Narrative and Numbers: The Value of Stories in Business

by Aswath Damodaran

To be a successful business, not only do you have to build a better mousetrap, but you have to tell a compelling story about why that mousetrap will conquer the business world to investors (to raise capital), to customers (to induce purchases), and to employees (to get them to work for you).

The first is that you follow simple rules in collecting data, including judgments on how much data and over what time period, and look for ways to avoid or at least minimize the biases that can find their way into that data. The second is to use basic statistics to make sense of large and contradictory data and statistical tools to fight data overload. You may be one of those people who remembers your statistics class from college fondly and puts it to good use when you have lots of numbers in front of you, but if so, you are more the exception than the rule. For too many of us, sadly, statistics is the forgotten discipline, making us vulnerable to data manipulation. Finally, you have to come up with interesting and innovative ways of presenting the data to make them understandable to those who might not grasp the statistical nuances.

starting with the question of whether your story is possible, a minimal test that most stories should meet; moving on to whether it is plausible, a tougher test to overcome; and closing with whether it is probable, the most stringent of the tests.

when listeners are absorbed in a story, they become more willing to accept arguments uncritically, that is, to drop their guard.

In business education, storytelling is a key part of all teaching and it has been formalized in the case study approach.

The single, central, most important way we screw up [is that] we tell ourselves too many stories, or we are too easily seduced by stories. And why don’t these books tell us that? It’s because the books themselves are all about stories. The more of these books you read, you’re learning about some of your biases, but you’re making some of your other biases essentially worse. So the books themselves are part of your cognitive bias.9

In his telling, which he based on his observations of Greek theater, every story needs a beginning, a middle, and an end, and what keeps a story going is that the incidents within the story are linked together by cause and effect. For the story to have an effect, the protagonist should see a change in fortune over the course of the story. It is amazing how well that structure has held up through time.

In the first one, overcoming the monster, you have the underdog, usually smaller and perceived to be weaker, beating out an evil adversary. A rebirth is a story of renewal, in which a person is reborn to live a better life. In a quest, the protagonist goes on a mission to find an item or thing that will save him or her and perhaps the world. It is what makes myths like Lord of the Rings and Star Wars so appealing to audiences. A rags-to-riches story is about transformation, with someone or something who is poor and weak rising to become wealthy and powerful. In a voyage and return, the characters embark either intentionally or accidentally on a journey of discovery that ends with them returning, usually wiser, happier, or richer, to their point of origin. In comedy, the intent is to make you laugh with the players or at them as they stumble through life’s

challenges, and in a tragedy you get the flip side: the objective here is to make you cry.

Understand your business and know yourself: As a storyteller, it is difficult to tell a story about a business if you don’t understand the business yourself.

The notion that numbers are scientific and more precise than stories is deeply held, and as a result of this belief, the revolution that Billy Beane brought to baseball has spread far and wide.

Unlike models that can be easily copied, storytelling is more nuanced, personal, and difficult to replicate.

I break the number-crunching process into three parts, starting with the collection of data, moving on to the analysis of that data, and ending with presenting the data to others.

Put simply, the law of large numbers states that as sample sizes get larger, your computed statistics from that sample get more precise. If that sounds unreasonable, the intuition is that as sample sizes get larger, the mistakes you may have on individual data points get averaged out.

One of the outgrowths of the surge in social media sites is the development of more sophisticated techniques for reading, analyzing, and storing qualitative data.

The other challenge in sampling is survivor bias, that is, the bias introduced by ignoring the portions of your universe that have been removed from your data for one reason or another.

In general, survivor bias will be a bigger issue with groups that have high failure rates, thus posing a more significant problem for investors looking at tech start-ups than for those looking at established consumer product companies.

The outlier problem: The problem with outliers is that they make your findings weaker. Not surprisingly, the way researchers respond to outliers is by ridding themselves of the source of the trouble. Removing outliers, though, is a dangerous game; it opens the door to bias, since outliers that don’t fit your priors are quick to be removed, but outliers that do fit your priors are maintained. In fact, if you view your job in business and investing as dealing with crises, you can argue that it is the outliers you should be paying the most attention to, not the data that neatly fits your hypothesis.

Once you have a story to tell about a company, the first test is to make sure your story is possible.

The second test is determining whether the story you are telling is plausible, a stronger test. For a story to be plausible, you have to provide some evidence that it can happen, by pointing first to other companies that have pulled it off and then to your own history to make a case that you are similar to these successful companies. The third and toughest test is determining whether the story you are telling is probable, and that requires that you be willing to quantify your story and make your best estimates of how your story will play out in numbers.

First, the businesses targeting the big market will be collectively overvalued. Second, the marketplace will become more crowded and competitive over time, especially with new entrants being drawn in because of the overvaluations. Thus, while revenue growth in the aggregate may very well match expectations of the market being big, the revenue growth at individual firms will fall below expectations and operating margins will be lower than expected. Third, the aggregate valuation of the sector will eventually decline and some of the entrants will fold, but there will be a few winners, and those entrepreneurs and VCs will be well rewarded for their investments.

The collective overvaluation of the companies in the big market will look like a bubble, and the correction will lead to the usual hand-wringing about bubbles and market excesses, but the culprit is overconfidence, a characteristic that is almost a prerequisite for successful entrepreneurship and venture capital investing.

The intrinsic value is the value you would attach to an asset based upon its fundamentals: cash flows, expected growth, and risk.

Marginal return on capital = Change in operating income/ Reinvestment This marginal return on invested capital is a rough measure of how good you think your company’s investments will be in the future. If it is too high or too low, and that judgment can be made by comparing it with the company’s cost of capital, its historical return on capital, or industry averages, it is a red flag that you should revisit your growth and reinvestment assumptions.

I have had my own struggles with letting go of my favorite stories, and while I don’t have a miracle cure, there are two actions that open me up for change. The first is to tell my story to the groups that are least likely

to like that story and allow them to air their disagreements. The second is to be open about the uncertainty that I feel in my own story and how it plays out in the resulting estimates and value.

In particular, narrative breaks represent an end to a story that might have had promise at some stage, but no more. Narrative changes make significant modifications to the story that you have for a company, and with those changes can come large changes in value. Narrative shifts are much smaller alterations that nevertheless will show up as increases or decreases in value.

If you are an investor trying to determine where the payoff from investing will be greatest for you, in addition to gauging your storytelling and number-crunching capabilities, I would suggest that you look at how well you deal with uncertainty and being wrong.