Employee Engagement is a Tricky Predictive Metric

By Greta Roberts, Mar 15, 2016

In my day job, my work focuses on using predictive analytics to decrease employee turnover or increase employee performance. One topic that frequently comes up is employee engagement data, and whether it is meaningful to the analysis. There can often be years of employee engagement data, and the data is typically in HR’s control.

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When beginning a new predictive analytics project, the client often mentions the importance of a “quick win.” However, implementing a quick win for a predictive analytics project can be difficult. There are at least two challenges, which I’ll describe, when taking a traditional quick win approach to predictive analytics projects.

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How Credit Risk Relates to Hiring New Employees

By Greta Roberts, Jan 07, 2016

After an employee is hired, it is too late to find out if they are a good risk. Like lenders, businesses need to be able to predict – before extending an offer – candidates with a greater probability of being successful in the role they’re being hired for.

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Whether you’re new to the concept of Predictive Workforce Analytics, or just brushing up, here are 12 essential rules to help Human Resources derive the most value from analytics.

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My plea to HR (and any other department hiring a Data Scientist)? Stop hiring real Data Scientists until you’re ready to do real data science.

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Four Functional Clusters of Analytics Professionals

By Greta Roberts, Oct 15, 2013

Available to ERS Clients only

In this IIA Client Phone Briefing, Greta Roberts takes a deeper dive into the four functional clusters of analytics professionals, identified in the 2012 Analytics Professionals Study.

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All In a Day’s Work: Four Functional Clusters of Analytics Professionals

By Greta Roberts, Pasha Roberts, Aug 06, 2013

Available to ERS Clients only

The groundbreaking 2012 Analytics Professionals Study by Talent Analytics, Corp and the International Institute for Analytics utilized many measures to understand the characteristics of modern analytics professionals and data scientists. The study examined 302 active analytics professionals in a diverse sample of companies, industries, sizes and circumstances.

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Quantifying Analytical Talent

By Greta Roberts, Jan 16, 2013

Available to ERS Clients only

Modern businesses have embraced analytics in a bigger, deeper, more sophisticated, and more specific way than in prior decades. This enhanced focus has led to many things: the measurement of everything, many new studies, new departments, new roles, and several educational initiatives. Glowing articles in the press and social media fuel this activity.

Though there is a great deal of actionable analysis coming out of this work, there is plenty of hype to go around. A new job category has been introduced, the “Data Scientist,” in deference to the new scope and tools involved, especially around Big Data. Under-standably, there is confusion in the job market about what this role entails. Hiring managers, scrambling to find the ideal analytics professional, share anecdotal tips such as “find those with creative degrees in music or art” along with the usual technical expertise.

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Demystifying Analytical Talent

By Greta Roberts, Jan 08, 2013

Available to ERS Clients only

This powerpoint presentation is the companion to a roundtable discussion led by IIA Faculty Member Greta Roberts. The presentation examines the “Demystifying Analytical Talent” study, developed in 2012 by Talent Analytics, Corp. and the International Institute for Analytics and describes the background, nature, activities, traits and performance of current analytic professionals, including data scientists. The results provide insights on how to better find, hire, deploy and utilize analytics professionals.

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Demystifying Analytical Talent

By Greta Roberts, Jan 08, 2013

Available to ERS Clients and Professional Members

In this IIA Client Phone Briefing, Faculty Member Greta Roberts reviews the “Demystifying Analytical Talent” study, developed in 2012 by Talent Analytics, Corp. and the International Institute for Analytics. This is the first time the background, nature, activities, traits and performance of current analytic professionals, including data scientists, has been quantitatively studied. The results provide insights on how to better find, hire, deploy and utilize analytics professionals.

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