Premature Quantification

by Joseph Esposito

It’s standard practice nowadays to talk about “the business model.” This conversation takes place in companies large and small, for-profits and not-for-profits. The term doesn’t necessarily mean the same thing to everybody. For some, it’s a simple answer to the direct question, “How does this company make money?” For others, it refers to a sophisticated financial exercise, almost always performed (yes, performed, like complex gymnastics) with Microsoft Excel.

These Excel models have become works of art.

I saw one not long ago that consisted of a series of linked spreadsheets that covered assumptions and multiple scenarios. What happens if the average price received for Segment 9 drops by $0.32? Well, everything gets recalculated instantly; note in particular the changes in Segments 3, 11, and 26 and the impact on cash flow, which in turn will alter the borrowing rate—which of course was recalculated. It’s stunning—and cool.

This particular model had sufficient complexity to manage a transaction of some size—say, the acquisition of Reed Elsevier by GE (this rumor started here). But the particular case for which it was developed was for an Internet company with no revenue. And all the assumptions of the spreadsheet proved to be wrong.

Prediction Pitfalls

Welcome to the world of premature quantification, where the allegedly scientific appeal of numbers masks an absence of sufficient forethought and strategic intelligence. It is not curable by taking a little pill. Fixing the problem requires a major overhaul of organizational culture. I am not optimistic.

Premature quantification strikes for-profits and not-for-profits alike, though usually in different ways. In the for-profit world, the classic instances of the ailment take the form of a Christensen effect, with a financial analyst attempting to “model” a new venture and finding it lacking because it is not forecast to generate as much profit as the organization’s existing businesses.

This is not a trivial problem, and one has to feel some sympathy for companies that fall into this pit. Take Google, for example, which has a stunning high-margin business in advertising sales. Just about any new business Google gets into will have lower margins than the existing advertising business, which makes it hard to get into new activities, as they will make the company as a whole seem less profitable by some measures.

For such companies, the quantification is premature because the analyst cannot possibly anticipate all the ways a new capability could be deployed. Indeed, even Google had no idea how they were going to make money when they started. Had someone insisted on a detailed financial model at that time, the company might not have gotten its original venture funding.

If Google seems too exotic an example, think of what it must be like to review new opportunities at hugely successful publishing companies such as Reed Elsevier, John Wiley, Springer, and Wolters Kluwer. Dear Mr. (Ms.) CEO, the memo begins, I have a great idea for a new service that will deliver a whopping 5 percent return on sales!

Well, let’s move on to the next, the more serious, proposal. Most of the time that means acquiring another company. What this leaves out is the possibility that the 5 percent business could grow into a 20 percent business or better in the years ahead.

In not-for-profits, premature quantification appears to be a relatively recent development, as straitened financial circumstances have made funding bodies and governing boards demand greater “accountability.” That’s a great idea in theory. What it often means in practice is that staff members who have little experience with numbers (and who may have come to the nonprofit environment precisely because they sought a mission-based rather than a commerce-based professional life) now must quantify things they have never thought of in this way before.

One recourse is to hire a consultant (I personally have been the beneficiary of this many times), whose task it is to come up with the “business model” that will make everything seem just right. Of course, as a former colleague used to say, you can’t perfume a pig—a financial model is only as good as the thought that went into it, and rarely does that kind of critical analysis and strategic discussion get enough attention.

Seduction by Spreadsheet

Okay, let’s put this in numbers: The quantification of strategy should take up 1 percent of the time put into strategic exercises.

When I mentioned quantification to a friend recently, he remarked that the crisis on Wall Street would not have been possible without the widespread use of spreadsheets. How’s that again? His point was that the orderly presentation of financial data on spreadsheets invites the perception of greater certainty than may be justified. Thus, people made major decisions based on the appearance of careful analysis where in fact there was none.

An alternative strategy would have been to talk with some of the people who bought homes they could not afford before they bought them, and to talk with the mortgage brokers who gleefully lent them money. But that’s not “scientific.”

The democratization of finance has been a terrible mistake. Numbers are hard, as we know when we see our kids struggling in their algebra classes. Spreadsheets turn everybody into a wannabe financier.

I am not anti-quantification. Publishing companies of all kinds are full of people who impede their chances for success because they will have nothing to do with numerical estimates. They appeal to intangibles (“Nobody knows how many copies we will sell”) or to cultural mission (“We are here to do this kind of thing even if it will not make money”).

The real issue is the quality (and quantity) of the work before the financial model is put together. In fact, organizations have to create a culture of quantification, but the numbers have to be good numbers, and they have to support a deep analysis of strategy.

Try This Scoring System

What gets lost when the spreadsheets come out too early—and serves to put an end to the discussion of strategy—is the iterative nature of operating a business. Think of the Public Library of Science, which was launched with a business model (premium journals with high fees to authors and a demanding peer review system) that later proved to be financially untenable. When PLoS began to adjust its model, many critics declared (and some jeered) that PLoS didn’t have a sound business model; some went so far as to indict the very notion of open-access publishing.

They were wrong. After some false starts with pricing, PLoS launched PLoS ONE, which operates on an adjusted model (lower fees, higher acceptance rates, a different form of peer review), which is proving to be successful. What the critics failed to see is that the real business model, if that is the proper term, is not something easily rendered in financial forecasts, especially for early-stage enterprises.

The real model is the intuition and flexibility of the management, which performs an experiment, evaluates the results, adjusts the parameters, and tests once—and twice and three times—again.

Let’s tally one point for the creative individual; another point for the special dynamism of creative people working together; a point for serendipity; another for the social institutions that gave rise to the creative staff in the first place. You get no points for making a mistake, but five points for learning from a mistake; and ten points for learning from the mistakes of others. In the end it all adds up.

Joseph J. Esposito is an independent management consultant, the Portable CEO, providing strategic advice, operating analysis, and interim management in the area of digital media to publishing and software companies in the for-profit and not-for-profit sectors. He writes extensively on digital media and has been awarded research grants from the Hewlett, MacArthur, and Mellon Foundations.