Next Gen Performance Measurement: making the complex simple

Date: September 15, 2016

Web“Making the complex simple” is an ambition of the asset management industry that somehow never seems to materalize. 

As far as performance measurement is concerned, this is an intrinsically difficult area made worse by multiplying data sets and systems – many of which are too slow to handle the volume of data coming down the line.

Furthermore, the resulting manual workarounds to compensate slow legacy systems are increasing, with the end result being a mess of calculations and recalculations that are hard to understand and even harder to turn around at month end.

The solution, of course, is to develop a performance system that can handle today’s data volumes and stakeholder requirements – one that can standardize and analyze the data in a hassle free, operationally efficient manner.


In an ideal world, month end should simply be another day. Perhaps not another day in paradise but you can’t have everything!

Data management is the biggest headache for performance teams. Issues can be around managing data quality, the lack of standardizations as well as the difficulty in onboarding new data sets and merging them with existing workflows. In addition, increasing costs related to the amount of time and effort put into managing data can also impair business agility.

What should a next generation performance measurement system look like?
Any system that is going to work in the long term, needs to allow for the production of better quality data within a shorter time frame. “Timely” and “accurate” are the watchwords here and the more the better: better decisions and actions result from high quality analysis.

The ability of asset managers to do this relies on new technology and its capacity to provide scale and flexibility. In its recent report on the need for change to asset management operating models, Ernst and Young looks at how new technology that can reduce complexity and increase opportunities for outsourcing is now replacing legacy custom applications. The preference is now tipping towards flexible vendor solutions and rationalizing the overall number of applications:

“In the front-office, for instance, firms are consolidating three or more platforms onto a single trading and order management platform.”

This is now happening in the middle-office too, where multiple legacy systems still exist, mainly due to the proliferation of systems to manage multiple asset-classes and portfolio types.

Moving onto a single consolidated platform can take care of issues related to scale if the technology is ‘elastic’ in its ability to handle high demand or large data volumes. Scalable cloud-based platforms have this advantage.

To date, building a new performance system from scratch has not been considered an option. But the fast moving pace of technological development – combined with the more powerful ‘elastic’ hosting capabilities of cloud computing – mean a new performance system that meets the requirements of today and the future is now possible.

Good design of such a system also results in a more streamlined process and a more user friendly front-end that can make day-to-day use more straightforward and efficient.

What system functionality is needed?
Eight top expectations from a Performance Measurement and Attribution System, by Saurabh Kumar identifies calculation functionality as the most important asset that a platform should have.

For Kumar, data control checks on the source data coming in and the ability to configure and customize at portfolio level means that the right source data is assured and the results of the calculations are 100% bullet-proof.

Systems also need to be flexible and provide for advanced functionality related to performance measurement, he argues. More sophisticated data management controls and the ability to easily identify problems and resolve any issues in a timely fashion means that turnaround times can be reduced to one or two days rather than one or two weeks after month end.

In addition a capable cloud-based system means that if anything needs to be reprocessed, then it can be turned around much more quickly. A matter of minutes instead of hours for example.

Along with the data management capability, any high-quality platform also needs to have a very graphical and user-friendly interface so that the entire process can be visualized easily. For instance, the workflow and user interface has to be easy to use, easy to navigate. Portfolios should be grouped into logical, operational workflow groups that share similar data controls and calculations between them.

“If the design of the system is cluttered, complicated or command based, then the Performance Analysts prefer to spend less time on the system and more time on excel spreadsheets,” says Kumar.

Being able to see things from the point of view of the end-user rather than a systems-design perspective is what makes for a great end product. Understanding the needs of the performance analysts themselves and knowing what to put in to make a significant improvement is the key to a really great system.

For example, a big leap forward will be to have all controls in one place rather than having to build processes around systems in order to identify any data issues that may occur. Auto-scalability is another way to remove issues around dealing with processing volumes and long wait times.

The benefit that should come with any new system design is the ability to make something that is inherently complex, as simple as possible. Software really does need to be simple and work intuitively for the people it was designed for. Recent advances in technology and the cloud means there is no reason why this cannot happen.

The message is clear and very obvious: software is there to make our lives simpler. This is now a primary focus for leading developers tasked with making the complex terrain that asset managers need to negotiate each day, into something more accessible and easier to navigate.


  • Performance measurement is an intrinsically difficult area made worse by multiplying data sets and systems.
  • The solution is a system that can handle today’s data volumes, but also provide the data control and workflow to make the process simpler and more efficient.
  • Any system that is going to work long-term needs to allow for the production of better quality data within a shorter time frame.
  • Moving onto a single consolidated platform takes care of the scale issue if the technology is cloud-based and ‘elastic’.
  • Systems also need to be flexible and intelligent, helping automate routine tasks and highlighting data issues.
  • Any high-quality platform also needs to have a very intuitive interface designed with the end user in mind.
  • The message that any system design should give out is that of making something that is inherently complex, as simple as possible.


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