Uncertain data values or dependencies are inevitable when carrying out long-term 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 using Monte Carlo experiments with the variables considered important. Consequentially, many of these deterministic models will lead to significant financial losses. Fortunately, there is a solution.
Simulation modeling 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. AnyLogic simulation models provide the power to uncover uncertainty and provide effective management, with mitigation strategies for risks and negative scenarios.
AnyLogic models are effective in asset management and have proven results across areas as broad as vehicle fleet management, investment strategy optimization, and hardware maintenance scheduling.
Modeling is ideal before committing to large projects, and during projects when there are significant modifications to the original specifications. The adaptability of AnyLogic has delivered effective results for large-scale construction projects, shipbuilding, and aircraft manufacturing. It is powerful for any kind of custom production project.
