Research

2017 Analytics Symposium - Chicago Summary and Recordings

By Jack Phillips, Oct 31, 2017

Available to Research & Advisory Network Clients Only

Earlier this month, IIA held its 8th Analytics Symposium and awarded the 2017 ANNY Excellence in Analytics Award to Cisco Systems in a packed house at the Gleacher Center in Chicago. Read the key themes of the event and watch the session recordings on demand.

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A New Approach to Technology Tool Selection at Steelcase

By Robert Morison, Oct 16, 2017

Available to Research & Advisory Network Clients and Professional Members

As part of an effort to increase analytics aptitude and usage across the enterprise, Steelcase is implementing an enterprise data visualization tool. Inspired by over 100 years of insight, Steelcase leverages the power of place to offer a comprehensive portfolio of workplace, healthcare, and education products, furnishings and services to serve the world’s leading organizations. Founded in 1912, Steelcase is the global leader in enhancing how people work, heal, and learn.

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Analytics Maturity Powers Company Performance

By David Alles, Sep 21, 2017

Available to Research & Advisory Network Clients Only

Does the development of enterprise analytics capability really drive superior company performance? IIA’s previous research briefs demonstrate that analytics maturity varies significantly between industries and across the top-performing companies in each industry. This follow on research brief uses IIA’s proprietary analytics maturity data – from leading companies like Amazon, Apple, Netflix and Google – and publically available financial and company data, to illustrate the positive association between analytics maturity and superior company performance.

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Are Analytics Truly Self-Service?

By Thomas H. Davenport, Jul 25, 2017

I have been thinking about some of the changes over the last decade in analytics, coinciding with the revised and updated release of my book with Jeanne Harris, Competing on Analytics. The book is ten years old, and much has changed in the world of analytics in the meantime. In updating the book (and in a previous blog post about the updates), we focused on such changes as big data, machine learning, streaming analytics, embedded analytics, and so forth. But some commenters have pointed out that one change that’s just as important is the move to self-service analytics.

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Is AI over-hyped in 2017?

By Joanne Chen, Jul 20, 2017

Over the next ten years, I don’t believe AI is overhyped. However, in 2017, will all our jobs be automated away by bots? Unlikely. I believe the technology has incredible potential and will permeate across all aspects of our lives. But today, my sense is that many people don’t understand what the state of AI is, and thus contribute to hype. So what can AI do today?

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5 Things New Analytics Leaders Should Do to Succeed

By Bill Franks, Thomas H. Davenport, Jul 19, 2017

Available to Research & Advisory Network Clients Only

There is a fair amount of management research suggesting that the first 90 days or so are the most important time of a leader’s tenure. It’s when you establish your reputation and it determines what people start to think about you in your role. It’s often hard to change those first impressions. Therefore, IIA held a webinar to discuss this very important period for senior analytics leaders like a Chief Analytics Officer, Chief Data Officer, VP of analytics, or similar senior role. This paper captures the key elements of the discussion between Bill Franks and Tom Davenport, which focused on five essential things new analytics leaders should do to set themselves up for success.

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Artificial intelligence has quickly become one of the hottest topics in analytics. For all the power and promise, however, the opacity of AI models threatens to limit AI’s impact in the short term. The difficulty of explaining how an AI process gets to an answer has been a topic of much discussion. In fact, it came up in several talks in June at the O’Reilly Artificial Intelligence Conference in New York. There are a couple of angles from which the lack of explainability matters, some where it doesn’t matter, and also some work being done to address the issue.

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Over the past two years, I observed a very distinct pattern between companies that successfully navigate the new digital world and those that fall behind. As it turns out, those who are emerging as the early leaders in the age of digital disruption share one thing in common – a clear statement of intent. This blog includes examples that have helped shape my thinking on this issue.

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Five Big Data Analytics Pitfalls to Be Aware of (And Avoid!)

By Bill Franks, Jun 28, 2017

Available to Research & Advisory Network Clients Only

Many people think that in the age of big data, we always have more than enough information to build robust analytics for almost every situation. Unfortunately, this isn’t the case. In fact, there are situations where even massive amounts of data still don’t enable basic predictions to be made with confidence. In many cases, there isn’t much that can be done other than to recognize the facts and stick to basic analytics instead of getting fancy. However, it is critical to recognize the situation before expending a lot of effort in a wasteful attempt to get predictive analytics to work in a situation where success isn’t in the cards. This challenge of big data that can’t be used to predict seems like an impossible paradox at first, but, as you’ll see, it is not.

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The Manufacturer’s Dilemma

By Geoffrey Moore, Jun 20, 2017

There is a lot of serious talk in America these days about improving the state of our manufacturing sector. Smart products, Internet of things, robotics, predictive maintenance—all great stuff. But none of it addresses the most fundamental challenge facing the sector: how to deal with a demand/supply inversion which has made the customer king.

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