From Mechanical to Mindful – The Nature of Investing: Resilient Investment Strategies through Biomimicry

Transformation 5

From Mechanical to Mindful

You’re right on the line!” an agitated audience member proclaimed. I had just presented results for the mid-cap funds I was managing to a big group of financial advisors.

“Ummm, what line?” I asked, a little bit confused. The backdrop to these meetings was a positive one: the funds were doing well, and so was the overall stock market (this was the late 1990s), so it was unusual to meet an unhappy investor. My first alarming thought was that he meant some sort of ethical line, or a personal one—that he did not approve of some of the fund’s holdings, or thought I had invested too much in technology stocks.

“This one!” he poked his finger at a set of papers. It was not a metaphorical limit he meant—it was an actual line, the line in the Morningstar chart that placed my fund in the mid-cap growth box. Sure enough, my fund was right on the edge between “blend” and “growth.”

“I have to sell your fund if you cross the line,” he explained, eyes wide. “Don’t cross the line.” It turned out that his firm had a strict asset allocation policy, so that if my fund moved from one box to another, he would indeed have to sell it.

“Well, I’m just buying the best mid-cap stocks I find,” I replied, trying to emphasize that my responsibility was to shareholders and not to the chart he held. He turned away in frustration, shaking his head.

This was my first clue that our assessment tools had taken on a life of their own. They had begun to influence our practices and cause us to adapt, but not in a healthy or intended way.

Nature’s Principle: Adapt to Changing Conditions

Adaptation is a curious concept for investors: we want to be nimble and to be able to adjust as the environment shifts, but we also want to be consistent and reliable. The detail behind the natural principle adapt to changing conditions acknowledges that we live in a world that is constantly in flux and illustrates that adaptation is not just about any old response. It’s the appropriateness of response that matters, the way that the response is triggered and managed. Proper adaptation requires designs and processes that are inherently dynamic, not static. The subprinciples of adaptation are:

  • Maintain integrity through self-renewal.
  • Embody resilience through variation, redundancy, and decentralization.
  • Incorporate diversity.

The first element of adaptability is the ability to maintain integrity through self-renewal. What does this mean? Persistence! Perseverance! Adaptable organisms are constantly adding energy and resources to heal and improve the system, on both micro and macro levels. Think of a tree that loses a big branch in a snowstorm—if it’s healthy, by the next spring you’ll usually start to see new branches forming near the lost limb. Or consider our own bodies, healing cuts by marshaling all sorts of different resources to clot the blood, fight infection, and form new skin and scar tissue around the wound. Self-renewal is the process of maintaining integrity, not of holding a rigid form constant in the face of change.

Adaptation also requires embodied resilience. It’s not enough to be resilient only in theory: this quality must be actively demonstrated and fostered through variation, redundancy, and decentralization. The quirky little sea slug called a nudibranch shows how these qualities are positive and necessary. Obviously, a slug is a vulnerable creature—slow moving and unprotected, offering a squishy, easy meal for predators. To protect themselves, nudibranchs are often crazily, garishly colored, alerting predators to toxicity. In a stunning show of adaptation, the source of this toxicity is directly related to the nudibranch’s particular environment: for example, many varieties protect themselves by eating toxic substances like the stinging cells from jellyfish tentacles or anemones. Instead of being poisoned themselves, the nudibranchs pass the toxins through to harm would-be predators. Other sorts of nudibranchs, rather than sporting loud colors of warning, take on the color of their own food sources—so, for example, one feeding on coral will be coral colored, invisible to attackers. These adaptations to local food sources allow the nudibranch to thrive in shifting (and threatening) conditions.1

A glance at sea slug photos (really, take a look!) reveals stunning variation within the species, while the multiple mechanisms for “borrowing” toxins from other creatures demonstrate redundancy. The way that adjustments are localized to each particular environmental setting reflects decentralization. Those three characteristics—variation, redundancy, and decentralization—tend to have a negative tone in business settings, where we often aim for consistency, efficiency, and centralization. But resilience is every investor’s dream: to be able to prosper in a range of changing environments, with all sorts of resource shifts and a wide mix of neighbors, some with friendly intentions and some more predatory.

The final component of adaptability, diversity, might at first seem to be the same as variation, discussed above. However, while variation refers to the mix of organisms, diversity refers to the mix of forms, processes, or systems that exist to perform a particular function. Variation is a mixture of “what,” but in this context, diversity is a mixture of “how.” In a forest, we can easily see the distinction: trees can regenerate through internal growth, seedling growth, or new shoots from old roots. Water capture can come from root systems, geographic features, or built structures. There are many different trees (variation), and also many ways for regeneration and water capture to occur (diversity).

Three key themes are embedded within the natural principles of adaptation. First, the concept of self-renewal as a dynamic cycle. Perhaps I am over-conditioned by years of exposure to women’s magazines, but when I see “self-renewal,” I tend to think of “antiaging” or turning back the clock. That association is completely misplaced in the context of biomimicry. Here, self-renewal does not imply going back to some prior form; rather it’s a tool for healing, change, and improvement. Going forward.

Luckily, outside the realm of beauty creams, this sort of self-renewal is a familiar idea. For example, education and training are forms of self-renewal, adding energy and resources to acquire new knowledge and capabilities. One of the most common aspirations in the business community is to be part of a “learning organization.” Similarly, Charlie Munger, Warren Buffett’s longtime business partner, often discusses his efforts to build diverse “mental models,” so that he has intellectual frameworks that help to navigate a wide range of situations. Early in his career, Munger realized that this self-renewal was so important that he decided to bill an hour a day to himself, so that he could invest the time in projects that interested him, rather than projects other people paid him to do.2 Whether physical, emotional, spiritual, or intellectual, these types of personal investments in renewal are all ways to build adaptive capacity.

Resilience is also a commonly confused term: the perception is that resilience means “bouncing back,” but the concept is more nuanced than that. In biological terms, resilience is about maintaining function in light of disturbance—not retaining form, not recovering to an original state. Within nature’s principles, resilience is explicitly multidimensional, incorporating variation, redundancy, and decentralization.

Those resilient qualities might sound fine for a forest, but in many human endeavors it’s not so clear that they’re desirable. In business, “redundancy” is usually a synonym for “waste.” Indeed, in human resources circles, when you are “made redundant,” it does not mean you’ve won a prize for your contributions to resilience; it means you’ve been fired. We tend to view the main mechanisms of resilience—variation, redundancy, decentralization—as enemies of efficiency. In our quest for efficiency in human endeavors, we can decrease resilience.

The third embedded concept in the adaptation principles is that diversity is an asset. This might be well understood in some organizational settings, but it is very rarely acknowledged in process design, where our assumption is that standardization is the best approach. There are a few specialties that value diversity, like airplane safety or nuclear engineering, where we want multiple options for landing the plane or shutting down a reactor core. But these are the exceptions, not the rule, and even then, we usually choose a mix of standardized options. Diversity of mechanisms is the exact opposite of standardization, and it is standardization that’s been the hallmark of our business practices since the days of Henry Ford. Of course, standardization might be well suited for assembly lines, with predictable work flows and homogeneous products, but we have misapplied it to many endeavors like investing, where conditions, products, and processes are constantly in flux.

Figure 5–1 Adapt to Changing Conditions: The Swarm

When bees seek a new hive location, the same simple rules guide information gathering and decision making: every scout is seeking to optimize location characteristics such as sun, safety, and height.

http://www.amazon.com/Honeybee-Democracy-Thomas.D.Seeley/dp/0691147213; http://www.nbb.cornell.edu/seeley.shtml

Translation to Investing

The qualities of natural adaptability are not always embraced in business, but they still seem like no-brainers when it comes to investing. We all recognize the inherent risks and uncertainties presented by a changing economic and investing environment, and the qualities of adaptability (and especially of resilience) represent a clear way to develop capabilities for navigating that changing environment.

Indeed, the premise behind most modern portfolio theory is that investors want to manage and mitigate risk. Unfortunately, as the theory has been put into practice, we have increasingly used narrow quantitative measures of risk like beta and VaR (value at risk) as proxies for the broader, more qualitative concepts of risk and uncertainty. This mismatch—the narrowness of the calculations versus the breadth and depth of the concepts they represent—can have devastating consequences.3

Even in this one small corner of portfolio theory, we see two different problematic layers. First, the mechanical layer: the calculations themselves are very narrow, each focused on just one subset of risk. Second, the human layer: this data is often misapplied and misunderstood, used to leap to much larger associations and conclusions than is warranted.

Though intended to explain and to control risk, many of our mechanisms for managing risk have only focused on very narrow, short-term measures. These tools have not improved long-term risk management, and have not increased adaptability; instead, they have unwittingly decreased it, by establishing more and more structured approaches that inherently have less variation, less diversity, less flexibility. We have chosen rigidity instead of responsiveness, in the hope that the walls of ever more solid structures and processes will repel risk and uncertainty at the perimeters of our endeavors. We have sought control—an impossible goal—instead of aiming for adaptability and resilience.

Natural Scorecard: Mutual Funds and Their Analytics

At first glance, mutual funds seem to be among the slower-moving organisms within the investment world. The structure of these products has been pretty constant for the last seventy-five years, and they rarely carry the same sizzle in the headlines as high-frequency trading or hedge funds do. But this underlying stability of form is exactly what makes mutual funds the perfect illustration of misdirected adaptation in our investment practices. The funds themselves have changed much less quickly than their ecosystem—the tools, policies, and procedures that surround them.

The steadiness in form also reflects a steadiness in function for mutual funds: far and away, their main function in the investment ecosystem is to provide diversification for investors. After all, it is a mutual fund! The whole point of a mutual fund is that people are coming together to share in both risks and returns. In natural terms, a mutual fund allows investors to invest in a small piece of a whole forest, instead of owning just one tree or a colony of beetles or a few acorns.

The principles of adaptability were easy to observe in fund management for more than fifty years. As recently as the early 1990s, the most common type of mutual fund was a “go-anywhere” fund, where the portfolio manager had wide discretion over where to invest shareholders’ money. If large-cap U.S. stocks looked attractive, they might be a fund’s largest holdings. If the manager believed there was more opportunity in small international companies, she could invest there instead, without extra permissions or external approvals or fear of “crossing the line.”

How does the basic mutual fund structure hold up to the standards of adaptation?

Does it adapt to changing conditions? Is it appropriately reactive? A fund can self-renew by redeploying assets from one holding to another—though whether reactions are appropriate depends on the manager and the circumstances.

Does it maintain integrity through self-renewal? A fund can demonstrate resilience through variation, redundancy, and decentralization of its holdings. As one of my early mentors said, “The greatest thing about fund management is, when things change, you can change your mind.”4

Does it embody resilience? Does it value effectiveness over efficiency? Does it incorporate diversity? Yes, a fund can incorporate diversity by holding multiple types of securities and multiple types of businesses.

The fundamental structure of mutual funds is pretty well aligned with natural principles of adaptability—somewhere around an A-minus. But as the number of mutual funds grew, so did the need to distinguish one fund from another. One essential challenge was sheer volume—variation, as defined in our principles above. An individual investor might be expected to sort through a few dozen options to make a reasonable choice, but several thousand? With more than three thousand U.S. mutual funds by 1990 (up from 564 in 1980), there were practical and serious issues of navigation that needed to be addressed.5

Another challenge at this time was variability: not only were there many funds in number (variation), but their results were also quite disparate (variability). Fund investors were being called upon to navigate a more and more complex landscape, but without many maps or tools to assist them.

With the proliferation in numbers of mutual funds and dispersion of their results, the stage was set for the development of tools to sort through all of that data. One early example of a tool for fund analysis is the investment style box, pioneered and popularized by Morningstar. This simple three-by-three grid sketches out categories for small-, mid-, and large-cap funds on the vertical axis, with value, blend, and growth styles across the horizontal axis.

Here is a quick review of the evolution of this one investment tool:

• The style box tool was developed in 1992 by Morningstar. Early on, the style boxes fulfilled their role exactly as designed: thousands of mutual funds on jumbled-up lists were sorted into straightforward categories, based not on what their names implied but on the data of their actual holdings. This was a huge service: now it was easy to tell which “large-cap” funds were secretly full of $300 million retail stocks and which “value” funds were full of high-flying biotech holdings.

• The tool had (and has) clear and legitimate function. Morningstar’s own advice notes: “How lines are drawn among value, blend, and growth is somewhat arbitrary, and it is perfectly acceptable for a fund manager to invest in a range of styles. The Style Box tool provides a context for understanding the holdings, not a constraint.”6

• However, misplaced feedback loops began to take hold, and the tool began to influence decision making in an unintended way, as noted in this chapter’s opening story. A study published in 2003 found that changes in Morningstar assessments had independent abnormal effects on fund flows (that is, effects independent of other performance variables) of 13 to 30 percent.7

• These style boxes have become such standardized tools that they are increasingly used as part of the default construct for asset management. This is one factor leading to the popularity of “target date” funds, a type of auto-adjusting portfolio that shifts assets between categories according to the shareholder’s stage of life. This type of fund had just under $50 billion in assets at the end of 2002, and mushroomed to approach $800 billion in assets at the end of 2012.8

Unintentionally, what started out as a needed and helpful tool began to influence decision making in inappropriate ways. In this regard, the Morningstar boxes are just one example of a much broader and deeper trend. When we assess a mutual fund model that is heavily tools-influenced, we see much less adaptability:

Does it adapt to changing conditions? Is it appropriately reactive? The more narrow a fund’s mandate (whether intentional or unintentional), the fewer opportunities there are for it to adapt.

Does it maintain integrity through self-renewal? It is more and more difficult for a fund manager to change her mind. Most funds are now managed by a combination of committees and computers, which dampens the opportunity for individual creativity and responsiveness.

Does it embody resilience? Does it value effectiveness over efficiency? Does it incorporate diversity? Again, a fund manager who is trying to stay “in the box” is by definition constrained.

During this tool-influenced era, discussions of businesses and products and whether they made for good investments have given way to discussions of tracking error, active bets, and portfolio construction. But the latter conversations rarely link those risk measures back to actual investments in the funds, or link those investments in turn to what is happening in the real world. We are increasingly attempting to manage risk by measuring it, and in proper context this might be a helpful endeavor. However, our measurements are less and less connected to tangible activity in the world, and thus we are less and less well equipped to take appropriate action. Our investment dollars are clearly reflecting a desire to manage and minimize risk and uncertainty, but they are also reflecting a desire to automate those processes, to avoid thinking about them. And with everyone using the same tools, resilience of the overall system is undermined.

This maladaptation of our funds and tools highlights an important paradox: one of the greatest conditions for resilience (variation of organisms) can also be related to conditions that are unappealing to investors (variability in results). How can we reconcile the high degree of dispersion that a resilient system implies with our desire for consistency?

To help sort out this paradox, it’s important to distinguish between two distinct elements, risk and uncertainty. Most of our tools are intended to help us understand variation (the range of elements) and manage variability (the range of results). The first part, understanding variation, is pretty well addressed by popular analytical methods.

But variability—breadth of results—is a lot tougher to understand, and even more difficult to manage. Variability has two components. The first is risk—where the range of possibilities is known but the outcome is not clear. The second is uncertainty—where neither the range of possibilities nor the outcome is known. This distinction between risk and uncertainty was documented by Frank Knight in the 1920s, and has been well illustrated more recently by Michael Mauboussin, amongst others.9 Think of risk as a question of where results fall along a normal distribution. Think of uncertainty as a situation where results fall in a huge, wide-open space.

If you illustrate these two pictures with hand gestures you can actually feel how different the challenges are: risk is a complicated but tidy mathematical exercise, while uncertainty is the great unknown. Really, try it. Put this book down and make these forms in the air. Risk … a nice, steady curve. Uncertainty … a wild flailing and flapping around. See? This is not a geeky irrelevant distinction—these are fundamentally different concepts.

Here is the tough part: we can model risk until the cows come home, but there are no good models for uncertainty; in fact, that is the definition of uncertainty, that it is not model-able. And that—let’s admit it—is terrifying. So as we’ve employed our ever-larger risk-management tool kits, it’s been easy to pretend that they work for uncertainty too. But they don’t.

Even worse, when we use ever more stringent mechanisms to control risk, we undermine exactly the characteristics that are needed to withstand uncertainty. When we limit creativity on the part of fund managers, our intention is to reduce risk, but instead we limit adaptation. When we create funds of funds like those target-date offerings, our intention is to reduce risk, but in doing so, we limit diversity. When we increase regulation and distribution, our intention is to reduce risk, but instead we increase centralization.

Our efforts to control risk have been in direct conflict with building an adaptive, resilient system.

Evolution

When I survey the investing landscape, I’m encouraged to see more and more “unboxed” investment approaches springing up. Some of these are occurring in the social investing, impact investing, and patient capital arenas, where the lines between philanthropy and investing are more and more blurred. Organizations like Acumen are pioneering “first loss” investments with philanthropic dollars, which allow more traditional investors to collaborate more easily on innovative social business ventures. Numerous family foundations have decided to deploy all of their assets toward their missions, not just the 5 percent they’d normally give away in grants each year. Discussions of “full-spectrum” investing have flipped their focus, from centering on what vehicle to use—that is, what box to choose—to what outcomes are sought—that is, what kind of world we want to foster with our efforts.

Some sense of the energy—and chaos—surrounding these unboxed investment approaches can be gained by observing the SoCap conference, held every fall in San Francisco. Topics range from gender lens investing to ocean-related endeavors to urban innovation to partnerships with indigenous communities. … In short, everything that you likely won’t find on your 401(k) form. Yet. In one short hour at the conference this year, I ran into friends from my biomimicry class, a spiritual conscious investing group, a women’s research project, a local food–advocacy organization, and a good old-fashioned venture capital firm. My mentor Susan Davis always advises that to start a revolution, you should throw a better party, and gatherings like SoCap are definitely more fun than most traditional Wall Street conferences are these days.

One critique of impact investing and other innovative approaches is that they sometimes appear to be clubs that are closed to all but the very wealthy, due to curious laws that are intended to “protect” others from taking too much risk with their money. Thankfully, many people are not daunted by this set of structures, and are finding ways to invest “out of the box” with whatever mechanisms make sense. The Transition Movement is helping local communities invest in a carbon-free future.10 Farmer’s markets and community agriculture programs are seeing record growth throughout the United States. Gift giving increasingly includes free-trade goods, charitable donations, or personal experiences, instead of mass-produced stuff. None of these activities fits on the Morningstar grid, and that’s exactly the point.

Pathway to Practice

Our search for resilience in portfolio management has been replaced by the partial—and often false—comfort of “risk management.” Yet within that misdirected journey, we can still dig back to the roots, identifying helpful starting points to set us on a more adaptable course. And then we can send up shoots, beginning to take steps along a different, more resilient pathway of practice.

The first step on that more resilient pathway is to refocus the questions we are trying to answer and to expand them to their higher level of significance. We do not need to ask why the tracking error for any given mutual fund changed by 0.1 in the latest quarter; we need to ask whether we are building adaptable, resilient products and systems. This shift in focus is like tending the garden versus being constantly in harvest mode.

Most importantly, we need to consider how to prepare for uncertainty, and to acknowledge that this preparation might include things that appear inefficient—or even risky—in the short term. Preparing for uncertainty connects with all the principles of adaptation that we’ve discussed in this chapter: investing in renewal, variation, redundancy, decentralization, and diversity. This preparation is like planting fruit trees that will benefit your children more than yourself, or adding a few drought-tolerant species even if it’s raining this week and the risk seems remote.

Once we establish this initial reorientation toward resilience in our investing, other layers of opportunity are revealed. For example, our portfolios should be adaptive and resilient, sure, but isn’t one way to accomplish this to invest in other entities that are themselves adaptive and resilient enterprises? This is the investing equivalent of planting new seeds, trying new crops. Some will fail, to be sure, but some will flourish.

With this question in mind, we can extend our thinking beyond the current boxes and pie charts, which are mainly comprised of public securities of large institutions plus sometimes an extra wedge for gold or real estate. Once we consider adaptation and resilience seriously, the question is not whether large-cap stocks will outperform small caps, or whether muni bonds will outperform Treasuries. The real question is whether our investing is supporting entities that are themselves resilient, and that are contributing in turn to resilience of life on earth. This is not reflected in any asset allocation pie chart I’ve seen, nor is it answered by owning a fund of funds.

Many of the tools and processes that have been developed in investing over the last thirty years are rooted in modern portfolio theory. This theory reflects a clear desire to understand, measure, and control risk, but it has some major shortcomings, much like the mutual fund tools we’ve analyzed in this chapter. Most significantly, it narrows the definitions of risk. This makes it easy to misinterpret various calculations, and to assume they mean much more than they really do.

Employing life’s principles helps us to refocus on bigger, more essential questions, and bigger, more essential functions. This in turn enables us to redirect our processes, procedures, and products—to realign them with essential concepts like adaptability and resilience. So instead of asking, what Morningstar box does this fund belong in? Or, what is the Sharpe ratio for this portfolio? We can ask, is this approach adaptable? Does it demonstrate variation, redundancy, and decentralization? Is it reflecting diversity in how form meets function?

Sowing Seeds of Resilience in Your Own Investing

One of the most important words related to the adaptability principles is “appropriate”: the goal is appropriate reaction to changing conditions. Now that we have examined some of the challenges our current investing has with respect to this principle, what is the appropriate reaction?

Consider the distinction between risk and uncertainty carefully. Be sure to avoid relying on traditional risk tools in situations where the real concern is uncertainty.

Use data as information, not as a prescription for action. Tools are just that—inputs into the decision-making process, not determinants of its outcome.

Plan feedback loops that match the intended function—seek data that demonstrate alignment with adaptability principles. What’s measured should relate to the purpose of the investment, should refresh itself over time, and should be met with an appropriate receptor and reaction.

Beware of “duration trading”—approaches that might decrease short-term risk are tempting, but they also might undermine long-term resilience. Try not to trade one for the other.

Invest in variation, redundancy, decentralization, and diversity.

Like farmers who are fostering resilience by replanting fields with multiple crops, natural windbreaks, and fewer chemical treatments, we can reinvest in adaptation and the roots of resilience: variation, redundancy, decentralization, and diversity.

We can move from rigid processes to responsive ones.

We can shift from mechanical to mindful.