How to put your employee data to wider use
Despite numerous conferences, papers and blogs on talent analytics, it remains a relatively new concept for many CHROs. In an article originally published in Personnel Today, I outlined seven key talent analytics tips that could help in the transformation of HR. You can read the full article here
Talent analytics simply involves using employee data and statistical analysis to create a greater understanding of the people in your organisation. Correlating your employee data against business outcomes provides actionable insights that can help you make more informed people decisions.
So, what are the seven tips I want to share?
#1. Review your existing employee data
Not surprisingly to create effective talent analytics you need usable data. You’ll undoubtedly have data on your employees, such as demographic data, their length of service and their prior experience. And you’ll have performance data – and you may have assessment data – such as personality or ability test results – from when they were recruited. The first step is to clarify exactly what data you can access on your employees.
#2. Ask a question
Essentially, you want your talent data to tell you something useful. The more data you have, the more questions you’ll be able to answer. But initially you might start with queries such as: What do our high performers have in common? Asking questions – or creating a hypothesis around a challenge you’d like to explore – will help to focus your attention.
#3. Analyse and correlate the relevant data
This is where it gets interesting! For example, your performance data will reveal the top performers in different parts of your business. By analysing the pre-hire assessment data from those employees, you may find some commonalities. One of our clients found that their top salespeople were empathetic, consultative and supportive. This surprised them, as they were expecting their top sales people to be confident extroverts. Knowing the key characteristics, competencies and motivations of your top performers can help you to create a “success profile” of what it takes to succeed in your organisation. You can then recruit and develop people against this profile.
#4. Check your assumptions
If you’re going to make decisions based on your data, or present it to the board, you have to be confident about its quality. If you have missing data or if your sample size is small, you may still be able to partly answer your question or support your hypothesis. However, you’ll need to highlight the imperfections of your analysis, as you won’t have full information.
#5. Design an appropriate intervention
The next step is to create a solution to the issue you’re addressing. In the full article I use the example of wanting to encourage more women to apply for technical roles in your organisation. In such a case, if the steps above are worked through, you would know where your current female applicants are coming from and understand if a high percentage of females drop out at any stage of the selection process. You will also have looked at the characteristics of your existing female technicians; you’ve tried to understand what attracted them to your organisation, what engages and motivates them to work with you and why they stay. You can then create a hypothesis of why you think you have too few female technicians. This may be related to how you’re describing the job, how you’re promoting it, where you advertise or how you’re managing your selection process. You can then take some action to rectify the situation. Focus on one or two measures that you expect will have an impact but involve low effort on your part.
#6. Validate the changes
After implementing your intervention, track and monitor the situation to assess the business impact. Don’t just implement the intervention and hope for the best. Collect evidence of what has changed, so you can correlate that change to your intervention.
#7. Share your successes
When your hiring managers start to see a higher ratio of better candidates then you’ll know the method has had an impact. This is where the good news about talent analytics gets to be shared. If you can show the tangible benefits of talent analytics, you can more easily gain additional investment, so you can gradually scale-up to address other challenges.
A word of warning though when working with talent analytics. It can be easy to be misled by your data. You may reach reasonable conclusions that turn out to be flawed. If you don’t have the capabilities to analyse and manage data in-house then take expert advice to help you ask the right questions, draw appropriate conclusions and choose the right interventions.
Read my full article here.
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