Rosy and Gloomy Biases When Evaluating Consumer Insights
It’s easy to be either an Eeyore or a Pollyanna. Here’s how to take a more realistic view.
A third big idea in my book, Owning Game-Changing Subcategories: Uncommon Growth in a Digital Age, is the role that rosy picture and gloomy picture biases play in building a subcategory. The stakes are high. Backing a “must-have” idea that has serious deficiencies can result in not only a loss of resources but a loss of time and innovation momentum. Conversely, erroneously terminating ideas that would create a major growth platform may be even more costly.
What Is the Rosy Picture Bias?
The rosy picture bias assumes that customers will be as impressed with the new offering as its loyal brand champions and that any problems can be easily overcome. This bias has several causes. First, the innovation champion, someone who is focused on the “must-haves” for months or even years, may have obsessive optimism and fear that killing the initiative might be career damaging.
Second, there is perceived organizational commitment that creates a momentum that is hard to stop. Finally, the innovation may just feel like a winner, logically or emotionally, and may have a buzz in the marketplace, even with minimal or inadequate testing.
“The rosy picture bias assumes that customers will be as impressed with the new offering as its loyal brand champions and that any problems can be easily overcome.”
In the context of the rosy picture bias, the following questions need to be addressed and assumptions challenged:
- Are the “must-haves” real? Are they so appealing and differentiating to a worthwhile segment that customers will avoid buying or using offerings that lack that “must-have?” Or is it only an incremental innovation that will not create loyal customers? Do you have confidence backed by market testing?
- Is the market substantial enough? Can it be accessed? Is there a Plan B – a way to find new applications and segments if the going-in targets fall short?
- Will significant competitors be attracted if the subcategory will be a success? Can barriers be constructed that will inhibit them from entering or handicap them upon entry?
What Is the Gloomy Picture Bias?
The gloomy picture bias suggests that a proposed new subcategory initiative will be costly in time and resources, have an uncertain outcome and involve risk without a clear payoff. This bias may be supported by unfavorable evidence from the market and is influenced by a tendency for people to be risk-averse. Tversky and Kahneman’s Prospect theory (for which they won a Nobel prize) demonstrated that individuals do not make decisions rationally by selecting options with the highest expected value, because “losses loom larger than gains.”
That helps explain why firms tend to overinvest in incremental innovation and underinvest in “big” innovations with more uncertain returns. To avoid having the gloomy picture bias kill off subcategory ideas that could be the basis for uncommon growth, it is worthwhile to analyze some of the assumptions being made with questions like:
- Could disappointing test results be turned around by identifying and remedying problems internally?
- Are flawed offerings that have appeared in the market caused by obsolete technology or organizational limitations that do not apply to us? Digital readers for a long time just didn’t get traction. Then came Kindle, which sold over 1 million units in a year and showed that sales of prior products were not a predictor of Kindle’s market acceptance.
- If planned applications or markets are inadequate, could we have “Plan B” applications or markets that will support a business? There are a host of successful subcategories that occurred when an application or market was found after the original turned out to be inadequate.
- Might it be possible to scale a subcategory market that is initially too small? Could the offering be extended into new applications, markets, or product variants? Other brands, like Nike and Starbucks, have taken subcategory markets into the mainstream. Is this possible?
- Might it be feasible to create or find new assets and competencies? Other organizations have done it successfully or found partners to help.
The lesson is to be objective and analytical when testing assumptions. And a good way to sniff out rosy or gloomy picture bias, especially in the digital age, is simply to try it out. Get a prototype, a crude version of the concept and put it in a test market or even release it so learning can occur. The live version of the concept will evolve as corrections and improvements are made, and your decisions will be clearer.
The e-book version of Owning Game-Changing Subcategories is now available and the book itself will be available in early April.