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Why would Mark Zuckerberg drop $1 billion on a company less than two years old with no revenues to speak of and no apparent business model? There has been an avalanche of pundits giving all sorts of reasons why the deal makes perfect sense:  The user base, a foothold in mobile, their technology, development team, etc, yet I haven’t found any of those explanations comelling. Usually, there is some strategic rationale and talk of synergies gained from eliminating costs, but the fact remains that great companies are not built through acquisitions and cost savings usually fail to materialize. However, as I pointed out in an earlier post, tech companies have an unusually good record with acquisitions (for instance, they had very small write-downs during the financial crises) and I think a lot of it has to do with the S curve.
While companies in the regular economy focus on established firms, tech companies tend to buy small firms in emerging areas. There are many S-curves going on at once so large tech companies make dozens of acquisitions every year, most of which are incorporated into existing products. What’s unusual about Facebook’s purchase of Instagram is that Facebook not only made a large investment in a brand they intend to keep separate, but they themselves are only eight years old. I’ve written before about digital laws, the most famous of which is Moore’s law which states that processing efficiency doubles every 18 months.
Although the chart specifically shows the trend for computations per kilowatt hour, it’s a fairly good surrogate for what’s going on in technology overall.
Put another way, if you’re an executive who cut his teeth in the Reagan years, your thinking is a trillion times too slow.


That brings us to Ray Kurzweil’s concept of the singularity, where advancement becomes so fast that it’s almost instantaneous (the concept gets its name from the point of infinite gravity at the center of a black hole). A lot of Kurzweil’s ideas are pretty far out and many of the predictions he made in his 2005 book, The Singularity Is Near, have proved too optimistic. While the trend isn’t 100% chronological, it’s clear that the S-curve is getting increasingly steeper.
However, it is a new kind of logic and certainly not the kind that they’ve traditionally taught in business schools or in statistics courses.
We no longer live in a world of Gaussian statistics, but a broken order of uncertainty and emergence in which inaction is every bit as dangerous as wrong action and traditional decision cycles are no longer viable. Its quite possible both will become reality but like you I am more interested in the rate of change view. The question about AI and multiple intelligences opens up a singularity in discussion itself – a massive, massive topic.
One reason I think that the rate of change and the AI scenarios will connect is that it may only be AI that can deal with the rate of change.
Not to take away from your interesting analysis, but could it simply be that the trend has exploded for consumption of visual content, and in the scheme of Facebook’s coffers, it was a minimal investment for a popular service? We are in the middle of a visual content revolution as information competes for our attention.


The S Curve is a well known project management tool and it consists in "a display of cumulative costs, labour hours or other quantities plotted against time".The name derives from the S-like shape of the curve, flatter at the beginning and end and steeper in the middle, because this is the way most of the projects look like. The S curve can be considered as an indicator and it's used for many applications related to project management such as: target, baseline, cost, time etc.
Engineering change management is a component of project management that can help you minimize cost and increase benefits. To think through your question, What happens when development cycle becomes shorter than decision cycles, I think, we are thinking again through the old mind-set.
For example MS Project does not have this possibility so a third party software application is needed to process the Baseline and Production Schedule data and generate the needed S Curve.( for example S Curve Generator that integrates with MS EXcel to generate S Curves). Decision cycles comes from the military mindset where you are trying to orient your activities based on the movements of your competitors( prospective ones, in the case of an ecosystem).
However, if firms could enhance their awareness, and look at each each decision as a starting node, whose steps would be driven by instantaneous feedback, I think it would make decision process synchronous with the development process, rather than being reactive, trying to catch up with the other.



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