A supply chain can be defined as a network of autonomous or semiautonomous business entities collectively responsible for procurement, manufacturing and distribution activities associated with one or more families of related products (Swaminathan, etc, 1998). Different entities in a supply chain operate subject to different sets of constraints and objectives. There is general consensus that supply chains are complex. According to Mitchell (2009), there are several key driver on complexity as these follows:
Clearly the more variables that need to be monitored and controlled in a supply chain the more complex the operation is. Variables here could be the number of suppliers, parts, available inventory levels, number of workstations in an assembly line, etc.
Variety refers to the distribution pattern of each of the variables of interest. As the company have more things that are different from each other, then it will make things much more complex because the company have to handle them in different ways.
The key to generating complexity in any field are the interactions between the different parameters. Obviously more interactions between parameters lead to a more complex supply chain. For example, the available inventory will affect the job lead time which will affect the utilization rates which will impact the revenue generated.
- Opacity of Interactions
Opacity essentially means not transparent. The less that is known the nature interaction between entities, the greater complexity.
- Dynamic Effects
The final reason for supply chain complexity is the dynamic nature of the system. Small perturbations at one end of the chain take some time to propagate through. While at the same time a small variation could magnify itself to a large swing at the other end. This is the so-called “bull whip” effect.
From the explanations above, we can conclude that Supply chains do not exist in a steady state. There will be interactions between entities in supply chain and also variety in the system itself. Moreover, the key aspect of SCM is to understand how the system responds to these changes. One of the tools is system dynamics.
System Dynamics (SD) was conceptualized by Jay Wright Forrester, professor of the Massachusetts Institute of Technology, during the mid-1950s. The objective of this methodology and computer simulation modeling technique was to help corporate managers improve their understanding of industrial processes where variables are associated to a system that is considered to be dynamic in nature (one that owns an ever-changing attribute). (Forrester, 1989; Radzicki & Taylor, 1997).
Source: Center for Transportation Studies – MIT
In system dynamics, we are moving from linear to circular thinking. We are going to consider of feedback and interaction among the entities. The feedback action or interaction within a system will be shown on the causal loop diagram. Causal loop diagram must have either Positive (+) or Negative (-) polarity.
All else being equal, if product quality increases then sales will increase above what it would have been, and vice versa.
All else being equal, if product price increases then sales will decrease below what it would have been, and vice versa.
Loops – two types based on the polarity
- Reinforcing Loop: A collection of links that form a loop that provides positive feedback
- Balancing Loop: A collection of links that form a loop that provides negative feedback
Source: Center for Transportation Studies – MIT
Lee, Padmanabhan and Whang (1997) used system dynamics in order to capture the effect on supply chain systems. They found that Information transferred in the form of orders tends to be distorted and can misguide upstream members in their inventory and production decisions. Moreover, the variance of orders may be larger than that of sales, and the distortion tends to increase as one moves upstream.
Commonly Recognized Patterns in Supply Chains:
Oscillation – fluctuation in orders increase as we move upstream
Amplification – the size of the fluctuations increase as we move upstream
Phase Lag – the impact is delayed longer as we move upstream
Lee, H., Padmanabhan, V. and Whang, S. (1997) The Bullwhip Effect in Supply Chains. Sloan Management Review, Spring edition, pp 93-102.
Mitchell, M, 2009, Complexity – A guided tour. Oxford University Press.
Supply Chain Complexity, http://www.simafore.com/hs-fs/hub/64283/file-15507473-pdf/docs/simafore-whitepaper-supply-chain-complexity-survey.pdf, accessed on 20 September 2016.
Swaminathan, J., Smith, S., Sadeh, N. (1998) Modeling Supply Chain Dynamics: A Multiagent Approach, http://www.cs.cmu.edu/afs/cs/user/sfs/www/papers/dsj04.pdf, accessed on 20 September 2016.
Sterman, J, 2000, Business Dynamics: Systems Thinking and Modeling for a Complex World.
Calvin Jhon Junior