Research

I won’t argue the merits of analytics here, though there are many, but I will describe for you one successful approach that forward-thinking analytics leaders have taken to create a thriving analytics program and a healthy analytics culture: Think of building your analytics program the way an entrepreneur would build a startup business.

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Direct conversations through on-site engagement with different lines of business is the most direct and effective means of understanding how sourcing processes are occurring today, as well as understanding how the sourcing need evolves and is expressed to suppliers. The initial approach should be selected based on the greatest likelihood of success, not necessarily the area of biggest spending.

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Evaluating Hadoop for Enterprise Big Data ETL

By Ajay Chandramouly, Aug 26, 2014

Like many leading IT organizations, my employer, Intel, has embraced the challenge of extracting business value from big data and turning the insights gained into a competitive advantage. Part of this challenge involves the process used to extract big data from multiple sources, then cleanse, format, and load it into a data warehouse for analysis, a process known as ETL (extract, transform, and load). But the conventional wisdom around ETL is shifting.

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Plan for Big Data Like It’s 2000

By Thomas H. Davenport, Aug 21, 2014

What kinds of activities and decisions should a company pursue as it wrestles with its big data strategy? I see two major decisions at first, and then several others that follow from them. I’ll use Monsanto as an example, since it is a company that is clearly moving from being a provider of seeds and herbicides to one that provides data and analytics-based products and services.

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Many organizations fall victim to what I’m about to discuss and a fundamental shift in how organizations think about and fund analytics is required to address it. Today, the systems used to facilitate analytics within most organizations are owned by IT, which means that IT owns the budget to purchase and maintain the systems

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Who Owns Your Data Exhaust?

By Thomas H. Davenport, Aug 07, 2014

More than twenty years ago, consultants Stan Davis and Bill Davidson, in the book 2020 Vision, argued that a company’s “information exhaust” (information byproducts gathered in the course of its normal business) could be used to “informationalize” a business (develop products and services based on information) and turbocharge its performance. Their primary examples of this phenomenon were information companies—Quotron, TV Guide, TRW, and the like. They did argue, however, that any company in any industry had the potential to be informationalized by its data exhaust.

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Analytic Relevance in the Healthcare Workforce

By Mark Dobeck, Jul 30, 2014

US colleges and universities must recognize their critical role in the local business ecosystem by not only understanding but anticipating the future needs and workforce skills that will be in-demand by the local business community. Business Analytics is acquiring an increasingly significant and strategic role in business, particularly in the healthcare field. Effective and accessible educational programs must subsequently be developed to teach and train the next generation of knowledge workers to be proficient in business analytics. Now is the time to evolve in order to develop an accurate and cross disciplinary analytics skillset profile for the healthcare industry.

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Dueling Schooling on Big Data and Analytics

By Thomas H. Davenport, Jul 22, 2014

There’s been a lot of discussion about the shortage of quantitative analysts and data scientists in this world, and many people wonder where they will all come from. Today I have good news and bad news for you. The good news is that there are a rapidly growing number of educational institutions that are offering courses, concentrations, and degree programs in analytics and big data.

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Is Big Data Good or Evil?

By Bill Franks, Jul 09, 2014

With all of the lawsuits working through the courts and all of the scary possibilities being discussed in the media, it has led some people to assume that big data is inherently evil. Once you believe that big data is evil, a natural response is to try and shut down the collection and analysis of big data to the maximum extent possible. While big data certainly has risks, it would be a classic case of throwing out the baby with the bathwater if the use of big data is shut down.

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The Analytics of Things

By Thomas H. Davenport, Jul 07, 2014

The press and blogosphere are full of references to “The Internet of Things” (TIoT) or even “The Internet of Everything.” It’s great to connect inanimate objects to the Internet, of course. But that’s only a first step in terms of doing something useful with all those connected devices. “The Analytics of Things” are just as important, if not more so.

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