Название | Diversity and Inclusion Matters |
---|---|
Автор произведения | Jason R. Thompson |
Жанр | Зарубежная деловая литература |
Серия | |
Издательство | Зарубежная деловая литература |
Год выпуска | 0 |
isbn | 9781119799542 |
The biggest reason surveys are not helpful is that they are based on majority rule and that by definition is biased against underrepresented groups.
What company will change their approach or their culture based on a small percentage of responses? Nobody does that. But if you think about it, you can have several departments that have one Person of Color or one woman, and if nine people love whatever policy you are polling, and one person hates it, you won't change it because it looks like 90% of people like it.
If you have four People of Color and all of them say they hate the policy or are unhappy with the manager based on that person's behavior toward them, but the other six people are happy, you still have 60% of satisfied workers. There is also the question of trust. If you are the only African American in a department and you are treated poorly, you know it would be a risk to put that in an anonymous survey. If you don't trust your manager or leadership team, you won't be honest on a survey because any negative response will be attributed to you. No one will give honest answers if they feel their direct manager will know who gave them critical scores.
If the interpretation of the survey is always based on majority rule, when you have a few People of Color, or other marginalized groups, their voice through the survey is fundamentally minimized. To overcome bias, what most companies do is try to protect the anonymity of the respondents by taking extraordinary measures. So, let's look at the same example: We have ten employees. One person says they don't like the policy you are polling, that gives you one out of ten. That's 10%. But you can't use that data or share it with the leadership team because they would immediately know the respondent in question was a Person of Color, LGBTQ+, and so on. So, what do you do? One strategy many companies use is to combine their responses with another department, a larger department. So, let's combine, for example, marketing with accounting. Therefore, it helps keep the results anonymous. Seems like that would work, right? Wrong. The problem is, if you put them in with accounting, which has twenty employees including three People of Color who are all happy with the policy, you have the same problem. You've just taken somebody who was 10% of a group, put them in a larger group, and now their vote is only 3%. It's actually decreased in importance. You have less reason to do any actionable things, because, guess what, nobody makes changes in policy or procedures or work culture, if you have 97% approval. There's no reason to change, and the only way this process of combining departments works is if all the members of the underrepresented group have the same opinion or response in the survey.
Not only that, you've now confused the data because you put the one Person of Color in another department. So how do you know which manager to deal with? You don't, because you keep combining department results into bigger and bigger datasets. This makes it hard to train the right person because you've promised everybody that the survey is anonymous. Therefore, efforts to keep surveys anonymous make the responses from underrepresented employees less statistically significant. The minute you show up and say, People of Color are not happy, and there's only one Person of Color, everybody knows who it is. The only way you can address their concerns using surveys is to violate any promise of anonymity.
All three of these issues make survey data difficult to act on. Generally, if you say, “The survey shows that there's a problem in the accounting department,” the accounting manager's response will typically be: What is the issue? Who has a problem? Can I see the surveys? By and large, you can't answer those questions or share the surveys, so it makes it very difficult for you to effectively execute on initiatives related to survey responses. Additionally, the leader of the accounting department could rightly point out that 90% their department is happy. Once you share specifics about the 10% who are unhappy, any leader will quickly figure out who those people are, meaning the survey is no longer anonymous.
For these reasons, it is important to understand how surveys can actually work and why many times they can undermine your efforts. Employees often feel particularly frustrated by surveys. They think, I tell you every year what's wrong, and you do nothing about it. The reason you cannot do anything about it is because surveys are anonymous, which makes it difficult for you to present a real picture of the problem. This is why I don't recommend using surveys, because small groups of people will never have their concerns validated or changes made in order to improve employer/employee relations.
More Effective Retention Efforts
Instead of surveys, I would recommend you do some other things. First, look at retention statistics for each department. This is specific data. Do you see high turnover? Unfortunately, much of this data reflects what has already happened, but at least it gives you a data point that you can use. High turnover can be addressed by working with the leader who's creating the problem. There's no need to train everybody and hope the managers who are hurting retention get it.
Quite frankly, most people don't know where to start with a DE&I program, and that can be very detrimental to the overall success of the program. If you are working with qualitative data, you would most likely start your diversity program by sourcing an outside program and applying it, regardless of the fit. On the surface, it looks like you're doing something, but it's not effective. That's why the type of data you collect is crucial. You need to see the whole story as it relates to your particular company. You need to understand how your company is doing in terms of recruiting and retaining a diversity of candidates in real time. In the next chapter, I will share with you what data to collect, where to get it, and what specifically to look for once you have it.
The other half of this framework is retention. In the simplest terms, this is inclusion. Ask yourself four questions about the employees of your company:
1 Who stays?
2 How long do they stay?
3 Do they get promoted? (And, how long does it take to get promoted?)
4 What are you doing to keep them?
The first three questions are answered with the CAPE process, which I will cover in Chapters 3 through 7.
The fourth question; What are you doing to keep them? Is the work you do to develop employee resource groups (ERGs), DE&I training, workshops, and professional development. (I'll cover these in Part II.) Professional development doesn't mean preparing People of Color and women for leadership positions. If this was your first thought, please check your bias now. One of the assumptions that limits opportunities for women and People of Color is that they are unprepared and/or need preparation. Professional development includes the unconscious bias training that all leaders should participate in to reduce bias in the hiring and promotion process.
KEY POINTS
To change the culture of the organization, you need a shared language and understanding of where the company is going.
Diversity is about reflecting the mixture of differences and similarities that we find in the world and acknowledging the related tension as we strive to develop more inclusive and high-performing environments.
Equity is the principle of creating full access and removing barriers to participation. Equity is fair treatment, access, opportunity, and advancement for all people, while at the same time striving to identify and eliminate barriers that prevent the full participation of some groups.
Inclusion is about making people feel welcomed and valued. Inclusion is retention.
The best way to get organizational change and create an inclusive environment is to use organizational change models and principles, such as the ADKAR model.
Notes