3 Actionable Ways in Which the HR Data Management Process Can Be Changed for the Better

Using data management to usher in the future of Human Resource

It can’t really go on the way it has!

That’s the general sentiment of most data analysts and data scientists, when asked about how well the Human Resource departments of today use the gold mine of information that they are sitting on.

The call of the day is – Intelligent HR.

And the concept is very succinctly put forth by Bernard Marr in his book “Data Driven HR: How to Use Analytics & Metrics to Drive Performance”.

Data-Driven HR: How to use Analytics and Metrics to Drive Performance
Data-Driven HR: How to use Analytics and Metrics to Drive Performance

While the human factor puts the “H” in HR, and will continue to do so, metrics and a Human Resource dashboard are gamechangers pushing the most progressive brands around the world to take HR decisions that seem unconventional but prove to be wildly effective.

Google installed sleep pods in its office because employee data showed the importance of power naps in promoting heightened cognitive functions and facilitating brainstorming.

The recruiters at Marriott Hotels would have overlooked an active talent sourcing medium – their Facebook page – had they relied on the number of CVs trickling in, instead of the number of offers made to candidates, by channel. They boast the largest “Careers” page on Facebook, which does an excellent job of mirroring Marriott’s informal, friendly yet luxurious vibe.

The bottom-line is, Human Resource data isn’t just about hours logged or vacations booked. If managed right, this information is poised to tell very compelling stories addressing C suite HR concerns like productivity improvement, retention boosts and leadership development.

Doing “HR Data Management” Just Right

#1 Transition from Hoarding to Choosing

The sheer volume of data flowing in from different employee touchpoints within a company can be overwhelming. And HR data management professionals tend to fall victim to the sentiment, “the more, the merrier”. However, it is better to vote in favour of immediate actionable insights than angle for hyperbolic future pay-offs which take years to materialize and store inputs that promote redundancy and eat database space in the meantime.

You can squish 50% or more out of the primary footprint of almost any kind of data, including databases

Across the board data storage minimization is considered a precursor to improving data efficiency. While there are many ways to go about minimizing the existing volumes of data in storage – like deduplication, compression and virtualization, the best way to work with inputs that yield results and boost ROI is to start with “why”.

  • Why is the data important?
  • Where can it be stored?
  • Are there immediate gains to be had from crunching and analysing the data?
  • What OKRs will be impacted with the help of the insights that the data can reveal?
  • What is the shelf life of the data? Some data sets are seasonal and can be leveraged only to affect certain changes or capitalize on particular opportunities.
  • How will employees be impacted by the decision to store the data?

With integrations abounding, often data management professionals do not get to choose the data they store. The simple rule of 70-20-30 comes to the rescue here.

70% of integrations with other business systems should funnel data related to the daily actions of employees. 20% of integrations must focus on interpersonal interactions, and interactions of employees with customers. 10% of integrations should bring numbers related to formal training and direct employee performance to feed and enrich the central HR database.

#2 Data Validation is Not an Afterthought

Data entry errors and omissions characterize human effort.

While keeping integrations in tight check helps minimize the storage of data sets that might not impact bottom-lines, it also invites the possibility of data corruption because of human intervention.

To maintain integrity of the information that is being used to influence HR policies, Human Resource information systems must have data validation rules.

It can be something as simple as ensuring that the country codes of the mobile phone numbers of employees match their location.

Or it can be a more sophisticated check like automatically referencing the sick days count of a worker when a manager tries to input the value of bonuses or benefits. An error doesn’t have to be a glaring mistake. Innocuous oversights can also snowball into uninformed HR decisions.

#3 Employee Data Security is the Biggest Concern on the Horizon

With privacy regulations like the GDPR, a breach from the outside isn’t the only issue that data specialists and managers are grappling with. Inadvertent access to what is considered “sensitive information” is reprehensible as well.

Any company storing employee data needs to consider the following mandates:

  • Data must be collected with employee consent. This is another reason why rampant integrations picking up employee details from platforms like Asana and Slack must be dealt with carefully.
  • Employees have the right to view personal records that a company has stored. There must be the ability to pull a comprehensive document, spanning the systems that interact with workers and store related information, and present this compilation to employees – on demand.
  • Sensitive personal information includes biometrics, ethnicity, performance review and annual assessment data. These are inputs that can be viewed and subsequently processed only by executives who can justify the need to do so. Data storage systems and databases have to go beyond encryptions to keep out malicious entities and thwart phishing attacks and graduate to evaluating access levels and permissions too for company staff too.

The ball doesn’t stop here though.

The final step in the HR data management process is insight consumption.

Good, clean, protected data is not going to make much of a difference if the people who take Human Resource decisions can’t be enlightened by the resulting insights.

Data visualization is the first step.

Creating custom reports, the second.

And finally, databases have to interact with robust predictive analytics machines to complement human perspective and eliminate bias from the functioning of HR.

This is the future of Human Resource, and the big change we’re clamouring for.


HR management software app system CakeHR human resources
softwareadvice FrontRunner HRIS HR management software app system CakeHR human resources
HR management software app system CakeHR human resources
HR management software app system CakeHR human resources

CakeHR is a one stop shop for your HR management needs. With attention to user experience & making the software easy to use yet packed with loads of features we strive to make your HR management as easy as a piece of cake!

Written By

Norberts Erts

HR Degen and Product Marketing Manager at Sage. Former Co-founder of HR software company CakeHR (acquired by The Sage Group plc in 2019). Keep a sharp eye on HR, marketing, business, finance, science, technology, and the connections between them.