Using People Analytics to Plan a DEI Strategy 

Getting and using diversity data can be tricky. But here's how to do it right.

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Jul 3, 2023

Workforce analytics — to the trained eye — can provide incredible detail and accuracy when it comes to the story behind your company’s diversity, equity, and inclusion (DEI) approach. The power of the data rests in its quality, the analysis, and how it influences the choices you make.

Your DEI strategy can become exponentially more targeted and effective once you assess your workforce demographics and pursue greater inclusivity in a targeted fashion. But capturing and analyzing diversity data isn’t always straightforward. Even businesses with the best intentions may feel uncertain about how to best design and harness diversity metrics. Here are six steps to use your analytics to shape a DEI strategy that works.

1. Identify Key Recruitment Metrics

Take a holistic look at your business processes — activities like hiring, promotions and training — and consider how your workforce looks at all levels. Then think about what you want it to reflect. This helps companies pinpoint specific areas where diversity should be heightened.

Consider a typical hiring funnel, with all prospects at the top. Descending in size, the next segments of the funnel are expressions of interest, resume screening for qualified leads, phone screening, multiple rounds of interviews, and the job offer.

To better measure diverse hiring, employers can create metrics for each part of the funnel — from the talent pool down to the acceptance rate — by gender, race, age, intersectionality, and other inclusion factors.

At each stage of the funnel, an organization can assess the demographic makeup of candidates and see if certain patterns emerge and compare against internal or external benchmarks to see where a deeper dive may be needed. Similarly, businesses should analyze HR metrics like promotions, turnover, and headcount regularly with diversity in mind.

2. Define Diversity Broadly

Diversity expands beyond race, ethnicity, gender, and age. Companies should also consider measuring neurodiversity and disability status, veteran status, sexual orientation, and gender identity.

Businesses often gather gender information from ID and employment eligibility documents, but it’s important to provide avenues for employees to volunteer information about their identity — some might identify as transgender or gender nonconforming for example.

Delving into diversity’s many dimensions creates more robust data, sheds light on deficiencies and deepens employers’ understanding of their employees.

3. Assess Data With an Intersectional Lens

Just as diversity takes many forms, some employees occupy more than one underrepresented group — for instance, women who have ADHD or people of color who are transgender. Individuals with overlapping layers of diversity may face more significant organizational barriers.

Ignoring intersectionality is risky. Consider gender: It’s an important metric on its own, but you can see an even clearer picture of your workforce when you overlay other dimensions of diversity like race or ethnicity.

Imagine a company that achieves gender parity — cause for celebration, right? A closer look at the data might reveal that only 15% of those women are women of color. Failing to recognize that shortfall means missing out on opportunities to include more diverse perspectives and boost innovation within the business.

4. Provide Good Data and Easy Access

People often say that data doesn’t lie. That’s untrue. Good data doesn’t lie, but to be good it must have integrity.

Data integrity means information is accurate, consistent, complete, and secure across the company. Pursue data integrity by crafting a precise data collection and storage method, regularly and rigorously checking for errors and educating all employees involved with collection about the extreme importance of data integrity.

Data matters only if it accurately represents your workforce. (There’s also an ongoing discussion about the ethics of data; many of the tools people rely on to “reveal insights” can also perpetuate and reaffirm societal biases. Some artificial intelligence and machine-learning systems are rife with bias.)

Beyond ensuring data integrity, business leaders must also guarantee that those in charge of diversity metrics have access to raw data. Aggregated data has already gone through one filter and does not allow for detailed modeling and analysis. There should be clear policies and standard operating procedures for data access and management. DEI analysts lose time if they’re forced to navigate unclear or poorly managed networks to access needed information.

Finally, business leaders and advocates of DEI metrics must also guarantee that the data is used ethically, accurately, and in a secure manner.

5. Consider the Level of Data

Collect data consistently and consider the level of detail you need to understand how your processes are unfolding. For instance, a year can provide just one data point, but if you collect data monthly, that year can turn into 12 data points and give a closer look at potential seasonal trends. The more granular the level of detail, the more information businesses can lean on to make better DEI decisions.

Business intelligence platforms are great tools for capturing more dynamic views of data. BI software allows businesses to automate reporting, allowing more time for deeper analysis. Some platforms can help provide data dashboards that allow you to drill down into metrics yearly, quarterly, monthly or even weekly.

Normally, technical users or business specialists create dashboards for teams. But if your company has a self-service approach to business intelligence, anyone can create new visuals from data in the dashboards. This makes it easier to do data modeling and analysis, and to explore, collaborate, and share findings with peers.

6. Make Data Collection the Start of Your DEI Journey, Not the End

Creating a data dashboard isn’t crossing the finish line; it’s just the beginning. Companies should use diversity data to shape their DEI strategy in a way that will drive systemic change, craft key performance indicators, measure progress toward KPIs, and advance their core business objectives. As your workforce changes, your analytics must evolve, too.

Diversity metrics are not static; this is an iterative process that is part of the ongoing work of understanding your personnel and business processes and noticing disparities among groups. Don’t be surprised if you find your diversity metrics change as you continue to ask more questions and probe into different levels within your organization’s diversity metrics. It takes time and effort to probe your business’s nuances.

Ultimately, to really move the needle on DEI, we need to continue learning about our employees, communities, and histories. We must focus on changing actions, processes, and behaviors, along with hearts and minds. And the only way to ensure that your strategy is working is to measure widely, correctly, and often. When deployed thoughtfully, diversity metrics aid in promoting the dignity of work and help businesses reimagine it for the better.

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