Why Diversity Professionals Need Predictive and Other Analytics

There’s a fair amount of buzz around diversity measurement and analytics. Advances in software, newly available data sources and how-to manuals have made it easier gain access to diversity measures.

Although interest in measuring the effects of diversity has been growing, the topic still challenges even the most sophisticated and progressive diversity departments. Many diversity professionals and practitioners know they must begin to show how diversity is linked to the bottom line or they will have difficulty maintaining funding, gaining support and assessing progress.

Over the past several years, diversity journals abound with volumes of information about the effect of a diverse workforce. The journal information is primarily from a talent representation point of view, focusing on organizational makeup of race, rank and gender (counting heads). Many of these diversity professionals are working with inconsistent, basic information and have yet to move from being reactive to proactive and predictive. In short, they have made little progress along the data-to-information-to-wisdom continuum needed to provide sophisticated diverse workforce insights that are critical to strategic decision-making.

How would you respond to the following questions:

• Do you struggle with defining or measuring the success of diversity initiatives or other diversity interventions?
• Are you constantly fighting the battle to show and justify the value that diversity initiatives or other diversity interventions are bringing to your organization?
• Does your organization view diversity initiatives or other diversity interventions as an expense versus an investment with predicted returns?
• Do you need to link diversity initiatives or interventions with the value it produces for your company?
• Do you need a method of predicting (forecasting) the value of diversity initiatives or other diversity interventions to help decide whether to train and/or do something else?
• Are your current diversity evaluation efforts always after the fact — do you need a way to measure success using leading indicators that drive continuous improvement?

If you answered yes to any of these questions, then predictive analytics for diversity is for you.

For the past eight years, I have been researching and developing a predictive analytics for diversity approach and framework that addresses all of the above questions and more. My goal is to create the next-level of diversity ROI-based tools that give diversity professionals a competitive edge and alignment to drive business performance and results.

What Are Analytics?
Analytics come in different types with a specific focus. They can be defined as follows:

• Analytics: the science of analysis.
• Descriptive analytics: tells what has happened in the past and usually the cause of the outcome.
• Predictive analytics: focuses on the future, telling what is likely to happen given a stated approach.
• Prescriptive analytics: tells the best course of action.

Descriptive diversity analyticscan help us understand human capital challenges and opportunities in utilizing a diverse workforce. On the other hand, predictive diversity analytics helps us to identify investment value and a means to improve future outcomes from diversity interventions and initiatives.

Companies struggle with evaluating whether their programs meet business needs and if they are worthwhile investments. Reasons given for not measuring diversity’s effect on business outcomes include statements such as, “It is too difficult to isolate diversity’s impact on results vs. the impact of other factors,” or “Evaluation is not standardized enough to compare well across functions.”

Sound business practices dictate that diversity professionals collect data to judge progress toward meeting the organization’s strategies and annual multi-year objectives. The Hubbard Predictive Analytics Framework, for example, is an approach that provides data to executives, including:

• Predicting the success of diversity intervention in the three areas of intention, adoption and impact, and measuring to see if success has been achieved.
• Leading indicators of future adoption (transfer of the intervention outcomes) and impact (business results).
• Making recommendations for continuous improvement.
• Isolating diversity and inclusion’s impact versus the impact of other factors.

The beauty of predictive analytics for diversity is that it uses leading measures (intention and adoption) as a signal of results (impact). If the leading indicators are below predicted success thresholds, actions can be implemented to make adjustments so the desired results are realized.

You can interweave outcomes and leading indicators into diversity interventions during the design and delivery phases to enhance their predictive validity and consistency in achieving sustained benefits. Predictive analytics practices help diversity and inclusion organizations move from an event-driven function to one that predicts success, measure performance against those predictions, and seen as returning significant shareholder value for the funds invested.

All told, the predictive numbers certainly support the world’s current fascination with analytics — and suggest that focus will continue to intensify in the years to come. Are you on board? If so, you will find an informative body of knowledge and insights waiting for your use to drive strategic performance improvement and success for your organization.