MEREDITH LYON

LEVERAGING DALLAS COLLEGE’S LABOR MARKET INTELLIGENCE CENTER

Our team designed a multipart feedback system that allows the LMIC to evaluate their organizational successes through the analytics platform Power BI, a customer survey through Qualtrics to generate meaningful feedback, an auto-response email to redirect customers to their online request form, and dashboards to communicate their value through storytelling.

The design team consisted of Meredith Lyon, Michaela Koveak, Kyle Spencer & Kyle Dovak.

The Labor Market Intelligence Center (LMIC) is the leading source of regional workforce information for the Dallas College Network. The LMIC is focused on aligning class curriculums to Dallas's labor market so that students are getting the skills that they will need to get hired and succeed in the workforce.

The goals of the organization are to:

1). Identify opportunities and trends in high-growth, emerging and economically critical industries, and occupations, and

2). Estimate the gap between labor market demand, available training, and existing or future workers.

In addition to workforce demands, the LMIC analyzes social barriers that prevent students from continuing their education. By addressing student’s basic needs such as child care, food, and transportation, the LMIC hopes to help students focus on their courses so that they can be prepared to enter the workforce.

Research Question

For the purpose of this study, the crux of the research asks: “How might we (HMW) leverage the Labor Market Intelligence Center to create a sustainable impact in Dallas County?” Our HMW question frames our design challenge and sets the foundation for our design research.

Human-Centered Design

“Human-Centered Design offers problem solvers of any background a chance to design with communities, to deeply understand the people we’re looking to serve, to dream up scores of ideas, and to create innovative new solutions rooted in people’s actual needs” (IDEO 09). 

For this project, we structured our approach around the seven-circle process as shown above. While our process isn’t perfectly linear, our roadmap to creative problem solving has helped us explain how we tackled our design challenge and the solutions we designed:

Define: Address the problem at hand by analyzing our How Might We statement.

Understand: Identify patterns of behavior and pain points for the LMIC. This was completed through primary interviews and secondary research.

Redefine: Synthesize all the information we gathered to create insights and themes.

Imagine: Brainstorm as many ideas as we can based on what we learned from our observations and experiences.

Make: Make sense of information by creating multiple prototypes and receiving actionable feedback from the LMIC.

Test: Bring our design ideas to life by rapid prototyping and testing.

Tell: Finalize the potential design solution and tell how it will create sustainable impact for the LMIC.

Series of Prototypes and Learnings

Based on our findings, our team felt most strongly about creating a success metric system for the LMIC to measure organizational performance and impact. We also wanted to test a customer feedback survey so that the LMIC could hear directly from customers and gain testimonials on the data that they delivered to their clients.

To begin to expand on our success metric system, we extensively researched success metrics that would be important for the LMIC to measure their performance. Our team decided on these key metrics:

Our Design Solution

Our team designed a multipart feedback system that allows the LMIC to evaluate their organizational successes through the analytics platform Power BI, a customer survey through Qualtrics to generate meaningful feedback, an auto-response email to redirect customers to their online request form, and dashboards to communicate their value through storytelling. This new approach allows them to show and share their successes to prove their value to Dallas College, future customers, and themselves. By examining these metrics they will be able to assess their own shortcomings and improve the quality of their work, as well as the data that they provide.