Practical analysis for investment professionals
30 March 2017

Survival Strategy: A Learning Investment Team

Let’s call this “Schuller’s Law”: The less personal the variable to be optimized in an investment process, the lower the organizational resistance.

For example, if a CIO trained during his university years in modern portfolio theory (MPT) applies the mean-variance optimization, a request to use minimum-variance optimization will likely encounter little resistance.

If the same CIO is asked to switch from correlation-based risk management to causality-based risk management, the resistance level will likely increase because this goes beyond the CIO’s original socialization. Resistance is usually greatest when the investment process variable relates directly to the individual, like optimizing the daily work routine, configuring the team role profiles, or reducing the knowing-doing gap.

Two structural factors dominate the underperformance of professional investors versus the market portfolio: the cost penalty and the behavior gap penalty. When optimizing an investment process, firms not only have to consider both penalties but also how minimizing each will generate differing levels of resistance.

In today’s environment, the industry forces investment managers to pick among the following paths:

  • Aggressively grow in size to help shape the industry’s concentration process.
  • Offer low-cost, fully-automated wealth management solutions.
  • Position themselves as leaders in an investment management niche using an innovation-driven competitive edge.
  • Accept being squeezed out of the market.

Most firms are too small, too conservative, or too burdened by overhead costs to avail themselves of the first two options. Assuming a will to survive, that leaves only the third path.

Simply picking up on pseudo-innovations — like running after fashion trends — won’t work.

To establish and maintain an innovation-driven competitive edge, a leading niche investment process requires a learning organization with a continuous improvement cycle.

Firms Need to Know If and How They Learn

Knowledge management has been an established and well-understood driver of organizational change in many industries for the past 20 years.

But the asset management industry has largely ignored knowledge management in both academia and practice. When asked how they learn, investment management decision makers or investment committees often respond with silence.

What a missed opportunity.

Every firm should move between the operational and meta-levels in its qualitative and quantitative optimization of the investment process. Only then can a firm more thoughtfully and rationally tackle the tough decisions, like what parts of the investment process can be outsourced to quantitative tools (algorithms, big data analysis, neural networks, etc.), what can help to proactively minimize cognitive biases, and how clients can be included in the learning process through expectation management techniques. In short, heuristics management constitutes a competitive advantage.

All firms need to work on both and low and high resistance investment process issues. Focusing only on latter does not create a competitive edge.

To transform an investment team into a high-performance investment team (HPIT), the tough issues must be dealt with. Inevitably it becomes personal.

Four Levels of Intervention

So, how does a firm get started? We classify four levels of change management intervention when establishing HPITs as part of optimizing the investment process.


A-learning-investment-team


The very same is true for choice architecture in an investment process.

If a certain individual behavior — a strong work ethic, for example — is expected, while the same standard is not set as part of the team or organizational culture, it only is a matter of time until individuals align their behavior with the established organizational culture or leave the organization.

To illustrate, say a staff member is expected to experiment with new asset allocation methods using an evidence-driven trial-and-error process, but the organization has a fear-based culture and responds poorly to errors. What will the employee do? Either return to the behavior encouraged by firm culture or leave.

Investment process optimization can begin at the individual or team level to harvest the low-hanging fruit. But for the change management process to have a lasting impact, it must also be embedded in the investment decision-making process and culture.

If change is neither genuine nor intentionally pursued, employees can wait out any requested interventions.

Individuals working at investment firms are not stupid. They know that the moment controversy arises, old conflicts or processes will reassert themselves.

The opposite is true at the best organizations. These firm continue their learning during tough times. They infuse lasting behavior modification in the choice architecture of the individual, the team, the process, and the cultural context of a learning organization.

If professional investment managers are serious about positioning themselves as leaders in an investment management niche through an innovation-driven competitive edge, these optimization goals have to be targeted.

schuller

And remember, this isn’t a choice. This is a survival strategy. Either do it or be squeezed out.

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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: ©Getty Images/fandijki

About the Author(s)
Markus Schuller

Markus Schuller is the founder and managing partner of Panthera Solutions. As a leading behavioral design company, Panthera optimally configures the investment decision design of professional investment processes to facilitate most evidence-based decision making. As adjunct professor, Schuller teaches such courses as Adaptive Risk Management, Investment Banking, and Asset Allocation for Practitioners at the renowned Master in Finance programs of the EDHEC Business School and the International University of Monaco. Schuller publishes in top academic journals, writes articles for professional journals, and delivers keynotes at international investment conferences. In short, as investment banker, adjunct professor, and author, Schuller looks back at 20 rewarding years of trading, structuring, and managing standard and alternative investment products. Prior to founding Panthera Solutions, he worked in executive roles for a long/short equity hedge fund for which he developed the trading algorithm. Schuller started his career working as an equity trader, derivatives trader, and macro analyst for different banks.

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