Uncertainty and Flexibility
In Area D in Exhibit 1.4 fall the situations that form the background of an evaluation: the scenarios can be credibly delineated and it is likely that management can take the necessary steps or seize the opportunity offered by change.
With regard to the situations referred to in Area C of Exhibit 1.4, change does not arise as a disruptive and intermittent phenomenon, but can lead back to the observable dynamics of the present.
As an example, in the valuation analysis of an important business in the spirit industry, the team doing the business analysis had described two scenarios. The first assumed decreasing sale volumes, consistently with the life cycle of a mature industry as observed in other firms within the same industry. The second one assumed instead, due to the strong brand value, a constant sale volume not affected by the general trend in the industry.
Given the notoriety of the brand and the strength of the commercial network of the business, it was unlikely to assume that management would have reacted passively to a reduction in sales. More realistically, it would have differentiated the products between the traditional ones and the new ones (“white” spirits, etc.).
Therefore, considering the operational flexibility permitted by the strength of the brand, the unfavorable scenario was modified assuming, after an initial decrease in sales, a return to the original levels with slightly lower margins given the increase in advertising costs.
The example shows a typical process of financial analysts, which translates into an upgrading of expectations in comparison to the industry due to the strength points of the business that confirm the hypothesis that the management can effectively react to unfavorable market conditions.
Obviously, the opposite reasoning also holds: when the firm under valuation is weaker than competitors, the average industry expectations can be modified and generate worse scenarios.
Growth opportunities for firm Alpha can also fall in Area D of Exhibit 1.4. Entering the business of packaging for cosmetic products and offering new services to pharmaceutical companies are a natural evolution of the core business of Alpha. Alpha has in fact adequate technological and managerial resources to sustain growth in those businesses which are similar to the niche in which it already has a leadership position.
1.5.2 Some Conclusions on Uncertainty and Managerial Flexibility
The approach outlined in the previous paragraph departs from traditional analysis since it tries to contemplate whether, with different scenarios, the firm's business model can be adapted to new assumptions and what those assumptions imply in terms of the creation of value.
From a historical standpoint, the first attempts to assess managerial flexibility, when future opportunities in the evolution of a business exist, have concerned themselves with R&D investments, brand and patent acquisition, development of new technologies, and the research and exploitation of natural resources. These attempts assume as a starting point the explicit representation of a firm's results as a consequence of managerial decisions expected to be taken in the future. Generally speaking, these methodologies today fall into the field of so-called real option valuation (ROV).6
In this framework, the value of a project is just the sum of two elements:
1.5.3 Valuing Companies Assuming a Dynamic Standpoint
The dynamic approach was first used in valuations of Internet companies and Internet stocks.
Looking at the background in which the so-called new economy– related ventures originated at the end of the nineties, we can identify the typical characteristics referable to area C of Exhibit 1.4:
● The operators' expectations assumed strong growth in the market.
● A high degree of uncertainty characterized the assumptions about Internet users' behavior and technological evolution.
● Entry barriers on the market were modest: Internet companies could have adapted the business model to eventual shifts.
After the radical U-turn in scenarios and expectations with respect to high-tech stocks, in the first half of 2000, the dynamic valuation models have been harshly criticized. Despite many excesses, the euphoria that drove markets and the analysts has left us an important contribution: the models adopted and the debate that followed have brought attention, also out of the academic studies, to the fact that managerial flexibility can be an appreciable factor in the valuation of businesses and acquisitions, and not only in well-defined investment niches (R&D, natural resources search and development, etc.). On the practical side, the key issue of the dynamic approach is the need for restricting the analysis only to the credible development of a business model.
1.6 RELATIONSHIP BETWEEN VALUE AND UNCERTAINTY
The basis for the determination of the cash flow that best represents the future expected performance of the business lies in the analysis of the risk profile of the business itself. This section aims at classifying some typical situations of uncertainty, and at representing the cash flows that best describe them. Exhibit 1.7 provides us with a general initial reference framework, which by the way proves useful in multiple valuation settings as well by enabling the expert to carry out a more refined comparability assessment.
Exhibit 1.7 Risk profiles and cash flows modeling
Exhibit 1.7 shows how valuations of businesses whose financial results are driven mainly by market factors or macroeconomic parameters are based generally on a single cash flow profile, referring to the scenario that management deems the most likely one (“management scenario”).
These valuations yield accurate results only when the distribution of expected results is symmetric. This condition is satisfied, for example, when the relevant risk factors depict a continuous distribution. Furthermore, it should be noted that such cash flow representation type requires historical data be both available and reliable. When there are multiple risk factors, the traditional representation centered on the management scenario may lead to undesired informational gaps.
Simulation techniques, like for instance the Monte Carlo, may in these cases improve the informational quality through the use of numerous combinations of the risk factors, yielding different expected results and different related results and valuations.
A second case is represented by the businesses subjected to idiosyncratic risks, which by their own nature are characterized by discrete (and at an extreme binary) outcomes distribution (e.g., businesses whose activity is based on the renewal of a concession). In these situations, the informational quality increases by projecting a cash flow pattern in each of the major scenarios that could take place. In practice, a final valuation can be obtained by weighting the valuations obtained in the different scenarios. As said, it is worth stressing the fact that this proceeding is sensible in those situations when risks have discrete distributions. Otherwise, the applicable case turns back to scenario A, which envisages the representation of the cash flow profile of only the most likely scenario.
For some businesses (case C of Exhibit 1.7), which are typically articulated along distinct sequential phases, risks
