Financial Policy Strategy in Times of Uncertainty

Financial Strategy in Times of Uncertainty


We endorse the notion that early preparation for severe scenarios is more cost-effective than winging it or reacting far too late. Additionally, in our almost four decades of existence, we have always advocated that business and financial strategies must walk pari passu. Companies in a comfortable financial situation can and should design financing strategies to support their business plans. Companies facing financial difficulties need to adapt their operational plans to fit their financial cash flows. This makes financial policy execution key in providing the right set of tools for the company to navigate through difficult times.

Preparation starts with the development of a robust business plan, also known as a static analysis, that incorporates the most accurate estimates for the company’s investments and their outcomes. This business plan should be compared and parameterized, taking into account the company’s historical results, the performance of its peers, as well as market expectations for the economy and the specific sector.

With that in hand and with a clear idea of the areas that need to be analyzed—such as capital structure, target dividend policy, minimum cash level, and credit rating—we can begin to sensitize the key variables of the financial model in order to understand their impact on the various dimensions of our business, such as its cash flow, dividends flow, and value.

This simulation can be performed in two non-mutually exclusive ways that differ from each other in the number of “rounds/scenarios” to be analyzed. The first one is the construction of alternative scenarios (optimistic/pessimistic) in addition to the static analysis. As a result of this exercise, we end up with three or more scenarios while the number of assumptions grows exponentially. It is at this point that we combine our expertise with that of the firm’s management to determine and assign probabilities to each of the scenarios and subsequently to compute the probability-weighted results.

This exercise is frequently eye-opening for the company and results in various and very important questions that management will look to answer such as “What is the maximum probability of loss we can bear?” or “For a given a probability, what is the maximum expected loss?” and even “Between two strategies with the same expected value, should we opt for the one with greater or lesser dispersion of results?”

We then move into the dynamic analysis in which the same key variables are sensitized thousands of times, with the aim of obtaining not only one or three points as in the static and scenario analyses respectively, but a distribution of results, providing a much richer view for financial decision-making.

So, which of the approaches is the most appropriate for my situation? The answer will depend on the robustness of the financial forecasting methodology as well as the quality of the assumptions. To get actionable results, the information going into the analysis must be reliable. If the quality of the information is low, the results will not be meaningful. In finance we call this GIGO, which stands for Garbage In/Garbage Out.

Restricting factors should also be cautiously considered. For example, contractual, legal, tax, and regulatory restrictions on the movement of resources within a conglomerate are relevant but often ignored. In some cases, a company cannot send its cash to another entity, and it is our role to consider these factors in order to provide results and recommendations that adhere more closely to the reality of the company. This approach can, for example, provide more grounded decision-making in situations in which the value of the sum of the parts differs from that of the consolidated company.

Now that we have gone through the static and dynamic analyses, we can return to the original question of this article of how to define a financial strategy in a context of great uncertainty. The short answer is that uncertainties need to be incorporated into the financial modeling, either through greater dispersion of key business premises, macroeconomic assumptions, and/or by the inclusion of discretionary, potentially black-swan-type events that are frequently discarded as outliers but indeed occur from time to time.

The static and dynamic analyses are the underlying basis for the recommended financial policy. This policy designed to maximize the levered enterprise value which is defined as the sum of the present value of: (i) unlevered cash flows of the company, (ii) impact of tax shield, (iii) tax planning implications, (iv) direct costs of financial distress, and (v) indirect costs of financial distress. A financial policy can go into various areas or topics such as hedging, debt management, optimal capital structure, risk management, and dividend policy. In pragmatic terms, such policies will translate into a mix of instruments designed to address the current uncertainty, such as revolving financing (to increase liquidity), new credit lines at reasonable rates, and renegotiation with customers and suppliers.

In our view, the recommended preparation and financial policy execution can act as an insurance policy for our clients. It may marginally increase the economic costs of the company short-term, but it will be a worthwhile investment for when an acute economic situation materializes and the cost of navigating the crisis becomes financially unbearable.

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