The Challenges of Data Migration

Introduction

I’m sure every one of you reading this has had to move home at least once in your life. Perhaps your old home was not big enough or didn’t have those modern, must-have amenities. The same can be true of your HR system. Whether due to organisational growth or a desire for greater business intelligence, your company’s needs may have changed and the time is right to make the switch.

When you move, the new building you find yourself in is not what makes personal belongings that do so. The same is true of your new HR system: what you take you with you when you move is what makes the system valuable to you and your organisation – and that is data, HR’s biggest commodity and the cornerstone for providing essential value to the business.

Data migration is a fundamental part of moving your HR home. The overall objective of data migration is to ensure you have a dataset in your new HR system that is complete, accurate and sufficient to meet the business needs. However, this comes with its own set of challenges, both business and technical.

The problem

Firstly, the business challenges. Data must be complete and accurate before you migrate it, otherwise what you move across will be of low quality. 

That means you identify the critical data points that you need, make sure there are no gaps and ensure that the data you do hold is correct. Furthermore, as an organisation you have to decide what data to take and what can be archived/left behind – taking too much historical data you don’t need makes the migration more complicated and can clutter your new system. Think of this as the box of old clothes that you take to the charity shop.

On the technical side, the complexity associated with data migration presents a unique set of challenges. It is common in a data migration project lifecycle to have several iterations to combat these as data will rarely all load correctly at the first attempt. These challenges include effective extraction of the data, getting the data mapping from source to target correct and ensuring consistent configuration of set-up data. A company may hold vast amounts of data, each a potential failure point, and it requires careful navigation.

Data migration

Data migration, like moving house, may sound daunting, but there is a recipe for success. Data migration projects need to have appropriate levels of senior management sponsorship to navigate the challenges that come with it. Sufficient ownership and drive are essential to ensure top quality, relevant data before migration takes place, which will help to avoid the issues detailed above.

All too often, bad data is permitted to pass with an attitude of “we can fix it later” to ensure the technical go-live of the system is not delayed. However, this will affect workflows, processes and consequently, the reputation of HR as a trustworthy source of data.

This kind of tunnel vision that focuses on system set-up and chasing the go-live deadline is a bygone idea. Modern HR needs to re-prioritise data quality and be mindful of data’s position as a critical workstream in HR system implementation.

Conclusions

When moving house, you hire the removal company that you can trust will get your valuables to the new place safely. Given its value and the complexity of moving it, you should apply the same approach to your data as you would your antique vase. Here at Epicenter, we understand the problems companies face in trying to keep to project deadlines while ensuring a successful data migration. This is why we have developed a set of data migration tools and services to facilitate the fusion of quality and efficiency in projects, ensuring a quick, accurate and repeatable process by automating key parts of the chain including data loads and data validation.

To find out more about our data migration services, you can contact us. If you would like to read more about data’s role in HR and the importance of data quality, we just released a White Paper about the Future of Data and Analytics in HR which you can download for free here.