Why analytics comes down to people
- Institutions must define analytics for its stakeholders, then engage them
- Engagement strategies center on end users, data designers, executives
- Analytics and institutional priorities/goals must align
Since joining St. Edward’s University, Chief Data Officer Justin M. Sloan has been overseeing implementation of a robust analytics programme. Ellucian Principal Consultant Dr. Henry DeVries spoke with Sloan about how shifting institutional culture matters as much as shifting technology.
DeVries: Why is it important to address the “people” side of analytics?
Sloan: You can put the best technology in place, but if you don’t tackle the people side, you won’t get anywhere.
When we decided as an institution to make a major investment in analytics, we first had to educate people about what that even meant from a practical and strategic standpoint. We had to manage expectations about the resources and participation success would require.
Then we had to make it clear what value each stakeholder would get out of supporting this initiative. Most end users don’t walk up to me and say, “I need more analytics.” But they do want information that will improve their ability to do their jobs. So we focused on that.
DeVries: Who are the main stakeholders you’re engaging?
Sloan: We tend to think about them in three groups—end users, data designers, and executives. Each group is in a different place, mentally and practically speaking, so the engagement strategies need to be different—and yet also aligned.
- With end users, it’s about demonstrating new ways to engage with information and the power of integrating data campus wide.
- With data designers, it’s about getting them to unhitch from their role as gatekeeper of all institutional data.
- With executives, it’s about rethinking the way they ask questions, and, perhaps more importantly, how they use the answers.
We also have to work across these three groups. We’re ensuring they understand each other, that their goals are aligned, and the silos are coming down.
DeVries: What are the tactics you’re using to engage these stakeholders?
Sloan: We’re at about the ten month mark of an 18-month initiative. The first few months were primarily about information sharing and level setting. We made sure everyone understood the landscape—what systems we had, what information each contained, which were connected and which were not, and what questions we could and could not answer. Painting a picture of our current state was a compeling way to gain consensus that change was necessary.
We evaluated our community to identify champions for this change across campus. We formed selection committees to evaluate new technology and held open forums to solicit input from students, faculty, and staff.
Now that we’ve selected new systems and developed an implementation plan, we’re about to begin a training and education process for end users. Training will include an introduction to new toolsets, our data governance plan, a common data glossary, and how to make a request for information or support. We’re trying to instill a new self-service mentality.
Q: What’s been the response to date?
Sloan: We’re well down the road, and there has been no panic, no one pulling the alarm. I attribute that to early and active engagement of all stakeholders.
People are motivated when they see the potential to improve student outcomes. Additionally, faculty and staff are realising the potential to gain new insights in order to invest limited resources more effectively.
Data designers are some of the most passionate advocates for redefining roles and processes, so that everyone is using data to make better decisions. They understand that by empowering end users to be self-sufficient, they can move the university further ahead in planning. Ultimately, the ideal would be to have about 70% of data available through self-service, with IT and IR handling the 30% that truly requires more sophisticated support. Right now it’s the other way around.
Q: How are institutional leaders embracing analytics?
Sloan: The university is in the process of developing a new strategic plan, and we’ve made it a priority to develop analytics that align.
The key performance indicators that come out of this plan will drive the way we structure dashboards and prioritize the collection of data. In the meantime, we’re working with university leaders on known priorities, such as enrollment and retention. We’re surveying current business needs and will layer in additional KPIs as we go.
We’ll know we’ve taken things to the next level when the institution is generating better data at a faster rate, and decision makers are spending the majority of their time prescribing actions and adjusting priorities based on that information.
Catch up on the series:
- How students expect institutions to use their data
- We have big data. It’s time for big insights.
- The cloud can transform your ability to use data - But you need some ground rules
If you have additional strategies or experiences to share around building an analytics-driven culture, please leave a Comment below.