The saying goes, “The only constant in life is change.” Except change is not constant.

As you’ve grown your business, have you noticed how the uncertainties and assumptions around each decision have increased, both in their number and their degree of uncertainty?

For example, if you offer a discount of 10%, how many more units must you sell to at least make the same profit. If you replace ageing, inefficient machines with new assets that contribute more to gross profit, what volumes are needed to compensate for the finance costs? Or in seeking to improve turnover, should you concentrate your capital on generating more leads, improving conversion ratios, managing margins, or reducing customer churn – for each additional rand spent, which area would yield the best return?

To cope with these complex decisions, a critical skill every entrepreneur needs is to be able to conduct at least a basic sensitivity analysis. In fact, if you’re a seasoned business owner, you’ve surely done some what-if analyses for your bigger, higher-impact decisions.

The basic model is to identify the key variables or inputs affecting your decision, identify the relevant outputs, then  build an algorithm that converts the inputs to outputs. With your model created, you simply assume your input values and calculate the expected output.

The value of the what-if analysis is in both validating your model and, ultimately, understanding how the variables influence the outcomes.

For example, if you operate an airline, 2 of the biggest costs affecting profits are fleet repayments or rental payments and the cost of fuel. Newer jets are significantly more fuel-efficient than older planes. But replacing a tired fleet would incur higher rental costs. So what would you do?

After modelling the key inputs, like volumes (passenger load factor (capacity utilisation), flights per day etc.), ticket prices, fixed and variable operating costs, a sensitivity analysis would help us see which input factors should be managed closely and which can be accepted and merely monitored.

The starting point we typically take to solve this conundrum is to first set a baseline for our assumptions of the most likely input values, then apply a basic what-if analysis of adjusting each input up or down by 10% and measuring the effect on the output value(s).

The input variable that causes the biggest change in output tells us which variable our business is most sensitive to.

There is much more available in doing sensitivity analyses, like multi-variable analyses and integrating the model with industry indicators or employee and customer behaviour changes. E.g. how might not investing in a new fleet of jets increase customer attrition when competitors’ shiny new models entice your customers away from you?

The greater the impact of your entrepreneurial decisions and the more ambiguities and assumptions involved, the more valuable a sensitivity analysis will be in managing change in your business.

For any entrepreneur building a business that feeds their wealth, a basic sensitivity analysis should be a frequently-used tool in the toolbox.