The true cost of data management for buy-side asset managers

By Alessandro Ferrari | 23 November 2015

The value attached to data for asset managers is ever increasing. In the past, data management was viewed as a mid and back office-only role, focused on timeliness, quality and accuracy, all while aiming to keep costs under control.

The burgeoning cost of data management combined with ever increasing demands on data quality, its availability and the efficiency with which it can be not only sourced but accessed all remain relevant business drivers.

Indeed, increasing associated costs and the potential for painful losses have been growing challenges for several years.

Beyond operational challenges, new strategic drivers are emerging that are increasing the data management burden on the buy-side.

There is a tide of change in progressive investment management firms: data management is rapidly becoming part of the C-level agenda owing to the recognition that ‘solving’ the issue of data management can unlock real value for the firm.

Firms are now facing additional data management challenges that include:

• Improving transparency and control to support data governance and evidence regulatory compliance
• Enabling and facilitating strategic business change
• 
Shortening time to market by increasing business agility and responsiveness.

But, firms need to understand the potential economic benefits of any course of action before committing to a significant investment. There is a perfect storm of competing data management priorities. How are investment management firms responding?

Increasing pressures for asset managers

Buy-side firms are facing increasing client pressure to acquire a larger number of data sets all requiring additional customisation. As the number of benchmark and reference data sources continues to grow, so does their complexity. Investment managers have to use a growing range of published indexes but also more complex customised benchmarks and blends.

There exists at the same time the need to meet more stringent regulatory requirements and the continued challenge to reduce operational costs.

This list of pressures is only set to grow.

Unfortunately, to date, accurately calculating the total cost impact of data management at buy-side firms has been the greatest challenge. As a result, it is becoming more difficult to support front office investment management teams and middle and back office analytics staff in their quests to both meet client demands and continue to satisfy the board.

Looking for answers

Data management is not a siloed task conducted by a handful of professionals. Instead the flows of benchmark and reference data around the firm are becoming more varied as demands from clients and regulators increase. This adds to the challenge of calculating the total cost of data.

According to the findings in the third RIMES Buy-Side Survey published a few months ago, use of data is growing beyond the core performance and data management teams. 80 per cent of risk departments and 63 per cent of compliance departments now regularly use reference and benchmark data (up from 59 per cent and 47 per cent respectively in 2014).

The needs of each individual department and the consumption of datasets are incredibly varied, with data differing in definition, quality level, required timeliness but to name a few.

The diverse range of functions using benchmark data for different purposes within a firm adds complexity.

With reliance on data across a breadth of teams, manual work-arounds and internal spreadsheets are rife. Very quickly, data management becomes a tangled web of processes and workflows that are hard to keep up to date and exploit, let alone uncover the cost to operate.

The devil’s in the data

When it comes to asset managers, data requirements and characteristics are different from other data types and thus its management requires specialist knowledge and expertise.

The array of data vendors that a single firm needs to engage with creates challenges such as presenting a variety of data licensing terms to manage. Each vendor may present its data in different formats which require manual effort to homogenise. 

A lack of standardisation creates a business challenge, from the onboarding of new indexes to the storing, management, and distribution of the data and its preparation for use by different business functions. As well as increasing costs, this can impair business agility and introduce opportunity costs.

In a nutshell, major issues are arising because there is a lack of standards or governance for managing the complexity of this data within a firm.

A proposed framework for understanding and managing the cost of data management

Working alongside Forrester Consulting, RIMES recently released a Total Economic Impact study to help asset managers calculate the return on investment and payback timescale when using a managed data service. The Forrester TEI framework has been designed to calculate the potential benefits of managed data services for any asset management firm.

The study adopted Forrester’s proven methodology to asses the Total Economic ImpactTM (TEI) of a managed service. It offers a robust framework and recognises that all benefits have a positive impact on the business even though qualitative benefits may be hard to enumerate in the short term.

Working with Forrester, RIMES has been able to create a framework that not only helps to map the associated costs of data management but also to dispel the myth that data costs relate to data vendor fees alone.

A closer look at hidden costs

Hidden costs can range significantly from managing data quality issues and consolidating disparate data sources, through to shadow investment in data validation and an inability to respond to client demands for new products.

It is critical to have a tool that is able to identify and capture all of the outlays associated with data management.

Without a data management solution, our clients frequently describe issues facing data quality and data timeliness issues. Significant time is wasted by performance and data operations teams on data validation and remediation in the face of these errors, in addition to ongoing data operations and ultimately the day job.

Quantifying the benefits of a managed data solution

Working with RIMES, firms are able to improve their productivity by as much as 20 per cent, and the composite organisation created in the Forrester study experienced additional savings in terms of productivity gains, cost avoidance of additional headcount, resource savings, data delivery cost reductions, and savings on legacy vendor services fees.

From the boardroom to the ‘shop floor’ the lid is being lifted on the pressure cooker. Teams can improve service levels and ensure quality data for disparate business functions consuming data. This oversight enables better management of the TCO (Total Cost of Ownership) of the full data management workflow and provide the business intelligence required to implement effective data governance processes and procedures.

Supporting the future of data management

Index and benchmark data are only destined to become more complex and as volumes of data grow and grow. Asset managers will continue to seek a reduced total cost of ownership in data management, whilst also continuing to demand greater responsiveness capabilities to respond to new business opportunities.

RIMES is committed to support asset managers with all their data management challenges. Ultimately, the key to unlocking the power of data within the firm is understanding it: what governs its use, who uses it and how the data is used.

Next steps

The Forrester TEI framework has been designed to calculate the potential benefits of managed data services for any asset management firm. We are encouraged by its power and flexibility and would like to help you measure the potential benefits for your own organisation.


By Alessandro Ferrari, SVP Global Marketing, RIMES

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