Each agency in the Federal Government invests significant resources every year to complete diversity analysis to meet the requirements of Management Directive 715 (MD-715). Provided by the Equal Employment Opportunity Committee (EEOC), the guidance in MD-715 is designed to help agencies meet the equal employment opportunity requirements section 717 of Title VII of the Civil Rights Act of 1964.
These numbers are significantly below benchmarks set by the private sector where white males make up only 36.1% of the overall workforce. In federal agencies, that number is 66.4%. For federal HR specialists attempting to identify the reasons for this disparity, there are several challenges. Limitations in technology, resources, and time often mean only surface level reporting and analysis – not nearly enough to uncover deeper rooted barriers in the data. To address this, agencies need a better set of processes to more fully understand why the needle isn’t moving and what actions they can take to ensure future progress.
Diving Deeper into the Data
While every agency prepares and delivers annual MD-715 reporting, that doesn’t mean they have the time or tools needed to dive as deep into the data as they could to uncover key triggers that lead to diversity barriers.
Often only the most immediately visible barriers are identified. In many cases, perceived barriers may only be part of a greater problem that remains hidden beneath the surface. Without a comprehensive picture, it’s difficult for agencies to make impactful changes that influence the results in the future.
Identifying a Larger Pool of Triggers
One of the challenges faced by federal EEO specialist is the sheer number of possible influences on a perceived barrier. Many times, incongruities can be attributed to seemingly unrelated factors, like geography, hiring pool size, census data and experience levels. At the same time, actual issues might be buried due to the lack of context.
For example, if a small agency office in Alaska has 100 employees, 68 of which are white males, a barrier might be perceived. However, there are several factors that could cause this to be the case. Location is one factor – Alaska’s demographics are different than California or Texas. The hiring pool here is likely also different than other agencies that can draw from across state lines, and there are the positions within that agency. Using census data, specialists can evaluate the likely demographics of specific positions based on degree type, experience, and location.
If the applicant pool is homogenous to start, it creates a natural barrier to diversity in those roles. At this stage, agencies need to look at why the hiring pool isn’t diverse, and what recruiting changes they can make to influence these numbers.
This type of context is crucial in understanding how to have an impact on the MD-715 reporting in future years. But without the right tools, it’s difficult to successfully identify and evaluate these and other more complex triggers.
How Technology Supports and Improves Barrier Analysis
Technology provides the horsepower needed to dive deeper into the data and evaluate significantly more potential triggers than would be possible through manual analysis. Using an algorithm that is designed to identify the impact of individual factors on dozens of key points in the recruiting, hiring, and training processes, technology tools can support comprehensive barrier analysis.
Instead of surface level triggers, agencies can identify thousands of potential triggers and their impact throughout the hiring and performance cycle. This means better understanding the influence of factors in the applicant pool, hiring process, resume evaluation process, interview and hiring staff, performance management process, and internal recruiting and promotions.
These same tools can help reduce the time spent completing MD-715 tables, shifting from data gathering to analysis. The result is a more impactful analysis of this data every year, and a greater impact on the diversity and inclusion initiatives within an agency.
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