Why We Love @RISK Software

Why We Love @RISK Software

“Are you placing enough interesting, freakish, long shot, weirdo bets?”

 — Tom Peters, author of “In Search of Excellence: Lessons from America’s Best-Run Companies”

Typically, we don’t offer up endorsements for software packages or specific suppliers. Today, we are going to make an exception to that rule.

If you are a middle market business CFO or CEO, get a copy of @RISK software from Palisades. @RISK uses Monte Carlo simulation to run risk analysis showing the multitude of possible outcomes in your spreadsheet model and shows how likely they are to occur. @RISK is often thought of as a tool for finance and negotiating transactions as seen in a recent $200 million co-financing deal between LS Capital and Sony; however, this very powerful and easy to use tool is for every business, no matter the industry or size.

According to Palisade, the software “mathematically and objectively computes and tracks many different possible future scenarios, then tells you the probabilities and risks associated with each different one,” – meaning you can decide for yourself which risks to take and which to bypass, allowing for “the best decision making under uncertainty.”

Sound like a mouth full?  It is, but the software — an add-in to Microsoft Excel — can help you make better decisions by helping you model probable outcomes.  Consider a simple P&L structure where:

  1. Your revenue is planned to be $50,000,000 by selling 1,000,000 units at $50/unit
  2. Your costs are $20/Unit
  3. You know that both your price and your cost vary based on market conditions

If you’re a typical Excel user, you’d model out this scenario to be $50,000,000 in revenue, $40,000,000 in COGS, and a $10,000,000 gross profit. At that point, you’d be done. Not with @RISK.  With this software, you can model in the fact that you know your average price is $50 per unit, but that it does fluctuate between $45/unit and $63/unit, depending upon the time of the year and the economy. You can also model in the fact that input prices that vary by some standard percentage, say 3 percent, is typical. Once modeled, you can run a simulation in @RISK to tell you what a probable gross profit will be based on these conditions and also tag a 90 percent probability range to see where those numbers fall.

In addition, they just launched version 6 which includes, among several other upgrades, an integration with Microsoft Project, and a new set of functions for simulating time series processes, or values that change over time.

Want to learn more?  Check out this video.

Happy modeling!

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