Supply Chain Complexity. A Short Survey to understand key issues

Size: px

Start display at page:

Download "Supply Chain Complexity. A Short Survey to understand key issues"

Julie Eaton
6 years ago
Views:

1 Supply Chain Complexity A Short Survey to understand key issues

2 Table of Contents Executive Summary... 3 What is complexity...4 Supply chain complexity...5 E f f e c t s o f S C c o m p l e x i t y Top 5 reasons for SC complexity...5 Survey Results...7 Key issues for supply chain managers...7 C o n c l u s i o n s References...10 About SimaFore

3 Executive Summary There is overwhelming agreement among academics and managers about the complexity of supply chains and its tremendous increase over the last few years. Most practitioners understand complexity at an intuitive level, but there has been a shortage of efforts towards developing a formal understanding of causes for this complexity. This paper summarizes the results of a short survey on complexity in supply chains. Specifically, we asked a series of 7 questions to gage the pulse of practitioners when it comes to supply chain and managing complexity. We found that there was broad agreement when it comes to the root causes for complexity in supply chains and very little debate about what is required to address this problem. However, there were still some debate about how to measure complexity and whether measuring this complexity has immediate benefits to managing it. 3

What is Complexity A complicated system, such as mechanical wrist watch, is formed of numerous components in some cases as many as one thousand - that are linked to each other.

4 What is Complexity A complicated system, such as mechanical wrist watch, is formed of numerous components in some cases as many as one thousand - that are linked to each other. But at the same time, the system is quite deterministic in nature. It cannot behave in an uncertain manner. It is certainly very complicated, but is also very easy to manage. On the other hand, systems such as an economy or a subset of the economy such as an industrial supply chain can behave in a myriad ways (called modes) and can spontaneously change modes of behavior, for example from nominal to failure. These systems have another component in addition to the large number of interconnections variability or uncertainty. With these systems, not only the number of behavioral modes increase, but the effort necessary to change modes can sometimes be counter-intuitively tiny in proportion. These systems have high complexity. Complexity, thus implies the capacity of a system to deliver surprises. Highly complicated products do not necessarily have to be highly complex. It is also true that high complexity does not necessarily imply very many interconnected components. In fact, a system with very few components can be extremely difficult to understand and control. This brings us to one general purpose definition of complexity. Complexity is a function of two fundamental components [1]: Structure. This is reflected via the topology of the information flow between the components in a system. Typically, this is represented via a Process Map or a graph in which the components are the nodes (vertices) of the graph, connected via links. Uncertainty. The amount of variability measured in terms of uncertainty or entropy in the interactions between the components of the system. 4

5 Supply Chain Complexity Effects of SC Complexity Complexity has two major effects. The first is an increase in the functionality of the system. Clearly if modern day big box retailers could not leverage global manufacturing and distribution capabilities, they would have none of their current advantages of wide reach, low prices to consumers and healthy returns to shareholders (at least during good economic times). No one would argue that the Wal-Mart of today is significantly more complex than the one started by Sam Walton several decades ago. The flip side of increase in complexity is that, left unchecked, growth in complexity can result at best in serious downswings in efficiency or at worst in catastrophic failures that may have consequences for the system and its environment. Examples abound today, and the quickest one could reach for is the effect of Chinese plant workers strike on the delivery of the latest Apple products and the accompanying public relations issues for the company. Supply chain complexity management can thus become a major challenge for today s managers. Top 5 reasons why supply chains become complex As with many other concepts which involve the term complexity, there is some debate on how to manage complexity in supply chains, but again without really defining complexity. Melanie Mitchell in her wide ranging coverage on complexity indicates that this is quite common in the science of complexity because of the lack of one single theory of complexity [2]. She acknowledges the struggle to herd together some core concepts that describe complexity. The good news for supply chain management is that some practitioners are quite rigorous and have come up with a few basic definitions and concepts. Thus a first step toward measuring complexity has been taken. The following factors are reasons according to [3] for SC complexity: 1. Numerousness 2. Variety 3. Interconnections 4. Opacity 5. Dynamic effects Numerousness is an undisputed indicator of supply chain complexity. 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, 5

6 orders received, orders completed, utilization rates of machines etc. One could also add the revenue generated as a variable. Variety refers to the distribution pattern of each of the variables of interest. For example, job orders do not always come uniformly spaced as they could be seasonal swings. On the other hand one can imagine a process where the utilization rate of a machine is consistently at or near capacity all the time (!). A process which has a mix of these different patterns in the parameters of interest is clearly more complex. The key to generating complexity in any field are the interactions between the different parameters. For example, the available inventory will affect the job lead time which will affect the utilization rates which will impact the revenue generated. But sometimes, there could be surprises among the interactions as well: you may find that the lead times not related to revenue, for example or you may find strange interactions such as a relationship between the utilization rates of one station with another which is not even in the workflow path. Obviously more interactions between parameters lead to a more complex supply chain. The other facet about interactions in addition to their existence is the nature of these interactions. Typically one would expect say lead times to decrease with available parts inventory levels. But what is the exact nature of this relationship? Is it a downward sloping line? Is it a curved line? Maybe there are distinct zones of behavior across a range of inventory levels? This could be referred to as the Opacity of the parameter relationships. Opaque until made clear by analysis. A more complex process not only has more interconnections, but the nature of these interconnections could be distinctly non-linear or chaotic or worse, unknown. 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. A fundamental reason for this is lack of information on true nature of the product demand. In the next section we present the full results of our brief survey on supply chain complexity. 6

7 Supply Chain Complexity Survey 7

8 8

9 Conclusions We have expanded upon the key aspects of a production or supply chain operation which result in increased complexity. Our very short survey, indicated that demand uncertainty is the biggest factor that influences supply chain complexity. Not surprisingly, managing demand uncertainty was ranked as the single most important factor in managing supply chain complexity. Supply chain complexity measurement and management tools enable practitioners to gain control over their supply networks. But challenges may be unique based upon industry verticals, available data and in-house expertise. How would you chose the best tool or technique to manage your network problems? Subscribe to our FREE tool, vistasc which will help connect your business analytics problem with the most appropriate tools, provide you access to ROI case studies and white papers, video tutorials for the most common tools and techniques and also an expert forum. Sign up is fast and simple just point your browser to! 9

References 1. J. Marczyk and B.R. Deshpande, Measuring and Tracking Complexity. Presented at the 2006 International Conference of Complex Systems, Boston, MA, June 2006 2. T. Blecker and W.

10 References 1. J. Marczyk and B.R. Deshpande, Measuring and Tracking Complexity. Presented at the 2006 International Conference of Complex Systems, Boston, MA, June T. Blecker and W. Kersten (Eds.), Complexity Management in Supply Chains Concepts, Tools and Methods. Erich-Schmidt-Verlag M. Mitchell, Complexity A guided tour. Oxford University Press About SimaFore SimaFore was established with the express objective of helping businesses find the right tools for the right problems to convert data into information assets. Our team of experts come from different backgrounds but the analytical techniques each have applied in their experience have several common threads: using data to understand cause and effects, building models to simulate systems or processes, and using a combination of analytics tools for forecasting. Our team shares a common vision - to help businesses remove the complexity involved in applying and deploying analytics. To make analytics accessible and affordable to anyone who has data. About Bala (BR) Deshpande Dr. Deshpande has 15 years of experience in the biomedical, automotive and consulting areas. He holds an MS in Mechanical Engineering (University of Utah), an MBA (University of Michigan) and a Ph.D. in Bioengineering (Carnegie Mellon University). Before founding SimaFore, he was involved in engineering consulting at EASi, software publishing with Ontonix and automotive product development at Ford Motor Company. 10

The dynamism and volatility of a project or a portfolio

The dynamism and volatility of a project or a portfolio PMI Virtual Library 2010 Giuseppe Graci, Balachandra Deshpande, and David Martin Complexity Measurement: A New, Comprehensive Metric for Project Management By Giuseppe Graci, Balachandra Deshpande, and