In 2021, we partnered with Chisa Miller, a dynamic diversity, equity, and inclusion consultant and educator, who was instrumental in helping us build foundational training programs and internal processes to eliminate conscious and unconscious bias.
In June, we held a workshop called Awareness and Courageous Conversations aimed at understanding and addressing implicit bias. Chisa engaged our corporate team in thought-provoking exercises and discussions to understand our own implicit biases and gave us strategies for embracing our differences and engaging in meaningful conversations at work. The deep and meaningful discussion amongst our team members taught us that we all are a product of our environment and we all have biases—our ultimate goal is to get out of our comfort zone and to choose to see people and their belief systems through a new lens.
At our annual All Hands Meeting in October, Chisa spoke to our corporate and attorney teams about the importance of cultivating a work culture where employees are connected and see each other at a human level. We engaged in small group discussions on the consequences of allowing employees to be invisible and what that means specifically for contract attorneys. We built a renewed understanding of the choice we make each day of truly seeing others and bringing them into existence. As noted by our attorney team member, Doug Antoon, “Chisa is calling us to a higher level of heartfelt thinking—reminding us to be better.”
To further our understanding of how to have difficult conversations in the workplace, our corporate team read We Can’t Talk About That At Work! by Mary-Frances Winter, as part of our ongoing DE&I Council Book Club.
In 2021 we also focused on restructuring our internal recruiting and hiring process to minimize bias. We conducted several training sessions for our corporate team and leveraged our learnings to redesign how we screen and vet new candidates. Key changes include predetermined interview panels, consistency in questions and process, and debriefs designed to minimize affinity bias.