6 Tips To Help You Refine Your HR Data Strategy

Data is king in every industry. Being able to make data-driven decisions is often what spells the difference between business failure and success.

When it comes to HR, the situation is no different. HR teams can, and should, use data to make better decisions, better understand and analyze the business impact of people, and improve leadership’s decision-making processes when it comes to people matters.

UNLEASH’s recent “Why HR Projects Fail” report found that a staggering 84% of respondents had been unable to successfully launch an HR project. As a result of the research, UNLEASH identified eight golden rules that seek to help HR professionals overcome these challenges.

As you can probably imagine, not having access to clean or ready data was the most frequently encountered challenge for HR tech projects. In fact, almost a third (30%)
of respondents told us they faced this problem, and only 11% of those who did were able to report highly successful outcomes.

With this in mind, here’s why your organization needs unpolluted data and how you can actually go about cleaning it.

Why you need clean data

First things first, data cleansing is not as scary as it sounds. It essentially refers to the process whereby data is cleaned, tidied, or deleted.

Once this is done, you can rest assured that your business will be left with data that is relevant and accurate. You’ll be able to leverage people analytics and data to significantly improve your recruitment and employee experience.

So, whether you’re changing from one human capital management system to another, or simply digitizing your paper-based records for the first time, clean data is a requirement.

Setting quality standards

The first thing you need to do is think about the quality of your data — or rather what data your HR department actually needs.

Once you have this information, you can start thinking about what expectations you can set going forward.

For example, what KPIs are going to determine the quality of your data, how will you meet these, and how will you monitor the health of your data.

More importantly, how will you ensure data is healthy going forward?

Identifying risks

In order to move forward, you’ll need to asses your current data strategy — or lack thereof — to figure out where the mistakes are happening.

Identify the risks, raise them with employees, and establish a processes that minimizes risk.

Avoiding silos

Don’t work in silos. You need to remember that every single employee is a data point — and this data is relevant to each and every department.

Communicate with all teams and work with them to understand the root cause of the data health problem. Don’t work in a silo.

Establishing a process — and sticking to it

There are many reasons why your data can become ‘dirty’ or polluted — it only takes a minor, innocent, mistake to trigger off a domino effect.

This is why you need to establish a process that works for everyone in the organization. You’ll need to agree on how the data is collected and analyzed — and where it’s stored securely.

Think about how you want to clean the actual data. Some businesses decide do it all at once, but this can be time consuming.

It may be worth you concentrating on a specific segment of data that you need to carry out a specific HR analysis.

Be ruthless — don’t hold on to what you don’t need.

Monitoring progress

Once your process is up and running make sure you take time to monitor progress and identify any new potential risks.

Your data strategy will be an ongoing process that you’ll need to monitor and re-visit as your teams and business grows.

In fact, your data should evolve with the business. You may well find yourself adding extra data points as the company expands into new market or head count increases.

Download our ‘Why HR Projects Fail‘ report to find out how you can make your next tech project a success.