Big data and analytics are transforming how companies operate.
Marketing and sales have been using data analytics for some time now, but human resources is relatively new to the table. HR analytics is a growing priority that is helping companies to make better, data-centric decisions with their people.
Broadly speaking, many companies have been slow to adopt data analytics in the HR field, although this is commonly seen as a goal for the near-future. What about the Human Resources Manager who would like to take a data-driven approach right now?
Here are a few priorities for becoming more data-centric:
Understand the role of data
By nature, human resources departments have always been a hub of data. Employee information has to be collected and stored, including data on performance, pay, qualifications and training. Human Resource Information Systems were introduced years ago to contain all of this data, but it’s only more recently that HR is also using statistical tools to work with the data.
Overall, you could say that HR managers have been accustomed to making intuitive decisions, based on personal experience or judgment. Employee appraisals are just one example. Traditionally, bias could easily creep into the appraisal based on the personal feelings of the manager doing the appraisal. Where data was used, it was often historic and not necessarily telling an accurate story of that employee in the present.
The same could be argued for hiring decisions, or decisions about who to train for what role. Evaluations often relied on a heavy intuitive component.
HR analytics data brings the opportunity for these key tasks to be more quantitative in nature. You can use real-time data for performance appraisals and offer more timely feedback. HR can demonstrate how their decisions add value to the company by pointing to the data.
As part of understanding the role of data though, it’s also important to acknowledge the potential tensions with people over its use. Many people express discomfort with the idea that they’re going to be “assessed by an algorithm” rather than a human judgment. (Of course, anyone who has felt that their previous appraisals didn’t accurately account for their results may be pleased).
Another source of tension is suspicion over what data may be used for. People may have ethical concerns such as whether data will be used to make the decision of who to hire or who to promote. The key is that humans are still at the helm. An algorithm may suggest that certain people could be a good fit based on their performance, but the HR manager should be making the decision. You could frame HR Analytics as additional support to make smarter decisions.
As part of the journey to being data-driven, the Human Resources Manager needs to be able to explain to employees and stakeholders how data is used and how integrity is maintained. They need to be able to gain the trust of employees, otherwise they may not be open to providing useful answers.
Ensure data quality
Data quality is another major challenge for HR managers. It is often the case that data may be siloed into several different areas or programs and managers need to find a way to bring it together for a thorough analysis.
Sometimes historic data is incomplete or missing. Sometimes the quality of the data is compromised where employees or others are evasive about providing honest answers to survey data (another issue where gaining trust is key).
What can help with data quality? It’s important to have people who are trained in data analysis and familiar with what to look for. They should be able to analyse data from the point of view of its strengths and weaknesses.
Secondly, having the right tools for analysis can help. Using something like R to provide a more robust analytical potential, including the ability to explore massive data sets is a good step.
Prioritise data security and privacy
Privacy and data security are major themes of the last few years. We’ve seen huge exposure of data breaches from companies like Facebook, multiple warnings to consumers about hacking issues and overall concern about protection of privacy.
The GDPR makes its data privacy principles quite clear:
- Lawfulness, fairness and transparency – you must process personal data lawfully, fairly and in a transparent manner in relation to the data subject.
- Purpose limitation – you must only collect personal data for a specific, explicit and legitimate purpose. You must clearly state what this purpose is, and only collect data for as long as necessary to complete that purpose.
- Data minimisation – you must ensure that personal data you process is adequate, relevant and limited to what is necessary in relation to your processing purpose.
- Accuracy – you must take every reasonable step to update or remove data that is inaccurate or incomplete. Individuals have the right to request that you erase or rectify erroneous data that relates to them, and you must do so within a month.
- Storage limitation – You must delete personal data when you no longer need it. The timescales in most cases aren’t set. They will depend on your business’ circumstances and the reasons why you collect this data.
- Integrity and confidentiality – You must keep personal data safe and protected against unauthorised or unlawful processing and against accidental loss, destruction or damage, using appropriate technical or organisational measures.
HR managers must safeguard data and be consistent about what they are gathering and for what purpose. They need to identify the specific data points that they really need to capture and no more.
Identify people problems where analytics can help
Another key step on the journey to being a data-driven Human Resources Manager is to identify clear people problems that can be solved through early identification and the help of analytics.
For example, HR Analytics is being used in:
- Recruitment
- Retention
- Appraisals
- Staffing considerations
- Learning and development
Analytics can help you to identify who is truly engaged and who may be at risk of leaving. When you consider your need for trained and/or senior staff, this can be especially important in a competitive job market.
Get buy-in from other departments
The journey of the HR department toward a data-centric approach tends to run more smoothly when there is buy-in from other stakeholders. For example, they can work together on issues that have a wider impact, or directly relate to company goals.
The overall aim should be to provide actionable insights to the right people at the right time. To do this, HR needs to have a good understanding of what their audience’s priorities are and be able to show how their analysis directly relates to those goals.
Final thoughts
Data analytics is relatively new in the HR field, although it is rapidly gaining ground. It’s important to note that it may take some time for HR to achieve a level of analytical maturity, but by focusing on these areas, it is possible to be a data-driven manager.
There are many more possibilities on the horizon for HR by taking a more quantitative approach. With the focus of many companies on deliverables, HR can show how they are meeting these.