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HR Data Health

HR Data Health was never easier to maintain. We help you standardize the data across your different HR systems, by mapping different data fields to a common format. Then, we show you a list of any missing or incomplete employee data as well as ways to fix those issues.

Race past the hurdles, we’ll do the double checking for you.

Always know what data is missing, get notified of any changes, and have total confidence in the reports you share across your company.

Your data is 0% healthy

Overall health score

Overall data quality score

Get an automated review of how well your data from multiple sources are mapping onto metrics and insights.


One of the top barriers to wide people analytics adoption is data quality. No more. See how your metrics are being build and have a quick and easy way to fix the reports and insights before sending them to your stakeholders.

icon attributesAttributes

Distributed data health KPIs

With your data ingested and normalized, we know exactly which data attributes are missing or need some love to get your metrics and insights to work. 


Customizable permissions ensure that reports are generated to the right members of your HR teams so that they can tend to their data quality issues to help maintain perfect metrics reporting and insights. With distributed responsibility for data quality you will be one step closer towards building an evidence-based practice in HR.

Reports

Weekly data quality reports

Keep a regular cadence on managing your data health, and prevent data debt from piling up as you scale your organization.


Get scheduled data quality reports to know if any changes in your employee records might impact the quality of your insights. Capture missing data, wrong inputs and outliers to make sure you have the right data to tackle the most important people challenges.

Data health score

Data health per metric 

Every metric comes with a data confidence score based on the quality of its component attributes


Now you will know how much you can trust your report before sharing it with the rest of the team, executive leadership or the board. Plus, you can inspect every metric down to employee level building blocks. 

Game changer for SMBs, reliable partner for Enterprise People Analytics teams

For HR in a scaleup

If you are an HR in a scaleup that uses several different tools from HRIS and ATS to manage your HR processes, you can hop on Orgnostic and get free data quality checks. It’s a piece of cake.

For Enterprise PA team

For Enterprise People Analytics team -we allow you to proactively manage data quality by sharing the data quality KPIs directly to users who are generating that data. Have a constant pulse on your data health and nudge users to take quick action.

“Orgnostic gives us a unique opportunity to manage employee data efficiently, right from the start, by ensuring that we have all relevant data in the system, complete and accurate. Every time we make an update or correct what’s wrong or missing, we get a better insight into what we are really looking for — whether it is headcount metrics or diversity metrics.”

FAQ

What is data integrity in HR?


Data integrity in HR refers to the accuracy, consistency, and reliability of human resources data. It ensures that the information stored in HR systems, databases, and records is complete, correct, and up-to-date.

Why is data integrity important in HR?

Maintaining data integrity in HR is crucial for various HR processes. It serves as the foundation for reliable decision-making, enabling HR professionals to access accurate and up-to-date information that ensures fair and effective recruitment practices, seamless onboarding experiences, precise payroll management, objective performance evaluations, strategic succession planning, and productive employee relations.

Prioritizing data health safeguards the organization from costly errors and inefficiencies. By consistently validating and maintaining the accuracy, consistency, and completeness of HR data, organizations can minimize risks associated with inaccurate reporting, incorrect compensation calculations, compliance violations, and inadequate workforce planning.

How to ensure data integrity in HR reporting?

To ensure data integrity in HR reporting, establish clear data standards, implement validation checks, and enforce user permissions and access controls. Conduct regular data audits, maintain data backups, and monitor data quality to detect and rectify any issues. Provide training to staff, document processes, and establish a data governance framework to ensure accountability and continuous improvement in data integrity practices.

How does Orgnostic help with ensuring data integrity in HR reporting?

We consolidate data from multiple HR systems into a single, consistent location. The data is pulled and broken down into its most basic quality attributes, and then normalized. This allows for the visualization and running of a unified set of metrics.

To correctly assemble and present the data as a metric, we map all the data attributes and define their functionalities. This helps us understand which data elements contribute to which precise metrics. Additionally, we can identify if specific metrics do not show proper values due to inadequate or missing input data.

This is the underlying mechanism of the Data Health Score that we present to you. You will see three different groups of data attributes: Needs Improvement, Missing, and Healthy. For each group, we show the score and steps on how to make improvements.

Our Data Health Monitoring is an ongoing process. Your data accuracy is updated on the go as you enrich the data in your HR systems. You can rely on us to always present you with an updated state of your overall data health, as well as precise directions on which data needs to be addressed.

You’re sitting on a gold mine. Time to extract it.

  • Combine data from multiple HR systems into one single, consistent location
  • Get actionable insights into which data attributes need improving
  • Ensure the quality of your reports and insights
  • Save time and gain confidence on your data accuracy and completeness
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