Data is becoming more important everyday in businesses. Whether this is the increase in tools, software, or availability of data, there’s no doubt that mastering analytics will boost a company’s performance. For New Zealand businesses facing the competitive job market, using data as a tool to inform strategic HR decisions is a great way to get ahead of the competition and improve your talent management.

Below, we will describe some of the benefits of data-driven HR, delving into specific applications of analytics across various HR functions in a New Zealand context.

Why Data-Driven HR Matters in New Zealand

Trends like remote work and the gig economy pose many new challenges and opportunities for HR professionals in New Zealand, with the constantly changing environment of work, turning to analytics is a great way to find some consistency and direction.

Here are some ways data-driven HR can help you navigate these areas:

• Informed Decisions: Data presents objective insights to replace intuition or guesswork in HR decision making.
• Improved Talent Acquisition: Analytics are a tried and tested method of identifying great candidates, target recruitment efforts effectively, and streamline the hiring process.
• Enhanced Employee Engagement: By analysing employee data, you can identify any areas for improvement in terms of motivation, satisfaction, and performance.
• Proactive Workforce Management: Having data empowers you to predict potential problems before they happen, such as high turnover or skill gaps.
• Data-Driven Compliance: Data analysis also ensures your compliance with New Zealand employment laws and regulations.

Utilising HR Analytics in Your New Zealand Business

Here are some more specific applications of HR analytics across some crucial HR functions:

1. Recruitment & Talent Acquisition:

• Identifying Top Performers: You can use past performance data to predict future success and identify ideal candidate profiles.
• Job Description Optimisation: By analysing job posting data from your industry, you can discover keywords that attract the best talent and use these in your future job descriptions.
• Candidate Sourcing Efficiency: Utilising analytics can help narrow the search for candidates and target recruitment efforts to the most promising talent pools
• Metrics to Track: Time-to-hire, cost per hire, quality of hire (retention rate), source of hire (platforms like job boards, employee referrals). 

Example:

A New Zealand-based software development company analyses data from their past hires to identify common skills and experience levels associated with top performers. This data informs the creation of targeted job descriptions and helps them source talent with specific skill sets on platforms frequented by software developers.

2. Onboarding & Retention:

• Mapping Onboarding Effectiveness: Analysing employee satisfaction to look for areas to improve in the onboarding process
• Predicting Employee Turnover: Utilising data to identify early signs of turnover, such as low engagement or absenteeism.
• Metrics to Track: New hire engagement, onboarding completion rates, time to productivity, retention rates by department, cost of turnover.

Example:

A large New Zealand retail chain uses data to track employee satisfaction during their onboarding period. They find that early access to training materials significantly improves engagement. This then allows them to adjust their onboarding process, and leads to higher retention rates.

3. Performance Management & Development:

• Skill Gaps & Training Needs: By analysing employee data you can uncover skill gaps within your organisation and develop targeted training programs or hiring processes.
• Performance Tracking & Measurement: Utilise data to set performance goals, track performance, and provide targeted feedback to employees.
• Metrics to Track: New hire engagement, onboarding completion rates, time to productivity, retention rates by department, cost of turnover.

Example:

A New Zealand logistics company analyses performance data to identify a training need for their warehouse staff in using new inventory management software. They develop a data-driven training program focused on the specific skills needed, ultimately leading to improved efficiency in their warehouse operations.

Specific Data Analysis Techniques (With Example)

Whilst the specific methods will vary depending on your data and goals, here are some common techniques you should familiarise yourself with and employ in your HR strategy:

Descriptive Statistics: Summarise key workforce characteristics (e.g., average age, tenure, salaries) using measures like mean, median, and standard deviation.

Data Visualisation: Present data visually using charts and graphs to identify trends and patterns (e.g., bar charts for comparing metrics across departments, scatter plots to identify correlation between variables).

Predictive Modelling: Utilise statistical models to predict future outcomes, such as employee turnover performance levels.

A/B Testing: Test different approaches to your HR initiatives (e.g., onboarding program formats) by comparing results from your control and test groups, and running their data through statistical tests.

Example:

A New Zealand manufacturing company wants to improve their employee engagement in an Auckland factory. They then utilise their HR systems to analyse the data for factors like absenteeism, overtime hours, and participation in company events. The data they collected is plotted and reveals a correlation between high absenteeism and low participation in company events, suggesting a potential issue with work-life balance. They then conduct an employee survey to gather further information. Based on their combined data analysis, they introduce flexible work arrangements and organise team-building activities to address the work-life balance concerns, and later see an improvement in absenteeism and work event attendance rates.

Key Considerations for Implementing Data-Driven HR in New Zealand

• Data Quality & Security: It’s important to make sure your data is accurate and that you prioritise security and compliance with New Zealand privacy regulations like the Privacy Act 2020.
• Employee Communication & Transparency: Being open and honest to your employees is crucial. You should explain how the data is used, and ensure employees understand how it benefits them.

Conclusion

Data is an incredible tool for a HR professional to help their organisation and employees. Bringing data into HR in your company is a great way of making decisions based on evidence. Many companies don’t allow HR a seat at the table as they don’t generate “revenue” like those in sales, or logistics etc. However, by using data you can show how HR supports the ultimate business goal and supports the business with revenue. With our leading experts in HR, we partner with New Zealand based companies and help them reach new heights in HR by using data to inform decision making in areas such as technology, training, onboarding, recruitment and more!