Even just a few years ago, conventional wisdom held that “innovation” and “operations” didn’t belong in the same sentence. Performance targets ruin the creative impulse. Science needs space, time, and freedom to flourish. Innovation can never be bottled into an efficient, machine-like operation.
That’s all true. But it misses the point. Of course innovation cannot be managed properly – if you intend to copy/paste operating models from other functions.
Thankfully, a more thoughtful approach is emerging. After decades of struggling to innovate, a new discipline of Innovation Ops has appeared within today’s corporations. It’s a new approach to innovation management suited to the prevailing dynamics of the information age. And it’s already taking root at companies like Westinghouse and Dow AgroSciences.
That’s a big attitude shift from the past, and in a short period of time. Here’s the three most important factors driving the change.
The proliferation of new innovation practices
We live in a very different world than even fifteen years ago. Across a wide range of industries, the pressure to innovate has increased – in some cases dramatically – leading to active and ongoing experimentation into how best to lead innovation. As a result, the number and type of new “innovation” tools, techniques, and practices has shot up exponentially, including:
Innovation Labs – to incubate and accelerate non-traditional innovation bets
Open Innovation – to access the best technologies and expertise around the globe
Lean Startup – to apply Business Model Canvas and similar practices within large companies
Design Thinking – to make sure that underlying customer needs guide the innovation process
The net effect is that most companies now contend with an alphabet soup of innovation initiatives, stakeholders, and internal priorities. Almost all such efforts are important and well-intentioned. Yet overlapping and poorly orchestrated innovation activities tend to cause a haze of confusion within the workplace. Sometimes they’re even in direct conflict with each other.
To combat mission creep, duplicative work, and wasted investments, a more coherent operating manual for innovation has become essential.
The rise of Knowledge Supply Chains
Since at least the industrial revolution, patterns of industrial innovation have evolved in generational cycles – fluctuating from large industrial labs in the Golden Age of Corporate Research in the 50s and 60s to the rise of an institutionalized startup economy over the past few decades.
The tectonic plates are once again shifting. Inside large corporations, the R&D function is digitizing, even as it continues to maintain excellence in traditional engineering disciplines. The practice of Open Innovation is now widespread. Previously siloed spheres of government, academic, industry, and startups increasingly work in conjunction with one another. Innovation has become a flexible, dynamic, global game.
Instead of relying solely on corporate R&D campuses (as in the mid-20th century), or staying focused only on acquiring startups (as in the early 21st century), the most innovative companies now orchestrate complex Knowledge Supply Chains – globally coordinated efforts that continually source both incremental and breakthrough opportunities.
As the next generation of practice takes shape, there is a fast-growing need to manage the operations of innovation with more rigor and visibility, much like the discipline of Supply Chain Management for physical goods and components.
The success of “Ops” disciplines in other functions
The same underlying causes that have elevated Innovation’s status has already been applied to other business functions with great success.
The term DevOps first began to appear about a decade ago. As software engineers will tell you, DevOps is more than just a name, it’s a philosophy for operating – one that prioritizes agile over waterfall, sprints over marathons. In the world of software development, the concept has become so popular that the metaphor has been extended well beyond its origins – everything from SysOps to Sales Ops. The common thread is a need to change the way business practices work in a software- and data-driven world.
As we’ve seen in this post, innovation practices in modern corporations are expanding and evolving in real time. The need for better coordination – for innovation to be fundamentally more agile, more distributed, and more scalable – now exists in almost every industry.
Innovation Ops is not, and never will be, a direct replica of DevOps or any other function’s “Ops” discipline. But the codification of key operating principles for corporate innovators is a necessary step for a function that is currently undergoing a generational transition.