Performance Measurement: The Devil’s in the Data

What are the ingredients of the ideal enterprise performance measurement and attribution platform?

Rich Mailhos, Eagle Investment Systems: For some investment managers there are tactical reasons for running performance solutions at a desktop level but, increasingly, investment organizations are turning to centralized, enterprise-wide solutions with the aim of improving accuracy, timeliness and understanding of performance across the business. In order to realize these benefits, there are a number of attributes firms should be looking for:

• The elimination of performance measurement silos among asset classes. Firms need a single enterprise or consolidated solution that can be utilized for all account types, asset classes and currencies. Therefore, being able to consolidate information from disparate and diverse systems into one solution, from which performance across the whole investment book can be measured, is an absolute must.

• Given the limitations of the majority of accounting systems that feed performance systems, another vital ingredient is for performance solutions to support the enrichment of core data. This is an essential component in ensuring the accuracy of performance data and enables portfolio managers to analyze the true impact of derivatives and other instruments in their portfolios.

• The ability to undertake automated exception-based processes enables firms to focus on analyzing their data rather than generating it. It's a key feature for driving operational efficiency and reducing overheads.

Ultimately, it all comes down to the quality of the underlying data. It's the data that determines the accuracy, timeliness and reliability of measuring performance.

• Finally, the system should be flexible enough to support industry standard and customized calculations for even the most complex financial instruments.

What are the primary challenges facing buy-side firms when it comes to producing accurate, timely and reliable performance and attribution reports?

Mailhos: Ultimately, it all comes down to the quality of the underlying data. It's the data that determines the accuracy, timeliness and reliability of measuring performance.
Many firms have to contend with multiple legacy systems that make the production of such reports a difficult and time-consuming task, if it's possible at all. Even where the data in source data systems is clean, they often have difficulty providing that clean data when it's required. This is something that is true across all asset classes.

How can technology vendors help buy-side firms when it comes to managing their performance and attribution calculations?

Mailhos: Vendors have a responsibility to adapt to different challenges or changing market conditions by customizing attribution models or return types. This includes regulatory demands and market trends, for example with the need for SRRI to support the UCITS directives. By staying ahead of such developments, vendors can ensure their clients are best placed to understand and measure their performance to drive better investment and risk decision-making. They can further simplify and streamline the process by enabling exception-based workflows. This helps firms achieve more accurate and timely results ─ daily or whenever it's needed ─ and enable data managers to focus on analyzing their data rather than generating it. Beyond that, vendors can support firms by providing flexible tools to customize their performance calculations and reporting methodologies.
In addition, vendors can help firms get their data management practices in order to enable consistent performance measurement across all asset classes. They can also simplify the deployment options, for example, through the provision of cloud-based solutions, rather than tactical desktop solutions.

Typically where do buy-side firms go wrong when rolling out new performance and attribution tools? What areas do they tend to underestimate?

Mailhos: One of the big issues for buy-side firms ─ and this applies to all aspects of data management ─ is recognizing the importance of senior management working together with business and IT sponsors to ensure enterprise-wide data governance practices are in place. Organizations often overestimate the quality of their data and, during implementations, significant data gaps and quality issues are frequently exposed.
Over-customization is another risk. Firms will often try to replicate the functionality and features of existing systems in their new one, which can lead to over-customization and over-complication. Instead, they should be encouraged to explore and adopt as much out-of-the-box functionality as possible before embarking on customization.
The vendor has an important role to play to help firms avoid or traverse these pitfalls. They should be coming to the table with a significant amount of experience and lessons learned, to help support firms in any situation. They should be in a position to understand the issues their clients are facing and help them to address them early on in the process.
The most successful projects are those where the client enters with an open mind toward changing their operations and processes. It is easy for clients to underestimate the change management and operational impact of their project, but in order to realize the full benefit of their new technology solution, some operational change is usually required.

How are institutional investors and regulators driving the evolution of performance and attribution functions on the buy side?

Mailhos: Many firms are starting to use new products and alternative asset classes such as derivatives, which has led to the need for enhancements in performance, attribution, and risk capabilities on the buyside. In addition, there is a convergence of front- and middle-office requirements with regulators driving the need for a better understanding of risk within the portfolio. This is driving the need for improvements in the timeliness and accuracy of performance measurement and attribution.
At the same time, targeted return-based analysis is overtaking market index-based benchmark analysis and strategy-based attribution is overtaking traditional segmentation analysis, such as by asset class or region. These changes are clearly having an impact on the way performance is measured.
Because of this growing focus on risk, exposure, transparency and access to data, senior management and business sponsors within investment organizations are demanding improvements in data access. These improvements include the ability to manipulate and visualize data in real time, from anywhere and at any time.

Rich Mailhos is product manager for Eagle Performance at Eagle Investment Systems.