Comparing GoldSim to @RISK by Palisade, Crystal Ball by Oracle, Risk Solver by Frontline Systems and other Monte Carlo Spreadsheet Add-Ins

A number of spreadsheet add-ins, such as @RISK by Palisades Corporation and Crystal Ball by Decisioneering, allow you to define spreadsheet cells as probability distributions and conduct Monte Carlo simulations within spreadsheets cells. Although these tools provide an incremental improvement over simple spreadsheets, they still suffer from weaknesses inherent to spreadsheet-based approaches:

Complex spreadsheets and add-ins are generally not transparent and can be very difficult to explain to others. Because of the row and column paradigm used by spreadsheets, the fact that equations are written in terms of cell references, the invisibility of the dependencies between cells, and the lack of a graphical means to document the model, most spreadsheet models have a low level of transparency. It can even make it difficult to understand your own model, particularly if you have not looked at it for some period of time. GoldSim's interface, which allows you to build hierarchical, graphical representations of your system (in terms of influence diagrams) was specifically designed to facilitate the construction of transparent, well-documented models that can be easily explained to others.

Complex spreadsheets are prone to errors. Due to the lack of transparency of complex spreadsheet models, not only can it be difficult to communicate your model to others, but it can also be difficult to check for errors. As a result, studies have shown that complex spreadsheets have a very high incidence of errors. GoldSim's hierarchical, graphical approach to model-building, combined with powerful debugging tools, means identifying and correcting errors is easier and requires less effort.

Spreadsheets and add-ins cannot easily represent complex dynamics. In a spreadsheet, you typically deal with dynamics by adding a row (or column) for each timestep (i.e., each day, each quarter, each month) that you want to forecast a value for. In addition to being a very awkward way to represent dynamics, this has a number of serious disadvantages: 1) it is difficult to represent dynamic feedback loops and delays, where a change made to one part of the system has a delayed impact; 2) sudden events (e.g., a deposit or withdrawal, an interest rate change) are difficult to accurately represent; 3) changes in the system's structure with time are hard to represent (e.g., taking out a loan when required), and 4) the length of the timestep cannot be dynamically adjusted during a simulation (e.g., in response to changing conditions). GoldSim is a dynamic simulation program, where representing such complex dynamics is straightforward.

Spreadsheets cannot easily represent stochastic systems and processes. All real-world systems have uncertain and  stochastic components. Although add-ins like Palisades @RISK and Decisioneering Crystal Ball enable Monte Carlo simulation within a spreadsheet, because spreadsheets cannot easily represent dynamic systems, it is difficult to represent stochastic processes. GoldSim was specifically designed to simulate such systems.

Spreadsheets have no ability to handle dimensions and units. Because spreadsheets deal only in numbers, and cannot represent units, great care must be taken when building models to handle unit conversions where mistakes are easy to overlook. GoldSim understands dimensions and units, carries out automatic unit conversion, preventing you from constructing dimensionally-inconsistent models.

These and other advantages make GoldSim simulation software a powerful and flexible improvement over spreadsheets and the spreadsheet add-ins such as @RISK, Crystal Ball and similar tools. 

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Making Better Decisions In An Uncertain World