This report communicates the processes that were followed to assess the quality of the 2019-20 employee census data. For the 2019-20 reporting period:

• The cut-off date for inclusion in the dataset was on 03 September 2020
• The dataset and gender equality indicator (GEI) scorecard were released on 26 November 2020
• 4,943 reporting organisations* were included in the dataset. This covers 11,179 businesses and 4,393,656 employees in the non-public sector.

Coverage/Relevance

The WGEA dataset covered 40.3% of the estimated overall Australian workforce. This is slightly down by 1.1 percentage points compared to the previous reporting period. Figure 1 shows that coverage declined for most industries, including retail trade and education & training. Coverage improved for manufacturing and construction and was stable for health care & social assistance.

Figure 1: The 2019-20 WGEA dataset - coverage of all Australian employees

Note: WGEA reporting guidelines require organisations involved in labour hire functions to capture their contracted staff within their WGEA report – this can lead to inconsistency in the capture of these employees between the WGEA and ABS.

External sources: ABS (2020) 6291.0.55.003 - Labour Force, Australia, Detailed - Electronic Delivery, March 2020. Result cited is for February 2020, available in data cube EQ05

Exemptions (Discretion Not to Name (DNN)) granted

The global COVID-19 pandemic restrictions had an impact on the capability of organisations to submit data to the Agency. For the 2019 – 20 reporting period, the Agency granted reporting exemptions (or discretion not to name (DNN)) to 134 reporting organisations across 17 industries. The potential loss of coverage was up to 3.9% across industries.  Table 1 shows that the exemptions had a slight impact on the workforce coverage particularly in the arts & recreation, administrative & support services, and retail trade.

Table 1: Coverage impact of exemptions on the 2019-20 dataset by industry

This table is sorted in descending order of coverage impact (%).

Timeliness

Figure 2 shows that 93.1% of reporting organisations that were not granted DNNs were able to submit verified data to the Agency by the cut-off date. This is an improvement of 1.9 percentage points to the overall timeliness rate, compared to the previous reporting period. Four industries declined in timeliness, most notably administrative & support services and information media & telecommunications. The majority of industries recorded improved their timeliness, including health care & social assistance and manufacturing. Timeliness rates were still above 80% across all the industries

Figure 2: 2019-20 WGEA dataset – timeliness by industry*

*Based on ANZSIC code provided by the reporting organisation

Table 2: Industry breakdown of 15 reports excluded from the 2019-20 dataset

This table is sorted in descending order of coverage impact (%).

Data quality checks - Questionnaire data

The most common anomalies that were accepted by the Agency as legitimate and included in the dataset relate to the governing bodies data. Table 3 shows that the most common anomaly relate to the target date for female representation falling in the current reporting period, which only affects around 2% of organisations in the dataset.

Table 3: Top 3 questionnaire anomalies in the 2019-20 dataset

Table 4 shows that the accepted anomalies relating to board members greater than 20 and a governing board having more than two chairs accounted for less than 10% of the total board members and chairs in the dataset. The rate of these anomalies will be continually monitored to ensure that they do not exceed the baseline rates as per below.

Table 4: Board member or chair anomalies - records affected 2019-20

Data quality - remuneration data

Organisations are able to provide remuneration data in unit level or aggregated format. Unit level data enables a richer analysis of remuneration data.

In the 2019 - 20 reporting year, the unit level dataset accounted for 2,272,197 records (52% of the 4,393,656 employee records).

Known limitations of the benchmark’s remuneration data provided by employers in general are summarised below:

• Approximately 0.6% of employee salaries are below $17,300. Most of these salaries are legitimate as some employees are under 15 years of age or are on a disability scheme payment in this dataset. There are legitimate cases where an employee has no salary (for example, in some religious organisations; and when an employee works on commission only).
• Approximately 1.0% of employers reported the same base salary and total remuneration amounts for some employees (noting that this situation can be legitimate under certain circumstances – for example, employees who are under 18 and work less than 30 hours a week, or employees that earn less than $450 a month).
• It is possible that salaries of some part-time or casual employees have not been annualised and/or converted to full-time equivalent amounts, which could lead to more variance in the salary data.
• Table 5 shows that there is more variance in the salary and remuneration unit level data submitted for Full-time employees compared to Part-time and Casual employees. Median absolute deviation (MAD) is used as a measure of variance as it is robust against outlier records.

Table 5: Median absolute deviation (MAD) of annualised salaries 2019 – 20 unit level dataset

WGEA census data - changes over time in reporting organisations

The overall size of the comparison group may have changed from last year. The industries granted the most DNNs (Administrative & support services, Arts & recreation services, and Retail trade) decreased, but the sample sizes for these industries are still within the range comparable with the last seven years.

Table 6: Industry breakdown of reporting organisations in WGEA’s benchmark dataset over time

Organisations may have changed size due to restructure or downsizing (Table 7).

• Organisations may have modified their ownership structure.

• Organisations may have chosen to report in a different way this year (e.g. as a collective last year and as separate subsidiaries this year).

Table 7: Organisation size breakdown of reporting organisations in WGEA’s benchmark dataset over time

WGEA census – changes over time in employee numbers

• Table 8 shows that while the number of employees for industries granted the most DNNs (Administrative & support services, Arts & recreation services, and Retail trade) decreased, the employee level for these industries are still within a range comparable to the last seven years.

Table 8: Industry breakdown of employee records in WGEA’s benchmark dataset over time

Table 9: Organisation size breakdown of employee records in WGEA’s benchmark dataset over time

Appendix I - 2020 Data Quality Checks