By Jack Phillips, Mar 23, 2017
IIA’s Spring Analytics Symposium in Silicon Valley last week is in the books and marked a significant milestone for our company across a variety of fronts. The innovation-themed agenda revealed how many of IIA’s research clients (e.g., Ford, VMware, Lilly, Cleveland Clinic) are driving high performance when it comes to analytics and data. The program included speakers from Silicon Valley digital native companies who shared their perspectives as businesses that were built on data. The contrast between traditional firms trying to graft new technologies onto legacy systems, and the data scientist-led firms like Pandora and Netflix was stark and illuminating.
By David Alles, Mar 21, 2017
The first week of March Madness is complete. 68 teams have been whittled down to 16 and the potential winners of many office pools have already been decided. It is estimated that Americans will play over 70 million brackets and wager over $10.4B on this year’s NCAA tournament. Given the interest, it is a great opportunity to show people the power of analytics in a context they will readily relate to (and potentially profit from).
By Jack Phillips, Mar 17, 2017
Full agenda for the 2017 Analytics Symposium - Silicon Valley
By David Alles, Mar 16, 2017
Is there a company more associated with Internet and data than Google? Founded in 1996 by Larry Page and Sergey Brin with the mission to “organize the world’s information and make it universally accessible and useful,” Google has grown into one of the largest and most profitable companies in the world. Expanding from their core Search business, Google has become a major force in mobile (Android), media (YouTube), productivity applications (G Suite – Mail, Drive, Docs, Sheets and Slides), personal computers (Chrome and Chrome OS) and cloud services (GCP – Google Cloud Platform) while also making significant investments in autonomous vehicles (Waymo) and broadband (Google Fiber). Reflecting the growing diversity of its business, Google was reorganized as a conglomerate under the Alphabet banner in 2015.
By Bill Franks, Mar 09, 2017
It used to be that a doctor was a doctor for the most part. Even a century ago, unless you lived in a large city, people likely had a town doctor who handled most every type of ailment and guided most any type of treatment. Given the limited medical knowledge and lack of sophisticated treatment options during this time, these generalists could often provide a level of care that was comparable to the best available. Today, that is no longer true in medicine and a similar trend is playing out in analytics.
By Cole Nussbaumer Knaflic, Mar 07, 2017
Today’s post is about one of my favorite dessert graphs: the pie chart. Those who follow my work know that I am not a fan. In fact, I’ve written posts with titles like “pie charts are evil” and given presentations called “death to pie charts.” It can be fun to be a little provocative sometimes. Though one might argue this is taking it too far.
By Ty Henkaline, Mar 02, 2017
The single most valuable practice any analytics team can engage in is rapid prototyping. Analytics teams already do a lot of making, and some do a lot of designing. What almost none do is a lot of prototyping. Prototyping enables a team to turn a potential analytics opportunity into a minimally viable solution – in just a fraction of the time and with just a fraction of the effort.
By Thomas H. Davenport, Feb 28, 2017
While humans may be ahead of computers in the ability to create strategy today, we shouldn’t be complacent about our dominance. As a society, we are becoming increasingly comfortable with the idea that machines can make decisions and take actions on their own. We already have semi-autonomous vehicles, high-performing manufacturing robots, and automated decision making in insurance underwriting and bank credit. We have machines that can beat humans at virtually any game that can be programmed. Intelligent systems can recommend cancer cures and diabetes treatments. “Robotic process automation” can perform a wide variety of digital tasks.
Beware of Workforce Vendors Using Predictive Workforce Language But Offering Non-Predictive Solution
By Greta Roberts, Feb 21, 2017
Talent Analytics, Corp. has a unique approach to workforce predictive analytics. At our firm, we measure success by how our projects quantifiably benefit the line of business. We watch it, track it, and report success. Our algorithms get better and smarter using the best data science methods available. I’ve been involved in the predictive workforce arena for almost two decades. I have to admit I’m surprised at how many vendors claiming to reduce employee turnover or increase employee performance do little more than offer a solution that “sounds” effective. They say the right predictive analytics buzzwords – without proving that their solutions actually work for their customers.
By Adam Greene, Feb 16, 2017
IIA has been monitoring the growing momentum of Cloud-based analytics. Recent blogs and research briefs include Analytics as a Service” The Buy vs. Build” Decision and Amazon Web Services Moves Aggressively in Big Data, BI and Analytics Services. These highlight the availability of new, high profile services that are targeted directly at traditional analytics activities. However, there are also a number of more subtle, but very significant developments taking place that warrant monitoring.