors can shape the behavior of your organization and to develop strategies for managing them.
Drawing these parallels across both, in developing strategies, we propose a mathematical model based on the Schrödinger equation to model organization behaviour. Therefore, managers can leverage an analytical model to develop different scenario outcomes of organizational behavior.
Modeling Organizational Behaviour with Schrödinger Equation
While it’s not possible to represent all the factors that influence organizational behavior with a single formula, the Schrödinger equation provides a framework for understanding how different factors can interact to influence the behavior of a complex system. In the Schrödinger equation, the Hamiltonian operator represents the factors that influence the behavior of a quantum system. This operator takes into account variables such as energy, potential, and other physical properties that affect the behavior of the system.
Similarly, in the context of organizational behavior, we can think of the Hamiltonian operator as representing the factors that influence the behavior of an organization. This might include variables such as leadership, culture, company strategy, external market forces, and other factors that shape how people within the organization behave.
We can’t represent all of these factors with a single formula, we can use the concept of the Hamiltonian operator as a way of thinking about how different variables interact to influence the behavior of an organization. By understanding how these variables interact, business leaders can gain new insights into how to manage and shape the behavior of their organizations.
The Math
Here’s an example of how the Schrödinger equation could be used to model organizational behavior, using the factors of leadership, culture, and company strategy:
ψ(x, t) = (1/√N) ∑n=1N wnψn(x) e^(-iEn t/ħ)
In this equation, ψ(x,t) represents the wave function that describes the behavior of the organization over time. The wave function is a complex function that describes the probability amplitude of different possible states of the system. The Schrödinger equation describes how the wave function evolves over time, based on the Hamiltonian operator that represents the factors that influence the behavior of the system.
In this case, we can represent the Hamiltonian operator as follows:
H = Hₒ + V
Hₒ represents the baseline behavior of the organization, while V represents the influence of external factors such as leadership, culture, and company strategy. We can assign random weights to each of these factors to model their influence on the behavior of the organization.
For example, we might assign weights of:
- Leadership (w₁) = 0.4
- Culture (w₂) = 0.3
- Company Strategy (w₃) = 0.2
We can then represent the potential energy (V) in the Hamiltonian operator as:
V = w₁V₁ + w₂V₂ + w₃V₃
Where V₁, V₂, and V₃ represent the potential energy associated with each of the factors (leadership, culture, and company strategy). The weights (w₁, w₂, and w₃) determine the relative importance of each factor.
Finally, we can use the Schrödinger equation to model how the behavior of the organization evolves over time, based on these factors:
iħ ∂ψ(x, t)/∂t = (Hₒ + w₁V₁ + w₂V₂ + w₃V₃)ψ(x, t)
By solving this equation, we can determine how the behavior of the organization will evolve over time, based on the influence of leadership, culture, and company strategy. While this is a simplified model that doesn’t take into account all the complexities of organizational behavior, it provides a useful framework for understanding how different factors can interact to shape the behavior of an organization.
Math is good; How do I use this?
To simplify for managers, I have developed a Streamlit application hosted on AWS AppRunner. With this, managers and business leaders can input factors and weights and visualize the organization’s behavior over time. This provides managers and business leaders a data-driven companion when developing strategy and simulate the behavior of the organization over time.
Furthermore, business leaders can also optimize for profitability, they can define a cost function that takes into account the organization’s revenue, expenses, and other relevant factors. The algorithm then uses optimization techniques to adjust the weights of the potential energy function to maximize profitability. This simulates how organizational behaviour influences company profitability. This includes plots of the organization’s behavior over time, as well as visualizations of the weights of the potential energy function and the resulting profitability.
Conclusion
While this model is far from perfect and may not capture all the nuances of real-world organizational behavior, it offers a useful starting point for exploring different scenarios and gaining insights into how to optimize an organization’s performance and how they can be optimized for success.. By combining this approach with other tools and methodologies from fields such as data science, machine learning, and design thinking, we can create a more comprehensive and nuanced understanding of organizational behavior.
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Interested in learning more about Olalekan Elesin or want to work together? Reach out through LinkedIn.
