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Check out this SlideShare that steps you through how to enable Real Time Analytics in your organization. It talks about how to avoid problems of contention, set up the right architecture and why an In-Memory Computing solution could help. Find out more by listening to our show on "Enabling Real Time Analytics" featuring guest Scott Zoldi of FICO.


Recently, I attended a Forrester conference where I was asked to present a question to a breakout group to discuss the application of Big Data to state government.  My specific question was: 

When developing our overall data strategy, it often feels like we're pushing a rope up hill. Some clients are still vested in using their spreadsheets, and some clients feel overly protective of their data.  When building a business case, how do we address the cultural differences between departments?  Is it possible to promote maturity using analytics, or is it the other way around, that the organization must mature to some level before analytics are worth the effort?

To expand on this a little bit, it seems that different agencies in state government are at different levels of maturity.  When we propose business analytics, we in IT are trying to come up with the service catalogue item such that any agency can subscribe from our centralized catalog of services.  Often, this is really limited to the agency’s maturity to consume the service.  In some agencies, we find very mature business processes that welcome analytics to provide prescriptive activities to optimize performance.

Collective intelligence enables us to access and organize unprecedented amounts of information and thereby enlarge the universe of possible solutions. Companies have sought to gather information efficiently from all manner of sources to make decisions from almost the beginning of commercial history, but there have always been forces of entropy. The systems for data collection remain in place, but the company is in fact no longer open to fresh ideas, and it becomes a collapsing world of dwindling options and antiquated approaches. The new technologies of collective intelligence, however, represent countervailing forces. Information sharing and collaboration are ceasing to exist as mere options. They are instead competitive necessities. Many companies that have not begun thinking long and hard about cloud and crowd systems and how they can be strategically integrated into extant architectures are doomed. They will not be able to compete with those who have achieved unparalleled reach and efficiency in their information-gathering, access and storage processes. Undreamed of sources for wise counsel will multiply dramatically the availability of solutions.

“There is one mind common to all individual men,” Emerson in “History” 
The term collective intelligence, as Emerson too testifies, has to be defined if there is to be clarity and discipline in the organizations availing themselves of the new technologies.  Hence the point is made:  Collective intelligence has to be understood in terms of these new technologies, even if there is nothing older in human history than the pooling of information. In recent decades, IT has been committed to a couple of kinds of systems.  There has been the transactional system, dedicated to the processing of orders and management capabilities as well as facility in the organization of relations with customers, suppliers, and partners in commerce.  The other system is collective intelligence, which is fundamentally about the expansion of the space in which solutions are possible, a sowing of the future with unforeseeable possibility.  Two associated concepts one hears employed in this regard are those of cloud and crowd.

The notion of collective intelligence is very far from new.  It can be traced back from Hegel to Heraclitus, the latter’s universal reason or logos, and down to William Morton Wheeler, who early in the 20th century observed that ants seem to coordinate their efforts in such a manner as to suggest a collective executive agency.  In an age even more physicalist in its presuppositions than Wheeler’s, it is hardly surprising that the computer has been included as a central actor. The shift in computing is from information technology in the form of transactional systems to an unprecedentedly vast sharing of data, and perhaps a new humility is in order as the realization dawns that no one person, group or institution has a monopoly on good ideas and that, further, as Quine observed, a concept is only what it is within a conceptual matrix.  That is, it is only what it is in its nature as shared.


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