Large companies and other institutions (universities, state governments, non-profits), are better managed than ever. Ironically, they are also less capable of dealing with important challenges.

Corporations, in particular, are too often focused on efficiency instead of resiliency. They are optimized for safety, predictability, and maintenance of what already exists. Their focus on capital efficiency is a deadly trap that creates fragility, not progress.

As a result, many of these businesses are not prepared to face the future — and are in greater peril than they seem, even if they don’t yet realize it.

The truth of the matter is we need scaled organizations to thrive, as they can solve important problems that small businesses simply cannot.

What the executive teams at these corporations must realize, then, is that successful innovation naturally emerges from deliberate inefficiency.

In short, these companies must harness the power of systematic experimentation to thrive in the face of an unknown future — one in which their competitive advantage can slip through their fingers, thanks to advances in technology, communications, and finance that are making it easier for small companies and individuals to disrupt the status quo.

Fail to do so, and they will merely engage in an illusion of innovation.

What is the "illusion of innovation"?

I have worked with dozens of Fortune 500 companies over the years to address the challenges of the innovator’s dilemma Clayton Christensen described.

My conclusion from that work? Most of the tools large organizations rely on to innovate do not produce the long-term change they seek and need. 

Innovation projects pursued inside corporations too often look like theater:‍

People acting busy doing something so executives can explain to the board and investors that innovation is definitely, without a doubt, a top priority

But when reviewed after the fact, most of the effort produces little impact.

It is too often “sound and fury, signifying nothing.” In many cases, this type of innovation theater investment is value-destructive, not neutral in its effect.

In other words? Large organizations would be better off doing nothing instead of pretending to innovate — instead of engaging in an illusion of innovation.

There is no one right innovation formula, or a right process or approach to bring a novel technological innovation to market.

That said, the most successful innovators think about business from first principles instead of as an opportunity to apply formulas.

Creativity within one's business results from collisions. More to the point, creativity results from taking an idea from one context and applying it to another.

And, often, the further you look outside your organization and immediate context, the more likely your mind is to be stretched to find creative solutions.

• Maybe you want to improve your company's existing products or services.
• Perhaps you want to create potentially high-performing adjacent offerings.
• Or it could be that you want to explore an entirely new, transformative innovation (e.g., a spin-off startup that solves a compelling problem) that requires a standalone lab or hub to experiment.

Whatever your goal, your business can avoid engaging in the illusion of innovation by creating new systems of governance, incentives, talent, and processes that are deliberately designed for running capital-inefficient experiments — experiments designed to challenge status quo thinking.

‍‍The value of deliberate inefficiency

Sooner or later, crisis always comes.

Over the long run, resiliency beats efficiency. Therefore, resiliency is a more productive long-term objective for scaled organizations.

Innovation can (and should) be directed at both efficiency and resiliency. Still, the pendulum often swings too far to efficiency.

This, in turn, leads to companies that are extraordinarily fragile and subject to shocks that deter sustainable, long-term growth and value capture.

The challenge is our scaled organizations are optimized for the preservation of what already exists (i.e., their core operating model) — not for building the new.

Put another way? These corporations are organized for:

• Seeking efficiency. They focus on enhancing team output and maximizing profits.
• Eradicating risk. They don't take big swings and stick to tried-and-true methods.
• Removing variance. They maintain fiscal responsibility to keep investors confident.
• Enhancing predictability. They want to clearly forecast revenue improvements.
  

Most of their incremental innovation (to the extent it succeeds at all) drives improvements in efficiency, not resiliency, and indeed not transformation.

It feels safe to "stick to the plan" because it promotes near-term stability. The issue? Too much efficiency inevitably leads to long-term failure.

This sizable and persistent challenge is at the root of plunging public confidence in the capability of large institutions — including corporations.

Scaled institutions seem less capable today than they once were at dealing with the big problems that confront us: pandemics, supply chain breakdowns, global climate change, access to essential resources, and other common challenges.

The answer to this problem, then, lies in embracing (some) chaos.

The idea that variation or volatility must be removed from companies for effective operation is unsound. Why? Because it constrains ingenuity.

It seeks to turn people into machines. It relies on a command-and-control system and hierarchy that does not enable flourishing and breakthrough empowering innovations.

Put plainly, it creates an illusion of safety but squelches insight.

Embracing transformative innovation

The trick in transformative innovation, like in certain kinds of investing, is to remember that it is the magnitude of correctness that matters, not the frequency.

This means you can be wrong a lot in the pursuit of transformative innovation, because — on the occasions when you are right — you are likely to achieve dramatic results. (Oftentimes, the creation of an entirely new, offshoot venture.)

Conversely, for scaled businesses, the frequency of correctness matters more than the magnitude. Leaders try hard to avoid anything that looks like a mistake.‍

These organizations' operating system — the culture, incentives, governance, processes, and talent — is optimized for scaled, efficient execution, not learning.

This tension is what makes truly meaningful, disruptive innovation so hard.

The secret to business resilience lies in creating structured systems that enable large-scale, big-magnitude correctness — but also frequent misses.

In the face of an unknown future, the best strategy for maximizing returns and minimizing risk is to run as many experiments as possible at the lowest possible cost per experiment — often through an innovation arm that is completely separate from the core business.‍

As Clayton Christensen said, “The worst place to develop a new business model is from within your existing business model.”

These corporate innovation teams are far too often subject to the same governance systems, metrics, and processes the scaled organization relies on to operate the existing business.

As a result, the innovation that does succeed ends up looking a lot like the existing business, not the transformation everyone hoped for.

All this context leads to a question:

What happens when a corporation tries to redirect the efficient machine toward the inherently inefficient activity of learning and seeking insight?

Scaled organizations depend on "deliberate strategy." Set a plan. Stick to it.

This works well when your business operates in an environment of high knowledge and low assumptions. Deliberate strategy is optimized for execution at a high and predictable level.

Empowering innovation, on the other hand, often requiring a radical departure from the core business, typically requires an “emergent strategy." This allows for agility, experimentation, and pivots — and all outside the constraints of core business operations.

Only when an emergent strategy is instituted can you enable your team members tasked to innovation projects to address opportunities, test assumptions, learn based on data and findings, and iterate in a way that leads to meaningful, radical innovation — not merely the illusion of innovation.