A Good Analytics Strategy includes a Chief Data Officer
Health care organizations with ambitious plans for data analytics would be well served to create a chief data officer, reporting to the highest level in the organization.
Health care organizations with ambitious plans for data analytics would be well served to create a chief data officer, reporting to the highest level in the organization, says Peter Aiken, founder of Data Blueprint, a Glen Allen, Va.-based consultancy.
A chief data officer should have clout, reporting into the same level as a CFO, CMO or Chief Risk Officer--generally to the President, COO or CEO, adds Aiken, also an associate professor of information systems at Virginia Commonwealth University. The need and value of a chief data officer is one of several steps to a successful enterprise analytics strategy that Aiken will cover during a three-hour Healthcare Analytics 101 Workshop at Health Data Management’s Healthcare Analytics Symposium & Expo, July 15-17 in Chicago.
Any organization embracing analytics needs to know what its various parts are doing and prioritize the initiatives, Aiken counsels. He recalls one organization that had 12 separate business intelligence initiatives and thought each one was enterprise-level. In health care, the knowledge, skills and abilities for saving money are very different from those same characteristics necessary for improving care and outcomes, but a single person may oversee both projects and not have the skillsets to do it well.
Recognizing that all data analytics are not alike and the need to prioritize them are early steps to take and are part of a “crawl, walk, then run” strategy that Aiken will lay out during the workshop. And overseeing the strategy should be a chief data officer dedicated 100 percent to analytics, not a CIO who has so much more on his or her plate, he asserts. “CIOs do everything; if we ask them to do more with data, it’s a zero-sum game and something else loses.” Besides, analytics simply doesn’t belong in the I.T. department, Aiken says. “You don’t want data thought of as a project. Data persists, but not an I.T. project. We measure data success in years and I.T. achievements in quarters.”
Other issues pertinent to an analytics strategy that Aiken will explore include understanding the organization’s maturity and capability to adopt analytics, achieving balance between the technology and the human capability to understand it, and implementing useful I.T. systems development practices. More information on the Analytics 101 workshop and the symposium is available here.
A chief data officer should have clout, reporting into the same level as a CFO, CMO or Chief Risk Officer--generally to the President, COO or CEO, adds Aiken, also an associate professor of information systems at Virginia Commonwealth University. The need and value of a chief data officer is one of several steps to a successful enterprise analytics strategy that Aiken will cover during a three-hour Healthcare Analytics 101 Workshop at Health Data Management’s Healthcare Analytics Symposium & Expo, July 15-17 in Chicago.
Any organization embracing analytics needs to know what its various parts are doing and prioritize the initiatives, Aiken counsels. He recalls one organization that had 12 separate business intelligence initiatives and thought each one was enterprise-level. In health care, the knowledge, skills and abilities for saving money are very different from those same characteristics necessary for improving care and outcomes, but a single person may oversee both projects and not have the skillsets to do it well.
Recognizing that all data analytics are not alike and the need to prioritize them are early steps to take and are part of a “crawl, walk, then run” strategy that Aiken will lay out during the workshop. And overseeing the strategy should be a chief data officer dedicated 100 percent to analytics, not a CIO who has so much more on his or her plate, he asserts. “CIOs do everything; if we ask them to do more with data, it’s a zero-sum game and something else loses.” Besides, analytics simply doesn’t belong in the I.T. department, Aiken says. “You don’t want data thought of as a project. Data persists, but not an I.T. project. We measure data success in years and I.T. achievements in quarters.”
Other issues pertinent to an analytics strategy that Aiken will explore include understanding the organization’s maturity and capability to adopt analytics, achieving balance between the technology and the human capability to understand it, and implementing useful I.T. systems development practices. More information on the Analytics 101 workshop and the symposium is available here.
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