October 8, and 9, 2014 were a very busy two days for the Public Relations team at General Electric. No less than 4 press releases were published about the first steps this very mature — not to mention very large — business has stepped into big data and analytics.
Consider, for example, how the big data and analytics business at General Electric ramped up to over $1Bil in sales: October 9, 2014, Bloomberg publishes an article written by Richard Clough, titled GE Sees Fourfold Rise in Sales From Industrial Internet. Clough reports “[r]evenue [attributed to analytics and data collection] is headed to about $1.1 billion this year from the analytics operations as the backlog has swelled to $1.3 billion”.
Early stage ISVs looking with envy at this lightning-fast entry should consider how scale, along with a decision to acquire IP via partnerships and acquisitions (rather than opting to build it in-house), and picking the right market made this emerging success story a reality. Let’s start by considering these three points in reverse order:
- Picking the right market: GE opted to apply its new tech to a set of markets loosely collected into something they call the “Industrial Internet”. These markets include Energy (exploration, production, distribution), Transportation, Healthcare, Manufacturing and Machinery. Choosing these markets makes complete sense. GE is a leader in each of these already. Why not apply new tech to old familiar stomping grounds?
- Leverage partnerships and acquisitions to come to market in lieu of rolling your own: Leading players in each of the markets GE opted to enter expressed burning needs for better security and better insight. Other players in each of the markets (Cisco, Symantec, Stanford University and UC Berkeley) all stand to benefit from the core tech GE brings to the table, so persuading them to partner was likely to have been a comparatively easy task. The most prominent segment of the tech (very promising security tech for industrial, high speed data communications over TCP/IP, Ethernet networks) understandably, came into the package from wurldtech, a business GE opted to acquire
- Scale: With GE’s production run rate of turbines, locomotive engines, jet engines, and other complex, massive industrial machinery, the task of finding a home for the millions of industrial sensors required to feed the analytics piece of the tech with the big data it desperately needs, does not look to have been a difficult task. Product management, appropriately, looked into its own backyard to find the consumers required to ramp up to scale in very fast time.
In sum, GE’s entry into this market, if the “rubber hits the road” and metrics bear out claims, looks to be a case study early ISVs should memorize as they plan their tech marketing strategy.
Ira Michael Blonder
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