Business Agility not only adds additional organizational disciplines into a Lean Agile framework, it also adds inherent complexity* into its corresponding Value Stream**. This added complexity can be called Value Stream Complexity because it is embodied within the Value Stream itself.
Value Stream Complexity, as introduced here, is a reflection of the interaction dynamics that emerge within the process states of the Value Stream when cross-organizational disciplines are added into the Business Agility Value Stream. The interaction dynamics occur because each state in the Value Stream may produce variable output values due to the cross-organizational interaction AND each of the varying outputs produced from a Value Stream state can produce changes in the processing actions taken within subsequent states of the Value Stream. The output of one state can thereby change not only the output of other states but also the processing itself within another state. The combinatorial effect of the interaction dynamics results in a changing system, not merely changing outputs of the system.
As an analogous system of complex interaction, consider the dynamics that occur within neural networks comprised of both excitatory and inhibitory neurons. Each neuron can change the processing behavior of other neurons within the neural network system as a whole, based on the particular type of output it produces. For example, an excitatory output may trigger a set of actions, whereas an inhibitory output may constrain another set of actions. The resulting output of the neural network as a whole is changed based upon the interactions of the excitatory and inhibitory neural outputs within the overall system. This complexity cannot be simplified away, but rather must be modeled or explored to capture the richness of the processing capabilities; this is termed true complexity.
Similarly with Value Stream Complexity; the complexity of the interactions between states cannot be simplified as isolated and segmented processing states because the system itself changes based upon not only the respective states themselves but also the effects of the interactions between the states.
The key starting point for addressing Value Stream Complexity is to recognize the existence of this complexity within the Value Stream so that it can be explored and modeled. Techniques for handling this complexity, as well as additional discussion points on these topics, will be presented in subsequent posts.
* The term “complexity“, as used in this context, is related to the corresponding definition as described in Team of Teams by Gen. McChrystal (2015) and in Cynefin by Snowden (2010).
** Value Stream as used here refers to the Lean Agility concept of a system-level process flow map with a collection of embedded metrics; these metrics include a timeline for value-add and non-value-add process states, as well as the delays between process states.