Research

Three Paths for Aligning Analytics to Business Strategy

By Daniel Magestro, Jack Phillips, Feb 27, 2017

Available to Research & Advisory Network Clients Only

As organizations strive to build their analytics capabilities, an unexpected challenge has plagued many efforts: The activities of analytics teams and the investments made to support them aren’t in sync with what executives expect or desire. On the surface, it might have seemed straightforward for “business analytics” to be in sync with the business’s strategic needs. After all, the decision to invest in the first place was driven by the business’s needs, right?

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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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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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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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How the Machine Learning of Today is Driving the Artificial Intelligence of Tomorrow

By Andrew Pease, JOSEFIN ROSÉN, Robert Morison, Dec 22, 2016

Available to Research & Advisory Network Clients Only

Machine learning is hot and for good reason. The components — big data, computing power, analytical methods — are in place, and compelling applications are multiplying. To capitalize on the technology, organizations must build experience. They must also proceed pragmatically with one eye on the business and the other on the ethical implications of the algorithms deployed and the decisions automatically made. To explore the opportunities, challenges, and success factors of machine learning today and tomorrow, IIA spoke with Andrew Pease, Principal Business Solutions Manager, Global Technology Practice at SAS Institute and Josefin Rosén, Principal Advisor Analytics, Nordic Government at SAS Institute.

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Mitigating Cybersecurity Threats at Educational Institutions

By Rob Harper, Robert Morison, Dec 14, 2016

Available to Research & Advisory Network Clients Only

With large amounts of sensitive information about students, faculty, and research programs, educational institutions have become common targets for hackers and cyber criminals. Counteracting the threats can be difficult with tight budgets and complex technological environments. To explore the cybersecurity challenges faced by educational organizations, as well as some of the opportunities to address them, IIA spoke with Rob Harper, Director of the Education Practice at SAS.

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Bringing Clarity to Data Science Projects With Decision Modeling: A Case Study

By James Taylor, Dec 05, 2016

Available to Research & Advisory Network Clients and Professional Members

This leading practice brief examines an organization that is a global leader in information technology. Like many large companies, it has teams focusing on data science in organizations like marketing, engineering, supply chain, and IT. They also have a centralized business intelligence and analytics capability, shared across internal operations.

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