Research

The vast majority of people building analytics and data science processes have every intention of being good and ethical. As a result, most potentially unethical and evil processes arise in situations where that wasn’t the intention. The problem is typically that proper focus and governance is not in place to keep analytics and data science processes on the side of good. On top of that, what is good and what is evil isn’t nearly as clear cut as we’d wish it to be.

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Mapping an Information Economy

By Doug Mirsky, Aug 16, 2019

Available to Research & Advisory Network Clients Only

Information Economies in Organizations

The data warehouse revolution began in 1991 when Bill Inmon published Building the Data Warehouse. Inmon observed, early in that book, that every organization has a naturally occurring information economy, and that most naturally occurring information economies were inefficient, duplicative and prone to produce suboptimal decisions.

This observation of Inmon’s has not gotten anywhere near the credit, or attention, it deserves. A decade’s worth of collective practice in advanced analytics should tell us that everything we know about real-world economies applies to our information economies. There is demand for information by people and functions in an organization, and there is a supply of (some of) that information. There is (some amount) of technical and procedural infrastructure – some kind of market — to bring demand and supply together in an organized way. That “market” infrastructure is often partial, fragile and in some cases ineffective. There are competitive alternatives (like cloud service providers and SaaS vendors), over- and under-regulation (various data governance models), excessive demand-side taxation (cost allocation strategies), failure to invest in infrastructure, and all other elements of economies.

When organizations are planning strategy-driven large-scale advanced analytics programs, they should begin their planning by characterizing their as-is information economy.

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Creating A Data Engineering Culture: What it is, why it’s important, and how, and how not, to build

By Jesse Anderson, Jul 31, 2019

Available to Research & Advisory Network Clients Only

Why do some analytics projects succeed while so many fail? According to Gartner analyst Nick Heudecker, as many as 85% of big data projects fail. However, the ROI from the other 15% that succeed is incredibly promising. With such a clearly high barrier to competency in executing big data strategies, there remains significant opportunity for first-mover advantage for enterprises that can crack the code to improving their outcomes.

So, what can organizations do to increase their chances of big data success? Part of the answer lies in creating a data engineering culture. This is the necessary foundation underpinning a big data analytics proficiency and enables companies to outperform the competition.

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Graph Analytics Use Cases

By Daniel Graham, Jul 10, 2019

Available to Research & Advisory Network Clients Only

Introduction In 1996, two computer science students — Larry and Sergei — were enthralled by the emerging internet. But finding anything on the undeveloped web was horribly difficult. Then came the “Aha!” discovery that academic web page citations (URLs) are a proxy for popularity. If many websites “like” the same web page, that page value is probably higher to researchers. So Larry and Sergei designed an algorithm called PageRank. It measured “link juice” — the strength between web pages. Google emerged from PageRank, web URLs and an advertising business model. This article explores the incredible value of “link juice.” Graph analysis turns the relational…

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Sanford Health Becomes Data-Driven

By Robert Morison, Jun 26, 2019

Available to Research & Advisory Network Clients Only

Sanford Health is a major health system with over 49,000 employees, 187,000 health plan members, and $6.1B in annual revenue. The organization has been pursuing a growth strategy for the last two decades. Milestones include: merging with a series of regional health providers, incorporating the North Dakota Public Employees Retirement System (NDPRS) members into its health plan, and most recently the 2019 merger with Good Samaritan Society, the largest not-for-profit provider of senior housing and services in the United States.

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Analytics Fluency – How Optum Is Boosting Six Critical Competencies

By Alex Barclay, May 08, 2019

Available to Research & Advisory Network Clients Only

Optum has launched a number of initiatives to boost analytics fluency, especially among its business leaders and team members. The goal is to equip individuals in business units, operations and other key parts of Optum with the knowledge and skills needed to effectively engage, employ and capitalize on analytics. While our efforts are a work in progress, we view analytics fluency as a critical prerequisite to “competing on analytics” and key to our mission of transforming health care. The next sections provide an overview of Optum and the challenges we’re addressing in health care, while subsequent sections describe the motivation for and our experience with fluency-building initiatives to date.

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Consultative Analytics at VSP Global

By Robert Morison, Dec 06, 2018

Available to Research & Advisory Network Clients Only

VSP established a central analytics group three years ago with the mission of empowering and enabling data management and analytics across the enterprise. That didn’t mean performing analytics for the entire organization, but rather shaping how analytics are performed by managing data more centrally, migrating to consistent technology platforms, promoting best practices, and scaling up analytics talent.

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Atlanta 2018 Analytics Symposium: Event Summary

By IIA Expert, Oct 24, 2018

Available to Research & Advisory Network Clients Only

IIA’s 10th Analytics Symposium was held in Atlanta on October 10, 2018. This Symposium brought together analytics leaders from different industries, functions, and geographies to share insights and best practices. Experienced and innovative analytical leaders from large enterprises (Ford, Honeywell, Optum, GE, and Symantec/ID Analytics) described their organizations’ analytical journeys and key lessons learned—about creating business value, building an analytics team, creating a more analytically savvy company, and dealing with the hype around AI. Also sharing insights and trends were leading academics (IIA co-founder Tom Davenport and Jennifer Priestley) and IIA leaders Bill Franks and Kathy Koontz. Read the event summary for key themes and insights from the conference.

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Atlanta 2018 Analytics Symposium Video: Alex Barclay

By Alex Barclay, Oct 24, 2018

Available to Research & Advisory Network Clients Only

Competing on Analytics is a “Team Sport,” but Which Sport?

Alex Barclay, SVP at Optum (part of United Health Group, a Fortune 10 company), outlines the capabilities required to compete on analytics and describe how the company is boosting these capabilities among executives, managers and analytics professionals.

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Atlanta 2018 Analytics Symposium Presentation: Alex Barclay

By Alex Barclay, Oct 16, 2018

Available to Research & Advisory Network Clients Only

Competing on Analytics is a “Team Sport,” but Which Sport?

Alex Barclay, SVP at Optum (part of United Health Group, a Fortune 10 company), outlines the capabilities required to compete on analytics and describe how the company is boosting these capabilities among executives, managers and analytics professionals.

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