Our Diverse Representation Framework (DRF) represents how we are redefining, rethinking, and resetting our approach to driving full-spectrum diversity in response to today’s changing talent landscape.

• Our goal is to drive exponential growth in diverse representation starting with innovative, data-driven solutions to transform our understanding of the internal and external talent market across job family, geography, and tenure.

• We developed DRF to provide data and insights that enable hiring managers and leaders to assess the talent pool in the markets where they do business and to use that information to identify, hire, retain, and promote diverse talent within the company. This approach will allow us to shift our talent strategy to create new pipelines of diverse talent.
• The numbers don’t really tell the whole story when it comes to diverse representation. With DRF, we’ve changed our approach to finding talent by developing a new framework of powerful analytics with data-driven insights to help us explore the factors behind the numbers. And we’re developing leadership tools and piloting applications that bring the data and insights to our leaders to support real-time decision making. 
• We introduced Diverse InterviewER Panels (DIPs) to ensure we represent diversity when we interview prospective new hires for opportunities across every function and region in our company.

• With DRF in its early stages, we believe that true business intelligence and insight have been the missing links in our ability to have the diverse mix of people across our company mirror the markets where we do business. With new insight, we can take powerful new actions, transform the way we make decisions around diverse talent, and drive exponential growth.
• With DIPs this year, we’ve made significant strides in attracting and interviewing more diverse candidates, including a 14% increase globally in the number of women candidates interviewed. Our research tells us that DIPs improve the likelihood of hiring African-American/Black candidates by as much as 70 percent and Hispanic/Latino and women candidates by 50 percent.