Athena Swan data provision

Staff in post on 31 July departmental overview

This dataset provides an overview of employees within a department/faculty at 31 July each year. Employees are divided into three groups based on their staff classifications in PeopleXD and other details in the PeopleXD appointment records such as grade and professorial title.

• Academic (grade 6+, staff class AC, AR, AP; all titular professors)

• Research (grade 6+, staff class AR or AP; not titular professors)

• Professional and support (all grades, all other staff classifications not AC, AR, AP)

Staff in post on 31 July detailed tables

Staff are classified into role groupings variously by a combination of staff classification, grade, professorial title, job title and a combination of these.

 Dimensions included are:

• sex
• roles
• contract type (permanent/open-ended, fixed term, self financing)
• working pattern (full-time, part-time, variable hours)

Maternity return rates

Maternity return rates are calculated based on appointment change reasons in PeopleXD and divided by contract type:

• Action Code = ML (maternity leave)
• Reason Code = MLS (maternity leave start)
• Reason Code = MLR (maternity leave return)

And the records are divided into the same three groups as staff in post

• Academic (grade 6+, staff class AC, AR, AP plus professorial title info)
• Research (grade 6+, staff class AC, AR, AP plus professorial title info)
• Professional and support (all grades, all other staff classifications other than AC, AR, AP)

Maternity longevity (retention)

Calculations are applied to work out if an individual was continuously employed at the University 6, 12, and 18 months after returning from maternity leave.

Paternity leave uptake

Dashboard shows the uptake of Ordinary Paternity Leave for the past five years as recorded in PeopleXD.

Leavers 1 August - 31 July

Leavers in the period are divided into the same three groups as staff in post and maternity

• Academic (grade 6+, staff class AC, AR, AP plus professorial title info)
• Research (grade 6+, staff class AC, AR, AP plus professorial title info)
• Professional and support (all grades, all other staff classifications other than AC, AR, AP)

Turnover calculations are provided and the data are broken down by working pattern and roles.

An overview of leaving reasons are also provided based on the leaving reasons selected in PeopleXD.

Recognition of Distinction

A summary of the outcome of the Recognition of Distinction awards are given by year, sex and outcome (successful/unsuccessful)

Data is included in the Athena_RecruitmentData Tableau workbook for the previous 5 reporting years on:

• Vacancies advertised on the University jobs website between 01-AUG and 31-JUL for each reporting year
• Vacancies that are closed and where data quality is complete and valid (check data quality using HRINFO21 Vacancy and applicant data quality report in HR Reporting).

Where vacancies resulted in an appointment being made, only vacancies with complete applicant status history (i.e. Applied; Shortlisted; Offer Made – Personnel; Offer Accepted – Personnel) are included. Therefore, any vacancies set to 'appointment made' where a mandatory stage of applicant status history is missing are not included. The ‘Applicant Statuses’ item in section 4 of Manage recruitment statuses and events illustrates the mandatory applicant statuses in a table by recruitment stage. For instance, the HR Analytics team have noticed that shortlisted is often missing when looking at University-wide recruitment data.

The HR admin team is required to follow the PeopleXD recruitment guidance including those on running the HRINFO21 Vacancy and applicant data quality report and clearing the red errors periodically. This may involve the need to add missing mandatory Applicant Statuses.

If a vacancy is missing from your Tableau view, first check for data quality issues using the HRINFO21 report. However, the HR Analytics Team cannot add in newly corrected data to the Tableau view on an ad hoc basis, but it may be included in the next scheduled Tableau refresh. It is essential that data errors are cleared down before the end of August annually and kept error free throughout the year to comply with data protection legislation.

Tableau dashboards provided

• Welcome landing page with details and data filter options.
• Overview tables showing headline figures for the number of vacancies by recruitment type, an applications-per-vacancy figure by recruitment type, and an overview count and percentage of applicant sex across the mandatory applicant status steps (applied, shortlisted, offer made, offer accepted).
• Recruitment type tables showing counts and percentages of applicants broken across recruitment type (academic, research, professional, and support) and by mandatory applicant status steps (applied, shortlisted, offer made, offer accepted). Note this shows just successful recruitments where an appointment was made to provide a fair comparison of sex by groups.
• Grade (Pay Scale) tables showing counts and percentages of applicants by advertised grade and by mandatory applicant status steps (applied, shortlisted, offer made, offer accepted). Note this shows only successful recruitments where an appointment was made to provide a fair comparison of sex by groups.
• Two dashboards showing Vacancy details as counts and percentages. Note this shows only successful recruitments where an appointment was made to provide a fair comparison of sex by groups.
• Data export – view one provides a count of applicants across mandatory applicant status steps for each vacancy. This tab contains up to three rows per vacancy (for the potentially three levels of applicant sex: female, male, unknown). The data shows vacancies with an appointment made, and those with no appointment made.
• Data export – view two provides all application details across the mandatory applicant status steps for each vacancy. This tab contains a row for every application made to each vacancy. The data shows vacancies with an appointment made, and those with no appointment made.