Most of the managers and executives we meet on a day to day basis are stuck in a paradigm of thinking about their companies, their industries, and their supply chains with a Newtonian world view.
Newtonian systems are linear systems and generally share the following characteristics:
- The whole system, and its performance, can be understood by studying the systems individual parts and functions. In this sense, Newtonian systems operate as “the sum of their parts.”
- The system state is relatively stable and quite predictable.
- The outputs of a linear system is proportional to the system’s inputs
- The Newtonian (linear) system’s performance can generally be pretty well modeled using a normal distribution curve. The tails of the distribution in such curves constitute anomalies in the performance of the system as a whole.
- Newtonian systems can be optimized
Your Supply Chain Is Not “Normal”
While you and your management team may still be under the misconception that your company’s, or your industry’s, or your supply chain’s performance is Newtonian in nature and may be model on a “normal distribution,” I believe that your experience will reveal the error in this thinking about these matters.
Simply ask yourself, and answer, these questions (taken from the bullet-points above):
- Is your company or your supply chain “relatively stable and quite predictable”?
- Is the output of your company or your supply chain directly “proportional to the system’s inputs”?
- Is there anything approaching a “normal distribution” in the events that make up your day to day activities in managing your operations or your supply chain? Do you spend most of your time on “normal” activities and only a tiny fraction of your time and energy on firefighting the “tail” events, or is it just the other way around?
- Have you successfully optimized your system and everything is under control now?
Your Supply Chain Is a CAS – Complex Adaptive System
Complex adaptive systems (CAS) are not linear. Instead, they are characterized by the following:
- Complex nonlinear systems can only be comprehended by mapping and coming to understand the dependencies and interconnections of the parts and functions.
- Complex nonlinear systems are highly dynamic and no predictions are valid for long
- Complex nonlinear systems tend to have fuzzy boundaries (it is hard to tell what is influencing what, especially at the edges of the system)
- Complex nonlinear systems are embedded with other systems and co-evolve (look and the diagram above and realize that each other system—your customers, your vendors, your distribution channel, and so forth—are all systems of their own that are “embedded” in your system and coexist and co-evolve with your company)
- The outputs of complex nonlinear systems are governed by a few critical points of interaction and are not directly proportional to inputs
- Complex nonlinear systems tend present with a Paretian statistical model where the tail events provide the relevant information for management and improvement
- Complex nonlinear systems cannot be optimized, but can be continually improved
The accompanying illustration shows only a tiny portion of the interactions that might occur in the complex adaptive system we call a “supply chain.” Actions of customers are not linear and predictable. Instead, the actions of customers are adaptive and based on internalized rules and thought processes influenced by the actions taken by other players—such as the distribution channel or even economic or political climate in which they operate. There are, quite literally, millions of immeasurable, untraceable interactions that affect the decision-making and actions of each player in the CAS.
Such unpredictability cannot be the rational subject of mathematical forecasting with any hope of accuracy that could be used to drive day-to-day actions. Predictability within a range is possible and can be used for scaling and long-range to mid-range capacity planning only.
Your “Levers” Don’t Work as Designed
You, doubtless, have experienced repeated the fact that simple “levers” devised based on Newtonian assumptions do not work in the management of a CAS.
For example, reducing costs does not necessarily—in fact, seldom does—result in increasing profits. This, despite the fact that in the boardroom or in the C-suite the executives are still correlating “reducing costs” with “improving profits.”
Something has got to change!
Take another look at the first bullet-point under the characteristics of a CAS:
Complex nonlinear systems can only be comprehended by mapping and coming to understand the dependencies and interconnections of the parts and functions.
The primary approach we take in working with new clients seeking internal or supply chain improvement involves building a logical map of the dependencies and interconnections involved in their CAS.
Of course, we realize there is no way to comprehend or map all of the millions of complex interactions. Instead, we try to help them narrow their focus to the ten or so key interactions that are clearly preventing them from making more money tomorrow than they are making today. That tend to be enough to help them get started down a path of ongoing improvement that leads to broad, system-wide, low-investment, profit-improving results.
It tends to rapidly change frustration and anger to smiles in a matter of a few short days or weeks.
You should give it a try.
Please leave your comments and questions below. What do you think? Is your company or supply chain a linear Newtonian system, or a CAS?
Contact us and we will send you a whitepaper from Demand Driven Institute entitled The Demand Driven Adaptive System.