Talent management analytics

Trust you are all keeping safe. These days the wellbeing challenge is not just covid19. It is mental health issues, money worries, societal pressures and the optical illusion that the grass is always greener on the other side.

I always like predictions and trends because change is constant and we must always ensure we are on the cutting edge.

Latest HR trends and developments within the field have had an impact on the use of the term HR itself. As HR is developing, the term should be better in line with the work that is done: the term ‘Human Resources’ would imply that people are a resource that can be used just like machinery. Even if this is the case, people are more sensitive and rightly so.

You can change it to Talent management, People Operations or People & Culture. These titles reflect the new and coming nature of HR. If you choose to name HR in your company, make sure it reflects the work you are doing.

Read Also: Essentials of talent management and business strategy for the future and the present

I will replace HR with Talent Management for today to get us into the groove and get us thinking. Today we will be looking at Talent Management analytics trends. Putting your data to use with Talent Management (TM) Analytics

TM Analytics even though nothing new is not being put to good use by many. To be honest many TM departments are not getting the most out of their data or are fully utilising analytics tools. Often, this misuse of data can be attributed to hard to use tools or simply getting lost in a sea of data.

Many TM departments have been collecting data for years, but not used it much. Hopefully, this is all set to change. However, until TA professionals start truly using their data and closing the gap between theory and practice, HR analytics is going to keep popping up on trend lists.

Most people use data only for support rather than illumination.

TM analytics is a data-driven approach to identifying and analysing people-related gains and challenges. With the help of TM analytics, TM professionals can combine and analyse the data they collect in order to discover new and useful insights. This provides the information needed to make better decisions, which are based on objective data rather than intuition or gut feeling.

Overall, leveraging analytics leads to better working environments for the talent and better profits for the organisation. It can even give TM the evidence-based leverage they need to back up their decisions with management.

The benefits of the field of analytics in TM is endless with the right combination of data at hand.

For example, an organisation with a high employee turnover rate likely already knows what that turnover rate is, but they do not know why. By putting the right data to use, the organisation could, for instance, figure out why employees are leaving or even predict when they are most likely to leave and find an actionable solution to reduce this.

To do this, TM needs to first determine the relevant metrics. While every organisation’s situation is unique, looking at resignation rates, drivers and segments is a good place to start. Then look for correlations with metrics such as pay increases, performance and promotion wait time. This can provide insight into who is leaving and why, so that you can craft a tailored employee retention plan to keep the best employees from leaving.

To know how well you have been collecting data, how long does it take for you to gather the following data and answer these few example questions about your organisation?

If you are done within a few minutes, then you are doing well. If not, it might be time to start thinking about how and where to gather TM data in one place to make any analytics project smoother, or even possible in the first place.

BASIC (these questions should take you less than 30 seconds to answer). How many people work within your organisation? What are the average age, gender or salary distributions?

ADVANCED How long have your employees on average been working for your company? Are certain segments at risk of leaving the organisation? If yes, why? When is the annual peak of sick leaves and what factors correlate with the increased amount of sick leaves?

HR analytics is an exciting field with a lot to offer. First, make sure to find out which questions you should be asking. The best questions are those which lead to actionable insights. Then, figure out which metrics will help you answer those questions. By taking these simple steps, you are already on your way towards contributing to a more data-driven organisation.

TM makes people fill out endless forms for just about everything without retrieving the data for planning and decision -making processes. For example, do people move to better locations when they get a raise? If not, why. This could help in the determination of the behavioural pattern of whoever is to be recruited.

Have a great weekend. We can use analytics even in our own private lives. Are you doing this? What analysis are you doing using what data?