Value. It is always wanted, commonly discussed, occasionally conceptualized, yet infrequently operationalized or measured correctly. But if optimizing value is a goal, then value needs to be operationalized with an equation. As the saying goes, “you can’t manage what you can’t measure,” and individuals and organizations should not simply assume they will know value when they see it.
Value equations are typically written as fractions with quality or outcomes in the numerator, and cost (and sometimes time) in the denominator. In healthcare, for example, Harvard Business School economist Michael Porter (2010) suggests that value equals outcomes divided by cost. Yet equations like these are problematic on at least five levels.
1. Oversimplification
Quality (or outcomes) is typically multidimensional. For example, the quality of a diamond is measured by 4 Cs: color, clarity, carat, and cut. While each of a diamond’s 4 Cs is associated with an objective or somewhat objective measure, the weighting of each is subjective and varies from person to person and organization to organization. You know the saying: “Beauty is in the eye of the beholder.”
The numerator in the value equation is, then, a composite term that oversimplifies the inherent complexity of quality or outcomes measurement. As a simple construct, the value equation does not acknowledge that quality or outcomes represents an array of variables. Adding this notation to the equation would serve as a friendly reminder that quality or outcomes measurement is multifaceted.
Cost typically changes over time. These changes can result from pricing and contracting, which can vary across buyers and may, in turn, reflect the volume purchased or market access. It is important to note that the value equation is, then, a point-in-time measure that may apply only to a unique buyer or subgroup of buyers. Here, too, the value equation masks the complexities of reality.
The value equation also fails to account for how a buyer’s brand perception impacts perceived value. After all, the buyer’s perception is the buyer’s reality.
2. Extrapolation
The value equation is blind to the fact that the relationships between value and quality or outcomes, and between value and cost, are curvilinear. The equation erroneously suggests these relationships are linear. A quick thought experiment illustrates the diminishing returns of quality or outcomes. As quality or outcomes approaches and ultimately exceeds the desired level, the impact on value begins to plateau.
As noted earlier, the numerator should be represented as an array of variables. And while each of these variables would have an independent effect on value, some of these variables may have interactive effects as well. For example, a drug could be described in efficacy and safety terms, and separately, these terms might impact value. But an interaction between these terms — where safety impacts efficacy and possibly compliance or continuation — could generate nonlinear effects.
Then there is the interesting phenomenon related to price increases and decreases. As demonstrated by luxury goods and services, the exclusivity achieved by higher prices can increase perceived value. Similarly, when the price of a product or service is deemed too low, the quality may be questioned and its perceived value can fall. The generally assumed inverse relationship between cost and value is then more nuanced than a straight line.
3. Misspecification
Supply and demand can also impact the valuation of a product or service. When a new product or service addresses an unmet need, the value is arguably high. Individuals and organizations are often willing to spend more for novel solutions. Yet its value can drop when the market becomes more crowded, even when its quality and cost remain the same. The value equation fails to account for market context. Context matters.
Equations that clearly signal their incomplete nature often include an extra term representing everything else that impacts the dependent variable of interest — in this case, value. Alternatively, some models include an error term at the end that represents the unexplained variability in the dependent variable. Both of these approaches transparently acknowledge that the equation fails to explicitly identify all the drivers. In contrast, the value equation lacks terms representing “everything else” that can have an impact on value or an error term describing the unexplained variability in value.
4. Normalization
The value equation is expressed as a ratio. A ratio implies that the impact of a change in outcomes or quality on value is proportional to the impact of a change in cost. However, that is likely not the case. The units used to measure quality or outcomes likely vary and differ from the units (dollars) used to measure cost. For example, a 20% increase in quality may not have the same effect on value as a 20% decrease in cost.
The solution to this problem would be to normalize quality or outcomes and cost. In essence, normalization levels the playing field — allowing the numerator and denominator to compete fairly for their impact on value. Yet nothing in the value equation tells us that quality or outcomes and cost have been normalized.
5. Miscalculation
Another weakness of an equation expressed as a fraction is the problem when the denominator equals zero. Remember playing with a calculator and dividing a number by zero? You probably saw an “E” displayed — your first encounter with the funny reality that any number divided by zero is undetermined. More recently, you’ve probably seen “#DIV/0!” when dividing by zero in Excel.
It’s not difficult to find real situations in which the cost of a product or service is arguably zero for the buyer. A loss leader, subsidies, or a free trial are scenarios where cost arguably can be zero. And in these instances, the value equation cannot calculate value. If, instead of dividing by cost, the equation added the effect of cost along with the positive and negative effects of the other drivers of value, then value could be calculated when cost is zero.
The value of a flawed value equation
Of course, like all models, all value equations are wrong — even those that address the five problems above. But that does not render the value equation useless. If the flawed value equation does nothing more than remind buyers to consider both quality and cost, then it has served an important purpose.
Individuals and organizations that make the effort to account for flaws in the value equation are doing the hard but priceless work of thinking about value — a step on the road to realizing the value they desire.
Porter ME. What is value in healthcare? N Engl J Med. 2010;363;2477–2481.
No Comments