Time for a paradigm shift in data management

The post-Covid19 world necessitates a new approach to traditional data management processes: Data as a Service.

Read the article and learn about:

  • What is Data as a Service and why you should care
  • Can Data as a Service be adopted by any organization regardless of size
  • What to look for in a Data as a Service provider
Ramesh Rabadiya
Ramesh Rabadiya
Global Strategy Data Management, Director, SimCorp
Linkedin Connect with Ramesh on LinkedIn

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.

How can Data as a Service work for different size organizations?

Smaller, more regional players have fewer systems consuming information and therefore experience fewer data reconciliation issues.

However, such firms can struggle more when it comes to accessing and maintaining resources and knowledge. Additionally, these institutions often lack the operational support particularly across multiple time zones.

Data is also often not recognized as an asset but as a cost function. As a result, data management functions are not seen as strategic and therefore not invested in enough to become a business differentiator.

These firms often rely heavily on excel spreadsheets, hard-coded connectors and manual processes which are all very risky and do not allow the organisation to scale. This often leads to frustrating situations amongst management and business teams when data is either unavailable or incorrect.

Larger - and sometimes global - players tend to have progressed further on their data management journey. As a result, many are experiencing the impact of poor original setups. These include:

  • Systems that are expensive to deploy and maintain, be it in the cloud or on premise.
  • Upgrades that require both IT and business resources, leading to ‘do as-is’ upgrades rather than implementing and benefitting from new features
  • Systems that require skilled resources to manipulate, both for onboarding and BAU operations
  • A high turnover of data-management resources

Our experience shows that the business teams of such organizations expect data to be correct given the large investment made, and therefore get frustrated when data-related issues happen.


Finding the right fit – what to look for in a Data as a Service provider?

Of course, to be a viable option, a DaaS offering needs to remain data agnostic and vendor neutral, be easily plugged into any client’s ecosystem and offer the same, if not greater, flexibility and transparency when it comes to data mastering processes and information exchange.

We believe that, when executed in the right way, Data as a Service can be a game changer for firms who truly want to make the most of their data.

You should be able to tap into a pool of incentivized, industry experts who will not only manage your daily market data operations, but also improve your business agility to respond to new changes.

This represents a unique opportunity that is difficult to achieve in-house – at least not at a competitive price. Furthermore, the service costs should be fully transparent, and you should be able to appreciate how the partnership evolves with technology and industry disruptions and as your business ambitions grow.

Data as a Service is not simply about head-count replacement nor should it be seen as a technology solution with a potentially disparate add on operations but as a service ecosystem for data management with a continuously evolving team leveraging insights and trends gained from experiences, accessibility to experts when needed as well as innovating to improve processes for instance by investing in technologies for process automation such as RPA, ML, AI, etc.

In turn, DaaS clients will see significant improvements in their management and teams frustrations around reference and market data, in their ability to plan for, track and report data-related changes and their impacts on their investments and in their capacity to both look after processes that could be improved and to take on new business initiatives.