Thursday

Thursday's Recap

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Key Takeaways
 

It’s a journey from ownership to stewardship.

“Data hawks and data doves” will always be with us, those who want to stringently control their data and those who believe that “data just want to be free.” Both approaches create difficulties when it comes time to pin down the provenance of “the truth” as represented by data. Shifting the conversation toward stewardship—on protecting the longevity, quality, and relevance of data—can cut through these divisions. Most institutions have a rich cultural history around their data, and data governance can challenge this history from every angle: political, technical, and organizational. Establishing data governance is a complex but necessary undertaking. It is likely to be multiyear project, even at smaller institutions.

IT should neither drive nor own analytics.

Analytics must be a shared responsibility across both the academic and administrative sides of the institution. This again implies the importance of high-level executive ownership of the analytics agenda. Inputs from both sides are required to achieve the holistic perspective needed to frame strategic questions. And key end users must agree on the goals of analytics projects, as they often understand the data and the likely consequences using it. If you expose bad data, you risk a loss of trust that can move your analytics initiatives a step backwards.

Training and communication are key elements of any enterprise analytics effort.

Considering the clarity of the “culture change” message throughout the Sprint, remarkably few polled participants reported that their institutions have a comprehensive communication and training program in place to help their campus community understand data governance. The University of Washington team has implemented an ongoing dialogue that is required with campus data custodians. Ongoing training, engagement, and communication are also essential aspects of rolling out new dashboards and other visualization tools. It helps to have a meta-analytics—analytics about analytics—that can help the analytics team understand and make decisions about the effectiveness and uptake of the analytical services it provides.

Analytics requires new skill sets.

The Arizona State University team highlighted another twist on the idea of reaching beyond IT to support analytics. Even within the technical support realm, IT cannot do analytics alone because IT professionals do not have the skills required to support deep analytical inquiry. Mathematicians, data modelers, and statisticians are required, all skills that are available on a major university campus.

 

Thursday's Activities

How is analytics used in the enterprise area? What kinds of data governance, policies, and infrastructure need to be in place to ensure effective institutional use of analytics?

Analytics requires team work and collaboration among different divisions. We’ve heard about academic initiatives this week, but analytics involves the entire campus community and impacts student affairs, institutional research, information technology, finance, and physical plant operations.
 

Analytics can help measure the health and wellness of the organization. It’s important to strategic planning and decision making. Analytics helps reveal trends, build models, and suggest strategies to optimize success. With analytics, problems can be anticipated and solved.
 

2:00–3:30 p.m. ET (UTC-4); convert to your time zone
 

Analytics for Enterprise Efficiency and Effectiveness
 

Archive of recorded webinar, presentation slides, and resources

Overview
In order to fully realize the benefits of analytics, attention must be paid to all aspects of the computing enterprise, from data quality and IT governance to change management and implementation. In this session, we will focus on exemplars along the input and output spectrum. Sara Gomez and Bill Yock will discuss the University of Washington's approach to data definition, data governance, and data management in a highly distributed environment. Next, Arizona State University’s Gordon Wishon and John Rome will present the ASU approach to ensuring the products of their data-mining activities are put in the hands of decision makers in useful and user-friendly data visualization forms.

Featuring
Sara Gomez, Associate Vice President for Information Management, University of Washington
Bill Yock, Director, Enterprise Information Services, University of Washington
Gordon Wishon, Chief Information Officer, Arizona State University
John Rome, Deputy CIO and Business Intelligence Strategist, Arizona State University
Leah Lommel, Assistant Vice President – Development, Arizona State University

Hosted by
Diana Oblinger, EDUCAUSE President and CEO
 

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