mapping

Solution to Strategic Supply Chain Mapping

Daniel Dumke — Mon, 23 Apr 2012 13:05:55 +0000

I just realized that my favorite book on crafting diagrams to better communicate in a graphical way (Envisioning Information) just has been turned into a paper on mapping supply chains.

So I am happy to summarize an article, which focusses on how to convey complex information in an concise and comprehensive way.

Supply chain mapping

I already wrote about this topic several times. But because this is a very important issue, I did not hesitate to do it again from a different angle.

There are several key advantages to supply chain mapping:

To link corporate strategy to supply chain strategy.

To catalog and distribute key information for survival in a dynamic environment (in order) to direct the focus of the managers.

To offer a basis for supply chain redesign or modification.

Current channel dynamics can be displayed in a supply chain map.

The process of building the strategic supply chain map, in itself, will help define the perspective of the supply chain integration effort.

continued in the article

However there are obstacles preventing an effective supply chain mapping. One is, as often, the complexity of the supply chain.

Even with only a few echelons in focus the number of entities and connections just explodes. Figure 1 shows the results of some simple calculation. A supply chain with five tiers and only two connections per tier already contains 13 chain elements.

Figure 1: Number of Entities in a Supply Chain Map (Farris, 2010)

So in no time a supply chain map looks like the one in figure 2 or 3.

Figure 2: Complexity of a “short” Supply Chain (Farris, 2010)

Figure 3: Bad Example for the Representation of Material Flow (Farris, 2010)

Issues in supply chain mapping

Four issues in supply chain mapping can be recognized.

[…] Four issues [were identified] which must be addressed to further the development of strategic supply chain mapping:

proprietary information;

inadvertently changing channel dynamics;

getting lost in too many details; and

providing an ineffective perspective for management use.

Recommended supply chain mapping

Over a five year period the author conducted several “classroom laboratories” with his students doing experiments on how to improve current mapping techniques.

This is where the above mentioned book comes into play. In it you find a picture of probably the oldest geo-visualization (figure 4). In this case it was used to describe the declining strength (measured in number of soldiers) of Napoleon’s invasion of Russia and the way back. Highlighting the fact that most soldiers did not die in battle, but on their way to and from Moskow.

Figure 4: First Geovisual Map (click to zoom; by Minard, 1844-1870; Farris, 2010)

While this also highlights the importance of a good supply chain. Focus in this case is on the massive amount of information which can be extracted from this diagram (strategies, movement, location, time, strength), while still keeping a relatively low size and low perceived complexity.

Based on this idea and other insights, several iterations with the students lead to several key learnings and a recommended supply chain map. Figure 5 shows the recommended map, displaying the supply chain interactions on an industry- (not company!) level.

Figure 5: Example of a Recommended Supply Chain Map (Farris, 2010)

Lessons learned:

Utilize geovisualization techniques

The mapping efforts utilized a geovisual technique combining weighted solid and dashed arrows and lines, defined symbology representing different trading relationships, and the representation of financial flow to develop maps rich in content.

Start at a higher level

It is highly unlikely a company would be able to, or would desire to, expend the resources required to map 100 per cent of all of their customers and suppliers. Each mapping effort must determine the economic trade-off between the level of detail of their map, the cost to gather the detail, and the benefit received. […] Owing to the ready access to economic data, an industry macro map may offer the greatest mapping value for a relatively minimal investment. It is recommended that the map designer begin at a high level and then drill down.

Strive to keep the maps strategic

[…] strategic supply chain maps must maintain a strategic emphasis, any users with a desire to drill down to an operational level should utilize alternative process-related tools such as the SCOR model […]. Keep the strategic supply chain maps at a high, strategic level and avoid undue complexity.

Manage a synergistic network

As value chain mapping continues to evolve, map designers may find that the term “supply chain” is a misnomer. Strategic supply chain maps quickly reflect a “supply network” as it is not unlikely that a customer’s customer may be a critical supplier’s supplier. Recognition of these types of relationships may have far-reaching strategic impact in terms of keiretsu-type relationships or jointly beneficial marketing efforts […].

Embrace mapping creativity

[…] it was determined there was no single approach to developing a strategic supply chain map. Creating a strategic supply chain map is as much an artistic endeavor as it is a defined process. […] It is recommended that firms attempting to strategically map their supply chain embrace this fact by asking multiple individuals who create a map to use the same data set. Each variation may result in components within the map which offer easier readability and should be incorporated into the final map.

Conclusion

The resulting supply chain map is overwhelming at first, but which map wouldn’t be. A complex system like a supply chain and its supporting parameters are just hard to zip onto a single page.

After a short while of looking at the map I was just amazed how much information could be deduced from it.

I think using the lessons learned and (not too many) different information layers in a map can result in highly aggregated and informative results, ergo in a real supply chain map.

Reference:

Faris II, M.T. (2010). Solutions to strategic supply chain mapping issues International Journal of Physical Distribution & Logistics Management, 40 (3), 164-180 DOI: 10.1108/09600031011035074

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Uncertainty in Value Stream Mapping Analysis

Daniel Dumke — Wed, 30 Nov 2011 15:09:00 +0000

Supply chain mapping can be a great tool to foster the understanding and from its results improve a supply chain network overall. Supply chain mapping can also be used to analyze the risks of a supply chain and improve its resilience (for an example in the blog follow this link).
A SC mapping can also lead to implications for risk management, but how do you include existing information about the risks themselves in the analysis?

Braglia et al. (2009) analyze this problem and suggest two approaches to include variability in a value stream mapping (VSM) with the goal of better identification of the wastes in a single plant setting, but I think their insights might also be interesting for a supply chain setting.

Method

Value stream mapping can be described as “a graphical representation of both materials and information flow within a facility”. This permits to analyze the process and make calculations, e.g. regarding the total production lead time (TPLT), the total value-added time (TVAT) and the efficiency of the process (η = TVAT/TPLT)

VSM is not the method of choice for all problems, beside some pros there are also the cons:
Pro

It shows the linkage between product flow and information flow;

it includes information related to production time as well as to inventory levels;

it helps to visualise the production process at the plant level, not just at the single process level.

The main cons include

it is a paper- and pencil-based technique, thus the accuracy level is limited and the number of versions that can be handled is low;

it lacks the spatial structure of the facility layout and how that impacts interoperation material handling delays;

it cannot address the complexity of high-variety low-volume type companies, whose value streams are composed of hundreds of industrial parts and products.

Uncertainty and VSM

The authors suggest two similar approaches to include uncertainty within the VSM: the stochastic and the fuzzy approach.

In the stochastic approach uncertainty is described using distribution function (figure 1) with a mean and standard deviation.

Figure 1: Representation of a Stochastic Variable (Braglia et al., 2009)

In the case of a fuzzy logic the uncertainty is described using a triangle function (figure 2), which can be described by the start and end values (a and c) and the maximum b.

Figure 2: Representation of a Fuzzy Number (Braglia et al., 2009)

Application

When applying one of the mapping approaches the authors suggest to follow the following seven step process:

The analysis starts with the identification of the value stream (i.e. product family) that has to be mapped.

Walking backward in the process (i.e. from the finished good inventory to the raw materials warehouse), practitioners collect all the relevant data and draw a sketch of the actual state map.

[To include the random aspects of the value stream,] the waiting/processing time of each activity is approximated [and represented by a corresponding function.

The actual state map is completed substituting, in the corresponding process boxes and on the timeline, deterministic times with the random variables.

[The TPLTs are calculated using stochastic methods]

Using lean principles possible future state maps are designed and their expected TPLT is evaluated […]

Obtained improvements are evaluated comparing the TPLT.

The major milestones in the process are therefore the completion of the map of the actual state and possible future state maps.

Figure 3 shows the actual state map for a case study company presented in the article. Underneath the map you find the process times with deterministic values, stochastic representation and fuzzy representation of the uncertainty (from top to bottom, click on the image to show a larger version).

Figure 3: Actual State Map (Braglia et al., 2009; click to enlarge)

One example for a possible future state of the supply chain is shown in figure 4, again with the respective lead times.

Figure 4: Future State Map (Braglia et al., 2009; click to enlarge)

Conclusion

Value stream mapping can be used in a supply chain setting as well. And it can help to find bottle-necks – and as shown here the randomness of processes can be included as well. The authors make a great job of explaining the mentioned approaches and sketching the implementation as well.
Sadly, they forgot to describe the advantages of the inclusion of randomness in the value stream mapping: After presenting a second future state the authors do a statistical comparison of the two outcome distributions and conclude: “Therefore both methodologies show that the first solution is definitely better than the second one.”
But, if they had just compared the deterministic process times they would have come to the same conclusion! So where is the point in including the randomness at all?

Reference:

Braglia, M., Frosolini, M., & Zammori, F. (2009). Uncertainty in value stream mapping analysis International Journal of Logistics Research and Applications, 12 (6), 435-453 DOI: 10.1080/13675560802601559

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