The Demand Driven Adaptive Enterprise. Carol Ptak
care as they progress through admittance, a medical unit, a Definitive Observation Unit (DOU), and finally an Intensive Care Unit (ICU).
FIGURE 1-2 Alternate strategic target chart scenario
Figure 1-2 depicts three different scenarios. In each case, the relative positions of each of the three considerations are plotted. It should be pointed out that all three of these scenarios are simply a point in time reference; it could be the same company just at different points in time or it could be three different companies at one point or even different points in time. The position and tension between these three important considerations is constantly shifting.
Which scenario is healthier? The scenario on the left may represent a company that is performing relatively well with regard to contribution margin and the market but is suffering from a working capital crisis. The middle scenario depicts a company that is failing to generate cash and is suffering from a working capital crunch. The scenario on the right is a company that is generating a high amount of cash, has abundant working capital and a well-defended and growing base of customers.
But how can leadership best hope to manage these basic elements in a VUCA environment? The key to both the short-term and long-term management of these elements can be found in concepts called “coherence” and “resiliency.”
Striving for Coherence and Resiliency
Coherence and resiliency are key terms in the emerging science of complex adaptive systems. What is a complex adaptive system (CAS)? First, let’s understand that any complex system is governed by three important principles:
The word “adaptive” introduces the element of how a complex system changes or reconfigures itself through a process known as “emergence.” Once emergence has occurred, then feedback and selection occur over a period of time resulting in further reconfiguration to the system. When complex systems are co-mingled or intertwined (such as highly integrated supply chains) these events and steps tend to cascade across systems, making a highly complex and evolving picture. Figure 1-3 is a modified version of Figure 10.1 from the book Demand Driven Performance—Using Smart Metrics. It lists nine characteristics of a CAS.
FIGURE 1-3 Complex adaptive system characteristics7
At this time we will focus on only two of these characteristics. The first is coherence. A complex adaptive system’s “success” depends on the coherence of all of its parts. A subsystem’s purpose has to be in alignment with the purpose of the greater system in order for there to be coherence. Without that alignment, the subsystem acts in a way that endangers the greater system it depends on. Coherence must be at the forefront of determining the signal set components, triggers, and action priorities. To maintain coherence, adaptive agents must ensure their signal sets contain the relevant information to direct their actions and are not at cross-purposes with the goals of the systems it depends on.8 The concept of coherence is consistent with the systemic approaches of thought leaders such as Ohno, Goldratt, and Deming and their respective disciplines of lean, Theory of Constraints, and Six Sigma. All of these disciplines urge management to organize and operate in a manner that emphasizes carefully aligning local actions to the global objective. Deming and Goldratt in particular were extremely opinionated about the failure of management and executives to understand and effectively embrace this concept, which is one that seems rooted in basic common sense.
The second characteristic of a CAS to be explored is resiliency. Resiliency allows a system to respond to a disturbance while maintaining equilibrium within its system boundary. In supply chain words, resilience is how well a system can return to stability when it experiences random or self-imposed variation. Resilience arises from the subsystem’s ability to respond to the feedback loops that regulate equilibrium. The ability to adapt and the diversity or flexibility of options/actions determines how quickly the system can recover and/or improve. The opposite of resiliency is rigidity.9
Obviously, if a system is insufficiently resilient relative to the level of disturbance, it is at risk of collapse. Reeves, Levin, and Ueda identified six basic risks to the resiliency of a complex system.10 Any organization wishing to avoid the threat of collapse must mitigate these risks. In the VUCA world these risks are more prevalent than ever.