Why HR should start to make the most of their data
Many companies are now using their data to find useful insights into their business, but are HR departments making the most of what they’ve got?
HR teams have a huge amount of data at their disposal. Drawing insights from this data can help to better understand its own workforce and drive positive business change. For example, data can show you what drives employee performance, when an employee is about to resign and how HR contributes to an organisation’s objectives.
The 2000 has witnessed a digital revolution where companies began to learn more about their customers. It was predicted at the time that there would also be a big evolution for HR, but the journey has only just begun for most HR departments. The possibilities and opportunities that data can provide is quite exciting. For instance, being able to recognise when a valued member of staff is thinking about leaving is an extremely valuable tool for businesses.
Why have HR departments yet to utilise the data available to them? It could be the result of ever changing technology. The speed at which it changes means by the time a system is functional, it could already be out of date. Also, the vast number of tools and amount of data can seem daunting and leave many businesses asking themselves where to begin.
Technology does advance so quickly that it’s important to start small before deciding which direction to head in and which areas you wish to learn about first. Instead of implementing a large system and connecting all departments, it’s better to find out the basics first by using the data you already have available and begin to explore from there.
Over the past year, Hays too has begun exploring advanced machine learning to manage its data. Data was collected about many aspects of their business with the recruitment firm developing algorithms and models to process this data and helping to identify key development opportunities. The expectation is that this will be of value to both of us and our clients.
This article was originally published on Hays.
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