Quantifying Uncertainty: Risk Analysis for Forecasting and Strategic Planning

By Brod, Daniel | Government Finance Review, June 1992 | Go to article overview

Quantifying Uncertainty: Risk Analysis for Forecasting and Strategic Planning


Brod, Daniel, Government Finance Review


In many respects public decision making has grown more complex in recent years. Public agencies find themselves increasingly influenced by the impacts of national and state legislation, budget constraints on operations, new regulations and growing demands for resources. As this changing environment becomes more complex, it requires the adoption of systematic approaches for evaluating the consequences of alternative management policies and external events. A more strategic orientation is becoming critical, particularly in the formulation of policy, both in the public and private sectors.

Strategic planning, as distinct from traditional approaches, is characterized by:

* a longer timeframe,

* an accounting for contingent developments

and uncertainties,

* linkages between planning and budgeting,

and

* a dynamic and continuing process.

Forecasts are the cornerstone of strategic planning. Budgets, revenues from taxes and other sources, the costs of projects--all are subject to some kind of forecasting process. There is one thing certain about any forecast: to some degree it will be wrong.

Because forecasts both form the basis for planning and are subject to uncertainty, there are two areas in which conventional forecasting may promote a negative effect in the smooth functioning of government. First, from the perspective of sound management, decision makers may be ill-served by their forecasts: while a forecast may represent a best guess, it does not inform as to the likelihood of the forecasted outcome being achieved nor does it provide insight into the probabilities of alternative outcomes occurring. This is crucial information for almost any management decision in government because it enables the manager to behave strategically. Managers can prepare for various contingencies and provide balanced reporting to both administration and constituents if equipped with the additional results cited above.

Secondly, forecasts can evoke public distrust and erode consensus. When there is no accounting for the uncertainties in a forecast result, this feeds the tendency to view forecasts as being biased in favor of the decisions which are based upon them. This tendency adversely affects the consensus for a public agency's chosen course of action. Not infrequently, that consensus is a key component for successful implementation. Moreover, if the forecasting process and its underlying assumptions remain undisclosed and obscure to the public, then consensus is undermined even further.

The techniques of risk analysis combined with a structured process of expert and public review have proven to be powerful tools which enable decision makers to successfully manage situations subject to uncertainty while building public confidence. Risk analysis modeling and the stages involved in expert and public participation in the forecasting process are described below. An example is presented illustrating how the Arizona Department of Transportation with Hickling Corporation and its Risk Analysis Process have applied these techniques in the forecasting of revenue from an excise tax for the finance of a new freeway system in Maricopa County.

Forecasting and Risk Analysis

Forecasting always involves uncertainty, and the farther into the future projections are made, the more uncertainty there is and the greater the risk of producing forecasts that deviate greatly from actual outcomes. Forecasts traditionally take one of two forms: first, a single "expected outcome," or second, one in which the expected outcome is supplemented by alternative scenarios, often termed "high" and "low" cases. Both approaches fail to provide adequate perspective with regard to probable vs. improbable outcomes.

The limitation of a forecast having a single expected outcome is clear--while it may provide the single best guess, it offers no information about the range of probable outcomes. …

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