Thriving in a Chaordic World
Former Visa International CEO Dee Hock (1999) coined the word "chaordic" to describe both the world around us and his approach to managing a far-flung enterprisebalanced on the precipice between chaos and order. Our sense of the world dictates management style. If the world is perceived as static, then production-style management practices will dominate. If the world is perceived as dynamic, however, then exploration-style management practices will come to the fore. Of course, it's not that simplethere is always a blend of static and dynamic, which means that managers must always perform a delicate balancing act.
In the last decade, a vanguard of scientists and managers have articulated a profound shift in their view about how organisms and organizations evolve, respond to change, and manage their growth. Scientists' findings about the tipping points of chemical reactions and the "swarm" behavior of ants have given organizational researchers insights into what makes successful companies and successful managers. Practitioners have studied how innovative groups work most effectively.
As quantum physics changed our notions of predictability and Darwin changed our perspective on evolution, complex adaptive systems (CAS) theory has reshaped scientific and management thinking. In an era of rapid change, we need better ways of making sense of the world around us. Just as biologists now study ecosystems as well as species, executives and managers need to understand the global economic and political ecosystems in which their companies compete.
A complex adaptive system, be it biologic or economic, is an ensemble of independent agents:
Who interact to create an ecosystem
Whose interaction is defined by the exchange of information
Whose individual actions are based on some system of internal rules
Who self-organize in nonlinear ways to produce emergent results
Who exhibit characteristics of both order and chaos
Who evolve over time (Highsmith 2000)
For an agile project, the ensemble includes core team members, customers, suppliers, executives, and other participants who interact with each other in various ways. It is these interactions, and the tacit and explicit information exchanges that occur within them, that project management practices need to facilitate.
The individual agent's actions are driven by a set of internal rulesthe core ideology and principles of APM, for example. Both scientific and management researchers have shown that a simple set of rules can generate complex behaviors and outcomes, whether in ant colonies or project teams. Complex rules, on the other hand, often become bureaucratic. How these rules are formulated has a significant impact on how the complex system operates.
Newtonian approaches predict results. CAS approaches create emergent results. "Emergence is a property of complex adaptive systems that creates some greater property of the whole (system behavior) from the interaction of the parts (self-organizing agent behavior). This emergent system behavior cannot be fully explained from measured behaviors of the agents. Emergent results cannot be predicted in the normal sense of cause and effect relationships, but they can be anticipated by creating patterns that have previously produced similar results" (Highsmith 2000). Creativity and innovation are the emergent results of well-functioning agile teams.
Another pair of words that indicate this perspective difference are optimization and adaptation. Optimization processes focus on efficiency and cost reduction. They are documented, measured, refined, and repeated. Adaptation processes focus on innovation, exploration, speed, and constantly reacting to meet external changes. Optimizing processes thrive in low-change, predictable environments, whereas adaptive processes thrive in high-change, uncertain ones.
An adaptive development process has a different character from an optimizing one. Optimizing reflects a basic prescriptive Plan-Design-Build lifecycle. Adapting reflects an organic, evolutionary Envision-Explore-Adapt lifecycle. An adaptive approach begins not with a single solution, but with multiple potential solutions (experiments). It explores and selects the best by applying a series of fitness tests (actual product features or simulations subjected to acceptance tests) and then adapting to feedback. When uncertainty is low, adaptive approaches run the risk of higher costs. When uncertainty is high, optimizing approaches run the risk of settling too early on a particular solution and stifling innovation. The salient point is that these two fundamental approaches to development are very different, and they require different processes, different management approaches, and different measurements of success.
Newtonian versus quantum, predictability versus flexibility, optimization versus adaptation, efficiency versus innovationall these dichotomies reflect a fundamentally different way of making sense of the world and how to manage effectively within it. Because of high iteration costs, the traditional perspective was predictive and change averse, and deterministic processes arose to support this traditional viewpoint. But our viewpoint needs to change. Executives, project managers, and development teams must embrace a different view of the new product development world, one that not only recognizes change in the business world, but also understands the power of driving down iteration costs to enable experimentation and emergent processes. Understanding these differences and how they affect product development is key to understanding APM.