The Uberization of Analytics
That Big Data and Analytics are potential game changers almost sounds like so last decade. Such wide ranging has been their acceptance that most organizations, across industries, are scurrying to get on to the bandwagon, lest they should miss out on the plethora of likely benefits.
Scores of corporations of all sizes, from Banking & Financial Services to Discreet & Process Manufacturers, from Telecom operators to Healthcare providers, from Retail & Ecommerce to Public Sector Enterprises & Utilities all recognize the opportunity to save costs, increase revenue, improve bottom-line and delight the customers.
Harnessing the power of Analytics tops boardroom agendas and increasingly the operational teams are tasked with putting together a PTE – detailed Plan to Execute.
The classical approaches, albeit often found wanting, to leverage the Power of Analytics, include one of the two choices, akin to the traditional make or buy decisions. The former includes setting up an Analytics COE – complete with cutting edge technology and in-house Data Scientists under the aegis of the CIO or the newly carved out Chief Analytics Officer. The latter comprises approaching a Data Service Provider and outsourcing bulk of the work.
While one could argue from both sides as to the efficacy of the either of the Classical approaches, there is a new paradigm emerging over the horizon that combines best of both the worlds. I call this the “Uberization of Analytics”.
The end game for most organizations exploring either of the Classical approaches is an Optimized Decision. However, in pursuit of this scarce commodity termed Optimized Decision, organizations end up spending millions on Technology Platforms and on recruiting the best number crunchers. These Technology Platforms are woefully prone to obsolescence and the talent needs frequent upskilling, i.e. if you manage to find the right mix first up.
The Uberization of Analytics brings together the best talent from a global pool of resources unconstrained by geography and the limited need to invest in Technology platforms. All this On- Demand whenever an Optimized Decision is required!
In addition is a huge advantage of having hyper-specialized resources working on hypercritical projects every time that an Optimized Decision is needed. There is no Technological glut and neither are you stuck with resources that are under skilled for a particular task!
The emerging paradigm brings in its fold a tremendous promise for late and early adopters alike. The case for Uberization of Analytics has never been stronger in pursuit of the Optimized Decision.