An employer and their industry share a goal of retaining employees. This study explores factors that contribute to an employee staying with an employer and within an industry. Overall, there are higher retention rates within an industry than with an individual’s first employer within that industry. This suggests that it is common for individuals to move between employers within an industry.
Middle-aged individuals have the highest likelihood of staying with their first employer and within that industry. This presents a potential target for talent attraction programmes. Younger employees have lower retention rates; however, this age group shows a significant increase in retention with training. This suggests that employers and industries providing training for their young employees will increase the likelihood of the employees retaining.
Retention of employees is essential to both employers and the industry. Employers often contribute financially to an individual’s training within an industry and therefore would be interested in investing in those that are likely to stay working with them. From an industry’s perspective, it is crucial that there are enough experienced workers at a given time, so it would be preferable for new talent to stay working in the industry. This report explores the trade-off between hiring young and old employees with and without training. The first section explores the retention of an individual with their first employer and the second section investigates retention rates within an industry.
The chart below demonstrates the retention rates of individuals with their first employer within an industry. Individuals between the age of 30 and 64 are overall shown to have higher retention rates in the trades than younger employees between the ages of 14 and 29. This implies that older employees are expected to stay with their first employer for longer than younger employees. However, age may not be the determining factor for this retention differential. Older employees are more likely to have prior experience in related industries than younger employees. This would put older employees in a better position to obtain more senior roles, better pay and improved working conditions, all which disincentivises them from leaving their first employer causing higher retention rates.
Apprentices are shown to have higher retention rates with their first employer than those that do not enter training. This gap is at its largest after four years (48 months) were three times as many apprentices are retained compared to non-apprentices. After four years the gap begins to converge, likely as apprentices holding out to complete their training finish and move on.
On average, an employer can expect a young employee who is not partaking in training to stay 6 months, while young apprentices can be expected to remain with their first employer for 26 months. The higher retention rate of apprentices could be due to employees being tied to their employer during training, likely because the employer is paying for their training.
Combining this chart with the one above, it can also be observed that apprentices have a smaller variation between age group retention rates than non-apprentices. This demonstrates that the expected length of employment of an apprentice is more certain than the retention of a non-apprentice.
The age group (14 to 19) has been pre-selected in the dashboard below due to the retention differences across age groups. You can adjust the population by changing the filters on the right of the chart.
Methodology
We determine the first employer that new workers to a trades industry start working with. Within this employer we determine how many months they continue to work with that employer. We apply additional breakdowns by their age group and whether they start an apprenticeship within the first year of starting work.
Note that the data has been suppressed by StatsNZ randomly rounding counts to base three, explaining why the lines are bumpy and sometimes jump up when they should only ever curve downwards. To counteract this, the lines have been smoothed by a moving average with a window of 5 months.
We have included a variable slider called 'Month threshold' this allows you to limit the starting point of the retention curve to only employees who have been employed at least that many months. For instance, you may be only interested in the retention of employees who make it past the 90 day trial period. To do this you can set the month threshold to 3.
Methodology
We determine the first employer that new workers to a trades industry start working with. Within this employer we determine how many months they continue to work with that employer. We apply additional breakdowns by their age group and whether they start an apprenticeship within the first year of starting work.
Note that the data has been suppressed by StatsNZ randomly rounding counts to base three, explaining why the lines are bumpy and sometimes jump up when they should only ever curve downwards. To counteract this, the lines have been smoothed by a moving average with a window of 5 months.
We have included a variable slider called 'Month threshold' this allows you to limit the starting point of the retention curve to only employees who have been employed at least that many months. For instance, you may be only interested in the retention of employees who make it past the 90 day trial period. To do this you can set the month threshold to 3.
This section looks at the retention of individuals within an industry. Overall, there are higher retention rates within an industry than with an individual's first employer. This suggests that often individuals will move between employers within an industry.
For an industry to increase their overall retention, they can consider the age groups that are likely to stay within the industry longer. Individuals between the age of 40 and 59 are shown to have the highest retention rates within an industry with individuals aged 65+ with the lowest retention rates, likely due to retirement. Younger individuals have low retention rates, suggesting that attempting to attract talent from school leavers may not be the best target. The most efficient use of resources for talent attraction could be the middle age groups that are likely career changers.
There is a much higher expected retention rate for an individual that is an apprentice than one that is not. It is likely that new employees entering apprenticeships are more committed to the industry than those who don’t enter training. It, therefore, cannot be concluded that training is the sole reason for the increases in retention. However, training likely does have an impact on the individual’s commitment to work in the industry, possibly due to the apprenticeship putting the individual in a better position to obtain a secure, well-paying job within the industry. Overall, this result indicates that industries should increase the attractiveness of an apprenticeship within their industry to increase overall retention.
The age group (14 to 19) has been pre-selected in the dashboard below due to the retention differences across age groups. You can adjust the population by changing the filters on the right of the chart.
Methodology
We take all new workers into trade industries and determine how many months they have worked within that industry over the next 5 years. From this, we determine the number of workers that retain working in the industry at each month. We apply additional breakdowns by their age group and whether they start an apprenticeship within the first year of starting work.
Note that the data has been suppressed by StatsNZ randomly rounding counts to base three, explaining why the lines are bumpy and sometimes jump up when they should not increase. To counteract this, the lines have been smoothed by a moving average with a window of 5 months.
We have included a variable slider called 'Month threshold' this allows you to limit the starting point of the retention curve to only employees who have been employed at least that many months. For instance, you may be only interested in the retention of employees who make it past the 90 day trial period. To do this you can set the month threshold to 3.
Methodology
We take all new workers into trade industries and determine how many months they have worked within that industry over the next 5 years. From this, we determine the number of workers that retain working in the industry at each month. We apply additional breakdowns by their age group and whether they start an apprenticeship within the first year of starting work.
Note that the data has been suppressed by StatsNZ randomly rounding counts to base three, explaining why the lines are bumpy and sometimes jump up when they should not increase. To counteract this, the lines have been smoothed by a moving average with a window of 5 months.
We have included a variable slider called 'Month threshold' this allows you to limit the starting point of the retention curve to only employees who have been employed at least that many months. For instance, you may be only interested in the retention of employees who make it past the 90 day trial period. To do this you can set the month threshold to 3.
Access to the data used in this study was provided by Stats NZ under conditions designed to give effect to the security and confidentiality provisions of the Data and Statistics Act 2022. The results presented in this study are the work of the author, not Stats NZ or individual data suppliers.
These results are not official statistics. They have been created for research purposes from the Integrated Data Infrastructure (IDI) which is carefully managed by Stats NZ. For more information about the IDI please visit https://www.stats.govt.nz/integrated-data/.
The results are based in part on tax data supplied by Inland Revenue to Stats NZ under the Tax Administration Act 1994 for statistical purposes. Any discussion of data limitations or weaknesses is in the context of using the IDI for statistical purposes, and is not related to the data's ability to support Inland Revenue's core operational requirements.
