New findings from Adox Research has warned asset managers and investment banks that cloud deployed, insight-driven data management will become the mainstream model in two to five years time, leaving legacy on-premise solutions to collect dust.
But the research conducted, which surveyed c-suite executives in 2018, found that the largest concern around adoption was in integrating with legacy platforms at 56%, greater than price/ROI at 41%.
Despite this, Gert Raeves, research director at Adox Research, advises against ripping out and replacing existing data management capabilities.
“A phased-in adoption is not just feasible, it’s unavoidable,” said Raeves, in a recent webinar.
“That being said it’s all about the speed at which change happens. In two to five years’ time that gradual adoption will get us to a stage where this becomes the mainstream model while having on-premise traditional data management will become islands,” he said.
For Raeves, the real challenge lies in changing the attitudes of stakeholders – of which, he believes should encompass more parts of the business, given the growing mission critical importance of data management. Likewise, this is how firms should decide how to phase-in the model.
“There’s a new picture starting to emerge,” said Raeves “a picture of data management that matters to traders, portfolio managers and risk officers rather than just to operations and IT.
“We’ve all sat in those rooms where heads would nod when we talk about data management as a very obvious operational burden. You need to pull in those business stakeholders – the chief risk officer, the investment and trading desks – and get them to see data as a genuine differentiator and competitive benefit,” said Raeves.
And adoption of the insight-driven data management model is already underway, according to Martijn Groot, head of strategy at Asset Control, the data quality software solutions company.
“We’re seeing more and more business users directly accessing platforms and technologies,” said Groot, on the same webinar panel. “Not too long ago you had specialist operations IT team that acted as a buffer middleman who dealt with dataset mining.
“Now, a lot of these users want to go direct [from various parts of the business] because they know what they need and want to go to source directly or they want it faster with programmatic integration with business processes,” he said.
To hear more about insight-driven data management, the current challenges and the application of machine learning and alternative data sources, listen now to the webinar on demand: Mapping the opportunities for insight-driven data management.