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Managed Services and the Evolving Operating Model

By Liz Blake, Global Head of Eagle Managed Services

According to a recent Experian white paper, ‘Building a Business Case for Data Quality’, 83% of organisations have seen bad data stand in the way of reaching key business objectives. In particular, the research identified lost sales opportunities, inefficient processes, and client relationships as among the more prominent areas affected, but also underscored that the internal impact can extend all the way to the culture of the organisation.

Nearly everyone today recognises the challenges created by the exponential growth in the volume, velocity and variety of data. How asset managers deal with this information glut, however, can dictate whether it presents an opportunity or a threat.

True data visionaries, for instance, will rethink their data function altogether to leverage the right balance of technology and services to instil newfound agility and ensure data is working for the business, not against it. This is in stark contrast to ‘incrementalist’ mentality in which asset managers simply tack new capabilities onto legacy systems and fight an ongoing struggle to keep pace with mounting internal and external demands.

The rise of managed services runs parallel to the transformation trend occurring across the industry as organisations seek new ways to streamline existing processes while making their data actionable through enhanced reporting, timely insights and evidenced-based decision making. It’s against this backdrop of transformation that managed services is equipping chief operating officers with a new paradigm to conceive a global operating model featuring scalable cost-effective solutions that solve current needs and future-proof the organisation as requirements evolve.

It is sometimes difficult to conceive the extent to which bad data can affect the culture of an organisation. In fact, it’s often not until after a transformation is complete and new capabilities have been put in place that the larger enterprise fully appreciates the advantages of a sustainable and robust data solution.

In one example that I will outline, Eagle Managed Services was tapped by a global asset manager whose internal data function effectively served as a triage unit to reconcile and resolve data errors. On certain days, the errors and false positives might number in the thousands over a 24-hour cycle. Given the capacity issues, in large part due to poor data quality, the data process was managed on a monthly basis. This only magnified the pressure to validate the data and deliver it in a timely manner across the enterprise.

A baseline analysis helped identify the breadth of the problem. We also supported testing for the upgrade process and ultimately took over the file and the data monitoring function. The number of errors, in short order, was reduced significantly and following the systems upgrade, we incorporated daily controls and automated data quality checks. In addition to providing a permanent fix, this accelerated the pace at which monthly reporting could be produced for both internal and external clients.

More importantly, though, the data management function, with the support of managed services, became a strategic asset to the organisation as opposed to a bottleneck and source of scepticism. This is just one example and it only scratches the surface of the types of capabilities a managed services offering can impart. But it speaks to why so many organisations are rethinking their global operating model. And for many, managed services has simply become part of the buy versus build analysis that accompanies any new investment.

At our recent client conference, one of the speakers noted that before any operational decision is made ‘we will ask ourselves, is this a core competency?’ The speaker further explained that if it’s a function that can be managed by a vendor with specialised expertise, ‘money will be better spent on someone on the research side, seeking alpha’.

While it seems cut and dried, once an organisation recognises its core competencies and acknowledges those areas that may reside outside the core, that’s the first step to becoming a true data visionary.

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