Setting Fund Director Compensation: Measuring the “Degree of Difficulty”

Jay KeeshanCompensation, Mutual FundsLeave a Comment

Our last bulletin discussed the many changes that fund directors have experienced in their duties over the past decade. The job has undoubtedly become more difficult, as has the task of setting their compensation each year. It is important that, given the responsibilities,pay be set in a way that is fair to directors, but equally important is that the fee is fair to the shareholders.

The traditional approach to setting compensation is to review annual studies that provide compensation data based on the value of the assets managed and perhaps the number of funds overseen by other boards in the fund industry. These studies are certainly of use and can provide a helpful reference for boards year to year. MPI, however,has long believed that these numbers are meant to be descriptive, not prescriptive;that is, while they provide a snapshot of current industry pay levels, it does not automatically follow that this data should be used to set a particular board’s pay.

Many boards take it a step further and identify a set of “peer” boards, that bear resemblance to theirs based on AUM and fund counts. A comparison to the median, or to a percentile rank as determined by the board, can be very helpful in providing guidance. However, given the evolving nature of the fund business and the uniqueness of each board’s duties, this approach may not be adequate. It also runs the risk of producing an “upward spiral” effect on compensation if boards continually set pay at or above the median.

With so many boards seeking guidance for their particular situations, MPI has endeavored to alleviate this problem by designing a more comprehensive approach. This model measures many of the variables that impact the “degree of difficulty”associated with fund governance.It uses a “relative” approach to setting compensation;that is, it measures how complex the governance issues are relative to other fund boards.A brief summary of this two-step approach follows, the principles of which can be applied by any board looking to evaluate and set their compensation.

STEP ONE: SELECTING A PEEROR REFERENCEGROUP BY “PROFILE”

Assembling a peer or “reference”group is a critical first step in the process. Selecting a relatively wide band of boards based on AUM (we often use the “half and double” rule) provides an initial set to start with. Then comes the important step of selecting boards with similar profiles, which means finding boards that bear many of the same types of responsibilities—sub-advisor oversight, product variety (i.e. open-end, closed-end, VA, etc.), and of course a similar range of fund counts, to name a few.The key is to match the oversight requirements as closely as possible. The scale is less important at this stage; if one board has 10sub-advisors and another has 30, that is probably acceptable. The difference will be made evident in the final scoring. We have found that a group of six to ten boards is usually sufficient.

STEP 2: SCORING THE “DEGREE OF DIFFICULTY”

Once a peer group has been assembled, the next step is to collect the relevant data for each board. Collecting this information can prove to be a bit of a task, but much of it is available in public disclosures and on fund company websites. This approach assesses the responsibilities across four broad dimensions of complexity,each made up of various components,as listed below:

  • Structural complexity examines the board’s duties as pertains to the various activities of the manager:
    • Distribution channels and platforms—degree of placement in retail supermarkets, insurance products, retirement vehicles and workplace offerings such as 401(k) and 403(b), savings platforms such as 529 plans, etc. as well as broker-dealers.
    • Number of sub-advisors—with regard to the additional effort required to oversee them.
    • New fund activity –a steady flow of recent fund introductions typically indicates future activity.
  • Product/offering complexity looks at the array of funds/products overseen by the board:
    • Total number of funds
    • Types of funds—open end/closed-end, variable annuity funds, life-cycle, target date, allocation, funds of funds, ETFs, etc.
    • Number of share classes–implies additional complexity.
    • Variety of fee structures –legacy, unified, etc.
  • Investment complexity–A deeper dive into the funds’ investment strategies and the makeup of the securities held. Scoring this can be somewhat subjective, but there are several measures that can be used, both quantitative and qualitative, such as:
    • Number of investment categories(equity, fixed income, international, etc.)
    • Alternative funds—the number and type of hedge fund and other non-traditional strategies require significant additional effort,education and expertise.
    • Other –tax strategies and securities lending programs, etc.
  • Organizational complexity/breadth of exposure–This weighs the potential impact on a director’s reputation with regard to legal exposure as well other opportunity cost factors:
    • Legal activity –any publicly known legal activity that the board is involved in is taken into account.
    • AUM –assets are a factor, particular with regard to legal exposure.
    • Number of sub-advisors –counted again here in the context of the opportunity cost posed by the avoidance of conflict related to the oversight of other financial firms.

Once the data is collected and assembled, directors can take two approaches to the analysis. A basic approach is to simply rank order the boards on each dimension. The average ranking of the subject board provides significant insight with regard to their position among the other boards. They may be near the middle or fall closer to the top or bottom.

A somewhat more complicated approach involves scoring the subject board on each component on a relative basis—i.e.,if the subject board is scored as a 5, determine where the others fall on a 1 to 10 scale. Weightings can also be assigned depending on the relative importance of each component. A raw score is then determined, and the subject board’s score is set at 100 as an index basis, with the other board’s scores falling above and below.

Either of these approaches will provide a relative position of the subject board among the peers. The final step is to determine the median compensation for each of the peer boards. These data points can then be analyzed such as in the following chart:

*For illustrative purposes only***

Though it is a relatively minor chore in contrast to their other duties, setting compensation is important to all parties involved. The intent of this set of tools is to help provide boards with better information for making the appropriate decisions.

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