Monthly Archives: May 2019

Embracing Analytics: What Asset Management Firms Can Learn from Major League Baseball

Baseball has demonstrated the profound impact of analytics. Although it is a major sport in the United States, the lessons learned from its data transformation have global application. As asset managers are similarly navigating data transformation in their own industry, they are looking to close the data and technological gap – and discovering Managed Services as a solution that can help them rapidly and effectively make the shift.

Liz Blake, Global Head of Eagle Managed ServicesSM


When Michael Lewis first published Moneyball, he documented how one baseball team embraced data. Fifteen years later, this data-first mindset has spread across the league, impacting how teams invest in free agents, how the game is managed, and even how they sell tickets.

For asset managers, this is more than a curiosity. Baseball’s data transformation foreshadows the change currently reshaping the investment business. Just as advanced analytics challenged long-held assumptions and, ultimately, rewrote convention in baseball, asset management now is undergoing a similar transformation.

Model for Asset Management Firms
Incorporating a true evidenced-based, data-centric mindset into baseball’s scouting and player selection required new thinking or risking being left behind. Today, investment managers are confronting similar challenges. They’re not only rethinking what they analyze and how they generate alpha; they’re reimagining their entire operating model to treat data as a true asset. This enables them to redeploy resources – both people and capital – in new and more effective ways.

Historically, baseball managers were relegated to manual tabulations of individual data points, stored on paper and in their memories to drive decision-making. For example, great managers may know that a batter was a good hitter and was likely to get on base.  However, in order to win more baseball games, teams needed analytics to know how he got on base (he hit a curveball to shallow right field). Using this information in context, managers were able to hone game strategies, like the “shift,” in order to get the batter out, and put their team in a better position to win games. Ineffective use of resources – such as bringing in a curveball pitcher to throw to a batter who loves hitting curveballs or leaving the third baseman and shortstop in their traditional positions waiting for a ball that is rarely going to come – are not winning strategies.

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Performance Measurement: Controls, Workflows, and Technology

Mark Goodey, Director, Senior Principal of Investment Analytics, Eagle Investment Systems


Recently, I was fortunate enough to observe a number of thought-provoking presentations and panel discussions as chair of the FTF Performance Measurement Americas Forum in New York. In reflection of the event, I’ve highlighted some of the key themes I found most impactful.

Improved Controls
Performance teams are under increasing pressure from internal audit teams—and, more importantly, external regulatory bodies—to ensure their data is passed through comprehensive control processing. Once validated, the data is deemed reasonably bulletproof in the eyes of consumers. There’s an acceptance that the performance function acts as a safety net for clients and, therefore, needs to act as a data quality feedback loop to other teams across the business. There is a firm ‘quality control’ component to the performance measurement function, requiring significant oversight of data and robust workflows.

Much of the conversation I witnessed centred on the data management challenges for performance teams, as well as the role of manual ‘eyes-on’ processes versus automation. Based on the increase in the volume of data, the sources of data, and the frequency of reporting, it’s apparent that processes and workflows need to be streamlined and the ‘maker-checker-supervisor’ process must be systematised. Ultimately, this comes down to a combination of human and technology processes. It’s essential that exception-based reporting, like that provided by Eagle, replaces manual reconciliation. This solution increases the human operator’s responsibility to supervise and oversee the data by using tools and dashboards to ensure data accuracy and resolve issues as they occur. At Eagle, one of our key considerations, as part of our continual product enhancement, is to enable any number of “checkers” and “supervisors” in the process at any time in order to satisfy regulatory demands. Eagle’s next Performance software release will introduce the ability to have any number of ‘flags’ to evidence a sign off by a stakeholder as part of an approval workflow, this will be audit ready.

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