How Software Vendors can Profit From Smoother Data Migrations

As we noted in an earlier blog in this series, fear of data migrations – and how that is stopping financial institutions from upgrading to technology platforms that allow them to automate and digitalise their service offerings – is hobbling firms’ ability to modernise and grow.

Technology innovation proceeds apace. And the modern marketplace, with its ever-greater client servicing expectations and regulatory compliance requirements, demands that financial institutions keep up. Yet data migration difficulties make moving from one IT system to another fraught with financial, operational and reputational risk.

Which is why institutions are looking to their software system partners for help.

Migration worries stymie software vendors too

Firms’ hope, as we’ve witnessed on many IT upgrade projects, is that the software company they have just contracted with will take charge of bringing the data over during the system implementation. That may have been the case once. It’s less common now. And with good reason.

Data migrations have always been problematic. The pre- and post-migration data clean-up involved is often complex and lengthy.

Where they do undertake the task, software vendors typically charge for the time and effort involved in migrating the data on to their systems, amplifying the project expense. Many will no longer even do that.

Wary of being blamed if a system migration proves difficult, prolonged or ultimately fails, growing numbers of software vendors won’t start the implementation until there has been a sufficient degree of data validation. Rather than carry out the migration themselves, they may instead partner with a specialist third-party implementation team, adding a further layer of fees into the process.

The data migration opportunity

But there is a real opportunity for software vendors to differentiate themselves here.

Client experiences determine a vendor’s reputation in the market. Unfortunately, the user experience with many software systems ranges from middling to frustrated. Often that is not down to the solution per se, but the consequences of poor data in the platform.

Making implementation projects smoother, faster and more efficient, and completing them on time and budget, results in happier clients. And a system working off clean data that’s been properly migrated results in a much better user experience. It also produces a higher return on the customer’s technology investment. Clients then become much stickier for the right reasons, rather than because they are too terrified to move.

Similarly, easing prospects’ migration concerns will help get potential clients over the line during the sales process. That can translate into big wins.

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 software vendors 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 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, vendors 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 vendors 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. Seeing where and why an issue emerged and how to fix it also helps avoid repeating the same mistakes.

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

Software vendors in turn can burnish their reputation among clients and prospects as trusted system implementation 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.