Denis R. Towill

Simplified Supply Chain Flows

Daniel Dumke — Mon, 25 Jul 2011 14:52:00 +0000

I have to distract myself a little bit from thinking about supply chain risks too much, so I thought why not use the chance to read a different article once in a while. Well, at least the authors are familiar: Paul Childerhouse and Denis R. Towill and their paper of 2003: “Simplified material flow holds the key to supply chain integration”

Pre-work

Childerhouse and Towill start with an historical analysis of applications of simplified material flows, starting in the 16th century with the progress made in the supply chain for war ships over to the description of the bullwhip effect all the historic examples are concerned with the simplification of the supply chain, where the…

…emphasis is on “clean” i.e. unbiased and noise-free information flows; time compression of all work processes; achievement of consistent lead times; choice of smallest possible planning period; adherence to the schedule i.e. elimination of pockets of “Just-in-Case” materials, selection by simulation of the “best” supply chain controls; and finally, matching the simulation model to the real work process via process flow and information analyses

In previous papers the authors already analyzed how supply chain simplification is possible and conclude with a list of simplification rules (Figure 1).

Figure 1: Twelve Rules to simplify the Flows within a Supply Chain (click to enlarge; Childerhouse and Towill, 2003)

Figure 2 shows symptoms of a supply chain, when the material flows are too complex.

Figure 2: Symptoms of overly complex Supply Chains (click to enlarge; Childerhouse and Towill, 2003)

Method

A case study with 23 value streams all across Europe have been analyzed and a degree of simplification has been calculated using a score for the above mentioned simplification rules.

Results

The authors present five hypothesis to test using this data:

The effectiveness of a supply chain can be measured by assessing the level of uncertainty for the four segments of supply, process, demand and control.
Conformance to the 12 simplicity rules reduces uncertainty and results in increased supply chain integration.
On average each of the 12 simplicity rules are adhered to equally.
The level of uncertainty in the supply chain can be determined from a set of dynamic behaviour, organisational, situational and process observations.
Companies that undertake major Business Process Re-engineering programmes via the application of the 12 simplicity rules reduce uncertainties in their supply chains.

The hypothesis one and two are supported by the data of the sample. Hypothesis three is rejected, since the authors find that in the sample some of the simplicity rules are implemented more often then others (figure 3).
The fourth and fifth hypothesis are validated as well.

Figure 3: Order of the implementation of the Simplicity Rules within the Sample (Childerhouse and Towill, 2003)

The authors conclude:

Practitioners are faced with a multitude of published alternative ideas and techniques to improve the performance of their supply chains. It can be seen that most of these proposals have their roots in simplified material flow.

Conclusion

So, what do I want to remember from this detour:

Uncertainty is a driving force behind supply chain inefficiencies and risk reduction therefore also a way to improve performance.
Supply chain simplification is according to the authors one of the most common, yet often renamed, ways to reduce uncertainty and improve performance

And I thought I would get rid of risks for now…

Reference:

Childerhouse, P. (2003). Simplified material flow holds the key to supply chain integration Omega, 31 (1), 17-27 DOI: 10.1016/S0305-0483(02)00062-2

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Supply Chain Simulation and the Bullwhip Effect

Daniel Dumke — Wed, 20 Apr 2011 08:59:00 +0000

I already reviewed some articles by Denis Towill primarily because he does some interesting research on simulation and supply chains, but also because I like his clear style in his articles.

In one of his early papers (1992) he teamed up with Naim and Wikner and described state of the art strategies to fight the bullwhip effect or as it is called in the paper by its older name: Industrial Dynamics.

Industrial Dynamics

I already described the causes of the bullwhip effect and how to measure it in an older post. The bullwhip effect describes amplifications in demand within the supply chain. Exemplary effects can be seen in figure 1.

Figure 1: Effect of the Bullwhip Effect (Towill et al. 1992)

Improving SC Dynamics

One way to improve the supply chain dynamics is to introduce a leaner supply chain, which in turn will lead to lower lead times and lower amplifications.

In a lean supply chain stocks are located at a low level of “added value”, to keep the inventory cost lower.

The next decision to make is to find the right trade-off between stock levels and production rates. If you increase the flexibility of production, you might be able to reduce the inventory overall. There are two alternatives:

Fixed process rate / varying inventory levels

Varying process rate / fixed inventory

There are four sectors where where further improvements can be acchieved:

Industrial engineering improvements, eg. changing the product design or changing the layout of the production

Production engineering improvements, eg. integration and sequencing of processes to reduce lead times

Information technology improvements, eg. quicker data capture and electronic data interfaces

Operations engineering improvements, eg. pull system instead of push, shared planning

Optimization

To examine their points, Towill et al. design a simple supply chain simulation model with four stages (retailer, distributor, warehouse and factory). The results (figure 2) show that above mentioned improvements can lead to a reduction in the amplification.

Figure 2: Strategies for Reducing Demand Amplification (Towill et al. 1992)

The authors conclude that reducing the overall lead times in the supply chain may be an expensive solution. As an alternative they suggest to remove some stages from the chain which also leads to significant reductions in the amplifications. Probably the cheapest way to reduce the bullwhip effect may be to increase collaboration in the chain, in this case especially concerning forecasts and planning.

Conclusion

Simulation model cannot only help in theoretical exercises. There are very important applications in real life applications as well when the task is to optimize generic strategy recommendations like those mentioned above.

Reference:

Towill, D., Naim, M., & Wikner, J. (1992). Industrial Dynamics Simulation Models in the Design of Supply Chains International Journal of Physical Distribution & Logistics Management, 22 (5), 3-13 DOI: 10.1108/09600039210016995

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Effects of Process Maturity and Uncertainty on SC Performance

Daniel Dumke — Mon, 31 Jan 2011 16:16:00 +0000

Process orientation may or may not be a very hip topic right now. Nevertheless effective processes are a foundation for company performance. Lockamy, Childerhouse, Disney, Towill and McCormack (2008), analyze and explain the impact of process maturity and uncertainty on supply chain performance, the full paper can be obtained here free of charge.

In close collaboration with several businesses they conducted an empirical study on this topic, which I present in the following.

Business Process Orientation and Quickscan

Business process orientation can be described using the dimensions process management, process jobs and process view.

Process management & measurement means that the company is using metrics on aspects of the process such as output quality, cycle time, process cost and variability, in contrast to traditional accounting measures.

Process jobs focus on processes as opposed to functions, and are cross-functional in responsibility.

Finally, process view is the cross-functional, horizontal picture of a business involving elements of structure, focus, measurement, ownership and customers.

Relationship between Process Capabilities and Maturity (Lockamy et al., 2008)

The authors used the Quick Scan methodology with over 20 different supply chains. It consists of the following four methods: questionnaire analysis, process mapping, semi-structured interviews, modelling from numerical data.

Each quick scan took about two weeks at the site of the client and resulted in: a current status of the organization and the supply chain, evaluation of the maturity of its practices and processes and its ability to meet current and future customer needs, furthermore details on the management of uncertainty and interfaces beteween these areas.

Supply Chain Maturity and Uncertainty

Supply chain maturity is described here using five cumulative levels:

Ad Hoc, marks an unstructured supply chain with badly defined processes. Typical are no process measures and few “process jobs”.

Defined, stands for a level where processes and the supply chain has been defined. Process performance is measured sometimes.

Linked, describes a level where supply chain management jobs have been established and performance measures are conjointly evaluated with clients and vendors.

Integrated, traditional functions beginn to disappear, supply chain measures and management is embedded into the organization. This leads to reduced SC cost.

Extended, collaboration is routine, competition is based on a multi-firm supply chain.

Supply Chain Management Maturity Model (Lockamy et al., 2008)

Supply chain uncertainty is defined similar to Christopher and Peck (2004) and devided into process, control, supply, demand uncertainty. Based on other empirical study it can be stated that:

Supply chain uncertainty significantly contributes to poor customer service levels, excess inventory, long lead times, increased quality inspections, and bureaucratic decision-making processes.

Results

After collecting all data during the quick scan on the process maturity and experienced supply chain uncertainty levels the author drew the following conclusions:

Reductions in supply chain uncertainty can be achieved by increasing the maturity levels of processes employed within the supply chains

By increasing supply chain maturity levels and by correspondingly reducing uncertainty, firms can improve overall supply chain performance

Levels of maturity in the area of process structure and jobs can significantly reduce the level of control uncertainty within supply chains

Reductions in demand and control uncertainty can be achieved by increasing the maturity levels of process measures utilised within supply chains

Process Maturity vs. Supply Chain Performance (Lockamy et al., 2008)

Conclusion

One would think that better processes lead to better supply chain performance. But it is hard to objectively measure the maturity of a specific process. How do you grade them. For example maybe a process is documented, but to which level of detail and how are current is it? There are processes that work perfectly without having a process chart available which documents the exact interfaces.

So evaluating processes is always an extremely subjective task. I trust the reputation of the participating author that they used all due diligence necessary. Nevertheless it would have been great to see more details on how the evaluation has been conducted.

Reference:

Lockamy, A., Childerhouse, P., Disney, S., Towill, D., & McCormack, K. (2008). The impact of process maturity and uncertainty on supply chain performance: an empirical study International Journal of Manufacturing Technology and Management, 15 (1) DOI: 10.1504/IJMTM.2008.018237

Christopher, M., & Peck, H. (2004). Building the Resilient Supply Chain The International Journal of Logistics Management, 15 (2), 1-14 DOI: 10.1108/09574090410700275

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Managing Supply Chains with multiple Pipelines

Daniel Dumke — Mon, 10 Jan 2011 15:42:00 +0000

Companies offer a smaller or larger range of products serving different markets, depending on their history and primarily the respective business model.

From a supply chain management point of view this poses the question if it is ok just to use the same supply chain strategy for all those products.

Pipelines vs. Supply Chains

Aitken et al. (2005) make a convincing argument against this approach and instead suggest the “pipeline” to describe

the specific operational mechanisms and procedures that are employed to service specific product/market contexts

within one supply chain.
So one supply chain usually contains several different pipelines.

Case Study

The authors conducted a case study with a lightning company producing a range of lighting products for diverse markets.
During the four year project there were two major phases: first the introduction of lean production, and second increasing the responsiveness of the plant.

Four different pipelines were identified by clustering the products. The clusters were defined by considering the trade off between economies of scale, economies of scope and the diseconomies of averaging.

Cluster 1: low volume products
Cluster 2: high volume, low variant products
Cluster 3: multiple variants of standard products
Cluster 4: customized products

Pipeline Strategies

Different pipeline strategies were identified and are listed in table 1.

Table 1: Categorization of Pipeline Strategies (Aitken et al. 2005; click to enlarge)

Conclusion

Pipelines are a useful way of differentiating supply chain and selecting the right strategies depending on the market and product properties. Aitken et al. describe a normative scenario, in practice differences in supply chains are often due to missing integration of different parts of a company (eg. after a merger). But especially in those cases it is necessary to develop an approach for reintegration without loosing sight of the different needs of the customers.

Reference:

Aitken, J., Childerhouse, P., Christopher, M.G., & Towill, D.R. (2005). Designing and Managing multiple Pipelines Journal of Business Logistics, 26 (2), 73-95

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Personalized Products and their Impact on Supply Chain Design

Daniel Dumke — Wed, 08 Dec 2010 09:41:00 +0000

Experts from research and business alike argue that within the last decades consumers have grown to be a more demanding factor for supply chain management. At the same time manufacturing and supply chain strategies adapted to this development (from lean to agile, see Christopher and Towill, 2000).

But how are customer demands going to develop? Are we already seeing the decentralized manufacturing world, where everybody uses his own 3D printer to produce individual products on their desks? Probably not yet.

But at least for some industries product personalization is one big issues these days. Poulin et al. 2006 analyzes what options companies have to personalize products for their customers and shows the possible effects on supply chain design.

Personalization

From the literature the authors summarize their framework for product personalization. It consists of the following eight options:

Poulin et al., 2006
Personalization Option	Characteristics
Popularizing	Limited number of product to match a wide variety of customer needs, for those who want off-the-shelf products. Focus on evolving the popular product mix in line ith evolving customer needs
Varietizing	Extensive mix of products to satisfy almost all customer needs. Retailers pick those they want to offer off-the-shelf and rely on quick delivery from the distribution network for fast delivery of the others
Accessorizing	A limited set of core products matched with a wide array of accessories. Final assembly of accessorized products performed to order either by the user, the retailer or a fulfillment center
Parametering	Customer defines the desired product through the setting of parameters and the selection of options. He is guided through the specification process. Manufacturing is strictly to order
Tailoring	Product designed/engineered to customer needs. The customer is closely involved in the product realization process
Adjusting	Product adjusted to customer needs after usage. Distributed information systems capture customer feedback
Monitoring	Product is replaced by more adequate product as the customer needs evolve, ensuring continually a best-fit product. This involves regular and interactive customer feedback
Collaborating	Client is viewed as a collaborator with an open dialog. Expert field systems interact with clients, seeking to continually optimize client return

Methodology

To gain insights on the effects on supply chain design the authors conduct a case study in the golf iron industry, where already now a high product variety is a standard. They build a systems model of the industry to improve understanding of the relevant factors and different clients.

After that they describe the deployment of each of the above mentioned personalization options within the industry. For example:

Golf clubs can be parameterized using different coloring
the tailoring option would be used if a customer asks for a different weight distribution in the cavity of an iron head to correct specific, personal miss-hits.
Adjustments would involve the post sale process, where the iron is adjusted to specific needs

Effects on Design

In the following table the effects on supply chain design are listed.

Table 2: Impact of Personalization Options on Demand and Supply Network Processes (click to enlarge, Poulin et al., 2006)

The authors then visualize the effects of the customer involvement and differing decoupling points within the supply chain, effectively generating multiple supply chains for the different customer demands (see figure 1).

Figure 1: Point of Customer Involvement and Decoupling Point of Personalized Offers (click to enlarge, Poulin et al., 2006)

Conclusion

Personalized products are going to be the order winners of the future. The supply chain design has to adapt to these challenges and Poulin et al. gives a good start to change the supply chain accordingly.

Reference:

Poulin, M., Montreuil, B., & Martel, A. (2006). Implications of personalization offers on demand and supply network design: A case from the golf club industry European Journal of Operational Research, 169 (3), 996-1009 DOI: 10.1016/j.ejor.2005.02.005

Christopher, M., & Towill, D. (2000). Supply chain migration from lean and functional to agile and customised Supply Chain Management: An International Journal, 5 (4), 206-213 DOI: 10.1108/13598540010347334

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The Supply Chain Uncertainty Circle

Daniel Dumke — Wed, 27 Oct 2010 16:17:00 +0000

How to shrink the “Uncertainty Circle” is the topic of a paper I read today. It has been written by Rachel Mason-Jones and Denis R. Towill and can be downloaded here free of charge.

This article from 1998 focusses on how to shrink the uncertainty within a supply chain and therefore improve performance, since

we believe that those companies which cope best with

uncertainty, are most likely to produce internationally

competitive bottom-line performance.

This hypothesis is also backed by several other authors like, Craighead et al. (2009) or Hendricks and Singhal (2005).

Within the product delivery process for a single company, the authors find four causes of uncertainty: supply side, manufacturing processes, control systems and demand side (see figure 1).

Causes of Supply Chain Uncertainty (Mason-Jones and Towill 1998)

The Circle

With the Uncertainty Circle it is now possible to visualize to effect of shrinking one of the risks without the other: Overall risk is only reduced by a (comparatively) small amount. This furthermore implies the goal for supply chain risk managers: Reduction of risk on all frontiers!

Uncertainty Circle and Risk Reduction Process (Mason-Jones and Towill 1998)

This of course does not have to happen at the same time. Companies usually start with improvements in their own manufacturing processes and establish lean thinking to improve lead times and quality. As a next step this concept may be enlarged to the companies suppliers as well to reduce supply side risks.

The authors then argue that much potential is left untouched on the reduction of demand side uncertainties and control systems.

Demand side risks can be reduced by improving the information flow from the end-customer throughout the supply chain and companies can tackle control risks by improving their ability to act on this new information with a adequate Decision Support System.

Supply Chain Design Strategies

The authors then simulate a given supply chain and test strategies to improve (in figure 3) “Information pipeline time compression only”, “Material flow pipeline compression only”, “Total Cycle Time compression”.

Rating Risk Mitigation Strategies (click to enlarge; Mason-Jones and Towill 1998)

Conclusion

Even though the article has been published twelve years ago the concept of the Uncertainty Circle can still be used as a framework to reduce risks within a supply chain. The comparison table shows the effects of different risk mitigation strategies clearly and should adapted and used by more companies.

Reference:

Mason-Jones, Rachel, & Towill, Denis R. (1998). Shrinking the Supply Chain Uncertainty Circle IOM Control, 24 (7), 17-22

Craighead, C., Hult, G., & Ketchen Jr., D. (2009). The effects of innovation–cost strategy, knowledge, and action in the supply chain on firm performance Journal of Operations Management, 27 (5), 405-421 DOI: 10.1016/j.jom.2009.01.002

Hendricks, K., & Singhal, V. (2005). An empirical analysis of the effect of supply chain disruptions on long-run stock price performance and equity risk of the firm Production and Operations Managment, 14 (1), 35-52

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Acting on Supply Chain Disruptions

Daniel Dumke — Thu, 22 Apr 2010 07:43:33 +0000

Supply Chain Risk manifests itself in many ways. Today the German airlines restored their regular flight schedule again after six days of no or limited air traffic, after the latest eruption of the Eyjafjallajökull vulcano on Iceland.

The consequences of such events only rarely become evident, but in the background emergency plans have to be executed (or developed).

Case

10 years ago a disruption affected the supply chain at Ericsson, luckily the effects of this event on Ericsson have been published. Its about the so called “Albuquerque accident” in 2000, which was documented by Norrman and Jansson (2004).

Disruption

The Albuquerque accident was a small (30 sqm area), short (10 minutes) fire within one of the clean rooms of a supplier at Ericsson. The supplier was responsible for a important RF-chip for the cell phone production. The consequences therefore were very severe. It took the supplier three weeks to get the production running again and after six month the yield was only 50% of the pre incident rate. The cost for Ericsson were estimated at $200 million (which was compensated by insurance companies).

Analysis

A review in the Wall Street Journal concluded that Ericsson

took too long to take action after the incident
its reporting to upper management was flawed
had no alternative suppliers for this component
has not been prepared for this kind of accident

So how did they react?

Results

The goal was to minimize the risk exposure within the supply chain.

To achieve this they took action on two sides:

Organisation
Assigning clear responsabilities and establish a matrix organization
Processes
Reinforce processes for risk identification, risk assessment, risk treatment, incident handling & business continuity planning

Business impact

Since the financial consequences of the disruption were carried by the insurance companies it was at first harder for Ericsson to renew the insurance policies, but just the other way around after implementing those strict SCRM program mentioned above. As a result Ericsson was paying less afterwards.

It is noteworthy, that after experiencing this disruption Ericsson percieves that the concepts of agility, responsiveness and leanness are inducing higher risks.

Conclusion

The article seams strongly influenced by Ericsson and the objective research and presentation might be questioned. I am definitively missing some more insights on the a priori analysis, since it is one corner stone of the design of the measures. Within the article only a short excerpt from the WSJ has been quoted.

Other authors (as Lockamy et al. (2008)) find a much more positive connection between business performance and supply chain risk management, so this should be further analyzed.

Reference:

Norrman, A., & Jansson, U. (2004). Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident International Journal of Physical Distribution & Logistics Management, 34 (5), 434-456 DOI: 10.1108/09600030410545463

Lockamy, A., Childerhouse, P., Disney, S., Towill, D., & McCormack, K. (2008). The impact of process maturity and uncertainty on supply chain performance: an empirical study International Journal of Manufacturing Technology and Management, 15 (1) DOI: 10.1504/IJMTM.2008.018237

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Agile Supply Chains

Daniel Dumke — Thu, 15 Apr 2010 09:43:00 +0000

I have been reading a lot of interesting articles lately, hence I could not post as often as I wanted. I found an article by van der Vorst and Beulens (2002; “Identifying sources of uncertainty to generate supply chain redesign strategies”) which opens a new perspective on the SCRM issue. I am going to publish a review later this week and link it here.
Today I wanted to highlight the basics of supply chain management by talking about “Supply chain migration from lean and functional to agile and customised” by Christopher and Towill (2000).
Agile supply chains are a quite new concept which emphasis a change in the corporate mindset to adjust to the constantly changing customer demand.

Agility

Agility is described as a capability which contains organisational structure, information systems, logistic processes and mindsets.
Result of an agile supply chain is its flexibility. It has to be separated from the lean supply chains or the lean manufacturing concept which focusses on reducing “fat” (eg. inventory, cost, …) wherever possible.

Market qualifiers / Market winners

Why does this change happen? According to Christopher and Towill there is a constant change of the factors which contribute to the market qualifiers and the market winners (based on Hill (1993)).

Hence periodically a new market winner emerges and downgrades the previous market winner to a market qualifier

For example in the early 80s the market winner was quality, in the late 80s it was cost. Presently the authors identified lead time as the new market winner.

Agile Logistics

Agile Logistics are defined by the four basic elements shown in the graphics.

Elements of agile logistics

An agile supply chain can be devided into two parts one where the products are pushed based on planning and forecast and one where products are pulled from the upstream within the supply chain based on the real customer demand.
So one part of designing an agile supply chain is the decision about where to place the decoupling points. There can be two different decoupling points one for the information decoupling (up to where in the supply chain is the information about customer demand shared) and the placement of strategic inventory.

Conclusion

This is a very good article to explain the basics of agile supply chains. There are many followers building on this work. But up to now I have not been able to find one article dealing with the measurement of agility or flexibility. This should be very useful for analyzing adequate measures to achieve agility.

Reference:

Christopher, M., & Towill, D. (2000). Supply chain migration from lean and functional to agile and customised Supply Chain Management: An International Journal, 5 (4), 206-213 DOI: 10.1108/13598540010347334

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