The endless possibilities of HR process automation

And how to ensure your HR automation project doesn’t suffer from poor data quality

It has taken a while, but the business world seems to have finally realised that their people & culture function (a.k.a. HR) is not just some afterthought. Among the majority of managers, it is beginning to dawn on them that people & culture actually make all the difference. HR as their distinctive competitive advantage instead of just some administrative business unit. Enter the age of people & culture!

Now all is needed is HR starting to act accordingly. Our focus should be on core issues such as our employee value proposition, company culture, talent management, employee engagement and the well-being. Today's HR professional should no longer engage in mind-numbing operational work such as keying data into systems, approving timesheets, running repetitive reports and manually generating contracts.

Today’s state of technology allows for intelligent automation of almost all recurring operational processes and automating systems and workflows is no longer an overly complex IT-driven ambition. Nowadays there are countless ways and low-code solutions to fully automate tedious HR jobs quickly and stably. Technical knowledge has long since ceased to be the biggest challenge. And by now we all have a clear understanding of the significant benefits process automation offers in terms efficiency, accuracy, and cost savings.

So don't we have to worry about anything at all? There is one thing… By far the biggest challenge surrounding successful automation of manual HR work is your data quality. Availability and quality (reliability) of data is by far the most critical factor in the success of any HR automation initiative.

Poor data quality can lead to completely wrong decisions and misunderstandings, which can have a significant impact on your organisation's bottom line. For example, if an HR system is not collecting accurate data on employee hours worked, the organisation may end up paying out incorrect bonuses or overtime pay. This can result in legal penalties and would for sure affect employee morale.

Moreover, systems that contain poor quality data which is used to automatically finish HR tasks can also lead to compliance issues. For instance, if your HR system is not collecting correct data on employee benefits, you might fail to meet important required legal standards around expenses, or pensions. This can result in legal penalties and reputational damage to the organisation.

To ensure your HR has access to high-quality data, organizations must invest in data governance processes. Data governance involves establishing policies, procedures, and processes to manage the collection, use, and storage of data. This includes putting in place data quality standards, data validation processes, and data monitoring systems.

It is also recommended to invest in data quality tools and solutions to help automate data quality processes. These tools and dashboards can help identify and correct data errors, and improve the overall quality of the data being collected. For example, organizations can use data quality software to validate data as it is entered into HR systems, ensuring that only accurate information is stored.

In conclusion, data quality is a critical aspect of HR automation that cannot be overlooked. But with the basics in place and availability of high-quality data at your fingertips, you can only imagine the things HR can focus on that really matter.

worldofwork? - Jochem ter Steege