The Investment Decision Process (IDP) model: From inception to a legacy of innovation

Almost three decades on, the investment decision process model continues to support asset owners around the world in understanding how each investment decision with an investment process contributes to the total fund performance.

We explore the origins and core concepts of the model with Jeroen Geenen, one of its original developers, and with Elske van de Burgt, Managing Director, Investment Performance, on how this client-centric and innovative spirit continues to shape our approach to improving performance measurement and attribution, today and into the future.

What prompted the team to develop a framework from scratch to help asset owners better understand the drivers of investment returns?

Jeroen: At that time, the field of performance attribution and evaluation was still in its infancy, and the practice of evaluating investment performance had not yet been widely adopted. A few articles had been published in general portfolio management journals, but the dedicated Journal of Performance Measurement, which focused on innovating and exploring ways to undertake performance attribution, in recognition that the insights gained would ultimately improve future decisions, had only just come into existence. During this period, the only attribution methods available (Brinson-Fachler, Brinson-Hood-Beehower) were pretty basic, relying on a simple two-step process: allocation and selection decisions. It was evident to our clients that this oversimplification would lead to flaws, as their decision-making process involved many more steps, rendering the model unusable for evaluating the actual decision-making process. As a result, there was a noticeable gap between what the literature offered and what our clients were looking for.

Elske: What they were looking for instead was performance attribution that reflected how decision-making was actually taking place in their investment process. This would require acknowledging that there are multiple levels of decision-making and that getting from the fund's benchmark/target to the actual portfolio involves numerous decisions: strategic, tactical, and operational. In addition, they needed a way to understand how an interaction effect was contributing to performance -an effect that appears to arise from a decision no one owns.

How did the Investment Performance team create a framework that allowed each decision to be analyzed on a standalone basis, while also explaining how those decisions, including their interaction effects, collectively contributed to the respective fund’s total return?

Jeroen: To help our clients better understand how each decision contributed to a fund’s total return, we recognized the need to challenge the prevailing literature at the time while maintaining the foundational strengths of the Brinson model. The team harnessed the Brinson model by arranging it into a hierarchical structure, in which the selection effects from each top-level category can, in turn, be decomposed into allocation and selection effects through a series of secondary Brinson models.

Following this, the selection effects within each category of the secondary Brinson models can themselves be further decomposed into allocation and selection effects through the application of tertiary Brinson models. This process can continue recursively, much like a set of babushka dolls - or, in more scientific terms, as a hierarchical telescoping sum. Using this principle, we were able to construct a hierarchy of Brinson models that precisely mirrored the actual Investment Decision Process. This became what is now known in the industry as the IDP model.

Elske: Of course, this may sound straightforward, but in practice it requires a substantial amount of mathematical complexity, enabled by technology. At its core, the IDP rests on a simple but rigorous principle: attribution itself cannot create or destroy value. The contributions from every step in the decision process must reconcile precisely to the total result. Those reconciled results can then be expressed as attribution effects by extending the principles of the Brinson model.

How was the IDP then implemented into PEARL – Ortec Finance’s performance measurement and attribution solution?

Jeroen: This was a significant challenge. While IDPs across different institutional investors share many similarities, no two are ever exactly the same. As a result, our team had to develop software capable of supporting the creation of an attribution hierarchy for decisions using the Brinson foundations, while retaining the flexibility for the end user to specify which step in the decision process corresponds to each level of the hierarchy. We initially predefined the decision hierarchy in the system in a static manner. This lack of flexibility meant that our team had to alter the hierarchy for individual clients, which was neither an efficient nor effective approach for our clients. So subsequently, we learned what levels of flexibility was required in practice when building each fund’s IDP and landed on a version of in PEARL, still in place today, that allows users to fully specify and adjust their fund’s IDP as part of the system configuration.

Elske: Not only that, but we also created the concept of time dependency. This means that the IDP can change over time – which we learned is a guarantee given the dynamics of investment management – while we keep a record of what the IDP looked like at any point in time.

Another important lesson we learned, and one that continues to influence how we innovate PEARL to this day, is the importance of listening to the client. What works in theory might not always be the best fit for our stakeholders' needs in practice. With that in mind, our team has expanded the model to allows our clients to attribute currency overlay decisions and specific attribution models for the fixed income component of the IDP.

Do the challenges faced by asset owners that led to the creation of the IDP still persist today? Are these challenges even more prominent than before? How has the landscape evolved?

Elske: Yes, although investment strategies and categories may have changed, there are still multiple decisions being made. With the growth of available instruments (e.g., derivatives) and asset classes (e.g., private assets), these decisions have become more complex and data-intensive. However, the framework of having an IDP, and explaining the difference between target and actual fund returns (and why), remains of utmost importance. This is why our top-down approach, capturing the value added by every investment decision, continues to be as powerful as ever.

The ability to measure the impact of overlays, which are by definition managed as an ‘afterthought’ once all major market allocations have been made, has become crucial. This is especially important as funds adopt increasingly sizable overlay strategies to hedge risks across currency, inflation, and interest rates, while also implementing tilts and dynamic asset allocation strategies.

Will the IDP model need to evolve to keep pace with the changing landscape of asset owners worldwide? How do you see it evolving? Any major developments?

Elske: There are three key areas our team will continue to focus on to better support our clients' needs and objectives, ensuring we capture their unique investment processes. We work closely with them, learning from their practical experiences to enhance our models and approach, just as we have always done since PEARL was initially established.

Enabling our clients to harness IDP to support the increasing adoption of total portfolio approach (TPA)

While the value added by decisions within a TPA approach can generally be well captured by our IDP model, it presents a challenge in how to adequately capture and represent factors in an ex-post context. This challenge arises from differences in how clients approach the TPA. Much like how IDPs are never quite the same for each investor, this necessitates enabling our clients to configure the setup to reflect their chosen approach while striking a balance on ensuring efficiency in the implementation process.

Attributing how investment decisions are contributing to ESG objectives

ESG is another key focus area, with growing recognition that sustainable practices and responsible corporate behavior can impact financial performance. We have been exploring this over the past few years, including developing an ESG attribution model in collaboration with MN, a leading Dutch fiduciary manager, to capture ‘non-financial’ metrics in the same way we assess risk and return.

Total fund performance attribution across public and private assets

Asset owners are continuing to increase their allocations towards private markets. While PEARL already has the models and metrics in place to evaluate private assets, we want to continue to improve how we integrate private and public asset analytics at the total-fund level and the implications for investment decision-making, and address the unique challenges of this asset classes across illiquidity, valuations, and benchmarking.