Business analytics, big data, and HR
Posted by Elise Toulman
Business analytics, and gathering big data, has been the talk of many an industry for quite some time now - and HR is no different. Advances in technology mean there’s no shortage of data being collected, but only those who are able to harness the expanse of information will gain true value from it, seeing greater business impact.
As an HR professional, to get ahead of the ever-growing competition in recruitment, it’s time to move away from relying on a hunch, in favour of a process governed by data and fact in order to make a hire that truly improves workforce performance. To incorporate it into HR practice, you must learn to tackle the wealth of information available in a world driven by data.
Gathering data is one thing, but using it for analysis is another. It’s this translation, and the creation of actionable insights, that enables managers in their decision making beyond the interview stages, and coordinates HR’s role in your organisation’s waste management.
Waste management, with relevance to recruitment, refers to time, money, and effort. Ineffective job profiling and inappropriate interview processes lead to bad hiring decisions, which waste both resource and energy. Add to that the re-hiring process if a new hire leaves after a few months, and we begin to see how valuable business analytics in recruitment can be!
If the data is translated accurately, and incorporated into the recruitment process fully, that reliance on a hunch becomes a process governed by data, driven by talent pools, applicant tracking systems, and objective measurement of skill, knowledge and ability - placing the right candidate in the right role.
The quality of the application of data should be paramount, which means that vanity metrics that look good but don’t offer much insight should be disregarded. Tracking something like the number of candidates in the hiring funnel is ultimately a vanity metric. It would be far more valuable to understand the quality of those candidates.
Historically, input metrics - such as calls made, emails sent, candidate sendouts - are used to illustrate efforts, but these mean nothing unless they’re pitched against output metrics like connected calls or opened emails. Context is essential in business analytics as it can reveal what is working, and where efforts should be redirected in the future.
At the other end of the process, turnover and exit interview data analysis will reveal what prompts employees to leave an organisation, fuelling change in talent retention. Predictive analytics can provide insight into talent management and allow for deeper forecasting. How much effort does it take to see “success”? How effective is that training course? Which employees are most likely to reach their targets? This sort of information gives your management team a well rounded, well informed view of gaps in the team, and where the business will benefit most from added resource.
Tools for gathering, analysing and interpreting business analytics data are becoming more affordable, and simpler to use. Reliance on agencies, outsourcers or headhunters is reduced by adopting cloud-based TAS and recruitment systems with social media integration. HR teams can set these up in-house and manage the process themselves, reducing costs, and ultimately increasing the value of HR. Financial values can be assigned to individual tasks throughout your organisation, which reveals the financial impact of the entire workforce on an employee-by-employee basis. Again, this has the potential to influence talent retention as well as bonuses, benefits and recruitment as whole.
The risk HR professionals face when learning to tackle the wealth of information available in a world driven by data, is being overwhelmed by it all. Analysts can create meaning from big data, but it’s the strategists that have the capacity to translate that data into actionable insights, and real results. While data driven recruitment is seen to be more effective across the board than legacy approaches, it’s not absolute. Even with access to psychometrics, data can’t apply emotion. HR, therefore, has evolved to become a blend of business analytics, and traditional people skills.