Unlike two decades ago, when diversity efforts were often part-time and data was scarce, DEIB programs today align around robust data from sophisticated people analytics capabilities. Today, cloud-based, real-time tools driven by data dashboards give HR leaders, senior management, and business managers the ability to accurately track DEIB statistics. These diversity dashboards and scorecards provide real-time data on businesses’ DEIB progress, pushing leaders to take direct, timely action to create a more diverse workplace.
While this approach demonstrates progress, Willburn pointed out that it also introduces a challenge by expecting statistics-minded analytics leaders to partner with less quantitatively inclined DEIB leaders to create diversity goals and accountability plans. This can lead to siloed, disconnected DEIB planning that misallocates resources and fails to support an organization’s overall objectives.
To combat this and create true alignment that leads to real change, DEIB and people analytics leaders need to agree on a definition for “inclusion.” As Garr explained, defining and measuring inclusion—with both perception data about an employee’s feelings and objective data about their actual levels of inclusion—is critical to help companies understand their three Ps: their people and whether they feel valued; their process, including the identification and overhaul of biased systems and policies; and their predictions, or determining factors such as shifting hiring rates that will lead to changes in diversity data.
The Eight-Step DEIB Analytics Journey
Next, Garr shared the DEIB and people analytics executives need to tackle these eight steps to get started on their DEIB analytics journey.
1. Identify partners. DEIB and people analytics leaders need to build ongoing relationships with the chief human resources officer, senior HR business partners, legal and privacy teams, and IT teams. To form these partnerships, the DEIB and analytics teams need to understand partners’ needs and fears; identify partners’ current levels of data sophistication and education needs; clarify objectives and map them to partners’ needs; and set clear expectations of the partnership.
2. Get demographic data in order. DEIB and business partners need to align on data definitions, sources, and security protocols, as well as how to gather and continually update the data to prevent getting stuck in static spreadsheets. DEIB leaders should take the lead on determining strategy, while people analytics leaders should provide the relevant data, insights, and updates to inform and measure the strategy’s effectiveness.
3. Understand the problem and ideate data stories. People analytics leaders need to use their broad understanding of the drivers that spur retention, engagement, promotion, and productivity to bring context to DEIB concerns. By analyzing the data and the broader company context, leaders can determine and prioritize the issues that need to be addressed.
4. Identify additional necessary data. After understanding the problem, DEIB and people analytics leaders need to hypothesize the cause of the issue. After creating a hypothesis, they next need to determine the additional data necessary to test it.
5. Prioritize problems to solve. Many organizations have more problems to solve than resources to fix them, so prioritization is necessary. DEIB and people analytics leaders should consider these questions when determining priorities.
- To what extent is this problem aligned to the big-picture DEIB strategy and priorities?
- What will be the top-line or bottom-line impact?
- How many employees will it impact?
- Is this problem a recurring, long-term one or an acute need?
- What level of effort and resources will be required?
- Will we be able to yield actionable insights that can result in behavior change as a result of this analysis?
- Who is asking the question? (CEO, CFO, CHRO, and so on.)
6. Analyze and refine data stories. Engage a variety of people in the analysis to counteract bias and include as many perspectives as possible. Consider whether the right question is being answered and whether a different analysis method or data set might yield better insights.
7. Share and explore. Present the data story in a way that builds understanding and creates insight that results in action. To do so, DEIB and people analytics leaders need to:
- Clearly define the terms, data, and the different contexts used.
- Restate the DEIB question.
- Tell a story using data to make your points, underscoring the “what” and the “so what.”
- Identify areas where it may be appropriate to dig more and structure conversations with stakeholders on those areas.
8. Take action and hold stakeholders accountable. After sharing insights, the DEIB and people analytics teams must continue to define, track, and update metrics to work toward progress. Leaders should:
- Define, in consultation with stakeholders, metrics that will capture progress on the DEIB objective.
- Make metrics as transparent and accessible as possible to as many people and as often as possible.
- Ensure data is continuously updated— no Excel spreadsheets with static data.
- Leverage tech to identify insights that were missed or are too politically sensitive to surface.
- Build DEIB metrics into existing dashboards so they become part of how the business is managed.
Understand the Process Never Ends
As organizations everywhere embark on journeys to increase hiring and development of diverse talent and cultivate a culture of belonging, Workday’s analytics and measurement tools, including VIBE Index, can help.