Striking the right balance
The world of performance analysis continues to evolve as does the required skill set for the people who work in this part of the industry. The number and type of instruments has grown, most notably in the areas of fixed income and structured products, and these new instrument types have raised the question of how each should be reflected in a portfolio and then treated for performance purposes.
In addition, there is more emphasis now on understanding portfolio construction and investment decisions, and correctly interpreting them in the performance analysis output. The need for closer, more interactive links with the fund managers and other end users of the results has also led to a need for people with a wider understanding of the investment industry than just the exciting performance side.
On top of all of this, there is continued pressure for more frequent and timely results. This keeps a good degree of the focus of a performance team on data quality and requires the ability to understand and, where necessary, investigate the accounting data from which the performance results are derived.
In terms of the ideal performance candidate, it is someone who understands the accounting data and is willing to investigate pricing, which includes trading, exchange rate and income data at a security level. This analyst should also understand different instrument types and fund manager strategies, in particular with regard to how the instruments should be aligned and what the strategies were trying to achieve, and the eventual needs of the end user (as in what type of analysis is required and to what level of detail). It may not come as much of a shock to learn that people who tick all of these boxes, and are equally happy handling each element, are somewhat thin on the ground. It tends to be the case that all of these aspects are required in a successful team but they have to be met by matching the strengths of a group of people. The shape and emphasis of most performance teams has changed over time to keep pace with the output and support they have been required to provide.
Once performance teams, within asset managers, had become a separate function from the fund manager assistants, the focus was mainly on data provision and quality. For the most part the role of the team was to supply companies with the raw data, in the desired format, to produce the performance report and then to check the output and investigate any anomalies then respond to any questions.
As the knowledge and sophistication of the internal and external end users increased, the demands grew in terms of the type of analysis required and this lead to a move towards a greater technical ability within the teams. That this needed to be more of an in-house resource rather than remain with the third-party data providers was due to the increase in ad hoc questions being asked as well as the aforementioned time pressures for the production of the regular reports. Companies such as WM and CAPS still had, and have, a role to play — in particular in terms of providing standard reporting packages, the independence of which continues to be of importance to consultants. Yet the need for more detailed analysis, as well as non standard period reporting, meant the analysis side of the performance teams had to develop. Over time, the growth in the need for more technical and indeed theoretical people in each team has been driven by the need to design and apply new models and methodologies and then to articulate the output. The actual maths behind the various types of analysis may look quite daunting when written down, and peppered with the usual number of Greek symbols, but the skill is more in knowing when, rather than how, to apply each of the calculations. For this the need for more technical people who understand what each formula is telling us is key in the first instance.
Portfolios had originally been viewed, in performance measurement terms, using a fairly rigid structure of all similar investments (eg, for equities countries or sectors and for fixed income government bonds or index linked bonds by country or currency) being treated as a single sector.
Now the trend is moving more towards understanding the make up of a portfolio to better reflect the decisions of the fund manager and so recognise connected trades (eg, those for which an offsetting swap is in place) and the need, where possible, to more accurately group holdings by investment decision rather than by actual investment.
As well as putting further strain on the underlying accounting data this has also increased the need for performance analysts to have better industry knowledge and be able to discuss the output in greater detail with the end user. Thus, again, the need for skills over and above the pure production of the results are more of a necessity in a balanced team and these include a good understanding of how each instrument works and how they can be used within a portfolio.
The technical and industry knowledge required has grown as the role of a performance analyst has become a far more interactive one. There is now an ever more frequent need to be able to explain, with confidence, the results to the end user, especially if they are telling a different story from that which had been expected. It is now necessary to be able to explain what each figure is telling us and how it has been derived as well as, in the first instance, to recognise any anomalies and investigate them accordingly ahead of presenting any results.
This increased interactive element of the role has also manifested itself in the need to define and design meaningful reports, in addition to those which are produced as standard, to help more clearly explain the figures themselves. It is a very definite skill, not only to be able to explain the results to the level of detail required but to be able to present them in such a way as not to lose the end user in a sea of numbers. This means knowing which figures to concentrate on, what needs further explanation and which calculations to use in order to demonstrate both the validity of the output as well as highlight the key factors.
The final area which has, in my opinion, driven the need for a more technical and theoretical side to the make up of a performance department has been the use of new, or different, methodologies and reporting conventions.
The information coming from a performance team has grown from the provision solely of performance returns to the inclusion of attribution, risk and more summary reports for uses such as management information systems (MIS) and GIPS. This has, of course, meant there has been a need for greater appreciation of the more varied results as well as, as mentioned before, the ability to explain them.
Equally though it has meant, often with a great deal of support from IT areas, that within the team there has had to be the capability for significant development work to take the underlying calculations, as they are introduced to the business as usual cycle, and populate them with the necessary accounting and benchmark data as efficiently as possible.
As the standard suite of reports grows it is generally the case that the production is quite manual at first before it becomes more automated and thus embedded in the business as usual reporting cycle. The performance team tends to have a major role to play in this migration towards an automated solution in addition to the role it must play in ‘selling’ the output to the eventual recipients in terms of what it is telling them and how it should be used.
I do feel that the dynamic of the team has shifted in regards to a greater reliance on these skill sets than was the case 10- or 15-years ago but this is certainly not to underplay the continuing requirement for the team to demonstrate practical skills.
In conjunction with the development work required and greater interaction with the end users the over-riding need remains to produce timely and accurate work that revolves around the ability to interpret and, often, question the raw data and set (and achieve) workable deadlines at the outset.
The most detailed, accurate and mathematically sound and insightful piece of work will fail to win over an audience and be properly utilised if the delivery of this work is unreliable with deadlines being met only intermittently. Equally, it tends to take just one wrong output for a single month to begin to undermine the confidence in the previous 12 months worth of work, regardless of whether the error or delay is as a result of issues with the system, the process, the member of the performance team who has produced it or from the raw data where it has been derived. It is for these reasons that I feel it is vital for a successful performance team to have a balance of technical and practical people.
The unavoidable truth is the production and verification work essential to the delivery of the performance output is often less interesting than the actual analysis of the data, the presentation and discussion of the results, or the designing of the final reports. Though the causes of the invalid data, either incorrect or simply raw data processed in such a way as to give incorrect performance results, may vary and so the investigation work to correct or amend issues will also differ, it is still seen as the more repetitive aspect of the performance role.
The perception of the importance of this work in terms of the overall duties of the team is often clouded by the fact the interaction tends to be more with other support areas within an organisation rather than with more front office based departments as tends to be the case at the analysis stage. Yet, it remains the case that having people with the ability to deliver timely and accurate results on an ongoing basis underpins the level of success or failure of a performance team. To this end, a team cannot function properly without these individuals who understand the importance of deadlines and have a sufficiently in-depth knowledge and understanding of the accounting data and systems to recognise and resolve data issues.
In some senses this type of work would appear to be the element of a performance role which is the most likely candidate for outsourcing conversations as it is more closely aligned with production rather than analytics. However, I remain somewhat sceptical about the relative strength of the argument to outsource this function over others of the performance team due to the frequently used issue of turnaround or service level agreements either to deal with the resolution of data issues or the changing of deadlines at short notice. My view is that even with a greater level of automation, the growth in the number and complexity of instruments and the equivalent advancements in the output itself will always need to rely heavily on people with the practical skills and application to produce the output on time.
As a final point, and once again, as stated earlier, I believe that a successful team is one that has struck a balance between technical and practical abilities. This can be achieved either by a mix of people with different core strengths or, as is generally the case in smaller teams, by people who themselves have both the technical experience (and who retain the drive to continue to develop this) allied to a solid appreciation of the practical side of the role.
In an ideal scenario this complementary skill set approach can be mapped to an individual’s development and logical progression through the levels within a performance team. An understanding of the raw data and the production processes of performance results is essential in building the ability to intuitively recognise potentially inaccurate results and relate this to the possible raw data issues which could either have caused them, if they are actually incorrect, or help to explain them and as such it is a good grounding for someone starting out in performance.
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