Author Archives: Greg Satell

About Greg Satell

Greg Satell is a popular speaker and consultant. His latest book, Cascades: How to Create a Movement That Drives Transformational Change, is available now. Follow his blog at Digital Tonto or on Twitter @Digital Tonto.

Better to be Careful than Smart

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GUEST POST from Greg Satell

Not too long ago, I had a post about the danger of trusting your feelings go viral on LinkedIn. The reason it was so popular wasn’t necessarily that everyone liked it, but because many wanted to voice their disapproval. A surprising number of people vehemently objected to the idea that they should interrogate their feelings or keep them in check.

Make no mistake. While it is true that our emotions can alert us to dangers that our rational mind fails to recognize, they can also lead us wildly astray. Our hippocampus, where our memories reside, has a bee line to our amygdala, which plays a role in governing our emotions, circumventing our rational brain in the prefrontal corpus.

We tend to assume that good judgment is a function of intelligence and education, but often it’s not. We need to recognize that there are glitches in our neural machinery and that our gut feelings can be triggered by random events as well as by people who seek to manipulate us. That’s why we need to be careful. It’s always the suckers who think they’re playing it smart.

Why Smart People Are So Easily Fooled

For decades, the global elite revered Bernie Madoff as one of the world’s most talented asset managers until it was all exposed to be, in his own words, “one big lie.” Elizabeth Holmes’s prominent board at Theranos were so clueless that they put their reputations behind a product that didn’t exist. Anna Sorokin, the daughter of a Russian truck driver, was able to convince the glitterati that she was, in fact, a fabulously wealthy heiress.

In each case, there was no shortage of opportunities to unmask the fraud. Inconsistencies in Madoff’s records were reported to regulators a number of times, but were ignored. Holmes wasn’t able to produce a single peer-reviewed study during 10 years in business to support her claims and there was no shortage of whistleblowers from inside and outside the company. Anna Sorokin left unpaid bills all over town.

Still, many bought the ruses and would interpret facts to support them. Madoff’s secrecy was seen as confirmation that he had a proprietary method. In Holmes’ case, her eccentricities were taken as evidence that she truly was a genius, in the mold of Steve Jobs or Mark Zuckerberg. Sorokin’s unpaid bills were seen as proof of her wealth. After all, who but the fabulously rich could be so nonchalant with money?

People should have known better. Stock market regulators are trained to recognize fraud. Prominent Theranos board members like George Shultz, David Bois and Henry Kissinger, earned their reputations over decades. Hotels allowed Sorokin to stay in luxury suites for weeks at a time before demanding payment. How could they have been so naive?

But what if smart people get taken in because they’re smart? They have a track record of seeing things others don’t, making good bets and winning big. People give them deference, come to them for advice and laugh at their jokes. They’re used to seeing things others don’t. For them, a lack of discernible evidence isn’t always a warning sign. It can be an opportunity.

Gated Community Elites And TED Talk Elites

Living in a gated community necessarily cuts you off from your surroundings. People outside can’t wander in and you can’t wander out. New businesses don’t sprout up and old ones don’t die. Routines are familiar and protected, you remain in your comfort zone and any random disturbance is immediately removed.

On the other end of the spectrum, when you go to fancy conferences your imagination becomes overstimulated. You are inundated with the new and unfamiliar. The normal human experiences begin to seem passé, a remnant of a lost age, while visions of the future begin to appear more genuine than the present reality.

The truth is that both of these environments are manufactured for the tastes of the well-heeled. Gated communities are built for those who want a simple sanctuary in a messy and complex world that doesn’t always follow a linear and understandable logic. The conference world tends to overemphasize the power of imagination and possibility, ignoring the fact that the status quo exerts a power of its own.

The best indicator of what we think and what we do is what the people around us think and do. We tend to conform to the opinions and behaviors of those around us and this effect extends out to three degrees of relationships. So not only our friends’ friends, influence us deeply, but their friends too—people that we don’t even know—affect what we think.

Confirming Our Priors

Clearly, the way we tend to self-sort ourselves into homophilic, homogeneous groups shapes how we perceive what we see and hear, but it will also affect how we access information. When a team of researchers at MIT looked into how we share information—and misinformation—with those around us. What they found was troubling.

When we’re surrounded by people who think like us, we share information more freely because we don’t expect to be rebuked. We’re also less likely to check our facts, because we know that those we are sharing the item with will be less likely to inspect it themselves. So when we’re in a filter bubble, we not only share more, we’re also more likely to share things that are not true. Greater polarization leads to greater misinformation.

We’re prone to think of our brains as biological forms of computers that take in and analyze data leading to rational conclusions. That’s not true. We tend to seize upon the most easily available information, rather than the most reliable sources. We then seek out information that confirms those beliefs and reject evidence that contradicts existing paradigms.

That’s the glitch in our mental machinery that Madoff, Holmes and Sorokin exploited. The investors in Madoff’s funds felt privileged to be allowed into an exclusive investment. Theranos board members thought they were building a better future. Sorokin made those around her feel like they had access to an aristocracy of sorts.

These weren’t mere notions or passing thoughts, but assertions of identity, which is why the shills were so eager to advocate for — and actively protect — their swindlers.

Making Allowances For The Glitches In Our Mental Machinery

We all like to have opinions and like act on them. When, for instance, people were asked if they supported bombing Agrabah, the fictional hometown of the Disney character Aladdin, 30% of Republicans and 19% of Democrats said yes. Yet our urge to make judgments has nothing to do with our ability to make wise choices.

Humans tend to think in terms of narratives. We like things to fit into neat patterns and fill in the gaps in our knowledge so that everything makes sense. People who are “smart,” have a greater ability to retain and process information than most and can use their imagination to build robust visions, but that’s no guarantee those visions will conform to reality.

We need to be hyper-aware that a track record of success makes us more confident and confidence in our judgments is inversely correlated to their accuracy. That’s why it’s often better to be careful than smart. There are formal processes that can help us do that, such as pre-mortems and red teams, but most of all we need to keep ourselves in check.

Perhaps most important is to appreciate that there are glitches in our mental machinery and we are greatly influenced by our social networks. The people around us tend to have access to similar information as we do and our perceptions are colored by prior judgments we’ve made. We are surrounded by mental minefields and the only way out is to proceed with caution.

There’s a sucker born every minute and they’re usually the ones who think they’re playing it smart.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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We Must Think Less Like Engineers and More Like Gardeners

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We Must Think Less Like Engineers and More Like Gardeners

GUEST POST from Greg Satell

In February, 1919, the famous philosopher Bertrand Russell received a card from his former student, Ludwig Wittgenstein, who was at that time in an Italian prison camp. “I’ve written a book which will be published as soon as I get home,” he would say in subsequent correspondence. “I think I’ve solved our problems finally.”

The “problems” he spoke of had to do with a foundational crisis in mathematics and logic that defied the efforts of the world’s greatest minds. The book, Tractatus Logico-Philosophicus, was an attempt to engineer a perfectly logical language from first principles. It would become enormously influential, leading to the Vienna Circle and the logical positivist movement of the 1920s.

Yet Wittgenstein would later disown the idea and it was, in the end, found to be unworkable. There are limits to what we can engineer. The world is a messy place. Rules inevitably have exceptions, which is why every system will always crash. That’s why we need to think less like engineers making machines and more like gardeners that grow and nurture ecosystems.

The Death of the Secular Gods

The problems Russell and Wittgenstein were working on were part of a larger paradigm shift. By the late 19th century, many intellectuals had begun to question ideas passed down from the ancient Greeks, such as Aristotle’s Logic, Euclid’s geometry and the miasma theory in medicine, overturning two thousand years of conventional wisdom.

It’s hard to overstate the seismic shift that this represented. Aristotle’s use of the syllogism, in which conclusions necessarily followed premises, Euclid’s postulate that parallel lines never intersect and Hippocrates theory that bad air causes disease, were considered to be the basic foundations upon which western thought was predicated.

Yet as human knowledge advanced, people began to see flaws in these precepts. Strange paradoxes called Aristotle’s logic into question. Mathematicians like Gauss, Lobachevsky, Bolyai and Riemann began to imagine curved spaces in which parallel lines did, in fact, intersect and scientists such as Robert Koch, Joseph Lister and Louis Pasteur established the germ theory of disease.

These would be, practically speaking, incredibly positive developments. The rise of non-Euclidean geometry made Einstein’s general theory of relativity possible and the germ theory of disease paved the way for antibiotics and much longer lifespans. Yet they created an unwarranted optimism about what the human mind could achieve.

A New Religion

In the early 20th century, science and technology emerged as a rising force in western society. The new wonders of electricity, automobiles and telecommunication were quickly shaping how people lived, worked and thought. Physicists like Einstein and Bohr became celebrities. It seemed that there was nothing that scientific precision couldn’t achieve.

It was against this backdrop that Moritz Schlick formed the Vienna Circle, which became the center of the logical positivist movement and throughout the 20’s and 30’s. At its core was Wittgenstein’s theory of atomic facts, the idea that the world could be reduced to a set of statements that could be verified as being true or false—no opinions or speculation allowed. Those statements, in turn, would be governed by a set of logical algorithms which would determine the validity of any argument.

Yet even as this logical movement was growing, the foundational crisis in logic continued. To solve the problem, David Hilbert the greatest mathematician of the era, proposed a program to solve the crisis that rested on three pillars. First, mathematics needed to be shown to be complete in that it worked for all statements. Second, mathematics needed to be shown to be consistent, no contradictions or paradoxes allowed. Finally, all statements need to be computable, meaning they yielded a clear answer.

Then things took a surprising turn. A young logician named Kurt Gödel would prove that every logical system is flawed with contradictions. Alan Turing would show that all numbers are not computable. The Einstein-Bohr debates would be resolved in Bohr’s favor, destroying Einstein’s vision of an objective physical reality and leaving us with an uncertain universe.

The Rise Of Faux Scientists

The verdict was in. Facts could never be absolutely verifiable, but would stand until they could be falsified. We could, after thorough testing, increase our confidence, but never be completely sure. Ironically, the demise of logic led directly to the era of digital computing and a new, technological age. Just as we learned that systems would always be fallible, the machines we built became unimaginably powerful.

At the same time, human agency was increasingly called into question. It was, after all, subjective judgements that led to the Great Depression of the 1930s and the enormous wars that followed it. As the Baby Boomers came of age in the 1960s, it seemed like everything was up for debate. All of the fuzziness and uncertainty of relying on human judgment increasingly seemed impractical.

Much like Wittgenstein and the Vienna Circle, a number of thinkers sought to engineer systems that would harness natural forces to create better outcomes. The Austrian School of economics eschewed government regulation in favor of consumer preferences. Neorealism in foreign relations argued that competition and conflict could govern that international order.

Yet unlike the original logical positivists, these ideas wouldn’t stay confined to academia, but would seep into the affairs of everyday people. The consumer welfare standard insisted that market price signals, not government bureaucrats, would decide if a transaction should be permitted, while the principle of shareholder value demanded that the stock market, not managers, should govern business decisions.

The results are clear. Too little antitrust regulation has increased concentration in the vast majority of American industries and strangled competition, which has decreased business dynamism and lowered productivity. Our economy has become markedly less productive, less competitive and less dynamic. Purchasing power for most people has stagnated. By just about every metric, we’re worse off.

We Need To Manage Ecosystems, Not Machines

We like to think of ourselves as rational actors, weighing each piece of evidence before making a decision. Yet our brains don’t work like that. We build up our perspectives through synapses in our brain and through our social networks, which form complex webs of influence. Once we adopt a point of view, we rarely adapt it to new evidence.

Engineers believe in laws that can be understood and put to specific use, so they build machines to perform specific tasks. Gardeners believe in complexity and emergence. They don’t design their garden as much as tend to it, nurture it and support its surrounding ecosystem. They don’t expect the same results every time, but understand they will need to adjust their approach as they go.

We need to think less like engineers and more like gardeners. For most important purposes, we manage ecosystems, not machines. We need to think more in terms of networks that grow and less in terms of nodes whose behavior we can predict and control. Our success or failure depends less on individual entities than the connections between them.

In a world driven by networks and ecosystems, we can no longer treat strategy as if it were a game of chess, planning out each move with near perfect precision and foresight. The task of leadership is to make decisions with full knowledge that many will be wrong and that you will need to make them right.

There’s no system to do that for us, no impersonal forces that will point the way. In the end, we have to put trust in ourselves. There isn’t anyone else.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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Business Leaders Must Learn About Political and Social Movements

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GUEST POST from Greg Satell

Business leaders have long been fascinated by the military. When Alfred Sloan created the modern corporation at General Motors, he based it on the army. In Wall Street, the antihero Gordon Gecko habitually quoted Sun Tzu. Retired generals like Stanley McChrystal earn huge fees advising CEOs and speaking to corporate conferences.

But what about nonviolent conflict? Research has shown non-violent movements are far more successful than violent uprisings, prevailing against powerful regimes against seemingly insurmountable odds. Yet, apart from a stray Gandhi quote here or Martin Luther King Jr. slide there, these go largely unexamined in the business world.

That’s a mistake. As I explained in Cascades, business leaders can learn a lot from the principles of social and political movements. There is abundant scholarship, going back decades, about why efforts succeed and fail. We know what works and what doesn’t. If you’re serious about being a transformational leader, you need to understand these strategies.

We Need To Learn About Not Only Successes—But Failures Too

Organizations are often inscrutable and hard to research. That’s why the preferred mode of analysis is case studies in which insiders are interviewed and a particular situation is interpreted by investigators. These can be helpful, but they also have severe limitations.

First, with shareholders and customers to please, managers are rarely eager to talk about failures. So we usually only hear about successes. Those, of course, are important but also subject to survivorship bias. For example, if a risky strategy results in 1% of the firms being wildly successful and 99% going out of business, then we’ll tend to hear glowing accounts of that lucky 1% and we’ll miss the vast majority that flamed out.

Social and political movements, on the other hand, are largely public events. Gandhi’s Himalayan miscalculation is just as well documented as his triumphant Salt March. We know as much about the failures of #Occupy as we do the ultimate success of the LGBTQ movement. We can look at similar strategies in different contexts and different strategies in similar contexts.

That’s extremely important. We need to learn from failures. It’s one thing to look at a strategy that succeeded, but can it prevail consistently or was that a one-off? Is it a universally successful strategy or highly dependent on context? We need to ask these questions relentlessly and it’s very hard to do that if we only look at the winners.

Change Is Always Multifaceted, We Need to Understand Multiple Perspectives

Another issue with the case study method is that it is necessarily limited. When researchers did a case study on company I used to run, to take just one example, they interviewed insiders (including me) and did their best to interpret what they heard and what they could glean from background information regarding the market.

Yet while I don’t think anything was inaccurate, it wasn’t exactly the truth either. Only a handful of people were interviewed, almost all of them were concentrated in a single part of the business and none of them, besides me, were involved in making decisions. The issues presented in the case study simply weren’t the ones we were actually wrestling with.

Now consider the prominent sociologist Doug McAdam’s paper on recruiting for Freedom Summer during the civil rights movement. He was able to analyze the applications of not only 720 volunteers, but 239 others that withdrew and 55 that were rejected. He conducted 80 in-depth personal interviews and, because the applications asked for social contacts, McAdam was able to document social ties.

That type of documentation simply doesn’t exist in case studies of firms’ internal deliberations and decision making. We rarely get access to internal data, much less insights from partners, customers, competitors and regulators. With social and political movements, on the other hand, we can examine thousands of first-hand accounts from every perspective.

That’s important, because the world is a messy place with a lot going on. Outcomes rarely boil down to a single decision and even key players disagree on which factors were determinant.

We Need To Overcome Resistance

Look at most change management models and what you see is mostly advice that is focused on persuasion. They suggest that the way to drive a transformation is to tell people about it. By creating a sense of urgency and need, you can build a coalition that will implement the change and shift practices for the long term.

Unfortunately, decades of serious research shows that the world doesn’t work that way. Researchers have long been aware of a so-called KAP-gap in which shifts in “knowledge” and “attitudes” don’t necessarily lead to a change in “practices.” For any given change there will also be people who will vehemently resist it, not for any rational logic, necessarily, but for reasons related to identity, dignity and sense of self.

On the other hand, in social and political movements the need to overcome robust—and even violent—resistance is front and center. Practitioners have developed tools such as the Spectrum of Allies and the Pillars of Support as well as innovative strategies like Dilemma Actions. We have decades of documentation on how these worked in a variety of contexts.

Make no mistake. We can’t simply cheerlead change. No one is going to embrace transformation simply because you came up with a fancy slogan. The truth is that whenever you ask people to change what they think or what they do, there will always be some who won’t like it and they will work to undermine what you’re trying to achieve in ways that are dishonest, underhanded and deceptive.

You need to prepare for that and you will learn far more from social and political movements than consultants interpreting case studies.

Change Is Too Important Not To Take Seriously

The most important challenge leaders face is to navigate change. We can optimize operations, streamline our organizations and motivate our people, but eventually our square-peg business will meet its round-hole world and we will need to adapt, build new skills and shift our strategies. Unfortunately, the overwhelming evidence suggests that we will fail.

Consider that, after decades of trying, skills like lean manufacturing, agile development and overcoming unconscious bias are woefully under-adopted in most organizations. Study after study shows that the vast majority of transformational efforts fail. We can’t continue to do the same thing and expect different results.

One reason for this dismal performance is how we research and learn about change. Today’s change management models simply aren’t based on facts or evidence, but rather the interpretation of case studies. Those can help us understand nuance and give us greater depth, but they are no substitute for rigorous research.

The truth is that we know a lot about change. Decades of studies have shown us that new ideas tend to come from outside the community and incur resistance. Research has shown there is a persistent gap between what people know and what they actually put into practice. We also know that transformation follows an s-shaped curve and that ideas are transmitted socially.

Unfortunately, current organizational change practices address none of these challenges. However, social and political movements do and through the work of scholars like Gene Sharp and practitioners Srdja Popović we know what works and what doesn’t. My own work has shown that these principles can be put to use in organizations.

The future is simply too important to be left to superstition and fantasy.

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

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Ideas Are Validated Forwards Not Backwards

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Ideas Are Validated Forwards Not Backwards

GUEST POST from Greg Satell

In 2007, our media company in Ukraine completed its IPO and would soon be valued at $100 million. For a rough and tumble organization that, just a few years before, was a relatively small business, it was exhilarating. We had big plans and were eager to execute them. It was a “damn the torpedoes, full speed ahead” moment.

We also had an innovative strategy that we thought was a clear winner — a bet on Ukrainian language media. Although the Russian language was dominant at the time, we thoroughly researched the idea and found that a large part of the market said they preferred Ukrainian. To grab the opportunity, we launched three major brands in a year.

It was a disaster. Although the first launch was cause for concern, we were moving so fast the other two were too far along to stop. Then the 2008 global financial crisis hit and we were soon struggling to stave off bankruptcy. It was a brutal lesson. You can research an idea, but you never really know what you have until you’ve actually tested it in the marketplace.

The Rule Following Paradox

The Philosopher Ludwig Wittgenstein famously wrote, “no course of action could be determined by a rule, because every course of action can be made out to accord with the rule.” He meant that every rule is subject to some interpretation and, given varying contexts, interpretations are bound to vary.

That’s essentially what happened to us. We did our research and combed through all the evidence. Television and advertising was, by law, in Ukrainian and not Russian. Consumer surveys consistently showed that a significant portion of the Ukrainian public preferred Ukrainian language media. There were plenty of signs that we were on to something.

Given that analysis, our course seemed clear. We should not only launch Ukrainian language products, we should proceed at a rapid pace so that we could move out ahead of the pack. Surely, once competitors saw how big the opportunity was, they would pounce and our opportunity would be squandered.

Except that there was no opportunity. We weren’t acting on facts, but our interpretation of them and that interpretation was horribly, drastically wrong. To make matters worse, all this was happening as the Ukrainian media market was hitting its peak and the world was about to head off a cliff into the worst financial crisis since the Great Depression.

Survivorship Bias

Business school professors and consultants gain fame—not to mention large fees—when they are able to define a novel concept or success factor. If you are able to isolate one thing that organizations should do differently, you have a powerful product to sell. A single powerful insight can make an entire career, which is probably why so many cut corners.

For example, in their study of 108 companies, distinguished INSEAD professors W. Chan Kim and Renée Mauborgne found that “blue ocean” products, those in new categories without competition, far outperform those in the more competitive “red ocean” markets. Their book, Blue Ocean Strategy, was an immediate hit, selling over 3.5 million copies.

Bain consultants Chris Zook and James Allen’ book, Profit from the Core, boasted even more extensive research encompassing 200 case studies, a database of 1,854 companies, 100 interviews of senior executives and an “extensive review” of existing literature. They found that firms that focused on their ”core” far outperformed those who strayed.

It doesn’t take too much thinking to start seeing problems. How can you both “focus on your core” and seek out “blue oceans”? It betrays logic that both strategies could outperform one another. Also, how do you define “core?” Core markets? Core capabilities? Core customers? While it’s true that “blue ocean” markets lack competitors, they don’t have any customers either. Who do you sell to?

Yet there is an even bigger, more insidious problem called survivorship bias. Notice how “research” doesn’t include firms that went out of business because there were no customers in those “blue oceans” or because they failed to diversify outside of their “core.” The data only pertains to those that survived.

The Problem With Case Studies

The gold standard for research is randomized, double blind trials in which some of the subjects receive some sort of intervention, a control group gets a placebo and no one, not even those conducting the study, know which subjects are in which group. This design minimizes the chance of bias affecting results.

Yet this type of design is impractical for studying real businesses that are competing in the marketplace. So researchers largely depend on case studies in which participants are interviewed after the fact. These can be helpful in that they offer first-person perspectives of events and their context, but have obvious problems.

First, much like in Wittgenstein’s rule-following paradox, a lot is left up to interpretation. There are rarely more than a half-dozen people interviewed and they tend to be insiders. We almost never hear from competitors, customers or lower level employees. Then the researchers themselves bring their own biases to what they see and hear.

There are also issues with survivorship bias. Clearly, key players will be much more forthcoming about successes than failures. So we tend to hear about strategies that worked when, for all we know, those same strategies may have failed in other organizations and other contexts. There’s simply no real way for us to know.

Incidentally, researchers did a series of case studies on our company and I was struck by how much they depended on who was interviewed. While there wasn’t anything factually wrong, a different sample of perspectives would have led to very different interpretations.

Adopting A Bayesian Strategy

Traditionally, strategy has been seen as a game of chess. Wise leaders survey the board of play, plan their moves carefully and execute flawlessly. That’s always been a fantasy, but it was close enough to reality to be helpful. Organizations could build up sustainable competitive advantage by painstakingly building up bargaining power within the value chain.

Yet as Mike Tyson pointed out, “everybody has a plan until they get hit.” We can research and plan all we want, but the real world is a messy place. The facts, as we see them, are really just interpretations of the data we have available to us. Invariably, there are other data we’re not seeing and, even that which we have in front of us, can be interpreted in multiple ways.

That’s why we need to take a more Bayesian approach to strategy, in which we don’t pretend that we have the “right strategy,” but endeavor to make it less wrong over time. As Rita Gunther McGrath has put it, it’s no longer as important to “learn to plan” as it is to “plan to learn.” We need to be more iterative, see what works and change course as needed.

Today, instead of thinking about strategy as a game of chess, we’d do better to envision an online role-playing game, in which you bring certain capabilities and assets and connect with others to go on quests and discover new things along the way. Unlike chess, where everyone knows that their objective is to capture the opponent’s king, we need to expect the rules to change over time and adapt accordingly.

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

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Five Elements of the Changemaker Mindset

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Five Elements of the Changemaker Mindset

GUEST POST from Greg Satell

Chances are, you work in a square-peg business, because that’s the best way to make money. You work diligently to improve the pegs and to get them to where they need to go better, faster and cheaper. It is through quality and consistency that you can best serve your customers, beat your competition and win in the marketplace.

The problem comes when your square-peg business meets a round-hole world. When that happens, following traditional best practices will only result in getting better and better at doing things people care about less and less. Round holes don’t concern themselves how good your square pegs are or how efficiently you can produce them.

Make no mistake. Eventually, every business eventually finds itself in a round-hole world. That’s why good companies fail. Not because they become stupid and lazy, but because the world changes and they lose relevance. Clearly, in the midst of disruption the only viable strategy is to adapt and shift from a traditional manager mindset to a changemaker mindset.

1. Don’t Look For A Great Idea, Identify A Good Problem

“Build a better mousetrap and the world will beat a path to your door,” Ralph Waldo Emerson is said to have written and since that time thousands of mousetraps have been patented. Still, despite all that creative energy and all those ideas, the original “snap trap,” invented by William Hooker in 1894, remains the most popular.

We’ve come to glorify ideas, thinking that more of them will lead to better results. This cult of ideas has led to a cottage industry of consultants that offer workshops to exercise our creative capabilities. They walk us through exercises like Brainstorming and SWOT analysis. We are, to a large extent, still chasing better mousetraps with predictably poor results.

The truth is that every great change leader starts out with a problem they just couldn’t look away from. Change doesn’t begin with an idea. It starts with identifying a meaningful problem. That’s why it’s so important that before you start an initiative you ask questions like, “What problem are we trying to solve? Is there a general consensus that it’s a problem we need to solve? How would solving it impact our business?

Make no mistake. Change isn’t about ideas. It’s about solving meaningful problems that people care about.

2. Anticipate Resistance

The biggest misconception about change is that if everyone just understood it, they would embrace it. That’s almost never true. Make no mistake, if you intend to create genuine impact, you will get pushback. Some people will hate it with every fiber of their being. Not for any rational logic, necessarily, just because for whatever reason, it offends their dignity, their identity, their sense of self.

In Rules for Radicals, the legendary activist Saul Alinsky observed that every revolution inspires a counterrevolution. That is the physics of change.

Every action provokes a reaction because, if an idea is important, it threatens the status quo, which never yields its power gracefully. Clearly, if you intend to influence an entire organization, you have to assume the deck is stacked against you and anticipate resistance.

A simple truth is that humans form attachments to people, ideas and other things and, when those attachments are threatened we tend to lash out in ways that don’t reflect our best selves. As much as we may hate to admit it, we all do it from time to time. Anyone who has ever been married or part of a family knows that.

That’s why anytime you ask people to change what they think or what they do, there will always be those who will work to undermine what you are trying to achieve in ways that are dishonest, underhanded and deceptive. Once you are able to internalize that, you can begin to move forward.

3. Identify A Keystone Change

Every change effort begins with some kind of grievance: Costs need to be cut, customers better served, or employees more engaged. Wise managers transform that grievance into a “vision for tomorrow” that will not only address the grievance but also move the organization forward and create a better future.

This vision, however, is rarely achievable all at once. Tough and significant problems have interconnected root causes, so trying to achieve an ambitious vision all at once is more likely to devolve into a long march to failure than it is to achieve results. That’s why it’s crucial to start with a Keystone Change, which represents a clear and tangible goal, involves multiple stakeholders, and paves the way for bigger changes down the road.

For example, when Paul O’Neill set out to turnaround Alcoa in the 1980s, he started by improving workplace safety, which also paved the way to improvements in operational excellence. At Experian, when CIO Barry Libenson set out to move his company to the cloud, he started with internal APIs. In both cases, the stakeholders who were won over in achieving the keystone change also played a part in bringing about the larger vision.

Focusing on a keystone change allows you to get out of the business of selling an idea and into the business of selling a success. When people see that something is working, even at a small scale, they want to be involved. They can bring in others who can bring in others still. That’s how you can grow your initiative to create the critical mass that moves the system toward widespread change.

4. Mobilize People To Influence Institutions

In the early 1990s, writer and activist Jeffrey Ballinger published a series of investigations about Nike’s use of sweatshops in Asia. People were shocked by the horrible conditions that workers—many of them children—were subjected to. In most cases, the owners lived outside the countries where the factories were located and had little contact with their employees.

At first, Nike’s CEO, Phil Knight, was defiant. “I often reacted with self-righteousness, petulance, anger. On some level I knew my reaction was toxic, counterproductive, but I couldn’t stop myself,” he would later write in his memoir, Shoe Dog. He pointed out that his company didn’t own the factories, that he’d worked with the owners to improve conditions and that the stories, as gruesome as they were, were exceptions.

The simple truth is that change rarely, if ever, starts at the top because it is people with power that create the status quo. They are attached to what they’ve built and take pride in their accomplishments, just like the rest of us. That’s why, to bring about genuine change—change that lasts—you need to mobilize people to influence institutions (or those, like Knight, who yield institutional power).

Eventually, that’s what happened at Nike. The protests took their toll. “We had to admit,” Knight remembered, “We could do better.” Going beyond its own factories, the company established the Fair Trade Labor Association and published a comprehensive report of its own factories. Today, the company’s track record may not be perfect, but it’s become more a part of the solution than a part of the problem.

If you want to create change in your organization, think about the institutions—both internal and external—that can bring it about. Which departments have budgets that can be deployed in service of change? Which external organizations, whether those are partners, suppliers, customers, industry organizations or regulators that could impact your change environment? Then think about who you can mobilize to influence those institutions.

5. Shift Your Mindset

Most of the time, we operate with a manager mindset and that works fine. We build consensus and execute with predictable outcomes. Our colleagues are motivated, customers are satisfied and everybody is happy. However, in an era of disruption it’s only a matter of time until we need to adapt and drive transformation. That’s never easy.

To pull it off we need to shift from a manager mindset to a changemaker mindset in which we no longer assume an environment of predictability, but explore unknowns in an atmosphere of uncertainty. Not everybody will be willing to make the journey with us, so rather than relying on a consensus, we will need to build a coalition and leave some people behind.

We start not by trying to convince skeptics, but by going to where there is already energy in favor of change. Once we identify those who are already enthusiastic about change, we can empower them to succeed and build on that success until we hit a tipping point (about 10%-25% of the organization) and the transformation becomes self-sustaining.

What makes our current era so challenging is that we often need to operate with both mindsets simultaneously. We can’t afford to put everything on hold while changes are underway, so we need to approach some things as managers and some as changemakers. It can be difficult and stressful, but it’s what needs to be done.

Perhaps most of all, we need to internalize the reality, proven time and time again, that transformation is not only possible, but that it does not have to come from the top. Anyone, anywhere can achieve enormous change. But first, you need to adopt a changemaker mindset.

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

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Misunderstanding Big Ideas is Very Dangerous

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Misunderstanding Big Ideas is Very Dangerous

GUEST POST from Greg Satell

In 1989, just before the fall of the Berlin Wall, Francis Fukuyama published an essay in the journal The National Interest titled The End of History, which led to a bestselling book. Many took his argument to mean that, with the defeat of communism, US-style liberal democracy had emerged as the only viable way of organizing a society.

He was misunderstood. Fukuyama pointed out that even if we had reached an endpoint in the debate about ideologies, there would still be conflict because of people’s need to express their identity. What many thought to be a justification, was actually a warning to expect people to rebel against an order imposed on them.

If you believe history is on your side, you’re likely to throw caution to the wind, get mixed up in things you shouldn’t and, eventually, you’ll pay a price. That’s the problem with big ideas, their nuance is often lost on those who hear them third or fourth hand and the high-stakes game of broken telephone tends to end badly. We need to approach ideas with more care.

The Global Village

Marshal McLuhan’s book Understanding Media, was one of the most influential works of the 20th century. In it, he described media as “extensions of man” and predicted that electronic media would eventually lead to a global village. Communities would no longer be tied to a single, isolated physical space but connect and interact with others on a world stage.

To many, the rise of the Internet confirmed McLuhan’s prophecy and, after the fall of the Berlin Wall, digital entrepreneurs saw their work elevated to a sacred mission. In Facebook’s IPO filing, Mark Zuckerberg wrote, “Facebook was not originally created to be a company. It was built to accomplish a social mission — to make the world more open and connected.

Yet, importantly, McLuhan did not see the global village as a peaceful place. In fact, he predicted it would lead to a new form of tribalism and result in a “release of human power and aggressive violence” greater than ever in human history, as long separated—and emotionally charged—cultural norms would now constantly intermingle, clash and explode.

For many, if not most, people on earth, the world is often a dark and dangerous place. For predators, “open” is less of an opportunity to connect than it is a vulnerability to exploit. Things can look fundamentally different from the vantage point of, say, a tech company in Menlo Park, California then it does from, say, a secured facility in St. Petersburg.

Context matters. Our most lethal failures are less often those of planning, logic or execution than they are that of imagination. Chances are, most of the world does not see things the way we do. We need to avoid strategic solipsism and constantly question our own assumptions.

The Paradigm Shift

The term paradigm shift has become so common that we scarcely stop to think about where it came from. When Thomas Kuhn first introduced the concept in his 1962 classic The Structure of Scientific Revolutions, he described not just an event, but a process that he noticed had pervaded the history of science.

It starts with an established model, the kind we learn in school or during initial training for a career. Models become established because they are effective and the more proficient we become at applying a good model, the better we perform. We then rise through the ranks and become successful.

Yet no model is perfect and eventually anomalies show up. Initially, these are regarded as “special cases” and are worked around. However, as the number of special cases proliferate, the model becomes increasingly untenable and a crisis ensues. At this point, a fundamental change in assumptions needs to take place if things are to move forward.

However, as Kuhn noted, the shift in thinking almost never goes smoothly. Most experts cling to the old model, because that’s what made them successful in the first place. The physicist Max Planck, who helped shift a number of paradigms himself, pointed out that “a new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”

The idea of paradigms shifting seems so hopeful and romantic that we often forget how hard it is for people’s mental models to change. The simple fact is that any time you set out to make a significant impact there will be people who won’t like it and will work to undermine you in ways that are dishonest, underhanded and deceptive.

Disruptive Innovation

In the 1990s, a newly minted professor at Harvard Business School named Clayton Christensen began studying why good companies fail. What he found was surprising. They weren’t failing because they lost their way, but rather because they were following time-honored principles taught at his institution, such as listening to their customers, investing in R&D and improving their products.

As he researched further he realized that, under certain circumstances, a market becomes over-served, the basis of competition changes and firms become vulnerable to a new type of competitor. In his 1997 book, The Innovator’s Dilemma, he coined the term disruptive technology to describe what he saw.

It was an idea whose time had come. The book became a major bestseller and Christensen the world’s top business guru. Yet many began to see disruption as more than a special case, but a mantra; an end in itself rather than a means to an end. This wasn’t, to be fair, what he envisioned, but things took on a life of themselves.

The results of all this disruption have been, by just about every measure, awful. Despite the hype, productivity growth has been depressed for most of the last 30 years. Our economy has become markedly less productive, less competitive and less dynamic, Income inequality is at levels not seen for a century and most American families are worse off.

Beware Of The Cult Of Inevitability

Big ideas are powerful because they encapsulate an essential truth. When Fukuyama wrote about “the end of history,” it really did mark a turning point in human affairs, just as Marshall McLuhan’s concept of a “global village” identified a shift in communications, Kuhn’s model of a paradigm shift helped us understand how scientific breakthroughs occur and Christensen’s ideas about disruptive innovation alerted us to dangers and opportunities we weren’t aware of.

Yet these ideas were important precisely because they described complex things. Once they rise to the level of a meme, we tend to discard the complex core and focus only on the candy shell. The concept becomes a caricature of itself, repeated so often that few stop to think about its implications and limitations, where it applies and where it does not.

The problem with big ideas is that they can seem so inevitable that we ignore human agency. If we are truly at an “end of history,” then decisions don’t really matter. A “global village” can seem like such a nice place that we ignore dangers from bad actors. If we believe we are on the right side of a “paradigm shift,” we may not notice those who are working to undermine what we are trying to achieve. “Disruption” can seem so cool we forget about the disrupted.

As Warren Berger explains in A More Beautiful Question, questions are more valuable than answers because, while answers tend to close a discussion, questions help us open new doors and can lead to genuine breakthroughs. That’s the value of big ideas. They can help us ask better questions.

But once we start looking to big ideas for answers, we stop exploring the world around us, our world constricts and, ultimately, we find that we are lost.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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Why Networks Can Outperform Hierarchies

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(And Vice Versa)

Why Networks Can Outperform Hierarchies

GUEST POST from Greg Satell

I still remember the bright autumn day in 2014 when I turned off of the main road in Exton, Pennsylvania onto a remote path. I was going to meet Brian J. Robertson, the creator of a hot new “flat” management approach called Holacracy. I was skeptical, because it seemed to be a cumbersome way to go about governance, but I was open to learning about it.

Many companies, most famously Zappos, were enthusiastically adopting it and there was no shortage of hype among the punditry about abolishing hierarchies. Brian, for his part, was gracious and patient with me, explaining how and why everything worked. Still, I had my doubts and remained unconvinced.

Recently, Stanford’s Bob Sutton pointed to Ronnie Lee’s research that confirmed my (and his) suspicions. While flatter structures can promote creativity, we need hierarchies to execute well. The truth is that hierarchies form naturally and, rather than trying to ignore that basic fact, we need to design enterprises with hierarchical networks in mind.

Evolution, Religion and Leadership

It’s become common today for many, especially in the academic world, to dismiss religion as the product of ancient superstition. Yet in The Righteous Mind, social psychologist Jonathan Haidt makes a powerful case that it plays an important evolutionary role. “There is now a great deal of evidence that religions do in fact help groups to cohere, solve free rider problems and win the competition for group-level survival,” he wrote.

So while many pundits often portray bureaucratic hierarchies as an anachronistic byproduct of the industrial revolution, it seems significant that religions tend to have hierarchical structures. Even religious activities that can be done individually, such as Buddhist meditation, are often led by someone who has an elevated group status.

So it stands to reason that hierarchy plays a similar governance role in organizations, helping to coordinate group activity by setting priorities, establishing basic rules and norms and, when needed, providing impetus to change direction and adapt to external events. Clearly, these are essential governance functions in any enterprise.

Many would say that, in an increasingly digital environment that helps us communicate and coordinate across boundaries of time and space, we simply don’t need the same levels of bureaucratic governance that we used to. However, what Professor Lee found in the startups he researched was that the levels of hierarchy increased significantly over the last 50 years, most probably due to the greater levels of complexity involved in work.

It’s important to note that, even after years of hype, it’s hard to find examples of successful non-hierarchical organizations. Even the rare exceptions, such as the Orpheus Chamber Orchestra, aren’t quite as flat in how they organize work as it would first seem. Zappos would eventually back away from Holacracy as would other early adopters, such as Medium.

Hierarchies Are Networks

The term “network” is often misconstrued. In management circles, it is often used to mean an organic, unfathomable, amorphous structure, but really a network is just any system of nodes connected by links. So, in that sense, any conceivable organizational structure is a network, even a typically hierarchical organizational chart.

The important question is what kind of networks do we want our organizations to be? If we look at the evidence from thousands of years of human civilization, we’d have to conclude that some sort of command and control mechanism is needed. At the same time, as our competitive environment becomes more complex, we want information to be able to go to where it is needed without getting stuck in leadership bottlenecks.

A bit of network science can be helpful here. For functional purposes, networks have two salient characteristics: clustering and path length. Clustering refers to the degree to which a network is made up of tightly knit groups while path length is a measure of social distance—the average number of links separating any two nodes in the network.

Ideally our organizational networks would have a high degree of clustering—to promote close collaboration and teamwork—as well as short path lengths so that information can get from one part of the enterprise to any other part with speed and efficiency. Intuitively, it seems like those two priorities are in conflict. However, thanks to some breakthroughs in network science in the late 90s, we know that such “small world” networks are not only achievable, but common.

What’s really important isn’t how your organizational chart is constructed, but how you design for connection and there are some common sense ways to do that.

Understanding Formal And Informal Structures

Every organization has both formal and informal structures. For example, while ostensibly open source communities have little formal organization, in practice they are very hierarchical, with high-status individuals driving the direction of the project. At the same time, even in a formal organization, there are informal relationships as when, say, you work in sales and your brother-in-law works in logistics in a very different part of the company.

Network scientists call people who link disparate networks in an organization boundary spanners and they are crucial for maintaining culture as an organization grows. Once you understand the importance of boundary spanners, you can start redesigning programs and platforms to optimize for connection.

There are a number of ways to network your organization by optimizing organizational platforms for connection. Facebook’s Engineering Bootcamp found that “bootcampers tend to form bonds with their classmates who joined near the same time and those bonds persist even after each has joined different teams.” At Experian, leadership found that a biking club led to boundary spanning collaborations at work, so they helped more clubs to get organized.

One striking example of how even small tweaks can improve connectivity is a project done at a bank’s call center. When it was found that a third of variation in productivity could be attributed to informal communication outside of meetings, the bank arranged for groups to go on coffee break together, increasing productivity by as much as 20% while improving employee satisfaction at the same time.

Perhaps most famously, Steve Jobs designed the headquarters both at Apple and Pixar to encourage random collisions among employees. It seems we’ve been asking the wrong question. The problem isn’t how we dismantle hierarchies, but how we connect them.

Leading Hierarchical Networks

For decades we’ve been hearing that we need to eliminate bureaucracy and break down silos. Yet there is little evidence of any success. In fact, when management guru Gary Hamel, who has been leading the call to “bust bureaucracy,” surveyed readers at Harvard Business Review he found that levels of organization had increased, not decreased.

The inescapable conclusion is that we’ve failed to do away with hierarchies because they serve a useful purpose. We need them. In much the same way, the much maligned “silos” form around centers of capability as a result of close collaboration. These are good things. We don’t want to eliminate them, we want to support and empower them.

So instead of trying to break down silos, we need to connect them. Network science tells us that it takes just a small amount of boundary spanning “random connections,” in order to bring social distance crashing down. We can’t just look at organizational charts, but need to focus on how meaningful relationships form in the real world.

The role of leadership in organizations has changed. It is no longer merely to plan and direct work, but to inspire meaning and empower belief. As I wrote in Cascades, the key to transformational change is small groups, loosely connected by united by a shared purpose. The job of leaders today is to help those groups connect and forge a common purpose.

If we are to lead effectively in an increasingly ecosystem-driven world, we need to empower networked hierarchies.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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Change Starts with Empathy

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(Even for Your Enemies)

Change Starts With Empathy

GUEST POST from Greg Satell

On September 17th, 2011, protesters began to stream into Zuccotti Park in Lower Manhattan and the #Occupy movement had begun. “We are the 99%,” they declared and as far as they were concerned, it was time for the reign of the “1%” to end. The protests soon spread like wildfire to 951 cities across 82 countries.

It failed miserably. Today, a decade later, it’s hard to find any real objective that was achieved except some vague assertions about “building awareness” and Bernie Sanders’ two failed presidential campaigns. Taking into the count the billions of dollars worth of resources expended in terms of time and effort, that is abysmal performance.

As I explained in Cascades, there were myriad reasons for #Occupy’s failure. One of the gravest errors, however, was the insistence on ideological purity and the lack of any effort to understand those who had different ideas from their own. If you expect to bring change about, you need to attract, rather than overpower. Empathy is a good place to start.

Finding Your Tribe

In 1901, before he became employed by the patent office, a young Albert Einstein put out an advertisement offering tutoring services in math and physics. Maurice Solovine, a Romanian philosophy student, responded to the ad but, after a brief discussion, Einstein told him that he didn’t need lessons. Still, he invited Solovine to come and visit him whenever he wished.

The two began meeting regularly and were soon joined by another friend of Einstein’s, a young Swiss mathematician named Conrad Habicht, and the three would discuss their own work as well as that of luminaries such as Ernst Mach, David Hume and Henri Poincaré. Eventually, these little gatherings acquired a name, The Olympia Academy.

Einstein had found his tribe and it became a key factor in the development of his “miracle year” papers that would turn the world of physics on its head in a few years later. It gave him a safe space to let his mind wander over the great questions of the day, formulate his ideas and get feedback from people that he trusted and respected.

This is a common pattern. Similar tribes, such as, the Vienna Circle, the Bloomsbury Group and the “Martians” of Fasori have, if anything, led to even greater achievement. So it’s easy to understand how those protesters descending on Zuccotti Park, finding themselves amongst so many who saw things as they did, felt as if they were on the brink of a historic moment.

They weren’t. And that’s what’s dangerous about tribes. Although they can lend support to a fledgling idea that needs to be nurtured, they can also blind us to hard truths that need to be examined.

Developing A Private Language

A tribe is a closed network that, almost by definition, is an echo chamber designed to develop its own practices, customs and culture. Perhaps not surprisingly, it is common for these networks to develop their own vocabulary to describe these unique aspects of the tribal experience and to make distinctions between members of the tribe and outsiders.

Consider what happened when Congressman John Lewis, the civil rights legend, showed up at an #Occupy rally in Atlanta. The protesters refused to let him speak. He left quietly and issued a polite statement, but an opportunity was lost and real damage was done to the movement and its cause. If John Lewis wasn’t welcome, what about the rest of us?

Later, the man who led the charge to prevent Congressman Lewis from speaking explained his reasons. He cited his suspicion of Lewis as part of the “two-party system,” which he felt had betrayed the country. Yet even more tellingly, he also explained that his main objection was due to the “form” of the event, which he felt was being violated.

It is common for tribes to fall into this kind of private language trap. The function of communication is inherently social and, if the customs and vernacular that you develop becomes so archaic and obscure that it is unable to perform that function, you have undermined the fundamental purpose of the activity.

Clearly, in any dialogue both the speaker and the listener have a responsibility to each other. However, if you consistently find that your message is not resonating outside your tribe, you probably want to rethink how you’re expressing it.

Shifting From Differentiating Value To Shared Values

Once you start separating yourself off and creating a private language for your adherents, it’s easy to fall into a form of solipsism in which the only meaningful reality is that of the shared experience of the tribe. Many aspiring revolutionaries seek to highlight this feeling by emphasizing difference in order to gin-up enthusiasm among their most loyal supporters.

That was certainly true of LGBTQ activists, who marched through city streets shouting slogans like “We’re here, we’re queer and we’d like to say hello.” They led a different lifestyle and wanted to demand that their dignity be recognized. More recently, Black Lives Matter activists made calls to “defund the police,” which many found to be shocking and anarchistic.

Corporate change agents tend to fall into a similar trap. They rant on about “radical” innovation and “disruption,” ignoring the fact that few like to be radicalized or disrupted. Proponents of agile development methods often tout their manifesto, oblivious to the reality that many outside the agile community find the whole thing a bit weird and unsettling.

While emphasizing difference may excite people who are already on board, it is through shared values that you bring people in. So it shouldn’t be a surprise that the fight for LGBTQ rights began to gain traction when activists started focusing on family values. Innovation doesn’t succeed because it’s “radical,” but when it solves a meaningful problem. The value of Agile methods isn’t a manifesto, but the fact that they can improve performance.

You Never Have To Compromise On Common Ground

One of the things that sticks in my head about my experiences during and after the Orange Revolution in Ukraine was an interview with Viktor Pinchuk. who is not only one of the country’s richest oligarch’s, but also the son-in-law of the former President and, at the time, a member of the Rada, the Ukrainian Parliament.

He was, by any definition, a full-fledged member of the “1%” that #Occupy took to the streets to protest. Before reading the article I would’ve expected him to be bitter about the abrupt shift in power. Yet he wasn’t. In fact, he explained that his biggest concern during the protests was that his own children were in the streets, and he feared for their safety.

The insight underlines one of the fundamental fallacies of failed change efforts like #Occupy and others, both in the streets and in the corporate world. They imagine change as a Manichean struggle between two countervailing forces in which we must either prevail or accept defeat and compromise. That is a false choice.

The truth is that any change we win by vanquishing our opponents is bound to be fleeting. Every revolution inspires its own counter-revolution. Lasting change is always built on common ground. The best place to start is by building empathy for your most ardent adversaries, not to give in to them, but to help you identify shared values.

After the Orange Revolution was over, we would learn that Pinchuk’s father-in-law, Leonid Kuchma, who was still in power, ordered the most reactionary forces in his regime to stand down. As it turned out, there were some places that even the famously corrupt leader would not go. In the end, he understood that his legacy, and therefore his interests, lay with the protesters in the streets.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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Four Things I Have Learned About Ideas

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Four Things I Have Learned About Ideas

GUEST POST from Greg Satell

I’ve always been inspired by ideas. Some, like Aristotle’s logic, shape the world for millennia. Others, like Einstein’s relativity, completely change our conceptions of what is possible. Still others, like mRNA vaccines, seem to emerge at just the right time. Ideas are what have marked humanity’s progress from living in caves to civilizations.

Yet bad ideas can destroy just as completely as good ideas can create. Fascism led Europe to effectively wipe itself out in little more than a decade. Communism relegated hundreds of millions of people to poverty and struggle. Corporate debacles like like Enron, WeWork and Theranos, have shown us that the wrong idea can cost billions.

We need to handle ideas with care, being open enough to new ones so that we don’t miss out on opportunities, but skeptical enough that we don’t get taken in by ones that do harm. What I’ve learned researching innovation and change is that creating, parsing and evaluating ideas is a skill that must be practiced and honed over time. Here are 4 things to keep in mind.

1. Ideas Can Come From Anywhere

Albert Einstein was an outcast in the world of physics when he unleashed four papers on the world that would change the field forever. When Jim Allison discovered cancer immunotherapy, it took him three years to find anyone who would invest in it. Katalin Karikó was told to abandon her research into mRNA vaccines or be demoted.

In The Structure of Scientific Revolutions, science historian Thomas Kuhn explained why breakthroughs so often happen this way. As the world changes and evolves, flaws in existing models become more evident, eventually becoming untenable. That’s what sets the stage for a paradigm shift. “Failure of existing rules is the prelude to a search for new ones,” he wrote.

Yet new paradigms almost always need to be championed by outsiders or newcomers rather than acknowledged experts. As the physicist Max Planck put it “a new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”

In Mapping Innovation, I showed how data and real-world experience bear this out. On the innovation platform Innocentive (now Wazoku Crowd), problems tend not to be solved within the domain in which they arose, but by a practitioner in an adjacent field. In fact, a study analyzing 17.9 million papers found the most highly cited work tended to come from highly specialized experts partnering with an outsider.

2. Ideas Need To Develop Over Time

In 1891, Dr. William Coley had an unusual idea. Inspired by an obscure case, in which a man who had contracted a severe infection was cured of cancer, the young doctor purposely infected a tumor on his patient’s neck with a heavy dose of bacteria. Miraculously, the tumor vanished and the patient remained cancer free even five years later.

It was a breakthrough, of sorts, but for more than a 100 years Coley’s work was viewed with skepticism and, in truth, there were serious problems with it. Coley couldn’t explain the underlying mechanism by which an infection could cure cancer and he couldn’t replicate his results with any consistency. When radiation therapy began showing success, most people forgot about Coley’s and his work.

Yet a small cadre of supporters kept the faith alive. His daughter, Helen Coley Nauts, would establish the Cancer Research Institute in 1953 to support immune-based approaches to cancer treatment. Over the next four decades, glimmers of hope would appear from time to time, but no one could make Dr. Coley’s idea work.

Then, in 1995 there was a breakthrough. Following a hunch, Jim Allison figured that maybe the problem wasn’t that our bodies couldn’t identify and fight cancer cells, but that something was switching the immune response off. If we could switch it back on, we would have a completely new tool to fight cancer. Allison would win the Nobel Prize for his work on the development of the first cancer immunotherapy drug in 2018.

Dr. Coley had the right idea from the start, but it wasn’t enough. It would take over a century to develop better understanding of cancer, genomics, as well as tools like recombinant DNA to make it work. Literally thousands of researchers worked around the globe for decades to make good on an initial insight.

3. Ideas Need Ecosystems

When Jim Allison was finishing up graduate school in the early 1970s, they had just discovered T cells and he was fascinated. He would later tell me how he was amazed about how all these things could be flying around our bodies killing things and somehow not hurt us. He decided to focus his career on figuring out how it all worked.

Over the next decade, Jim and his colleagues started piecing together a larger picture of how the immune system worked through a vast array of signals and receptors that regulate our immune response, triggering it to increase activity and to shut down once the threat has dissolved. A colleague had noticed that one of these molecules inhibited tumor growth.

Dr. Coley and Jim Allison occupied world’s. To Coley, the immune system was like an on/off switch and, triggering the immune system should lead directly to an immune response to fight cancer. Yet Allison was part of a much larger ecosystem that led to a different understanding that allowed him to target a specific receptor in the regulation system. That opened the floodgates and now cancer immunotherapy is a major field of its own.

The simple fact is that ideas need ecosystems. Look at any major technology and it’s not the initial invention that creates the impact, but the secondary and tertiary technologies. Electricity needed appliances to change the world. The internal combustion engine needed vehicles. Computers needed software and the Internet.

We can’t just look at nodes, but must consider networks. It’s through those connections that we create the combinations that can help us solve important problems.

4. You Need To Let The Muse Know You’re Serious

One of the toughest things about ideas is that they can only be validated forward, never backward. You never know if you have the right idea until it’s been tested in the real world and, even then, there could be some confounding factor you may be missing. As Kevin Ashton put it, “Creation is a long journey, where most turns are wrong and most ends are dead.”

That’s tough work. You can’t just expect lightning to strike. Truly creative people know you have to work at it every day. Sometimes it goes easier and sometimes it’s a bit tougher. There are constant disappointments and true epiphanies are rare. But if you keep with it you’ll find that most days you can come up with something, even if it’s something small.

Somebody told me once that you have to let the muse know that you’re serious. Producing ideas leads to more ideas, which allows you to start creating connections between them. The more you produce, the better the chances are that some of those connections will be novel and lead to something important. That’s how you produce an idea that matters.

But even then the work isn’t over, because the world your idea enters into keeps evolving and changing. That’s why you need to share it and encourage others to build on it so that it can grow and reach its true potential. Ideas must combine and recombine so that they can memetically evolve. For our ideas to succeed, we need to serve them well.

As Daniel Dennett put it, “A scholar is just a library’s way of making another library.”

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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Innovation Should Always Serve the People

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Innovation Should Always Serve the People

GUEST POST from Greg Satell

The global activist Srdja Popović once told me that the goal of a revolution should be to become mainstream, to be mundane and ordinary. If you are successful it should be difficult to explain what was won because the previous order seems so unbelievable. That’s what true transformation looks like.

Yet many leaders approach innovation and change as if they were swashbuckling heroes in their own action movie. Companies like Theranos, WeWork and Uber squandered billions of dollars on business models that never made any sense. People post their latest ChatGPT prompts on social media while Elon Musk trolls Twitter.

These days, innovation has become, far too often, solipsistic and self-referential, pursued for the glory of the innovators themselves rather than for the benefit of everyone else and there is increasing evidence the venture-funded entrepreneurship model is crowding out more productive investments. We need to move away from hype and focus on impact.

The Eureka Moment Myth

In 1928, Alexander Fleming, a brilliant but sometimes careless scientist, arrived at his lab after a summer holiday to find that a mysterious mold had contaminated his Petri dishes and was eradicating the bacteria colonies he was trying to grow. Intrigued, he decided to study the mold. That’s how Fleming came to be known as the discoverer of penicillin.

Fleming’s story is one that is told and retold because it reinforces so much about what we love about innovation. A brilliant mind meets a pivotal moment of epiphany and—Eureka!— the world is forever changed. Unfortunately, that’s not really how things work. It wasn’t true in Fleming’s case and it won’t work for you.

The truth is that when Fleming published his results in 1929, few took notice. It wasn’t until 1939, a decade later, that Howard Florey and Ernst Chain came across Fleming’s long forgotten paper, understood its significance and undertook the hard work to transform it into a viable treatment that could actually help people.

Yet even then, to make a significant impact on the world, penicillin had to be produced in massive quantities, something that was far out of the reach of two research chemists. Florey reached out to the Rockefeller Foundation for help and moved to the US to work with American labs. In 1943 the U.S.’s War Production Board enlisted 21 companies to produce supplies for the war effort, saving countless lives and ushering in the new age of antibiotics.

The truth is that innovation is never a single event and is rarely achieved by a single person or organization. Rather, it is a process of discovery, engineering and transformation that typically takes decades to complete.

The Rise Of So-So Innovations

It’s been clear for some time now that we’ve been in the midst of a second productivity paradox. The first one, which lasted from the early 1970s to the mid 1990s, saw diminished productivity gains amid increased investment in information technology and prompted economist Robert Solow to note, “You can see the computer age everywhere but in the productivity statistics.”

In 1996, with the rise of the Internet, productivity growth began to boom again but then disappeared just as abruptly in 2004 and hasn’t returned since. Despite the hype surrounding things such as Web 2.0, the mobile Internet and, most recently, artificial intelligence, productivity growth continues to slump.

Part of the answer may have to do with what economists Daron Acemoglu and Pascual Restrepo refer to as so-so technologies, such as automated customer service, which produce meager productivity gains but displace workers nonetheless. In effect, they give the appearance of progress but don’t really improve our lives.

Consider an airport bar where ordering has been automated through the use of touchscreens. It’s hard to see how, given the high rent, food preparation and other costs, this technology would have a dramatic effect on productivity akin to, say, replacing a horse with a tractor in an agricultural economy. In fact, given that the technology hasn’t been widely deployed outside airports, the major effect seems to be inconveniencing patrons.

Acemoglu and Restrepo argue that a large-scale version of this phenomenon has been occurring since the late 80s. Digital technologies, to a large extent, have displaced labor, but have not had the same offsetting productivity impact as earlier technologies so the overall effect is to decrease wages rather than to raise living standards.
What Innovation Really Looks Like

Katalin Karikó, 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. Katalan chose to stick with it and, if the Covid pandemic had never hit, her name might very well be lost to history.

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. Kevin Ashton, who himself first came up with the idea for RFID chips, wrote in his book, How to Fly A Horse, “Creation is a long journey, where most turns are wrong and most ends are dead.”

Because digital technology has become so pervasive, offering a substantial architecture that lends itself to tweaking, we’ve lost the plot. Innovation isn’t about Silicon Valley billionaires peacocking around on social media, but solving important problems. We need to shift our focus from disrupting industries to tackling grand challenges.

Building Collaborative Networks And To Tackle Grand Challenges

While researching my book Mapping Innovation, I had the opportunity to interview dozens of great innovators, from world-class scientists to super-successful entrepreneurs and top executives at some of the world’s largest corporations. I was surprised to find that, in almost every case, they were some of the most thoughtful, generous people I’d ever met.

The truth is that, for innovation, generosity is often a competitive advantage. By actively sharing their ideas, innovators build up larger networks of people willing to share with them. That makes it that much more likely that they will come across that random piece of information and insight that will help them crack a really tough problem.

The digital revolution has been, if anything, a huge disappointment and Silicon Valley’s tendency to be solipsistic and self-referential probably has a lot to do with that. The simple fact is that the developers banging away at their laptops can achieve little on their own. To tackle our most significant challenges, such as curing cancer, climate change and global hunger, they need to work effectively with specialists with different skills and perspectives.

What we need today is to build collaborative networks to solve grand challenges. The recent CHIPS Bill is a good start. It not only significantly increases our investment in basic research and development, but also allocates billions of dollars of investments into building regional ecosystems and advanced manufacturing.

Yet the most important thing we need to change is our mindset. We need to focus less on disruption and more on creation and, to create for the world we need to focus on what it means to live in it. We can no longer measure progress in terms of how many billionaires a technology creates. We need to focus on making a meaningful impact on people’s lives.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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