Uncertain data values or dependencies are inevitable when carrying out long-term strategic planning. However, these uncertainties are often not fully appreciated, with decisions being made using deterministic analytical models that require all data affecting the economic situation to be precisely known or bound. In reality, some of these values are unknown, and a best guess, group consensus, or incomplete data set is used as a proxy.
In addition, key variables are sometimes dismissed or not included in the analysis. For instance, interactions between two minor factors may be an unidentified, but major, cost driver. These are the unknown unknowns, the unexpected or unforeseeable conditions, and their impact cannot simply be resolved with Monte Carlo experiments using the variables considered important. Consequentially, many of these deterministic models and optimization attempts will lead to significant financial losses. Fortunately, there is a solution.
Strategic planning software based on simulation can be used in these situations to cover the range of possibilities, by uncovering hidden interactions, testing dependencies, and revealing sensitivities. The results enable informed thinking, beyond the simple quantification of system perceptions given with analytical methods. Strategic planning with AnyLogic software provides the power to uncover uncertainty and provide effective management, with mitigation strategies for risks and negative scenarios.
AnyLogic models are effective for asset management optimization and portfolio risk analysis, with proven results across areas as broad as vehicle fleet management, investment strategy optimization, and hardware maintenance scheduling.
Simulation modeling is ideal before committing to large investments and projects, and throughout the entire lifecycle for risk analysis and resource optimization. The adaptability of AnyLogic simulation software has delivered effective results for large-scale construction projects, shipbuilding, and aircraft manufacturing. It is powerful for any kind of custom production project and investment.
To make your first steps in the application of simulation to project modeling, you can read the Modeling and Simulation in Complex Project Management book. It provides a theoretical overview of project management, as well as an introduction to the three most widespread modeling techniques (system dynamics, agent-based, and discrete event modeling) using some simple models of project management as examples.
Using simulation for optimization and strategic planning is key to accurate analysis and valuable insights for your project and asset management.
