Let’s be honest here: HR doesn’t exist without employees, and HR practices don’t exist without the facts and figures related to these employees. Whether it be records of employee hours, tables of recruiting expenses, or innovative methods to calculate productivity output, new forms of data calculation emerge every day to help improve the HR experience for both HR professionals and their companies.
Simply put, data driven HR is a way of relying on facts and figures rather than gut feelings. Though HR is the practice of working with people, its strength lies not in its people personness but rather in the value of its analytical skills. At a time when everything can so easily be recorded and accessed, there is no reason why HR should fall short of the technological marvels of our time.
One of the reasons why HR professionals might still be reluctant to switch to a heavily data-oriented model is that this change can bring with it uncertainties and feelings of overwhelm. And we get it: introducing new spreadsheets, websites, or AI softwares to practice can make things more difficult before it makes them easier. With more systems to learn, information to input, and statistics to follow, the margin for human error increases.
But once it’s all been said and done, and the practice has been converted to a data-driven one? Then there’s no looking back – you’ll be surprised how much more efficient everything feels, wishing you had attempted the switch way before.
Questioning where to begin? Here are some of our insights into whether you might need to adopt a more data-driven HR model, and how to make the change in a way that fits your company structure:If you’re struggling to translate the company vision into quantifiable goals,
Then chances are you need to be thinking about how your corporate milestones would look like as numbers such as revenue, market value, and productivity increase rates. Figuring out key statistics to work towards, and inputting them onto digital softwares, will help you truly align with company objectives rather than ‘embody’ them on a subjective level. Working towards tangible goals will ensure that you are carrying out all practices with the company’s vision in mind.If workplace productivity has come to a halt,
Then you might want to implement similar changes on an employee level. If employees are simply working towards a ‘vision’ rather than quantifiable objectives, levels of output between every employee is bound to be drastically different. Having clear objectives that can be measured analytically allows not only the employees but also the HR department to calculate output more effectively, later using this data to decide on the best practices that improve employee productivity.If you can’t seem to be able to measure up to the rest of the market,
It might be that your business is struggling to adopt innovative practices. If the rest of the companies in your field are advertising on TikTok and your corporation is just about getting started on Instagram, chances are you aren’t being as effective as possible in measuring business growth strategies with the best outcomes. Analytics data can be used here not only to increase the flexibility of the current workers, but also to hire new employees who will add to the growth of the company. Data-driven hiring systems can help you find the best suited innovators, assessing potential employee collaborations before the candidates have even started working for you.If you need a way to decide on what’s working and what’s not,
Analytics can help you figure that out too. With data-driven models you will be able to asses trends in both success and failure, predicting outcomes before they’ve even happened and allowing you to drive your funds towards the areas that work the best. And when you have allocated the HR budget on growing the areas that do work, you will increase those success rates and reduce the failures.
Wondering how to go about it? Here are 3 foundations that can help you get started
Allocate a sufficient portion of your data technology on gathering people analytics
As an HR practitioner, you are only as good as the collaborations between your employees. So when getting started on data-driven models, it’s best to start with employee relations. Statistics in this area can help solve all kinds of issues, in fields from retention to productivity to teamwork. Quantifiable data on which practices have been working and which ones have not is invaluable in helping your organisation go that one step further in moving from insight-based strategy implementation to fact-based strategy implementation.
When you have the analytics, interpret them and integrate them into your practices
Of course it’s not how much data you have, it’s how you use it. Make sure you assess your employee data thoroughly, keeping an eye out for the unexpected trends. Did Team A work especially well with Team C on Project 1? Perhaps there is more to unearth there, and perhaps these two groups should be put to work together on another project. But when they collaborated again on Project 4, did they only reach half the previous level of productivity? Perhaps the objectives of Project 4 were not clear enough in allowing them to identify quantifiable goals. When you have all of this data, don’t just glance at the surface but dig under it to make better informed decisions.
Take it one step at a time
If this all seems a bit too overwhelming, start by identifying one problem at a time. Focus only on a specific area that needs improvement, and start gathering data related to that. Prior to analysing the outcomes of the data, focus on 3 hypotheses that you have about the problem. Then, while analysing the statistics, look at whether your theories were correct (or the percentage as to which they were correct). Then gather more data on the same issue and double check your previous findings, confirming their outcomes once again. Based on your insights, make one to two HR recommendations about data-based strategies that could be implemented to solve the original issue, and make sure to give company executives plenty of numerical evidence as to why you reached this conclusion.
So what are you waiting for? Switching to a data-based HR model might feel difficult in the short term, but will save you so much time and money in the long run!