About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Managed Services and the Evolving Operating Model

Subscribe to our newsletter

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.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: How to organise, integrate and structure data for successful AI

25 September 2025 11:00am ET | 3:00pm London | 4:00pm CET Duration: 50 Minutes Artificial intelligence (AI) is increasingly being rolled out across financial institutions, being put to work in applications that are transforming everything from back-office data management to front-office trading platforms. The potential for AI to bring further cost-savings and operational gains are...

BLOG

Strong Governance, Privacy Policies Can Negate AI Risks, Informatica Says

Debate about the limitations of artificial intelligence (AI) in data management was stoked further this week when a leading vendor warned that applications built on nascent large language model (LLM) technology could pose an “existential threat” to companies if not deployed thoughtfully. Jason du Preez, vice president of privacy and security at cloud data management...

EVENT

TradingTech Summit MENA

The inaugural TradingTech Summit MENA takes place in November and examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions in the region.

GUIDE

Corporate Actions USA 2010

The US corporate actions market has long been characterised as paper-based and manually intensive, but it seems that much progress is being made of late to tackle the lack of automation due to the introduction of four little letters: XBRL. According to a survey by the American Institute of Certified Public Accountants (AICPA) and standards...