Narrative and Numbers: The Value of Stories in Business (Columbia Business School Publishing)

by Aswath Damodaran

As I have wrestled with valuation questions, one of the most important lessons I have learned is that a valuation that is not backed up by a story is both soulless and untrustworthy and that we remember stories better than spreadsheets.

Stories not only help us connect with others but, as research indicates, they are far more likely to be remembered than numbers, perhaps because they trigger chemical reactions and electrical impulses that numbers do not.

good storytelling can make a huge difference in the success of a business, especially early in its life.

These developments have come with a cost, which is that the problem that you face in investing now is not that you don’t have enough data but that you have too much, often pulling you in different directions. One of the ironic consequences of this data overload is that, as behavioral economists have established conclusively, our decision making has become even more simplistic and irrational because we have all this data at our disposal. Another irony is that as numbers come to dominate so many business discussions, people are trusting them less, not more, and falling back on stories.

So let’s see where we stand. We relate to and remember stories better than we do numbers, but storytelling can lead us into fantasyland quickly, a problem when investing. Numbers allow us to be disciplined in our assessments, but without stories behind them, they become weapons of intimidation and bias rather than discipline. The solution is simple. You need to bring both stories and numbers into play in investing and business, and valuation is the bridge between the two, as shown in figure 1.1. Figure 1.1 Valuation as a bridge between numbers and stories.

How can you adapt and control storytelling in the context of valuing businesses and making investments? You begin by understanding the company you are valuing, looking at its history, the business it operates in, and the competition, both current and potential, it may face. You then have to introduce discipline into your storytelling by subjecting your story to what I call the 3P test, 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. Not all stories that are possible are plausible, and among all plausible stories, only a few are probable. Until this point, you are primarily on the storyteller’s turf, but you now have to follow up by explicitly linking your tested story to numbers that determine value, that is, the value drivers of a business. Even the most qualitative stories about corporate culture, management quality, brand name, and strategic imperatives can and should be connected to value inputs. It is those value inputs that should become the numbers in models and spreadsheets that lead to the value assessments on which you base your decisions. There is one final step in this process, and it is one that most of us find challenging. If you tell good stories, it is natural to get attached to them and to view any questioning of those stories as an affront. While it is good t...

I will classify narrative alterations into three groups: narrative breaks, in which real-life events decimate or end a story; narrative changes, in which actions or outcomes lead you to alter the story that you are telling in fundamental ways; and narrative shifts, in which occurrences on the ground don’t change the basic story but do alter some of its details in good or bad ways.

Early in the life cycle, when a business is young, unformed, and has little history, its value is driven primarily by narrative,

stories work best if they not only involve listeners but require them to think on their own and make their own connections.

If stories play to emotions and past experiences are skewed sometimes by false memories, you can see the advantages of introducing numbers into the conversation. When a storyteller has wandered into fantasyland, the easiest way to bring him or her back to Earth is with data that suggests the journey is either impossible or improbable. Similarly, when a story is so powerful that it overwhelms listeners, all it may take are a few pragmatic questions about what it will take to deliver the promised outcomes to bring listeners back to their senses.

From Aristotle I learned the importance of keeping the story simple, with a beginning, middle, and end, and not getting distracted.

Freytag made me understand the need to bring in both successes and reversals in a business story, since narratives without these are flat and boring. Campbell’s structure highlighted the importance of characters in the story and how audiences relate to the key narrator’s troubles and triumphs, a lesson that, in young companies at least, the story is as much about the founder or the person running the business as it is about the business. Finally, this version of the story brought home the realization that stories connect with audiences because they feed into all-too-human impulses.

Using the lessons from story structure and story types, here are the steps you can adopt to tell a better story. 1. 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. If your vision for the business in terms of what it does and where you see it going in the future is fuzzy or unformed, your story about it will reflect that confusion. This is true whether you are the CEO of a well-established business with a long history talking to equity research analysts or the founder of a start-up seeking venture capital money. In fact, as the founder of a start-up is so integral to the business, you are as much a part of the story as the business you have founded, and some introspection (on the role you hope to play in this venture) may be needed. 2. Understand your audience: Your business story may not be the same when you are talking to different stakeholders (employees, customers, or potential investors), because each has a different interest in the story. While employees may share your enthusiasm for the success of the business, they are just as interested or perhaps more so in how you plan to share that success with them and the personal risks they face from failure. Customers are more interested in your products than in your profits and want to hear the part of your story in which you explain how your product or service will meet their needs and what they w...

If numbers are dangerous because they come with the illusions of control, precision, and objectivity and can be easily imitated, how will adding stories to numbers reduce those problems? First, the nature of stories is that they are fuzzy and remind us that precise as the numbers look, changing your story will change the numbers. Second, that recognition also will dispel the notion that you somehow can deliver the numbers you have forecast, since stories can be changed by forces out of your control. Third, when you are forced to unveil the story that backs your numbers, your biases are visible not just to the rest of the world but to yourself. I also believe that the capacity to combine stories with numbers makes it more difficult for others to imitate you, if you are successful. Unlike models that can be easily copied, storytelling is more nuanced, personal, and difficult to replicate.

There are three steps in the data-to-information process, and this chapter will be built around these steps, since at each step there is both promise and peril. 1. Data collection: The first step is collecting the data. In some cases, this can be as simple as accessing a computerized database. In others, it will require running experiments or surveys. 2. Data analysis: Once the data has been collected, not only does it have to be summarized and described, but you have to look for relationships in the data that you can use in your decision making. It is at this stage that statistical analysis comes into play. 3. Presentation: Having analyzed the data, you have to present it, not only so others can see and use the information you have gleaned from the data, but so you yourself have a sense of what that information is.

Table 6.1 Market Analysis Category Questions Comments Growth How quickly is the overall market growing? In addition to looking at the average growth rate over time, you also want to detect shifts in the market across product lines and geographies. Are some parts of the market growing faster than others? Profitability How profitable is this business, in the aggregate? Look at profit margins (gross, operating, and net) and accounting return trends over time. Are there any trends over time in the profitability? Investing for growth What assets do companies in this business have to invest in, to grow? With manufacturing companies, investment is generally in plant, equipment, and assembly lines, but with technology and pharmaceutical companies, the investment may take the form of R&D. How much investment are companies making collectively in this business to generate their growth? How easy is it to scale up? Risk How much do revenues and earnings vary across time? Volatility in your revenues/earnings can be caused by macroeconomic variables, which can include interest rate, inflation, commodity price, and political risk, or from company-specific variables. What are the forces that cause these operating numbers to change? How much debt (or fixed commitments) do companies in this business tend to carry? What are the risks that companies in this business may fail? What is the trigger (debt payments due or running out of cash) that cause failure?

Table 6.2 Competitive Analysis Category Questions Comments Growth Are there big differences in growth across companies within the business? If companies in the business are growing at different rates, you are trying to assess whether it is related to size, geography, or market segment. If there are big differences, what are the determinants of these differences? Profitability Are there big differences in profitability across companies within the business? If there are big differences in profit margins across companies, you are looking to see what types of companies earn the most and which ones the least. If there are big differences, what are the determinants of these differences? Investing for growth Is there a standardized investment model that is used by all companies in the market? As companies grow in this business, you are checking to see whether their investing needs decrease (economies of scale and networking benefits) or increase (with more competition). If not, are there differences in profitability and growth across companies with different models? Risk Are there big differences in risk (earnings variability and survival) across companies within the business? You are interested in whether there are variations in risk (operating and survival) across companies, and if so, what causes those variations. If there are big differences, what are the determinants of these differences?

Once you have a story to tell about a company, the first test is to make sure your story is possible. As you will see later in this chapter, there are narratives that fail this very weak test, and these stories of course are destined for the business fairy-tale book. How, you might ask, would anyone be delusional enough to tell an impossible story? Caught in the heat of storytelling and surrounded by people who think like you, it can happen. 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. Not everything that is possible is plausible and many stories that pass the plausibility test flounder when put to the probability test.

Breaking down stories by using this spectrum also allows us to get perspective on how different investment philosophies think about investing stories and, by extension, investment value. Old-time value investors, weaned on the dividend-based valuation models in Ben Graham’s book on security analysis1 and brought up on the adage that you only invest in the known and predictable, will invest in “highly probable” narrative companies, complaining even then that they would prefer total certainty for those companies. More aggressive value investors may venture a little further down the probability path and invest in companies with lower probability outcomes at the right price. Growth investors have to be more willing to bet on plausible story lines and build them into growth projections, accepting the fact that these projections come with more risk. Later-stage venture capitalists tend to be bunched up toward the lower end of the plausibility spectrum, investing in companies that have promise and potential (another way to think of low-plausibility narratives). Early-stage venture capitalists are taking their chances on possibilities, knowing full well that only some of these possibilities will become plausible and fewer still will make it all the way to the probability end of the spectrum. Figure 7.4 captures the range of investment philosophies and where they fall in the possible to probable spectrum.

Let’s now add the twist that causes the deviation from rationality and makes both the entrepreneurs and VCs overconfident, the former in the superiority of their products over the competition and the latter in their capacity to pick winners. This is neither an original assumption nor a particularly radical one, since there is substantial evidence already that both groups (entrepreneurs and VCs) attract overconfident individuals. The game now changes, since each business cluster (the entrepreneur and the VCs that back his or her business) will now overestimate its capacity to succeed and its probability of success, resulting in the following. 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 extent of the overpricing will vary, depending on the following factors: 1. The degree of overconfidence: The greater the overconfidence exhibited by entrepreneurs and investors in their own products and investment abilities, the greater the overpricing. While both groups are predisposed to overconfidence, that overconfidence tends to increase with success in the market. Not surprisingly, therefore, the longer a market boom lasts in a business space, the larger the overpricing will tend to get in that space. In fact, you can make a reasonable argument that overpricing will increase in markets where you have more experienced VCs and serial entrepreneurs, since experience often adds to overconfidence. 2. The size of the market: As the target market gets bigger, it is far more likely that it will attract more entrants, and if you add in the overconfidence they bring to the game, the collective overpricing will increase. 3. Uncertainty: The more uncertainty there is about business models and the capacity to convert them into end revenues, the more overconfidence will skew the numbers, leading to greater overpricing in the market. 4. Winner-take-all markets: The overpricing will be much greater in markets in which there are global networking benefits (i.e., growth feeds on itself) and winners can walk away with dominant market shares. Since the payoff to success is greater in these markets, misestimating the probability of success will ha...

Every decade or so, this phenomenon of collective overpricing plays out in a young market—

Figure 7.8 The iron triangle of value.

The chapters leading into this one have been focused on telling a story about a company, one that fits the company’s circumstances and the business arena in which it operates, and the challenge you face is in how to reflect that story in value. While there are many ways you can do this, the most versatile framework, in terms of being capable of incorporating almost any story, is one that uses the structure of a valuation model. Thus, if you think of cash flows as your endgame, you can start by first estimating revenues as the product of the total market that you see the company aiming at and the market share that you estimate it will be able to command within this market. Multiplying these revenues by the pretax operating margin yields the operating income of the company, and netting out taxes generates the after-tax operating income. Netting out what the company has to reinvest to generate growth will result in the free cash flow. Finally, discounting these cash flows back to today at a risk-adjusted discount rate gives you value.

Figure 8.3 Connecting stories to valuation inputs.

To set the table for the comparison, let me start with an assessment of the differences between the valuation and pricing processes. The value of a business is determined by the magnitude of its cash flows, the risk/uncertainty of these cash flows, and the expected level and efficiency of the growth that the business will deliver. The price of a traded asset (stock) is set by demand and supply, and while the value of the business may be one input into the process, it is one of many forces, and it may not even be the dominant force. The push and pull of the market (momentums, fads, and other pricing forces) and liquidity (or the lack thereof) can cause prices to have a dynamic entirely their own, which can lead to the market price being different from value.

When valuing a business, you start by valuing its existing investments and then augment that value with the value created or destroyed by growth, before adjusting for risk in the cash flows. The steps involved are described in figure 9.1.

if the return on capital you generate is equal to your cost of capital, the terminal value will not change as growth changes, since growth becomes a neutral variable.

The macro variables that you can build corporate stories around are many, but the three that are most used are commodity, cyclicality, and country. In the first (commodity), you build a story around a commodity-driven company, with the commodity price being the central variable and the company’s expected response to commodity price changes determining value. In the second (cyclicality), the valuation is of a company, and the primary driver of operating numbers is the overall health or lack thereof of the economy. Thus, your story starts with the economy, with the company woven into it, and requires that you link your company’s prospects to how well or badly the economy does. In the third (country), the driver of value for the company is the country in which it is incorporated and where much of its operations are centered, with your views on the country having a much bigger impact on your value than your views on the company.

Instead, here are four lessons that I draw from this table: 1. Soaring narratives, soaring values: I know that some people view DCF models as inherently conservative and thus unsuited to valuing young companies with lots of potential. As you can see in table 14.8, if you have a soaring narrative about a huge market, a dominant market share, and hefty profit margins, the model will deliver a value to match. It also stands to reason that when you have big differences in value estimates, it is almost always because you have different narratives for a company, not because you have a disagreement on an input number. 2. Not all narratives are created equal: While I have listed multiple narratives, some of which deliver huge values and some of which do not, not all are equal. Looking to the future as investors, some narratives are more plausible than others and thus have better odds of succeeding. 3. Narratives need reshaping: The narrative for Uber that you develop is based on what you know today. As events unfold, it is critical that you check your narrative against the facts and tweak, change, or even replace the narrative if the facts require those adjustments, which was the point that I made in chapter 11. 4. Narratives matter: Success when investing in young companies comes from getting the narrative right, not the numbers. That may explain why some successful venture capitalists can get away being surprisingly sloppy with their numbers. ...

stories without numbers are just fairy tales and numbers without stories to back them up are exercises in financial modeling.