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As we have already seen and understood, Root Cause Analysis focuses on identification of all those independent variable X's (further narrowed to critical X's) deemed as input, which has an impact on the dependent output variable Y. In other words, identification of all causes which influences the effect. In a Sensitivity Analysis, also referred to as "What-if" or "Simulation Analysis", we determine how the output-dependent variable (Y or effect) varies when each of the independent variable (X or causes) are varied under a predefined set of assumptions. Simply stating, how different values of each independent X, will have an impact on Y. Once we have the critical X's identified using the relevant Tools & Techniques of Root Cause Analysis, applying Sensitivity Analysis on these Critical X's will be extremely helpful to see how the focus metric Y, behaves by changing the values of each X under a set of predefined assumptions. This paves way to develop solutions in a more scientific method within the identified X's and a combination of this approach across all input causes will help us with a more comprehensive solution that can be implemented during the Improve phase. Let us now see an example. I am running a small coffee shop and below are my financial workings as on date Cost/Cup of Coffee - INR 12 Number of Cups of Coffee Sold per month - 4000 Operating Expense (incl. Rent, Salary, Milk, Sugar, Coffee power etc.,) = INR 40,000 Based on above workings my Monthly Income is INR 48,000 [12 per cup x 4000 cups per month]. My Profit after deducting the Operating Expense is INR 8,000 [Opex INR. 48,000 - Monthly Income 40,000]. I will now but a problem statement with a business case that I need to improve my Profits from this coffee shop. At an high level, if I want to put this in a mathematical format for my business case in Cause and Effect method Y=F(X), using Root Cause Analysis techniques, at an high level, we can say profits are influenced by price per cup, number of cups sold and the operating expenses. Profits = f(Price per Cup, Number of Cups Sold, Operating Expense, ...) I need to work on each of these levers either increase or decrease to improve my profits. While at an high level, going by thumb rule, we always say to reduce the Opex and it in itself can lead to another root cause analysis on what we can vs what we cannot. But looking at the other two levers of cost per cup and number of cups to be sold will form an interesting strategy to plan around and the Sensitivity Analysis will help me take a decision. With Sensitivity Analysis, I can play around by increasing or decreasing the price or increasing or decreasing the number of cups sold and its impact on my profit. As per the rules of Sensitivity Analysis, we make some assumptions and in this case we make an assumption that my Operating Expense will remain fairly at same price or allowed to go by not more than 10%. With this ground rule you can see the below table which helps you draw conclusion. I can now make some quick comparisons now. If I retain my current price of INR 12, but build strategies to increase sales to 5000 cups a month (increase in 1000 cups) I will make INR 20,000 profit vs my current profit of INR 8,000. Even an increase in Opex by 10% should still yield me INR 16,000 which is double my current scenario. Like wise if I want to retain the sale at 4000 cups and increase the price to INR 15 , I will have a similar story. In summary, with Sensitivity Analysis applied on Root Cause Analysis, it shows, how within each Inputs, you will have options to explore to arrive at a desired stable Output with Voice of Customer at crux.