Overcoming the Deficit Mindset

Too often the development of workforce development and training tools and resources starts and operates from a deficit mindset—an assumption that workers or jobseekers are unemployed or underemployed because they lack skills, knowledge, and motivation to help themselves. This does not take into account ineffective systems that fail to empower workers and jobseekers and ensure they gain the skills and support they need to access better career opportunities. Workforce development is seen as a service delivered to jobseekers rather than a process of working with jobseekers and communities to overcome structural inequities that throw up barriers to good jobs.

This mindset is so deeply embedded in our processes and systems that workers and jobseekers either often internalize these perceptions or so mistrust systems intended to meet their needs that they opt out of them altogether. When such a mindset infects assumptions that inform jobseeker tools, education, and training options, it further alienates marginalized workers from seeking solutions.

To counteract this line of thinking, experts designing workforce development and training solutions need to:

  • Engage workers and jobseekers to understand their needs, attitudes, and perceptions and design systems, tools, and services with these insights in mind.

  • Work with community-based organizations to better understand the needs of particular groups and communities and develop trusted partners to assist with outreach.

  • Assess their own assumptions, biases, and language/communications  to determine how they may skew the development of tools, training, and other resources.

  • Be willing to adapt and change based on the feedback of all stakeholders and challenge existing processes and systems that are not meeting the needs of those they are aiming to serve.

  D4AD Insight

During development, the Michigan D4AD team relied on feedback from case managers to ensure that the language used in the predictive elements of the tool did not suggest a predetermined pathway to workers and unintentionally replicate structural biases. Based on this feedback from caseworkers, and technical assistance from D4AD, the Michigan team worked intentionally to incorporate asset-based language to convey how the information is intended to build on the strengths and skills of workers and jobseekers.