Tag Archives: COVID19

The Breakthrough Lifecycle

GUEST POST from Greg Satell

Many experts suspect that the COVID crisis is receding into the background. It is, of course, hard to know for sure. There will continue to be debate and we will still need to have some mitigating measures in place. Still, for the most part, people are back at work, kids are in school, and relatively normal routines have returned.

Generations from now, historians will most likely still question what lessons are to be gleaned from the past few years. Should we strengthen our multilateral institutions or have they become so sclerotic that they need to be dismantled? Is the rise of populist nationalism a harbinger for the future or a flash in the pan?

One thing I don’t expect to be hotly debated, in fact seems perfectly clear even now, is that science saved us. Untold thousands, working mostly anonymously in labs around the world, created a vaccine of astonishing efficacy in record time. It is these types of breakthroughs that change the course of history and, if we can embrace their power, lead us to a better future.

A Seemingly Useless Idea

The MRNA technology that led to the Moderna and Pfizer-BioNTech vaccines have the potential to revolutionize medical science. It can rapidly reprogram the machinery in our cells to manufacture things that can potentially cure or prevent a wide range of diseases, from cancer to malaria, vastly more efficiently than anything we’ve ever seen before.

Yet while revolutionary, it is not at all a new idea. In fact Katalin Karikó, who pioneered the approach, published her first paper on mRNA-based therapy way back in 1990. Unfortunately, she wasn’t able to win grants to fund her work and, by 1995, things came to a head. She was told that she could either direct her energies in a different way, or be demoted.

This type of thing is not unusual. Jim Allison, who won the Nobel Prize for his work on cancer immunotherapy, had a very similar experience when he had his breakthrough, despite having already become a prominent leader in the field. “It was depressing,” he told me. “I knew this discovery could make a difference, but nobody wanted to invest in it.”

The truth is that the next big thing always starts out looking like nothing at all. Things that really change the world always arrive out of context for the simple reason that the world hasn’t changed yet.

Overcoming Resistance

Humans tend to see things in a linear fashion. It is easier for us to imagine a clear line of cause and effect, like a row of dominoes falling into each other, rather than a series of complex interactions and feedback loops. So it shouldn’t be surprising that, in hindsight, breakthrough ideas seem so obvious that only the most dim-witted would deny their utility.

When we think of something like, say, electricity, we often just assume that it was immediately adopted and the world simply changed overnight. After all, who could deny the superiority of an efficient electric motor over a big, noisy steam engine? Yet as the economist Paul David explained in a famous paper, it took 40 years for it to really take hold.

There are a few reasons why this is the case. The first is switching costs. A new technology almost always has to replace something that already does the job. Another problem involves establishing a learning curve. People need to figure out how to unlock the potential of the new technology. To bring about any significant change you first have to overcome resistance.

With electricity, the transition happened slowly. It wouldn’t have made sense to immediately tear down steam-powered factories and replace them. At first, only new plants used the electricity. Yet it wasn’t so much the technology itself, but how people learned to use it to re-imagine how factories functioned that unlocked a revolution in productivity gains.

In the case of mRNA technology, no one had seen a mRNA vaccine work, so many favored more traditional methods. Johnson & Johnson and AstraZeneca, for example, used a more traditional DNA-based approach using adenoviruses that was much better understood, rather than take a chance on a newer, unproven approach.

We seem to be at a similar point now with mRNA and other technologies, such as CRISPR. They’ve been proven to be viable, but we really don’t understand them well enough yet to unlock their full potential.

Building Out The Ecosystem

When we look back through history, we see a series of inventions. It seems obvious to us that things like the internal combustion engine and electricity would change the world. Still, as late as 1920, roughly 40 years after they were invented, most American’s lives remained unchanged. For practical purposes, the impact of those two breakthroughs were negligible.

What made the difference wasn’t so much the inventions themselves, but the ecosystems that form around them. For internal combustion engines it took a separate networks to supply oil, to build roads, manufacture cars and ships and so on. For electricity, entire industries based on secondary inventions, such as household appliances and radios, needed to form to fully realize the potential of the underlying technology.

Much of what came after could scarcely have been dreamed of. Who could have seen how transportation would transform retail? Or how communications technologies would revolutionize warfare? Do you really think anybody looked at an IBM mainframe in the 1960s and said, “Gee, this will be a real problem for newspapers some day?”

We can expect something similar to happen with mRNA technology. Once penicillin hit the market in 1946, a “golden age” of antibiotics ensued, resulting in revolutionary new drugs being introduced every year between 1950 and 1970. We’ve seen a similar bonanza in cancer immunotherapies since Jim Allison’s breakthrough.

In marked contrast to Katalin Karikó’s earlier difficulty in winning grants for her work, the floodgates have now opened as pharma companies are now racing to develop mRNA approaches for a myriad of diseases and maladies.

The Paradox Of New Paradigms

The global activist Srdja Popović once told me that when a revolution is successful, it’s difficult to explain the previous order, because it comes to be seen as unbelievable. Just as it’s hard to imagine a world without electricity, internal combustion or antibiotics today, it will be difficult to explain our lives today to future generations.

In much the same way, we cannot understand the future through linear extrapolation. We can, of course, look at today’s breakthroughs in things like artificial intelligence, synthetic biology and quantum computing, but what we don’t see is the second or third order effects, how they will shape societies and how societies will choose to shape them.

Looking at Edison’s lightbulb would tell you nothing about radios, rock music and the counterculture of the 60s, much like taking a ride in Ford’s “Model T” would offer little insight into the suburbs and shopping malls his machine would make possible. Ecosystems are, by definition, chaotic and non-linear.

What is important is that we allow for the unexpected. It was not obvious to anyone that Katalin Karikó could ever get her idea to work, but she shouldn’t have had to risk her career to make a go of it. We’re enormously lucky that she didn’t, as so many others would have, taken an easier path. It is, in the final analysis, that one brave decision that we have to thank for what promises to be brighter days ahead.

All who wander are not lost.

— Article courtesy of the Digital Tonto blog
— Image credits: Pixabay

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Stringing Together an Innovation Story

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How convergence and creative collisions fuel invention

Stringing Together an Innovation Story

GUEST POST from John Bessant

It was the Covid lockdown that did it. Got me into compulsive listening. As my physical world contracted so I spent more and more time taking voyages inside my head, carried along by music. These days the choice of vessels in my harbor is impressive; I can embark on a whole series of different journeys depending on my mood — jazz, classical, soft folky reminiscence or driving angry rock. But whatever the journey there’s a pretty good chance a guitar will feature somewhere in the mix.

(Confession; I’m a guitar player, have been since I was twelve years old and managed to persuade my parents to let me trade the trumpet I was learning as part of the school orchestra for a six string I’d seen in a shop window).

Even allowing for my bias and your many different musical tastes, you’d probably agree that taking the guitar out of our aural landscape would leave it a poorer place

And it would certainly be a commercially poorer one as well — the market for guitars is booming. It’s currently worth around half a billion dollars and is estimated to grow steadily. Covid-19 was an important sales agent, nudging millions of people to try and fulfill their dreams of converting air guitar playing to the real thing. Fender, one of the biggest names in the industry, had the best sales of its 80 year history during 2020 while James Curleigh, CEO of market leader Gibson, commented that during that year “we literally couldn’t deliver enough. Everything we were making, we could sell!”

But how did the guitar get here? And what role did innovation play in the process?

It’s an instrument with a long history — in fact if you take the idea of stretching strings across some kind of frame and letting the vibrations conjure sounds then we’re back at least three thousand years. There’s a stone carving of a Hittite musician entertaining at a Babylonian party in the Ancient Orient Museum in Istanbul and what he’s playing looks suspiciously close to being a guitar. It clearly didn’t take long for others to catch on the concept of the ‘chordophone’ (to give the technical term for a device which generates sound in this fashion). The Greeks and Romans had their harps and lyres, the Egyptians adding the lute, originally developed in Mesopotamia. And the Moors of north Africa have the oudh, an instrument with a lute-like body and a long neck, probably based on a dried gourd and later fashioned of wood. As it journeyed across to Spain it morphed into what we’d recognize today, a multi-stringed wooden necked device. Encyclopaedia Britannica has the origins of the Spanish guitar as something emerging in the 16th century, deriving from the guitarra latina, a late-medieval instrument with a waisted body and four strings.

Along with the lute, mandolin and other derivatives of the plucked instrument variety it became a widely-played instrument over the next four hundred years. Its popularity came partly from its versatility — it could sit center stage in an orchestral concerto but it could also accompany a lone balladeer or form the centerpiece of a fiery flamenco stomp. And partly from its portability — it was the ideal traveling instrument for the itinerant musician. You could find it in taverns and town squares, concert halls and at court and it spread far and wide, migrating from Europe with the early settlers to the emerging New World.

From the innovation point of view the guitar followed a classic pattern — plenty of experimentation with materials, number of strings, neck length and a host of other parameters in search of the right balance of sound and functionality. And then the emergence of a ‘dominant design’, the configuration which set the pattern, laid down the roadway along which the development of the instrument would travel in an extended period of continuous improvement. Most sources agree it was the Spanish guitar builder Antonio Torres Jurado who did this in 1850 with his invention of the fan-braced design. Bracing the hollow body with struts of wood meant it didn’t keep collapsing in on itself because of the tension in the strings and you could build a big enough body to give you the balance of tone, projection and volume which players required.

But by the end of the 19th century the guitar had come up against an increasingly frustrating limit. It wasn’t loud enough. You could have the sweetest, most lyrical tone but if you were trying to make yourself heard amongst the dance bands which emerged as the twentieth century dawned you had a problem. Innovation, of course, thrives on these conditions and a whole new breed of entrepreneurs began experimenting to try to make louder guitar. They explored many routes — making the whole instrument bigger (but more cumbersome), changing materials (like the steel guitars pioneered by the National company), and playing around with alternative sound amplification principles (like the resonator cone, a kind of dustbin-lid built into the guitar top which vibrates like a speaker and replaces the simple sound hole of the guitar).

This last was particularly embraced by the Dopraya Brothers, Slovakian immigrants to the USA who set up the Dobro company and gave their name to the guitar variant whose haunting sound instantly conjures the wide prairie landscape with its rolling tumbleweed in a thousand films.

Plenty of innovation — but no real breakthrough, nothing radical enough to bring a step change in performance. Until entrepreneurs began to borrow ideas from different industries and to import alternative technologies. As Keith Richards of the Rolling Stones expertly explained in a BBC interview looking at the history of the electric guitar, ‘all they did was put a phone in it….’ Then, after a trademark raspy guffaw, he added “But it was the right phone at the right time!”

Electronics in the early twentieth century had already given us the telephone, the radio and the gramophone and it had become clear that converting sound waves into electrical impulses and then reversing the process offered opportunities for amplifying instruments like the guitar. Patents from around 1910 reinforce Richards’ analysis; people were putting telephone transmitters inside violins and banjos. By the 1920s hobbyists used the (by then widely available) carbon button microphones from telephones, attaching them to the bridge of their instruments. Unfortunately these had a weak signal and as you increased the sensitivity to try to make it louder the microphone picked up other sounds and generated the unpleasant squeal of feedback.

The breakthrough came in 1931 when George Beauchamp designed a one piece instrument, cast in metal and resembling more a frying pan rather than a guitar. Harry Watson of the National Company takes the credit for having built the design which qualifies as the world’s first electric guitar. The key innovation was the use of a device to convert the instrument’s vibrations into electrical signals which could then be amplified — an arrangement of coils of wire wrapped around a metal core and designed to ‘pick up’ the signal. The concept of the pickup belongs to Watson’s friend Arnold Rickenbacker; the idea worked and in 1932 the two of them formed the Rickenbacker company and in 1937 they were awarded a patent.

That breakthrough fired the starting pistol for another innovation race with established manufacturers rushing to bring imitations to market and entrepreneurs looking to exploit the new possibilities in new (and hopefully better) designs. There was plenty of innovation space to play in. Not least dealing with the main limitation of the frying pan idea which was that it was a lap steel guitar, designed to be played horizontally with the instrument resting on the knees. Whilst the ‘Hawaiian sound’ associated with such an instrument was popular it had its limits; Rickenbacker quickly came up with their ‘electro-Spanish model B’ which was designed to be played upright with a strap — the instrument we know and love today.

Some sought to move the new idea to scale through celebrity endorsement. The Gibson company was one of the biggest players in the rapidly-growing musical instrument industry; they launched their Electro-Spanish 150 with the backing of the celebrated jazz guitarist Charlie Christian and a price tag of $150 trying to create a Model T Ford machine.

There was plenty of pent-up demand in the market; with the expansion of the dance band era musicians needed to play louder. But the limits of the design were still there — even if you replaced the sound hole with f-holes or did away with it altogether you still had the problem of sound waves bouncing around inside a hollow-bodied instrument and generating unwanted feedback.

Enter a user innovator, one Les Paul. Already a guitar player with a big following on the country and western circuit he was also a tinkerer. And in 1940 he came up with a solution to the feedback problem — why not dispense with the hollow body altogether and make the guitar solid? He built the Log — a wooden post with a pickup attached along which he stretched the strings. Recognising that he might have trouble pitching his new design he disguised it by gluing two halves of an old Epiphone guitar to the wooden post to give it the familiar guitar shape. This was simply a cosmetic addition to reduce the shock factor; in terms of the sound it made no contribution whatever.

In classic user innovator style he wasn’t particularly interested in producing and marketing the device himself — he had plenty to do as a performer. So he took it to the Gibson company, reasoning that with their history they might be interested in a radical innovation like this. Gibson had built their success on (and took their name from) the ideas of an eccentric mandolin maker who revolutionised the design of that instrument in 1910, doing away with the round bellied Neapolitan model and replacing it with the flat-backed variety. Unfortunately (for them as it later turned out) their response was decidedly lukewarm and so Les shelved his project.

Innovation is often like a soup; market needs and enabling technologies being stirred together by various entrepreneurs and coming slowly to the boil. As it reaches the right temperature so a breakthrough idea bubbles to the surface in two or three places simultaneously. So it wasn’t entirely surprising that in another part of the country someone else was playing with a similar idea to Les Paul.

This one was taking shape in the workshop of Paul Bigsby, an engineer with a passion for two things, country music and motorcycles. He shared this with a friend, Merle Travis, another successful country singer who talked about his ideas for improving the guitar he played — making it easier to tune, capturing the sustain which he could get from a steel-bodied guitar but without the feedback. Bigsby built guitars as a sideline to his motorcycle business and was able to bring Travis’s ideas to life; together they developed their own version of a solid bodied electric guitar.

And meanwhile in another part of the galaxy, or at least further up the road in California another player was about to join the game. Leo Fender wasn’t a guitar player — his instrument was the saxophone. He was an accountant by training though his passion was electronics — he’d spent his childhood disassembling and rebuilding radios and enjoyed exploring the growing potential of the new technology. While working as a book-keeper in Anaheim he was contracted by a local band leader to build a public address (PA) system; it was a success and he was asked to build six more.

That nudged the entrepreneur in him; in 1938 along with his wife he opened a radio repair shop with a borrowed $600 — “Fender Radio Service”. He quickly built up a business repairing and servicing the amplifiers and occasionally guitars for the many roadhouse bands coming through. This was a valuable apprenticeship; through the many projects he worked on he developed a deep understanding of the typical problems and how to improvise solutions to fix them quickly. He was continuously prototyping and experimenting with new ideas and implementing those ideas in the next project which came through his door.

He wasn’t alone; in particular he shared ideas with another enthusiast — Doc Kaufman — who was a lap steel guitar player, with a day job working for the Rickenbacker company. The two of them played around with ideas and eventually launched their company, K&F, to build lap steel guitars; in 1944 they patented their version incorporating Fender’s own design for a pickup; Kaufman left in 1946 and Leo renamed the company Fender Manufacturing. He worked on their ideas further, coming up with a thin solid body electric guitar which would be easy to tune, wasn’t too heavy and crucially didn’t feedback in the way the hollow bodied machines did. Pretty much the specification which Merle Travis had brought to Paul Bigsby.

In 1950 he launched it as the Fender Esquire and then, having added a second pickup, renamed it the Broadcaster in 1951. The threat of a lawsuit from the rival Gretsch company forced him to change the name and so the guitar became known as the Telecaster. The new wave was about to break.

Fender’s skills weren’t just in electronics; he was a pretty good listener too. He picked up on plenty of feedback from customers in his service business and so instead of improving on the Telecaster for his next product he set about designing a new machine incorporating many of their ideas. This led to a guitar which built of the strengths of the Telecaster but which added innovations in pickups — 3 instead of 2, giving the player plenty of control via a 5-way switch. The result was the Stratocaster, launched in 1954 and about to change the world of music.

Its success owed a lot to timing; the growth of Rock ’n’ Roll changed the format of dance bands towards the smaller trios and quartets and the sound and capability of the machine lent itself perfectly to the loud driving style. (Fender also had a hand in changing the shape of the ‘back line’ of the band, displacing the double bass with his solid-bodied Precision bass, introduced quietly alongside the Telecaster in 1951).

The Stratocaster appeared in Buddy Holly’s hands on the cover of his 1957 album and around the world musicians began taking notice. In the UK Hank Marvin, lead guitarist in Cliff Richard’s backing band The Shadows, was one of the first to own one and their success with a strong of instrumental hits firmly established the new sound. Not least in the ears of a generation of youngsters who aspired to own one and make their own music; as one of them, Pink Floyd’s David Gilmour said, ‘(the Stratocaster) is about as perfect as a guitar gets’. In the hands of another, one James Marshall Hendrix, the machine was pushed to its limits — not least through exploiting the very feedback which Leo Fender, Paul Bigsby and Arnold Rickenbacker had worked so hard to try and reduce!

The response from the other guitar manufacturers was once again one of copy and develop, rapid imitation and improvement. Gibson were quick to pick up on the new trend but had a long hard slog up the learning curve to reach the point where they could master the new tricks of building solid bodied guitars with complex pickups. In 1955 they launched their new guitar and went looking for another celebrity to help them promote their new product. They recruited one of the top performing acts of the time, Mary Ford and her partner — Les Paul. The man who they remembered as ‘the guy with the broomstick with the pickups on it’, and whose ideas they had turned down a decade earlier. They made slight amends by naming the guitar after him — and alongside the Stratocaster it is still one the most sought after models and has been widely imitated around the world — not least because of the exposure given it by a rising blues guitarist, Eric Clapton.

The rest is (recent) history. The market for both professionals and increasingly amateur musicians grew and with it a rising tide of innovation. Variations on the basic dominant design established by Leo Fender, Les Paul, Merle Travis and others proliferated with different shapes, different materials, extensive improvements around the electrics and so on. Bringing us to today’s world where — unless the person in the next apartment is at the early stages of trying to master thrash metal riffs — those innovations have helped create the soundscape into which we can escape, whether as players or listeners.

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How COVID-19 Has Exposed Us

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How COVID-19 Has Exposed Us

GUEST POST from Greg Satell

The moon landing in 1969 was, in many ways, the high point of the American century. Since then, we’ve been beset by scandals like Watergate, Iran-Contra and two presidential impeachments, mired in never-ending wars that we don’t win, while increasingly encumbered by rising debts and income inequality amid falling productivity growth. Incomes have stagnated while education and healthcare costs have soared.

Yet in an essay written back in February, just before the Covid-19 crisis, Ross Douthat wrote that these apparent woes are actually signs of success. In effect, he argued that we lack major technological breakthroughs because we become so technologically advanced, and we lack economic progress because we’ve become so prosperous.

Even then, it was a strange and somewhat maddening position to take. Why would Douthat, an intelligent and insightful man, write such things? Because he so wanted to believe them that he went in search for facts to support them. Many of us have been doing the same. Yet the Covid-19 crisis has unmasked us and it’s time to start facing up to the truth.

A Failed Market Revolution

In 1954, the eminent economist Paul Samuelson, came across an obscure dissertation written by a French graduate student named Louis Bachelier around the turn of the century. The paper, which anticipated Einstein’s later breakthrough on Brownian motion, declared somewhat innocently that “the mathematical expectation of the speculator is zero.”

Samuelson’s discovery launched a revolution in mathematical finance models based on on Bachelier’s assumption, including the Efficient Market Hypothesis, portfolio theory, the Capital Asset Pricing Model (CAPM) and the Black-Scholes model. The underlying assumption was that markets were rational, and risk could be quantified and managed effectively.

The flaws in these models should have been obvious even at the time and some, including the mathematician Benoit Mandelbrot, pointed out that markets were far more volatile than the financial engineering models predicted. Nevertheless, policymakers chose to ignore the warnings and put their faith in the “magic of the market.”

Probably the biggest failure of market fundamentalism is that, as economist Thomas Philippon points out in his book The Great Reversal, over the past 40 years markets in the United States have become significantly weaker. In a similar vein, a study published in Harvard Business Review that examined 893 industries found that two thirds had become more concentrated.

The truth is that we’ve chosen weaker markets and less competition, which has led to less dynamism and innovation. That’s no accident.

Digital Disruption

In Regional Advantage, AnnaLee Saxenian describes how Silicon Valley replaced Boston’s “Technology Highway” as the center of the digital universe. While Boston was corporate and hierarchical, Silicon Valley was freewheeling and networked. The Silicon Valley ethos was very much the counterculture.

So, it was no accident that when Steve Jobs flew to New York to recruit John Sculley, who was at the time President of Pepsi, to lead Apple he asked him,”Do you want to sell sugar water for the rest of your life, or do you want to come with me and change the world?” The implication being that selling computers was a higher calling than selling soft drinks.

That was nearly 40 years ago and while the Covid-19 crisis has certainly highlighted some benefits of digital technology, such as cheap and effective teleconferencing, it’s also become clear that the digital revolution has largely been a disappointment. Productivity growth, except for a relatively brief period in the late nineties and early aughts, has been depressed since the 1970s.

Compare the iPhone to the breakthroughs of the mid-twentieth century, such as Bell Lab’s transistor, Boeing’s 707 and IBM’s 360 and it becomes clear that while digital technology has done much to disrupt industries, it’s done relatively little to create significant new value, at least in comparison to earlier technologies.

The Uncertain Promise of Globalization

The aftermath of the fall of the Berlin Wall was a time of great optimism. With the Cold War over, books like Francis Fukayama’s The End of History predicted a capitalist, democratic utopia in which free markets would conquer the world making everyone more prosperous. Those that refused to reform would be unable to compete.

While there were genuine achievements, especially in lifting up the world’s poorest, it’s hard to see how globalization has made us significantly better off. In fact, rather than the triumph of freedom, we’ve seen a global rise in populist authoritarian movements, the polar opposite of what intellectuals like Fukayama predicted.

In the United States, the situation has become especially dire. Social mobility and life expectancy in the white working class are declining, while anxiety and depression are rising to epidemic levels. While wages have stagnated, the cost of healthcare and education has soared, squeezing the middle class. Income inequality is at its highest level in 50 years.

So, while it’s true that there have been real benefits from globalization, such as curbing inflation, we’ve done little to mitigate the costs to the average citizen. That didn’t just happen but was the result of choices that we made.

We Need to Choose Resilience and Grand Challenges Over Output and Disruption

The Covid-19 crisis has unmasked us. We thought that markets, technology and globalization would save us, that we could just set up some sensible rules of the road and everything would run on autopilot. That’s clearly untrue. We took short-term profits while ignoring long-term costs, loaded up on debt and hoped for the best.

The current crisis has followed the same pattern. We simply failed to prepare for known risks because it seemed expedient not to. George Bush warned about the possibility of a pandemic as did his Health and Human Services Secretary. Jay Leno mocked them. The Obama administration set up a step-by-step playbook and it was ignored. The long list of failures goes on.

Yet we don’t have to be victims of our failed choices. We can learn to make better ones. After the 1918 Spanish Flu pandemic, we embarked on a 70-year productivity boom. Out of the ashes of World War II, we built a new era of peace and prosperity that was unprecedented in world history. We can do so again. We have that power.

New technologies, under development as we speak, will likely give us the power to cure cancer, create clean energy, save the environment and colonize space. We can rebuild the middle class, usher in a new era of peace and prosperity, increase life expectancy while improving quality of life. These are all things we may be able to achieve in the next decade or two.

Yet those possibilities are merely potential that we can succeed or fail to actualize. We can, as we did after World War II, choose to invest in the future and tackle grand challenges. We can build new infrastructure, spawn new industries and create an educated workforce. Or we can, as we did after the end of the Cold War, choose disruption over construction.

What’s clear is that nothing is inevitable. The digital revolution didn’t have to be a dud. The Great Recession didn’t have to happen. The Covid-19 Pandemic could have been, at the very least, greatly mitigated. We are responsible for the choices we make. Now is the time to shoot for the moon (and Mars), not to grade ourselves on a curve.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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A Human-Centered Approach to Mastering Disruption

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A Human-Centered Approach to Mastering Disruption

GUEST POST from Chateau G Pato

Disruption. The word itself can evoke a sense of panic in the boardrooms of established organizations. It represents the unknown, the sudden shift that threatens to destabilize markets, render existing strategies obsolete, and even collapse empires. Yet, in our volatile, uncertain, complex, and ambiguous (VUCA) world, disruption is not just a possibility; it’s a relentless certainty. The true differentiator for success in this era isn’t about avoiding disruption, but about mastering its management. And at the heart of this mastery lies a profound commitment to human-centered change and innovation. It’s about recognizing that people – your employees, your customers, your partners – are not merely components of the machine, but the very engines of resilience and reinvention.

Effective disruption management transcends mere contingency planning. It demands an organizational culture that is inherently adaptable, relentlessly curious, and deeply empathetic. It requires the courage to challenge assumptions, the agility to pivot rapidly, and the wisdom to learn from every experience – both good and bad. Let’s explore how leading organizations have exemplified these principles through two powerful case studies, revealing the human thread that weaves through their triumph over turbulence.

Case Study 1: The Global Logistics Industry & The COVID-19 Shock

From Supply Chain Gridlock to Agile Lifeline

The dawn of 2020 brought with it a disruption of staggering scale: the COVID-19 pandemic. For the global logistics and supply chain industry, it was an existential shockwave. Traditional systems, built on predictable flows and just-in-time efficiencies, buckled under unprecedented demand surges, crippled by sudden labor shortages, and fractured by international border closures. The world watched as shelves emptied and critical medical supplies became scarce.

However, amidst this chaos, giants like Amazon, FedEx, and a constellation of regional innovators didn’t just survive; they redefined their roles. Their success wasn’t born from static playbooks, but from a dynamic, human-centered response. They rapidly iterated and deployed contactless delivery models, adapting safety protocols not just for efficiency but for the psychological safety of both their workforce and customers. They harnessed the power of real-time data analytics, not just for route optimization, but to predict demand fluctuations and proactively reroute essential goods to areas of greatest need.

Perhaps most profoundly, their leadership empowered frontline employees. Truck drivers, warehouse workers, and delivery personnel became critical innovators, devising on-the-ground solutions for complex, evolving challenges. Leaders listened, decentralized decision-making, and invested in immediate support—from personal protective equipment to rapid retraining. This cultivated an extraordinary level of trust and shared purpose, transforming a fragmented network into a resilient, adaptive lifeline for global communities.

Key Lessons from the Logistics Response:

Distributed Intelligence & Empowerment: Equip and trust your frontline teams; they hold the most immediate insights and often the most pragmatic solutions.
Rapid Experimentation (Build-Measure-Learn): Don’t strive for perfection upfront. Test, learn from feedback, and quickly iterate new solutions, even under immense pressure.
Empathy-Driven Operations: Prioritize the physical and psychological well-being of your employees and customers; their safety and trust are foundational to resilience.
Data as a Human Enabler: Utilize data not just for efficiency, but to inform human decisions and adapt quickly to evolving needs and risks.

Case Study 2: Netflix vs. Blockbuster – The Empathy Divide

A Masterclass in Customer-Centric Disruption

The story of Netflix and Blockbuster is a cautionary tale and a beacon, respectively, in the annals of disruption. Blockbuster, the once-dominant king of video rentals, famously dismissed an opportunity to acquire a nascent Netflix in 2000 for $50 million. Their rationale? Netflix’s DVD-by-mail model seemed niche, and their own late fees were too lucrative to abandon. This was a classic product-centric, rather than human-centered, blind spot.

Netflix, conversely, was built on a foundation of deep customer empathy. They didn’t just offer DVDs; they offered a solution to the frustrations of physical stores, limited choices, and the egregious late fees that plagued Blockbuster’s customers. They listened to the human desire for convenience, variety, and a sense of fairness. As broadband internet became ubiquitous, Netflix didn’t hesitate to disrupt its *own* successful DVD-by-mail model. They recognized the evolving human need for instant gratification and personalization, investing heavily in streaming technology and, crucially, in data-driven content recommendations and original programming.

Blockbuster, meanwhile, clung to its brick-and-mortar legacy, unable or unwilling to shed the very aspects of its business that were becoming pain points for consumers. Their leadership failed to understand the human shift towards digital access and personalized entertainment experiences. Netflix, by consistently putting the customer’s evolving needs at the very core of its strategy – a true demonstration of Human-Centered Change™ in action – didn’t just manage disruption; it orchestrated it, evolving from a DVD service to a global entertainment powerhouse.

Key Lessons from Netflix’s Triumph:

Obsessive Customer-Centricity: Deeply understand and anticipate evolving human needs and frustrations; this is your ultimate compass.
Strategic Cannibalization: Be willing to disrupt your own profitable business models if it serves a superior, emerging customer experience.
Long-Term Vision over Short-Term Myopia: Resist the temptation to prioritize immediate gains when fundamental market shifts are underway.
Culture of Continuous Learning & Adaptation: Foster an organizational mindset that embraces new technologies and business models, even if they seem small or unprofitable at first.

The Human Thread: Cultivating Resilience and Reinvention

These case studies underscore a critical truth: successful disruption management is not a technological problem; it’s a human one. It demands a leadership commitment to fostering environments where curiosity thrives, experimentation is encouraged, and empathy guides every decision. To build an organization capable of not just surviving but thriving amidst continuous disruption, consider these human-centered imperatives:

Cultivate Psychological Safety: Create a culture where speaking up, challenging norms, and even failing fast are embraced as vital components of learning and innovation. Fear is the enemy of adaptation.
Empower the Adaptive Mindset: Invest in continuous learning, providing opportunities for employees to develop skills in areas like design thinking, agile methodologies, and data interpretation. Equip your people to be lifelong learners.
Champion Cross-Functional Collaboration: Break down silos. Disruptive challenges rarely fit neatly into departmental boxes; solutions emerge when diverse perspectives converge and collaborate.
Lead with Radical Transparency & Empathy: During times of uncertainty, clear, honest, and empathetic communication from leadership builds trust and reduces anxiety, freeing people to focus their energy on solving problems.
Design for Human Resilience: Build systems, processes, and a culture that is inherently flexible, capable of absorbing shocks, learning from them, and quickly reconfiguring. This means focusing on human capabilities and adaptability, not just rigid procedures.

Disruption is not a wave to be merely endured; it is a current that can be navigated, harnessed, and even ridden to new horizons. By placing the human element – our innate capacity for innovation, collaboration, and resilience – at the heart of your strategy, you can transform the daunting challenge of disruption into your greatest opportunity for sustained growth and meaningful impact.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: 1 of 850+ FREE quote slides from http://misterinnovation.com

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Four Reasons the Big Quit Exists

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Four Reasons the Big Quit Exists

Turns out the pandemic prompted mass numbers of employees finally say, “take this job and shove it” to employers and careers they don’t like. Life is too short to be miserable at work.

In a recent NICE Webinar, we discussed how job quit rates have hit a historic high—even while the economy is still recovering from two years of furloughs and layoffs. This is often referred to as The Great Resignation.

Enlightening research from Gallup gathered in March of 2021 found that 48% of the working population in the United States is actively job-hunting or seeking out new opportunities.[1]

NICE Employee Churn word cloud

So, while we watch the labor market churn with no signs of settling, how can businesses avoid the costs of high turnover rates?

“How to Reduce the Risk of Employee Churn Amid the Big Quit”
(click to continue reading this article on the NICE blog)

Image credits: NICE

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A Brave Post-Coronavirus New World

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A Brave Post-Coronavirus New World

GUEST POST from Greg Satell

In 1973, in the wake of the Arab defeat in the Yom Kippur war with Israel, OPEC instituted an oil embargo on America and its allies. The immediate effects of the crisis was a surge in gas prices and a recession in the west. The ripple effects, however, were far more complex and played out over decades.

The rise in oil prices brought much needed hard currency to the Soviet Union, prolonging its existence and setting the stage for its later demise. The American auto industry, with its passion for big, gas guzzling cars, lost ground to the emergent. The new consciousness of conservation led to the establishment of the Department of Energy.

Today the Covid-19 crisis has given a shock to the system and we’re at a similar inflection point. The most immediate effects have been economic recession and the rapid adoption of digital tools, such as video conferencing. Over the next decade or so, however, the short-term impacts will combine with other more longstanding trends to reshape technology and society.

Pervasive Transformation

We tend to think about innovation as if it were a single event, but the truth is that it’s a process of a process of discovery, engineering and transformation, which takes decades to run its course. For example, Alan Turing discovered the principles of a universal computer in 1936, but it wasn’t until the 1950s and 60s that digital computers became commercially available.

Even then, digital technology, didn’t really begin to become truly transformational until the mid-90s. By this time, it was well understood enough to make the leap from highly integrated systems to modular ecosystems, making the technology cheaper, more functional and more reliable. The number of applications exploded and the market grew quickly.

Still, as the Covid-19 crisis has made clear, we’ve really just been scratching the surface. Although digital technology certainly accelerated the pace of work, it did fairly little to fundamentally change the nature of it. People still commuted to work in an office, where they would attend meetings in person, losing hours of productive time each and every day.

Over the next decade, we will see pervasive transformation. As Mark Zuckerberg has pointed out, once people can work remotely, they can work from anywhere, which will change the nature of cities. Instead of “offsite” meetings, we may very well have “onsite” meetings where people from their home cities over travel to headquarters to do more active collaboration.

These trends will combine with nascent technologies like artificial intelligence and blockchain to revolutionize business processes and supply chains. Organizations that cannot adopt key technologies will very likely find themselves unable to compete.

The Rise of Heterogeneous Computing

The digital age did not begin with personal computers in the 70s and 80s, but started back in the 1950s with the shift from electromechanical calculating machines to transistor based mainframes. However, because so few people used computers back then—they were largely relegated to obscure back office tasks and complex scientific calculations—the transformation took place largely out of public view.

A similar process is taking place today with new architectures such as quantum and neuromorphic computing. While these technologies are not yet commercially viable, they are advancing quickly and will eventually become thousands, if not millions, of times more effective than digital systems.

However, what’s most important to understand is that they are fundamentally different from digital computers and from each other. Quantum computers will create incredibly large computing spaces that will handle unimaginable complexity. Neuromorphoic systems, based on the human brain, will be massively powerful, vastly more efficient and more responsive.

Over the next decade we’ll be shifting to a heterogeneous computing environment, where we use different architectures for different tasks. Most likely, we’ll still use digital technology as an interface to access systems, but increasingly performance will be driven by more advanced architectures.

A Shift From Bits to Atoms

The digital revolution created a virtual world. My generation was the first to grow up with video games and our parents worried that we were becoming detached from reality. Then computers entered offices and Dan Bricklin created Visicalc, the first spreadsheet program. Eventually smartphones and social media appeared and we began spending almost as much time in the virtual world as we did in the physical one.

Essentially, what we created was a simulation economy. We could experiment with business models in our computers, find flaws and fix them before they became real. Computer-aided design (CAD) software allowed us to quickly and cheaply design products in bits before we got down to the hard, slow work of shaping atoms. Because it’s much cheaper to fail in the virtual world than the physical one, this made our economy more efficient.

Today we’re doing similar things at the molecular level. For example, digital technology was combined with synthetic biology to quickly sequence the Covid-19 virus. These same technologies then allowed scientists to design vaccines in days and to bring them to market in less than a year.

A parallel revolution is taking in materials science, while at the same time digital technology is beginning to revolutionize traditional industries such as manufacturing and agriculture. The expanded capabilities of heterogeneous computing will accelerate these trends over the next few decades.

What’s important to understand is that we spend vastly more money on atoms than bits. Even at this advanced stage, information technologies only make up about 6% of GDP in advanced economies. Clearly, there is a lot more opportunity in the other 94%, so the potential of the post-digital world is likely to far outstrip anything we’ve seen in our lifetimes.

Collaboration is the New Competitive Advantage

Whenever I think back to when we got that first computer back in the 1980s, I marvel at how different the world was then. We didn’t have email or mobile phones, so unless someone was at home or in the office, they were largely unreachable. Without GPS, we had to either remember where things were or ask for directions.

These technologies have clearly changed our lives dramatically, but they were also fairly simple. Email, mobile and GPS were largely standalone technologies. There were, of course, technical challenges, but these were relatively narrow. The “killer apps” of the post-digital era will require a much higher degree of collaboration over a much more diverse set of skills.

To understand how different this new era of innovation will be, consider how IBM developed the PC. Essentially, they sent some talented engineers to Boca Raton for a year and, in that time, developed a marketable product. For quantum computing, however, it is building a vast network, including national labs, research universities, startups and industrial partners.

The same will be true of the post-Covid world. It’s no accident that Zoom has become the killer app of the pandemic. The truth is that the challenges we will face over the next decade will be far too complex for any one organization to tackle it alone. That’s why collaboration is becoming the new competitive advantage. Power will reside not at the top of hierarchies, but at the center of networks and ecosystems.

— Article courtesy of the Digital Tonto blog
— Image credit: Unsplash

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Cognitive Bandwidth – Staying Innovative in ‘Interesting’ Times

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Cognitive Bandwidth - Staying Innovative in ‘Interesting’ Times

GUEST POST from Pete Foley

‘May you live in interesting times’ is the English translation of an ancient Chinese curse. Superficially presented as a blessing, its true meaning is of course far from positive. As memes go, it has lasted quite a while, perhaps because from a cognitive perspective, that little twist, and the little puzzle it forces us to solve makes it more subtle, but also more impactful than a more direct insult. But the ‘blessing and a curse’ dichotomy that it embodies is also a fundamental insight. Opportunity usually brings potential for trouble, and trouble usually bring potential for opportunity, largely because both involve change. So many are going through an awful time on many fronts at the moment, but if that has a silver lining, it is that with it comes change. And ultimately that creates an opportunity for innovation, and hopefully better times.

Big Issues Create Big Opportunity: I’ve written before about the opportunity that Covid-19 presented for innovation. The shattering of habits and established behaviors, combined with dramatic shifts in personal and work situations opened the door to trial of new products and services to a degree not seen in a generation. But as we (hopefully) continue to emerge from Covid, we’ve been sucker punched by numerous other things. The horror of war in Europe being the most shocking, but we are also facing enormous economic challenges in the form of energy shortages, inflation, supply chain issues, the great resignation and rapidly changing socio-political landscapes. And of course, we still have numerous other pressing ‘pre-Covid’ issues such as climate change, pollution and economic inequality that also require urgent attention.

That is a lot of problems that need solving. And as awful as Covid was for everyone, the current issues around supply chain, global economic instability, inflation and increased cost of debt likely create at least as immediate operational issues for many organizations, and hence an equally urgent need for innovation.

Another Innovators Dilemma. Unfortunately, the time when we need most innovation is often when it is hardest to deliver it. Innovation doesn’t happen overnight, and usually needs clear strategy, resources, funding, creativity and knowledge. And all of these are currently in short supply. An uncertain and rapidly changing world makes setting long-term strategy challenging. Supply chain challenges can have huge short-term operational impact, and suck up resources and expertise normally allocated to longer-term innovation. The great resignation and early retirements reduce available expertise. And on top of all of this, inflation, increasing interest rates, raw material prices and labor costs are squeezing finances. None of this is terribly new news, or insightful, but it does provide context for another, sometimes less obvious barrier to innovation that I want to talk about: One that operates more on the individual level – the squeeze of cognitive bandwidth.

Cognitive Bandwidth: The innovation journey needs creativity everywhere from the nascent front end through to launching into market. Ultimately that creativity comes from individuals. That in turn requires those individuals to be allowed the cognitive bandwidth, or ‘quality thinking time’ to ideate. We can only effectively think deeply about one thing at a time. This is our ‘cognitive bandwidth’, and it is a finite resource. There are only so many hours in a day, and most of us can only allocate a small fraction of those to think deeply about problems or process information. And of course the more problems we are facing, the less bandwidth we usually have. The more difficult the situation, the more of our time is spent distracted, jumping from one issue to another, or attempting to ‘multi-task’. Even when we carve out time, the current climate means all too often we are stressed, or in an elevated emotional state. This reduces the quality as well as quantity of our thinking, and so further narrows our individual cognitive bandwidth.

The Covid Squeeze: Covid-19 of course sucked up a lot of cognitive bandwidth. We had to find new ways to work, learn new tools, and new ways to manage personal lives and work-life balance as many found themselves taking on new roles as educators, care givers, chefs, simply learning how to share an office with a spouse for the first time. There were some compensating effects, such as reduced travel, but even that likely had some less obvious and hard to measure impacts on the creative process that I’ll discuss later. But perhaps the biggest, albeit largely intangible impact on cognitive bandwidth was the impact Covid had on our collective emotional state. Covid, and the changes it brought was hard on everybody. Everyone has there own stories, and we’ve all seen the increase in mental health issues that accompanied the pandemic. But this is almost certainly the ‘tip of the iceberg’. Virtually everyone has experienced some degree of increased stress and negative emotions during Covid, and this directly impacts cognitive bandwidth and hence individual innovative capacity.

The Post-Covid Sucker Punch: One thing I think we were all looking forward to was a return to some semblance of normal. But unfortunately, as Covid (hopefully) subsides, reentry into the post Covid world is proving to be very bumpy, and we are facing the cornucopia of other issues described above. This not only creates a host of ‘fires’ that need to be put out, but it also inevitably takes an emotional toll. After two years of disrupted work and home-life, we are now asking people to again step up and be ‘unusually’ innovative in difficult circumstances, and against a backdrop of war and human suffering. Fatigue and burn-out are almost inevitable.

At a practical level, I see this on a day-to-day basis. I sit in a lot of innovation teams, and one pattern I observe consistently is the workforce getting increasingly stretched; both from a time and emotional perspective. I see more and more people getting pulled out of meetings to fight fires, people attempting to double task, or stepping in and out of meetings, or simply looking frazzled and overworked. Of course, none of this is new, overwork and stress existed log before Covid. But it’s also not surprising that it appears to be increasing during a long period of constant change.

The Neuroscience of the Creative Moment. Innovative thinking comes in multiple forms, but it all requires time. We need time to think deeply, and consciously about problems, and to assimilate data and knowledge. But ‘downtime’ is also a critical, if less understood part of the creative process. There is a very good reason that Eureka moments often happen in the bath, shower, or middle of the night. When the mind is relaxed, has time, and not focused on an immediate problem, it is more likely to make surprisingly obvious connections, or see things in different ways. This is often when the biggest ideas occur. We need conscious thinking to build essential foundations of knowledge, but the most interesting ideas and connections often happen when we are not trying. Have you ever had a name on the tip of your tongue, but no matter how hard you try, you cannot find it? Then a few hours later when you are not trying, it pops into your head? This is an analogous mechanism, where conscious focus simply reinforces and repeats converging on the same, sometimes unwanted result, but when we relax, it opens the channel to the needed connection. There is a lot of research around how this works, which includes the interaction between default mode and executive function, the role of alpha waves and flow state, and the conceptual blending process. It’s still very much an evolving science, but one thing that is fairly consistent across this research is that downtime and periods of reduced stress play an important role in the creative process and making connections. Unfortunately, for many, the pandemic reduced relaxation and ‘own time’. Needing to learn new skills and new ways of working, while also having to solve a myriad of new and ever changing problems sucked up time. Even the loss of commutes took away a period of solo reflection where many of us consciously or unconsciously processed and synthesized the day’s information. But perhaps the hardest pill to swallow has been that while we all hoped that the end of Covid would have provided some relief, if anything the news cycle has got worse. This takes an emotional toll. Part of this reflects the ratings competition within media that favors an ever-increasing stream of bad news. But unfortunately it also reflects a very challenging global reality and very real problems and suffering.

What Can We Do?

There are of course limits to what we can do within our sphere of influence. Most of us cannot directly impact the war in Ukraine, the supply chain crisis or global diplomacy. But we can take steps to reduce pressure on our teams, and ourselves, and thus make innovation and creativity a little easier.

1. Make tough strategic priority decisions. Primarily this is a leadership task, but it’s also something we can to some degree manage in our personal portfolios. One reason we see so much innovation during crisis is focus, and a willingness to sacrifice some goals or standards for more important ones. For us to replicate this means being very selective about what fires to fight, while also being willing to let others burn themselves out. This is not without risk, as short-term survival is of course a prerequisite for any successful long-term strategy. But during periods of rapid change, we also see rapid reversals. For example, spikes in raw material costs are often short-term, and developing alternatives can often take longer than the problem lasts. It sounds obvious, but is often deceptively difficult, especially as deciding to let the wrong fire burn itself out can be quite career limiting. But making difficult priority calls, and saying ‘no’ can be critical to maintaining our innovative and competitive edge, by keeping limited cognitive bandwidth focused of the most important tasks.

2. Help talent to focus on what is really important, and to grow skills that are most relevant to the future. There has been an ongoing trend to increasingly ask talent to handle their own administrative and organizational work. This is partly driven by technology that reduces the need for specialized knowledge to manage many logistics tasks. And eliminating support roles looks good on margins and fixed costs. But asking a highly skilled technical expert to cover their own admin not only adds to their workload, but it is also inefficient, as we are effectively overpaying them to complete tasks that often don’t play to their core skills. Conversely, there is also a lot of skill on the sidelines at the moment, while many have developed skills in working remotely. So is one option is to leverage this to free up innovators and experts. Let them focus more on their areas of expertise, by bringing back more general support roles. Or bring in temporary outside help where short-term issues require expertise that is not anticipated to be part of long-term strategy.

3. Schedule down-time, and create a culture where it is encouraged. Build protected spaces in calendars when meetings are not allowed. Encourage lunch breaks, and enable casual team-building events and wellness practices. It’s easy to view these as non-essential, and the type of activities that we cut first when times get tough. But they are critical to an innovative culture. Mental downtime is not a luxury or a perk, but an essential part of the creative process. And in too many cases, we’ve been in crisis mode for so long, that tool has become blunt or burnt out.

4. Further support this with the design of our physical environments. Another trend has been the move to open offices and shared space. This has benefits for both collaboration, and for space efficiency as hybrid home/office working models emerge. But studies have also shown more innovative ideas emerge when people work alone than in brainstorming environments. So it is critical to provide both physical spaces and a culture that enable private reflection and quiet concentration where people can potentially synthesize information and make connections. The key to a cognitively diverse innovation culture is to provide options for different thinking styles. And this also means that acknowledging that benefits of work from home are not one size fits all. For some it’s a blessing, but both work style and personal circumstance can make working from home a challenge for others. To support a cognitively diverse workforce, some people, especially those early in their careers, may need work as a sanctuary, and a bigger physical footprint at work than others.

5. Finally, distribute work evenly. I remember someone telling me early in my career that, ‘if you need something done quickly, go to the busiest person’. There is some truth in that, and some people thrive on high workload. But it only works to a point, and if taken too far, we risk overloading the cognitive bandwidth of our most creative people, even if they may not realize it themselves. By all means give the most challenging and most important tasks to the best people. But don’t overload them too much. They will often be happy to take on more, but it may not be best for them, their creativity, or the organization. Look very hard to see if the load is evenly distributed within an organization, and if not, ask hard questions why not? And if you are the person everyone comes to, practice saying ‘no’ occasionally!

The good news is that humans are pretty resilient, so it doesn’t always take huge changes to get significant results. We are all the progeny of ancestors who survived wars, famine, disease, social upheaval and natural disasters. And it’s worth noting that we are often at our most creative during periods of greatest tragedy.

Technology advanced at a phenomenal pace during WW-II, and more recently the speed of development of Covid vaccines was staggering. But there are clues in those situations that we can learn from. Resources and focus were unprecedented. During WW-II virtually everything was thrown against the war effort, and tough, sometimes brutal priority calls were the norm.

Project Warp Speed put enormous resources against the Covid vaccine and took huge risks on uncertain bets. Of course, most of us working in innovation don’t have these almost infinite resources, but we can be very strategic in how we use what we have. And keep in mind that wartime mentality is meant to be short-term, while Project Warp Speed was designed to last about a year.

We are in the business of creating a sustainable innovation culture. So, we are not just about protecting the cognitive bandwidth of individuals in the short-term, but also preventing burn out, and creating a sustainable cognitive culture.

Image credit: Pixabay

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Innovation in the time of Covid – Satisfycing Organizations

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Innovation in the time of Covid - Satisfycing Organizations

GUEST POST from Pete Foley

Many of us spend a lot of time thinking about consumer habits, and how to change or reinforce them. As innovators that’s pretty central to our job. And Covid has presented us with a unique opportunity, as so many consumer habits have been disrupted. But work habits are as ingrained and as hard to break as consumer behavior, and so Covid provides a similar once in a generation opportunity to change work processes.

We have been forced us to work differently. Remote working has meant less oversight and more autonomy. In parallel, the world has changed rapidly around us, forcing us to make quicker decisions while relying on less data. As a result, we’ve also probably made a few mistakes, but hopefully also learned from them. It’s been tough, but it’s also been a unique opportunity for learning and change.

The Organizational Brain: I love analogies, and an obvious one is that the change in many organizations brings their processes closer to how the human brain makes decisions. They’ve been satisfycing – a concept borrowed from Behavioral Economics, that describes decisions that are good enough, not always perfect, but reached faster, and with less ‘process’.

This is a key concept in understanding real human behavior. Time is critical to survival. An early human being chased by a hungry saber tooth didn’t have time to ponder every possible escape route. He or she just had to get away from the predator before it reached them, or at least move away faster than the slowest member of the tribe. As a result, we are the ancestors of people who made timely decisions based on limited data, not those who stood pondering every possibility in search of perfection.

Even contemporary decisions, while often not quite as urgent as escaping from a hungry predator, typically involve an analogous trade off between time and completeness of information. How many people know every detail about a stock, or even a car, before they buy? In reality we rarely have time to fully process every relevant piece of information for any decision we make, but instead use a mixture of heuristics, proxy’s and our gut, together with some analysis to make good enough, but often not perfect decisions.

A Corporate Flaw: A flaw in traditional economics was that time was largely ignored. It assumed that humans made perfect decisions based on all available data, no matter how long that took. In many ways, businesses, especially big corporations lean towards this much slower, data based type of decision. Employees have to justify decisions to a far greater degree than we do as individuals. Telling a boss or a shareholder that a decision ‘just felt right’ is probably career limiting, especially if it turns out to be the wrong decision. But this slows them down, and leaves them vulnerably to more agile, less risk averse competition making good enough decisions faster. I’d also argue that a lot of time is also spent creating the illusion of certainty. We collect supporting data, pre-align with a boss, or seek consensus via a team, but all too often this is an exercise in precision, not accuracy. We are only as good as our models, and these often struggle to accurately predict the complex, fast moving real world we live in. I’m sure a few people will not be comfortable with this premise, and I’ll dive a little deeper later, but it’s born out by the high proportion of innovations that fail, despite great supporting consumer data and business projections.

The Covid Change: The good news is that Covid has forced us to change. Meetings have been switched to virtual, and in many cases participation has been trimmed. We haven’t abandoned consensus, but in many cases we’ve had to be more choiceful about when and where it’s needed. We have been forced to give people more autonomy, if only because oversight has been impossible. And hand in hand with all of this, in many cases we’ve also been forced to make decisions without the same level of supporting data we are used to. The pace of change has accelerated, while many of our usual methods of testing have been stymied, or at least had to go through significant changes. Before Covid we may have debated and aligned, or run additional research or tests, both to make more informed decisions, but also to CYA should things go wrong. In the last 18 months we’ve more often had to go with our gut, or at least make decisions where we’re far less ‘ certain’ about the outcome.

We will not know how this has worked out for some time, if ever, as we lack a frame of reference for operating in a pandemic. But my guess is it this has probably worked out fairly well. We probably have made a few more mistakes, or at least sub optimal decisions. And we’ve likely learnt a few hard lessons as well. But most of the time, we’ve probably made good enough decisions. And we’ve likely compensated by learning and adapting on the fly, or have perhaps built more flexibility into our plans to compensate for the lack of ‘certainty’ in our business plans. In other words we’ve been more closely mirroring at an organization level how the human brain works.

I’m going to argue that this is a good thing, for at least four reasons.

1. Less Meetings!! When the work we have to do is too big, too difficult, or beyond the expertise of one person, we create a team to do it. But teams also represent a trade-off. It’s a conundrum that the very differences that make teams so valuable can also make them cumbersome and time consuming. As we add different skills and perspectives in a team, transaction costs increase, all too often resulting in seemingly endless meetings in the pursuit of consensus. At P&G it wasn’t uncommon to have entire days of back-to-back meetings.

And Mea Culpa, I’m a recovering meeting addict. At times that back-to-back schedule almost felt like a badge of honor. Conversely sitting at a desk and thinking, or quietly reading was treated with deep suspicion in some circles, despite it often being a highly productive exercise

2. We’ve grown capability. We’ve been forced to give people more autonomy, which develops skills and motivation. Not everyone will have thrived when pushed out of their comfort zones, but we’ll have given people opportunity, and that will ultimately pay dividends

3. We’ve been forced to embrace more learning from failure.We talk a lot about this, especially in innovation, but more often than not we still celebrate success far more than failure. But a good scientist designs tests to fail, in order to challenge a hypothesis. This does happen in business, but realistically most consumer research is designed to demonstrate success, and hence move us through the next stage-gate in our business process. But we’ve probably made a few more mistakes, so we’ve probably learned a bit more.

4. Perhaps most importantly, we’ve learned to live, and act with less data. Humans all have a risk aversion bias, albeit some more, some less. Data makes us believe we are increasing the quality of our decisions. It can even provide a rational for procrastination.- “Let’s get more data before we push the button’. Historically this has often caused us to run big, expensive consumer research, generate complex volume forecasts, and present detailed and precise (if not accurate) business plans to management. It feels good to believe we are betting on a near certainty, but that’s often unrealistic. A majority of new products fail, despite having excellent consumer and volume forecasting data to back them up. The reality is that the world we place innovation into is usually too complex to accurately predict. The very act of introducing something new disrupts the system, as does any competitive response. And if we are truly introducing something innovative or disruptive, it should by its very nature invalidate at least some of the careful validation work that has gone into our forecasting models and methodologies. All too often, our research creates an illusion of certainty, or at best, over estimates our ability to predict the future. It feels better than it performs.

I’m not suggesting we completely abandon consensus, or consumer testing and modeling. These are great tools for weeding out bad ideas, and for anticipating and fixing issues that are more obvious in hindsight than in enthusiastic foresight. And they can certainly help us to ball-park initiatives, especially if they are not too disruptive. But the success rate of innovation in market strongly suggests that our models are not as reliably predictive as we’d like to believe. It certainly suggests that if we can, we are betting off fine-tuning in market than we are fine tuning for a volume forecast.

Conversely, the human brain is, at least for the next few years, the smartest decision-making ‘entity’ we know. It routinely makes satisfycing decisions that balance the need for action against the cost of obtaining and processing additional information. It accepts ‘good enough’ as a start point, and is really, really good at not locking into decisions prematurely, but using feedback loops to adjust on the fly. It uses heuristics for quick decisions rather than certainty. Given that it’s the pinnacle of millions of years of evolution, it’s probably not a bad thing if our organizations more closely mirror it.

Assuming we eventually vanquish Covid, we’ll all be searching for new equilibriums as the world restabilizes. There are things I’m personally really keen to bring back, such as the serendipity that comes from real human-to-human interaction. But I also hope we don’t loose what we’ve learned. Risk aversion will nudge us to revert back to higher degrees of certainty. And there will certainly be contexts where this makes sense, especially in pharmaceuticals and medicine, where we’ve taken unusual risks because of exceptional time constraints. But in less life and death fields, we may have found we can give people more autonomy, be more selective about consensus, have less meetings, better embrace learning from failure, and may not need as many consumer tests or as precise volume forecasts, as we previously thought. A little bit of agility built into the back end can go a long way to reduce the perceived need of illusory certainty at the front.

Image credit: Pixabay

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COVID-19 Presents an Opportunity to Create an Innovation Culture

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GUEST POST from Pete Foley

I left P&G about eight years ago, and one of my last jobs involved working on innovation culture. It was a passion project, and the topic of one of my first blogs published outside of P&G. It’s also something I keep coming back to, as I believe it is one of, if not the most important components of a successful innovation organization. But I’m writing this because I believe Covid19, together with recent socio-political dynamics has created a once in a lifetime window to effect cultural change in our organizations. It’s a huge opportunity, but one that comes with commensurate risk.

Changing culture is hard. A leadership team can often make a strategic change almost on a dime, but culture has much deeper roots, and so takes longer to change. Strategy is more about what we are doing, culture is more about how we do it. It’s comprised of a multitude of little everyday things that ultimately much of our time. It’s how we make decisions, take risks, act or procrastinate, how much we share, how much we listen. In other words it’s deeply linked to fundamental behavior and values, and is heavily influenced by habits and the unconscious decisions frameworks that Daniel Kahneman calls System 1 thinking. As such, it cannot be changed by management decree. It can be nudged by changing reward or organizational structure, something we tried every few years at P&G. But ultimately changing culture means either changing people’s deeply rooted behaviors, or changing the people themselves.

That’s hard to do, and also inefficient, at least in the short-term. If an innovation team is thinking about process, it’s not thinking about innovations. But Covid19 created a once in a lifetime opportunity. I’d not wish the last 18 months on anyone, but like it or not, our cultures have been disrupted, and that gives us a semblance of a fresh start, and hence an opportunity for change. Habits have already been broken, ‘givens’ challenged and new skills learned. And if the great resignation actually occurs, we can expect an elevated level of personnel movement both between and within companies to go along with broken habits and new skills. A perfect storm for cultural change. .

But how do we take advantage of this rare opportunity? Culture is a big, hairy topic, with a lot of moving parts, so one option is to be a little reductionist, and break it down into it’s component parts. My personal culture model is a hybrid derived from many sources, and comprises Capability, Space, Psychological Safety, Designed Serendipity and Motivation. Let’s look at them in turn:

Capability– Innovation needs people with knowledge and experience. But it also needs fresh perspective. Too much experience locks us into isolated pillars of expertise that make it hard embrace new technology. But too little experience risks the merry-go-round of constantly reinventing the wheel. We need to balance between the two. But we can hit that balance far more effectively if we retain the right kind of experience, experts who are also cognitively agile, open to new experience, and so able to integrate fresh ideas with their hard earned knowledge. The conundrum is that these experts are often the most likely to seek out new challenges, or to relish the risk of career changes. In other words, those most likely to participate in a ‘great resignation’. This makes it imperative to proactively identify, recruit or retain experts with high mental agility, or T-Shaped innovators who can bridge between different groups.

But it’s not enough to get the right mix at the organizational level, we need it to drill down into individual teams. Humans have a habit of self selecting groups that they feel comfortable working with, which can mean diversity within an organization translates into diversity between, rather than within teams. Curating teams to ensure each fully team reflects organizational diversity reduces factions, spreads knowledge, enables cross mentoring and thus creates a stable but not stagnant culture more quickly after a period of change. It also grows the next generation of innovation leaders who have learnt bridging skills ‘on the job’, by working in cognitively diverse teams.

Space –Innovators need time and autonomy. Obviously this needs to be within some reasonable constraints, as businesses today cannot afford ivory towers.. But truly disruptive ideas take time, and some failure along the road to success. Build too much stage gate control into innovation, enforce unrealistic timelines, or talk about productive failure without actually embracing it, and the result will be mediocrity and increasingly smaller innovations. Everything becomes disruptive in name, but not reality. The good news is that this is perhaps the biggest opportunity to come out of Covid19, as for many, remote working has increased both time and autonomy. Of course, remote working comes with downsides, some of which I discuss below, and not everybody has more time at home. But overall we’ve been given a gift of more time and more autonomy. It’s critical that we take full advantage of this, and don’t lose it, or over-manage it in the name of efficiency.

2. Psychological Safety. Failure is now widely acknowledged as part of the innovation process. But in reality, but when the rubber hits the road, it’s still often considered as a negative. After all, we build a culture that values capability and expertise so that we can anticipate ‘obvious’ pitfalls, and so avoid failure. But if we’ve sufficient capability, that makes failures more valuable, as the unexpected is the single biggest source of disruptive and breakthrough innovation. Furthermore, the scientific method, when employed correctly, designs tests to challenge our assumptions, not confirm them. We run tests to uncover unexpected issues before we go to market. So as we rebuild innovation culture, it is critical that the psychology safety needed to fail productively is not just preserved, but enhanced. It really is the key to big ideas. But at the same time, it’s also critical not to confuse it with ‘safe spaces’. Psychological safety has nothing to do with avoiding ideas we are uncomfortable with. Instead it’s about creating an environment where people can safely challenge their own and others’ ideas, share unpopular opinions and failures, and be treated with respect when they do so. That is fundamental to the scientific method, and hence to an effective innovation culture.

3. Designed Serendipity. While this is a reductionist analysis, it’s impossible to avoid how interdependent these components are. Capability needs space to operate, while space helps to create psychological safety. That in turn makes it easier to fail, and share unexpected results. And our most disruptive ideas typically come from those results experts weren’t expecting. Assuming that most competitors have similar pools of expertise, surprising results are the only way to break a close innovation race. These can come from failures, as discussed above. But they can also come from outside, either from someone viewing our results through a different lens, and so seeing something we miss because of confirmation bias, or from somebody sharing information that they wouldn’t realize is relevant to us. While we cannot force this type of cross- disciplinary interaction to occur per se, we can design organizations to facilitate it. We can create spaces where people mix and communicate informally. Or run training sessions that bring together mixed teams. A coffee bar in a work place, or an excellent cafeteria that encourages people to stay on site and mix all have benefits that are hard to quantify, but can also do an enormous amount to trigger an innovative culture. But much of this requires people to be physically present. Remote working provides time and convenience benefits, and works well for some tasks. But we need to prevent the pendulum from swinging too far. Whether it’s the serendipity of unexpected discussions at the water cooler, or the subtle body language that encourages someone to share a counter intuitive idea, or a failure, some personal interactions work better when people are physically in the same place. We can certainly learn from our Covid experience, and reduce non productive time in the office. But subtleties such as body language and microexpressions get lost on Facetime, making tough discussions tougher, sharing ‘bad’ results harder. And without physical presence, we’ll lose much of the serendipity of insight and information sharing in common physical spaces. We don’t have to go back to where we were, but getting the balance right will drive competitive advantage by optimizing sharing, serendipity, and recruitment and retention.

4. Motivation. I’ve saved what I think is the hardest topic until last. Intrinsic motivation is absolutely key to an innovative culture. If people love what they are doing they will go the extra mile. Passion means problems stay top of mind, increasing the chances of serendipitous innovation, or ‘Eureka moments’. Money is important if you don’t have enough, but it’s intrinsic motivation that drives disruptive innovation. That motivation largely comes from one or all of three places; fascination with a problem, deep commitment to a team or authentic alignment between project and individual purpose. The first two are fairly self-evident. But the last one has always been tricky, and has become more difficult in our post Covid, more polarized world. Firstly, it must be authentic. For example, motivating a team to get behind a sustainability project that turns out to be largely greenwashing, or that evolves from authentic to greenwashing under timing or economic pressure can quickly turn motivation into indifference, or worse. And the line between greenwashing and real environmental initiatives is often more fuzzy than we like to admit. There are inevitably trade offs as we try and balance the needs of a business with the need to improve an environmental footprint, and often what starts as a major benefit gets trimmed en route to market. And it’s not one size fit’s all, as one persons authentic is another persons greenwashing. Furthermore, environmental is probably the easiest of the ‘purpose motivators’ to manage.

For more contentious social justice areas, it’s increasingly likely that not everyone in a team will be aligned with a project. Even if they put aside their personal views, intrinsic motivation will inevitably fall in this situation. Conversely, tap into a teams passions too well, and we risk the core brand or product becoming secondary to the ‘cause’. But even bigger risks as we look outward to the consumer. Even if we have an organization that shares common values, taking a position on a contentious social justice issue is quite likely to alienate a significant segment of consumers. Yet we know from Ehrenburg-Bass research that broad appeal and availability usually generates more volume than loyalty, and so even initiatives that enjoy short-term bumps in volume from socio-political positions can suffer long-term damage. The short-term loyalty they create is often more short-lived than any emotional disconnection from a brand from consumers who disagree. There are also additional issues with cognitive fluency, as while some brands are a good fit with environmental or social justice positions, many are not. Consumers only associate about 1-3 attributes with a brand, and there is a significant risk of with subtraction by addition if a brand starts focusing on communications that are not a fluent fit with core equity.

None of this means we shouldn’t strive to create greener products, and indeed for many categories a healthy environmental profile is rapidly becoming price of entry. The picture with social justice is more complex and more polarized, but again, all companies should strive to do the right thing, and be good corporate citizens. But it’s important to do so carefully, ensure that we’re not alienating consumers, that initiatives are a fit with equity, and are sufficiently differentiated at a time when environmental and social justice communication is pervasive. And there is always the question of source validity, and whether your brand has the perceived authority to take a position on an issue. And if our goal is to improve intrinsic motivation and employee satisfaction, it’s also worth considering that internal cultural benefits can often be achieved more effectively via inwardly facing initiatives that don’t risk alienating consumers.

In conclusion, Covid19 has created opportunity for significant change in innovation culture, and in some cases, that change is already irreversible. But it is sill important to step back, ask ourselves how much we want to change, and what parts of our culture we may want to protect. If you are reading this, you are probably an innovator, and so change is in your blood. But do keep in mind that the grass is always greener. Whether we are innovating products, services or organizations, the new often looks better simply because we don’t know the issues we haven’t yet discovered.

I sometimes think innovation is like a giant game of wack-a-mole, where we innovate to improve one area, only to inadvertently create a new unexpected one along the way. Sometimes these are minor, and just a part of the innovation process, sometimes they are much bigger, as in Boeings 737 Max. This does not mean we should stagnate, or miss a once in a generation opportunity. But just as culture is usually slow to change, it’s also slow to fix if we get it wrong. So before messing too much with the DNA of an organization, it’s worth at least considering if the upside is worth the inevitable disruption, both anticipated and unanticipated. We have a once in a lifetime opportunity – don’t miss it, but don’t throw the baby out with the bathwater either!

Image credit: Pixabay

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Mask of the Road Warrior – The Xupermask

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Xupermask on WILL.I.AM

WILL.I.AM and Honeywell have collaborated to bring the Xupermask to market.

What is the Xupermask?

It’s probably easiest to describe the Xupermask as equal parts: health & safety equipment, personal electronics, and fashion statement.

At its heart the Xupermask is a human-centered design intended to empower the user to feel both safe AND productive. It addresses the following set of user needs that are mostly unmet by traditional mask options:

1. Fits well to the face so escaping air doesn’t fog up your glasses
2. Fit also better prevents unsafe air from entering
3. Fans improve the ease of respiration
4. HEPA filters improve air quality
5. Built-in microphone for easier and safer phone calls
6. Built-in Bluetooth noise cancelling headphones for phone and entertainment

For me, the Xupermask seems like overkill for many day to day situations.

But, when I think about getting on public transport every day or flying on a commercial airline cross-country or across an ocean, the idea of having a Xupermask to wear becomes quite appealing.

And for those of us in the western United States, this could come in quite handy during forest fire season – just saying.

What do you think about the Xupermask?

Innovation or not?

Image credit: Xupermask

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Human-Centered Change and Innovation

Innovation, change and transformation thought leadership, lovingly curated by Braden Kelley

Tag Archives: COVID19

The Breakthrough Lifecycle

A Seemingly Useless Idea

Overcoming Resistance

Building Out The Ecosystem

The Paradox Of New Paradigms

Stringing Together an Innovation Story

How convergence and creative collisions fuel invention

How COVID-19 Has Exposed Us

A Failed Market Revolution

Digital Disruption

The Uncertain Promise of Globalization

We Need to Choose Resilience and Grand Challenges Over Output and Disruption

A Human-Centered Approach to Mastering Disruption

Case Study 1: The Global Logistics Industry & The COVID-19 Shock

From Supply Chain Gridlock to Agile Lifeline

Key Lessons from the Logistics Response:

Case Study 2: Netflix vs. Blockbuster – The Empathy Divide

A Masterclass in Customer-Centric Disruption

Key Lessons from Netflix’s Triumph:

The Human Thread: Cultivating Resilience and Reinvention

Four Reasons the Big Quit Exists

A Brave Post-Coronavirus New World

Pervasive Transformation

The Rise of Heterogeneous Computing

A Shift From Bits to Atoms

Collaboration is the New Competitive Advantage

Cognitive Bandwidth – Staying Innovative in ‘Interesting’ Times

Innovation in the time of Covid – Satisfycing Organizations

COVID-19 Presents an Opportunity to Create an Innovation Culture

Mask of the Road Warrior – The Xupermask