Essentials of Capacity Management, by Reginald Tomas Yu-Lee. Essentials of . high skill levels in all areas of supply chain management so companies are focusing .. be as much as a third of the operating cost of a supply chain, decisions. Essentials of Sarbanes-Oxley by Sanjay Anand. Essentials of Supply Chain Management 3rd Edition by Michael Hugos. Essentials of Technical Analysis for . Presenting the core concepts and techniques of supply chain management in a clear, concise and easily readable style, the Third Edition of Essentials of Supply .
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It also includes coordination and collaboration with channel partners , which may be suppliers , intermediaries , third-party service providers, or customers. More recently, the loosely coupled, self-organizing network of businesses that cooperate to provide product and service offerings has been called the Extended Enterprise. Supply-chain management is the management of such a chain. With SCEM, possible scenarios can be created and solutions devised.
Including third-party logistics or other gathering agencies as part of the RM re-patriation process is a way of illustrating the new endgame strategy.
As organizations strive to focus on core competencies and become more flexible, they reduce their ownership of raw materials sources and distribution channels. These functions are increasingly being outsourced to other firms that can perform the activities better or more cost effectively. The effect is to increase the number of organizations involved in satisfying customer demand, while reducing managerial control of daily logistics operations.
Less control and more supply-chain partners lead to the creation of the concept of supply-chain management. The purpose of supply-chain management is to improve trust and collaboration among supply-chain partners thus improving inventory visibility and the velocity of inventory movement. In recent decades, globalization, outsourcing, and information technology have enabled many organizations, such as Dell and Hewlett Packard , to successfully operate collaborative supply networks in which each specialized business partner focuses on only a few key strategic activities.
However, with the complicated interactions among the players, the network structure fits neither "market" nor "hierarchy" categories. From a systems perspective, a complex network structure can be decomposed into individual component firms. Therefore, the choice of an internal management control structure is known to impact local firm performance. First, as an outcome of globalization and the proliferation of multinational companies, joint ventures, strategic alliances, and business partnerships, significant success factors were identified, complementing the earlier " just-in-time ", lean manufacturing , and agile manufacturing practices.
Firms with geographically more extensive supply chains connecting diverse trading cliques tend to become more innovative and productive. Supply-Chain Management draws heavily from the areas of operations management, logistics, procurement, and information technology, and strives for an integrated approach. Historical developments[ edit ] Six major movements can be observed in the evolution of supply-chain management studies: creation, integration, and globalization,  specialization phases one and two, and SCM 2.
Creation era[ edit ] The term "supply chain management" was first coined by Keith Oliver in However, the concept of a supply chain in management was of great importance long before, in the early 20th century, especially with the creation of the assembly line. The characteristics of this era of supply-chain management include the need for large-scale changes, re-engineering, downsizing driven by cost reduction programs, and widespread attention to Japanese management practices.
However, the term became widely adopted after the publication of the seminal book Introduction to Supply Chain Management in by Robert B. Handfield and Ernest L. Nichols, Jr. This era has continued to develop into the 21st century with the expansion of Internet-based collaborative systems.
This era of supply-chain evolution is characterized by both increasing value added and reducing costs through integration. A supply chain can be classified as a stage 1, 2 or 3 network.
In a stage 1—type supply chain, systems such as production, storage, distribution, and material control are not linked and are independent of each other. In a stage 2 supply chain, these are integrated under one plan and enterprise resource planning ERP is enabled. A stage 3 supply chain is one that achieves vertical integration with upstream suppliers and downstream customers. An example of this kind of supply chain is Tesco. Profits generated by operating efficiencies provide people with rewards and the reason to strive to succeed In supply chain management, everyone can acquire and install technology so technology alone cannot constitute a significant competitive advantage.
The advantage lies in the way the game is played. The radically transformative idea here is to employ a process where everyone can see everyone in real-time, and everyone can see what needs to be done moment to moment as events unfold.
If we have common goals, we will get better and better at coordinating our actions with each other to achieve those goals.
I used this technique in a commercial supply chain composed of 40 manufacturers, 26 distributors and 4, stores, and saw how the introduction of real-time visibility created surprising and sustainable increases in operating efficiency 1. Nobody wants to be seen in public as incompetent or endangering the success of the group.
People modify their behavior in order not to be seen as the source of failure. Everyone must perform well if the whole supply chain is to perform well. Supply chains are practical and pragmatic as logistics must be, yet because supply chains are so easily measured, they are a powerful way for people and organizations to practice working together for a common benefit.
And as they get better at this, many other things become possible. In order to play this game people need to know what the score is at all times. They need to know if they are moving toward the goal or away from it.
They need current information that reflects events as they happen, not batch reports delivered 30 days after the end of the last quarter. This allows them to make good, timely decisions and coordinate effectively. Once people are able to see the score and track events as they happen they need to understand how their actions influence the score. If operating results are trending away from performance targets people need to know what to do to bring operations back on track.
If results are on target people need to know how best to sustain them. That means people get the training they need to do their jobs well. It also means that people have the opportunity and authority to act as they see fit when the need arises.
If no action can happen until requests and permissions are passed up and down a chain of command, then responses will be too slow and people will become frustrated with the poor results. When people can see the score at all times and when they know how to act in order to achieve predefined performance targets there is one more condition that must be present in order for a strong alliance to emerge.
That condition is that people have a stake in the outcome. Often this is in the form of a monetary reward when performance targets are achieved.
Without a stake in the outcome, people become bored or indifferent and they will not make the effort to constantly improve and adjust operations to respond as the world changes.
And without this constant effort challenging performance targets cannot be achieved month after month, year after year. In an interview with Steven Johnson I posed six questions and asked him to share his insights on a range of topics. These topics range from what gives a system emergent Essentials of Supply Chain Management, 3rd Edition Promise of the Real-Time Supply Chain 8 characteristics to how could companies organize their supply chains so as to encourage and benefit from emergent behavior.
How is an emergent system different from an assembly line? The catchphrase that I sometimes use is that an emergent system is "smarter" than the sum of its parts.
They tend to be systems made up of many interacting agents, each of which is following relatively simple rules governing its encounters with other agents.
Somehow, out of all these local interactions, a higher-level, global intelligence "emerges. An ant colony is a great example of this: colonies manage to pull off extraordinary feats of resource management and engineering and task allocation, all by following remarkably simple rules of interaction, using a simple chemical language to communicate. There's a queen ant in the colony, but she's only called that because she's the chief reproductive engine for the colony -- she doesn't have any actually command authority.
The ordinary ants just do the thinking collectively, without a leader. A key difference between an emergent system and an assembly line lies in the fluidity of the emergent system: randomness is a key component of the way an ant colony will explore a given environment -- take the random element out, and the colony gets much less interesting, much less capable of stumbling across new ideas.
Assembly lines are all about setting fixed patterns, and eliminating randomness; emergence is all about stumbling across new patterns that work better than the old ones. One of the central lessons, I think, is that emergent systems are always slightly out of control. Their unpredictability is part of their charm, and their power, but it can be Essentials of Supply Chain Management, 3rd Edition Promise of the Real-Time Supply Chain 9 threatening to engineers and planners who have been trained to eliminate unpredictability at every turn.
Some of the systems that I've looked at combine emergent properties and evolutionary ones: the emergent system generates lots of new configurations and ideas, and then there's a kind of natural selection that weeds out the bad ideas and encourages the good ones.
That's largely what a designer of emergent systems should think about doing: it's closer to growing a garden than it is building a factory. What does it mean when you say that emergent systems display complex adaptive behavior? The complexity refers to the number of interacting parts, like the thousands of ants in a colony, or the pedestrians on a street in a busy city. Adaptive behavior is what happens when all those component parts create useful higher-level structures or patterns of behavior with their group interactions, when they create something -- usually unwittingly -- that benefits the members of the group.
When an ant colony determines the shortest route to a new source of food and quickly assembles a line of ants to transport the food back to the next; when thousands of urbanites create a neighborhood with a distinct personality that helps organize and give shape to an otherwise overwhelming city -- these are examples of adaptive behavior. What is negative feedback as opposed to positive feedback? What role does negative feedback play in the ability of a system to exhibit adaptive behavior?
Negative feedback is crucial, and it's not at all negative in a value-judgment sense. Positive feedback is what we generally mean when we talk about feedback, as in the guitar effect that we first started to hear as music in the 60s: music is played through a speaker, which is picked up by a microphone, which then broadcasts it out though the speaker, creating a sound that the microphone picks up, and so on until you get a howling noise that sounds nothing like the originally music.
So positive feedback is a kind of self-perpetuating, additive effect: plug output A into input B which is plugged into input A.
Negative feedback is what you use when you need to dampen down a chain like this, when there's a danger of a kind of runaway effect, or when you're trying to home in on a specific target. Think of a thermostat trying to reach a preset temperature: it Essentials of Supply Chain Management, 3rd Edition Promise of the Real-Time Supply Chain 10 samples the air, and if the air's too cold, it turns the heat on, then samples it again.
Without negative feedback, the room would just keep getting hotter, but the thermostat has been designed to turn the heat off when the air reaches the target temperature. Ants use a comparable technique to achieve the right balance of task allocation throughout the colony: an individual ant who happens to be on foraging duty will sample the number of ants also on foraging duty that she stumbles across over the course of an hour -- if she encounters a certain number, she'll switch over to another talk nest building, say in order to keep the colony from becoming overrun with foragers.
In your book you mention a designer who has proposed building a learning network of traffic lights that will find an optimal solution to continually changing traffic conditions. Is this grid an example of an emergent system?
The idea proposed in the traffic model is not to take the traditional engineering, top-down approach and say: "let's look at the entire city and figure out where all the problems are, and try to design the roads and the light system to eliminate the problems.
So the light would be able to register the number of cars stacked up at the intersection, and it would be able to experiment with different rhythms of red and green, with some feedback from its near neighbors. When it stumbles across a pattern that reduces delays, it sticks to that pattern; if the delays start piling up again, it starts experimenting again.
The problem with this sort of approach is that on Day One it's a terrible, terrible system, because it doesn't yet know anything about traffic flows. You'd have to teach it quite a bit before you could actually implement it. But it would learn very quickly, and most importantly, it would be capable of responding to changing conditions, in a way that the traditionally engineered approach would not.
That's a hallmark of adaptability.
Consider a system composed of many different companies whose goal is to provide a market with the highest levels of responsiveness at the lowest cost to themselves.
High levels of responsiveness require that these companies work together to design, make, and deliver the right products at the right price at the Essentials of Supply Chain Management, 3rd Edition Promise of the Real-Time Supply Chain 11 right time in the right amounts.
What are some of the things that these companies could do to organize themselves into an emergent system? There's a telltale term in supple chain systems, which may well be unavoidable -- the term "chain" itself.
Almost all emergent systems are networks or grids; they tend to be flatter and more horizontal, with interaction possible between all the various agents. The problem that supply chains have with positive feedback revolves around the distance between the consumer and those suppliers further down the chain -- because the information has to pass through so many intermediaries, you get distortion in the message.
Most emergent systems that I've looked at have a great diversity of potential routes that information can follow; the more chain-like they become, they less adaptive they are. The other key here is experimentation: letting the system evolve new patterns of interaction on its own, since these can often be more useful and efficient than the pre- planned ones.
Of course, you don't want to waste a few economic quarters experimenting with different supply chains, most of which are a disaster. But that's where some of the wonderful new modeling systems for complex behavior can be very handy: you can do the experimenting on the computer, and then pick the best solutions to implement in real life.
This invisible hand emerges to set product prices so as to best allocate available supplies to meet market demands. Local interactions between large numbers of agents, governed by simple rules of mutual feedback, produce a macro effect for the system as a whole that results in what we call emergent behavior. As we begin to practice supply chain management as a game between companies and people who are motivated to achieve certain performance targets, we will see emergent behavior in supply chains.
Good players in the supply chains of particular markets will seek each other out because by playing together they can create more efficient supply chains and generate better profits. Supply chains will form up like sports teams and these teams will compete with each other for market share. Just as the game of basketball or soccer evolves over time, so Essentials of Supply Chain Management, 3rd Edition Promise of the Real-Time Supply Chain 12 too will the game of supply chain management.
New tactics, techniques, and technology will come about. Market demands and the desire for competitive advantage will drive companies to collaborate and innovate with each other to win at the game of supply chain management.
Computers are best used to automate the rote, repetitious activities that humans find to be dull and boring.
These are all the on-going and routine activities of recording and monitoring supply chain operations. Computers do these tasks very well. They do not fall asleep, they do not miss details, and they can handle enormous volumes of data without complaint. People are best used to do the creative and problem solving activities. These are the activities that do not have clear right or wrong answers.