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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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

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

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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Influence - Ask and You Shall Receive?

By Greta Roberts, Oct 19, 2012

An exciting new metric, “Influence”, is making its way into the enterprise market. While most influence research has been applied to the internet at large, it is tempting to apply this concept to interactions inside of a company. In our knowledge-based economy, it only makes sense to capitalize on this flow of knowledge.

For the sake of this article, let’s put aside concerns about the reliability, stability and completeness of these metrics. And, we will also put aside the privacy concerns. Let’s assume for the moment that these numbers do reliably show the information impact of an individual on their enterprise. Let’s even say that we print this number in large print next to each person’s picture on their home page - in fact we have already seen (numerous) software systems doing this.

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Employees are People Too

By Greta Roberts, Aug 08, 2012

There’s no going back on the fact that numbers are the language of business. What’s fantastic is that employees also have numbers that help to describe and value their characteristics. (Notice I said “also” not “only”). To be valued as a business asset, employees also need to be described by numbers. Analytics, statistics and new technologies make it possible to include employee numbers as an asset (or not) in understanding a business’ portfolio.

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After attending several analytics conferences over the last month, I’m beginning to understand an important nuance about the community we call “analytics” worked by “analytics professionals” or “data scientists.” It seems as if the defining boundary of our discipline is almost always that we data scientists apply ourselves to business, organizational, and market data.

The important nuance? Businesses, organizations, and markets all involve interactions between people. Always.

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As the discipline of analytics grows and becomes more complex, it becomes more critical to understand the people who are well suited to this sophisticated challenge. True Analytics Professionals (that go beyond spreadsheet work, standard BI reporting tools and ad-hoc SQL queries) will want to fill their teams with, and be surrounded by, other Analytics Professionals who can engage in similarly sophisticated analytics.

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It is a common and natural question for leadership to wonder what “human factors” drive (or hinder) performance in their enterprise. And further, whether it is possible to reliably measure these factors and use them for ongoing improvement.

In today’s discussion we will share some of our thinking and research to build models that measure what drives humans to perform. Future articles will review the real challenges of actually defining or quantitatively measuring their performance.

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Brain Science 101 for Data Scientists

By Greta Roberts, Apr 11, 2012

I recently attended a seminar at nearby MIT. This session was led by H. Sebastien Seung who wrote a recently published book titled: Connectome: How the Brain’s Wiring Makes Us Who We Are.

His discussion got us thinking … about why people are the way they are, how (if) they change, how to measure them, and how who we are impacts our business performance. Like others before him - Dr. Seung’s approach is to map areas of the brain by EEG or fMRI. This approach has been around for a long while and is a rather old school approach (though still unsolved). Though fascinating, neither the EEG nor the fMRI reveals how the brain works, or makes any strides to helping us make this information useful by businesses.

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