Simulation scenarios

Simulation scenarios - are used an assessment of the value of the strategic decisions. These decisions differ from each other in terms of the impact of the environment on company's situation.

Simulation scenarios are used in management to model and test different potential outcomes of a decision or action. This can help managers to better understand the potential risks and benefits of different options, and make more informed decisions.

Simulation scenarios applications

Simulation scenarios can be used in a variety of management applications, including:

• Financial forecasting: Simulation scenarios can be used to model different economic and market conditions and their impact on a company's financial performance. This can help managers to identify potential risks and opportunities, and make more informed decisions about investments, financing, and other financial matters.
• Supply chain management: Simulation scenarios can be used to model different supply chain scenarios and their impact on costs, delivery times, and inventory levels. This can help managers to identify potential bottlenecks, optimize logistics, and reduce costs.
• Production planning: Simulation scenarios can be used to model different production scenarios and their impact on costs, delivery times, and inventory levels. This can help managers to identify potential bottlenecks, optimize logistics, and reduce costs.
• Human resources management: Simulation scenarios can be used to model different organizational scenarios and their impact on the workforce. This can help managers to identify potential issues related to employee engagement, retention, and productivity, and take steps to address them.
• Risk management: Simulation scenarios can be used to model different risk scenarios and their impact on the organization. This can help managers to identify potential risks and take steps to mitigate them.
• Strategic planning: Simulation scenarios can be used to model different strategic scenarios and their impact on the organization. This can help managers to identify potential opportunities and challenges, and make more informed decisions about the direction of the organization.

Overall, simulation scenarios can help managers to better understand the potential outcomes of different decisions and actions, and make more informed decisions that align with the organization's goals and objectives.

Stages of preparation

Process of development of simulation scenarios consists of 7 stages:

1. Specify environmental factors affecting the company and their intensity (expressed using units of measurement, and places of occurrence).
2. Specify the descriptors of certain factors for the evaluation of main problem.
3. Determination of the likelihood of the occurrence of descriptors from the previous stage.
4. In this step model are checked through the calculation of a matrix of likelihood values.
5. Scenarios are developed together with their descriptive part based on the model created in previous stage.
6. At this stage it is possible to obtain variants of scenarios based on critical cases (scenarios with small probability, but serious consequences for the company).
7. Summary of earlier stages is prepared, and managers make decision to choose the optimal strategy, which has slightest threat and gives a good chance of success.

Examples of Simulation scenarios

1. Online retailing: This scenario allows companies to simulate the potential effects of changes in online retailing, such as the introduction of new technology or changes in customer demand. The scenario simulates the impact on sales, cost, and profit over a period of time.
2. Competition in the market: This scenario simulates the impact of changes in competition in the market, such as the introduction of a new product or the entrance of a new competitor. The simulation allows companies to assess the impact on their market share, pricing, and profitability.
3. Supply chain disruptions: This scenario simulates the impact of disruptions in the supply chain, such as an increase in raw materials costs or a delay in the delivery of supplies. The simulation allows companies to assess the impact on their production, inventory levels, and costs.
4. Political decisions: This scenario simulates the impact of political decisions, such as changes in tax policies or trade regulations. The simulation allows companies to assess the impact on their operations, costs, and profitability.

Advantages of Simulation scenarios

Simulation scenarios are a powerful tool to evaluate the potential outcomes of strategic decisions, as they allow for a comprehensive assessment of the consequences of the decisions in different environments. The advantages of simulation scenarios include:

• Accurate predictions: Simulation scenarios provide an accurate picture of the likely outcome of a decision under different conditions. This helps to make informed decisions with the highest chance of success.
• Improved decision making: Simulation scenarios allow for better decision-making by providing a detailed assessment of the risks and rewards associated with different strategies.
• Improved collaboration: By providing a comprehensive overview of the potential outcomes, simulation scenarios can improve collaboration between stakeholders and help them to identify areas of agreement and disagreement.
• Flexibility: Simulation scenarios are flexible and can be adapted to different contexts, meaning that they can be used for different types of strategic decisions.
• Cost-effectiveness: Simulation scenarios are cost-effective, as they are less expensive than many other forms of assessment.

Limitations of Simulation scenarios

Simulation scenarios are useful tools for assessing the value of strategic decisions, but they have certain limitations. These include:

• Computational complexity: Simulation scenarios may require a large amount of computing power to generate the results, which can be costly and time consuming.
• Limited data: Simulation scenarios are limited by the amount of data available to generate the results, which may be incomplete or inaccurate.
• Assumptions: Simulation scenarios require assumptions to be made about the environment and the decisions being evaluated, which may not be accurate or relevant.
• Interpretation: The results of simulation scenarios are only as good as the interpretation of the data, which can be subjective and may not accurately reflect the actual situation.
• Real-time analysis: Simulation scenarios are not able to provide real-time analysis, which can be important for making quick strategic decisions.

Other approaches related to Simulation scenarios

Simulation scenarios can also be assessed using other approaches such as:

• Game theory: a mathematical approach to analyzing decisions made by two or more players in scenarios involving competition or conflict.
• System dynamics: a methodology for studying the behavior of complex systems over time, enabling users to analyze the effects of feedback loops on the dynamics of these systems.
• Agent-based modelling: a modelling technique which uses autonomous agents to simulate the behavior of social systems as a whole.
• Optimization techniques: a group of techniques used to minimize or maximize objectives in order to make the best decision in a given situation.
• Network analysis: a method for understanding complex interconnected systems, such as supply chains or communication networks.

In summary, simulation scenarios can be analysed and assessed using a variety of approaches such as game theory, system dynamics, agent-based modelling, optimization techniques, and network analysis. Each of these approaches has its own strengths and weaknesses, and can be used to gain a better understanding of the impacts of strategic decisions on an organisation's environment.

Simulation scenarios — recommended articles

Internal analysis — ASTRA analysis — Scenarios of possible events — Business portfolio analysis — Strategic analysis methods — Strategic management tools — EFE matrix — Strategic analysis — SPACE method

References

• Postma, T. J., & Liebl, F. (2005). How to improve scenario analysis as a strategic management tool?. Technological Forecasting and Social Change, 72(2), 161-173.