Supply Chain Risk Quotes

In business, supply chains risks are not only correlated to the competition or to collaborators or to customers. Supply chain risk is also correlated to all of the companies and industries using the same imputs as your business.

When we look at supply chains and distribution in nature, we see that natural systems include an abundance of nodes in a network. Distribution is widely spread - enough to include the maximum nodes feasible yet not enough to add unnecessary time or cost to the path a thing takes from source to destination. This maximizes efficiency, and minimizes the risk of congestion and bottle-necks.

Outsourcing requires a tight integration of suppliers, making sure that all pieces arrive just in time. Therefore, when some suppliers were unable to deliver certain basic components like capacitors and flash memory, Compaq's network was paralyzed. The company was looking at 600,000 to 700,000 unfilled orders in handheld devices. The $499 Pocket PCs were selling for $700 to $800 at auctions on eBay and Amazon.com. Cisco experienced a different but equally damaging problem: When orders dried up, Cisco neglected to turn off its supply chain, resulting in a 300 percent ballooning of its raw materials inventory. The final numbers are frightening: The aggregate market value loss between March 2000 and March 2001 of the twelve major companies that adopted outsourcing-Cisco, Dell, Compaq, Gateway, Apple, IBM, Lucent, Hewlett-Packard, Motorola, Ericsson, Nokia, and Nortel-exceeded $1.2 trillion. The painful experience of these companies and their investors is a vivid demonstration of the consequences of ignoring network effects. A me attitude, where the company's immediate financial balance is the only factor, limits network thinking. Not understanding how the actions of one node affect other nodes easily cripples whole segments of the network. Experts agree that such rippling losses are not an inevitable downside of the network economy. Rather, these companies failed because they outsourced their manufacturing without fully understanding the changes required in their business models. Hierarchical thinking does not fit a network economy. In traditional organizations, rapid shifts can be made within the organization, with any resulting losses being offset by gains in other parts of the hierarchy. In a network economy each node must be profitable. Failing to understand this, the big players of the network game exposed themselves to the risks of connectedness without benefiting from its advantages. When problems arose, they failed to make the right, tough decisions, such as shutting down the supply line in Cisco's case, and got into even bigger trouble. At both the macro- and the microeconomic level, the network economy is here to stay. Despite some high-profile losses, outsourcing will be increasingly common. Financial interdependencies, ignoring national and continental boundaries, will only be strengthened with globalization. A revolution in management is in the making. It will take a new, network-oriented view of the economy and an understanding of the consequences of interconnectedness to smooth the way.

Now they can acquire “the egg from one source (including, in many cases, the intended mother) and the womb from another.”50 This “unbundling” of the supply chain, Spar explains, has prompted growth in the surrogacy market.51 “By removing the traditional link between egg, womb, and mother, gestational surrogacy [has] reduced the legal and emotional risks that had surrounded traditional surrogacy and allowed a new market to thrive.

The goal is to hit the sweet spot of maximum value optimization, where foolish risk is balanced against excessive caution.

A risk is an event that may or may not occur, such as a hurricane. Risk is just another word for uncertainty. A threat is the impact the risk would have on your supply chain; in the case of a hurricane, one threat could be that your factory would be flooded.

How can you run Analytics “as one”? If you leave Analytics to IT, you will end up with a first-class race car without a driver: All the technology would be there, but hardly anybody could apply it to real-world questions. Where Analytics is left to Business, however, you’d probably see various functional silos develop, especially in larger organizations. I have never seen a self-organized, cross-functional Analytics approach take shape successfully in such an organization. Instead, you can expect each Analytics silo to develop independently. They will have experts familiar with their business area, which allows for the right questions to be asked. On the other hand, the technical solutions will probably be second class as the functional Analytics department will mostly lack the critical mass to mimic an organization’s entire IT intelligence. Furthermore, a lot of business topics will be addressed several times in parallel, as those Analytics silos may not talk to each other. You see this frequently in organizations that are too big for one central management team. They subdivide management either into functional groups or geographical groups. Federation is generally seen as an organizational necessity. It is well known that it does not make sense to regularly gather dozens of managers around the same table: You’d quickly see a small group discussing topics that are specific to a business function or a country organization, while the rest would get bored. A federated approach in Analytics, however, comes with risks. The list of disadvantages reaches from duplicate work to inconsistent interpretation of data. You can avoid these disadvantages by designing a central Data Analytics entity as part of your Data Office at an early stage, to create a common basis across all of these areas. As you can imagine, such a design requires authority, as it would ask functional silos to give up part of their autonomy. That is why it is worthwhile creating a story around this for your organization’s Management Board. You’d describe the current setup, the behavior it fosters, and the consequences including their financial impact. Then you’d present a governance structure that would address the situation and make the organization “future-proof.” Typical aspects of such a proposal would be The role of IT as the entity with a monopoly for technology and with the obligation to consider the Analytics teams of the business functions as their customers The necessity for common data standards across all of those silos, including their responsibility within the Data Office Central coordination of data knowledge management, including training, sharing of experience, joint cross-silo expert groups, and projects Organization-wide, business-driven priorities in Data Analytics Collaboration bodies to bring all silos together on all management levels

3D printers are already producing parts that are lighter than traditionally built parts, are much stronger in design, and are more readily produced on demand for machines as sophisticated as NASA rockets and Air Force fighters. But for mission-critical products like these, there’s also a risk, one that’s put into context by James Regenor, director of the additive manufacturing and innovation unit at precision parts manufacturer Moog, Inc.: “How can the maintenance crew on a U.S. aircraft carrier have absolute confidence that the software file they downloaded to 3D-print a new part for a fighter jet hasn’t been hacked by a foreign adversary?” To tackle this problem, Regenor’s team at Moog has launched a service it calls Veripart, which uses blockchain technology to, among other things, verify the software design and upgrading work performed by different providers of 3D-printed products along a supply chain. It plans to incorporate a host of features that, among other things, will protect intellectual property and make it more flexible and dynamic as an asset.

Perhaps the most important thing to remember about supply chain vulnerability to political actions is cumulative risk: The risk of disruption in any one node of a supply chain may be low, but the cumulative risk of disruption across the entire supply chain is much higher.