Data Empowerment Through Design Thinking

We talk about data in a way that feels abstract.

Those of us who are data advocates, who want to help others become empowered to use data to improve student outcomes, need to focus on the experience of using data for decision-making by taking a more embodied approach.

Design thinking offers a human-centered approach to problem-solving. Design thinking includes a broad set of participatory tools, like stakeholder maps and empathy interviews. But the broad idea is for a team to follow these steps to develop innovative solutions that directly address the needs of the humans a program or product is designed for:

Step 1. Empathize (seek to understand the experience of the user)

Step 2. Ideate (come up with as many creative ideas as your team can think of, grounded in the experience of those that will use this product or program)

Step 3. Prototype & test (design a rough version of your team’s solution, which you then test and get feedback with the intention of exploring different solutions and refining over time)

Data is a tool in the design thinking process.

Data is embedded in this creative process, both in the “empathize” and the “prototype & test” steps. Central to design thinking is user data, which allows the design team to get close up and understand the needs of an individual user. Also important is larger scale data, which offers a different lens for seeing the far-away big picture of the experience of many users.

Here is an example. A group of educators at a regional college come together to create a new career counseling program for students. The college puts together a “design team,” which should be made up of people from different perspectives, in design thinking the creative solution lies in the team. This team invites a few individual students to share their career motivations, their process for gathering career information, and their work-based learning experiences. They also bring to the table outside research on career education approaches as well as data on high-quality career pathways in their local economy. The team will design a program, and then prototype and test it out, refining the experience based on user data rather than expecting that it will be perfect on the first try. Following the design thinking steps, the team can design a program that puts students in the center, which should lead to a better experience and better outcomes.

You can see how data is central to the creative idea-generation and decision-making process: user experience data, data from research, broader-scale quantitative data, and data from ongoing feedback loops.

Design thinking offers a process for engaging humans with data.

The principles behind being human centered when designing any program or product are the same principles behind data visualization. Data visualization techniques help turn raw data into clear, actionable insights, which makes it so real humans can use data for decision-making.

People (including myself) love to talk about data visualization. It’s one place where centering the user experience has successfully infiltrated the discussion around data, and the people-oriented way of thinking tends to blow the minds of my fellow data nerds.

But I believe that design thinking can improve other aspects of the experience of using data beyond data visualization. There is much work to be done to build a data culture across the organization and within individual teams. This is the work of changing the culture so that staff ask actionable questions and think to bring data into the meetings where decisions are being made. How does a team change their workflows to regularly introduce data with more intention?

Enter design thinking.

The design question behind my work is: How might we cultivate a data culture across higher education where staff feel empowered, equipped, and motivated to use relevant data to inform their everyday decisions?

You might adapt this question for your organization to ask: How might we design a data literacy program that is accessible, engaging, and directly addresses the needs of our diverse staff, fostering a culture of data-informed decision-making?

Here are some ideas for walking through the design thinking steps as you design a program (or maybe just some first steps) for data empowerment at your organization or institution.

Step 1. Empathize. Bring together a team and talk to some humans that use data at your institution or organization. Assume you can’t come up with any new ideas if you only exist in your own experience. Be open to surprise and therefore to creative solutions.

This might look like hosting a roundtable where staff from various units come together to discuss their comfort with data, awareness of currently available data, and pain points when incorporating data into their workflows.

Bring into the conversation whatever relevant data you might have, such as dashboard user metrics, to find out who is (and is not) using data. Identify key challenges and opportunities and clearly define the outcomes of the program you are creating.

Step 2.  Ideate. What are all the creative ideas your team could possibly think of around moving staff (and faculty, the board, students, etc.) from where they currently are with data literacy and data behavior to where you want them to be. Some creative ideas I have heard recently include:

·      A video series of “MythBusters” about data misconceptions

·      A data visualization challenge during “Love Data Week”

·      A data buddy system pairing data novices with experienced staff members for peer-to-peer learning and support

3. Prototype & test. Try some ideas out and gather feedback. Be biased towards action. Assume you won’t get it right the first time and plan to keep refining.

Data work is changing as technology advances. Most people in the work of creating social change now have access to data relevant to the decisions impacting their work. Many of these people do not (yet) have the skills needed to ask actionable questions and incorporate data into their decision-making. Data leaders in the future will be less focused on the technical tasks of cleaning and analyzing data and more focused on the human tasks of data buy-in, data literacy, data empowerment. I believe design thinking could be one of the most valuable skills to center the experience of real people using data as we usher in a new phase of data and analytics work in higher education.

What do you think? Have you used design thinking when creating data programs for the humans you serve? I’d love to hear more.

I’m so glad you’re here.

-Tait