IT | Human-Centered Change and Innovation

A New Age Of Innovation and Our Next Steps

GUEST POST from Greg Satell

In Mapping Innovation, I wrote that innovation is never a single event, but a process of discovery, engineering and transformation and that those three things hardly ever happen at the same time or in the same place. Clearly, the Covid-19 pandemic marked an inflection point which demarcated several important shifts in those phases.

Digital technology showed itself to be transformative, as we descended into quarantine and found an entire world of video conferencing and other technologies that we scarcely knew existed. At the same time it was revealed that the engineering of synthetic biology—and mRNA technology in particular—was more advanced than we had thought.

This is just the beginning. I titled the last chapter of my book, “A New Era of Innovation,” because it had become clear that we had begun to cross a new rubicon in which digital technology becomes so ordinary and mundane that it’s hard to remember what life was like without it, while new possibilities alter existence to such an extent we will scarcely believe it.

Post-Digital Architectures

For the past 50 years, the computer industry—and information technology in general—has been driven by the principle known as Moore’s Law, which determined we could double the number of transistors on chips every 18 months. Yet now Moore’s Law is ending and that means we will have to revisit some very basic assumptions about how technology works.

To be clear, the end of Moore’s Law does not mean the end of advancement. There are a number of ways we can speed up computing. We can, for instance, use technologies such as ASIC and FPGA to optimize chips for specialized tasks. Still, those approaches come with tradeoffs, Moore’s law essentially gave us innovation for free.

Another way out of the Moore’s Law conundrum is to shift to completely new architectures, such as quantum, neuromorphic and, possibly, biological computers. Yet here again, the transition will not be seamless or without tradeoffs. Instead of technology based on transistors, we will have multiple architectures based on entirely different logical principles.

So it seems that we will soon be entering a new era of heterogeneous computing, in which we use digital technology to access different technologies suited to different tasks. Each of these technologies will require very different programming languages and algorithmic approaches and, most likely, different teams of specialists to work on them.

What that means is that those who run the IT operations in the future, whether that person is a vaunted CTO or a lowly IT manager, will be unlikely to understand more than a small part of the system. They will have to rely heavily on the expertise of others to an extent that isn’t required today.

Bits Driving Atoms

While the digital revolution does appear to be slowing down, computers have taken on a new role in helping to empower technologies in other fields, such as synthetic biology, materials science and manufacturing 4.0. These, unlike so many digital technologies, are rooted in the physical world and may have the potential to be far more impactful.

Consider the revolutionary mRNA technology, which not only empowered us to develop a Covid vaccine in record time and save the planet from a deadly pandemic, but also makes it possible to design new vaccines in a matter of hours. There is no way we could achieve this without powerful computers driving the process.

There is similar potential in materials discovery. Suffice it to say, every product we use, whether it is a car, a house, a solar panel or whatever, depends on the properties of materials to perform its function. Some need to be strong and light, while others need special electrical properties. Powerful computers and machine learning algorithms can vastly improve our ability to discover better materials (not to mention overcome supply chain disruptions).

Make no mistake, this new era of innovation will be one of atoms, not bits. The challenge we face now is to develop computer scientists who can work effectively with biologists, chemists, factory managers and experts of all kinds to truly create a new future.

Creation And Destruction

The term creative destruction has become so ingrained in our culture we scarcely stop to think where it came from. It was largely coined by economist Joseph Schumpeter to overcome what many saw as an essential “contradiction” of capitalism. Essentially, some thought that if capitalists did their jobs well, then there would be increasing surplus value, which would then be appropriated to accumulate power to rig the system further in capitalists favor.

Schumpeter pointed out that this wasn’t necessarily true because of technological innovation. Railroads, for example, completely changed the contours of competition in the American Midwest. Surely, there had been unfair competition in many cities and towns, but once the railroad came to town, competition flourished (and if it didn’t come, the town died).

For most of history since the beginning of the Industrial Revolution, this has been a happy story. Technological innovation displaced businesses and workers, but resulted in increased productivity which led to more prosperity and entirely new industries. This cycle of creation and destruction has, for the most part, been a virtuous one.

That is, until fairly recently. Digital technology, despite the hype, hasn’t produced the type of productivity gains that earlier technologies, such as electricity and internal combustion, did but actually displaced labor at a faster rate. Put simply, the productivity gains from digital technology are too meager to finance enough new industries with better jobs, which has created income inequality rather than greater prosperity.

We Need To Move From Disrupting Markets To Tackling Grand Challenges

There’s no doubt that digital technology has been highly disruptive. In industry after industry, from retail to media to travel and hospitality, nimble digital upstarts have set established industries on their head, completely changing the basis upon which firms compete. Many incumbents haven’t survived. Many others are greatly diminished.

Still, in many ways, the digital revolution has been a huge disappointment. Besides the meager productivity gains, we’ve seen a global rise in authoritarian populism, stagnant wages, reduced productivity growth and weaker competitive markets, not to mention an anxiety epidemic, increased obesity and, at least in the US, decreased life expectancy.

We can—and must—do better. We can learn from the mistakes we made during the digital revolution and shift our mindset from disrupting markets to tackling grand challenges. This new era of innovation will give us the ability to shape the world around us like never before, at a molecular level and achieve incredible things.

Yet we can’t just leave our destiny to the whims of market and technological forces. We must actually choose the outcomes we prefer and build strategies to achieve them. The possibilities that we will unlock from new computing architectures, synthetic biology, advanced materials science, artificial intelligence and other things will give us that power.

What we do with it is up to us.

Image credit: Pixabay

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innovvation starts here

Should innovation be spelled with two v’s instead of one?

With so many words starting with the letter v being so central to innovation and rolling up into two even more powerful v words, maybe we should spell it innovvation to help organizations remember to focus on the two keys to successful innovation:

Value
Veracity

The Importance of Value to Innovation

The first v in innovvation is value. Value is such an important v that you will hear me say often that Innovation is All About Value and is composed of three elements:

Value Creation is pretty self-explanatory. Your innovation investment must create incremental or completely new value large enough to overcome the switching costs of moving to your new solution from the old solution (including the ‘Do Nothing Solution’). New value can be created by making something more efficient, more effective, possible that wasn’t possible before, or create new psychological or emotional benefits.

Value Access could also be thought of as friction reduction. How easy do you make it for customers and consumers to access the value you’ve created. How well has the product or service been designed to allow people to access the value easily? How easy is it for the solution to be created? How easy is it for people to do business with you?

Value Translation is all about helping people understand the value you’ve created and how it fits into their lives. Value translation is also about understanding where on a continuum between the need for explanation and education that your solution falls. Incremental innovations can usually just be explained to people because they anchor to something they already understand, but radical or disruptive innovations inevitably require some level of education (often far in advance of the launch).

All of the details of what each of these three keys to innovation success are reside in my previous article Innovation is All About Value. It’s well worth the investment of time to read it.

The Importance of Innovation Veracity

A few years ago I wrote about the importance of innovation veracity and how when it comes to innovation, veracity is all that matters. As a quick refresher, let’s look at the definition of the word veracity from our friends over at Merriam-Webster:

Veracity

1: devotion to the truth : truthfulness
2: power of conveying or perceiving truth

So, veracity is the second v in innovvation. There is probably no better way to spend your innovation time than to spend it identifying the right customer insight and the right way to communicate the solution with customers which you’ve created to serve the insight.

For the three components below that will help you get to veracity, I must give credit to the documentary A Good American (a must see). I will stay away from the politics of the movie so I don’t give away the punchline, and just say that it profiles the work of a group of computer scientists who designed a system to protect American citizens from terrorism at a lower cost and with greater privacy protections than the system that was eventually funded and profiled in a different movie – Snowden.

It’s probably no coincidence that Oliver Stone was involved with both films, but that fact is of course irrelevant to the discussion here. What is important is that the film A Good American contains great monologues by the protagonist that provide insight into the power of meta data.

As an innovation coach what’s important to me so I can help a wide variety of clients, is not the particular context of any particular client, so much as the meta information in a variety of applicable tools and frameworks that I collect or create to serve them. What’s important are the insights that can be applied across all industries and all innovation contexts.

What I’ve been able to extract out of this particular film and into the innovation context, so that I can share them with you, are the protagonist’s view of three components that help you identify signals and drive the transformation of DATA into INTELLIGENCE (or innovation veracity in our context), and they are:

Volume – in order to derive meaningful conclusions you need a lot of data inputs, in this case, lots of idea fragments (ideas come later)

Variety – multiple perspectives are necessary to avoid blind spots and increase the potential for connecting idea fragments

Velocity – volume by itself is not enough, momentum is important too. You have to keep Stoking Your Innovation Bonfire

Conclusion

By focusing on value and veracity in our innovation efforts we will arrive at the most important goal of our innovation pursuits – and yet another v – Victory!

So dig deeply to understand where value comes from in your context, and then keep digging. Only when we truly understand the sources of value in any particular context can we create new sources of value for the value consumers in that context, create the proper means of accessing the value, and translate that value for people in the context and in adjacent contexts that might expand the consumption of the new value.

And strive to also understand the indisputable truths in your context that will enable you to achieve the veracity and the resonance you will need to renew the organization’s permission to exist in your context, fuel your continued success, and ensure your next victory.

Download the PDF version here:

Keep innovating!