How Consultants can Profit from Smoother Data Migrations

Data migrations are central to financial institutions’ ability to modernise and grow.

Upgrading systems to keep pace with technology innovation is essential if firms are to automate and digitalise their service offerings in line with the needs of the modern marketplace. Yet data migration difficulties make moving from one IT system to another a perilous undertaking, fraught with financial, operational and reputational risk.

Which is why institutions are increasingly turning to consultants for help with their system migration projects.

Data migration work is a mixed blessing

As we’ve witnessed from our front-line work in this area though, data migration projects can be a mixed blessing for consulting firms.

Yes, they can provide significant work and help foster business relationships – especially given the scale and complexity of the tasks involved. But the (significant) risk of a troubled or failed migration can bring damaging reputational and commercial consequences for those involved.

So it’s imperative migrations are done well. Making the projects smoother, faster and more efficient, and completing them on time and budget, will result in happier clients. And happy clients are more likely to become repeat clients. By showing they can do a better job than their rivals, consultants can also build a competitive advantage in the space.

Sounds obvious, right. Making the grade in practice is not so easy unfortunately.

It’s all about the pre-migration

The key to a successful IT migration lies in understanding what data the financial institution has from the outset. Getting a clear picture of the state of a client’s dataset at an early stage, by identifying any discrepancies and missing elements, enables consultants to enhance the quality, integrity and consistency of the data before it is moved from point A to point B. That minimises the data errors and duplication that come across during the transition. Clean, uniform data also tightens the mapping to the new platform and makes it less complex to implement.

The big question is how best to do it?

One common method firms employ to achieve the requisite data validation is to commit bodies to the data cleansing tasks – often by running spreadsheets and comparing them against downloaded data and data scripts to check for discrepancies. And by dedicating people to the mapping, they aim to ensure all the necessary data translates across and goes where it should.

This kind of manual-heavy approach has obvious downsides. It takes time and consumes valuable resources – not to mention the potential for human error it introduces. Even where it seems everything has been correctly mapped, rogue lines of data that put a spanner in the works are inevitable.

The clean data solution

Automated data quality tools offer consultants a faster, more reliable alternative. An automated system removes the expense and variability of human checking. Data errors, inconsistencies and duplication can be identified much quicker, enabling staff to concentrate their efforts on resolving issues. By seeing where and why an issue emerged and how to fix it, users can avoid repeating the same mistakes. For the acquiring firms in M&A transactions, automated checks can also evidence where data problems lie and ease the integration effort.

Plus an automated data quality system is always on. It provides consulting firms with a 24/7 data analyst that takes no holidays, requires no training and makes no mistakes.

Consultants in turn can burnish their reputation among clients and prospects as trusted data migration partners, able to get the job done with maximum speed and minimum fuss. In an age of ever-growing IT and data dependency, the business opportunities it opens up could be invaluable.