The ultimate significance of our work will be revealed only over time. We have high hopes for our longevity and impact because our work falls very neatly into a well-established pattern for the transformation of tacit, intuitive knowledge (art), into codified, well-understood, explicit rules (science). We believe we are playing a leading role in a growing field (new venture predictive analytics), which is transforming the management of new venture innovation from an art to a science. We also believe our version of new venture predictive analytics, will become the standard platform for the full life cycle of a mid or long term new venture initiative.

Today, only skilled experts or lucky entrepreneurs with impeccable timing can cobble together successful new ventures. Their work proceeds through intuitive trial and error experimentation at customer levels. The significance of the evolution of competitors’ motivations/means, and the evolution of technology systems/subsystems is rarely factored. Today’s creation/design processes are incomplete, costly, time consuming, and ultimately unreliable 80 percent of the time; unfortunately, there is little alternative when reliable theories are not in place. New venture innovation and investment still looks very much like this today. Investment decisions and tactics are typically based on intuition; learning, if it happens at all, is only at the products/customer level. The now popular lean start-up and open innovation methods are simply new forms of trial and error experimentation at the customer level. Here is how Wim Soens, director of R&D and Innovation at CogniStreamer, Inc. describes conditions today:

“Shaping radical ideas – in order to turn them into concepts is quite “fuzzy” and not fully understood by process designers. The current state-of-the-art in this domain is still at an experimental stage, and no real standards or best practices have been defined yet.”

Entrepreneurs, corporations, corporate venture capital (CVC) and venture capital (VC) alike live a perpetual contradiction, convinced on a case-by-case basis that the new venture they have just launched or financed will succeed even as they cannot escape the fact that 80 percent of all new ventures – including theirs – ultimately fail. Incumbents’ practices are built primarily on management team experience. This narrow model has made it very hard to learn how to succeed at new venture innovation. Clayton Christensen, the Harvard professor proclaimed by Forbes as the most important strategic thinker in the past 50 years and author and creator of the Disruptive Innovation Theory has this to say about conventional new venture investment practices:

In the face of [new venture] uncertainty, some widely accepted rules of thumb have emerged. For example, a mantra for most venture capitalists is that it is folly to make investment decisions based upon the start-up’s technology or business model. The VCs have concluded from their trials and errors that even they – the best in the world – cannot predict in advance whether the plans described in a start-up’s business plan will actually work. As a result, they typically assess – intuitively – whether the management team has the intuition to succeed. If members of the team are experienced and perceptive, the VCs reason, they can develop the right technology and business model- because they and only they will have the instinct to change direction when needed. As far as affecting outcomes in a meaningful and predictable way, however, this approach ranks up there with “feed a cold, starve a fever.” It is little more than an aphorism based on selective memory, the force of repetition, and the hope that at least it does no harm. Christensen’s work is one of the inspirations and insights responsible for our success.

The field of medicine offers a great analogy for our work. Here, Clayton Christensen weighs in again:
When we cannot properly diagnose the underlying disease effective care generally can be provided only through the intuition and experience of highly trained (and expensive) caregivers – medicine’s equivalent of Warren Buffett.
At the other end of the spectrum, we define precision medicine as the provision of care for diseases that can be precisely diagnosed and for which the underlying causes are understood. This makes it possible to develop a predictable effective therapy. Most infectious diseases live here: we have dispositive tests for their presence and well-understood and highly effective treatments for their cure. We can all but guarantee an outcome for an individual; exceptions are rare and noteworthy.

Not all of medicine falls into the “intuitive” and “precision” category, however. There is a broad domain in the middle called empirical medicine. The diagnosis and treatment of a pathology falls into this third category when a field has an incomplete but still very valuable set of causal models and validated patterns. The connections between actions and outcomes are consistent enough that results can be usefully, if imperfectly, predicted. We are in the realm of empirical medicine. Empirical medicine enables caregivers to follow the odds. They can generally guarantee the probabilistic outcome only for a population.

The methods of empirical-based front-end invention have been with us for the last 5 years. Strangely, most executives remain intoxicated with their fuzzy, front-end mind-sets and methods. This intoxication has proven lethal. Here’s why. It excuses everyone. It provides a screen for incompetence. After all, how does any invention process that is perceived as inherently “fuzzy” and “artsy” repeatedly produce output that needs to be “precise” and “predictable” within the time frames demanded today? And so, this negative, fuzzy, front- end thinking actualizes negative results. Ironically, along the way it has emboldened the lives of consultants, CEOs, managers, and venture/private equity capitalists (think the “thousand men guarding the past”).

Their raisin d’etre has hinged on their clients or stakeholders accepting the fact that shaping ideas for high- growth ventures is at worst a slot machine process and at best a process that can only succeed on the intuition and experience embedded in the black-box of senior executives’ minds. Gary Loveman, Chairman of the Board and CEO of Harrah’s entertainment, describes this conventional wisdom associated with people in powerful positions:

Decision making, especially at high levels, not only fails to demand rigor and dispassionate analysis, but often champions the opposite as the scarce talent that identifies CEO’s and visionaries from otherwise smart but less inspired people.

Conventional mind-sets and methods continue to waste resources, and they are always justified as “the cost of doing business” or the “cost of being innovative.” But this is a key point: businesses cannot afford to waste resources.

On September 23, 1999, NASA’s $300 million Mars Orbiter entered Mars atmosphere at the wrong angle and destroyed itself in the process. Later, NASA discovered the cause of the calamity. Someone, somewhere, failed to convert units from metric to English. The same thing happens in new-venture design. One person is using one ontology or set of models and someone else is using another ontology and model set. What’s worse is they don’t even realize they are doing it. Consequently, there is no connection, no understanding, and no progress. They somehow build their product, but they never align or assess correctly the underlying assumptions. How could they? Different ontologies and models are used, and no one is even aware it is going on. Result—a lot of time and money is spent during product and market development, and inevitably the team and its investors discover, “Houston, we have problem.”
Ventureland, We Have a Problem!

New ventures and new-growth initiatives fail 80% of the time. Our Company accepted the challenge 15 years ago to determine “why” new venture failure rate is 80% and do something to fix it. Our research covered the fields of finance, management, leadership, technology evolution, innovation practices, design, and psychology. When it was all synthesized, one factor stood out as both the “problem” and “solution”—theory. The problem we found was new venture theory-making has been driven by “tacit” theory models (below the level of awareness) held by “founders” and “investors” operating off their own experiences, assumptions, and stories (picture the Mars Orbiter). This “gut feeling” theory making is like “art” or “alchemy.”

This alchemy is pervasive and perverse. It’s given us what we got—80% failure rate. Now, the evolution of alchemy-based innovation to chemistry-based innovation is at hand. In this new view, the front end of venture innovation requires the use of the scientific method. Unfortunately, step one of the scientific method requires a hypothesis which in turn requires a “theory of success” for a venture idea. Our firm has codified venture theory.