A sentiment from the recent World Economic Forum at Davos, “No more heroes for the global elite,” when used as a barometer for what is currently exciting the world, indicates that we are at an inflection point. The assessment suggests that the norms and standards that usually generate enthusiasm — whether a leader who has caught the imagination of the world, a promising regional economy that will drive global growth or an innovative new technology — simply do not exist. In complex adaptive systems (CAS) terms, this likely translates to being in a state of "far from equilibrium."
Typical CAS characteristics such as "far from equilibrium" and "sensitive dependence on initial conditions," among others, can be used to guide an approach to planning. Such an approach often results in the generation of a range of algorithms that, in concert, push an organization to more rapidly become sustainable.
Plans Versus Planning
Being far from equilibrium is not necessarily a bad thing, precisely because it requires exploring spaces of possibility that will create different structures and new patterns of relationship. It is at times like these that Eisenhower’s dictum “Plans are useless, but planning is indispensable” becomes useful — and not least because this highlights a fundamental approach to successfully operating in a CAS.
Among characteristics common in CAS, those which easily marginalize the utility of plans include distributed control, co-evolution of divergent elements, emergence of surprising structures and processes, presence of both order and chaos and a general sense of unpredictability. It is precisely this general nature of unpredictability that paradoxically makes the discipline of planning very useful. This is because a rigorous process of planning marked by practices such as scenario analyses, simulations and generating a range of algorithms more easily attune an organization to the real-time situation or scenario it may be entering into.
The recognition of markers associated with a situation, and any planning process that has already interpreted aspects of a possible situation, will likely increase an organization’s success. Success will be amplified if such planning results in a set of algorithms that accentuate possibilities centered on such markers. This is generally due to another CAS property — sensitive dependence on initial conditions — that tend to morph a market in favor of an organization most ready to capitalize on dynamic possibilities in that market.
An Output Of Planning
For example, the design of our pricing algorithms at Zappos is an instance of a complex organizational problem and could not have come about without planning how products might behave in a given market. Each algorithm is based on a set of assumptions of how customers, competitors, products, channels and possible value propositions may interact as drivers in such a market where no single, central authority is the coordinator. As the interaction between these drivers proceeds, a product’s behavior or positioning in the market will change in real time. The change is primarily driven by the evolution of the market itself, which will reward real-time adaptability in line with the market’s own urge of development.
Hence, most of our website's available products are assigned an algorithm that assumes a view of the market based on a combination of customer, competitor, product, channel and value-proposition elements. An algorithm may generally be optimized for some financial goal, and the performance of that goal will unequivocally indicate the direction in which a particular segment of the market is evolving.
There is no plan, hence, but the act of planning has resulted in a set of algorithms that will dynamically adjust how products exist in the market in real time. These algorithms must be fine-tuned, diversified or temporarily shelved accordingly. Products must be reassigned to different algorithms. In this manner, a set of financial metrics and other objectives can more easily be optimized for.
Application Of Algorithms To The Human Resources Space
A similar process can be extended into the realm of human resources. Hence, reimagining an organization as a complex adaptive system of many autonomous “nodes” — people, teams and departments — multiple “algorithms” or dynamic-processes can be created that optimize for different organizational goals.
An algorithm can exist for fulfilling profitability goals. Another algorithm can exist for optimizing entropy. Real-time management of entropy takes place through EQ. Entropy scores and scores of a number of related metrics automatically generate customized recommendations for teams and areas of an organization. These recommendations aim at optimizing that part of the organization to achieve a lower entropy score. Here, the whole process where entropy and EQ interact to create a more creative and sustainable organization is none other than an instance of an algorithm.
Algorithms for individual development, and development of key organizational principles, can similarly be created. These will each be assigned to a set of nodes and those nodes will operate in a manner constrained by the algorithms.
The advantage of such an approach to planning, encapsulated by dynamic algorithms that cause rapid shifts in outcomes, is that an organization will be able to adapt, evolve and even shape a market in real time.
