Exponential Organizations: Why new organizations are ten times better, faster, and cheaper than yours (and what to do about it)

by Salim Ismail

The key outcome when you access resources and information-enable them is that your marginal costs drop to zero. Quite possibly the granddaddy of information-based ExOs is Google, which doesn’t own the web pages it scans. Its revenue model, the butt of many jokes ten years ago, has enabled Google to become a $400 billion company, a milestone it reached by essentially manipulating textual (and now video) information. LinkedIn and Facebook together are worth over $200 billion, and that’s just as a result of digitizing our relationships—that is, turning them into information.

Sources of this Big Data are emerging everywhere. For example, we mentioned the three separate initiatives for low Earth orbit (LEO) satellite systems that within a few years will deliver real-time video and images anywhere on the planet. Despite the inevitable privacy and security concerns bound to arise with the launch of LEO satellite systems, there is no doubt that scores, even hundreds, of new businesses will emerge from access to this massive new information source.

Remarkably, and often tragically, most companies today are still driven almost solely on the intuitive guesses of their leaders. They may use data to guide their thinking, but they are just as likely to fall prey to a long list of self-delusions—everything from a sunk-cost bias to a confirmation bias (see below for a list of cognitive biases). One reason for Google’s success is that it is more ruthlessly data-driven than most other companies, right down to its hiring practices.

This technique is popularly known as the Lean Startup movement, which was created by Eric Ries and Steve Blank and is based on Ries’s book of the same name. The Lean Startup philosophy (also known as the Lean Launchpad) is in turn based upon Toyota’s “lean manufacturing” principles, first established a half-century ago, in which the elimination of wasteful processes is paramount. (Sample principle: “Eliminate all expenses with any goal other than the creation of value for the end customer.”)

University of Michigan economist Scott Page found that diverse teams are more successful at answering complex questions than are homogenous groups or individuals, even if the homogenous groups and individuals are more talented. His conclusion, however, shouldn’t be all that surprising. Charles Darwin discovered that evolution progressed fastest wherever small groups of a species isolated from the main population adapted to stressful conditions. By the same token, small, independent and interdisciplinary teams are critical to future organizations, especially at the edges.

“We want hardware to be as easy as software.” Indeed, hardware is increasingly dissolving into software.

Starting in the 2000s, startups could test the market like never before by leveraging A/B testing, Google AdWords campaigns, social media and landing pages. Now an idea could be partially validated before product engineering even began.

Credit: Alexander Osterwalder. For more on how to create effective value propositions, we recommend reading Osterwalder’s new book, Value Proposition Design: How to Create Products and Services Customers Want.

For example, let’s look at the financial services industry. A classic bank offers many services such as payment infrastructure, trust, mobile and social wallets, e-commerce and m-commerce solutions, lending, investments, stocks, etc. It is a consolidated or aggregated offering of different individual financial services. Those banks are now being disrupted by a variety of financial startups, including Square, Clinkle, Stripe, Lending Club, Kickstarter, eToro and Estimize. We consider this fragmentation of individual financial services a form of unbundling. Now, what if all these startups decided to cooperate or merge within the next five years? What if they agreed to create alliances via open APIs? What if they partnered and rebundled? You’d end up with a completely new bank with at least 10x less overhead than that of its predecessors, as the new entity would require less real estate and fewer employees.

In an illuminating exercise conducted in 1998, IBM asked a hundred blue-chip company chief information officers if they used open source software in their companies. 95 percent said no. Yet when interviewers asked the same question of those companies’ systems administrators, 95 percent answered yes, an outcome that led IBM to make a major strategic shift into open source. Celebrated—even recognized—or not, open source software runs the Internet (and thus the world) today.

A key differentiator for Google Ventures is its use of data analytics and algorithms to assess deals. The company employs seven data scientists who collect and analyze as much data as possible before deciding where to invest. As Maris said, “We have access to the world’s largest datasets you can imagine. Our cloud computer infrastructure is the biggest ever. It would be foolish to just go out and make gut investments.” Other firms, such as Sequoia Capital and Y Combinator, are taking note and adapting quickly.

For example, Google recently demonstrated that its best employees were not Ivy League students, but rather young people who had experienced a big loss in their lives and had been able to transform that experience into growth.

According to Google, deep personal loss has resulted in employees who are more humble and open to listening and learning.