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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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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Like many other Americans who went to bed on election night prematurely, I learned about Donald Trump’s stunning victory in the U.S. presidential election on my phone early in the morning. The result was unambiguous but shocking and hard to process, especially at 5 a.m. But also like many other Americans, my shock wasn’t driven by a lack of awareness of Americans’ prevailing anti-establishment mindset and desire for change that tilted the vote (I’ve resided in three of the four key Midwestern states that “flipped”), but by the disconnect between the final result and the longstanding, data-driven expectation we had overly trusted.

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Analytics for Everyone

By Scott Langfeldt, Daniel Magestro, Nov 07, 2016

Available to Research & Advisory Network Clients and Professional Members

Although the focus of analytics initiatives in large organizations often is targeted at enabling data scientists to extract insights from big data sets and complex models, the reality is that users and beneficiaries of analytics capabilities extend across the entire organization. Well, at least that should be the case: Changing the culture to be more data driven is more about changing the mindsets of everyday “consumers” of data and analytics. Putting this broader population of workers in the spotlight, I sat down with Scott Langfeldt at Teradata to discuss the characteristics and needs of these workers, how to support those needs, and the value that better enabling them brings to organizations.

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2016 Analytics Symposium Summary

By Daniel Magestro, Oct 13, 2016

Available to Research & Advisory Network Clients Only

On September 27, IIA hosted the 2nd Analytics Symposium of 2016 at the State Room in Boston, MA. We welcomed a record number of IIA clients, industry experts, faculty and guests for a day of lively conversation, best-practice sharing and lessons learned.

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Analytics Journal: Making Analytics Projects Succeed

By Daniel Magestro, Oct 04, 2016

Last week the International Institute for Analytics hosted its semi-annual Analytics Symposium in Boston, bringing together 100+ analytics leaders from companies across industries for a day of best-practice sharing on many facets of analytics programs. Agenda topics ranged from artificial intelligence and workplace automation, to defining analytics roles and forming effective recruiting partnerships with universities.

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Embedding Analytics in the Organization

By SANDRA HOGAN, Robert Morison, Sep 26, 2016

Available to Research & Advisory Network Clients Only

When one says, “embedded analytics,” both business people and analytics professionals tend to think first of automated models and analyses embedded in business processes, for example, to score customer propensities or suggest offers to make. That’s only part of the story. An analytical enterprise — one that maximizes the strategic, competitive and operational value of its data and analyses — has analytics broadly embedded in the thinking and behavior of individuals and the culture of the organization.

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Analytical Excellence Among Digital Natives

By David Alles, John Burshek, Sep 19, 2016

Available to Research & Advisory Network Clients Only

The maturation of the Internet, the explosion of mobile, and the collapsing cost of cloud computing has led to the the rise of “Digital Native” companies. Founded after the mainstream adoption of the Internet, Digital Natives have been able to build and scale data-centric business models and data-driven cultures that create significant competitive advantage, allowing them to disrupt the markets they compete in. These companies are winning, in part, through targeted applications of data and analytics.

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Cyber Security: Driven by Data and Analytics (Part 3)

By Mark Dobeck, Aug 08, 2016

Available to Research & Advisory Network Clients and Professional Members

The headline grabbing data breaches bring cyber security and data vulnerability problems to the forefront of government/public and corporate policy. Most of the high profile cyber attacks involve the theft of individual identity or personal data. The cyber attacks adversely impacted the target organization as well as the persons whose data was compromised. The most common driver behind the attacks is greed and the opportunity to monetize stolen data assets. There is an active wholesale black market where one can find competitive offers to sell stolen identity information in bulk through nefarious websites. Hacking is becoming personal.

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Beyond Showcasing: The Makings of Strong Visual Designs

By Elliot Bendoly, Jul 15, 2016

Available to Research & Advisory Network Clients Only

Contextual fit and cognitive bias formed the focus of the last two entries in this IIA whitepaper series, “Traps and Hazards in Data Visualization Tool Design and Selection” and “Leveraging Biases in Visual Design.” In the second of these entries, the use of the Standard Convention (Bendoly 2016) was described in brief. This system of classification for graphical renderings is described not merely as an academic exercise. Instead it is a critical part of a broader effort to pin down the nature of interface design options and the biases individuals hold that either facilitate or stymie the interpretation of certain graphical renderings. In short, we can’t effectively tackle the visualization design questions of “What?” or “How?” until we grapple with “Why?”

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