The what-if analysis can support decision makers along the investigation of a set of alternative approaches to forecast or estimate according to the context of the application.
The design of the analysis
Designing a what-if analysis requires a methodological framework able to detect the true levers to pull in the hands of analysts or even end-users. According to the literature, the following list may be considered as the theoretical skeleton for approaching effectively a what-if analysis:
- Goal analysis, aimed at determining which business phenomena are to be simulated, and how they will be characterized. The variables must be identified according to the level of granularity and impact on the goal analyzed;
- Business modeling, which builds a simpliﬁed model of the application domain to help the designer and end-users to understand the business phenomenon as well as give her some preliminary indications about which aspects can be either neglected or simpliﬁed for simulation;
- Data source analysis, aimed at understanding what and where information can be extracted;
- Multidimensional modeling, which deﬁnes the multidimensional schema describing the prediction by taking into account the static part of the business model produced at phase II and respecting the requirements outlined in phase 1;
- Simulation modeling, whose aim is to deﬁne, based on the business model, the simulation model allowing the prediction to be practically structured, for each given scenario, from the source data available;
- Data design and implementation, during which the multidimensional schema of the prediction and the simulation model are implemented on the chosen platform, to create a pilot for testing;
- Validation, aimed at evaluating, together with the end-users, how the simulation model fits the real business model and how reliable the prediction is. What-if analysis is not a one-way process, but it has to be iterated seeking for the best possible fit. The higher this fit, the more effectively analysts can actively manage the simulations.
A data-driven approach to the strategy execution
In this environment, the most successful businesses over the next decade will be those able to execute strategy better than their competitors by exploiting data to ensure the right alignment with strategy formulation. The execution is the result of thousands of decisions made every day by employees acting according to the information they capture from data inspecting and modeling.
In this scenario, advanced analytics on a wide range of data could be a source of competitive advantage in the decision making process and measurement activities. A what-if approach in key financial and business processes allows being always prepared to sudden changes driven by independent variables impacting on business performances.
A what-if analysis in corporate finance processes
To build a set of scenarios that reflect different assumptions on future macroeconomic, industry or business developments seem to be the right approach to a “fair” company’s valuation. Empowered with a robust model, senior management can use the sensitivity analysis to understand how changes in key inputs can impact on the value creation theme. In a preliminary phase, two steps should be executed:
- Assessing the impact of individual drivers: start by testing each input one at a time to see which has the largest impact on the company’s valuation;
- Analyzing trade-offs: strategic choices typically involve trade-offs between inputs into a valuation model (i.e. raising prices leads to fewer purchases, lowering inventory results in more missed sales).
Then, when it comes to analyzing scenarios for company’s valuation within a DCF model (Discounted cash flow), it is fundamental to critically review assumptions. In the valuation field, this can be stretched along many variables. Here below a graphical representation of the analysis is presented. The marginal variations of the weighted average cost of capital (WACC) and the growth rate impact directly the EV via the formulas of corporate valuation.