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Big Data, Big Hairy Problems – Bring ‘Em On! by Simon Arkell, CEO, Predixion Software

Oct 21 2013

A couple of weeks ago I was honored to participate in the Accenture “Journey to Analytics ROI” panel in San Francisco. To say that I was enamored with the location, organization and quality of attendees is an understatement. You see we have been working with Accenture for much of the last 12 months and, most recently, in addition to inviting Predixion Software to be a global alliance partner, Accenture led our most recent round of funding as a company alongside GE. Having an organization with the size and reputation of Accenture as a key investor and strategic partner is a massive accelerator for Predixion as a 4 year old company, and the experience of actually participating in an Accenture event such as this is great for business and the industry. Our space is topical, exciting, intriguing challenging and competitive!

During the Accenture panel it became obvious to most of us that big data is upon us and the industry has to do a better job of making predictive analytics more accessible to the average business user. Much of the content of the panel was centered around this and many of the questions were big data centric. From capturing data, to making sense of it and making it actionable, it is clear, that these topics are on most peoples’ minds.

To me, big data is an amorphous topic that can mean so many things. What is clear is that the age of big data and analytics is well and truly upon us and we are just scratching the surface. In the “Kitty Hawk Days of Big Data” enterprises must react and participate or risk falling behind. Accenture rightly focuses on “The Journey to ROI” because many projects cannot get funded sufficiently if there is no ROI attached. The challenge we face is that we are in a new age and use cases, although high in potential, have not all had sufficient time to bear fruit and generate ROI. This is likely to change as innovative companies try new things and generate the return they are looking for and then publish those outcomes. The momentum will grow and it will be companies like Predixion and Accenture that move the needle for corporations around the globe, across all industries. New companies with funny names like Jointly, Cirro, SourceThought, Maana, Ubix, Pivotal and others are sprouting up with new approaches that take big data well past just another flavor of Hadoop and it’s exciting to see their growth.

One example of the meteoric rise of data volume, veracity, velocity and all the other V’s is the sensor data generated in what GE calls the “Industrial Internet.” Cisco calls it the “Internet of Things.” I call it “Really Bloody Big Data!” GE’s software initiative to pull this together is based in San Ramon, CA and is co-incidentally called “Predix.” We at Predixion are proud to be listed as a strategic partner alongside great companies like Intel, Amazon Web Services, Intel, Accenture and Cisco and we are working with those partners to help solve big hairy problems at GE. The industrial internet is effectively the management of the incredible volumes of data that come from sensors that are attached to all things made by GE. From oil well blowout preventers to MRI scanners, locomotives and jet engines, the value that can be created when captured, understood and used is incredible. GE states that just a 1% reduction in inefficiency in the healthcare industry as a result of this technology would save the industry over $63 Billion per annum. These are big numbers folks and I for one am glad to be working with Accenture and GE to be a part of the future for these types of revolutions.

With software like Predixion’s and global consulting services like Accenture’s attacking problems like GE’s, you have a potent combination that can change industries. It’s not enough to install great software, the real gems lay in the change management that can come from implementing such innovative solutions across industries. How does a nurse change the way he operates if he is now intervening on high risk patients whose predicted outcome he has never had visibility into before? How does an airline technician change her approach to preventative maintenance when the data flying off a jet engine part is scoring a predictive model in real time and alerting her on a smart phone that a part needs replacing? I was lucky enough to dine with some industry heavyweights this past week including the CEO of GE, Jeff Immelt. The big request from his biggest customers? ZERO DOWN TIME. It is the big hairy goal and predictive analytics can take companies there in all industries. Its fascinating stuff and we are at the beginning of a new revolution.

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