At Brown Brothers Harriman (BBH), we seek to partner with a select group of the highest-quality investment managers that we believe are best in class. Partnering with only a select roster of managers allows us to perform deep research on both prospective and existing managers, but also increases the importance of making great manager selection decisions. We look to partner with managers for the long term, thinking of these relationships as akin to marriage. This too increases the need to make great decisions.
Manager selection and monitoring are part of the role of our Investment Research Group. As institutional investors, we are often asked what we look for when conducting manager research and reviews. Because every investment manager is different, our diligence process is unique to each situation. However, some areas are core to every manager underwriting process, and we refer to these as the “10 Ps.” We seek to identify those managers whose people, passion, perspective, (willingness to) progress or evolve, philosophy, process, portfolio management, partnership, principles, and performance lead to a sustainable edge that we believe is highly likely to produce attractive returns over time. We have found that consistent use of the 10 Ps in our diligence process reduces the chance of adverse manager selection. Of course, no approach or process fully eliminates the possibility of mistakes, but our goal is to enhance the probability of selecting only the best investment managers. As such, the 10 Ps have been designed and refined to improve the probability of investment manager success in the future.
The 10 Ps are based not only on a detailed review of academic literature, trade journals, and white papers, but also on our own research and experience. When evaluating investment managers, we consider both qualitative and quantitative factors. Interestingly, the 10 Ps are predominately qualitative considerations that involve a considerable amount of judgment, which is part of the challenge of manager selection. Quantitative data are used to make assessments in each of these areas, but judgment must be applied in successful interpretation of that information.