Enterprise Resilience

In a world of ever-increasing complexity, connectivity, and turbulence, it is time to abandon the mechanistic view of the enterprise as a controllable artifact, and to view it instead as a living system embedded in a dynamic network. We can define the resilience of an enterprise in terms of its behavior as a living system:

A resilient enterprise continues to grow and evolve in order to meet the needs and expectations of its shareholders and stakeholders. It adapts successfully to disruptive changes by anticipating risks, recognizing opportunities, and designing robust products and processes.

It follows that resilience requires both a focus on internal process excellence and an awareness of emerging patterns in externally coupled systems, including regulatory, socio-economic, and environmental changes.

An overview of enterprise resilience is suggested in the table below, divided into both functional and structural aspects. At the strategic level, managers are concerned with robustness of the enterprise over time scales that are measured in years. Here, functional resilience involves understanding strategic threats or opportunities and developing creative and powerful responses (e.g., innovative products). Structural resilience involves organizing the enterprise to reduce vulnerability to change and increase versatility (e.g., diversifying through acquisition). At the tactical or operational level, managers are concerned with continuity of the enterprise over shorter time scales. Here, functional resilience involves agility in recognizing and resolving problems (e.g., emergency response), and structural resilience involves establishing safeguards against disruption (e.g., alternate supply channels). While adaptation in natural systems usually requires genetic evolution, human enterprises can anticipate change and respond more rapidly.

Table 1: Multiple Aspects of Enterprise Resilience

Functional
(Sense, Respond)

Structural
(Organize, Build)

Strategic

(Robustness)

  • Adaptation

  • Innovation

  • Transformation

  • Fortification

  • Centralization

  • Diversification

Tactical or Operational (Continuity)

  • Recognition

  • Resistance

  • Recovery

  • Redundancy

  • Flexibility

  • Security


Insights into the resilience of complex systems can help to design more resilient business models. For example, a collection of distributed electric generators (e.g., fuel cells) connected to a power grid can be more resilient than a central power station in handling disruptions – this is a form of structural resilience. Similarly, a geographically dispersed workforce linked by telecommunications may be less vulnerable to catastrophic events that could disable a centralized facility. Alternatively, flexible manufacturing facilities and versatility of employee skills are examples of functional resilience in supply chain management.

To better understand enterprise resilience, it is helpful to examine the properties of other complex systems. The concept of resilience originated in the ecological and social sciences, where it is critical for survival and growth. Ecologists define resilience as the capacity of a system to tolerate disturbances while retaining its structure and function. Similarly, psychologists define human resilience as the ability to transform adversity into a growth experience. Research on complex, non-linear systems suggests that they perpetually evolve through an “adaptive cycle” of growth, crisis, transformation, and renewal as shown in Figure 1; for example, mature forests are periodically destroyed by fire or vermin, and then regenerate.

Figure 1: The Adaptive Cycle in Complex Systems

Holling's Figure 8 diagram

Source: L.H. Gunderson and C.S. Holling, eds., Panarchy, Island Press, 2002.


In the business world, the adaptive cycle applies at many different levels, from the life cycle of a product to fluctuations in the global economy. The front loop of the adaptive cycle is similar to the well-known S-curve, or logistic curve, which rises steeply and then flattens out due to constraints on growth. This period is typified by gradual accumulation of wealth, increasing connectedness, and decreasing resilience. Eventually, the system is destabilized by one or more disruptions – examples include industrial accidents, political upheavals, economic crises, disease epidemics, technological failures. This leads to collapse of the existing equilibrium, and the system enters a period of chaotic change and reorganization, corresponding to the back loop of the adaptive cycle, during which wealth is depleted and connectedness decreases dramatically. However, this process of “creative destruction,” provides opportunities for innovation – new scientific discoveries, new institutions, new relationships, and new business processes – so that the system shifts into a more resilient state and re-enters the growth phase.

Disruptions are not always triggered by catastrophic events. In a highly connected industrial system such as a complex supply network, small disturbances can occasionally cascade into massive discontinuities that have lasting impacts on the business. Non-linearity implies that these radical shifts can occur suddenly, when conditions reach a “tipping point.” Unfortunately, the very system complexity that generates these disturbances makes it virtually impossible to predict their nature or timing. Smooth changes can usually be tolerated by adjusting the system behavior, but real systems don’t have smooth curves.

Statisticians have found that complex, interconnected systems often follow a power law pattern; for example, an event of magnitude X might occur with a frequency of 1/X2. This means that extreme events are much more likely than predicted by the commonly-used normal, bell-shaped distribution, which assumes independence among system components. The power law explains the apparent frequency of extreme disruptions, such as hurricanes, stock market swings, and traffic jams. While it is difficult to predict these occurrences, we may be able to improve enterprise resilience by anticipating change scenarios and finding creative ways to take advantage of the system dynamics rather than merely reacting to disturbances