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Data Health Update: Cleaning Your HR Data Just Got Easier

Data cleanliness often blocks us from diving deeper into people analytics. Learn how Data Health takes the tedious work out of cleaning your HR data.

People Ops folks have enough on their plate. Recruitment, onboarding, talent development, compensation management, conflicts resolution, you name it. There is no planned time (or any time whatsoever) left on their hands for cleaning the data in their HR tools.

And as we all know by now — cleaner data enables more accurate HR metrics that lead to better organizational insights and improved HR processes.

Here’s how this update of Data Health makes cleaning your data easier through connecting data to metrics, listing items to update, and allowing you to enrich your data.

What is Data Health?

Orgnostic’s Data Health feature automatically maps all the fields in your HR tools (HRIS and ATS) that have missing data or hold incorrect inputs.

The cleaner this data is, the better the quality and accuracy of Orgnostic insights you can use to devise your strategy.

What’s new

Orgnostic is now enabling you to see the dependencies between the data coming from your HR apps and HR metrics. This should help you figure out what’s more important for you so you can start cleaning there.

Metrics are calculated based on data attributes that usually represent a field in your HRIS or ATS — things like employment status, ethnicity, contract start date, etc.

With this update, you’ll be able to see a section listing affected metrics on the left hand side for each card.

Metrics affected by unclean HR data
Metrics affected by unclean HR data

List of items to be updated

Previously, you could for example see the message “2 employees out of 96 have x” next to each data attribute that should be cleaned. However, it was unclear which 2 employees we were talking about. There was space for improvement.

We have now introduced a list of the exact items you need to update, for example a certain individual’s team, their missing PTO, compensation history, leave kind type, etc. on the right-hand side of each data health card.

List of items to be updated to clean HR data
List of items to be updated to clean HR data

We’ve tried to map this information to specific employees to make it more intuitive and easier to locate and clean in your HR tools. At the end of the day, most of the data you are collecting is tied to employees.

Note that you won’t be seeing the right hand side list with the list of employee names on data health cards in the Healthy section, because all of the data attributes are good.

Leave types and data enrichment

We are now also taking steps towards helping you enrich your data by allowing you to add information about your candidate and employee data on top of your existing data in HRIS and ATS.

For example, you can “enrich” your Time off request types by putting them into “planned” and “unplanned” buckets. On the right-hand side of the cards, you’ll be able to see a list of all of your PTOs that are not mapped to any planned, unplanned or “not a leave” groups.

Why is this important? It’s important as it directly affects multiple HR metrics such as Leave type distribution, Unplanned leaves and Cost of unplanned leaves, which are directly linked to the engagement and burnout of your employees.

Until we’ve rolled out the interface for you to set this on your own on the Orgnostic platform, we are inviting you to give us a ping through Slack or email, and we’ll set these up for you.

Orgnostic Data Filler surveys, which allow you to automate data enrichment, have also been updated.

You will now be able to see how many people have opened the survey. Of course, you should first start the surveys if you haven’t already.

New data attributes

As we grow and learn more about our customers, their needs and data, we are adding new data attributes our customers can track and update.

For this batch we are introducing:

  • Employee Location — see which employee entrees lack location information and improve multiple metrics in one update. This enables you to observe data based on location for Headcount Growth, Turnover Rate, Time to Hire, and many other metrics.
  • Current Salary — keep an eye on three components: amount, currency, and time period. You should track these if you want to have metrics like Headcount Cost, Cost of Unplanned Leaves, and others.

That would be all for this update, we hope that it will make keeping your HR data clean faster and easier.

If you would like to quickly find the HR data you need to clean, you can connect up to two data sources to Orgnostic for free.

If you have any questions or feedback, we’d love to hear from you. Reach us at [email protected]

Happy data cleaning!

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