How do you simulate business strategy?

3 Simulation models

Simulation models are the core of any simulation tool, and they define the structure, variables, parameters, and logic of the system you want to simulate. Depending on the level of detail, complexity, and realism you want to achieve, a simulation model can be based on different approaches and frameworks. For example, game theory models use the concepts and methods of game theory to analyze decisions and outcomes in competitive or cooperative environments. Agent-based models use agent-based modeling to simulate the emergence and evolution of collective phenomena from individual behavior and rules. System dynamics models use system dynamics to simulate the effects of policies and actions on performance and stability. All these models can help you make better business strategy decisions.

5 Simulation examples

Illustrating how to simulate business strategy, let's look at some simple examples from economics. These examples are not meant to be comprehensive or realistic, but rather to demonstrate basic concepts and methods of simulation. For instance, a Cournot duopoly can be simulated with a game theory model. This model involves two firms producing a homogeneous good with identical marginal costs and a linear demand function. The goal is to find the Nash equilibrium, the output levels that maximize the firms' profits given the output levels of the other firm. Spreadsheet software can be used to create a table with the output levels of the firms as rows and columns, and the profits of the firms as cells. We can then use formulas to calculate the market price and the profits for each output level. In another example, an agent-based model can simulate the diffusion of a new product in a market with potential customers. The adoption rate depends on coefficients of innovation and imitation, which measure propensity for independent or social adoption. The goal is to find the adoption curve, which is the cumulative number of adopters over time. Finally, a system dynamics model can simulate the supply chain of a beer distributor consisting of four stages: factory, distributor, wholesaler, and retailer. The supply chain faces fluctuating demand from customers and fixed order delay from suppliers. The model seeks to find an optimal order policy that minimizes total cost of supply chain. MATLAB or other software supporting system dynamics modeling can be used to create a diagram representing flows and stocks along supply chain, as well as feedback loops and delays affecting them. Different order policies can then be compared and evaluated for performance and trade-offs.