JEDI1.1 How to Track the Mandatory First Social Identity (Gender at Birth vs. Sex at Birth)

Modified on Wed, 18 Mar at 10:25 AM

Choosing your five worker related measurements

How to collect and disaggregate your data

Case Study 1: Boutique marketing agency with 60 workers

Case Study 2: Global FMCG (Fast Moving Consumer Goods) company with offices in multiple countries

Under the Justice, Equity, Diversity and Inclusion (JEDI) Impact Topic, companies are expected to collect data and feedback and then use that information to choose targeted JEDI actions. Specifically, under the JEDI 1.1 sub-requirement, if you are a company with 50 or more workers (by headcount), you are required to:

Collect data on gender identity or sex at birth for at least five worker-related measurements, and
Disaggregate that data to report internally on those measurements.

All of this must be done in a way that is voluntary and allows workers to remain anonymous.

Gender identity versus sex at birth

Before designing your data collection approach, it’s important to understand the distinction between these two categories.

Gender identity is an individual’s internal, deeply-held knowledge of their own gender. Everyone has a gender identity. Gender identity categories vary by country, culture, and language, and change over time. In many English-speaking countries, the categories are: man, woman, and non-binary or non-conforming.
Sex at birth is assigned to a person when they were born based on their external anatomy (either male or female). Sex at birth does not reflect the complex development of the human body. Sex is not solely determined by anatomy, nor is it strictly binary. People can also change their body through medical transition in ways that fundamentally alter the sex they were assigned at birth. Many companies already hold this information indirectly through legal or HR records. In contexts where asking about gender identity is difficult or risky, the standards allow you to meet JEDI 1.1 by collecting sex at birth only.

Safety first: The standards make two key points here:

The company is not expected to hold information on sex, gender or social identity as part of employment or personnel records.
The company should take alternative measures if asking about gender identity is not permitted by law or may put workers at risk.

Examples of acceptable alternatives include:

Asking only for sex at birth (e.g. male or female).
Including an unnamed “other” category (e.g. man / woman / other) without labelling specific categories.
Including “prefer not to say” or allowing workers to skip the question entirely.

Where you do have the option, the guidance explicitly encourages collecting gender identity rather than only sex at birth, because this better reflects how people experience the workplace and discrimination.

Under JEDI 1.1.3, you must select and track at least five worker measurements and break them down by gender identity or sex at birth data. This helps you identify where disparities exist and take meaningful, focused action.

The standards provide a non‑exhaustive list of acceptable worker‑related measurements, including:

Employment categories (job classification, status, contract types),
Representation in the highest governing body and executive team,
Recruitment, promotion, training opportunities or participation,
Retention, attrition, or turnover,
Working hours and overtime,
Wages (linked to FW2),
Perceptions of working conditions,
Complaints or grievances (linked to PSG3),
Perceptions of workplace culture (linked to FW4).

By selecting measurements that cover the full employee lifecycle, you can pinpoint exactly where disparities occur. For example:

Recruitment: Who is applying, shortlisted and hired?
Promotion: Are specific gender groups "stuck" in particular levels or functions?
Wages: Are you paying equally for equal work across all identities?
Retention & Attrition: Who is leaving, where, at what career stages, and what is driving them out?
Perceptions of Culture: Do different groups (e.g. "man," "woman," and "non-binary" workers) experience your workplace differently?

How to collect and disaggregate your data

When planning the method to collect and disaggregate this data, you must factor in the three core principles from JEDI 1.1.4:

Voluntary: workers must be able to choose whether to provide their data.
Anonymity: workers must be able to remain anonymous.
Non‑de‑anonymisation: the company takes care not to accidentally identify individuals, especially in small groups.

Read the article How to Collect JEDI Data Anonymously and Voluntarily for detailed guidance on best practices to follow while collecting JEDI data.

Case Studies

Collecting data on gender or sex at birth in worker-related measurements helps companies better understand how impacts and opportunities vary by gender or sex within the company. This information helps guide the decision of which actions to take under JEDI2.

Read these case studies to understand how a company collects data to understand sentiments on diversity and inclusion in the workplace, track how these experiences may differ by sex or gender, and then use that insight to select their JEDI actions for JEDI2.

Case Study 1: Boutique marketing agency with 60 workers

1. How they collected the data

2. The 5 worker measurements they chose

3. The JEDI action they decided to take

They decided to use a single anonymous survey to understand employee sentiment about workplace culture using an external third party tool, sent to workers via a generic survey link not linked to their employee record.

In the invitation, they explained that participation was voluntary and anonymous, and data would only be shown at a department level where there were at least 5 workers to protect anonymity. Otherwise, it would be aggregated with company-wide numbers, due to the small company size of 60 total employees.

They also decided that they would do this survey annually and communicated this to demonstrate the long-term commitment to driving action and improvement.

They decided on 5 worker measurements to understand if there were differences or significant gaps between different genders as it relates to:

1.Perceptions of workplace culture (including responses to specific workplace culture related questions workplace culture survey).

2.Hiring rates (including % breakdown of men and women hired in the previous year);

3.Promotion rates (including % breakdown of men and women who received promotions in the previous year);

4.Training opportunities and participation (information on all of the training and development opportunities offered and % breakdown of attendance and participation rate of men and women);

5.Turnover/attrition (including the rate of annual turnover for women and men, compared to the combined company turnover rate for the previous year);

At the point of launching this exercise, they communicated that these areas would be the focus for the data collection exercise, in order to encourage voluntary participation and buy-in from workers.

For the hiring rates measurement, the data showed near‑equal hiring rates, but for the promotion rates, a 30% lower rate for women when compared to men. They used this data point to launch a workshop series to equip leaders and line managers to help understand the reasons and drivers behind this.

The HR team also standardized performance rubrics to ensure that all candidates are evaluated against objective criteria rather than subjective assessments like “culture fit,” “leadership presence” or “visibility.”

Case Study 2: Global FMCG (Fast Moving Consumer Goods) company with offices in multiple countries with 3,700 workers

1. How they collected the data

2. The 5 worker measurements they chose

3. The JEDI action they decided to take

With their global footprint and varying legal landscapes, the HR team launched a Global JEDI Survey hosted by an encrypted third-party firm.

To meet the safety requirements of JEDI 1.1.3, they used alternative measures in high-risk regions and workers in those locations were asked only for "sex at birth" or given unnamed "other" categories, and the option to skip questions entirely.

To encourage voluntary participation (JEDI 1.1.4), they issued a global privacy pledge explaining that no identifiable data would be shared with local management or stored in regional HR files, and that participation was voluntary and could be anonymous.

To gain a holistic view of their global workforce, they selected 5 worker measurements that could highlight systemic trends across different cultures.

The first 4 measurements included specific survey questions:

1. Retention and attrition/turnover rates;

2. Promotion rates

3. Representation at Executive level;

4. Perceptions of working conditions.

5. Wage data: This worker measurement was not included in the Global JEDI Survey. The wage analysis was done using an HR extract prepared by the system administrator, who removed all personal identifiers before sharing the disaggregated dataset for JEDI analysis.

The disaggregated data revealed a significant “leaky bucket” in retention of workers who selected “non-binary” and “women” in major distribution hubs. By cross-referencing this with their “perceptions of working conditions” data, they identified that a lack of gender neutral facilities and inflexible shift scheduling were disproportionately affecting workers who were non-binary and those with caregiving responsibilities.

In response, the company committed to a global facilities upgrade to add gender-neutral restrooms and private changing areas. Additionally, they moved from JEDI 1 to JEDI 2 by implementing a Core Hours policy that allows more flexibility for workers with caregiving responsibilities, which the data showed predominantly impacted the women in the distribution hubs.