An Adaptor Strategy for Enterprise Risk Management Part II, Investing In Resilience: Nurturing Human and Financial Resources

By M. Bruce Beck, D. Ingram and M. Thompson

Risk Management, June 2022


In this second part of our article[1], our focus is on the nurturing function of the Adaptor. If the Adaptor’s switching function set out in Part I is all about operating an already “built” business, its nurturing function is all about what precedes that operational stage. It is about investing in the built make-up and fabric of the business—its diversified asset portfolio, its people, their skills—thus to enable that business to operate with resilience. Such Adaptor nurturing might even position the business to experience the benefits of “bouncing forward,” as a part of some Schumpeterian “creative destruction.”

But we are not quite finished with the nuts and bolts of the control engineering that drove our argument in Part I. Because resilience is all about the dynamics of a system. And the whole point of control engineering is this: Take the dynamic behavior of the system as is (be it economy, business, portfolio, whatever) and re-engineer it so that it is more to our liking. We shall close with something further on this, something strange-sounding: A “non-minimum-phase” system. Perhaps it might be exploited to disrupt any propensity of an investment portfolio to suffer from pro-cyclicality in the markets and economies of the business’s operating environment.

Adaptor Exceptionalism: A Reminder

This is the gist of our argument. Rational Adaptability (RA) for enterprise risk management (ERM) has been in place for over a decade now. Each risk-coping strategy in that scheme—maximizer, conservator, pragmatist, and manager—is ideally tailored to the needs of one of the four seasons of risk (Figure 2, Part I). This foursome may be referred to as the Basic 4 rationalities of Cultural Theory (CT).

The fifth rationality of CT (that of the Adaptor) does not appear in our previous scheme of RA for ERM. It has lain dormant, as it were, until now. As the Special +1 Adaptor strategy this fifth rationality is to be charged with fulfilling two qualitatively different functions:

  • Switching, of swapping one risk-coping strategy out of the company’s driving seat and substituting in another, as and when the season of risk turns.
  • Nurturing, to ensure the company has the wherewithal—inter alia—to expedite the switching, precisely because the Adaptor has been sustaining the viability of the new risk strategy to be substituted into the driving seat, when the moment comes.

There is a “long and short of it” to this exceptionalism of the Adaptor: A label T signaling (literally) slow time, i.e., the behavior of things and changes in things over the longer term; versus a label t, for quick time and variations in the shorter term, notably the everyday scale of making and implementing risk-coping decisions by the four strategies. Each (maximizer, conservator, pragmatist, or manager) avails itself in its own distinctive way of company operating data referenced in quick time t. These are data on the incoming risk disturbance stream d(t) in Figures 1 and 3 of Part I, the outgoing company performance y(t), and the company’s decisions u(t).

The attention of the Adaptor, in contrast, is focused on the status of the makeup of the company, as this evolves over the longer-term T. Building out a business is not done “once and for all.” It is ongoing, albeit (and this is the point) in slow time T. To nurture the system in this way, the Adaptor can be furnished with data on the ever-evolving structure of the business, as reflected in our special control-engineering ingredient of the time-varying model parameters α(T). These α(T) are the coefficients appearing, for example, in econometric-like models of how the d(t), y(t), and u(t) vary and are related one to another.

Given doubtless the unfamiliarity for most readers of this device (α(T)), Part I provides a link to a lengthy discussion thereof. It is, we may say, an exercise in entering into and clambering about in the abstraction of parameter-space α(T). But this does have its lighter moments, even one that might put a smile on your face.

What We can Find and Admire in the Resilience of Nature

That of which we speak so readily in everyday language, and of which we seem to want so much—“resilience,” that is—is something we should say is manifest outwith. We observe something we construe as part of it in the phrase “bounce back,” as in an economy bouncing back to recover its pre-disturbance equilibrium or growth trend. We observe this as something of the outward-facing behavior of a system, in the business output-response outcomes—technically, the y(t). Much of what we experience in these desired outward-facing features is born of what is within, within the structure and make-up α(T) of the system.

The sense of resilience being unfolded in this Part II of our article, i.e., resilience as a systemic property, is due originally to systems ecologists.[2] If we asked, therefore, what might be the epitome of what we so admire of resilience in the ecosystems of nature, this would be our answer. A part of the pine forest is being destroyed by fire; on the floor of this patch of forest, lies a pinecone, sealed with resin; the resin requires the intense heat of the fire for its melting; before germination is initiated; to yield up, in a word, rebirth.

This rebirth—as something of the kernel of resilience—belongs to the systems of Nature. It is the rebirth that leads to repetition of the cycle that has gone before. The germinated pine seed matures to become essentially exactly the same species of pine tree in the forest as the cone from which it derived, at least in our lifetimes. It is the product we find today as the outcome of prior eons of natural evolution.

In contrast, the bounce forward to a novel cycle not witnessed before, belongs to the systems of Man. This bouncing forward is a process of (relatively) “super-fast” evolution over perhaps months to a decade or two (of the order of T therefore). It occurs in the co-evolving supra-systems (identified as {…}) of {Technology}, {Economy}, {Human Needs-Wants}, and {Mobilizable Resources}.

In short, the distinction between resilience and bounce forward resides in these juxtaposed couples: Rebirth and repetition versus novelty; Nature versus Man; and prior eons versus months-years-decades now and to come.[3]

Recovery from shock within an unchanging season of risk can be said to be the bounce back of local stability in the behavior of the business. Navigating with aplomb through all the chops and changes in the seasons (and the within-season shocks along the way)—thus to emerge from the past business cycle fully ready to embark on another cycle—can be said to be global resilience in the behavior of a business.

Something of the kernel of resilience resides in this: The diversity of species in the ecosystem. Which to unpack a little, implies the following.

Organization in an Ecosystem

Basically, the ecosystem as a whole remains resilient (and does not fail) as a function of diversity in its parts (the species); each of which species fulfills functions without which the ecosystem as a whole would not remain viable, to persist and endure. Indeed, peering deeper into the details of the organization of ecosystems, it is argued that duplication of the discharge of these whole-system-critical functions by more than one part (one species) is of the essence in resilience. In stark contrast to our technocratic view of systems, redundancy (and indeed some inefficiency) in the discharge of such functions by more than one mechanism—more than one employee, more than one investment vehicle—is crucial.

We encounter in the natural world what we have come to call “ecosystems.” We have looked into their organization, to grasp the essence of what bestows resilience on the behavior and integrity of these systems, which we have (all) come to know and cherish. What we see in them today is, as we have observed, the result of evolutionary processes over past eons—well beyond the comparatively short span of business cycles.

Can we too have something of this essence in our business systems of resilience … please? Well, yes, maybe.

To make a start we shall need some in principle scheme for monitoring the declining (or rising) potential within the inner makeup of the business for navigating the risk environment with resilience, business cycle after business cycle. An Adaptor dashboard might be what we are looking for. After that, we shall need to be persuaded that something like this dashboard might work in practice.

The Thought of a Dashboard—for Tracking Diversity and Duplication in Nurturing the Affairs of a Business

The archetypal problem in economics—of allocating scarce resources in meeting human needs and wants—has been approached from the fivefold perspectives of our maximizer, conservator, manager, pragmatist, and, somewhat exceptionally, that of the Adaptor. This appeared as a chapter in a 2010 edited volume The Limits to Scarcity. Contesting the Politics of Allocation. The chapter was based on an outline of a one-act farce with the foregoing five dramatis personae, each with their own distinctive “way of economizing.”

The key insight for present purposes—of introducing the idea of an Adaptor dashboard—was this. Scarcity per se is not the problem. It is when the voice of any one of the five characters is silenced—when scarcity-based policy decisions go uncontested—that (to quote) “the little red warning lights should start blinking.”

A light-bulb moment indeed: For a dashboard, no less!

Beginning to Take Shape: The Adaptor’s Dashboard

This is the nascent idea. Resilience in the organizational make-up of an ecosystem depends on preserving the diversity of species: To sustain the discharge of functions critical to the whole-system retaining its viability, hence the capacity of that system to endure and evolve over the long term.

Resilience in the organizational make-up of a business should accordingly depend on preserving the viability of all five of our attitudes, with the Adaptor provided with a dashboard of colored-flashing lights signaling the viability—or otherwise—of each of the other four risk-coping strategists. In principle, none of the four should ever be denied their voice or go extinct (with no devotees, advocates, proponents).

So, reflect on this. In everything of our argument hitherto—in respect of Rational Adaptability for ERM using the Surprise typology; in respect of the Adaptor switching function in the cascade control scheme of Figure 3 (Part I) and its subsequent elaboration—the new autopilot for the new season of risk should be ready to occupy the company driving seat “in a heartbeat.” If that autopilot has been rendered non-viable, forget company resilience in the longer term. Witness, for example, the “Great Moderation” in the U.S. economy from 1984 to 2007 (the inspiration for our season of moderate). During such a long run of any one type of risk environment, people and groups tend to migrate toward a risk attitude that is consistent with that long-standing environment, while others wane and wither. After all, given the Great Moderation, surely boom and bust as such (uncertain, too) must finally have been banished from the economic cycle? The only way must be the manager way—surely?

Flashing red lights would have been positively blinding the Adaptor—had there been a dashboard with lights to flash … and an Adaptor to apprehend and comprehend them.

Reflect on this too, in passing. Creativity in problem-solving should derive from a plurality of candidate risk-coping decisions, from among which the one and only decision is selected for enactment. In other words, there should be the benefit of a plurality of “bases to be touched” before proceeding.

Monitoring and Investing in the Human Resources of a System: The Linz Innovation Ecosystem, Austria

This likewise has systems ecology as its origin; the very same leads that brought us to the little red warning lights in contesting the politics of resource allocation.

A few years ago, the city of Linz established an innovation ecosystem on the site of a former tobacco plant (Tabakfabrik). Tens of businesses are now established on the site. An inventory (not a dashboard as such) of some 60 “personality types” among employees distributed across these businesses has been drawn up and is being actively maintained.

Each personality type fulfills a specific role: From “the seeker” to “the destroyer,” and a host of types in-between—including types well suited to touching off some bounce forward. Several of each such type fulfill roles assumed by employees categorized as maximizer, conservator, manager, pragmatist, and Adaptor. The inventory of human resources for the whole innovation ecosystem is therefore a 2D matrix: Of roles; and their parent rationality (and, of course, parenthetically, their company affiliation). In effect, there is a dashboard with multiple panels of colored lights, each capable of flashing.

In actuality, in the Linz innovation ecosystem, a colored “slide-bar” table has been assembled from personnel survey data. It refers to 12 personality types (employee skills/roles). Each of the 12 bars comprises a red, a white, and a blue segment: Red signaling “more” such types are needed; white for “OK”; and blue for “fewer” such types. Not quite little red lights flashing, but one gets the idea.

Actions, moreover, are taken on the basis of the dashboard’s status: To communicate to whomsoever (in whichever business) events such as the following. A dashboard light flashes red, to signal the conspicuous absence from the ecosystem campus of an employee with the requisite personality trait. Or, worse still for resilience in the ecosystem, multiple flashing red lights signal no employees with the relevant traits in any of the roles categorized as, say, pragmatist, ergo the absence of an entire voice on campus, or an entire and distinct risk-coping strategy. Imagine a business with no skilled proponent of the pragmatist’s strategy of diversification, as and when the company’s season of risk transitions to uncertainty. The actionable item would be to pre-empt such a state of affairs: To train or recruit an employee with the requisite skill(s).

This—and this is the punchline—is tantamount to an Adaptor investing in nurturing the human-capital make-up of the (whole) innovation ecosystem.[4] It is the second function, to accompany the Adaptor’s switching function (of autopilot swapping).[5]

Something Like This in an Insurer?

The words we are using here are ones somewhat divorced from the individual person, the individual employee. There is, first, the “whole-system, mission-critical functions,” such as the four ways of discharging risk-coping. Each of which is supremely critical depending on the given season of risk. Second, there are clusters of employees who, quite naturally and inevitably, organize themselves as a function of the social-power dynamics at work and unfolding in the company. These groups—“rationalities,” “solidarities”—collectively discharge the mission-critical functions.

In reality, there are we the people; we plain, ordinary, individual human beings. We exert influence over others; they exert it over us; and some of us—CEOs, for example—have significantly more power than others.

Individuals, with their prior risk-coping prejudices, are hired; while employed in the company, individuals may migrate out of one prior stance on risk and into another (and another); and individuals retire, taking with them their evolved risk-coping preferences. It can take the retirement of but a single individual for an entire strategy to be lost from the company, for instance, that of the conservator. The CEO can determine hires and fires. CEOs can impose their risk-coping preference on and over any current risk-coping preference of an employee.

Stuff happens; life happens. Yet in the midst of the company’s social-power dynamics—but somehow wondrously disengaged from it—the Adaptor is supposed to be keeping a (just-as-marvelously effective) well-trained eye on nurturing the diversity of risk-coping talents among the rest of us—caught up in the tumult of all these dynamics.

Take the mock-up below (Table 1) of an Adaptor dashboard. It has been assembled on the basis of our prior work on RA for ERM.[6] The distributions of personnel upholding each of the four risk-coping strategies is shown for 14 different insurers. Highlighted in red are instances that might be of concern to our hypothetical Adaptor in any one of the companies. These are instances of companies in which (at the time of our survey) fewer than 10 percent, or more than 50 percent, of personnel adhere to one or more of the four strategies. The nurturing instinct of the company Adaptor would be to advocate rebalancing of these skewed distributions.

Table 1
Adaptor Dashboard

Company Conservator Manager Maximizer Pragmatist
1 4% 38% 27% 31%
2 18% 38% 33% 12%
3 19% 36% 26% 19%
4 13% 31% 31% 24%
5 0% 44% 0% 56%
6 12% 41% 20% 27%
7 8% 38% 38% 15%
8 0% 44% 44% 11%
9 0% 40% 27% 33%
10 24% 47% 22% 7%
11 8% 54% 31% 8%
12 10% 34% 24% 31%
13 3% 52% 19% 26%
14 29% 41% 21% 9%

The challenge is this. In the light of this article, could the presence and practice of some elements of an Adaptor strategy improve the sustainability of the plurality of bases to be touched prior to the making of a decision? What lessons could be distilled from practice in the Linz innovation ecosystem and transcribed into an insurance company?

So, What Would an Adaptor Do for the Financial Makeup of the Company?

If we can argue thus the case for charging our Adaptor with the task of investing in nurturing the social make-up of an entity, why not argue the case for charging the Adaptor with the task of nurturing its financial make-up?

Indeed, a novel (and perhaps more important) design feature can be introduced from the original principles of ecosystem organization. It is that of scale. The idea runs as follows. Resilience in the organization, hence the behavior of an ecosystem, resides in the presence and maintenance of diversity among the parts (species), and duplication (hence redundancy) in the discharge of whole-system-critical functions across scales. Achieving this is most readily apparent in respect of, first, species size and mass and, second, the spatial extent of their activities. Somewhat less obvious is the role of variety and diversity in the temporal scales of their respective dynamic behaviors.

Consider this. Though of quite different sizes, spatial ranges, and metabolic dynamics, the mouse and the moose both fulfill, hence duplicate, two of the crucial system-wide functions of a wetland ecosystem: Nutrient renewal and re-dispersal; and seed conditioning and dispersal. In our control engineering terms, each has its own quite different systemic, dynamic parameters: Of dead time (short—long); time-constant (fast—slow); natural frequency (high—low); damping factor (small—large); steady-state gain (small—large), and so on. So now, we note, we can conceive of yet another abstract category of parametric design space: Of an α(T) associated with the intrinsic dynamic properties of a portfolio, which are themselves varying slowly over time. Witness, in fact, the weakening over the years and decades of the restorative forces (something akin to a damping factor) in national economies, as discussed in the previously mentioned link.

The dynamic behavior of the whole of a portfolio of financial assets is ideally designed so as to minimize (inter alia) pro-cyclicality in the constituent behaviors of its part assets. The parts, while therefore delivering performance crucial to the portfolio as a whole, might desirably do so in ways that are maximally diverse in their individual temporal responses to one and the same financial shock: That some assets should go up when others go down. To which end there are some parameters attaching to the dynamic oddity of a so-called “non-minimum phase” system.[7] Now what financial assets might display that kind of behavior in response to which kind of shock?


There is a body of theory in control engineering having to do with adaptive control. Surprisingly perhaps, it has not been called upon in either of the two parts of this article. But it surely is in the link between Parts I and II. And there is more of it in a postscript to our article. An especially interesting class of adaptive control is touched upon therein. It is called “dual adaptive control.” It would be tantamount to probing the risks-unknowns and steering the business through one and the same premium-setting or reserving decision. There is more “clambering about” to be done in the α(T) space.

Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries, the newsletter editors, or the respective authors’ employers.

M. Bruce Beck, Ph.D., is scholar in residence, FASresearch, Vienna, and guest senior research scholar at the International Institute for Applied Systems Analysis (IIASA). He can be reached at

David Ingram, FSA, CERA, FRM, PRM, is part-time consultant at Actuarial Risk Management and an independent researcher, writer and speaker regarding ERM and insurers. He can be reached at

Michael Thompson, Ph.D., is emeritus scholar at the International Institute for Applied Systems Analysis (IIASA). He can be reached at


[1] Our article “The Adaptor Emerges” appears in the December 2021 issue of The Actuary magazine. It is available here: It is based on our Research Report to the Society of Actuaries on “Modeling the Variety of Decision Making” (2021).

[2] The material differences among the attributes of stability, resilience, bounce back, renewal (in the ecological sense), bounce forward, and creative destruction (in the economic sense) are discussed at length in the Link. Salient here, however, is that the nature of bounce back has been equated by systems ecologist Holling to engineering resilience — especially the “engineering” of control engineering(!) — when what he argues is really needed, is a good deal of what he calls ecological resilience.

[3] Bounce forward, as distinct from resilience (as discussed in the Link), is a positive instance of that oft-heard phrase in economics of “structural change,” which itself is often associated with the schools of evolutionary economics and complexity economics, in the form of the co-evolving supra-systems just mentioned. Witness, notably W Brian Arthur’s 2009 book The Nature of Technology. What It Is and How It Evolves. The treatment of structural change in the Link is in turn itself an exercise in cross-disciplinary Systems Thinking. All the core ideas (and ways of dealing with structural change) derive from the 2002 book Environmental Foresight and Models: A Manifesto. It is authored and edited by MBB.

[4] Including the structures and procedures for achieving the highest of deliberative quality in the governance surrounding business decision making.

[5] Which all begs the question: Who is the Adaptor type for the Linz innovation ecosystem? It is, we submit, Harald Katzmair, founder and CEO of FASresearch, Vienna. He, however, wisely declines to confirm or deny any such attribution.

[6] Underwood, Ingram, and Thompson, “All on the Same Train But Headed in Different Directions,” Intelligent Risk (2014).

[7] An aircraft behaves as a non-minimum phase system in the following sense. If the pilot wishes to have the aircraft climb, the action taken to achieve this causes the center of mass of the plane to fall before it climbs. The general nature of a non-minimum phase system, therefore, is that its initial response to perturbation is in the opposite direction to its later (and enduring) response.