Rimes panel: Global data management trends in a time of crisis

On July 28, 2020, Rimes hosted a debate on global data management trends in the financial sector. The debate marked the publication of the eighth Rimes’ annual Buy-Side Survey and the virtual panel comprised Ambika D’Souza, VP Performance & Analytics at T. Rowe Price; Jonathan Hammond, Partner at Sionic; Rob Middleton, Target Operating Model & Data Director at Royal London Asset Management; and Sylvain Pendaries, Head of Data Governance and Strategy at Janus Henderson Investors. The session was moderated by Andrew Barnett, Global Head of Product Strategy at RIMES. What follows is a summary of the main points raised during the debate, which took place under Chatham House Rules.

Summary of the survey

The session kicked off with a summary of RIMES’ 2020 Buy-Side Survey. Conducted between February and April 2020, the survey garnered more than 100 quality responses from asset managers, servicers, and owners from across the globe. As the survey took place during the emergence of COVID-19, it provides an early insight into how the pandemic is impacting buy-side firms. The eighth edition of the survey, the results are also useful in understanding industry changes year-on-year.

The main findings of this year’s survey include:

• The size of the data management team in buy-side firms is growing in the US and shrinking in Europe, the Middle East & Africa (EMEA). Data management headcount in Asia Pacific remained comparatively stable year-on-year
• Sourcing new types of data, such as Environmental, Social and Governance (ESG) data is now a key priority for firms
• The focus of data governance is shifting from traditional ‘policies and procedures’ capabilities to ‘measuring and monitoring’ capabilities
• Interest in blockchain as a potential data management tool has declined year-on-year, whereas interest in AI and data lakes/warehouses has jumped
• The importance of managing data costs for asset managers rose rapidly after the World Health Organization recognized COVID-19 as a pandemic.

The impact of COVID-19 on buy-side operating models

When lockdowns were initiated, buy-side firms were quick to set up remote working capabilities. This enabled workers to re-establish close to normal levels of productivity. The benefits of home working are increasingly appreciated by employees, and it’s likely that elements of this working model will remain in place long into the future.
However, the global slowdown is affecting firms as CEOs look to cut costs where possible. As the true cost of data management is often not fully understood by the business, important data management initiatives are being side-lined for more visible strategic deployments with simpler business cases. Where data projects are being funded, it is for big-ticket data lakes and analytics projects to help firms understand shock events and their impact on financial markets.

Cost control in the face of data explosion

New sources of data are coming into the market continually, and threaten to increase data costs significantly. To help manage and contain these costs, firms are becoming more interested in data provenance and lineage. The goal is to identify a single source of truth for market data for use across the firm in order to eradicate data duplication and the associated cost inefficiencies. Another area where firms are looking to cut cost is through reducing instances where the same data is taken from multiple sources. In good times, multiple data sources are useful for comparisons, but in lean times they can be considered an extravagance and should be reviewed as part of broader rationalization conversations.

The key to success in cost management is having complete visibility of data use within the organization. In addition, data management teams need to be expert in the contents of data as this knowledge will help them make informed decisions about which data sets to keep.

Data costs are also rising because the definition of market data is expanding to include new data sets such as ESG. To help tackle this, firms should move data into a central place and control who has access to what.

Outsourcing data management can help firms realize cost control, and significantly the Buy-Side Survey revealed a threefold increase this year in firms looking at outsourcing as a data management cost control mechanism compared to 2019.

Measuring the success of data governance

The first step in effective data governance is to understand what success looks like. Firms need to define data governance standards and put in place a common language and governance framework across the organization. To add real value, data governance must be linked to clear business outcomes, and that requires input from business users.

Another key element is that governance efforts are sponsored by people from the highest levels of the business. Not everyone in a buy-side firm understands the importance of data governance, and some may see it as unnecessary bureaucracy. Senior management support is vital in helping to build an organization-wide understanding and culture of governance.

Building trust in data is all about provenance and lineage. However, firms are moving to a model where data governance is becoming a cooperative endeavour between data managers and operational users. These relationships need to be managed in the right way to ensure they work smoothly.

The future of data management

Robotic Process Automation (RPA) is likely to play an increasingly important role to help firms reduce costs and turn data into more of a commodity. From an organizational perspective, it’s possible that data will become an issue for all, rather than one of concern only to the data management team. Self-service will play a role in enabling this change: rather than waiting for data reports, operational staff will be able to query a single source of data themselves, using intuitive tools, so they can proceed with their core tasks more efficiently.

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