The what-if analysis: How it’s done and the benefits

The term “what-if” can immediately invoke feelings of anxiety and fear. This is not unusual, as it’s a natural human reaction to prefer the comfort of predictability over the vagueness of uncertainty. It’s in our nature to plan our day, week, and year based on the data available to us. But what-if analysis is a powerful tool for dispelling anxiety and fear while preparing your business for the unpredictability of simply doing business.

What is what-if analysis?

What-if analysis is a business process through which organizations analyze the impact of potential factors on their strategy, financial health, and productivity. Rigorous what-if analysis is an important part of active forecasting, keeping business leaders well-informed through the availability of robust data. This leads to better decisions and a more agile business strategy—one that allows you to react to crises and opportunities.

The difference between scenario planning and what-if analysis

Scenario planning is a specific type of what-if analysis, which uses multiple factors to create alternative scenarios for analysis. Compare this with sensitivity analysis, another type of what-if analysis, which focuses on the uncertainty that a single factor can create. You might hone in on employee attrition, for instance, and create a what-if analysis that simulates a 50% increase in attrition to determine the impact this would have on other aspects of the business.

Conversely, with scenario planning, you can combine multiple factors into a potentially elaborate simulation of the realities your business is facing. What happens if consumer spending falls by 25% and product revenue falls by 15%? Do you have the tools to find out the root cause and fix it? Are your budgets flexible enough to adapt to such significant changes? Whether sales are booming or declining, finance leaders need to go back and revisit their forecasts to assess the impact on cash flow and profitability and set correcting strategies.

How to perform what-if analysis

Properly executed what-if analysis can give your organization crucial insights that lead to a more flexible business strategy, better responses to sudden changes, and an overall more robust business. Here’s a quick step-by-step guide to performing your what-if analysis.

Step 1: Identify factors and trends you want to test for

This may seem like an obvious step, but it can be easier said than done. So many factors can potentially affect your business’s bottom line that it’s tough to know where to start. Even if you’re running a sensitivity analysis, you’ll need to pick a single factor to test for and identify all dependencies throughout the organization. In this step, you’ll also want to keep an eye out on external trends you want to test for, both those specific to your industry and broader markets.

It’s best to consult with leaders who can give you insight into the factors that should be covered by your what-if analysis. Otherwise, you’ll have to sift through potentially hundreds of factors.

Step 2: Set your baseline plan and strategy

Before you can analyze the what-ifs, you need a baseline to compare them to. This will mean consolidating information on your overall business strategy and any of the factors you’re looking to modify for your analysis—like employee headcount, revenue, and inventory. Getting this data together can take time and involve multiple teams, so account for this in your timeline.

Step 3: Prioritize potential what-ifs

Now that you have your baseline and the factors you want to analyze, you’ll want to prioritize them. As you get deeper into the planning stages of your what-if analysis, you may encounter new data or insights that make factors you’ve outlined less relevant for your analysis. To avoid this, you’ll want to use both qualitative and quantitative approaches to prioritize—and perhaps even eliminate—some of the factors you outlined in the first step. Questions you can ask yourself to do this include:

• How likely is it that this factor will change within the timeline my analysis is accounting for?
• Is there another factor that better represents the hypothetical I’m testing for?
• Have leaders outlined that this specific factor is important?
• What am I trying to achieve in analyzing this factor?
• Are there past analyses that could inform factor selection?

Step 4: Build scenario or sensitivity analysis

Having now prioritized your factors, you’re ready to build out the main components of your analysis. The exact steps you take to do this will vary, depending on the tools you’re using and whether you’re performing a scenario or sensitivity analysis. Generally speaking, however, you’ll want to do the following.

Scenario analysis

• Combine the factors you’ve identified for analysis into a scenario that can be summarized in a few sentences. This will ensure that you’ve drafted a cohesive scenario while allowing you to easily communicate the goal of your analysis with anyone who needs to be informed.
• Build a way to simulate and track the impact of your scenarios on business-critical variables. This can be with the built-in features of your spreadsheet tool of choice, but financial planning and analysis (FP&A) software is usually best for this.
• Plan for potential errors or skewed results, whether that’s from your methodology, unexpected dependencies, or even the tools you’re using.

Sensitivity analysis

• Identify all variables that can be affected by the single factor your analysis will be evaluating.

• Build a way to simulate the impact of that single factor on the rest of the business. This involves mapping out a network of dependencies.
• Plan how you’ll review the results of your analysis to surface potential errors.

Step 5: Run your analysis

There are so many ways to run a what-if analysis, keep these best practices in mind as you run your analysis.

• Account for bias: Biases affect every single process, and that includes what-if analysis. A bias can emerge from just about any source, including the industry you’re in, how business has been over the last few quarters, and even the makeup of the team running the analysis. These biases can cause you to overestimate the influence of certain factors or accidentally ignore important dependencies.
  
• Rely on expertise: Like many other resource-intensive processes, there is a temptation to offload what-if analysis to those with less experience. Even if the argument can be made for costs savings, there is a level of expertise required for what-if analysis.
  
• Don’t put more emphasis on more likely outcomes: If you prioritize the factors in your analysis only by how likely they are to happen, you’re likely to emphasize them more in your analysis. Doing so can skew your results and cause you to miss valuable insights. Remember that the most unlikely events can be some of the most devastating.
  
• What-if analysis is an ongoing process: Your what-if analysis can rarely be a one-and-done process. To really keep your organization agile, you should be forecasting and analyzing potential scenarios on a regular basis. Make sure your process is repeatable, and strive to improve it with every iteration.

Step 6: Assess results

Once you’ve run your what-if analysis, it’s important to review your findings and turn them into actionable insights and reports. That way, business leaders throughout the organization can make the most of your results. Have a plan in place to turn your data into something that can be easily consumed or presented to maximize its impact.

How to use FP&A software for what-if analysis

Organizations of all sizes use what-if analysis to evaluate the flexibility of their business strategy and draft plans to respond to potential scenarios. The tools used for this vary greatly, with many businesses still using spreadsheets and tons of manual work to build and run their what-if analysis.

While Excel has built-in what-if analysis tools that can make this slightly easier, most trained scenario planners avoid using spreadsheets in their work. So what tools do they use?

Usually, they use FP&A platforms—like Prophix.

When it comes to scenario planning and what-if analysis there’s no tool quite like Prophix. By pulling data from all across your organization, Prophix can create dynamic dashboards that allow users of any skill level to create and simulate scenarios without nearly as much manual work as other methods.

Check out this demo to see it in action!

What are the benefits of what-if analysis?

A properly run what-if analysis has significant upside for your organization and should be a key part of your forecasting. Some of these benefits include:

Business agility

How easily could your organization pivot in response to a significant market change? One that has the potential to slash your revenue while increasing your operating costs? What-if analysis is one of the best ways to test this and increase overall agility.

Better reaction to change

Agility describes how quickly and easily your organization can make significant changes in strategy, but agility alone doesn’t account for the actual impacts of those changes. With what-if analysis, you can pair agility with better decision-making.

Mitigation of variance

By focusing on the many potential eventualities of your business, you can better account for factors that would create variance in your most important success metrics.

Resiliency

By forecasting potential scenarios and analyzing them, you can learn how to shore up your organization’s weaknesses. This allows you to be more resilient in the face of significant market shifts.

In summary, what-if analysis is all about envisioning and implementing ideas and goals that let you compete and win in the marketplace. But using dated techniques can decrease its efficacy. Don’t let old habits of the past slow down your organization and its predisposition to change. A Financial Performance Platform, like Prophix, provides the office of the CFO with the tools to be hyper precise, ultra-adaptable, and drive dramatic performance. In a rapidly evolving environment, finance leaders strives to gain a competitive edge in a world of big data and increasing complexity.