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.
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.
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.
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Horace unpacks the rumored, denied, and seemingly inevitable arrival of iPhone on China Mobile. Reflecting on smartphone adoption in the US, where does the unconventional logic take us from here?
via 5by5 | The Critical Path #105: Subsidize This.
Fresh off of back-to-back AirShows, Horace discusses the future of his “cinematographic” presentation style and announces Airshow World Tour. We also look at episode #103′s prescient prediction of Amazon’s move into delivering their own products.
via 5by5 | The Critical Path #104: Cinematic Presentations.
In this episode we move beyond just talking about our pet theories of automotive disruption and interview someone who is doing something about it.
Asymcar 8: The EcoV | Asymcar.
If you want to know more about Toyota’s secret sauce, why GM could not make an electric vehicle and how decisions are made in the auto industry then you should listen.
As automobiles become smartphone accessories, they become an interesting industry to study. Here is a recent (since 1961) history of the US market.
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).
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. 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.
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The latest comScore US smartphone survey showing three months’ ending October data has been released and there were no surprises. Smartphone penetration grew to 62.5% representing 149.2 million users. I made a slight adjustment to the predictive logistic function parameters (p1 = 93, p2 = 22.5).
The correlation between predictive and actual logistic function (P/(1-P)) is shown below.