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Does Predictive Analytics (BI) Field Represent a Potentially Major Disruptive Innovation?

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Does the burgeoning field of Predictive Analytics (PA) and the competitive advantage that it can potentially reap represent a potentially major disruptive technology of the near future?  Or will it go by the wayside (i.e., in terms of being disruptive) in the same manner that Artificial Intelligence (AI) computer technology and applications did in the 1980s and 90s?

Several big name companies like IBM and SAIC are making serious runs at developing PA based software applications as their major business models.  IBM is pulling out all the stops here as it recently bought out Cognos and SSPS for their PA assets and high levels of expertise in order to build up its new PA consulting model for its Global Business Services consulting group.  In addition, engineering firm SAIC has recently announced a major PA application system that is now market ready (i.e., SAIC plans to market this new PA application on a worldwide basis alongside its hardware and consulting services).

To elaborate, SAIC’s new “Distribution Monitoring System” is designed to proactively predict the occurrence of failures in distribution and transmission systems in a matter of days, weeks, or even months before they occur.  The utilization of a “complex-event” processing engine evaluates masses of data (i.e., data mining) against rules laying out the relationship between specific, fairly obvious events in the life of a particular device and the likelihood that such a device will fail (and when it will fail).  Millions of records containing event driven data can be run either daily or in real time against these rules of thumb (or indicators) that have been designed to identify potential failure points and the timing of their occurrence.  This process then utilizes a knowledge database that can correlate  faults and failures (i.e., it learns to proactively detect problems that can cause failures).  A neural network is then utilized which can determine whether a failure will occur at some point and can also assess, with a stated probability, when the failure will occur.

In support of the above premise that PA could become a major disruptive technology in the near future, a recent study by McKinsey Consulting Group infers that corporations are going to have to embrace disruptive technologies that will shape the new economic terrain that is evolving out of the latest global economic downturn.  As economies around the world emerge from the recent economic downturn, many companies are starting to grasp that what follows most likely won’t be just another typical turn of the business cycle.  The resulting new economic terrain will undoubtedly be shaped by persistent uncertainty, tighter credit, lower consumer spending, greater consumer saving, and more pronounced government involvement in business (i.e., McKinsey terms this as being the “new normal”).  The use of powerful PA and Business Intelligence (BI) technologies may be the difference maker for companies in terms of removing the persistent uncertainty factor and, as a result, being better able to proactively address potentially serious problems before they become detrimental to the bottom line (i.e., a distinct competitive advantage).  The premise here is that those organizations that don’t invest heavily (or effectively) in PA and BI technologies may be left behind the “eight ball” in the currently evolving new economic order.

So the key question here is, does the burgeoning field of Predictive Analytics and the competitive advantage that it can potentially generate represent a major disruptive technology of the near future (i.e., in terms of dominant business models and profitability)?  Or does it represent just another trendy (and costly) “fad” that will go by the wayside without much impact?  My bet is on the former.

Addendum:  One factor to consider in the disruptive technology genre is the impact of the new technology (or innovations) on the existing business model.  It seems as if many disruptive innovations are really not “disruptive” in terms of the technological challenges presented, but are disruptive from the standpoint of the resulting business model challenges that don’t get managed properly.  Polaroid’s handling of the digital imaging technology when it was new is a real good example of this (see Case below).  It lends creedence to the premise that promising new technologies can end up falling through the cracks due to the failure of their supporting business models (and companies).  As a result, the necessary business model changes also need to be considered and implemented whenever a  new disruptive technology is being implemented in order to be successful.

 Case -> Comparing Polaroid’s Film-Based Business Model with Apple’s iTunes Model –

I).  Being a technology driven company, Polaroid was all about the technological “challenges” presented by the instant photo processing industry at the expense of marketing challenges involved (resulting in Polaroid’s eventual bankruptcy filing).  When digital imaging came on the scene Polaroid was able to deal with it from a technological standpoint, but it could not change its existing film-based business model based on polaroid film sales over to one based on digital imaging/processing  (i.e.,  no film involved).  As a result, the arrival of digital imaging technology served as a very disruptive innovation from a business model standpoint for Polaroid as it went from being very profitable to “collapsing” revenues in a short period of time.  This was evidently due to Polaroid’s propensity to view the new digital imaging technology as a technological challenge only, while ignoring the business model challenges presented by the technological change.  The key point here is that disruptive innovations are not primarily technological challenges, but actually business model challenges instead if not managed competently.  

Footnote:   In Polaroid’s defense, there are numerous hurdles involved in restructuring business models, which include  a). re-educating employees;  b). initial lower profitability;  c). current product cannibalization;  d). increased  management/stakeholder/customer conflicts;  e). complex organizational changes (including culture, etc.);  and f). conflict with traditional (i.e., successful) core competencies. 

 II).  Also being a technology driven company, Apple too is driven by the technological challenges presented by the computer and electronics industries. But unlike Polaroid, Apple is also driven by defining the new business models that need to be adopted in order to help propagate its ”disruptive innovation” types of products.  Apple’s iTune has basically turned the recording (or record) industry “on its head” in that consumers can now purchase and download individual songs at home instead of having to pay for entire albums of songs bundled onto CDs at record stores.  As a result of this “disruptive” business model, record stores are now a thing of the past as iTunes has revolutionized the music industry at the retail level due to its lower costs, increased conveniences,  and more desirable product selection changes.  As a result, some retail record stores have moved over to the movie/DVD side of the industry, but it is just a matter of time before this extended business model meets its demise too due to the arrival of even more disruptive innovations in the movie industry.  These innovations will primarily be based on new delivery technologies (e.g. better internet streaming methods, et al).

NOTE:  Interested LinkedIn members having disruptive technology interests are invited to join LinkedIn Group ”Disruptive Technologies” .