The idea or concept of added value is different in the eyes of clients, but also in the eyes of financial modelling professionals. Especially in the current economic climate, there is an even bigger need for professionals to demonstrate the added value they provide to clients.
One area of value-adding importance is incorporating sensitivity analysis into your best practice financial model.
Sensitivity Analysis in a nutshell
It is an approach in financial modelling to conceptualise how varying values of an independent variable, will alter a specific “dependent variable under a given set of assumptions” (Investopedia.com 2012). It is highly value-adding to a financial model because it enables users to ascertain, the impact the actual outcome of a specific variable will have, if it changes from its given and assumed number.
A basic example would be to understand the impact on net income, as a result of changing the corporate tax rate, which would alter the corporate tax expense on a company’s pre-tax income.
The immense value of Sensitivity Analysis
A sensitivity analysis can be applied to a financial model in many ways. As discussed, undertaking a sensitivity analysis on a company’s net income, by flexing the corporate tax rate is a high-level example. A more detailed and micro approach to sensitivity analysis would be where a service-based company wants to analyse the forecasted return from a new contract. It may want to compare a preliminary contract price, and compare it to hypothetical changes in certain key drivers; in order to compare and improve expected financial returns.
As the above example demonstrates, the following company can understand the overall impact of a $750 increase in the “Course Enrolment Fee per Student”, coupled with a 25% decrease in the number of “Full fee-paying Students”, delivers an overall drop in forecasted earnings from the contract being analysed.
Dashboard to compare Sensitivity outputs against Base case
Your best practice financial model can go one step further. The model can leverage its existing dashboard functionality and deliver further value. A fine example is a dashboard that can compare the above sensitivity outputs against base case, which in this case is a service company’s base service price, sales volumes etc.
The following Waterfall Chart can demonstrate this. This Model can generate such a chart in terms of Gross Profit, EBIT, Net Profit After Tax (NPAT) or Operating Cash Flow; in this instance the Gross Profit option has been selected to reveal the previously analysed increase of $750, but offset by a 25% decrease in the number of “Full fee-paying Students” decreases Gross Profit from $174,590.0 to $152,590.0.
In addition, under Incremental Costing; EBIT falls from $159,718.9 to $137,718.9 and NPAT from $111,704.9 to $96,304.9, and Full Costing falls from $149,804.9 to $127,804.9 and NPAT from $104,765.0 to $89,365.0.
The addition of sensitivity analysis into a best practice financial model can provide immense added-value to the analysis of a company’s financials. As defined, it is a tool for financial modellers to apply, in order to better ascertain and forecast financial returns based on the manipulation of independent variables. It helps management to get a better sense of the revenue or cost drivers influencing financial returns of a company.
Finally, the incorporation of the sensitivity analysis into the Dashboard features of a financial model further reinforces via a high-level graphical summary, how certain independent variables can be flexed to alter financial returns.