Category Archives: Big Data vs Strategy

Media Buying is Just the Tip of Advertising’s Disruptive Iceberg

Two weeks ago, Gary Milner wrote a lucid prediction of what advertising might become. He rightly stated that advertising has been in a 40-year period of disruption. Bingo. He went on to say that he sees a consolidation of media buying into a centralized hub. Again, I don’t question the clarity of Milner’s crystal ball. It makes sense to me.

What is missing from Milner’s column, however, is the truly disruptive iceberg that is threatening to founder advertising as we know it – the total disruption of the relationship between the advertiser and the marketplace. Milner deals primarily with the media buying aspect of advertising but there’s a much bigger question to tackle. He touched on it in one sentence: “The fact is that a vast majority of advertising is increasingly being ignored.”

Yes! Exactly. But why?

I’ll tell you why. It’s because of a disagreement about what advertising should be. We (the buyers) believe advertising’s sole purpose is to inform. But the sellers believe advertising is there to influence buyers. And increasingly, we’re rejecting that definition.

I know. That’s a tough pill to swallow. But let’s apply a little logic to the premise. Bear with me.

Advertising was built on a premise of scarcity. Market places can’t exist without scarcity. There needs to be an imbalance to make an exchange of value worthwhile. Advertising exists because there once was a scarcity of information. We (the buyers) lacked information about products and services. This was primarily because of the inefficiencies inherent in a physical market. So, in return for the information, we traded something of value – our attention. We allowed ourselves to be influenced. We tolerated advertising because we needed it. It was the primary way we gained information about the marketplace.

In Milner’s column, he talks about Peter Diamandis’ 6 stages that drive the destruction of industries: digitalization, deception, disruption, demonetization, dematerialization, and democratization. Milner applied it to the digitization of media. But these same forces are also being applied to information and rather than driving advertising from disruption to a renaissance period, as Milner predicts, I believe we’ve barely scratched the surface of disruption. The ride will only get bumpier from here on.

The digitization of information enables completely new types of marketplaces. Consider the emergence of the two-sided markets that both AirBNB and Uber exemplify. Thanks to the digitization of information, entirely new markets have emerged that allow the flow of information between buyers and suppliers. Because AirBNB and Uber have built their business models astride these flows, they can get a cut of the action.

But the premise of the model is important to understand. AirBNB and Uber are built on the twin platforms of information and enablement. There is no attempt to persuade by the providers of the platforms – because they know those attempts will erode the value of the market they’re enabling. We are not receptive to persuasion (in the form of advertising) because we have access to information that we believe to be more reliable – user reviews and ratings.

The basic premise of advertising has changed. Information is no longer scarce. In fact, through digitization, we have the opposite problem. We have too much information and too little attention to allocate to it. We now need to filter information and increasingly, the filters we apply are objectivity and reliability. That turns the historical value exchange of advertising on its head. This has allowed participatory information marketplaces such as Uber, AirBNB and Google to flourish. In these markets, where information flows freely, advertising that attempts to influence feels awkward, forced and disingenuous. Rather than building trust, advertising erodes it.

This disruption has also driven another trend with dire consequences for advertising as we know it – the “Maker” revolution and the atomization of industries. There are some industries where any of us could participate as producers and vendors. The hospitality industry is one of these. The needs of a traveller are pretty minimal – a bed, a roof, a bathroom. Most of us could provide these if we were so inclined. We don’t need to be Conrad Hilton. These are industries susceptible to atomization – breaking the market down to the individual unit. And it’s in these industries where disruptive information marketplaces will emerge first. But I can’t build a refrigerator. Or a car (yet). In these industries, scale is still required. And these will be the last strongholds of mass advertising.

Milner talked about the digitization of media and the impact on advertising. But there’s a bigger change afoot – the digitization of information in marketplaces that previously relied on scarcity of information to prop up business models. As information goes from scarcity to abundance, these business models will inevitably fall.

Where Should Science Live?

Science, like almost every other aspect of our society, is in the midst of disruption. In that disruption, the very nature of science may be changing. And that is bringing a number of very pertinent questions up.

Two weeks ago I took Malcolm Gladwell to task for oversimplifying science for the sake of a good story. I offered Duncan Watts as a counter example. One reader, Ted Wright, came to Gladwell’s defence and in the process of doing so, took a shot at the reputation of Watts, saying with tongue firmly in cheek, “people who are academically lauded often leave an Ivy League post, in this case at Columbia, to go be a data scientist at Yahoo.”

Mr. Wright (yes, I have finally found Mr. Wright) implies this a bad thing, a step backwards, or even an academic “selling out.” (Note: Watts is now at Microsoft where he’s a principal researcher)

Since Wright offered his comment, I’ve been thinking about it. Where should science live? Is it a sell out when science happens in private companies? Should it be the sole domain of universities? I’m not so sure.

Watts is a sociologist. His area of study is network structures and system behaviors in complex environments. His past studies tend to involve analyzing large data sets to identify patterns of behavior. There are few companies who could provide larger or more representative data sets than Microsoft.

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Peter Norvig, Director of Research at Google

One such company is Google. And there are many renowned scientists working there. One of them is Peter Norvig, Google’s Director of Research. In a blog post a few years ago where he took issue with Chris Anderson’s Wired article signaling the “End of Theory”, Norvig said:

“(Chris Anderson) correctly noted that the methodology for science is evolving; he cites examples like shotgun sequencing of DNA. Having more data, and more ways to process it, means that we can develop different kinds of theories and models. But that does not mean we throw out the scientific method. It is not “The End of Theory.” It is an important change (or addition) in the methodology and set of tools that are used by science, and perhaps a change in our stereotype of scientific discovery.”

Science as we have known it has always been reductionist in nature. It requires simplification down to a controllable set of variables. It has also relied on a rigorous framework that was most at home in the world of academia. But as Norvig notes, that isn’t necessarily the only viable option now. We live in a world of complexity and the locked down, reductionist approach to science where a certain amount of simplification is required doesn’t really do this world justice. This is particularly true in areas like sociology, which attempts to understand cultural complexity in context. You can’t really do that in a lab.

But perhaps you can do it at Google. Or Microsoft. Or Facebook. These places have reams of data and all the computing power in the world to crunch it. These places precisely meet Norvig’s definition of the evolving methodology of science: “More data, and more ways to process it.”

If that’s the trade-off Duncan Watts decided to make, one can certainly understand it. Scientists follow the path of greatest promise. And when it comes to science that depends on data and processing power, increasing that is best found in places like Microsoft and Google.

 

 

 

 

 

Decoupling Our Hunch Making Mechanism

Humans are hunch-making machines. We’re gloriously good at it. In fact, no one and no thing is better at coming up with a hunch. It’s what sets up apart on our planet and, thus far, nothing we’ve invented has proven to be better suited to strike the spark of intuition.

We can seemingly draw speculative guesses out of thin air – literally. From all the noise that surrounds us, we recognize potential patterns and infer significance. Scientists call them hypotheses. Artists call them artistic inspirations. Entrepreneurs call them innovations.

Whatever the label, we’re not exactly sure what happens. Mihaly Czikszentmihaly (which, in case you’re wondering, is pronounced Me-high Cheek-sent-me-high) explored where these hunches come from in his fascinating book, Creativity, The Psychology of Discovery and Invention. But despite the collective curiosity about the source of human creativity – the jury remains out. The mechanism that turns these very human gears and sparks the required connections between our synapses remains a mystery.

We’re good at making hunches. But we suck at qualifying those hunches. The reason is that we rush a hunch straight into becoming a belief. And that’s where things go off the rails. A hunch is a guess about what might be true. A belief is what we deem to be true. We go straight from what is one of many possible scenarios to the only scenario we execute against. The entire scientific method was created to counteract this very human tendency – forcing rational analysis of the hunches we churn out.

Philip Tetlock’s work on expertise in prediction shows how fragile this tendency to go from hunch to belief can make us. After all, a prediction is nothing more than a hunch of what might be. He referred to Isaiah Berlin’s 1950 essay, “The Hedgehog and the Fox.” In the essay, Berlin quotes the ancient Greek poet Archilochus, “”a fox knows many things, but a hedgehog one important thing.” Taking some poetic license, you could said that a hedgehog is more prone to moving straight from hunch to belief, where a fox tends to evaluate her hunches against multiple sources. Tetlock found that when it came to the accuracy of predictions, it was better to be a fox than a hedgehog. In some cases, much better.

But Tetlock also found that when it comes down to “crunching hunches”, machines tend to bet man hands down. It’s because humans have been programmed for thousands of generations to trust our hunches and no matter how much we fight it, we are born to treat our hunches as fact. Machines bear no such baggage.

This is an example of Moravec’s Paradox – the things that seem simple for humans are amazingly complex for machines. And vice versa. As artificial intelligence pioneer Marvin Minsky once recognized, it’s the things we do unconsciously that represent the biggest challenges for artificial intelligence, “In general, we’re least aware of what our minds do best.” Machines may never be as good as humans at creating a hunch – or, at least – we’re certainly not there yet. But machines have already outstripped humans in the ability to empirically analyze and validate multiple options.

Fellow Online Spin columnist Kaila Colbin posited this in her last column, “When Watson Comes for Your Job, Give it to Him.” As she points out, IBM’s Watson can kick any human ass when it comes to reviewing case law – or plowing through the details required for an accurate medical diagnosis – or assisting students prepare for an upcoming exam. But Watson isn’t very good at coming up with hunches. It’s because hunches aren’t rational. They’re inspirational. And machines aren’t fluent in inspiration. Not yet, anyway.

Maybe that’s why – even in something as logical as chess – the current champion isn’t a machine, or a human. It’s a combination of both. As American economist and author (Average is Over) Tyler explained in a blog post, a “striking percentage of the best or most accurate chess games of all time have been played by man-machine pairs.” Cowen shows four ways a man-machine team can outperform and they all have to do with leveraging the respective strengths of each. Humans use intuition to create hunches, and then harness the power of the machine to analyze relevant options.

Hunches have served humans very well. They will continue to do so. The trick is to decouple those hunches from the belief making mechanism that has historically accompanied it. That’s where we should let machines take over.

 

 

The Wave Form of Complex Strategy

I’ve been thinking about waves a lot lately. As I said to a recent group of marketing technologists, nature doesn’t plan in straight lines. Nature plays out in waves. As soon as you start looking for oscillations, you seem them everywhere. Seasons, our brains, the economy – if complexity lurks there, chances are there is a corresponding wave.

So how do waves tie into my recent two columns (Part One and Part Two) about agency relationships? Simply this – like most complex things, our corporate strategy should also plot itself against a wave-like cycle. And in that cycle, there is a place for both external partnerships and internal execution.

Let me give you two examples of the ubiquity of waves.

Remember how I talked about Bayesian Strategy? Again, it’s a wave, or, if you’d prefer, a loop (which is simply a wave plotted in a different form). It is a process of setting a frame, opening that frame to external validation and then updating that frame based on our newly perceived reality. This approach to strategy borrows from the work done on how we make sense of the world, which is also a loop, or a wave.

Alex “Sandy” Pentland’s “Science of Great Teams” also embodies its own wave:

“Successful teams, especially successful creative teams, oscillate between exploration for discovery and engagement for integration of the ideas gathered from outside sources. At the MIT Media Lab, this pattern accounted for almost half of the differences in creative output of research groups.”

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Alex “Sandy” Pentland

The thing about waves is that they require very different approaches at the peaks and valleys of the wave. The oscillation is caused by this dynamic tension. The act of gathering input is very different than the act of synthesizing and acting on that output. And it’s very difficult to do both at the same time. Again, Pentland found this in his observation of effective teams, “Exploration and engagement, while both good, don’t easily coexist, because they require that the energy of team members be put to two different uses.”

Increasingly, in complex situations, we have to incorporate wave planning into our strategic approach. And when it comes to marketing, this will likely include a wave that winds itself through working with an external partner to gather the value that comes from their external perspective and in creating an internal “sense-making” discipline with an embedded marketing team. This will require a clear understanding of control and authority transference at the appropriate times. Like the Exploration/Engagement cycle of Pentland’s teams, both are necessary but they shouldn’t necessarily run in parallel.

I’ve found in the past that most of the value that can come from a strong external partnership gets burned off in turf wars and discounting outside information and advice because it doesn’t come from “inside”. Even when this information is accepted, it’s subsumed into internal dialogues and documentation, losing whatever insight it once offered.

Similarly, the partner loses precious cycles trying to keep up to speed with the internal directional course changes that inevitably happen. The problem comes when both these processes try to co-exist and run along the same straight line. The result is a rapidly zig-zagging line that tries to stay the course but loses any energy it might have had in constantly readjusting itself to meet “straight line” strategic objectives.

I believe the right answer to the in-house/agency debate is not an “Either/Or” but rather a wave-aware “And.”

The Case for Strong External Marketing Partnerships

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Sherry Turkle

We like to spend time with others that agree with what we have to say. In her book, Reclaiming Conversation, Sherry Turkle says this leads to us living in a bubble – in this case – a bubble of agreement. While soothing to our own sensibilities, this can be a dangerous path to walk down. It leads to dangerous biases in perception like Group Think and Information Cascades. It doesn’t give us a true picture of what the world is really like.

Last week, I said that a shorter “sense-making” cycle is one reason why moving advertising and marketing in-house might be a better way to go. But what if those sense-making cycles lead to a skewed view of the world because of perceptual distortion? What if it leads to us seeing the world not as it is, but as we wish it was? Today, as promised, I want to look at the other side of the question – the advantages that can come from having strong external partnerships.

As I said last week, Bayesian Strategy relies on three principles:

  • Strategic planning is a continuous and iterative process
  • Strategic plans are nothing more than hypotheses that are then subject to validation through empirical data
  • The span of the loop between the setting of the strategic frame and the data that validates it should be kept as short as possible.

While moving more functions – including marketing – in-house helps with the last of these, it can lead to problems with the second step: Empirical Validation.

Prolonged ideological homogeneity is never a good thing. Yet human nature craves it. So, from Socrates on down, we have created rational frameworks that force us to consider divergent thoughts. Democracy is built on such a framework. But over time, most organizations naturally move towards a shared opinion of the world – and that opinion usually starts at the top. It’s what Avinash Kaushik calls the HIPPO Syndrome – The Highest Paid Person’s Opinion.

Agreement bubbles expand due to confirmation bias. Even if we pay lip service to validating our opinions with empirical data, what we count as data depends on what we believe. We look for evidence that confirms our beliefs. We can deny we do it, we can chastise ourselves for doing it, but the fact is, it’s human nature. In the end, we’ll still do it, because we’re programmed to do so.

One way to reliably poke our “agreement bubbles” is to build robust mechanisms to both encounter and embrace ideas from outside the bubble. Remember a few months ago, when I wrote that cultures in which higher percentages of atheists are found also tend to be more innovative? The same factors are at work here. Those cultures have more ideological divergence. More perspectives are considered. The result is almost always a more accurate view of the world. Everyone wants to believe they are “right”, but what is “right” – or as close as is possible – is a synthesis of many different opinions and beliefs.

In this case – especially with something as vital to strategy as marketing – a strong external partnership can force us to consider our agreement bubbles. This is where an agency can bring new views to the table. But the agency and the client have to realize that this is where the value of these partnerships lies. They have to embrace this role and build the trust required to introduce external perspectives into the strategic sense-making cycle.

With two sides of the argument now sketched out, we’ll look next week at how the agency partnership of the future might look.

The Case for Bringing Marketing Inhouse

“We were just writing a lot of checks to agencies, but digital marketing is now in our brand DNA.”
Blake Cahill – Philips Global Head of Digital

When we talk about disruptions in marketing, one of the elephants in the room is the increasing demand to bring marketing in house. Companies like Phillips are bringing more and more marketing functions in-house. As an ex-agency guy, this will sound either blasphemous or disingenuous, but I suspect that it might be the right way to go. I’ll tell you why. It has a lot to do with the evolution of strategy.

In the past, we did two things when we planned strategy. We planned in relatively straight lines and we planned over long time frames – a minimum of 5 years was not unusual.

Here’s how it would play out. Executives would go through their strategic planning exercise, which may or may not include getting input from the internal and external marketers. Strategic plans would be formed and this would then be broken down into departmental directives. Department heads – including marketing – would then execute against the plan, with periodic progress reviews scheduled. The entire loop, from input to executional plans, could easily span several months or even a year or more.

The extended timeline is just one of the issues with this approach to strategy. The other problem is that this assumes that strategic planning is only something executives can do. The strategic frame is only set at the highest levels of the organization. And it’s the executive’s prerogative to either consider or completely ignore any input from their direct reports. Even if they do consider it, this feedback is likely several steps removed from the source – namely – the market.

I’ve written before about the concept of Bayesian Strategy. There are three basic foundations to this approach:

  • Strategic planning is a continuous and iterative process
  • Strategic plans are nothing more than hypotheses that are then subject to validation through empirical data
  • The span of the loop between the setting of the strategic frame and the data that validates it should be kept as short as possible.

With Bayesian strategy, the corporation needs to maintain a number of acutely aware “sensing” interfaces that provide constant data about the corporation’s current “reality”:

  • The internal “reality” – especially in more qualitative areas that might fall outside typical KPI’s – like moral, satisfaction, communication effectiveness, etc.
  • The external “reality” – What’s happening in the market? What are customer’s perceptions? What is the competition doing?

These “sensing” interfaces create the frame for the organization. As such, they’re integral to the setting and updating of strategy. Just as our brain depends on our senses to define our sense of what’s real, the organization depends on these interfaces. And when it comes to the “external” reality, no department is in a better position to make sense of the world than marketing. The span of distance between marketing and the management of the company should be as short as possible. This is very difficult to achieve when you rely on external partners for that marketing.

When a company like Phillips brings marketing in-house, it’s more than just a cost-saving or consolidation effort. It’s bringing the function of marketing as close as possible to the core brand. It’s not only giving it a seat at the strategic table but making it one of the key contributors to that strategy. Like I said, it’s a move that makes a lot of sense.

But there is another side to this story, and that has to do with perspective. I’ll look at the flip side of this argument next Tuesday.

 

Welcome to the World of Wicked Problems

The World is becoming a wicked place. And not in the way you think (although that may be the case as well).

I’m referring to the explosion of wicked problems. Wicked problems are thorny, complex, dynamic problems that defy black and white solutions. These are questions that can’t be answered by yes or no – the answer always seems to be maybe. There is no linear path to solve them. You just keep going in loops, hopefully getting closer to answer but never quite arriving at one. Usually, the optimal solution to a wicked problem is “good enough – for now.”

I believe the ability to deal with wicked problems will be the single biggest factor in separating winners from losers in the future. Dealing with wicked problems requires a different tool set than the one we’ve always used in the past. It requires open, nimble minds. It requires the ability to break complexity into components that can yield individual insights, then synthesizing those insights together into a workable process. Most importantly, however, it requires a willingness to start all over again when that process is finally put in place. And you have to do that with a totally open mind; jettisoning any baggage you might be carrying from the past iteration. In short, it requires an approach I’ve referred to in the past as Bayesian Strategy.

A world full of wicked problems also requires a new kind of leadership. In the past, we wanted leaders who had all the answers. But in a world of wicked problems, there are no answers. In this world, we need leaders who understand the value of adaptability and iteration. Open minds are critical. Beliefs take a back seat to curiosity and imagination.

I’ve had a recent history of taking beliefs to task. Beliefs are cognitive short cuts we use to avoid thinking. In a fairly stable and predictable world, beliefs served a purpose. They are the intellectual equivalent of habits. If the same actions (or thoughts) always yield the same results, why bother with rational analysis? It’s a waste of energy. If we can predict what the end looks like, stopping to rationalize looks an awful lot like wavering or being indecisive.

But predictability is becoming increasingly rare. With wicked problems, we need to be willing to tear apart our view of the world and test it for validity. We need to unpack our beliefs and be willing to sacrifice them if empirical evidence shows them to be false. We need to introduce scientific rigor into our thought process.

This comes down to the difference between complexity and complication. Sending a man to the moon and sequencing the human genome were both complicated problems. Currently, climate change would fall into the same bucket. In each case, there was a lot to be done, but we knew what we had to do. We just needed to marshall the resources to do it. We could predict what the end would look like. This was a world where we needed unwavering leadership and a belief in a commonly understood end-state. To be successful, we just had to get sh*t done.

Creating a sustainable future for advertising and publishing are both complex problems. This makes them wicked. And they’re not alone. Wicked problems are emerging everywhere: educational reform, transportation infrastructures, global economic dynamics, national security, even the future of democracy. In each area, technology and its gravitational pull on society are dealing a handful of wild cards into the deck. We have no idea what success might look like. We are trying to find answers in a whirling, emergent environment, where rules are constantly in flux.

Here, we have to take a different approach. It’s not a straight line. It’s an endless loop.

A New Definition of Order

The first time you see the University of Texas – Austin’s AIM traffic management simulator in action, you can’t believe it would work. It shows the intersection of two 12 lane, heavily trafficked roads. There are no traffic lights, no stop signs, none of the traffic control systems we’re familiar with. Yet, traffic zips through with an efficiency that’s astounding. It appears to be total chaos, but no cars have to wait more than a few seconds to get through the intersection and there’s nary a collision in site. Not even a minor fender bender.

Oh, one more thing. The model depends on there being no humans to screw things up. All the vehicles are driverless. In fact, if just one of the vehicles had a human behind the wheel, the whole system would slow dramatically. The probability of an accident would also soar.

The thing about the simulation is that there is no order – or, at least – there is no order that is apparent to the human eye. The programmers at the U of T seem to recognize this with a tongue in cheek nod to our need for rationality. This particular video clip is called “insanity.” There are other simulation videos available at the project’s website, including ones where humans drive cars at intersections controlled by stoplights. These seem much saner and controlled. They’re also much less efficient. And likely more dangerous. No simulation that includes a human factor comes even close to matching the efficiency of the 100% autonomous option.

The AIM simulation is complex, but it isn’t complicated. It’s actually quite simple. As cars approach the intersection, they signal to a central “manager” if they want to turn or go straight ahead. The manager predicts whether the vehicles path will intersect another vehicle’s predicted path. If it does, it delays the vehicle slightly until the path is clear. That’s it.

The complexity comes in trying to coordinate hundreds of these paths at any given moment. The advantage the automated solution has is that it is in communication with all the vehicles. What appears chaotic to us is actually highly connected and coordinated. It’s fluid and organic. It has a lot in common with things like beehives, ant colonies and even the rhythms of our own bodies. It may not be orderly in our rational sense, but it is natural.

Humans don’t deal very well with complexity. We can’t keep track of more than a dozen or so variables at any one time. We categorize and “chunk” data into easily managed sets that don’t overwhelm our working memory. We always try to simplify things down by imposing order. We use heuristics when things get too complex. We make gut calls and guesses. Most of the time, it works pretty well, but this system gets bogged down quickly. If we pulled the family SUV into the intersection shown in the AIM simulation, we’d probably jam on the brakes and have a minor mental meltdown as driverless cars zipped by us.

Artificial intelligence, on the other hand, loves complexity. It can juggle amounts of disparate data that humans could never dream of managing. This is not to say that computers are more powerful than humans. It’s just that they’re better at different things. It’s referred to as Moravec’s Paradox: It’s relatively easy to program a computer to do what a human finds hard, but it’s really difficult to get it to do what humans find easy. Tracking the trajectories and coordinating the flow of hundreds of autonomous cars would fall into the first category. Understanding emotions would fall into the second category.

This matters because, increasingly, technology is creating a world that is more dynamic, fluid and organic. Order, from our human perspective, will yield to efficiency. And the fact is that – in data rich environments – machines will be much better at this than humans.   Just like our perspectives on driving, our notions of order and efficiency will have to change.

 

Why Disruptive Change is Disruptive

There were a lot of responses to my last column, looking at why agencies and clients have hit the point of irreconcilable differences. Many of those responses were in agreement. In fact, none were in outright disagreement. This surprised me. A lot of Online Spin readers are people who work for very big agencies. I can only conclude that you elected to show your dissention through your silence.

But there were many that fell in the “Yeah-but” category:

Tiffany Lyman Otten wrote,

“This, like anything, is a sign simply that agencies must evolve – again.

Jill Montaigne adds,

“Yet, our own ongoing advertiser conversations confirm that rather than walking away from their traditional agency relationships, clients desperately need and want their agencies to evolve.”

David Vawter chimes in,

“As long as there is something to sell, people will be needed to create and produce the ideas that sell it.”

Agreed. But…

All of the above comments pointed to a new trend in the marketing ecosystem – that of a network of specialists, often in the form of micro-agencies, that appear to be finding niches to hang on to in the tidal wave of change that is sweeping over our industry.

I used to head one of these agencies. Our area of specialty was in user behavior with search interfaces. We did well in this niche. So well, in fact, that we were eventually acquired by a bigger agency. Bigger agencies are always vertically integrated. As such, they offer clients the one-stop shop model. They move to that model because that is the model they know. It is the model they are programmed to create. It is an organizational form that is dictated by their P&L targets. There is no operational wiggle-room here. They simply can’t become anything else.

Tiffany, Jill and several others all used the word evolve, like it is a magical formula for survival. But evolution is like a tree. Once your branch has been determined, you have to evolve outward from that branch. You can’t suddenly leap to another branch. If you’re a chimpanzee, you can’t suddenly decide one day to evolve into a budgie. You can evolve into a new type of chimpanzee, but you’re still a chimpanzee.

What does happen in evolution, however, is that the environment changes so drastically that the tree is dramatically pruned. Some branches are lopped off, so that new branches can sprout. This is called punctuated equilibrium, and, as I’ve said before, this is what I believe we’re going through right now in marketing. Yes, as David rightly notes, “As long as there is something to sell, people will be needed to create and produce the ideas that sell it.” It’s just that the form that takes may be dramatically different that what we currently know. It could be – correction – will be a marketing ecosystem that will be dominated by new species of marketers.

We tend to equate evolution with change – but evolution is a very specific kind of change. It’s change in response to environmental pressures. And while individual species can evolve, so can entire ecosystems. In that bigger picture, some species will emerge and thrive and others will disappear. What is happening to agencies now is just a ripple effect from a much bigger environmental change – analogous to a planet size asteroid slamming into the business and marketing ecosystem that evolved over the past two centuries.

Big agencies are the result of corporate evolution in the previous ecosystem. We are quick to take them to task for being slow, or dumb, or oblivious to client needs. And perhaps, in the new ecosystem, those things are true. But those are the characteristics of the species. No agency intends to be dumb or unresponsive. It’s just an evolutionary mismatch caused by massive disruption in the environment.

These things happen. It’s actually a good thing. Joseph Schumpeter called it Creative Destruction. But, as the name implies, it’s a zero sum game. For something to be created, something has to be destroyed.

Why Agencies and Clients are Calling It Quits

“Love on the Rocks – ain’t no surprise.”

Neil Diamond

In yesterday’s Online Spin, Maarten Albarda signaled the imminent break up of agencies and clients. Communication is close to zero. Fingers are being pointed. The whisper campaign has turned into outright hostility.

When relationships end, it can be because one of the parties is just not trying. But that isn’t the case here. I believe agencies are truly trying to patch things up. They are trying to understand their one-time life partner. They are desperately gobbling up niche shops and investing in technology in order to respark the flame. And the same is true, I believe, on the client side. They want to feel loved again by their agency of record.

I think what’s happening here is more akin to a break up that happens because circumstances have changed and the respective parties haven’t been able to keep up. This is more like high school sweethearts looking at each other 20 years hence and realizing that what once bonded them is long gone. And, if that’s true, it might be helpful to look back and see what happened.

The problem here is that the agency is a child of a marketplace that is rapidly disappearing. It is the result of the creation of the “Visible Hand” market. In his book of the same name, Alfred Chandler went to great lengths (over 600 pages) to chronicle the rise of the modern organization. The modern concept of an advertising agency was a by-product of that. Vertically integrated organizations came about to overcome some inherent inefficiencies in the market – notably the problem of geography and the lack of a functional marketplace network that came with rapid expansions in production and transportation capabilities. Essentially, markets grew too rapidly for Adam Smith’s “Invisible Hand” to be able to effectively balance through market dynamics. Organizations grew to mammoth size in order to provide internal efficiencies that allowed for greater profitability. You had to be big to be competitive. Agents of all types filled the gaps that were inevitable in a rapidly expanding market place. Essentially an agent bridged the gap between two or more separate nodes in a market network. They were the business equivalent of Mark Granovetter’s “weak tie.”

Through the 20th century advertising agents evolved into creative houses – which is where they hit their golden period. But why was this creativity needed? Essentially, agencies evolved when advances in production and distribution technologies weren’t enough to expand markets anymore. Suddenly, companies needed agencies to create demand in existing and identified markets through the sparking desire. This was the final hurray of the “visible hand” marketplace.

But the explosion of networking technologies and the reduction of transactional friction is turning the “visible hand” market back into the “invisible hand” market of Adam Smith – driven by the natural laws of marketplaces. The networks of the marketplace are becoming more connected than ever.

This is a highly dynamic, cyclical market. Straight line strategic planning doesn’t work here. And straight line strategic planning is a fundamental requirement of an agency relationship. That level of stasis is needed to overcome the inherent gaps in a third party relationship. Even under the best of circumstances, an arm’s length relationship can’t effectively “make sense” of the market environment and react quickly enough to maneuver in this marketplace. And, as Albarda points out, the client-agency relationship is far from healthy.

The ironic part is all of this is that what was once an agency’s strength – its position as a bridge between existing networks, has turned into its greatest vulnerability. Technology has essential removed the gaps in the market itself, allowing clients to become more effectively linked to natural networks of customers through emerging channels that are also increasingly mediated by technology. Middlemen are no longer needed. Those gaps have disappeared. But the gap that has always been there, between the agent and the client, not only still exists, but is widening with the breakdown of the relationship. Agencies are like bridges without a river to span.

If you read the common complaints from both sides in the presentations Albarda references , they all come from the ever-widening schism that has come from a drastic change in the market itself. Simply put, the market has evolved to the point where agency relationships are no longer tenable. We on the agency side keep saying we need to reinvent ourselves, but that’s like saying that a dog has to reinvent itself to become a fish – it’s just not in our DNA.