What-If Analyses: Scenario, Sensitivity & Simulation

Instructor: Dr. Douglas Hawks

Douglas has two master's degrees (MPA & MBA) and a PhD in Higher Education Administration.

Even the best manager or analyst can't predict the future. But, different types of 'what if' analyses can help managers anticipate potential future scenarios. In this lesson, we'll discuss some of these 'what if' analysis tools.

What Is 'What if?'

One of the key functions of management is planning. That may not sound like a difficult responsibility, but when you ask 'planning for what?', the discussion becomes more complex. How can managers effectively plan for different future possibilities if nobody knows what the future holds? The answer is that knowledgeable, skilled managers are able to utilize 'what if' analyses to anticipate the most likely future situations they will need to manage, and then plan accordingly.

To help bring these analyses to life, let's use a simple example. Imagine you've developed a new composite material that can be used for mobile phone casing and also absorbs solar energy to charge the phone. Yours isn't a case, but an actual composite that the manufacturers can make their phones with that is practically unbreakable, uncatchable, and keeps a phone charged all the time. Like any good entrepreneur, you want to know what to expect when your patent is finalized and you announce this new material in three months.

There are three popular 'what if' analyses that can be performed to help you conceptualize what types of situations you may face in the future. Each is slightly different, and each will give you a little more information than the other two. These three, which we'll discuss in more detail below, are: sensitivity analysis, scenario analysis, and simulation analysis.

Sensitivity Analysis

A sensitivity analysis is an analysis that estimates how sensitive your dependent variable (in this case, amount of material sold) is to a change in an independent variable (for your casing composite, price). In some situations, you may have historical data to use when completing your sensitivity analysis, but in your case, you have to use as much information as you can find about how much work it is for mobile phone manufacturers to change their suppliers, how much they currently pay for casing material, and how much you might be able to help them be offering a truly innovative new feature on their phone.

In a sensitivity analysis, you are only looking at how sensitive the change in an outcome is based on changing a single variable. But, you can consider many more factors than just the outcome. For example, you may think a manufacturer is going to pay big bucks for your composite, but think about the implications. If they use your composite, they will lose a lot of the money they make by selling power adapters and cords. Also, will your composite work with the cases they already sell, or will they have to use a special case?

At the end of a sensitivity analysis, you want to be able to estimate that 'an X% increase in price will result in a Y% decrease in the amount of my product sold.' While that may be an ideal result for a sensitivity analysis, it doesn't have to be quantitative. You may simply want to know what factor, within your control, will have the most significant impact on sales. If you go through a logical, methodical process to identify the impact one variable has on our desired outcome, you are conducting a sensitivity analysis.

Scenario Analysis

Once you understand what a sensitivity analysis is, a scenario analysis is fairly simply to comprehend. A scenario analysis is when you make assumptions about a number of independent variables and environmental factors, and consider their impact on the outcome of your analysis. Instead of looking at how one variable impacts the outcome, like in a sensitivity analysis, you look at many different factors that could impact a situation in the future.

For example, with your new solar-charging mobile phone composite, instead of just thinking about how price might impact sales, think about other factors. What if you have competition you don't know about, and they go to market first? What if your material makes the phone heavier, and the manufacturers know consumers prefer light phones? What if a battery supplier for mobile phones has a new battery that will last a whole week? What if you find out your material interferes with a clear data and voice signal?

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