Decision Support: @Risk 5.0

Model, Simulate, Understand (from Palisade product presentation)

Running an analysis with @RISK involves three simple steps:

1. Set Up Your Model. Start by replacing uncertain values in your spreadsheet with @RISK probability distribution functions, like Normal, Uniform, or over 35 others. These @RISK functions simply represent a range of different possible values that a cell could take instead of limiting it to just one case. Choose your distribution from a graphical gallery, or define distributions using historical data for a given input. Even combine distributions with @RISK's Compound function. Share specific distribution functions with others using the @RISK Library, or swap out @RISK functions for colleagues who don't have @RISK.

Next, select your outputs - the "bottom line" cells whose values interest you. This could be potential profits, ROI, insurance claims payout, disease recovery rate, or anything at all.

More on Modeling in @RISK

Input distributions may be correlated with one another, individually or in a time series. Correlations are quickly defined in matrices that pop up over Excel, and a Correlated Time Series can be added in a single click. A Correlated Time Series is created from a multi-period range that contains a set of similar distributions in each time period.

All @RISK functions and correlations in your model are summarized - with thumbnail graphs - in the dashboard-style @RISK Model window, and you can watch distribution graphs pop up as you browse through cells in your spreadsheet.

Share Your Model with Others
@RISK functions can be stored in the @RISK Library, a SQL database for sharing with other @RISK users. @RISK functions may also be removed with the Function Swap feature, enabling your models be to shared with colleagues who don't have @RISK installed. @RISK will keep track of any changes that occur in the spreadsheet while the @RISK functions were "swapped out." You can control how @RISK should update formulas when it finds changes in the model. In addition, you can have @RISK automatically swap out functions when a workbook is saved and closed and automatically swap in if necessary when a workbook is opened.

2. Run the Simulation. Click the Simulate button and watch. @RISK recalculates your spreadsheet model thousands of times. Each time, @RISK samples random values from the @RISK functions you entered, places them in your model, and records the resulting outcome. Explain the process to other by running your simulation in Demo Mode, with graphs and reports updating live as the simulation runs.

3. Understand Your Risks. The result of a simulation is a look at a whole range of possible outcomes, including the probabilities they will occur. Graph your results with histograms, Scatter Plots, cumulative curves, Box Plots, and more. Identify critical factors with Tornado charts and sensitivity analysis. Paste results into Excel, Word, or PowerPoint, or place them in the @RISK Library for other @RISK users. You can even save results and charts right inside your Excel workbook.

More on @RISK Results

Clear, Easy-to-Understand Results
@RISK provides a wide range of graphs for interpreting and presenting your results to others. Histograms and cumulative curves show the probability of different outcomes occurring. Use overlay graphs to compare multiple results, and summary graphs and Box Plots to see risk and trends over time or over ranges. Right-click menus and handy toolbars make navigation a snap. All graphs are fully customizable - including titles, axes, scaling, colors, and more - and ready for export to Excel, Word, or PowerPoint. You can watch results graphs pop up as you browse through cells in your spreadsheet.

@RISK provides you with sensitivity and scenario analyses to determine the critical factors in your models. Use sensitivity analysis to rank the distribution functions in your model according to the impact they have on your outputs. See the results clearly with an easy-to-interpret Tornado diagram, or uncover relationships with Scatter Plots. Sensitivity analysis pre-screens all inputs based on their precedence in formulas to outputs in your model, thus reducing irrelevant data. In addition, you can use @RISK's MakeInput function to select a formula whose value will be treated as an @RISK input for sensitivity analysis. In this way, multiple distributions can be combined into a single input, streamlining your sensitivity reports.

All simulation results for both outputs and inputs are summarized - with thumbnail graphs - in the dashboard-style @RISK Results Summary window. Simulation results may be saved directly in your Excel workbook, and also placed in the @RISK Library to for sharing with other @RISK users.