Unlock the Power of DEI Technology: Better Buy-In

Written by Ian Ehninger, Explorance.

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Synopsis: Our second blog in a series examining the use of the latest technological solutions to facilitate the work of DEI leaders, this post focuses on how to use these solutions to attain one of the most elusive elements of an overall DEI strategy – collective buy-in. Read our earlier blog posts here.  

Between 2015 and 2020, the number of people with the title “Head of Diversity” grew 107%, according to LinkedIn data. In a best-case scenario, every person in this role is equipped with the authority and tools they need to foster an entire workforce of DEI champions. In reality, the average turnover for a Head of Diversity, or CDO, is just three years.

Chief among the challenges of making desired change is getting full-throated buy-in from throughout the organization. This challenge stems from a combination of factors that emerge without the right technological tools. When the role of CDO isn’t afforded the appropriate stature, when DEI problems are unclear, or if there’s no pathway for accountability, the struggle for buy-in never ends.

The ideal scenario is possible. Whether having transitioned from program management or C-suite, the gravity of the responsibilities leads most DEI leaders to take on the CDO mindset. With that mindset, here are ways to get buy-in, and the participation and investment needed to make a real difference.

Enhance the Role

The best employee engagement technology provides tangible ways to elevate the CDO role from an honorary one to one that has a seat at the strategic table. Natural language processing of open-ended comments helps the CDO evaluate the effectiveness of quantitative information now being used to make decisions that impact DEI. Are the right questions being asked? Do existing evaluation tools need to be updated based on trends in employees’ unscripted comments?

Sophisticated technology can help you be the person who answers those questions. BlueML is a unique text analytics solution designed for employee experience. It analyses open-ended comments to reveal meaningful insights such as the true meaning beyond positive or negative sentiment, and recommendations employees are hoping you will act upon.

For new DEI initiatives, diversity managers might have to create the company’s first engagement tool. In that case, using BlueML to get a clear understanding of what employees think, feel, and recommend can guide the creation of that tool.

For more mature programs, BlueML is a linchpin for gathering data from the entire tech stack. Either way, you quickly come away with data-backed insights for strategic-level conversations.

Turn Feelings into Data

Clarity is of the utmost importance for buy-in, but difficult to attain when highly sensitive and often emotional DEI issues are on the table. People’s true feelings can be difficult to capture. But, when emotions are quantified with advanced machine learning technology, they become insights that everyone can respond to in a meaningful way.

They also become the basis for benchmarks that were previously too nebulous to set. For instance, quantitative questions will never be able to capture nuances of whether employees are feeling well, included, fatigued, or close to burnout. These are revealed not just by what the employee says, but how they say it. And you can avoid survey fatigue by asking one open-ended question every so often rather than throughout an entire survey.

With BlueML, your organization will be able to track emotional comments across various channels, such as exit surveys, Glassdoor, and Indeed reviews. Only machine learning trained specifically for DEI can turn these sentiments into actionable, quantitative insights. Run massive data sets quarterly monthly, or whenever makes the most sense for you.

Single Player to Team Sport

Too often, DEI is seen as a one-person job. The diversity leader’s goal is to show that the responsibility for fostering DEI rests throughout the organization, starting from the top. The CDO is the driver, but every manager is responsible.

First, ML data analysis can drive leadership accountability by pointing to measurements and activities that are unequivocally meaningful. Company leaders are more likely to support DEI efforts when they fully understand needed resources and investments. Armed with data, diversity managers can justify budgets and hold accountable those making budgetary decisions.

Employee-generated insights can also be used to educate the entire organization about existing challenges. From there, you can develop and empower ambassadors who help implement solutions day-to-day. Truly useful insights will also delineate how to strengthen Employee Resource Groups. At the same time, these insights can help when recommending comprehensive measures that show DEI impacts do not exist in a silo.

Finally, imagine the velocity of an organization with 100 managers armed with actionable insights. The easiest way to globalize DEI activity is to distribute actionable insights to all teams. In this way, you can quickly show or prove the value of action plans while enabling consistency and accountability.

Build Trust

Establishing high levels of trust is critical to getting buy-in. Reviewers want to trust the data they see. Employees want to trust that what they share is received accurately and is valued. Leadership needs to trust that DEI will have its intended impacts. Because BlueML vastly reduces bias in data analysis, it sits at the nexus of trust-building for DEI leaders.

BlueML allows a closed loop where people can see nearly immediate action in response to their comments. And it ensures that results don’t depend on who performs the analysis.

For instance, human nature can lead advocates of a program to read employee comments about it as more positive. On the other hand, somebody who wants to defund the program might privilege negative comments or those that show it’s not working.

The biggest buy-in challenge might have less to do with trust or confusion than with the fact that new ideas can be disruptive. In an organization where DEI measurement already exists, people worry about the impact of changing the measurement instrument. But those same people are often struggling to understand how to meet existing goals. In that case, BlueML can be used to measure for performance or improvement against existing benchmarks, enhancing the established measurement system.

Using comment analysis as another line of evidence alongside qualitative data lets you feel confident you are “fighting the right battles.” If needed, Explorance’s Consulting Services Team can help identify those potential courses of action the data reveal. With bias diminished, leaders, and everyone on the team, can trust in highly objective data, and the actions that stem from it.

Arrive Ready

Fast, in-depth data analysis helps overcome a major challenge for many diversity leaders: a background outside HR or DEI. Among CDOs at S&P 500 companies, 33% have experience in organizational development/learning and development; 31% in marketing/sales; 30% in talent acquisition; 25% in corporate social responsibility; and 16% in legal/compliance. 1

DEI leaders tapped from outside traditional talent pools can nonetheless derive immediate insights with BlueML comment analysis. Even without a team, a single person can analyze data to assess current DEI needs from the first day on the job. And they will be equipped with data-backed recommendations to respond rapidly to emerging problems. Armed with BlueML, a diversity manager from any background becomes a CDO: Confident on Day One.

Given the many challenges to buy-in DEI leaders must overcome, the high turnover rate in the role is understandable. But Blue ML helps address newness and marginalization of DEI roles, sensitive subject matter, and lack of trust and accountability. Armed with a tool purpose-built for DEI, leaders are better able to avoid stumbling blocks on the road to long term success and impact.


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