Tax strategy: how to deal with uncertainty?

• Author: Hafkenscheid, Rutger

Introduction

More and more, companies are formulating and documenting an explicit tax strategy. As in any strategy, decisions made pursuant to a tax strategy have a long-term effect and thus involve uncertainty. To date, there is little literature on how to make strategic tax decisions under conditions of uncertainty. This article discusses the types of uncertainty that tax directors face when making strategic decisions and describes the techniques they can use to improve the decision-making process.

Corporate and Tax Strategy

The tax strategy of a company should support the company's overall corporate strategy. The corporate strategy, as well as the operational, marketing, and financial strategies all affect and help define the scope of the tax strategy.

Corporate strategy deals with more fundamental questions than the supportive ones like tax strategy. The three basic questions are: (1)

* what markets is the company in?

* what is the company's strategic posture, i.e., does it shape its future, adapt to market changes, or reserve the right to play?

* which courses of action does the company take, i.e., large bets, options, or no regret moves?

Corporate Strategy and Uncertainty

At each strategic level, the company faces uncertain futures. For strategic decision-making, Courtney identifies three uncertain elements in the future. The first element is that of clear trends--e.g., demographics that help define potential demand for future products and services. The second element consists of factors that are currently unknown but that could in fact be knowable with the right analysis. Examples are performance attributes of current technologies and elasticities of demand for stable categories of products. The third element is the uncertainty that remains after the best possible analysis has been done, called residual uncertainty, e.g., the future market demand for innovative new technologies. To analyze residual uncertainty, Courtney distinguishes four levels of uncertain futures (displayed nearby), each with their own analytical techniques

Level 1: A Clear-Enough Future

Here, the residual uncertainty is in fact irrelevant for strategic decision- making. Forecasts will be sufficiently narrow to point to a single strategic direction. Consider a funeral insurance company in the West European market. Demographic factors determine market size and insurance losses, while market share and income from investing insurance premiums can be forecast with relative accuracy. Because residual uncertainty is small, strategic decisions can be made with the traditional strategy toolkit, including net present value and internal rate of return calculations, and the calculation of pay-back period.

[ILLUSTRATION OMITTED]

Level 2: Alternate Futures

At this level, the future can be described as a few discrete scenarios. Analysis cannot identify which outcome will occur, but probability analysis will shine light on a well defined limited number of outcomes. The residual uncertainty is larger than in Level 1, but most of the outcomes are determined by either clear trends or knowable uncertainty. Consider the Big Four accountancy firms, which together form an oligopoly, dominating the accountancy market for multinational corporations, with a high entrance barrier and a strong lobby with regulatory bodies. For them, uncertainty lies in the unpredictability of their competitors' strategies, which can be analyzed with techniques like game theory and option valuation models. Techniques to value strategic options are expected value calculations, mini-max regret and basic Monte Carlo simulations.

Level 3: A Range of Futures

At Level 3, a range of potential futures can be identified, defined by a limited number of key variables, but with outcomes lying anywhere along a continuum bounded by that range. There are no natural discrete scenarios. Although parts of the variables determining the strategic outcomes can be identified as clear trends and knowable futures, a substantial number of variables fall within a wide range of values. Consider a telecom company that needs to decide whether to bid for a mobile telecom licence in the African market. Market research might identify only a broad range of potential customers, say from 10 percent to 30 percent of the population, and there would be no obvious scenarios within that range. Strategic decisions will be supported through scenario planning and real options valuation.

Level 4: True Ambiguity

At this level there is no basis to forecast the future. Level 4 situations are rare, but do exist. Examples of this type of uncertainty are the strategic decisions made by biogenetic companies and market entry for consumer...