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Discovering the Right Planning Approach for your Supply Chain

Daniel Dumke — Mon, 24 Oct 2011 13:51:00 +0000

Some weeks ago I wrote about Fisher’s suggestions on how to select the right supply chain for your product. But how to continue from there? How do different products affect the further planning steps needed?
So I looked for another article to fill the gap and found “Selecting the right planning approach for a product” by Kaipia and Holmström (2007) which covers different planning approaches for different products.
This review is based on the review of Fisher’s model, so make sure to read that article as well.

Methods

The authors build their planning approach on three methods:

Literature review
Development of a framework to differentiate planning approaches for different types of products based on a case company
Application of the selection framework in a case study

Figure 1: Overview Case Companies (Kaipia and Holmström, 2007; click to enlarge)

Case companies

Three case companies were examined: Vaisala, Mattel and Zara. Figure 1 exhibits the product properties and planning approaches currently used by them.

Vaisala, focusses on short lead times in the distribution network and local component buffers for supplies. Production is “to-order” with a high degree of flexibility. The strategic goal is to be responsive to customer demand.
Mattel, Inc, uses continuous, planned product changes, to keep supply and manufacturing efficient.
Zara’s system is based on fast reaction to changes in sales, in combination with a highly compressed design-to-customer process. Half of the demand can be seen as quite stable, so overall less responsiveness is necessary.

Planning approaches

The authors distill eight planning approaches from the literature, which are used as a basis for the selection of the right planning process. Included in figure 2 are the features and requirements for each planning approach.

Figure 2: Planning Approaches with Features and Requirements (Kaipia and Holmström, 2007; click to enlarge)

Selection process

Using the cases different product properties in supply and demand are analyzed and aligned with the requirements of the planning approaches. From this the authors deduce the selection process shown in figure 3.

Figure 3: Selection Process for the Right Planning Approach depending on the Product Type (Kaipia and Holmström, 2007; click to enlarge)

The authors conclude with general recommendations for the right planning approach for several OEM product types, shown in figure 4.

Figure 4: Recommendations for different Product Types (Kaipia and Holmström, 2007; click to enlarge)

Conclusion

While Fisher (1997) kept his work low-key, with only few pinpointed recommendations for specific products or companies, the authors in this article were more aggressive. There is even a strategy of last resort if everything else fails: simplify, invest and create the “planning organization”.

I did not find any errors in their logic conclusions, but of course these recommendations might be overly specific for many other case studies. What to use? I really liked the approach of listing the different planning approaches with the respective requirements and to deduce the planning process for the different product types from that, so may be this might be the common denominator which could be used for a multitude of cases.

Reference:

Kaipia, R., & Holmström, J. (2007). Selecting the right planning approach for a product Supply Chain Management: An International Journal, 12 (1), 3-13 DOI: 10.1108/13598540710724347

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Finding the Right Supply Chain for your Product!

Daniel Dumke — Wed, 12 Oct 2011 14:08:00 +0000

This again is an old classic in supply chain risk literature. In 1997 Marshall L. Fisher published this article in the Harvard Business Review targeting a simple question: “What is the Right Supply Chain for Your Product?”

It is noteworthy that this appears to be one of the most often cited papers in supply chain management. So I overlook the fact that it is quite weak on the methodological foundations.

The full text of this paper can be found here.

Product types

One of the major highlights of Fisher’s work is its simplicity. The author defines two basic products: functional and innovative products (figure 1). The major differentiating factor is the uncertainty of demand: Functional products (e.g. a classic Coke) show a rather predictable demand pattern and have long product cycles. Innovative products on the other hand show an unpredictable demand, and the life cycle can be as short as a few month.

Figure 1: Product Properties (Fisher 1997)

Supply chain types

Staying in the realm of simplicity Fisher also sees two basic types of supply chains or supply chain strategies a company can select (figure 2).

First there is the Physically Efficient Process, which can supply a specified amount of products at the lowest cost possible.

Second there is the Market-Responsive Process, which focusses on quick adaptability towards changing market needs.

Figure 2: Supply Chain Categorization (Fisher 1997)

Strategic Implications

The strategic implications become obvious quite quickly. One does not want to match a efficient supply chain with a fast changing market, since this would probably leave the company either with a huge excess inventory or, if too little is produced, with many unsatisfied customers.

On the opposite side one should not match a responsive supply chain with a steady market demand. Cost for maintaining this flexibility are potentially to high to maintain a positive product margin.

Figure 3 shows the matches in a matrix.

Figure 3: Matrix Matching Products with Supply Chain (Fisher 1997)

Conclusion

The implications of this concept are intriguing, just define the type of your products and adapt the supply chain accordingly. Fisher validates his points by describing two case studies (Campbell Soups and Sport Obermeyer) where his concept was successfully employed.

On the other hand, the concept is really simplistic. There are overlaps in the defining factors of the process and product categories making them harder to separate than it seems: What really is a predictive demand and when is it unpredictable?

And the critique continues. In 2011 Perez-Franco, Singh and Sheffi documented some of it in their article (which I reviewed here), which indicates that the concept is not viable in reality.

Of course this does not mean that I underrate Fisher’s contributions: with this article he still contributed to the discussion of supply chain strategy and its influencing factors and it serves as a basis for many more works, as I mentioned above.

The conclusion I draw:

Consistency: Of course there should be a connection between the product of a company and it’s supply chain strategy. But there are many other factors which have to influence an effective and efficient supply chain design as well.

Methodological: Never rely solely on a handful of sample case studies as the foundation of a concept. Sometimes you will be right, but very often you will be wrong.

You can continue reading on Discovering the Right Planning Approach for your Supply Chain.

Reference:

Fisher, M.L. (1997). What is the Right Supply Chain for Your Product? Harvard Business Review, March-April, 105-116

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Combination of Product and Supply Chain Design

Daniel Dumke — Wed, 20 Jul 2011 08:01:00 +0000

In research the decisions on the product and the corresponding supply chain are usually separated. This happens for a variety of reasons, one may be the reduction of problem complexity, another that the research focus is on a brown field approach where the products are seen as given.

This makes this article even more interesting, since it combines the both decisions in one conceptual process and a model to optimize the decision.

Figure 1: Iterative Process for simultaneous Design of the Product and Supply Chain (Lamothe et al., 2006)

Process

The process (figure 1) consists of two major steps. First product variants are developed. In the second step a simultaneous optimization of the supply chain and the product variants is conducted.
The process is meant to be interactive, so that the product designer has the chance to make redesign decisions after step two to learn from the optimization results.
This leads to a generic Bill of Materials (BOM) which contains the different options for the product design alternatives.

Figure 2: Generic Bill of Material for different Markets and Service Requirements (Lamothe et al., 2006)

Model

The authors use a classic Global Supply Chain Model and extend it to consider the generic BOM. The objective is to minimize the total costs (addition of all fixed and variable costs), which is subject to the generic BOM and other constraints (e.g. capacity, shipping, …).

Application

Finally, the authors apply their model at a wiring harness supplier of a car manufacturer. Overall there are 48 possible product families. Using an implementation of their model the authors solve the supply chain optimization and conclude with the result in figure 2.

Figure 3: Resulting Supply Chain after the Optimization (Lamothe et al., 2006)

Conclusion

The idea of the generic Bill of Materials which contains all product variants makes it possible to integrate multiple product variants in the mixed integer linear program.
The algorithm seems to be fast enough to produce optimal solutions within minutes and can therefore be used as a basis for new models integrating other global aspects like taxes and exchange rates.

Reference:

Lamothe, J., Hadjhamou, K., & Aldanondo, M. (2006). An optimization model for selecting a product family and designing its supply chain European Journal of Operational Research, 169 (3), 1030-1047 DOI: 10.1016/j.ejor.2005.02.007

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Decision Support for Supply Chain, Product and Process Design

Daniel Dumke — Wed, 02 Feb 2011 13:46:00 +0000

Many companies are struggling with the idea to use modern optimization techniques to support decision making in strategic supply chain management.

But beside mathematical modeling of the supply chain there are other methods as well, such as network based approaches. In their 2005 paper Blackhurst, Wu and O’Grady present a more intuitive decision support method with the goal to improve decisions within the supply chain context.

Methodology

Figure 1: Example Product Chain Decision Model (Blackhurst et al. 2005)

Complex and dynamic systems like supply chains are hard to understand as a whole. The PCDM (Product Chain Decision Model) uses a network based approach. The network (example see figure 1) therefore consists of different nodes (place nodes: marked by circles and transition nodes: marked by bars). Transition nodes are used for processes, transferring input into output (eg. a transport, production, …), where place nodes are used for components within the supply chain (eg. production facility). The connections are marked by an arrow.

Case Study

Figure 2: Case Study for Chassis Assembly using PCDM (click to enlarge, Blackhurst et al. 2005)

As an example Blackhurst et al. use a case study, where they model the chassis assembly of Rockwell Collins, using actual data of their processes. The result of the status quo can be seen in figure 2. The network presentation is enhanced by the added information, like the lead time (LT) and the reorder point (ROP) at the nodes.

With the help of these networks the authors then optimize the network from the base case with local informations first to an information sharing network. This already helps reducing echelon inventory a lot. The second adjustment is to change raw materials to improve the product and the network even further.

Conclusion

The presented method for improving the supply chain network is intuitive, easy to understand and implement. Yet, it does not seem to be so new, nevertheless, it is a nice addition to the usual supply chain networks to add some key indicators directly at the nodes.
Even though this tool might seem overly simplistic, I really recommend using more tools like these. Many companies do not even analyze their network on a systematic basis, so this looks to be a good starting point for companies which have not used similar tools before.

Reference:

Blackhurst, J., Wu, T., & O’Grady, P. (2005). PCDM: A Decision Support Modeling Methodology for Supply Chain, Product and Process Design Decisions Journal of Operations Management, 23 (3-4), 325-343 DOI: 10.1016/j.jom.2004.05.009

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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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Leading by Design

Daniel Dumke — Mon, 06 Dec 2010 15:26:00 +0000

Is there consensus about the role of product design as the leading function in the supply chain? Not yet! This article introduces the topic of integrating decisions in product and supply chain design and gives a short glimpse on the “how to implement” part.

Case study

During the last weeks I conducted the following case study on the impact of product design on supply chains using literature and expert interviews, looking for an answer to the basic question: What are the advantages of integrating product design into your supply chain decisions?

European retailer for furniture

Supply chain management starts with the product design. They are using this integration to reduce cost but also carbon emissions. One example, the packaging they use is designed for the specific transportation requirements so that efficiency is raised.
Marks & Spencer, UK
Are using their product design as an integrated part of its overall risk management. Apparel design is also leading procurement decisions (see reference for more information).
Big European food company
Product design is lead my marketing function. Supply chain design is guided by those decisions.

Research

In the literature Khan et al. 2008 also take the view that product design and supply chain design should be integrated more to improve overall results. They first state that product design is usually neglected in corporate risk management. To minimize risks the authors recommend to establish “design led procurement” and “design-led risk management” to improve agility, relationships with suppliers, while on the other hand avoiding over dependence.

How To

Fixson (2005) introduces a framework for an integrated decision making of product, process and supply chain decisions. Decisions taken within those three domains depend on six different product characteristics:

Product modularity
Component complexity
Loosely coupled interfaces
Number of components
Product platforms
Component commonality

Product Characteristics Impacting (constraining and enabling) Design Decisions in Product, Process, and Supply Chain Domain (Fixson, 2005)

He argues that the more interfaces exist between product components the higher the complexity not only in the production processes but also within the supply chain design. This framework however can be used as,

a guideline to focus on design decisions critical for the product and company under consideration; [… it can help to] explore the advantages and limitations of various operational strategies for given product architectures [… and] to improve a company’s strategy planning capabilities over time.

Conclusion

From systems theory it should be obvious that integrating decision making should lead to better results than decisions in separate functions. But the mentioned examples are only a skewed sample to emphasize the point: Yes, it makes sense to integrate product development. But the implementation has to be thoroughly planned.

Reference:

Khan, O., Christopher, M., & Burnes, B. (2008). The impact of product design on supply chain risk: a case study International Journal of Physical Distribution & Logistics Management, 38 (5), 412-432 DOI: 10.1108/09600030810882834

Fixson, S. (2005). Product architecture assessment: a tool to link product, process, and supply chain design decisions Journal of Operations Management, 23 (3-4), 345-369 DOI: 10.1016/j.jom.2004.08.006

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