OPERATIONS

Hidden Suppliers Can Make orBreak Your Operationsby Thomas Y. Choi, Benjamin B. M. Shao, and Zhan Michael Shi

MAY 29, 2015

With the size and complexity of supply chains

soaring, a daunting challenge is confronting

companies: identifying the critical nodes

hidden within the vast expanse of their supply

networks. These are suppliers, or supplier

sites, that might be in the second-tier or lower,

which means the big buying companies would

ordinarily have no contact and might not even

know exist.

These nexus suppliers could be important

for one or both of two reasons:

A disruption of its operation would have asurprisingly huge impact on the original-equipment manufacturers production. (Amuch-cited example is how an explosion at aGerman factory owned by Evonik Industriesthat supplied 70% of world demand for a type

of nylon resin wreaked havoc in the auto industry.)

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The supplier possesses critical market information. (For instance, LG Electronics learned byaccident that the Taiwan Semiconductor Manufacturing Company (TSMC), which hasconnections to lots of industries, can provide early signs of changes in economic conditionsand, as a result, supply and demand.)

We are the members of a research team at CAPS Research, a joint venture of Arizona State

University and the Institute for Supply Management, that is on the verge of creating a way to

identify these suppliers by doing three things: creatively applying network concepts, taking

advantage of emerging large databases, and utilizing business analytics, the practice of

methodically exploring data in an iterative fashion.

The field of operations is becoming more familiar with network concepts such as various

types of node centrality measures a gauge of how critical a node (each supplier) is to the

network: e.g., its number of connections, the variety of industries from which these

connections come, how quickly it can reach others in the network, and so on. If companies

could get their hands on such data for all the members of their supply networks, they could

compute centrality measures for all of their suppliers and identify the most critical ones based

their scores. Yes, there could be thousands of these nexus suppliers, but we now have the

computing power to identify how critical each is.

Currently, generating a map of supply

networks is a daunting task. Many companies

and research centers have attempted it and

found it to be labor intensive and time

consuming. See this article for a description of

one thats being tested at Ford and this one for

a sample supply network involving Honda that

took several years to complete.

The good news is in the last few years, companies have begun selling large databases that can

make this job much easier. We are using Bloomberg Supply Chain Database (SPLC), which

keeps track of about 28,000 companies worldwide. Other potential databases include Capital

IQ, FactSet Revere, and LexisNexis. For each company, SPLC provides a list of suppliers and

customers, based on information revealed in a variety of sources (public filings, industry

reports, etc.). For a given buying firm, we can identify all its suppliers, its suppliers suppliers,

and continue iteratively. We can then use the collected supplier-customer relationships to

construct an extensive supply network for the focal firm.

Then we can integrate complicated mathematical measures of centrality to create a nexus

supplier index (NSI), which is an aggregate measure of criticality of a supplier in a buying

firms supply network.

Once we have computed initial NSI scores for all suppliers, we can use business analytics to

validate the scores. We have compiled the data for the top three tiers of a particular

automotive company to its third-tier and identified over 8,000 suppliers. We have computed

NSI scores for second-tier suppliers and are in process of compiling fourth-tier data to

compute the NSIs for third-tier suppliers. We plan to provide a formal CAPS Research report

on our effort by September of this year.

Once a buying firm has identified and scored the nodes in its supply chain, it can group its

nexus suppliers into different categories according to their distinct network positions and

develop and implement suitable strategies to manage each type in order to achieve such

objectives as minimizing costs, mitigating risks, increasing responsiveness, and discovering

and accelerating the development of potential innovations. Then it can start monitoring its

nexus suppliers and make use of the knowledge they can provide.

In an era when extended, complex supply chains pose unprecedented risks and

opportunities, big buying companies cannot afford to be in the dark about suppliers far down

their supply chains. Thanks to advances in knowledge about network modelling, databases,

and analytics, they dont have to be.

Thomas Y. Choiis executive director of CAPS Research and chaired professor ofsupply chain management at Arizona State Universitys W. P. Carey School of Business.

Benjamin B. M. Shao is an associate professor of information systems at ArizonaState UniversitysW. P. Carey School of Business.

Zhan Michael Shi is an assistant professor of information systems at Arizona StateUniversitys W. P. Carey School of Business.

Related Topics: SUPPLY CHAIN | MANUFACTURING | OPERATIONS MANAGEMENT

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Thomas Choi 23 days ago

There are several groups that use graph theory to understand supply networks, CAPS Research andElementum being two of them. There are differences. Suppose there is a critical supplier in the third or fourthtier level but a focal buying company such as GM or Siemens is not aware of this supplier. What we are tryingto do at CAPS Research is to identify this supplier. If there is a risk event at this supplier, Elementum wouldthen kick in and try to figure out how this event would actually impact the focal company.

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