Play and Innovation

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All too often, I find that, in the scramble to keep up with our changing world and business environment, we let the stress of needing to innovate get in the way of the play that drives innovation. When I host a brainstorm, I make sure to structure it as a game or a set of games that we’ll play in order to arrive at a broad range of new ideas. From these ideas, we can then hone in on the one or few to move forward with. The book “Gamestorming” is a great resource for learning how to structure these brainstorm games. I find time and again that incorporating play into the business environment leads to innovation.

In this video, Steven Johnson, author of a wonderful book, “Where Good Ideas Come From”, debunks the idea that necessity is the mother of invention by explaining the history of how the computer came to be.

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CMO Mondays: Snapchat files for IPO

snapchat-logo

Last week, Snapchat’s parent company, Snap Inc., filed paperwork for an IPO, with an expected valuation of $25 billion or more. In 2014, Snapchat introduced advertising into the platform. In 2015, it generated $60 million in revenue from that advertising, and, in 2016, it expects to exceed its target of $350 million in revenue. Snapchat is targeting $1 billion in revenue in 2017.

Snapchat reports 150 million users daily and 235 million users monthly, including 41% of 18- to 34-year-olds in the U.S., according to Nielsen. Snapchat shows strong signs of being a healthy business. With continued user and revenue growth, Snapchat will be a hot company for several years to come – even with the new scrutiny of the public markets.

snapchat-monthly-active-users

But, long-term, Snapchat could face a similar issue as Twitter: being a company that offers only a niche audience advertisers. Unlike Google and Facebook that offer a large and broad range of audiences to advertisers, Snapchat caters mainly to younger Millennials and Generation Z audiences. Facebook touts ~1.71 billion monthly users – approximately 25% of the world’s population. By comparison, Twitter has ~313 million monthly users. Twitter has struggled in recent years to win over investors – primarily because it is compared to Facebook. Twitter has only ~18% of the monthly users that Facebook has. And, Twitter has been criticized for its slowing user and revenue growth while being unprofitable. Twitter’s stock price has dropped from $69 per share at its peak in January 2014 to $18.79 today.

trouble-at-twitter

 

While we can expect that Snapchat will continue to grow its user base at a nice rate for the foreseeable future, as it captures more of share the 34-year-old and under audience, the real test will come when Snapchat can no longer rely on that audience for user growth. It will need to stay relevant to the new young audiences entering their teens and twenties, while expanding its relevancy to older audiences. And, it will need to do this while achieving profitability. Otherwise, in a few years, we could be seeing Snapchat face similar issues that Twitter has faced in recent years.

Regulatory Tension of the Sharing Economy

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Airbnb is in talks to settle a suit in which they sued New York City and New York state after Governor Cuomo signed a law that would impose fines on Airbnb hosts that break local housing regulations. According to a Bloomberg article, people that advertise vacant apartments in a multi-unit building for 30 days or less could be fined as much as $7,500 (for repeat offenders). People are still allowed to rent out a room in their house or apartment as long as they are also staying there.

The settlement of Airbnb’s suit concerns whether or not the company will be liable for fines incurred when users of its platform break local regulations. Airbnb claims that the new law seems to target its company and violates Section 230 of the Communications Decency Act, which protects Internet intermediaries (such as Airbnb) from being held liable for content published by its users on its platform.

My city of Austin, TX has seen similar regulatory tension this year. In February, the City Council imposed regulations to restrict short term rentals that are not owner-occupied, limiting Airbnb and Austin’s own darling, HomeAway, from operating in the city. In May, Uber and Lyft lost Proposition 1, which aimed to let the two TNCs (transportation network companies) self-regulate background checks for their drivers. In a fairly tight election, Austin citizens voted 56% against Prop 1 and 44% for it – leaving it to the city to run the background checks on drivers. Uber and Lyft left Austin’s city limits instead of complying with the new law.

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What we’re seeing is a natural tension between fast innovation in the private sector and slow evolution in the public sector. Regulators at city, state and federal levels are grappling with how to manage the changes brought forth from companies in the sharing economy. These companies are eliminating wasted capacity at a rapid rate, and that can have some positive and negative side effects. A frequent complaint around Airbnb and HomeAway is from neighbors of the apartments or homes that are being rented out – that the guests at these short-term rentals are disruptive. On the other hand, Austin saw a 12% drop in drunk driving crashes after Uber came into the city, and then saw a 7% spike in drunk driving incidents immediately after Uber and Lyft left the city.

Personally, I believe that the benefit derived from these companies outweighs the negative impacts. But, I do believe these companies need to strike a balance between entering a market and proving customer demand, and proactively engaging regulators to find a reasonable long-term regulatory framework for operating these new business.

Human Morals in Machines

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One of my co-authors, Laura Sawyer, shared the below TED Talk, “Machine intelligence makes human morals more important” by Zeynep Tufekci. Tufekci discusses both the precision of our machine learning algorithms, as well as how the unconscious biases of the programmers developing the algorithms are making their way into the algorithms. She explores these issues by giving us examples of how machine learning could affect the hiring (read: not hiring) of people that might struggle with depression or that are likely to become pregnant, how these algorithms use biases to decide who gets paroled, and how these algorithms decide who sees what content or ads.

Tufekci makes a strong case for the need for transparency and to audit our machine learning algorithms, as once those algorithms begin to learn on their own, they become a black box. We don’t know what they’re learning, how they’re making decisions, and what biases are present in making those decisions.

In our republic, we’ve set up checks and balances for decision-making with the Executive, Legislative and Judicial branches of government. In our companies, we have checks and balances for decision-making with the structure of the executive team, board of directors, and investors. Our society’s decision-making has thrived because of thoughtful and rigorous debate. So, why couldn’t we hold our machines to the same standards?

My favorite quote from Tufekci talk is below. Enjoy the video.

“We cannot outsource our moral responsibilities to machines. Artificial intelligence does not give us a get out of ethics free card.”

CMO Mondays: Have We Become Too Specialized?

A CMO recently asked me what is one of the biggest pitfalls I see brands falling into. The number one issue that I see is that marketers have become too specialized and too siloed, and therefore the full potential value of the brand is not capitalized.

Growth in complexity from technologies, channels and data.

As you can see from the slides above, marketing has experienced a proliferation of new technologies and channels, and this intimidates marketers and executives. In an effort to make marketers’ jobs easier, companies building products for marketers have actually made their jobs harder and more complex. So, now you see this trend of marketers becoming over-specialized and marketing teams more siloed. Someone might only know analytics, or only know social, or PPC and display, or brand and creative. And, they advocate for one discipline over the other because that’s what they know and are comfortable with. It’s the lens through which they view the world. But, great marketing isn’t about technology or channels. It’s about audiences. It’s always been about understanding audiences’ human behavior to create products, communications and experiences that enroll those audiences to buy into the brand. If we know our audience inside and out, then deciding which technologies and channels to apply to engage those audiences becomes much easier.

The exponential growth in data hasn’t helped in this matter. The need for data has reinforced our nature to play it safe and created some false positives. This is symptomatic across business – not just marketing. “Advertising is dead.” “Why invest in creatives when the data will just tell us what content audiences want? Then, we can use tools to automate content creation.” These philosophies are easy to spout in an era when marketers are being pressured to lean budgets. But, when everyone is swimming in the same direction, opportunity presents itself in the opposite.

Great marketers think more like anthropologists and communicate like orators.

The growing need for general marketers.
The best marketers are Renaissance people. They don’t live solely in the art bucket or science bucket, but, rather, they bridge the two. Great marketers think like anthropologists and communicate like orators – painting a view of the world and enrolling us into that view. They study human behavior from a mix of hard data (think analytics), soft data (think observations) and experience (think intuition) to arrive at universal human truths about customers and their wants and needs. From these truths, great marketers create solutions to those needs – whether they be in the form of products, services, business models, experiences or, simply, stories.

Two Thinking Systems
Perhaps my favorite article on this subject is “The Second Road of Thought” by Tony Golsby-Smith. Here, Golsby-Smith discusses how “the western world bought the wrong thinking system from Aristotle.” An excerpt below:

“This ranks as one of the worst investment decisions our civilization has made, and it has led us into using the wrong toolkits for our enterprises ever since. The thinking system we invested in was Aristotle’s ‘analytics’, and we made the choice around the era of the Enlightenment which ushered in what we today call the Scientific Age. That decision has proven so sweeping that it now monopolizes what most people characterize as ‘thinking’. Thinking processes are dominated by the culture of the sciences, and you get no better evidence of this than our universities, the home of thinking, where any subject must position itself as a science to be taken seriously. Traditional approaches to strategy sit fairly and squarely at this table of logic and Science.

What few people realize is that Aristotle conceived of two thinking-systems, not one. We made the big mistake of just buying one, and allowing it to monopolize the whole territory of thought. We should have bought them both, and used them as partners. Instead we have only one thinking tool in our hands and we are using it for all the wrong purposes. Here is how it happened.

Aristotle was the first person to codify thinking into a system. He did this for a reason: he lived in perhaps the most dramatic social experiment of human history, the invention of democracy by the Greek leader Kleisthenes around 450 BC. This political system did what no other had tried to do: it delivered decision making into the hands of human beings. Prior to that, regimes were governed by the king of the gods. That meant that no matter how sophisticated they might have been in terms of Engineering or Mathematics, they were not sophisticated about human reasoning, especially where decision making was concerned. Clearly, Kleisthenes’ political reforms created a great need to codify the processes by which humans think and can arrive at ‘truths.’ If ever there was a do-it-yourself manual, this was it! Ordinary humans were playing god in Aristotle’s Greece.”

Golsby-Smith goes on to describe the two roads of thought:

  1. THE LOGIC (or ‘analytics’) ROAD: This is ‘where things cannot be other than they are’ and is tied to the realm of natural science.
  2. THE RHETORIC (or ‘dialectic’) ROAD: This is ‘where things can be other than they are’ and is tied to the realm of human decision making.

The Logic Road is the process by which we diagnose what already exists, whereas the Rhetoric Road is the process by which we humans design the future. I would argue that while marketing is experiencing a renaissance right now, it is headed squarely in the direction of ‘analytics’ because of the overwhelming technologies, channels and data discussed above. As business and finance has disappointingly placed statistics (which is the mathematical application of diagnosing the past to predict the future) at the center of its theory and practice, so now marketers are following this trend. But, the breakthrough brands that capture our hearts and minds (and wallets) in the future will be those that master the art of rhetoric as equally as they master the science of analytics.

The art of storytelling
David Ogilvy was quoted as saying “It takes a big idea to attract the attention of consumers and get them to buy your product. Unless your advertising contains a big idea, it will pass like a ship in the night. I doubt if more than one campaign in a hundred contains a big idea.” Never has this been more true. Audiences today experience an attention deficit from the devices, channels, messages and alerts that bombard their senses every waking moment. Content is more fleeting than ever, and audiences’ retention is shorter than ever. Yet, great storytelling increases audiences’ sense of trust and empathy and increases their retention. This enables us, as marketers, to direct human behavior. Indeed, neuroeconomist, Paul Zak, taught us that character-driven stories consistently cause the synthesis of cortisol (a hormone that focuses our attention) and oxytocin (a hormone that creates a sense of empathy and connection). In other words, the better crafted and more relevant the stories we marketers tell about the brand, the more our brand will stand out to and connect with audiences. There is, apparently, scientific benefit to the art of storytelling. See the video below for more details on Zak’s research.

So, all marketers should be trained in storytelling. The Coca-Cola Company has invested in having screenwriters train their marketers, and IBM has recently been hiring screenwriters. If you want your brand to stand out, invest in striking creative and crafting remarkable stories. Yes, by all means, leverage new sources of data to glean insights about your audiences that can inform that creative. But, people today – more than ever – need to be inspired. We need brave brands (and brave marketers behind those brands) to take chances and inspire audiences into action.

The science of analytics
Meanwhile, every marketer should be trained in basic market research and data science, so that they know how to run their own analysis, as well as review others’. Not every marketer needs to be a practicing statistician by any means. But, the important thing is to understand what questions to ask when reviewing data, so that we know how to interpret and apply its findings to actions that the brand should take. Critical is knowing what you’re looking for in the first place in order to design an analysis and measurement approach that can glean the knowledge you seek.

The tactics of channels and technologies
If you have a handle on storytelling and analytics, then channels and technologies become fairly simple. From the data, we glean what story might resonate with customers, what channels they engage in, what their behaviors are in each of those channels, what content formats they engage with most, and we have a sense for what we need to measure in order to learn and improve over time. The trick is then to tell the brand’s story consistently and natively in each of those channels. And, we look for technologies that meet the specifications we need in order to tell that story effectively in each of those channels, and to capture the data we need to measure and learn from our activities.

The need for speed
Given the pace of business is only increasing, it doesn’t make sense to have large groups of hyper-specialized individuals trying to figure out how to work with each other, interpret each other and take actions away from each individual’s contributions. When one does not have context (experience) for what another person does, it’s difficult to make create action. Rather, if we want to move at the speed of business, we should have less, more well-rounded people collaborating. Thus, every marketer should gain experience in both the art and science of marketing. Read Scaling Agile @ Spotify by Henrik Kniberg & Anders Ivarsson to see how this approach has worked in agile software development at Spotify.

Welcome to the Post-Capitalist Society

welcome-to-the-post-capitalist-society

“In 2000, President Bill Clinton said in his last State of the Union address: ‘America will lead the world toward shared peace and prosperity and the far frontiers of science and technology.’ His economic team trumpeted ‘the ferment of rapid technological change‘ as one of the U.S. economy’s ‘principal engines’ of growth.”

I read an article in the Wall Street Journal entitled “The Great Unraveling | America’s Dazzling Tech Boom Has a Downside: Not Enough Jobs” by Jon Hilsenrath and Bob Davis. The premise is that the technology industry has not lived up to its promise of job creation – particularly since the year 2000. And, that this disappointment has led to political outsiders like Donald Trump and Bernie Sanders gaining momentum in this presidential race.

The article goes on to list some interesting facts and statistics:

“Google’s Alphabet Inc. and Facebook Inc. had at the end of last year a total of 74,505 employees, about one-third fewer than Microsoft Corp. even though their combined stock-market value is twice as big. Photo-sharing service Instagram had 13 employees when it was acquired for $1 billion by Facebook in 2012…

…The five largest U.S.-based technology companies by stock-market value—Apple, Alphabet, Microsoft, Facebook and Oracle Corp. —are worth a combined $1.8 trillion today. That is 80% more than the five largest tech companies in 2000.

Today’s five giants have 22% fewer workers than their predecessors, or a total of 434,505 as of last year, compared with 556,523 at Cisco Systems Inc., Intel, IBM, Oracle and Microsoft in 2000.”

On the surface, yes, it looks like the technology industry has failed to meet its promise. The younger technology companies founded after the year 2000 are employing less and less people. The jobs of the Industrial Revolution are being replaced by robots and software, and this will only accelerate with the long awaited maturation of artificial intelligence / machine learning. Every business today is (or should be) a technology business in some capacity to take advantage of the operational efficiencies (i.e. cost savings) that technology can provide.

But, a closer look shows that it’s not the technology industry that failed us. It’s our rhetoric and education that failed us. We read the tea leaves wrong about the transformation that technology would bring because we looked at the past to predict the future.

The First Four Revolutions
As I’ve written about before, economist Carlota Perez taught us that every half century, society has a “big bang moment” – a technological breakthrough – that ushers in a new technological revolution.

5 Successive Technological Revolutions of the Last 250 Years

If you consider the five successive technological revolutions we’ve had, starting with the Industrial Revolution in 1771, each created more jobs than the previous. And, this would make sense. With each revolution, we built more and bigger things, and we did it by hand. Physical labor was the currency of capitalism.

6th Technological Revolution Around the Corner

Why the Fifth Revolution Is Different
But, three things changed all that in our current revolution: the Age of Information and Telecommunications, which saw its big bang moment in 1971 with the Intel microprocessor, and which is at its tale end.

  1. Moore’s Law: An observation in 1965 by Intel’s co-founder, Gordon Moore, states that the number of transistors per square inch on integrated circuits had doubled every year since their invention and would continue to for the foreseeable future. This has decreased the size of our computing devices while simultaneously increasing their processing power exponentially for fifty years. And, it is only now beginning to slow.
  2. The Internet: Have you heard of this thing? It’s pretty amazing. Throughout history, innovation has been driven primarily through physical locations. “Hot spots”, as they’re referred to in network science, were typically found where there was a concentration of people and ideas colliding. These hot spots have popped up throughout history from the coffee houses in the Age of Enlightenment to the Parisian salons of Modernism. Some of these hot spots have also been industry specific like Silicon Valley for tech, Los Angeles for film and TV, and New York for finance. The Internet (and the World Wide Web) distributed the hot spot, so that its not restricted to a centralized location. The hot spot became decentralized, and has led to innovations like Safecast, which I mentioned in yesterday’s blog post.
  3. Cloud Computing: Then, cloud computing came in and decentralized computing infrastructure. Suddenly, you didn’t need to buy or lease expensive on-premise servers to build software. You simply rent what you need – and only what you need – when you need it. The price of software development dropped exponentially. Not only do you save on hardware (server) costs, but you save by not needing expensive people that know how to service the hardware.

So, what does this all sum up to? Since the rise of capitalism and throughout the first four technological revolutions, capitalism created more jobs because the primary economic resources were physical assets: gold, land, ships, railroads, skyscrapers, cars, etc. and the labor that was needed to build and manage them. But, while the fifth revolution started this way, it is ending by headed in the opposite direction. The economic force of capitalism, combined with Moore’s Law, the Internet and cloud computing, is driving a reduced need for employees. Today, one can build a highly valuable business with exponentially lower (near $0) infrastructure, supply chain and employee costs. Every non-critical resource simply becomes dead weight.

Capitalism Has Hit Its Tipping Point.
Consider this observation that Tom Goodwin shared in a 2015 TechCrunch article entitled “The Battle for the Customer Interface”:

“Uber, the world’s largest taxi company, owns no vehicles. Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. And Airbnb, the world’s largest accommodation provider, owns no real estate. Something interesting is happening.”

something-interesting-is-happening

The Wall Street Journal article mentioned above highlights that Instagram had only 13 employees when it was acquired by Facebook for $1 billion in 2012, and WhatsApp had only 55 employees when it was acquired by Facebook for $19 billion in 2014.

The winners in the new capitalism are those that can create value with the least resources – including employees.

Why Our Rhetoric and Education Is Wrong
For longer than I can remember, political rhetoric around economic growth has been about job creation and good education to fill those jobs. This made sense given our history. But, what you see today is a frustration that those jobs aren’t being created – at least not in the technology industry. If anything tech is displacing those jobs.

In our new economy, employment looks more like a shorter long tail. As Chris Anderson, author of The Long Tail describes…

“The theory of the Long Tail is that our culture and economy is increasingly shifting away from a focus on a relatively small number of “hits” (mainstream products and markets) at the head of the demand curve and toward a huge number of niches in the tail. As the costs of production and distribution fall, especially online, there is now less need to lump products and consumers into one-size-fits-all containers. In an era without the constraints of physical shelf space and other bottlenecks of distribution, narrowly-targeted goods and services can be as economically attractive as mainstream fare.”

longtail

Anderson wrote his original article about the long tail in 2004, describing the effects of the Internet on commerce. iTunes and Amazon are prime examples in the music and CPG categories respectively. But, twelve years after the original article, we can now see that the same effects are happening to employment.  At the head of the tail are the largest employers – slow, lumbering legacy companies with immense overhead. Further down the head are the new class of technology companies – except that they are employing less people than their predecessors. They look more like a small, passionate and nimble tribe – with a minimal number of full-time employees supplemented by an army of flexible, contract workers (to whom you don’t have to provide expensive benefits). Consider companies like Uber, Lyft, Instacart, Luxe and Favor. Then, you get into the long tail. And, these are less so companies; more so, individuals that have learned to make a living through the digital economy. They’re building mobile apps for iOS and Android, creating subscription e-commerce businesses through Cratejoy, or selling craft goods on Etsy. They may even be content creators on YouTube, Instagram or podcasting. Indeed, the Wall Street Journal article highlights that “An Apple spokeswoman says it is ‘creating jobs in new industries like the App Economy.'”

Peter Drucker predicted such a change. In his book “Landmarks of Tomorrow”, he talked about the shift to the “post-capitalist society” where knowledge would become the primary economic resource over land, labor and financial assets. This gave rise to the concept of “knowledge workers” that is so common in management and consulting today. 

Where We Go from Here

“Give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime.”

So, our rhetoric needs to shift away from “get an expensive education, so you can get a good job and have a nice, long career” to “learn to learn, so that you can create your own income and be self sufficient.” The United States was built on entrepreneurship – on life, liberty and the pursuit of happiness. If we want to prepare our people for the pursuit, don’t give them a skill and hand them a job; teach them the game of business and let them play.

From Futurist to Nowist

Director of MIT Media Lab, Joi Ito gave TED Talk on becoming a “now-ist” instead of being a “futurist”. In this talk, Ito describes how he was in Cambridge at MIT when a magnitude 9 earthquake hit off the coast of Japan. Ito was panicked, as he watched the news and the press that was coming from the Tokyo power company about the explosion at the nuclear power plant that was only 200 kilometers away from his home where his family was at that time.

The people on TV weren’t telling Ito anything that he wanted (needed) to hear regarding the nuclear reactor, levels of radiation, etc. So, he went to the internet for information instead, and there he found people in similar situations. So, they formed a community called Safecast to measure the radiation and get the information out to everyone else because the reality was that the government wasn’t going to do it for the people. Today, Safecast has 16M data points (the largest open database of radiation measurements), data visualization tools, an app that shows radiation in Japan and around the world, and other resources for the open community.

It’s remarkable to see how people can come together so quickly under a shared purpose to build something of immense value like this. One year ago, I was in Nuevo Vallarta with my family – my wife, three kids and parents – when Hurricane Patricia hit the west coast of Mexico, just 180 miles south of where we were staying. For twenty-four hours we monitored the hurricane from our mobile devices, getting access to news from the U.S. because the Mexican government wasn’t providing any information. All we got from U.S. news outlets was fear-mongering about how deadly the hurricane was going to be – not just because of the winds, but more so because of the tsunami-sized waves that the hurricane would bring ashore. Not at all comforting when you’ve been evacuated under ground (sea) level in a bunker. Having factual, open-sourced data like this in that situation would have been invaluable. The closest I could find was the National Hurricane Center, which became my main source for information during that period.

Ito goes on to discuss his perspective on innovation. Three key takeaways are:

  1. “Deploy or Die” motto – Moore’s Law made the cost of trying new things (innovation) virtually zero. So, innovation has moved to the fringes where makers can make and test things first before they need to hire MBAs and raise funds.
  2. “Learning over Education” – A perspective that “education is what they do to you” whereas “learning is what you do to yourself.” This particularly resonates with me, as I’ve practically googled my way into the career that I’m in. I wasn’t a marketer by training. I stumbled into this six years ago when I left the movie business. But, curiosity and the willingness to test and try new things accelerated my success as a marketer.
  3. “Compass over Maps” – You can’t expect to plan things from beginning to end at the beginning. But, if you have a strong compass, you can discover your way to the outcome you seek. This speaks to being resourceful, which is the first thing I look for in a team member after culture fit. 

Below is Ito’s TED Talk. Hope you enjoy.