Historically, organizations have chosen one of three routes to scaling and improving market and reference data management operations:
- Implementing and operating EDM systems
- Purchasing utility feeds
- Outsourcing data operations.
Despite the resources allocated to data projects over the last few years, many firms are yet to see the merits as they continue experiencing several pain points.
Turbulent times, such as those that we are experiencing today, only accentuate the need for access to clean and reliable information. It is therefore clear to us that organizations cannot go back to the old way of doing things.
While all three possible approaches have merits, they also share one key challenge: lack of agility to keep up with data-related market, business and regulatory changes. Furthermore, at many organizations, clunky data management, manual processes and legacy systems abound, making it increasingly challenging to respond to disruption.
The unfortunate result is that data analysts spend too much time manually sourcing, validating, correcting and distributing data sets that require deep domain knowledge and synchronization between systems. This is a clear waste of talent that could be routed to more value-added activities.
In this article, we build a case for Data as a Service as the ideal standard for the operating model of the future. We believe those organizations that explore this option today will be set up for success in the post Covid-19 world.
What is Data as a Service and why you should care?
Most asset managers use more or less the same financial data sources and apply similar validation rules to ensure they can rely on that source of information for further calculations. While many institutions believe they have unique requirements, most of the industry processes financial data in a similar way. What this means is there is little upside to investing heavily in a function that isn’t necessarily the most business-differentiating.
Training and maintaining both system and data domain knowledge is a costly function, averaging at 3 to upwards of 20 full-time employees per firm. On top of that, upskilling the team’s knowledge to cater for growth events such as mergers, new products or market launches and onboarding of new data sets is a very tedious and costly process – for very little upside.
On the other hand, having data that is clean, accurate and can be accessed rapidly is market-differentiating. As is the ability to implement changes to data easily. So logically firms should be diverting resources away from being able to store siloed data in house, and towards solutions that allow them to innovate and respond to fast changing market conditions.
One such solution is Datacare—SimCorp’s Data as a Service (DaaS) offering. It’s important here to differentiate between managed services and DaaS. While there are plenty of managed services in the marketplace, these tend to only host the technical operations for a company. That means they still suffer from all the shortcomings outlined above.
Data as a Service, on the other hand, not only encompasses the operational hosting, but also access to advice, analysis and change management services, which allow firms to actually act on the data they pay for. The concept is all about offloading the inherent risks and burdens associated with data management to a third-party, cloud-based provider. This means that rather than regional teams managing different silos of data, instead you have one central source of data that is expertly managed on your behalf– freeing up your analysts to more value-added activities.
The majority of my data team was engaged in change management, trying to understand technical as well as certain business changes, which was unnecessary and distracting from their primary duties. The ‘Data as a Service’ offering from Simcorp has helped us to take away this burden so that we could focus on more value-adding activities.Ruchir Verma, Head of Global Services, Investment Management, Zurich Insurance Company Ltd.