DEI Data Introduction
Conventional wisdom states that every successful DEI strategy starts with data. Because using data makes the difference between an effective diversity and inclusion initiative and a tick-the-box exercise.
Data helps you establish benchmarks, identify gaps, set goals, measure your progress, and stay accountable. It can also help you identify signs and signals of issues your employees have before they become full blown problems.
But in our information rich world, it can be hard to separate signals from noise. It can be hard to tell which data to track and how to track it. We’re in a cultural moment where we’re rich in fads but poor in discernment.
The sense of urgency, the ‘bandwagon effect’, being swayed by what others are doing, and the overwhelming number of tactics, opinions, and options to choose from can lead us to use heuristics, or mental shortcuts, to sort through the clutter.
In particular, we often rely on the availability heuristic: the tendency to use information that comes to mind quickly and easily when making decisions about the future.
We reach for the most well-known or most-talked-about approaches. We grab for tactics before defining the problem we’re trying to solve. We over-index on the loudest or most visible symptoms, without investigating their root causes.
This approach leads to less-than-successful outcomes.
So while using data is critical, it is not a panacea. In fact, if you haven’t defined the why, the what, and the where of using data, you won’t be any better off than if you had not started with data in the first place.
Let me give an example.
A North American financial services consulting company I worked with had several problems: out of 14 partners, only one was female, none were ethnic minorities, and overall they had just less than 2% Black employees.
And strikingly—though not surprisingly—there was a higher than normal turnover among those Black employees, and higher than normal rates of Black employees put on PIPs – performance improvement plans.
The Director of HR, supported by the CEO and managing partners, called in a DEI consultant who surveyed female and minority employees and conducted exit interviews with ex-employees.
Based on the data, the consultant recommended several initiatives, but first and foremost to focus on creating ERGs and a mentorship program for female and Black employees.
Though this was greeted enthusiastically by the employees, a year into the program, the data showed no significant change of turnover and PIPs, and no change in representation in the partner group.
Looking again at the data and the suggestions from the consultant, they saw that the extremely low numbers of Black employees, in particular, led to a sense of isolation and exclusion, which exit interviews confirmed.
They acknowledged that their recruitment strategies were an issue and decided to proactively overhaul their approach to begin reaching out to a more diverse pool of applicants.
While this increased the absolute number of female and Black employees, the rate of turnover and PIPs didn’t change, and promotions continued to lag.
They were now 2 years into the process. Frustrated to see such negligible results, they brought in another DEI consultant who did more research and identified the key role that management played in supporting underrepresented employees.
To address the ongoing problem, HR, together with the consultant, created an obligatory inclusive management training for entry and mid-level managers.
9 months later, they looked at the data, and saw a 4% increase in the number of Black employees, a 2% reduction in turnover, a slight increase in female partners (1 more female on the board), and no reduction in PIPs for Black employees.
This lack of progress in DEI initiatives is not uncommon. And, they were also guided, every step of the way, by data:
- The number of female and racial and ethnic minorities were carefully tracked
- Exit interviews were conducted
- Annual engagement surveys and inclusion surveys were used
Root Cause vs. Symptom
They had identified some significant problems, and had attempted to address each one. But they hadn’t yet discovered the root cause or causes.
You could say they went from symptom to tactic too quickly, leaving out a deeper root cause analysis.
The root cause is the syndrome underneath the symptom at the surface.
The root cause gives you incontrovertible evidence of the underlying issues. And by focusing on root causes, you are deploying your resources in the most cost efficient way possible because root causes are leverage points.
There are usually one or two root causes that create multiple symptoms at the surface. And attacking the surface symptoms with individual tactics alone is not only expensive but can also be confusing for employees, as tactics are often unrelated and sometimes conflicting, ultimately failing to improve metrics as we saw above.
But when you get to the root cause, and focus your strategy on that, you can more effectively and successfully address the many surface symptoms in a more cost- and time-efficient way.
Once you have discovered the root cause of the problem you can then more fully understand what it is, where it stems from, and ultimately how to fix it. To find the root cause, you need to use data. But data won’t help unless you first understand the Why, What, and Where of Data to help you explore the root cause.
The Why, What and Where of Data
As we saw in our examples, data is important. But what’s equally important is knowing why you’re using the data and what you’re looking for. Are you:
- Taking stock of the state of the organization?
- Identifying signals of symptoms?
- Creating a baseline to measure results?
- Identifying root causes for symptoms already identified?
- Measuring results?
If you want to use metrics and measurements, first you must ask why.
Why are you using data? What is your purpose?
Are you assessing the state of the culture? If so, what are you measuring: engagement, sense of inclusion, number of racial and ethnic minorities? And why?
Are you using data to quantify employee satisfaction? To find root causes of already-identified symptoms? To set a benchmark to measure progress? To measure progress against your benchmark?
What are you measuring?
Does what you are measuring align with your why? Are your instruments and what they measure also in alignment with your why?
For example, if you want to identify whether there are symptoms that need addressing, an engagement survey is unlikely to help.
And yet many companies use them for their inclusion efforts. Engagement surveys are important, showing the percentage of people in the company who are engaged. This might point to early signs and signals on inclusion and marginalization.
But the engagement survey is like taking a temperature at the doctor’s office. It tells you something is wrong but doesn’t tell you what. You know your body is fighting an infection but you don’t know what the infection is or where it’s located.
Other companies use an inclusion survey to assess to what degree employees feel included. Many of these surveys identify employee perception and experience, which identifies the symptoms to tackle. But they may not surface the root causes of those symptoms.
What behaviors or practices create a sense of exclusion for racialized employees? What is the root cause behind women lagging at higher levels of management?
And what about where?
Finally, many surveys over-index along demographic lines like race, ethnicity, gender and sexual orientation. Obviously this is critical for diversity and inclusion efforts, but you may be overlooking other employee groups that can be useful for getting to the root cause.
Where do problems occur more than they do elsewhere? In what employee levels? What departments? At what level of tenure? What about age and generational groups?
The fact is, employees have more in common with each other based on their level in an organization than they do based on their race. We know this because of decades of research on inter-rater reliability of 360s.
Without carefully thinking about the “where,” your DEI initiatives may make the assumption that all Black employees, or all women, regardless of level, department, and tenure, may be having the same experience.
The benefit of looking at levels as well as demographics is that you might uncover critical differences within the organization, and even stumble upon a root cause.
Looking at tenure, levels, and department can reveal an interesting set of facts, which can ultimately lead to initiatives that produce better results.
In the example given at the beginning of the article, high turnover at the entry level was identified as a major problem, especially for racialized employees. What was interesting though, was looking at the problem through the lens of employee levels.
Entry level employees rated opportunities for development and advancement as low. But their managers rated it even lower. And this was after the inclusive management training program was created.
Even though these first level managers were given training on how to empower their reports, the entry level employees, they themselves didn’t feel empowered or supported.
Their managers, their bosses were not supporting their development. The inclusive leadership skills they were being taught were not reinforced or supported by their managers.
The managing partners were so focused on business development and client work that they paid scant attention to developing their teams and direct reports.
Creating a diverse, inclusive, and equitable organization is a top priority. But making sure your strategies are effective should be a top priority as well. DEI is far too important to risk failure by taking short cuts: reaching for popular tactics, not defining the problem you’re trying to solve, and solving symptoms without finding their root cause.
Diagnosing root causes requires some deeper digging into the data, but before you do, it’s critical to establish the why, what, and especially the where of your inquiry.
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