To increase retention rates in an industry, it is useful to have insight into factors that increase an individual’s likelihood of staying in an industry. This study investigated correlated factors to retention rates overall and in the agricultural, construction and manufacturing industry. The following are the overall findings:
- Out of the various age groups, middle-aged workers show the highest retention rates.
- Males have higher retention rates than females.
- Workers of Asian descent are shown to have the highest retention rates, followed by European workers.
- Retention by rurality was specific to the industry.
- Qualifications between levels 4 and 6 were shown to be the most beneficial for retention rates.
- An individual with a relevant qualification to the industry is more likely to retain longer than those that do not have a qualification or an unrelated qualification.
- Those that had prior experience in the wider related industry were more likely to remain in their new sector.
- The more an individual moved between sectors in the past the less likely they were to stay in their new sector.
For more information on industry-specific findings see below.
It is in an industries best interest to put efforts towards retaining their workers as this reduces turnover costs and increases the experience level in the workforce. Understanding contributing factors to an individual’s likelihood of staying in the industry can assist with initial hiring decisions and strategies to increase retention rates. This report explores several potential correlated factors and compares them across the food and fibre industries: agriculture, construction and manufacturing.
Middle-aged workers had the highest retention rates overall. Agriculture retention rates were more favourable with 30-40-year olds while manufacturing retention rates are consistently high with individuals between age 35-60. On the other hand, construction retention rates were highest with the 15-20 age group at 31%. Between age 20 and 60, the retention rates for construction were constant between 20% and 25%.
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Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
Overall, females have slightly lower retention rates than males. This is consistent across the three industries explored, with manufacturing having the smallest difference between males and females. Every sector shows this same pattern apart from the wool sector where females have higher retention rates.
Methodology
Overall, Asian workers are shown to have the highest retention rates. This holds for agriculture and manufacturing, however, in construction European workers top Asian workers. In the agricultural sector Asian workers are retained at a considerable high rate of 47% after 5 years, with European the second highest at 18%.
Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
Rural and urban workers have very similar retention rates overall. In the agricultural industry, rural workers are retained at 19% after 5 years while urban workers are only retained at 11%. On the contrary, in the manufacturing industry urban workers are retained at a higher rate than rural workers.
Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
Overall, a qualification between level 4 and 6 is favourable for retention rates. In the agricultural industry, a higher qualification is shown to be correlated with higher retention rates. Whereas in manufacturing, there is little difference in retention rates between qualification, other than qualifications between 1 and 3 which has shown to be associated with lower retention levels. In construction, a qualification at level 7 or above is correlated with low retention rates.
Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
The chart below demonstrates the relationship between whether an individual’s qualification is related to the industry they are in has an impact on their retention. Those with a relevant qualification are more likely to be retained than those who do not. Unrelated qualifications have slightly lower retention rates than no observable qualifications.
Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
Overall, those who were previously working in the wider related industry were more likely to remain in their sector. Overall, previous financial and insurance service workers had the highest retention after 5 years in their new sector. This is consistent with the agricultural industry, where the second-highest retention rates were with those who were in the wider agricultural industry. For the construction industry, those who were previously working in education showed to have the highest retention rates, followed by past construction workers.
Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
The longer an individual’s history is with a previous in their previous industry, the more likely they are to remain longer in their new sector. This trend is consistent across all the three industries explored.
Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
The more industries an individual has worked in the past, the less likely they are to stay in their new industry. This trend is consistent across all industries explored.
Methodology
We gather all new workers between the years 2006 and 2009 in select New Zealand industries. From these new workers we track how long they remain working in their new sector.
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.
