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HR Data Management: Ways To Make It Easier

March 31, 2021

HR data management shouldn't be a problem within your organization, but it probably is. You have lots of data in all shapes and sizes (and places, and purposes, and overlaps, and more!), and that can be overwhelming. But, we promise you that managing your HR data is easier than you think!

In this article, you'll find ways to make HR data management easier. Hopefully, this helps you to take advantage of the real benefits of one of your company’s greatest assets.  

Types of Data 

Within your organization, you have many types of data about people. In buckets that might be called talent data, workforce data, or HR data, you will find data about jobs, learning, skills, performance, output, writing, networks, demographics, diversity, tenure, promotion rate, engagement and so, so much more. 

While these are all different, they are all key parts of the full picture of the workforce and the talent market.  When they're used as a single dataset rather than silos, you’re able to gain deep insights into your organization. 

In fact, often, only one type of data is not enough to get a complete insight into a topic area. For instance, consider that you have a turnover rate of 20%. Here, you probably used structured data to determine this percentage. Yet, you won't have any insight into the reason for the turnover rate without interviews (or unstructured data). You won’t even know whether 20% is a good result or a bad one for your company, job, or industry.

With integrations (and a data lake), your records can be connected for a single data set. Understanding this is an important part of HR data management. In the same breath, good hr data management is key to using different types of data together.

Making HR Data Management Easier 

Here are some steps you can take to ensure your data is not difficult to manage. 

Keep All The Valuable Data 

Here’s how you can think about HR data. 

In the past, people would consider which data might bring actionable insights, then keep that data and let go of the rest. This is no longer how things are done. These days, you simply need to focus on gathering data. Your systems and staff can harvest whatever insights they need, whenever they are ready.  

Always remind yourself: you never know what data you might need in the future, so preserve and curate as much as you possibly can. The only real reason to get rid of data is for compliance reasons, and even then you might prefer to anonymize or deidentify it.  Sure, archive if you must, but active storage in your data lake doesn’t cost any more than archive costs.

As long as you have systems in place ensuring that your data is current, clean, and curated, then you'll be fine. By doing this, you won't have any decayed data being stored, nor will you have any redundancy. 

You may be concerned that managing all of this data will be difficult, but it really isn’t. All of this HR data management is automatic and self-adapting, so you don’t need to be concerned about that at all. 

Ensure There Is Adequate Access To The Data

hr data management

Image by George Becker on Pexels

Another aspect of HR data management requires you to focus on access. Specifically, you need to ensure people have access to the data they need, where they need it. 

For the purposes of analytics and making predictions, more data is better. This means that your analysts and data scientists must be able to get their hands on as much data as possible. With increased access to data, they can provide you with answers and insights to your business queries faster. 

There is a need for easy access on a smaller scale too. For instance, recruiters may need easy access to candidate information. 

At SwoopTalent, we believe that convenient data is of utmost importance. Our browser extension allows you to see across systems.  Our browser extension allows you to see across systems with ease. You will have access to rich data and links whenever you need it too.

Use Data Hubs On Top Of Data Lakes 

HR data management has never been easier than it is today. With technology like data lakes and data hubs, your data is always structured and packaged as effectively as possible. The two systems can work together to ensure data is accessible, easy to use, and beneficial.

Other Steps to Take: 

There are also some smaller but equally important points to remember when it comes to HR data. 

  • Make data management be an important part of your strategy, not just a line item on separate projects - your data is THAT important.
  • Ensure people get the maximum possible set (that they have permission to see).
  • Keep a visual map of every system connected to your data lake, including your roadmap to add more.
  • Analyze your data trends, ideally with machine learning.
  • Use anomaly detection for hygiene.
  • Ensure that you're following the law in relation to the storage and destruction of data. 
  • Always ensure that your data is of high quality. 
  • Security of data should also be a priority. This is required by law, and most candidates appreciate security too. Your vendor, like SwoopTalent, can easily take care of that for you. 

hr data management

Image by Gustavo Fring on Pexels

Final Thoughts 

HR data management is a critical part of success in AI, machine learning, and analytics, so you need to place it right at the top of your strategic priorities. By taking a strategic, leading view with an approach like a talent data lake, your HR/people/workforce/talent data can be in optimal condition. Then you can always maximize the benefits that you leverage from talent data. 

You will have easy access to data, a leg up on AI and machine learning, easier system integrations and migrations - and analysis will be a breeze too. The best part is that you don't have to go it alone in the HR data management process. SwoopTalent’s amazing platform automates it all. Contact us today!

Main Image by Pixabay on Pexels

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