Research

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.

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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.

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Revisiting Common Obstacles to Analytics Success

By Robert Morison, Daniel Magestro, Feb 13, 2017

Available to Research & Advisory Network Clients Only

In 2013, IIA published a popular and useful research brief in response to a client’s general question: What are the common hurdles encountered when putting analytics to work in a business, both in developing analytical models and applications and in building enterprise analytical capability? For us, this question is so central to IIA’s mission of helping organizations navigate the many challenges to achieving analytics maturity, that we decided it was time for an update and a re-evaluation of common obstacles faced by analytics leaders and practitioners. This update is informed by major forces and trends in play over the past few years.

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Six Very Clear Signs That Your Job Is Due To Be Automated

By Thomas H. Davenport, Feb 07, 2017

In H. G. Wells’s classic The War of the Worlds, the narrator pauses a moment to rue the fact that he didn’t react sooner to the arrival of an “intelligence greater than man’s”—in his case, Martians landing on earth. Comparing himself to a comfortable dodo in its nest, he imagined those ill-fated birds also dithering as hungry sailors invaded their island: “We will peck them to death tomorrow, my dear.” And what about you? As intelligent technologies take over more and more of the decision-making territory once occupied by humans, are you taking any action? Are you sufficiently aware of the signs that you should? To help you get the head start you may need, here are the signs that it’s time to fly the nest. All of them are evidence that a knowledge worker’s job is on the path to automation.

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Inquiry Response: Scaling Analytics Talent Growth

By Greta Roberts, Feb 06, 2017

Available to Research & Advisory Network Clients Only

We are strategizing how to scale our analytics talent over the next few years, and looking for insights on how to determine how many resources are enough.

Questions:

  • What business drivers would cause our organization to grow our talent base? Do we have enough talent as it is?

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The Myth of the Data Scientist Shortage

By Thomas H. Davenport, Jan 24, 2017

Technologists and business folks alike overstate the shortage of data scientists. They just need to know where to look. Here are some common excuses companies use for not employing data scientists, and why they’re no longer valid.

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Inquiry Response: Building Analytics Career Paths

By IIA Faculty, Jan 19, 2017

Available to Research & Advisory Network Clients Only

A Healthcare Provider client was looking to build stronger career paths for their analytics team. The client wanted to hear about other organizations’ paths and strategies that could leveraged for its own talent acquisition, development, and retention.

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Analytics as a Service: The “Buy vs. Build” Decision

Jan 18, 2017

Available to Research & Advisory Network Clients Only

The idea of competing on analytics – building and sustaining competitive differentiation from innovative use of advanced predictive and prescriptive analytics – has moved, in less than a decade, from a revolutionary notion to a strategic commonplace.

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Over the past 30+ years, businesses have spent billions on talent assessments. Many of these are now being used to understand job candidates. Increasingly, businesses are asking how (or if) a predictive talent acquisition strategy can include the use of pre-hire assessments? As costs of failed new hires continue to rise, recruiters and hiring managers are looking for any kind of pre-hire information to increase the probability of making a great hire.

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The Analytics Project Lifecycle: Charting the Full Path to Realized Value

By Daniel Magestro, Jan 05, 2017

Available to Research & Advisory Network Clients Only

One of the most referenced and quoted taglines in business analytics has a discouraging ring to it: something like 70 percent of all analytics projects fail. Conference keynoters, technology vendors, analytics solution providers, internal analytics evangelists, and (yes) advisory firms all use this catchphrase to highlight various barriers to analytics success — and the need for dedicated effort and investment to navigate the barriers.

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