Data as a Service Requires a Mindset Shift06.08.2021 By Markets Media
Data As a Service is Not Just a Paradigm Shift; It is a Mindset Shift
By Ramesh Rabadiya, Global Strategy Data Management, Director, SimCorp
As buy-side firms re-emerge into the real world and to their offices, one of the key priorities on the agenda will be to address the escalating complexity around data management. This is especially important as over the past 15 months we have witnessed one of the most turbulent and volatile periods in global financial markets. The resulting impact has been detrimental for operational resilience, affecting processes across the investment chain, and ultimately the bottom line.
As with all forms of adoption, there are already front-runners who recognize the significance of data management as critical to investment management and to delivering a competitive advantage. In 2019, the Investment Management function of Zurich Insurance Group took the decision to optimize its operating model, moving to a new future-proof way of working; Data as a Service.
In this article, SimCorp explores some of the key themes that emerged in a recent interview with Zurich Insurance Group (Zurich)*. We know technology plays a key role in operational change, but it appears there is also an equally critical human element at play. A mindset shift is necessary, if firms are to move away from inefficient and unsustainable workflows and towards a future-fit model.
Data is Central to Everything You Do
“As an investment function, data is central to everything we do. To get the right value from data, you need people who understand it, who can analyse it, and who can make the most out of it. We have a great team, but workdays are often not long enough to do all they could do with data.” Michael Kopf, COO, Investment Management at Zurich Insurance Group
One way to interpret this is that understanding the significance of data processes, means understanding that they underpin everything and anything you do in investment management, from investment decisions to reporting. But many firms are simply unable to connect the data challenges and resource constraints they face, with the resulting impact to the business outcomes they desire. No asset manager is in the business of data management, yet data sits at the core of every workflow in the investment chain.
Much of the data challenges experienced by buy-side firms can be chalked up to the limitations of traditional data management operating models. Today, there is a growing divergence caused by the lack of scalability and cloud readiness, making it far more difficult to accommodate the widening digital agenda firms are embracing. On an operational level, this equates to poor data quality and inadequate coverage of a fast-moving market, whether it’s exposure to new instruments and asset classes, or automating the new market and reference data that flood investment management systems today.
Additionally, a widespread top-down mindset of data management as being ‘non-essential to alpha generation’ perpetuates time spent by staff on manual tasks, including data collation and exception and change management, thereby reducing time available for core tasks like insight creation. This not only impairs alpha generation, but also heightens operational risk and increases data quality and transparency issues.
In short, buy-side firms are stuck in neutral when it comes to data, and the need for one golden source of market and reference data across products and portfolios is more critical than ever.
Alongside this challenge is the need to increase capacity and capability. The general industry response to this in the past has been for firms to hire more resources to address capacity issues. But this approach is rarely sustainable in the long term, nor does it really address or increase capability. It is particularly ineffective when there is a desire to re-focus resources towards more high-value workflows that leverage skill and talent, or in cases where firms are looking to achieve growth and solve long-term outcomes, such as digitalization and innovation.
Data as a Service Requires a Mindset Shift
“We wanted to shift to a more outcome-orientated mindset, but our teams were too busy processing the data and simply keeping the lights on to focus on the bigger picture. This required a shift in mindset from simply making sure the data was on time and of high quality, to really looking at the function of the data and considering how to use it to create that additional value.” – Ruchir Verma, Head of Global Services, Investment Management at Zurich Insurance Group
As most market and reference data is homogenous, there is often no value or advantage in obtaining and processing inbound data manually. Rather, firms need to realize that the value lies in the insights that can be gained from that data, which starts with acknowledging data as an asset that can support business outcomes. It also requires leveraging a holistic data management service that deliver the means to achieve this successfully, where traditional EDM model and outsourcing options cannot.
At its core, Data as a Service enables a firm to be less focused on the processes at play, and more concerned with the outcomes of that process, whether that outcome is a certain insight or an actionable investment decision. It traverses further than the traditional EDM models in the market today, inclusively delivering a combination of business operations, change management processes and advisory, as a fully managed service.
“We saw tremendous value in the advisory part of the service because the data landscape is constantly evolving. For example, ESG data sets are still changing shape, and having a partner who can advise on how to manage and incorporate these changes, and ultimately remain one step ahead, is extremely valuable.” – Ruchir Verma, Head of Global Services, Investment Management at Zurich Insurance Group
Having a partner provide expert advisory on a whole range of asset strategies and data types forms a key advantage for firms, helping them stay on top of industry, regulatory and market changes, and it can even become an extension of their own internal teams. This advisory component is not only a key differentiator, but also a part of the service that delivers the greatest support in responding to a continually evolving landscape. Combined with change management, the advisory service simplifies the onboarding of new data sets, as well as the implementation of new regulations, such as the incoming Sustainable Finance Disclosure Regulation (SFDR).
Building the Business Case Around Data
Achieving the move from process to outcome-oriented requires a significant mindset shift within operations, and also management. The following best-practice processes are critical to selling a strategic vision and creating a successful business case.
Keeping discussions focused on the requirements to achieve a desired outcome, such as improved decision making or automating downstream processes, rather than around functions and features.
Linking data management capabilities and value creation directly to business outcomes such as alpha generation or future growth. This firmly places data as an integral pillar of the firm’s strategy and a driver for change.
Finding allies within the organization who truly understand and have bought into this strategic vision. This requires helping people see the need for change on this scale, and then building the energy and motivation to embrace that change.
Making meaningful work a core objective within the business case. A stronger data management model allows employees to focus on what they are truly excited about, e.g. analytics and insight innovation, which in turn adds value to the business.
For firms considering inaction as the safest bet, the question is: what is the opportunity cost of doing nothing? What is the firm missing out on by not embracing change? For one, there is real cost, such as the cost of all the manual processes that resources end up working on day in and day out, and the subsequent alpha lost as a result of the excessive time spent here. But there is another more intangible cost to consider, that of staff motivation and happiness, which is not only compelling for employers, but equally significant for their success.
Data and Digitalization for a Future-Fit Model
If firms are able to overcome the mindset shift when it comes to data management and understand the opportunity cost of inaction, then they stand a chance at not only achieving operational resilience now, but also at positioning themselves more robustly in the future. One of the key benefits of Data as a Service is that it facilitates digitalization throughout the organization.
The creation of one source of reliable and accurate truth throughout the investment chain acts as a solid foundation for the adoption of newer technologies, which in turn can optimize and scale processes across the organization. The end result is a more agile and outcome-oriented business that can respond to markets, as they evolve. Further, the industry-wide adoption of cloud, as a scalable, future-fit operating model, has also become a significant driver in how the buy side tackles data management and the digital agenda.
Back in the here and now, the first step is for firms to recognize that data is a critical part of everything they do, and that it is a vital asset in driving business outcomes. That requires not just a paradigm shift in how firms operate today, but also a mindset shift, to create meaningful and lasting change.
Data management in itself holds no strategic value, and for many firms it’s a resource drain. But fast access to trusted data has the power to change everything. Empowering skilled resources to focus on data analytics rather than data processing, ultimately means more time spent on generating alpha, responding to markets and creating growth. That is the game-changing future of Data as a Service.
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