Why does the employer want to gather data?
Why should I answer the survey?
The short answer is:
To help your employer create a workplace that provides equal opportunities for all employees.
The slightly longer answer is as follows:
Your employer wants to become better at providing equal opportunities for all employees.
To achieve this, your employer has to:
- Anchor the DEI commitment in the top management and overall strategy
- Perform in depth analysis to find out what the actual problem is in your workplace
- Implement the right solutions that actually have an effect.
Points 1 and 3 are things only the employer can do something about.
To Achieve point 2, the employer needs help from the employees. The employer can gather some data themselves, but the employer is not allowed to ask for personal data such as skin color, sexual orientation, disability level, and religion. At the same time, we know that these are important characteristics that affect how much unconscious bias employees face, which in turn affects whether all employees have equal opportunities.
By helping to answer questions about culture and representation, you are helping us tell your employer what is most important to address in your workplace to make the workplace even better at ensuring that all employees can use their full potential. That's what we call a win-win-win situation.
What distinguishes this survey from a regular employee survey?
This survey is different from regular employee surveys in several ways.
Employee safety:
We at Equality Check send out the survey, and we collect and analyze the raw data. This means that your employer does not see what you or your colleagues have answered; they only receive insights (visualized results) where no employees can be identified. In other words, you can be completely sure that your answers will not have any negative consequences, either because you have answered something that you think your employer does not like, or because you have chosen not to answer at all. Most employers treat employee data correctly and with respect, but we know that many employees are afraid that the data might be used against them. Therefore, we will never give your employers employee data.
Different type of data:
Because we at Equality Check are an independent third party, it means that we can collect data that employers cannot collect. This is what GDPR calls "special category" data, which includes for example, sexual orientation, skin color, religion, and functional level. By collecting the data, we can help employers see if there are any groups that are deliberately or unintentionally experiencing discrimination.
Expertise and analysis:
Most employee surveys or pulse surveys are just a battery of questions sent out, and it is up to the leader to analyze what the answers mean. Equality, inclusion, and diversity are very complex fields. In addition, we know that all types of data analysis take much longer than many may think. The result is that data is often not analyzed and converted into insights (we have learned this "the hard way" through previous surveys where we presented data without analysis and found that few had the capacity to turn the data into insights they could use to improve the situation). Therefore, we present the data analyzed in clear insights and diagnoses based on our expertise.
Measures that work:
Many people feel that employee surveys or pulse surveys are conducted without consequences or follow-up. Equality Check provides your employer with ready-analyzed feedback on what the challenge is in your workplace and links it to specific research-based solutions to improve the result. We can also measure development over time so that we can see that the development is moving in the right direction.
How will the employer see the information?
Below you can see an example of how the employer sees the information. The employer does not see individual data (data of a single employee). We collect the data and present it as useful insights that the employer can act on. It's a win-win for everyone: you as an employee don't have to worry about the employer knowing what you have answered, and the employer doesn't have to worry about holding sensitive data, and they don't have to spend time analyzing data and acquiring domain expertise.
As you can see below, we collect the data and present the representation in the company in this way to the employer:
- Gender: percentage of men, women, and others
- Ethnicity/skin color: percentage of ethnic underrepresented and percentage of ethnic majorities
- Sexual orientation: percentage of heterosexuals and percentage of LGBTQI+
- Functional level: percentage of people with disabilities and percentage of people without disabilities
- Children under 12: whether or not you have children under the age of 12
- Age: divided into four age brackets
To display these graphs, there must be a minimum of five in each subgroup (i.e. "LGBTQI+" is a subgroup of the group "sexual orientation" and "men" is a subgroup of the group "gender") .
If there are less than five in a subgroup, these will be combined with other subgroups in the same group that have less than five - thus creating a new subgroup named "Grouped". For example, if there are only 3 people in the age bracket "45-64", and 4 in the age bracket "29-44", they will be combined into "Grouped" under age. In order for us to display "Grouped", it must contain five or more people.
Furthermore, we present the different responses from the culture and inclusion survey divided into the demographic parameters above (gender, ethnicity, sexual orientation, functional level, children under 12 and age), and distributed by job category.
This means that we for example display the average score for the experience of future potential divided into women, men and other. Every answer will be included. If "Grouped" contains less then 5 people, the responses of these people will be randomly distributed across the other demographic groups, thus potentially slightly altering their score. We chose this approach in order to keep their answers as contributions to the whole, while maintaining anonymity.
The same applies when we display culture and inclusion questions divided by job category.
Are you one of the few employees with your characteristics? See the question "There are only a few 'like me' in the company, am I still anonymous?" to read more about our restrictive data presentation to ensure that no one can know who you are.
Who can see insights from the data?
Employers:
Above, you have seen how employers are presented with data in the form of insights that they can use to improve the workplace for all employees.
Researchers:
We are very interested in obtaining as much research as possible on which groups of employees are consciously or unconsciously discriminated against, why it happens, what measures work, and so on. There is a great lack of knowledge, and we believe that knowledge and research are the best way to help organizations improve.
Therefore, we collect the data in large datasets. In these datasets, we remove all information that can identify individuals (such as names, email addresses, employer names). So much information is removed that no one who sees the datasets has any possibility of identifying individuals. We have lawyers who review the dataset to ensure that it is anonymized correctly.
We can provide such datasets to researchers so that they can conduct more research on equal opportunities in the workplace. We only collaborate with reputable researchers who are associated with serious research environments.
Here you can see an updated list of research environments we collaborate with:
- Core, Institute for Social Research.
When researchers have finished their analyses, their access to the dataset is deleted. Since researchers cannot identify individuals, they cannot publish the research in a way that identifies individuals (of course).
Others: We use the same aggregated and anonymized datasets to showcase more information about various demographic backgrounds, such as by industry or in Norway as a whole. When we collect all the answers from all of Norway, we will eventually have large enough datasets to say something about:
What is often called "intersectionality" without identifying individuals. This means that we can layer multiple characteristics on top of each other and see how this affects inclusion and culture, and how representation is at different levels in organizations. For example, gender, religion, and sexual orientation.
More detailed background and how it affects inclusion. For example, which ethnicities are most susceptible to unconscious discrimination, not just whether ethnic minorities experience more unconscious discrimination.
When we share such insights, the principles of group size are the same as we always have when showing data, so that no one can be identified.
I'm afraid of reprimands if I answer correctly, what should I do then?
Most employers are genuinely interested in improving workplace conditions for employees. In our experience, this is the most common motivation for sending out our survey.
That being said, we are well aware that this is not the case in all organisations. Our founder, Marie Louise Sunde, is a doctor and has worked several years in a hospital. She chose to speak up about unsatisfactory working conditions at her former workplace, knowing that it would cost her her job. Several of us in Equality Check have experienced firsthand how difficult systematic reprimands from employers can be, and as a result we take this very seriously. You can be completely sure that we will not risk reprimands on your behalf.
In the question above, you can read and see more about how the employer sees the information. There you will find that the information will never be presented in a format that directly or indirectly exposes employees. That means that the employer will never be able to know what you have answered, or if you have answered at all. In other words, you do not need to be afraid of reprimands, even if you work somewhere where you suspect (or have experienced) that the employer may give reprimands for feedback they do not like.
There are only a few 'like me' in the company, am I still anonymous?
This is a question we often receive, and we understand why. In the survey, we ask many questions about who you are, and if these are combined, it can be very easy to understand what you have answered even if your name is removed. You can be completely sure that we will not present the data in a way that makes the employer (or anyone else) able to identify you. Here we tell more about how we present the data so that you can be completely confident about it.
When we say that we anonymize your data for the employer, we have taken into account that if we combine all the data points you have answered, it is often very easy to understand who has answered what. This means that we do much more than just removing your name when we send the data to the employer. We do not send the data as you answer it, we send aggregated data insights. This means that we collect data from many employees and present it as a common value back to the employer. In the question of how the employer sees the data, you can see an example of how the data is presented to the employer.
How the data is displayed depends on how many with the specific characteristics have answered. For us to show a given data point or a group of data points, there must be a minimum of 5 with exactly this collection of characteristics who have answered.
Let's use a concrete example: Let's say you are a 35-year-old man who works as a developer in a workplace with 200 employees. You have brown skin and are Jewish. There are no other Jews in the workplace. There are only 5 others you can think of who are brown-skinned, and only 2 who are men and none of them are developers. In addition, you are the only one who has dared to say aloud that you have experienced negative comments based on your religious affiliation.
In this case, we will show aggregated data to the employer where we show the following information:
- We show how employees of ethnic minority and ethnic majority report the different culture & inclusion indicators as there are a total of 6 employees who are brown-skinned.
- We show how employees of different genders report the different culture & inclusion indicators.
We do not show the following information because it is less than 5 in these groups:
- We do not combine gender and ethnicity, as there are less than 5 women and less than 5 men who are brown-skinned in total.
- We do not link data on ethnicity and job title, as you are the only one who is brown-skinned and a developer.
- We do not show anything about religion because you are the only one who is Jewish.
This is not a complete comprehensive list of what we show or do not show in a given example, but is intended as a description to reassure you that we understand the situation.
How long is the data stored?
We store the data from the surveys for up to 12 months. We have developed an annual plan for employers to systematically work on equality, inclusion, and diversity throughout the year. Therefore, we store the data for 12 months so that we can produce useful analyses throughout the year.
After 12 months, we delete the data that allows us to identify individuals. Then, we store the data in anonymous, aggregated datasets so that we for example can analyse trends over time, and use the data for benchmarking.
Anonymous, aggregated datasets mean that we delete all data points that allow us to identify who responded (such as name, email, employer). This means that even we at Equality Check cannot identify individuals. We receive help from our lawyers to ensure that the dataset is anonymized.
I regret it, how can I delete the data?
What if I don't want to answer?
No problem, you can just choose not to answer.
If you want to answer some but not all questions, you can simply choose "skip" for the questions you do not want to answer.
Some of the data is of "special category" - why can Equality Check collect it?
In privacy legislation (GDPR), some personal data is called "special category". This is particularly sensitive data such as ethnicity, religion, and sexual orientation. This type of data has extra strict requirements for collection and storage.
This type of data can only be collected voluntarily, and requires separate consent (that's why you checked twice to answer the survey, both for regular data and data of special category).
Most lawyers believe that an employer cannot collect data of special category even if the employer says it's voluntary. The reason is that there is a power imbalance between employer and employee. Employees may therefore feel pressured to give up data even if the employer says it's voluntary, for fear of consequences for saying no.
We at Equality Check, not the employer, collect the data. Equality Check is an independent third party. This means that we have no employer responsibility towards you as an employee, and there is no risk that you will reply to the survey just because you are afraid of reprimands if you do not respond. We do not share raw data with the employer, which means that the employer will never know if you have answered or not. The employer will also never have access to individual data, so the employer can never know what you have personally answered.