By Robert Handfield, Aug 23, 2016
A recent visit to a mid-sized hospital in the Northeast United States provided a number of important insights into how great a problem material handling data integrity is in the daily life of those people who work in operating rooms across the country. The nurses, buyers, surgical techs, operating room specialists, and physicians who work on the front lines of hospitals, are having to deal with massive forces of friction that are reducing their ability to provide top tier patient care.
By Bill Franks, Aug 11, 2016
I see a strong parallel between athleticism and analytic capability. I also see a strong parallel between learning to speak multiple languages and learning to work within differing analytic environments. I’ll explain what I mean by both of these statements in this blog in the hope that it will help make the path forward seem clearer and less intimidating.
By Jack Phillips, Aug 08, 2016
At IIA, we spend most of our time helping enterprises build, sustain and measure their enterprise analytics capabilities. But, we are always on the lookout for standout players who combine technology and analytics for good in their communities.
By Greta Roberts, Jul 25, 2016
For most companies, their current pre-hire talent assessments are wasted data. Results are delivered in an individual report that cannot be analyzed or aggregated. For most “legacy” talent assessments, it’s difficult or impossible to determine what positive (or negative) business effect the assessments are having. It often comes down to the question of “how much the HR person believes the results.” This is a bad measure of success. But it doesn’t have to be that way.
By Bill Franks, Jul 14, 2016
Is your organization doing all it can to modernize your data collection and analytics processes? Barely a decade ago, networks like AMC had virtually no information on consumers. Today, they are able to capture information at a level not possible until very recently.
By Rich Lanza, Jun 21, 2016
We only need the first and last letters to decipher more than half of words in the English language. This has implications for game shows, and more importantly, the business world.
By Bill Franks, Jun 09, 2016
Much like the Fibonacci sequence appears repeatedly in nature, there are recurring patterns in data that, once recognized, can improve both our analytics and our efficiency in creating them.
By Keri Pearlson, Jun 03, 2016
HR leaders can learn a lot from the experiences of MLB teams and sabermetrics. Teams who successfully use these tools have been able to field better teams, recognize true contributors, identify top performing teams, and understand the really contributing factors to better performance. Those are the same goals our organizations have. Ultimately, it’s about bringing the right people to the right roles and the right time—for baseball teams and corporate teams.
By Daniel Magestro, May 27, 2016
Perhaps more than any industry, healthcare analytics inspires a sense of purpose among data-evangelizing types like myself. When transactional data involves steps in disease treatment, and personalization refers to the individual’s experience in a clinical setting, it’s easy to get caught up in the many data-driven approaches to saving lives and improving outcomes.
By Thomas H. Davenport, May 25, 2016
Perhaps the most important leadership issue is preparing your employees for roles in which they augment smart machines, and vice-versa. There will be new jobs involving implementation and oversight of these technologies—getting them installed, monitoring their daily performance, and improving them over time. Employees with some aptitude need to be groomed for such roles.