Management game theory

Management Game Theory provides mental models to integrate behavioural capital with finance and HR data. Behavioural capital is becoming increasingly important in creating business value. These “soft skills” are difficult to acquire because human social context is complex due to different personalities and biases.

However, there is an emerging new science that will solve this problem and foster organizational performance. Game theory sheds light on management behaviour and helps illuminate the relationship between the actions of management and the performance of subordinates. It helps illustrate why some organizations fail at change management or face high staff turnover. Game theory is science that applies mathematics to better understand human decision-making and social behaviour.

Game theory is key in creating new generation model-driven artificial intelligence to reinforce managers’ behaviour and create sustainable competitive advantages.

Every leader, manager or supervisor is playing a game that includes the following game theory principles:

Strategic game

A leader’s behavior today affects an organization’s profits after twelve months. This phenomenon of long-term effects makes leadership strategic. Every leader has a certain management mindset or policy that he or she follows, either consciously or subconsciously. There are also human biases that dictate leadership behavior. In addition, there are personal assumptions about the rewards of leadership behavior. Some leaders are able to predict future rewards while others think only about fast rewards or avoiding possible punishment, which may be strategically unwise.

Bayesian game

The management game is Bayesian, meaning we have to make decisions with imperfect information. Managers’ have prior assumptions about their leadership behavior’s effects. With experience, the prior assumptions may change as learning from doing gives a better understanding about the context and behavior’s causalities. This is called reinforcement learning that rational persons naturally have, and it is also included at Bayesian game theory. Leaders operate in an organization environment that is complex and may sometimes be hard to comprehend. However, leaders know certain probability distributions upon which they can base their decisions. Rational leaders utilize the brain’s natural phenomenon of reinforcement learning despite the imperfect information from complex environment.

Stochastic game

The management world is stochastic, which usually leads to negative surprises. One cannot expect that each day’s activities will be fulfilled as planned. Often there are stochastic interventions which require our attention. Also, humans are heavily affected by current moment bias in which short-term reward (or avoiding immediate punishment) is valued more than long-term reward (which would require different actions and more strategic thinking). The stochastic world is evolving and manager behaviour will have a great effect on the outcome.

Non-symmetric game

Leaders, managers, and supervisors are all in non-symmetric positions compared to their subordinates. The leadership power of managers is controlled by management systems. Thus, managers usually have different strategies than their subordinates. While worker focuses on doing their tasks, managers have to think about whole team collaboration and performance. In addition, there are myriad personal and social features that form the way leaders use their non-symmetric power to influence subordinates.

Signalling game

The behaviour of the leader can modify a team’s culture and culture dictates the signalling game. When there is common trust that problems are solved in a positive way, there will be more signals about possible problems and development needs. In addition to staff comments and feelings, there are also signals from management systems. For example, a digital leaderboard can signal increased sickness risk and recommend activating early intervention for preventing absences. In this case, the digital system analyzes data (i.e. staff inquiries and other data) and sends out alarms and offers advice for action.

Non-cooperative or cooperative game

In the famous prisoner’s dilemma there are two prisoners who can’t communicate but are forced to choose to either cooperate with each other or act in their own best interest. In the context of an organization, communication is not restricted, but the same type of social decision dilemma is present in every organization and team: Do the employees choose to cooperate, or do they act on their personal best interest? A non-cooperative mindset reduces productivity and may cause severe performance problems. Using game theory, it is possible to foster a more cooperative mindset in which employees innovate and solve problems in a positive atmosphere.

Zero-sum or general sum game

In a zero-sum game, gain for one player results in a loss for the other player. A zero-sum game mindset is harmful to organizations because it prevents cooperation. In the general sum game, the players help each other to achieve rewards and higher performance levels. General sum players are also willing to take risks together. They are focused on winning and are ready to make sacrifices to secure long-term rewards. Both, the zero-sum and general sum game leave marks at organization data, thus it is possible to analyze which type of game the organization plays. Data-driven AI helps identify exiting culture and model-driven AI helps with teaching which behaviors lead to the general sum game.

Why is game theory combined with machine learning an incredible breakthrough?

We can model complex human behavior in an organizational context using mathematical modeling. First, we have to make digital presentations for organizations that model the effect of management decisions on fiscal and human performance, then we must implement Markov sequences at this digital twin and start running reinforcement Q-learning with the Bellman function. This may sound complicated (and it actually is), but when the digital twin world is built, it explains why human capital management within organizations is so difficult. AI can provide advice for managers in their decision-making, forming sort of a crystal ball that reveals future alternatives and reinforce behavior for winning.

There are significant benefits in utilizing game theory, data-analytics and machine learning in an organizational setting. I believe there is going to be an emerging new management science in this field. Game theory provides mental models to integrate behavioural capital with finance and HR data. This is not an easy task, but this revolutionary research has already begun. At this stage, it is essential to have close research collaboration with companies where data is created every day and performance problems are difficult to solve. It seems that Kurt Lewin’s saying, “Nothing is more practical than good theory,” applies here as well.
Marko Kesti

CEO
Tel. +358 (0)40 717 8006
Email: info@playgain.fi

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