Stories are powerful — they were probably a key factor in our species’ evolution, and they’re undoubtedly an important tool in any leader’s toolbox. However, they can also be dangerous, because they can be misleading in subtle ways. These include but are not limited to the following: they tend to make success and failure seem more predictable than they actually are (hindsight); they assert causation where only correlation exists; they look at data sets in blunt, unsophisticated ways; they’re often based on anecdotes; they explain “success” based on factors that many failures in the same cohort display. Don’t ignore stories — but approach them with a critical, skeptical eye.
There’s no doubt that stories are powerful tools. In Sapiens, historian Yuval Harari argues that the ability to craft stories helped humans cooperate to achieve unprecedented progress and ultimately dominate the world. Today, it’s inconceivable that a product launch, a startup pitch, a popular documentary, or a TED Talk doesn’t feature captivating stories.
And with good reason: Stories offer multiple advantages. They help us discern complex matters, remember ideas, communicate with others, and make predictions about the future. It’s important for managers and entrepreneurs to harness these benefits and HBR offers a wide range of content designed to improve storytelling skills. But, precisely because of their potent and lasting effects, it’s crucial for decision makers to recognize the different ways in which stories can be misleading.
Authors like Nassim Taleb and Tyler Cowen have provided many warnings about narratives that underrepresent uncertainty and distort our understanding of causality. In HBR articles, Hilary Austen reveals how the allure of stories can lead to biased evaluations and irreversible mistakes in business, and Jonathan Gottschall shows how stories misled decision makers about the truth behind Theranos. In our book The Myth of Experience, we discuss the fact that it’s easier to write and embrace the wrong story than to ignore it. Hence, especially when tackling critical problems and consequential decisions, it pays to become a story skeptic.
Some stories simplify reality by warping or ignoring the effect of time. Thus, a first set of warning signs involve time-related biases.
Hindsight. Narratives generated after a certain result emerges typically downplay alternative scenarios that could have happened but didn’t. As a result, stories tend to make success and failure seem more predictable and deterministic than they actually are. Yet even outcomes that seem the most obvious in hindsight are often uncertain at the time of the decision. For example, groundbreaking ideas such as photocopying, the modern PC, Google, or Harry Potter felt like foregone conclusions after their immense success. But they were all initially rejected by expert investors, who stood to gain fortunes from them. In fact, in many cases, not even the owners of ideas can accurately predict their own potential. Xerox failed to invest in their own pioneering PC technology, and in its early days, Google tried to sell itself for a tiny fraction of its eventual value.
Correlation mistaken for causation. Stories can suggest causality between contemporaneous and correlated events, even when such a link doesn’t actually exist. Urban legends like the Sports Illustrated cover jinx stem from such misperceptions. When an athlete or team makes it to the cover but subsequently underperforms, the magazine gets blamed, even if this result would be expected due to regression to the mean. Similarly, managers can form faulty beliefs about the effects of praise and punishment, especially when the best performers they praise go on to perform worse, and the worst performers they punish subsequently improve. Faulty connections between successive events also fuel conspiracy theories like the supposedly causal links between some vaccines and autism, or certain newly developed technologies and the coronavirus pandemic.
Myopia. Some stories fail to spot an existing relationship when causes and effects are far apart in time. Many strategies, like vaccination or the adoption of a new technology, don’t show their effects immediately. To make things more complicated, some investments feature worse-before-better dynamics, which can easily be missed or misinterpreted by stories. Shortsighted narratives lead new leaders to receive acclaim or blame for results occurring right after their appointment even though they may actually be due to previous administrations. Such myopia can prompt management to opt for quick fixes that merely relieve symptoms rather than effective long-term cures.
Expiration. Stories are based on the past, so they can quickly become obsolete when situations change suddenly and dramatically. However, the traditions built on them often persist beyond those expiration dates. Only a few decades ago, a college degree would almost certainly guarantee a lucrative career. This is no longer true, but this notion is one cause of the growing student debt crisis. Stories are especially short-lived when processes grow non-linearly, leaving competent decision makers asleep at the wheel. Blockbuster, Myspace, and Nokia all seemed invincible a short time before their rapid downfalls.
Some stories simplify reality by omitting a crucial part of the picture. Thus, a second set of warning signs involve selection biases.
Averages. Data-based analyses and scientific findings are frequently storified to allow for easier transmission and understanding. However, many such presentations oversimplify reality by limiting discussions to average statistical effects. As a result, one may expect a certain strategy to boost profits, more education to increase income, and grit to produce success. Stories based on these causal links could also fit one’s prior beliefs. Yet they would only be valid for the average of the samples on which they are based and might hide significant risks and nuances around that expected outcome.
Anecdotes. It’s appealing to induce overarching stories from personal experience and striking episodes. However, these are just small samples that tend to be unrepresentative. In fact, given wide ranging variabilities in circumstances and personalities, the more unique an observation, the less likely it is to generalize. Many organizations have thus started to favor data-based algorithms over experience-based narratives when they tackle complex decisions. For instance, Michael Lewis’s Moneyball is about the unreliability of anecdotal and experience-based stories when assessing potential performance in baseball.
Survivors. Learning from success stories is both fun and motivating. Analyses of the common traits of successful people and organizations are ubiquitous. However, this approach overlooks the fact that these same traits may be equally prevalent in the not-so-successful. Especially when the success rate is low, stories tend to emphasize how uniquely talented and hardworking the successful are. Yet they conveniently ignore scores of failures with similar skills and work ethics, who didn’t achieve the same level of success for all sorts of circumstantial and random reasons. As a result, narratives that suffer from survivorship bias lead to a false belief that success is more controllable and predictable than it is.
Outcomes. Stories often focus on observable outcomes while ignoring underlying processes. One consequence is a widespread blindness to possible deceptions and unethical behaviors that contributed to those outcomes. There’s an extensive list of long-running and popular stories based solely on successful outcomes that eventually revealed their dark sides. These cases involved Ponzi schemes, opioid crises, and fraudulent business practices, among other transgressions. Yet another consequence of outcome-based stories is a misunderstanding of how innovation works. Narratives on creativity typically glorify the final versions of successful ideas along with a few flashy creators, while ignoring most of the underlying intricate collaborative processes conducted by scores of risk-taking entrepreneurs. As a result, innovation seems more individualistic and deterministic than it really is.
Unfortunately, there are at least two further complications beyond these warning signs. First, some stories can feature a combination of them. They may, for instance, focus exclusively on the successful outcomes of a few surviving anecdotes with the benefit of crystal-clear hindsight. The more warning signs a story shows, the more skepticism is warranted. And second, time-related biases and selection problems can occur even when stories are otherwise factually correct. What we know in hindsight, the final outcomes we observe, and the correlations or the average effects we estimate can indeed be true. Hence, stories can be misleading despite providing information.
The solution to the problems of storytelling isn’t to stop telling stories or to ignore them completely. That would deprive us of their vital benefits. Instead, astute decision makers can use stories to their advantage by taking convenient and convincing narratives as theories to be scrutinized, rather than truths to be followed. They would use these warning signs to test, refine, and then update relevant narratives. This would incentivize storytellers to be more careful as they craft their messages. Hence, story skepticism could eventually lead to better and more valid stories, improving our collective learning and decisions.
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December 17, 2020 at 09:08PM
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Don't Let a Good Story Sell You on a Bad Idea - Harvard Business Review
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