Nurturing Data Culture at the Program-Level, the Intermediary-Level, and the College-Level

My work is to help higher education teams build their data culture-- meaning I coach teams through workshops or grantee cohorts to embed data into workflows in order to make better decisions. This newsletter is written for the program-level team, whether you lead a program at a non-profit or at a college. But I also support teams at other levels, namely the organization-level (aka the non-profit intermediary or philanthropy) or the college-level. Strategizing around building a data culture across an entire organization or entire college requires different tools, but some of the people-challenges are the same.

To build a data culture requires three components: a. Data, b. Technology, c. People. I argue that across all three levels the “people” part is the hardest part. Also, people are the whole point of why data is valuable. Who cares about your fancy dashboard if no one is using it? At each level, data is an asset that helps the team make better decisions so that they can get better at what they do.

To illustrate the different levels, I dug up a metaphor. Prepare thyself for a very punning post, inspired by spring in Capitol Hill (where I live).

Nurturing a data culture at the:

1.     Program-level is like a well-maintained vegetable garden.

2.     Organizational-level (at an intermediary or a philanthropy) is like a community garden.

3.     College-level is like planning out a complex botanical garden.

Why do the different levels of data culture matter?

The steps to build a data culture look different at different levels of complexity and infrastructure. And yet if we want to build a world where every person and every team contributes to data-informed decision-making, it matters how teams feel empowered to nurture their data culture.

Building a data culture at the institution-level involves decisions that are (ideally) grounded in a strategic plan, where leadership needs to think about large-scale technological infrastructure and change management steps across a complex organization.  At the program-level decisions are more about improving the implementation of their individual program to serve students better. We should care about data culture at all levels if we are to build data-empowerment across our field.

[Obviously there are other levels of data-culture as well – and increasingly I’ve been thinking about the state-wide data system and culture. If you work in another level, I’d love it if you’d message me and tell me how it fits or (more likely) how I have definitely taken this metaphor too far.]

Cultivating a data culture at a program-level is like tending to a well-maintained vegetable patch.

A well-maintained vegetable patch (or program-level team) are the sub-plots that make up either a community garden (non-profit organization) or a fancy botanical garden (college or university). These are the departments or student-success programs that serve students. As an outside “Data Culture Coach” (yes, I made this title up), I have coached teams of faculty implementing agricultural education programs at a university and teams of college advisors supporting high school students in the college application process -- both are examples of program-level teams that need data to improve.

Program-level teams must make a plan and figure out how to harvest data (did you see what I did there?) in ways that don’t take over their programmatic work. These teams need to hone the skills of asking actionable questions and answering them using relevant data (and not get distracted by everything one could explore).

If every program-level team is empowered to nurture their data culture, meaning using data in the everyday meetings where decisions are being made, together they build an organization-wide or institution-wide data culture.

Specific Seeds. A data culture offers a valuable tool for any program-level team, namely the ability to improve their program by tracking progress towards their outcomes and using data to make decisions for more informed design and implementation. The cultivators of a vegetable patch (program-level team) focus on specific seeds (i.e. targeted data) by narrowing in on their programmatic goals (what vegetables are we trying to grow).

• If the project is a youth mentorship program, data on attendance, student progress reports, and mentor feedback would be the specific "seeds" sown.

Maintain your Patch and Keep it Simple. The program-level team cares for their data culture by identifying a few key data sources and using the data at regular intervals in their program cycle. Likely getting access to the right data looks like asking actionable questions of institutional or publicly available data and/or by creating feedback loops with program participants through surveys or focus groups. Teams may collaborate with the institution’s IR or organizational-level MLE “specialists” to leverage more advanced tools, but on a daily basis they work with what they need without letting it take over their work of implementation.

Focus on Harvesting Actionable Insights. A program-level team is efficient with limited data-related resources. How might we focus on instead on harvesting data to inform project decisions, improve program delivery, and demonstrate the program's effectiveness?

Cultivating a data culture at an organization (such as a non-profit intermediary or philanthropy) is like planting a community garden.

Cross-Pollination. There needs to be ongoing collaboration around making sure the data speaks to each other from different sources in order to be actionable. If your organization is in the business of generating knowledge, there is work around knowledge management-- documenting what you are learning and regularly sharing it out.

Essential Tools. The complexity of the data and the technological needs are usually far more accessible than for the institution (as they were built for different purposes).  Yet, leaders at an intermediary organization must build centralized systems that the program-level teams can contribute to in ways that allow regular interactions with the data across programs.

Focus on Collective Yield. The ultimate goal for cultivating a data culture across the organization is less on precise program-level improvements and more on valuable insights relevant to the strategic direction of the organization. How might you improve program effectiveness across the organization? How will data contribute to organizational level strategy and decision-making? How are different programs contributing to the organization’s collective learning and outcomes? How will your data help to tell your organization’s story across different programs?

Cultivating a data culture at a college or university is like planning out a complex botanical garden.

It takes strategy to get staff and faculty across the enterprise to utilize data. It also takes substantial data expertise and technological infrastructure.

Colleges need data experts.

· The “highly trained horticulturists” (aka data and analytics professionals) analyze and interpret complex datasets, ensuring their accuracy and accessibility through reports and dashboards. These experts design and maintain the technological infrastructure that supports data storage, processing, and visualization.

·      The “experienced botanists” (aka data stewards) maintain quality and security according to data governance policies and procedures.

Colleges also utilize “advanced growing systems” (aka complex technological infrastructure) in order to maintain data storage, security, analysis and accessibility through visualization.

Colleges increasingly are investing in “educational greenhouses” (aka data literacy initiatives) to equip faculty and staff with the data literacy skills.

Focus on Mature Data Capabilities Across the Institution. Institutions have an immense responsibility to use data-informed decision-making to center the needs of vast numbers of students and offer as high-quality an experience to every student as possible. Obviously, the strategy for setting up a data culture structure is far more complex.

I argue that part of that strategy should be empowering program-level teams across the institution.

Let’s strategize data use across the institution or organization -- and also empower every program-level team to nurture their own data culture.

When I talk about building a data culture to institutional leaders, there are strategic, high-level action steps to be considered (e.g. write a data governance charter, create a data strategy roadmap – lots more to come soon through our www.changewithanalytics.com project).

This is a different vantage point than nurturing the data culture of a program-level team. The program team needs to narrow in on the actionable data relevant to their focused program-improvement goals. By empowering program-level teams at institutions and intermediary organizations we can aim to build a data culture from the ground up, where every team practices making data-informed decisions that improve the experiences of students across higher education.