What is HR data?

While some HR data can be considered people data, it refers to any data that HR teams are responsible for looking after and storing. HR data can relate to:

• Talent development
• Onboarding
• Offboarding
• Interview data
• Employee survey data
• Learning and development data
• Succession planning data
• Absence data
• Job architecture data
• Financial data
• Demographic data

Structured vs unstructured HR data

Many HR teams may have access to a wide range of data, though some of it may require additional processing before it becomes actionable. Examples of unstructured data include:

• Emails
• Videos
• Webpages

In contrast, structured data is organised and easier to analyse. Examples include:

• Spreadsheets
• SQL databases
• Times and dates
• Phone numbers
• National Insurance number

Using AI to organise unstructured HR data

Structured data is typically easier to store and manage, while unstructured data may require additional tools before it can be analysed.

As we highlighted in our guide to AI in HR, unstructured data can be processed by AI tools, which clean and organise it, allowing datasets to be extracted and stored in a management system. These tools may help organisations structure or review large datasets as part of their broader data-management process. AI tools are also valuable for analysing large and complex datasets, as we explore in the next section on big data.

What is big data in analytics and why is it useful to HR?

Some organisations analyse HR data to help inform decisions such as recruitment planning or budgeting. This can include gathering information on both current employees and potential candidates, a process known as talent analytics. It involves working with big data, which refers to vast and complex data pools collected from a wide range of sources. Because these datasets can be large and complex, traditional tools are often insufficient for analysis. Instead, HR teams may rely on machine learning tools or AI to effectively process and interpret the data.

Differences between HR data and people data

Some types of HR data fall under the category of people data. People analytics may offer insights that organisations use when reviewing workflows, project management tools, learning and development or performance goals. Including: 

• Workflows
• Project management tools
• Learning and development
• Performance goals

We found that people analytics often requires a team of professionals trained in data analytics, who might be part of the business’s HR team. For more advanced analytics such as prescriptive analytics (which works with predictions to suggest outcomes), Some organisations choose to bring in data specialists when working with more advanced analytics.

In contrast, HR data encompasses a broader range of data types, which can include financial data related to the business. This might involve recruitment budgets or the cost per hire.

Related: What is data literacy and how it can benefit employees

How can data analytics in HR help with business transformation?

HR analytics can support business planning by helping teams examine patterns and estimate potential outcomes of different strategies. These insights may assist organisations as they evaluate transformation efforts or explore new tools or processes. 

It can also help leaders navigate volatile economic climates and a complex employment market. Hiring Lab findings show that the UK’s labour market is still facing inactivity levels higher than they were during the pandemic, requiring businesses to explore transformative solutions.

Workforce transformation can be useful for businesses looking to:

• Update their remote or hybrid working practices
• Upskill their employees in a ‘digital-first’ industry
• Identify skills gaps
• Conduct needs assessments
• Introduce their teams to an agile approach

Predictive analytics may offer estimates or scenario projections that organisations may use when planning workplace changes.

Leveraging HR data

HR teams may only be using a fraction of the data they could be using to inform decisions. One form of HR data that some organisations review is psychometric testing. Information gathered from this testing may include:

• Working style information
• Personality profile
• Skill set including hard and soft skills
• Professional development opportunities

Some organisations review this information to explore potential learning and development opportunities. Some organisations review psychometric or behavioural data to understand working styles within teams. This information may help them consider how different approaches or strengths could complement existing team dynamics.

Other underutilised data includes offboarding or exit interview data. This information may offer insights that some organisations take into account when reviewing retention-related questions. Organisations sometimes review exit-interview data to better understand turnover patterns or employee experiences.

Industry best practices for using HR data 

Organisations often review how their HR data is stored and maintained, including how it aligns with applicable data-protection requirements. Some also consider how frequently they analyse performance-related data and whether the information is relevant for their goals. Advanced analytics may involve specialists with data-analysis training or experience.

When reviewing HR data, organisations often consider factors such as\

• Ensuring that employees are comfortable with how their data is used and how often, e.g. some employees may find real-time performance analysis stressful in the long-term
• Determining whether any data being analysed is useful for achieving business goals
• Checking how fresh the data is, as stale data can provide redundant predictions

Businesses across the UK may not be taking full advantage of the potential of HR data. There are several ways organisations may work with HR data: hiring experienced data analysts to work with predictive analytics, using psychometric testing results to inform learning and development and applying HR data to support broader workplace culture or wellbeing initiatives. When working with HR data, organisations typically review how their practices align with relevant data-protection requirements.