The Retrofitting of Broadcasting

I returned to my broadcast school for a visit last week. Yes, it was nostalgic, but it was also kind of weird.

Here’s why…

I went to broadcast school in the early 80’s. The program I attended, at the Northern Alberta Institute of Technology, had just built brand new studios, outfitted with the latest equipment. We were the first group of students to get our hands on the stuff. Some of the local TV stations even borrowed our studio to do their own productions. SCTV – with the great John Candy, Catherine O’Hara, Eugene Levy, Rick Moranis and Andrea Martin – was produced just down the road at ITV. It was a heady time to be in TV. I don’t want to brag, but yeah, we were kind of a big deal on campus.

That was then. This was now. I went back for my first visit in 35 years, and nothing had really changed physically. The studios, the radio production suites, the equipment racks, the master control switcher – it was all still there – in all its bulky, behemoth-like glory. They hadn’t even changed the lockers. My old one was still down from Equipment Stores and right across from one of the classrooms.

The disruption of the past four decades was instantly crystallized. None of the students today touched any of that 80’s era technology – well – except for the locker. That was still functional. The rows and rows of switches, rotary pots, faders and other do-dads hadn’t been used in years. The main switching board served as a makeshift desk for a few computer monitors and a keyboard. The radio production suites were used to store old office chairs. The main studio; where we once taped interviews, music videos, multi-camera dramas, sketch comedies and even a staged bar fight? Yep, more storage.

The campus news show was still shot in the corner, but the rest of that once state-of-the-art studio was now a very expensive warehouse. The average iPhone today has more production capability than the sum total of all that analog wizardry. Why use a studio when all you need is a green wall?

I took the tour with my old friend Daryl, who is still in broadcasting. He is the anchor of the local 6 o’clock news. Along the way we ran into a couple of other old schoolmates who were now instructors. And we did what middle-aged guys do. We reminisced about the glory days. We roamed our old domain like dinosaurs ambling towards our own twilight.

When we entered the program, it was the hottest ticket in town. They had 10 potential students vying for every program seat available. Today, on a good year, it’s down to 2 to 1. On a bad year, everyone who applies gets in. The program has struggled to remain relevant in an increasingly digital world and now focuses on those who actually want to work in television news. All the other production we used to do has been moved to a digital production program.

We couldn’t know it at the time, but we were entering broadcasting just when broadcasting had reached the apex of its arc. You still needed bulk to be a broadcaster. An ENG camera (Electronic News Gathering) weighed in at a hefty 60 pounds plus, not including the extra battery belt. Now, all you need a smartphone and a YouTube account. The only thing produced at most local stations is the news. And the days are numbered for even that.

If you are middle aged like I am, your parents depend on TV for their news. For you, it’s an option – one of many places you can get it. You probably watch the 6 o’clock news more out of habit than anything. And your kids never watch it. I know mine don’t. According to the Pew Research Center, only 27% of those 18-29 turn to TV for their news. Half of them get their news online. In my age group, 72% of us still get our news from TV, with 29% of us turning online. The TV news audience is literally aging to death.

My friend Daryl sees the writing on the wall. Everybody in the business does. When I met his co-anchor and told her that I had taken the digital path, she said, “Ah, an industry with a future.”

Perhaps, but then again, I never got my picture on the side of a bus.

We Don’t Need More Athletes and Models – We Do Need More People Who Understand Complexity

Have you seen the Verizon ad?

 

The one that starts with LeBron James walking towards the camera. He tells us “We don’t need more LeBrons” He’s followed in quick succession by other celebrities, including model Adriana Lima, quarterback Drew Brees and soccer star David Villa, all saying we don’t need more of their kind. The ad wraps up by saying what we do need is more people in science and technology to fill the 4 million jobs available. Verizon is pitching in by supporting education in STEM subjects (Science, Technology, Engineering and Math). The world, apparently, needs a lot more engineers.

Fair enough. The world runs on science and technology. But there’s an unintended consequence that comes with that. Technology is making the world a more complex place. And what we really need is more people that understand what complexity means.

By complexity, I don’t mean complicated. Those are two different things. I mean complexity in its classic sense – coming from the Latin “com” – meaning “together” – and “plex” – meaning “woven”. “Woven together” is a pretty good starting point for understanding complexity. It’s a concept that depends on connection, and we are more connected than ever before. Whether we like it or not, with connection comes complexity. And when we’re talking about complexity, we’re talking about a whole new ball game where all traditional bets are off.

There’s another funny thing about complexity. It’s nothing new. The world has always been complex. Biology has long been the domain of complex adaptive systems. This is true of all of the physical sciences. Benoit Mandelbrot found fractal complexity in leaves and the coastline of England. Quantum physics has always been around. It wasn’t invented at the beginning of the last century by Max Plank, Albert Einstein and Niels Bohr. It just took us most of our history as a species to discover it, hiding there beneath the deceptively simple rules of Isaac Newton. Complexity has always been part of nature. We’ve just been ignoring it for a long, long time, believing with all our hearts in a simpler, more comprehensible world.

Humans hate complexity, because complexity brings with it unpredictability and an inherent lack of control. It leads naturally into chaos. We much prefer models with foreseeable outcomes. We have been trying for many years to predict the weather, with very limited success. Why? Because weather is complex and often chaotic. And it’s getting more so, not less.

But the extreme weather we’re seeing more and more of is analogous to many parts of our world. Complexity is rearing its head in more and more places. It lies beneath everything. In the words of the Santa Fe Institute, the self-proclaimed world headquarters for complexity science — “(they) endeavor to understand and unify the underlying, shared patterns in complex physical, biological, social, cultural, technological, and even possible astrobiological worlds”

Which means complexity is everywhere. It impacts everything. And almost none of us understand it. But we’ve got to figure this stuff out, because the stakes are huge.

Let’s take something as important to us as democracy, for instance.

There is nothing especially complex about the idea of democracy. But the model of democracy is a different beast, because it relies on the foundation of our society, which is incredibly complex. Democracy is dependent on unwritten rules, which are in turn dependent on conventions and controls that have been inherent in our society. These are what have been called the “soft guardrails of democracy”. And they are being eroded by our newly connected complexity. A few weeks ago, some of America’s top political scientists got together at Yale University to talk about democracy and almost all of them agreed – democracy is in deep trouble. Yascha Mounk, from Harvard, summed up their collective thoughts succinctly: “If current trends continue for another 20 or 30 years, democracy will be toast.”

So complexity is something we should be learning about. But where to start? And when? Currently, if people do study complexity science, it’s generally at the post-grad level. And that’s just a handful of people, at a few universities. We need to start understanding complexity and it’s implications much sooner. It should be covered in grade school. But there’s no one to teach it, because the majority of teachers have no idea what I’m talking about. In a recent dissertation, a researcher from the University of Pennsylvania asked science teachers in a number of schools in Singapore if they were familiar with complexity. The findings were disheartening, “a large sample of ninety Grades 11 and 12 science teachers in six randomly- selected schools across Singapore revealed as many as 80% of the teachers reported that they did not have prior knowledge or heard of complex systems.” By the way, Singapore is consistently rated best in the world for science education. Here in North America, we trail by a significant margin. If this is a problem there, it’s a bigger problem here.

If you’re old enough to remember the movie the Graduate, there was a scene where “the Graduate” – played by Dustin Hoffman – was wandering around his parent’s cocktail party when he was cornered by a family friend; Mr McGuire. McGuire offered a word of career advice. Literally – one word:

“I just want to say one word to you – just one word. Are you listening? Plastics.”

That was 50 years ago. Today, my word is “complexity.”

Are you listening?

Trust No One, Trust Nothing

In just one day last week looking at the headlines on MediaPost – two different articles mentioned a lack of trust – a lack of trust in contextual ad placement and a lack of trust in audience measurement data. But our industries trust issues go far deeper than just those two instances. Article after article cite an erosion of trust and the spreading of relational fault lines in every aspect of the industry.

The question of the day is “Where did the trust go? The follow up question then becomes, “What do we mean by trust?”

That is a difficult question. Trust is a word with many, many meanings. Over 20 years ago, University of Minnesota business professors D. Harrison McKnight and Norman L. Chervany wrote an extensive review to answer just that question. In it, across the many constructs of trust, they identified four dimensions: benevolence, integrity, competence and predictability. But not all these dimensions are required in all applications of trust.

First of all, there are two broad categories of trust: structural trust – trust in a system – and interpersonal trust – trust in a person. In their analysis, McKnight and Chervany looked at six constructs of trust that can apply in different situations. For the sake of this discussion, let’s focus on two of these:

“System trust: the extent to which one believes that proper impersonal structures are in place to enable one to anticipate a successful future endeavor.”

And…

“Situational Trust – meaning that one has decided to trust without regard to the specific persons involved, because the benefits of trusting in this situation outweigh the possible negative outcomes of trusting.”

What trust that did exist in marketing what an outcome of these two constructs. Both tend to apply to the structure of marketing, not the people in marketing. The headlines I cited earlier both pointed to a breakdown of trust on the system level, not the personal level. Now, let’s look at those four dimensions as they apply to structural trust in marketing. No one has ever accused marketers of being overly benevolent, so let’s set that one aside. Also, I would argue – strenuously – that marketers today – including those at agencies – are more competent than ever before. They have been mostly successful at turning marketing from an arcane guessing game that paraded as art to an empirically backed science. So a lack of competency can’t be blamed for this trust breakdown. That leaves integrity and predictability. I suspect there’s a compound relationship between these two things.

The reason we’re losing structural trust is that marketing is no longer predictable. And this lack of predictability is triggering a suspicion that there has been a corresponding lack of integrity. But the unpredictability of marketing is no one’s fault.

Marketing today is analogous to physics at the turn of the last century. For 200 years the universe had been neatly ruled by Newton’s Laws. Then physicists started discovering things that couldn’t be so neatly explained and the Universe became a place of Uncertainty Principles, Schrödinger’s Cat and Strange Attractors. Everything we thought was predictable in all situations suddenly become part of a much bigger – and more complex – mystery.

Similarly, mass marketing could run by Newton-like laws because we were dealing with mass and weren’t looking too closely. Apply enough force to enough people with enough frequency and you could move the needle in what seemed like a predictable fashion. But today marketing is a vastly different beast. We market one-to-one and those “ones” are all inter-connected, which creates all types of feedback loops and network effects. This creates complexity – so predictability is as dead at the afore-mentioned Schrödinger’s Cat (or is it?)

I don’t think this comes as news to anyone reading this column. We all know we’re being disrupted. I think we’re all beginning to understand the challenges of complexity. So why don’t we just accept it as the new normal and continue to work together? Why are clients feeling personally betrayed by their agencies, market research firms and ad delivery platforms? It’s because our brains aren’t very nuanced when it comes to identifying trust and betrayal. Brains operate by the “when you’re a hammer – everything looks like a nail” principle.

Rationally, we understand the different between interpersonal trust and situational trust, but we have to remember that our rationality is reinforced by emotional rewards and cautions. When we’re in a trusting relationship – or system – our ventrial striatum, medial prefrontal cortex and caudate nucleus all perk happily along, priming our brains with oxytocin and pushing all the right reward buttons. But whether it’s a person or a situation that betrays our trust, the same neural mechanisms fire – the insula and amygdala – creating feelings of frustration, fear, anger and resentment.

Now, none of this is the fault of anyone in marketing. But humans work on cause and effect. If our marketing is not working, it’s easier to assign a human cause. And it’s much easier to feel betrayed by a human than by a system.

 

The Assisted Reality of the New Marketer

Last week, MediaPost’s Laurie Sullivan warned us that the future of analytical number crunchers is not particularly rosy in the world of marketing. With cognitive technologies like IBM’s Watson coming on strong in more and more places, analytic skills are not that hot a commodity any more. Ironically, when it comes to marketing, the majority of companies have not planned to incorporate cognitive technologies in the near future. According to a report from IBM and Oxford Economics, only 24% of the organizations have a plan to incorporate CT in their own operations.

Another study, from Forrester, explored AI Marketing Readiness in Retail and eCommerce sectors. The state of readiness is a little better. In these typically forward thinking sectors, 72% are implementing AI marketing tech in the next year, but only 45% of those companies would consider themselves as excelling in at least 2 out of 3 dimensions of readiness.

If those numbers seem contradictory, we should understand what the difference between cognitive technology and artificial intelligence is. You’ll notice that IBM refers to Watson as “cognitive computing.” As Rob High, IBM’s CTO for Watson put it, “What it’s really about is involvement of a human in the loop,” and he described Watson as “augmented intelligence” rather than artificial intelligence.

That “human in the loop” is a critical difference between the two technologies. Whether we like it or not, machines are inevitable in the world of marketing, so we’d better start thinking about how to play nice with them.

 

I remember first seeing a video from the IBM Amplify summit at a MediaPost event last year. Although the presentation was a little stilted, the promise was intriguing. It showed a marketer musing about a potential campaign and throwing “what ifs” at Watson, who quickly responded with the almost instantly analyzed quantified answers. The premise of the video was to show how smart Watson was. But here’s a “what if” to consider. What if the real key to this was the hypotheticals that the human seemed to be pulling out of the blue? That doesn’t seem that impressive to us – certainly not as impressive as Watson’s corralling and crunching of relevant numbers in the blink of an eye. Musing is what we do. But this is just one example of something called Moravec’s Paradox.

Moravec’s Paradox, as stated by AI pioneer Marvin Minsky, is this: “In general, we’re least aware of what our minds do best. We’re more aware of simple processes that don’t work well than of complex ones that work flawlessly.” In other words, what we find difficult are the tasks that machines are well suited for, and the things we’re not even aware of are the things machines find notoriously hard to do. Things like intuition. And empathy. If we’re looking at the future of the human marketer, we’re probably looking at those two things.

In his book, Humans are Underrated, Geoff Colvin writes,

“Rather than ask what computers can’t do, it’s much more useful to ask what people are compelled to do—those things that a million years of evolution cause us to value and seek from other humans, maybe for a good reason, maybe for no reason, but it’s the way we are.”

We should be ensuring that both humans and machines are doing what they do best, essentially erasing Moravec’s Paradox. Humans focus on intuition and empathy and machines do the heavy lifting on the analyzing and number crunching. The optimal balance – at this point anyway – is a little bit of both.

In Descarte’s Error – neurologist Antonio Damasio showed that without human intuition and emotion – together with the corresponding physical cues he called somatic markers – we could rationalize ourselves into a never-ending spiral without ever coming to a conclusion. We need to be human to function effectively.

Researchers at MIT have even tried to include this into an algorithm. In 1954, Herbert Simon introduced a concept called bounded rationality. It may seem like this puts limits on the cognitive power of humans, but as programmers like to say, bounded rationality is a feature, not a bug. The researchers at MIT found that in an optimization challenge, such as finding the optimal routing strategy for an airline, humans have the advantage of being able to impose some intuitive limits on the number of options considered. For example, a human can say, “Planes should visit each city at the most once,” and thereby dramatically limit the number crunching required. When these intuitive strategies were converted to machine language and introduced into automated algorithms, those algorithms got 10 to 15% smarter.

When it comes right down to it, the essence of marketing is simply a conversation between two people. All the rest: the targeting, the automation, the segmentation, the media strategy – this is all just to add “mass” to marketing. And that’s all the stuff that machines are great at. For us humans, our future seems to rely on our past – and on our ability to connect with other humans.

GE: A Different Company for a Different World

One week ago today, John Flannery took over as the new CEO of General Electric. He’s only the 3rd person in the past 36 years to have held the role. He takes over from Jeff Immelt, who in turn inherited the post from the iconic Jack Welch in 2001. Welch started his reign in 1981.

GE has been around for a long time. It actually predates the Dow Jones Index by 4 years (having been founded in 1892) and is the only one of the 12 original companies listed that still exists. It – perhaps more than any other company – serves as a case study for the evolution of the multi-national mega corporation. But GE is in trouble. Share prices are down. It’s struggling to retain its considerable grip on the industries in which it competes. Flannery has his hands full.

The GE story is also interesting because Jack Welch was the first rock star CEO. In 1981, when the Welch reign began, we were still very much in the era where sheer bulk equaled success. Size bestowed a considerable advantage on companies like GE. Welch recognized this and introduced the now famous “Number One or Number Two” strategy; where he pared down GE’s portfolio to just the industries where they could be either first or second in the world.

Ironically, given that he was lionized as one of the great corporate strategists of his era, Welch was relatively unimpressed with the classic interpretation of strategy.

“Forget the scenario planning, yearlong studies, and 100-plus page reports that “gurus” suggest. They’re time consuming and expensive, and you just don’t need them. In real life, strategy is very straightforward. You pick a general direction and implement like hell.”

It was this embracing of flexibility in planning that eventually led Welch to rethink the rigidity of his “One or Two” dictum. Jeff Immelt followed the same playbook, shutting down portfolios like finance and placing a heavy bet on high tech infrastructure. But despite Immelt’s best efforts, GE’s market cap dramatically eroded, shedding almost 30% and $150 billion in value over his 16-year stint as CEO. When you stack it up against Welch’s numbers – a 2790% increase in market cap in the 20 years his hand was on the steering wheel – it’s hard not to come to the conclusion that Immelt was a horrible CEO and Welch was a super star. But as logical as this seems, it’s based on faulty logic – what Phil Rosenzweig calls the Halo Effect. That fact was, the world of Immelt’s GE was a vastly different place than was the world of Welch’s GE, even setting aside mega events like 9/11 and the financial meltdown of 2008.

In those 16 years, many of economist Ronald Coase’s original reasons why a corporation exists disappeared. Most of them had to do with the market friction that came from a rapidly expanding physical market place. If you want the exhaustive analysis of this, go ahead and plow your way through the 600 plus pages of Alfred Chandler’s seminal work – The Visible Hand. But to pare that down to the barest essentials: it was much more efficient to actually build physical things and distribute them to a geographically dispersed market when you had a vertically integrated corporation where you could manage every step of the process. This was the world in which Jack Welch became the CEO of GE.

That’s not the world we live in today. Because transactional friction has been ruthlessly eliminated by technology, the efficiencies of the open market usually equal and sometimes exceed that of a corporation. Need a massive international transactional platform? The emerging blockchain commons can provide that. Need marketing capabilities that weren’t even dreamt of by even the biggest multinationals just a decade ago? Take your pick of almost 5000 MarTech vendors. Your start up office grown too big for your garage? You can even rent a corporate headquarters, complete with all the bells and whistles.

So the biggest question facing Flannery in 2017 is this: Are mega corporations – and, by extension, GE – even relevant any more? If we stick to Coase’s strict definition, the answer is probably no. But perhaps there’s another reason for corporations to exist: the critical mass of innovation.

Although she was vilified for it, I believe Marissa Mayer was on to this when she herded all of Yahoo’s teleworkers into the same physical location. In the infamous memo, Yahoo’s HR Director, Jackie Reses, said,

“Some of the best decisions and insights come from hallway and cafeteria discussions, meeting new people, and impromptu team meetings. Speed and quality are often sacrificed when we work from home. We need to be one Yahoo!, and that starts with physically being together.”

Mayer defended her decision by first acknowledging that “people are more productive when they’re alone,” and then stressed “but they’re more collaborative and innovative when they’re together.

Researchers have found that when the population of a city grows, the amount of productivity scales supralinearly. If you double the population of a city, you don’t just get a 100% boost in productivity, you also get a 30% bonus. Cities are the most effective innovation engines ever devised. And the reason is simple. When you pack a bunch of intellectually diverse people into the same space, magic happens. Mayer understood this. Unfortunately, the realization was “too little, too late” to save Yahoo but that doesn’t mean her logic was faulty.

As John Flannery steps into the CEO role, he may run full speed into the realization that the benefits once bestowed by being massive have turned into liabilities. What once made GE great now threatens to drown it. But there are still 300,000 different minds that work for GE. Frankly I’m not sure mega corporations can ever be relevant again in a friction-free marketplace, but if they can, the answer lies in the innovation potential of those minds.

Sir Martin and the Terrible, Horrible, No Good, Very Bad Week

Sir Martin Sorrell must feel like he’s trying to hold water in his bare hands.

First, the normally bullish European Investment Bank Exane BNP Paribas – double whammied Sorrell’s WPP last week with a double downgrade – from “outperform” to “underperform” – and dropped their target price for the stock by a whopping 27%. The analyst quoted in the release, Charles Bedouelle, said, “Marketing is driven by mobile, nimbler brands, ecommerce and automation. These areas are dominated by platforms where agencies are sparse, raising the risk of lower mid-term growth.”

Then, just yesterday, Mediapost’s Joe Mandese told us that Pivotal Research Group downgraded the entire ad sector, including Interpublic, Omnicom, Publicis and WPP. This time, analyst Brian Wieser said, “While we continue to expect growth for agencies, challenges that became much more visible by the middle of last year are likely to compress expansion in years ahead vs. prior expectations.”

Or, in simpler terms – “The gig is up Guys.”

WPP and the rest of advertising’s usual suspects have depended on an ad market with a significant amount of inherent friction. Friction creates pockets of value for intermediaries, who turn a profit by dealing with that friction on behalf of its clients. This friction has been relentlessly eliminated from the market in the past two decades thanks to technology. Yes, advertising has become more fragmented, but more significantly, it’s also become more fluid. The advantage once offered by agencies has been flipped into an anchor. Business models founded on the exploitation of friction in markets are not very good at dealing with transparency and fluidity.

When I was heading my own digital service company, we could chart the lifespan of a client with pretty reliable predictability. We specialized in search and most of our clients retained us when they were just starting out. This is the period when there is the greatest amount of friction – starting from standing still. We’d get them up and running and within a few months start delivering some pretty impressive ROI numbers. Over the next few years, we’d expand campaigns and find pockets of unexploited potential. Returns would grow. Budgets would increase. Clients would be happy. Life was good.

For awhile.

But there was an inevitable tipping point. As campaigns matured and Google – bless their techie hearts – relentlessly removed friction from the search advertising market, our perceived value would start to decline. At some point, it became an academic line item decision. When the cost of bringing search in house was less than our agency fees, we knew the end was near. We might prolong it for a year or two but the math was working against us. I remember one particularly somber December 24th when we received word from our largest client that they were not renewing our contract for the coming year. That represented about 16% of our total yearly revenue. And this was a client who loved us to pieces just 12 months earlier. It was not a happy Christmas. But it was pretty hard to argue with their logic.

Now, compared to WPP, we were a pimple on the butt of a flea on the tail of a dog who happened to be riding an elephant. And just like WPP, we were always looking for ways to add value by diversifying in other areas. But I suspect the logic is the same. If you depend on friction to add value, and that friction is disappearing, sooner or later you’ll disappear too. Your business model will slip right through your fingers. Just like water in Sir Martin’s hands.

 

The Death of Sears and the Edge of Chaos

So, here’s the question: Could Sears – the retail giant who has become the poster child for the death of mall-based retail shopping – have saved themselves? It’s an important question, because I don’t think Sears was an isolated incident.

In 2006, historian Richard Longstreth explored the rise and fall of Sears. The rise is well chronicled. From their beginnings in 1886, Richard Sears and Alvah Roebuck grew to dominate the catalog mail order landscape. They prospered by creating a new way of shopping that catered specifically to the rural market of America, a rapidly expanding opportunity created by the Homestead Act of 1862. The spreading of railroads across the continent through the 1860’s and 70’s allowed Sears to distribute physical goods across the nation. This, combined with their quality guarantee and free return policy, allowed Sears to rapidly grow to a position of dominance.

In the 1920’s and 30’s, Robert E. Wood, the fourth president of Sears, took the company in a new direction. He reimagined the concept of a physical retail store, convincing the reluctant company to expand from its very lucrative catalog business. This was directly driven by Sear’s foundation as a mail order business. In essence, Woods was hedging his bet. He built his stores far from downtown business centers, where land was cheap. And, if they failed as retail destinations, they could always be repurposed as mail order distribution and fulfillment centers. But Wood got lucky. Just about the time he made this call, America fell in love with the automobile. They didn’t mind driving a little bit to get to a store where they could save some money. This was followed by the suburbanization of America. When America moved to the suburbs, Sears was already there.

So, you could say Sears was amazingly smart with its strategy, presciently predicting two massive disruptions in the history of consumerism in America. Or you could also say that Sears got lucky and the market happened to reward them – twice. In the language of evolution, two fortuitous mutations of Sears led to them being naturally selected by the marketplace. But, as Longstreth showed, their luck ran out on the third disruption, the move to online shopping.

A recent article looking back at Longstreth’s paper is titled “Could Sears Have Avoided Becoming Obsolete?”

I believe the answer is no. The article points to one critical strategic flaw as the reason for Sear’s non-relevance: doubling down on their mall anchor strategy as the world stopped going to malls. In hindsight, this seems correct, but the fact is, it was no longer in Sears DNA to pivot into new retail opportunities. They couldn’t have jumped on the e-com bandwagon, just as a whale can’t learn how to fly. It’s easy for historians to cast a gaze backwards and find reasons for organizational failure, just as it’s easy to ascribe past business success to a brilliant strategy or a visionary CEO. But the fact is, as business academic Phil Rosenzweig shows in his masterful book The Halo Effect, we’re just trying to jam history into a satisfying narrative. And narratives crave cause and effect. We look for mistakes that lead to obsolescence. This gives us the illusion that we could avoid the same fate, if only we are smarter. But it’s not that simple. There are bigger forces at play here. And they can be found at the Edge of Chaos.

Edge of Chaos Theory

In his book, Complexity: Life at the Edge of Chaos, Roger Lewin chronicles the growth of the Santa Fe Institute, an academic think tank that has been dedicated to exploring complexity for the last 33 years now. But the “big idea” in Lewin’s book is the Edge of Chaos Theory, a term coined by mathematician Doyne Farmer to describe a discovery by computer scientist Christopher Langton.

The theory, in its simplest form, is this: On one side you have chaos, where there is just too much dynamic activity and instability for anything sustainable to emerge. On the other side you have order, where rules and processes are locked in and things become frozen solid. These are two very different states that can apply to biology, sociology, chemistry, physics, economics – pretty much any field you can think of.

To go from one state – in either direction – is a phase transition. Everything changes when you move from one to the other. On one side, turmoil crushes survivability. One the other, inertia smothers change. But in between there is a razor thin interface, balanced precipitously on the edge of chaos. Theorists believe that it’s in this delicate interface where life forms, where creativity happens and where new orders are born.

For any single player, it’s almost impossible to maintain this delicate balance. As organizations grow, I think they naturally move from chaos to order, at some point moving through this exceptional interface where the magic happens. Some companies manage to move through this space a few times. Apple is such a company. Sears probably moved through the space twice, once is setting their mail order business up and once with their move to suburban retail. But sooner or later, organizations go through their typical life cycle and inevitably choose order over chaos. At this point, their DNA solidifies to the point where they can no longer rediscover the delicate interface between the two.

It’s at the market level where we truly see the Edge of Chaos theory play out. The theory contests that adaptive systems in which there is feedback continually adapt to the Edge of Chaos. But, as in any balancing act, it’s a very dynamic process. In the case of sociological evolution, it’s often a force (or convergence of forces) of technology that catalyzes the phase transition from order back to chaos. This is especially true when we look at markets. But this is an oscillation between order and chaos, with the market switching from phases of consolidation and verticalization to phases of chaos and sweeping horizontal activation. Markets will swing back and forth but will constantly be rewarding winners that live closest to the edge between the two states.

We all love to believe that immortality can be captured in our corporate form, whether it be our company or our own body. But history shows that we all have a natural life cycle. We may be lucky enough to extend our duration in that interface on the edge of chaos, but sooner or later our time there will end. Just as it did with Sears.