Research & Insights

Last week, IIA attended the O’Reilly Strata Data Conference (@StrataData) in New York City. The conference tagline was “Make Data Work” and it provided a comprehensive overview of continued innovation in the big data and analytics ecosystems. In this blog, VP David Alles covers the top seven highlights from the conference.

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Cutting Through the Hype of Artificial Intelligence, Part 2

By Bill Franks, Sep 19, 2018

Available to Research & Advisory Network Clients Only

Artificial Intelligence (AI) is one of the hottest topics in the analytics space today. Within a two- to three-year span, AI went from relative obscurity to an extreme level of industry attention and media coverage. As a result, organizations that barely knew how to spell artificial intelligence a few years ago are now charging full steam ahead in pursuit of AI initiatives. In many ways, this is a good thing. After all, AI is quite powerful and has the ability to drive tremendous value if applied appropriately. However, this attention also has some negative consequences. Most notably, the topic of AI is so full of hype today that many organizations are struggling to separate what is real and achievable from what is pure hype and wishful thinking.

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Everyone who has lived within the world of analytics has seen cases where different parts of a business have made use of slightly differing definitions of core business metrics. Sometimes these differences lead to only minor and non-material disagreement. At other times, the differences in definition can cause massive divergence of reported results and related actions taken. Organizations must ensure that where differences exist in definitions those differences are either reconciled or clearly labeled and articulated to provide the proper context. When is the last time your organization took the time to really examine the strengths and weaknesses of the metric definitions being used on a daily basis?

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DELTA Plus Model & Five Stages of Analytics Maturity: A Primer

By Thomas H. Davenport, Sep 11, 2018

Available to Research & Advisory Network Clients Only

The purpose of this research brief is to summarize the key elements of DELTA Plus and Five Stages of Analytics Maturity, and discuss how these two frameworks can be used to understand analytical maturity in your organization. Two new components were added to the DELTA model, creating the DELTA Plus model. The DELTA Plus Model Framework encompasses the five foundational elements of a successful analytics program (Data, Enterprise, Leadership, Targets, and Analysts) and introduces two new elements (Technology and Analytical Techniques) required for high performance.

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Why Attend Fall Symposium?

By Linzie Reynolds VanWieringen, Sep 06, 2018

This fall IIA is bringing together some of the top analytics professionals from around the country to speak at the 2018 Analytics Symposium – Atlanta.

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Data and Analytics Trends Impacting Marketing - PART 1:  Channels and Personalization

By Michael Koved, Aug 30, 2018

Available to Research & Advisory Network Clients Only

Analytics advances are accelerating at an unprecedented pace, and perhaps nowhere more quickly than in marketing. Advances in computing hardware, software applications and delivery channels enable marketers to deliver timely and relevant messages to customers in ways that were unimaginable five or 10 years ago. New data sources are becoming available, and innovative ways to use data to shape the customer experience continue to push the envelope of possibilities. However, keeping track of the advances and being able to decipher which are relevant to your reality has a direct inverse relationship to the rate of change.

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Inquiry Response: The Benefits of Having an Analytics Pipeline

By IIA Expert, Aug 27, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

Our data and analytics group is six months old, and we’re challenged by many things: creating an intake process, developing the community, managing data ownership. We’re a heavily top-down organization—with the executives dictating our strategic initiatives for analytics—so we wonder if an analytics pipeline would fit into our culture.

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Everyone seems to agree that analytics, AI and Big Data are changing the world and that cloud computing is accelerating the adoption of these technologies. Combined, they are disrupting traditional business models and creating new market opportunities. If you are an analytics leader, data scientist, ML engineer, software engineer or other related role you see first-hand the power of analytics to unlocked hidden value in existing businesses or to enable completely new businesses. Are you using your first-hand knowledge of analytics to shape your investment strategy?

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Bumps and Triumphs on the Road to Optimization at UPS

By Jack Levis, Aug 21, 2018

Available to Research & Advisory Network Clients Only

United Parcel Service (UPS) is now well known for instituting ORION, an optimized routing system for UPS drivers that has been called the world’s largest operations research project. ORION determines the most efficient delivery route for every driver, every day, resulting in savings of more than 100 million driving miles. The project serves as an excellent case study on how embedding analytics and models within the day-to-day operations of the business—in this case, package delivery—can reap huge cost savings benefits.

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Inquiry Response: Creating Community with Embedded Analytics Teams

By IIA Expert, Aug 20, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

I’m leading the effort to embed analytics teams into other business functions, but I want their allegiance to be to analytics rather than the function they support. How do you create enough autonomy to ensure integration with the business units, while at the same time ensuring the teams don’t go native?

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