Legacy platforms and cost of change are biggest hindrances to data management

d that legacy data platforms are the biggest obstacles to improving their data management and analytics capabilities, according to research from Asset Control. Whereas, for 31%, the cost of change is seen as the biggest hindrance to progress.

The poll of finance professionals, conducted through Adox Research Ltd., also revealed that for more than half of financial institutions (56%), the integration of legacy systems is the biggest consideration as they plan investment in future data management and analytics capabilities.

“What we’re seeing is financial institutions being held back by legacy data management platforms which they have acquired or developed over the years. These systems can slow down organisations as they are costly to maintain, miss audit or lineage information, often cannot scale to new volume requirements, and do not quickly and easily provide business users the data they require. While businesses recognise there is a need to update their data management systems they are sometimes reluctant to do so due to cost of change and perceived difficulties of integrating their systems with new solutions. Although I understand where these concerns come from, businesses also see the risks posed by inertia,” says Mark Hepsworth, CEO, Asset Control.

However, when it comes to considering new data management and analytics capabilities, firms remain focused on the fundamentals. More than a third (36%) of respondents cited ease of use and flexible deployment as their top business consideration, while 41% deemed ROI to be the biggest determiner.

“It is clear that while firms are currently being held back by the cost of change and legacy systems, they can see that both these challenges can be overcome with the right solution. While ROI is, of course, important in any business, these organisations must also consider how much their current data management systems are holding them back by delaying processes, lowering productivity and causing data discrepancies because they lack a clear and comprehensive view on their sourcing and validation process,” adds Hepsworth.

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