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Innoveracy: Misunderstanding Innovation

Illiteracy is the inability to read and write. Though the percent of sufferers has halved in the last 35 years, currently 15% of the world has this affliction. Innumeracy is the inability to apply simple numerical concepts. The rate of innumeracy is unknown but chances are that it affects over 50% of us. This tragedy impedes our ability to have a discourse on matters related to quantitative judgement while policy decisions increasingly depend on this judgement.

But there is another form of ignorance which seems to be universal: the inability to understand the concept and role of innovation. The way this is exhibited is in the misuse of the term and the inability to discern the difference between novelty, creation, invention and innovation. The result is a failure to understand the causes of success and failure in business and hence the conditions that lead to economic growth.

My contribution to solving this problem is to coin a word: I define innoveracy as the inability to understand creativity and the role it plays in society. Hopefully identifying individual innoveracy will draw attention to the problem enough to help solve it.

One example is in the following quote:

“Lastly, nationally circulating tabloid Ilta-Sanomat gets a look at Nokia’s fabled tablet computer that was developed nine years before the iPad hit the market. According to the paper, Nokia had its own innovative tablet device ready in 2001, but unfortunately it never made it to the shops. A former Nokia expert Esko Yliruusi says that the project was suspended a heartbeat before the tablet hit the market because it was thought that there was insufficient demand for such a device.”[1]

To explain what’s wrong with this usage we need some definitions.

The definition of innovation is easy to find but it’s one thing to read the definition and another to understand its meaning. Rather than defining it again, I propose using a simple taxonomy of related activities that put it in context.

  • Novelty: Something new
  • Creation: Something new and valuable
  • Invention: Something new, having potential value through utility
  • Innovation: Something new and uniquely useful

The taxonomy is illustrated with the following diagram. The position of the circles shows the embedding of meaning[2]

Screen Shot 2014-04-18 at 7.54.26 AM

To illustrate further, here are some examples of the concepts.

  • Novelties: The choice of Gold as a color for the iPhone; the naming of a version of Android as “Kit Kat”; coining a new word.
  • Creations: The fall collection of a fashion designer; a new movie; a blog post.
  • Inventions: Anything described by a patent; The secret formula for Coca Cola.
  • Innovations: The iPhone pricing model; Google’s revenue model; The Ford production system; Wal-Mart’s store design; Amazon’s logistics.

The differences are also evident in the mechanisms that exist to protect the works:

  • Novelties are usually not protectable but since their value is very limited the copying is not seen to cause harm.
  • Creations are protected by copyright or trademark but are not patentable since they lack utility.
  • Inventions can be protected for a limited time through patents but can also be protected indefinitely by being kept secret. Their uniqueness may also be the means by which they can be kept a secret.
  • Innovations can be protected through market competition but are not defensible through legal means.

Note that the taxonomy has a hierarchy. Creations are novel, inventions are creations and innovations are usually based on some invention. However inventions are not innovations and neither are creations or novelties. Innovations are therefore the most demanding works because they require all the conditions in the hierarchy. Innovations implicitly require defensibility through a unique “operating model”. Put another way, they remain unique because few others can copy them.

To be innovative is very difficult, but because of the difficulty, being innovative is usually well rewarded. Indeed, it might be easier to identify innovations simply by their rewards. It’s almost a certainty that any great business is predicated on an innovation and that the lack of a reward in business means that some aspect of the conditions of innovation were not met.

The causal, if-and-only-if connection with reward is what should be the innovation litmus test. If something fails to change the world (and hence is unrewarded) you can be pretty sure it was not innovative enough.

Which brings us to the quote above. The fact that the Nokia tablet of 2001 not only did not succeed in the market but was not even released implies that it could not have been innovative. The product was only at the stage of perhaps being an invention (if it can be shown to be unique) or merely a creation (if it isn’t.) Furthermore, if the product is so poorly designed that it is literally unusable then it is just a novelty. A design, sketch or verbal description might be novel but it does not qualify as an innovation or an invention or even a creation. How far the depiction went toward making a dent in the universe defines its innovativeness.

Why does this matter?

Understanding that innovation requires passing a market test and that passing that test is immensely rewarding both for the creator and for society at large means that we can focus on how to make it happen. Obsessing over the mere novelties or inventions means we allocate resources which markets won’t reward. Misusing the term and confusing it with activities that don’t create value takes our eye off the causes and moves us away from finding ways of repeatably succeeding.

Recognizing that innoveracy is a problem allows us to address it. Addressing it would mean we could speak a language of value creation that everyone understands.

Wouldn’t that be novel?

Notes:
  1. A video showing the device is here, in Finnish. []
  2. The size of the circles also suggests degree of effort required and potential reward. Note that this is not a Venn diagram. []

Postmodern computing

There are 7.1 billion people on Earth. Coincidentally there are also 7 billion mobile connections.  Those connections are held by 3.45 billion unique mobile subscribers.[1] Unsurprisingly, the largest national mobile markets (by number of subscriptions) correspond closely to the most populous nations.

Screen Shot 2014-04-07 at 7.21.46 AM

Considering smartphones, last year 1 billion smartphones were sold and the number of smartphones in use is about 2 billion[2]

Given the rapid adoption of smartphones, it’s also safe to assume that smartphone penetration will follow population distribution. In the US, where comScore data is published monthly, penetration is following a predictable logistic curve.

Screen Shot 2014-04-07 at 7.55.13 AM

 

Assuming similar patterns world-wide we can forecast regional smartphone penetration. Screen Shot 2014-04-07 at 7.56.49 AM

This yields the following forecast for smartphone usage world-wide.

Notes:
  1. GSMA []
  2. There are also about 2 billion 3G/4G connections world-wide []

The price is right

One of the axioms of hardware business is that prices fall over time. The consumer price index for personal computers and peripheral equipment from 1998 to 2014 is shown below:

CUUR0000SEEE01_Max_630_378

The price index suggests that prices for computers should be 54% of 2007 levels. Charles Arthur illustrated this on a global basis using a separate set of data.

The data shows that the weighted average selling price (ASP) of a PC has fallen from $614.60 in the first quarter of 2010 to just $544.30 in the third quarter of 2013, the most recent date for which data is available.

Invulnerable

On a recent podcast I noted that Google was perceived as invulnerable. In contrast, Apple is seen as temporarily enjoying a stay of execution.[1] This is not necessarily a bad thing for Apple. The more gushing the loathing or scorn, the more likely it’s a reaction to love and attraction. A brand dies not from hate but from apathy.

But nor is it necessarily a good thing for Google be be seen as invulnerable. There might be no “Google death knell counter”. There might not be a “Google is doomed” trope. If an executive from Google quits or is fired there is no investor panic. If a product is withdrawn there is no mourning. There are no journalists pursuing Pulitzer prizes by describing some seamy underside of Google. But there are no overt displays of affection either. Google is seen, on balance, as benevolent and hopeful. The discussion on business robustness is simply missing.

I suspect the absence of scrutiny comes from Google being seen as an analogy of the Internet itself. We don’t question the survival of the Internet so we don’t question the survival of Google — its backbone, its index, and its pervasive ads which, somehow, keep the lights on. We believe Google is infrastructure. We don’t dwell on whether electric grids are vulnerable, or supplies of fuel, or the weather(!)

Too complex, too pervasive. These are systems, not things. And people are not designed to contemplate systems. We leave that to experts, or better yet, computers.

The reason Apple is contemplated at all is that it’s not seen as a system. Even the suggestion that Apple is a system is implicitly treated as an impossibility. Because it’s not a system it’s fragile. It’s a person, or an idea, or a product or a singular “key” to something. It is, ultimately, mortal. The only debate is when it will die and points are earned for calling it sooner rather than later.

But what if Apple were a system? And what if Google were a person (or three?)

 

Notes:
  1. The list of Apple Achilles’ Heels is so long and creatively composed that it would take ages to compile, but here are just a few: the Mac (vs. Windows), Digital Rights Management (which kept the iPod alive), dozens of lawsuits (including from The Beatles), the Mac (when it ran Windows), PlaysForSure, Music Labels retaliation, the Zune, Android and clones, the Kindle and Amazon in general, more Mac, iTunes, iPod and iPhone and iPad killers than can be counted; Steve Jobs is ill, Jony Ive will quit, Tony Fadell quit, Rubinstein quit, Forstall was fired, etc. Feel free to add more through comments. See also Apple Death Knell Counter. []

But Apple does not pursue profits either!

In my essay on Google’s absence of profit (or income or business) motives questions were raised on the stated absence of hunger for profits from Apple and what difference there might be from Google’s philosophy.

Indeed, Jony Ive stated:

“Our goal isn’t to make money. Our goal absolutely at Apple is not to make money. It may sound a little flippant, but it’s the truth.”[1].

He was probably repeating what Jobs had previously stated:

“I remember very clearly Steve announcing that our goal is not just to make money but to make great products”[2]

However, note that both quotes are qualified. In the case of Jobs, he said “not just to make money”. Jobs clearly stated that great products lead to money. That great products are causal to money and therefore that if you make great products you make money. One leads to the other.

Ive also continued in this reasoning:

“Our goal, and what gets us excited, is to try to make great products. We trust that if we are successful people will like them. And if we are operationally competent we will make revenue. But we are very clear about our goal.”

I would paraphrase the Apple logic as ”Great products are the means by which we sustain our business. By focusing on the product, the customer is satisfied and through that satisfaction we create the free cash flows which can be used to fund more products.”

There is a difference between Apple’s “indifference to money” and the “indifference to business models” that Google exhibits.

Google steps even further away from cash flows. Its goals are to build great things guided by their vision and patterns in the data they collect. The value is in the data itself rather than in any transaction.

As long as the source of money is unfettered, its provenance is uninteresting. A business model is a profit algorithm. It could be linked to the data but it need not be. Markets are messy and imperfect. Data provides much clearer views into value. You could conclude that value itself cannot be trusted to the judgement of the public. Value is to be determined through the recognition of patterns on data privately collected.

So when I say that Google has disdain for market mechanisms I mean that they believe they can do better. Apple still values the user as the ultimate adjudicator of its actions. Google looks past the user and interprets their intentions.

Google sees markets as ultimately obsolete.

Notes:
  1. at the British Embassy’s Creative Summing in July 2012 []
  2. Walter Isaacson’s Steve Jobs []

Google’s three Ps

A company is nothing more (and nothing less) than three things: people, processes and purposes. In the language of the software engineer these would be inputs, algorithms and specifications. In the language of classical business analysis they are assets (or resources), organization structures and business models. In military theory, these are logistics, tactics and strategy.

This is the trinity which allows for an understanding of a complex system: the physical, the operational and the guiding principle. The what, the how and the why.

When approaching any analysis problem, these questions form the foundation of causal inference. What is it, how does it work and why does it exist?

When analyzing nature the sciences often help with the what and the how but rarely address the why.[1] In contrast, man-made systems (e.g. systems of law, religion and commerce) require an answer to the why as there is a presumption of a will in their creation and preservation. The why allows ultimate judgement on the merit of an enterprise. The why may escape us but it’s assumed to always be there. For instance, in criminal law the motive is often a crucial piece of evidence but it’s not always found. In business, the motive for action or for organization is a crucial piece of the puzzle which often explains the what, who and how, but here the ultimate why is usually profit. This the characteristic of a for-profit business, the purpose is explicit.

Notes:
  1. Religion attempts to answer the whys which science leaves as unanswerable. []

Moonshot

When describing the process of disruptive innovation, Clay Christensen set about to also describe the process by which a technology is developed by visionaries in a commercially unsuccessful way. He called it cramming.

Cramming is a process of trying to make a not-yet-good-enough technology great without allowing it to be bad. In other words, it’s taking an ambitious goal and aiming at it with vast resources of time and money without allowing the mundane trial and error experimentation in business models.

To illustrate cramming I borrowed his story of how the transistor was embraced by incumbents in the US vs. entrants in Japan and how that led to the downfall of the US consumer electronics industry.

Small upstarts were able to take the invention, wrap a new business model around it that motivated the current players to ignore or flee their entry. They thus successfully displaced the entrenched incumbents even though the incumbents were investing heavily in the technology and the entrants weren’t.

In the image below, the blue “path taken by established vacuum tube manufacturers” is the cramming approach vs. the green entry by outsiders who worked on minor new products which could make use of the rough state of transistors at their early stages of development.

Screen Shot 2013-12-17 at 12-17-3.04.59 PM

The history of investment in transistor-based electronics shows how following the money (i.e. R&D) did not lead to value creation, quite the opposite. There are many such examples: The billions spent on R&D by Microsoft did not help them build a mobile future and the billions spent on R&D by Nokia did not help them build a computing future.

There are other white elephant stories such as IBM’s investment in speech recognition to replace word processing, the Japanese government spending on “Fifth Generation Computing” and almost all research into machine translation and learning from the 1960s to the present.

But today we hear about initiatives such as package delivery drones and driverless cars and robots and Hyperloops and are hopeful. Perhaps under the guiding vision of the wisest, most benevolent business wizards, breakthrough technologies and new infrastructures can finally be realized and we can gain the growth and wealth that we deserve but are so sorely lacking.

Bundling and Pricing Innovation

This was initially posted on LinkedIn December 16, 2013.

Innovation comes in many forms. Many times innovation is thought of as technological improvement or as invention. We can all cite examples of inventions which turned into industries which re-defined civilization. The steam engine comes to mind but there were many others before and after. Inventing something is certainly a way to create value but it’s not as common or as reliable a method as it might seem. Creating Intellectual Property is one thing, finding a defensible market and business model is quite another.

More often companies innovate in terms of processes or the “algorithms” which are used to deploy existing resources. Wal*Mart was immensely innovative in the way it organized itself and laid out a low-cost business model. More recently Amazon has innovated in distribution and fulfillment based on the ability to dispense with showrooms for products and sell directly online. There is little in terms of technology which Amazon “invented”. Rather, it deployed off-the-shelf technology in a novel way.

But what I want to address is a more mundane sort of innovation: marketing innovation, specifically pricing. Few would consider a price model to be an innovation but in fact it’s a core lynchpin to many breakthrough innovations. It was pricing which permitted Henry Ford to build an industrial empire. He could have built cars for those who could afford them as cars were defined in 1907 but he chose to build a car around a price point which was around the median of the population. A car “so low in price that no man making a good salary will be unable to own one.” His business logic began with a price and the product and process followed.

How many Americans will be using an iPhone when the US smartphone market saturates?

As previously noted, the US smartphone market has followed an almost perfectly logistic growth. The measured data (via comScore, in green below) follows a predictive logistic function (thin blue whose formula is discussed here).

Screen Shot 2013-12-13 at 12-13-11.30.54 AM

The other notable market observation is how closely the iPhone follows the same pattern as the market. The red line representing the iPhone above is almost perfectly parallel to the green and blue lines which represent the overall market. The reason for this seems to be that consumers are absorbing the product in similar way to how they are absorbing the technology.[1] The “learning model” which underpins logistic models could offer clues as to the cause. It suggests that there is a direct communication that happens between the product and the consumer.

Notes:
  1. Note that this pattern of adoption has happened even though the product has been at least partially unavailable to the entire market until quite recently. []

When will there be one billion iOS devices in use?

iOS unit sales crossed over 700 million units last month. That is a significant milestone but the total number of units in use is likely to be lower. My estimate based on device replacement assumptions is that about 500 million are still in use.

The estimated break-down of units sold and in use by device type is shown below:

Screen Shot 2013-11-25 at 11-25-2.59.59 PM