In my recap of the IBM Vision 2017 conference, I wasn’t sure what to expect from IBM’s Think conference and its new format, but went into it with an open mind. The volume of content I and other attendees were confronted with at IBM Think, though, was overwhelming: there were approximately 2,000 sessions to choose from! Outside of sessions on the usual suspects (Cognos Analytics, Planning Analytics, SPSS Modeler, etc.) it was difficult to see beyond those subject areas, if not for some excellent keynote presentations by IBM kick off the conference, which can all be viewed on-demand, particularly the Chairman’s keynote from IBM CEO Ginni Rometty.
Ginni reflected on two watershed moments over the past 60 years where we saw exponential growth when “both business and technology architectures change at the same time”:
Ginni believes a third, as-yet-unnamed, watershed moment is beginning: the convergence of digital platforms with artificial intelligence, in the hands of users, to enable us to learn exponentially. You might be asking what does this have to do with analytics? Everything!
As the saying goes, “those who fail to learn from history are doomed to repeat it”, and it is our “history”, in the form of the data that we possess, that Ginni suggested will enable us to take this next leap forward. For companies, this means all kinds of data “owned” by your business: financial, customer, telemetric, and more. We at QueBIT have long advocated warehousing and storing this data to support analytics of all kinds. Indeed, with the digital platforms available today to manage vast amounts of data there is no reason any customer should consider throwing away data—if you do, you’re doomed, in this case, to being without information that can “teach” predictive and artificial intelligence models of the future by learning from your past.
Many of QueBIT’s solutions already take a giant step toward in this future direction, by helping our customers drive better business decisions around demand planning, price optimization, maintenance, financial consolidations and more. Two of our sessions at Think, which were highlighted by IBM, shared implementations of our solutions, like Galileo and how it’s helped bring significant ROI to customers through more accurate forecasting, driven by customer data and machine learning. In fact, one of QueBIT’s customers, LKQ, was awarded an “IBM Client Excellence and Transformational Award” in Planning Analytics for the predictive price optimization solution (Achilles), which we helped them implement. For QueBIT’s customers, the future is now!
It’s easy to get lost in a sea of technology and data and forget that it’s the users, who can use both, which ultimately drive our success. As Ginni was quick to point out in her keynote address “you are going to empower people with all forms of digital intelligence… man and machine get better answers than man or machine alone.”
This is a great time to talk about how we empower users with “digital intelligence”, or analytics, today by summarizing what we learned about IBM Analytics software, and what is coming that we can look forward to:
With tools such as these to empower your users, the future looks very bright, indeed!
There is so much more that came out of the Think 2018 conference that I didn’t have room to share here, including really exciting technical innovations being worked on by IBM Research like crypto-anchors for blockchain, quantum computing, lattice cryptography, AI-powered robot microscopes and more—all of these may change our future as we know it, too (even if we may not be able to see them!) and I’d encourage taking a look at a recap of IBM’s 5 in 5 presentation to see more.
Hopefully you now have a better picture of how QueBIT is preparing its customers to embrace the next watershed moment in analytics and artificial intelligence. We at QueBIT take great pride in having a deep understanding of both analytics and technology, and how the two can be applied together to deliver amazing results for our clients. If you would like to learn more about anything in this post, just tweet us at @askQueBIT or email us at info@quebit.com.