Sunday, September 29, 2013

tweets

HuffPostEducation (@HuffPostEdu)
9/28/13 8:01 AM
Student expelled after engaging in tug of war with teacherhuff.to/16ONG6u

Deb Mills-Scofield (@dscofield)
9/29/13 6:35 AM
By @Digitaltonto A New Age Of Disruption - Old notions of change management no longer work because it is not ass... ow.ly/2Ai2Xc

However, it can happen to anyone.  As Moisés Naím put it in The End of Power, “Power is easier to get, but harder to use or keep.”  The truth is that now everybody gets disrupted sooner

For most of corporate history, scale provided benefits that went beyond just consolidation of fixed costs and negotiating power, but also included informational advantages.  Now, however, the scale economy has been replaced by a semantic economy, where information flows freely across once impermeable boundaries of firm and industry

UC Berkeley’s AnnaLee Saxenian argues that the semantic economy is not only a technological phenomenon, but a personal one as well.  Her research suggests that the “brain drain” from developing countries has been replaced by a “brain circulation” in which the worlds best minds often straddle cultures.

The bottom line is that old notions of boundaries of scale, industry and geography have become impotent.  These boundaries have been replaced by often informal connections that transcend formal structures.

The result is big data and it is incredibly disruptive.  A small startup or even an individual can rent supercomputing capacity from AmazonMicrosoft or Rackspace and put it to work on data sets from their own business activity, from public sources such asdata.gov or, if needed, purchase them at a reasonable cost.

so what if google.. whoever .. sees this as gift to world in shared economy.. helping prototype app

Large, established businesses can benefit as well.  In the old industrial economy adapting to changes in the marketplace meant cumbersome retooling.  Yet MIT’s Erik Brynjolfsson and Andrew McAfee argue that a data driven approach can allow firms to achieve scale without mass by implementing changes instantly across the enterprise.

imagine MIT as one of the nodes for this.. more than they already are.. exponentially more...


It’s not just the amount of data that is changing, but the nature of data as well. Information used to be something separate from the real world.  We would collect it using controlled studies with small samples and then scale it up to reflect what was going on in our organizations and in the marketplace.
The point of data collection in the industrial economy was to make sure we “got it right” before we invested in action.  We’d get the smartest guys, put them in a room and they would make decisions that would determine the strategy of the enterprise.

and got it right - referred to an assumed normative system.. ie : the masses of people who have been or ate going through public Ed.
note.. most never get out of it until...
#1 regret of dying.. no?

For example, UPS has installed sensors on its fleet of trucks so that they can perform maintenance as needed instead of at regular intervals.  They also use the data to improve scheduling and reduce idling


we pay for and inestimable in and believe in this for ie: ups.. but not for the human spirit.. humanity

that they can perform maintenance as needed instead of at regular intervals.  They also use the data to improve scheduling and reduce idli


ie.. just in time v just in case v according to our clock... no?


The upshot is that organizations are changing the way they learn.  Rather than trying to come up with the right idea and then testing it in the marketplace, we can now run market simulations at much lower cost with much lower risk.  Rather than having to get it right, we can iterate quickly and simply strive to be less wrong over time.



wonder if Clay (& others) .. get frustrated a bit.. that they were saying this ten yrs ago..

perhaps we play catch up,..
what if we have the true .or closest .. next iteration of your disruption mentality.. all at once.
zoom waaaaay in.
what really is happening at that point of inflection.. that most don't get past...

maybe this..
a people experiment