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Brand Management

Accounting For Risk In Brand Management

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Accounting For Risk In Brand Management

Accounting for risk is an important part of informed and responsible marketing budgeting and planning. Simple net present value (NPV) analysis uses the expected values of sales and costs and ignores any variations in these numbers. There is an elegant simplicity to this approach that makes comparisons among alternative investments relatively easy and decision-making straightforward. If NPV is positive, the investment should be undertaken; if it is negative, it should be rejected. However, the single NPV number often hides important information about the riskiness of candidate investments.

The Future Is Unknown And Unknowable

In the words of economist John Kenneth Galbraith: “There are two kinds of forecasters: those who don’t know, and those who don’t know they don’t know.” Simply stated, virtually all forecasts are wrong, but some are more wrong than others. It is a near certainty that today’s estimates of future sales volumes, prices, costs, and competitor’s actions are going to be wrong.

However, just because they may be wrong is not a reason to ignore them. Rather, it is useful to acknowledge the likelihood of error and examine how changes in assumptions and potential estimation errors might affect the NPV of a particular investment. Two marketing actions that produce the same net present value when risk is ignored may differ substantially in the degree of risk involved. Prudent management decision-making would select the less-risky action in such a circumstance. Thus, there is a need to make some adjustment for risk when comparing alternative marketing investments.

As a first step, it is useful to ask whether risk will have a significant impact on an investment’s net present value. Many marketing investments carry very modest risks. This is because results can often be monitored in real time, at least by means of intermediate marketing outcomes, and can be modified or eliminated quickly. There is little point in doing a comprehensive risk analysis if the risk is negligible. A useful method for going beyond the information conveyed by a risk-adjusted NPV is sensitivity analysis.

There are various ways to adjust for risk. The simplest approach is to make a subjective assessment of risk based on what is known. Such “guesses” are fraught with problems. It is difficult for a manager to cognitively determine how the many factors that influence risk may interact to produce an outcome. Information that is already uncertain leads to even greater uncertainty when combined. Human judgment is fraught with biases. The following describes a number of common biases that separate marketing oriented leaders and professionals from the right decision.

Common Biases In Risk Estimation And Decision-Making

Affective bias: an emotional predisposition for, or against, a specific outcome or option that influences judgments.
Ambiguity Aversion: a preference for outcomes with explicitly stated probabilities over gambles with diffuse or unspecified probabilities.
Anchoring: estimation of a numerical value is based on an initial value (anchor) that is not sufficiently adjusted when arriving at a final answer.
Availability bias/ease of recall: the probability of an event that is easily recalled is overstated.
Certainty bias: a preference for sure things; tendency to discount uncertain events.
Confirmation bias: a desire to confirm one’s belief leading to unconscious selectivity in the acquisition and use of evidence.
Conjunction fallacy: The joint occurrence (conjunction) of two events is judged to be more likely than the constituent events.
Conservatism bias: failure to sufficiently revise judgments after receiving new information about an event under consideration.
Endowment effect: the disutility for losing is greater than the utility for gaining the same amount.
Equalizing bias: decision makers assign similar weights to all objectives’ or similar probabilities to all events.
Gain/Loss Bias: descriptions of a decision and its outcome(s) may result in different decision depending on whether the outcome(s) are described as gains or as losses.
Gambler’s fallacy/the hot hand: tendency to think that irrelevant information about the past matters when predicting future events, for example, that, when tossing a coin, it is more likely that “heads” comes up after a series of “tails”.
Ignoring base rate: ignoring base rates when making judgments and relying instead on specific individuating information.
Motivated Reasoning: the desire for a particular outcome or the desire to avoid a particular outcome leads to select use and weighting of information consistent with the desired outcome.
Myopic problem representation: an oversimplified problem representation is adopted based on an incomplete mental model of the decision problem.
Omission of important variables: one or more important variables are overlooked.
Optimism bias: a cognitive bias that causes someone to believe that they themselves are less likely to experience a negative event. It is also known as unrealistic optimism or comparative optimism. Optimism bias is common and transcends gender, ethnicity, nationality and age.
Subadditivity/super-additivity bias: When judging individual sub-events, the sum of the probabilities is often systematically smaller or larger than the directly estimated probability of the total event.
Sunk Costs: considering sunk cost when making prospective decisions.

Contributed to Branding Strategy Insider by: David Stewart, excerpted from his book Financial Dimensions Of Marketing Decisions.

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