Supply Chain Management

Supply chain optimization

2008-09-19T19:22:00.000-07:00

Supply Chain Optimization is the application of processes and tools to ensure the optimal operation of a manufacturing and distributionsupply chain. This includes the optimal placement of inventory within the supply chain, minimizing operating costs (including manufacturing costs, transportation costs, and distribution costs). This often involves the application of mathematical modelling techniques using computer software.

What need is being addressed?

Typically, supply chain managers are trying to maximize the profitable operation of their manufacturing and distribution supply chain. This could include measures like maximizing gross margin return on inventory invested (GMROII)( balancing the cost of inventory at all points in the supply chain with availability to the customer ), minimizing total operating expenses (transportation, inventory and manufacturing), or maximizing gross profit of products distributed through the supply chain. Supply chain optimization addresses the general supply chain problem of delivering products to customers at the lowest total cost and highest profit. This includes trading off the costs of inventory, transportation, distributing and manufacturing.

Supply chain optimization has applications in all industries manufacturing and/or distributing goods, including retail, industrial products, and consumer packaged goods (CPG).

What approaches and solutions exist?

The classic supply chain approach has been to try to forecast future inventory demand as accurately as possible, by applying statistical trending and "best fit" techniques based on historic demand and predicted future events. The advantage of this approach is that it can be applied to data aggregated at a fairly high level (e.g. category of merchandise, weekly, by group of customers), requiring modest database sizes and small amounts of manipulation. Unpredictability in demand is then managed by setting safety stock levels, so that for example a distributor might hold two weeks of supply of an article with steady demand but twice that amount for an article where the demand is more erratic.

Then, using this forecast demand, a supply chain manufacturing and distribution plan is created to manufacture and distribute products to meet this forecast demand at lowest cost (or highest profitability). This plan typically addresses the following business concerns: - How much of each product should be manufactured each day? - How much of each product should be made at each manufacturing plant? - Which manufacturing plants should re-stock which warehouses with which products? - What transportation modes should be used for warehouse replenishment and customer deliveries?

The technical ability to record and manipulate larger databases more quickly has now enabled a new breed of supply chain optimization solutions to emerge, which are capable of forecasting at a much more granular level (for example, per article per customer per day). Some vendors are applying "best fit" models to this data, to which safety stock rules are applied, while other vendors have started to apply stochastictechniques to the optimization problem. They calculate the most desirable inventory level per article for each individual store for their retail customers, trading off cost of inventory against expectation of sale. The resulting optimized inventory level is known as a model stock. Meeting the model stock level is also an area requiring optimization. Because the movement of product to meet the model stock, called the stock transfer, needs to be in economic shipping units such as complete unit loads or a full truckload, there are a series of decisions that must be made. Many existing distribution requirements planning systems round the quantity up to the nearest full shipping unit. The creation of for example, truckloads as economic shipment units requires optimization systems to ensure that axle constraints and space constraints are met while loading can be achieved in a damage-free way. This is generally achieved by continuing to add time-phased requirements until the loads meet some minimum weight or cube.

Optimization solutions are typically part of, or linked to, the company's replenishment systems distribution requirements planning, so that orders can be automatically generated to maintain the model stock profile. The algorithms used are similar to those used in making financialinvestment decisions; the analogy is quite precise, as inventory can be considered to be an investment in prospective return on sales.

Supply chain optimization may include refinements at various stages of the product lifecycle, so that new, ongoing and obsolete items are optimised in different ways: and adaptations for different classes of products, for example seasonal merchandise.

Whilst a few software vendors are offering supply chain optimization as a packaged solution, others are running the software on behalf of their clients as application service providers.

What are the claims for supply chain optimization?

Firstly, the techniques being applied to supply chain optimization are claimed to be academically credible. Most of the specialist companies have been created as a result of research projects in academic institutions or consulting firms: and they point to research articles, white papers, academic advisors and industry reviews to support their credibility.

Secondly, the techniques are claimed to be commercially effective. The companies publish case studies that show how clients have achieved reductions in inventory whilst maintaining or improving availability. There is limited published data outside of these case studies, and a reluctance for some practitioners to publish details of their successes (which may be commercially sensitive), therefore hard evidence is difficult to come by.

Recent Developments

The trend to provide software as a service is a new business model that is now being applied to building and designing optimization solutions. Services are charged as used, rather than through licensing installed or hosted software.

http://en.wikipedia.org/wiki/Supply_chain_optimization

Demand optimization

2008-09-19T19:10:00.001-07:00

Demand optimization

Demand optimization is the application of processes and tools to maximise return on sales. This usually involves the application of mathematical modelling techniques using computer software.

It has particular applications in retail, where merchants wish to identify the best combination of price and promotion to achieve desired sales,gross margin, inventory or market share objectives.

The methods used are similar to those applied in the related field of supply chain optimization, where mathematical algorithms are applied to large databases of sales data to help predict future outcomes. In the case of demand optimization, as well as in house sales history, there may be competitive pricing information.

Because it is still a new field, authoritative data on the benefits of demand optimization is not widely available, although suppliers offer case studies of early adopters which claim rapid return on investment, especially in the optimization of the timing and level of price markdowns.

Benefit shortfall

A benefit shortfall results from the actual benefits of a venture being lower than the projected, or estimated, benefits of that venture.^[1] If, for instance, a company is launching a new product or service and projected sales are 40 million dollars per year, whereas actual annual sales turn out to be only 30 million dollars, then the benefit shortfall is said to be 25 percent. Sometimes the terms "demand shortfall" or "revenue shortfall" are used instead of benefit shortfall.

Public and private enterprises alike fall victim to benefit shortfalls. Prudent planning of new ventures will include the risk of benefit shortfalls inrisk assessment and risk management.

If large benefit shortfalls coincide with large cost overruns in a venture - as happened for the Channel tunnel between the UK and France - then fiscal and other distress will be particularly pronounced for that venture.^[2]

The root cause of benefit shortfalls is benefit overestimation during the planning phase of new ventures. Benefit overestimation (and cost underestimation) are main sources of error and bias in cost-benefit analysis. Reference class forecasting was developed to reduce the risk of benefit shortfalls and cost overruns.

Cost overrun

Cost overrun is defined as excess of actual cost over budget. Cost overrun is also sometimes called "cost escalation," "cost increase," or "budget overrun." However, cost escalation and increases do not necessarily result in cost overruns if cost escalation is included in the budget.

Cost overrun is common in infrastructure, building, and technology projects. One of the most comprehensive studies [1] of cost overrun that exists found that 9 out of 10 projects had overrun, overruns of 50 to 100 percent were common, overrun was found in each of 20 nations and five continents covered by the study, and overrun had been constant for the 70 years for which data were available. For IT projects, an industry study by the Standish Group (2004) found that average cost overrun was 43 percent, 71 percent of projects were over budget, over time, and under scope, and total waste was estimated at US$55 billion per year in the US alone.

Spectacular examples of cost overrun are the Sydney Opera House with 1,400 percent, and the Concorde supersonic aeroplane with 1,100 percent. The cost overrun of Boston's Big Dig was 275 percent, or US$11 billion. The cost overrun for the Channel tunnel between the UK and France was 80 percent for construction costs and 140 percent for financing costs.

Three types of explanation of cost overrun exist: technical, psychological, and political-economic. Technical explanations account for cost overrun in terms of imperfect forecasting techniques, inadequate data, etc. Psychological explanations account for overrun in terms of optimism bias with forecasters. Finally, political-economic explanations see overrun as the result of strategic misrepresentation of scope and/or budgets.

All of the explanations above can be considered a form of risk. A project's budgeted costs should always include cost contingency funds to cover risks (other than scope changes imposed on the project). As has been shown in cost engineering research ^[1], poor risk analysis and contingency estimating practices account for many project cost overruns. Numerous studies have found that the greatest cause of cost growth was poorly defined scope at the time that the budget was established. The cost growth (overrun of budget before cost contingency is added) can be predicted by rating the extent of scope definition, even on complex projects with new technology. ^[2]

Cost overrun is typically calculated in one of two ways. Either as a percentage, namely actual cost minus budgeted cost, in percent of budgeted cost. Or as a ratio, viz. actual cost divided by budgeted cost. For example, if the budget for building a new bridge was $100 million and the actual cost was $150 million then the cost overrun may be expressed as 50 percent or by the ratio 1.5.

Cost-benefit analysis

Cost-benefit analysis is a term that refers both to:

a formal discipline used to help appraise, or assess, the case for a project or proposal, which itself is a process known as project appraisal; and
an informal approach to making decisions of any kind.

Under both definitions the process involves, whether explicitly or implicitly, weighing the total expected costs against the total expected benefits of one or more actions in order to choose the best or most profitable option. The formal process is often referred to as CBA, or Cost-Benefit analysis in the United States.

Closely related, but slightly different, formal techniques include cost-effectiveness analysis and benefit effectiveness analysis.^{[citation needed]}Social Return on Investment (SROI) analysis builds upon the logic of cost-benefit analysis, but differs in that it is explicitly designed to inform the practical decision-making of enterprise managers and investors focused on optimising their social and environmental impacts.

Theory

Cost Benefit Analysis is typically used by governments to evaluate the desirability of a given intervention in markets. The aim is to gauge the efficiency of the intervention relative to the status quo. The costs and benefits of the impacts of an intervention are evaluated in terms of the public's willingness to pay for them (benefits) or willingness to pay to avoid them (costs). Inputs are typically measured in terms of opportunity costs - the value in their best alternative use. The guiding principle is to list all of the parties affected by an intervention, and place a monetary value of the effect it has on their welfare as it would be valued by them.

The process involves monetary value of initial and ongoing expenses vs. expected return. Constructing plausible measures of the costs and benefits of specific actions is often very difficult. In practice, analysts try to estimate costs and benefits either by using survey methods or by drawing inferences from market behaviour. For example, a product manager may compare manufacturing and marketing expenses to projected sales for a proposed product, and only decide to produce it if he expects the revenues to eventually recoup the costs. Cost-benefit analysis attempts to put all relevant costs and benefits on a common temporal footing. A discount rate is chosen, which is then used to compute all relevant future costs and benefits in present-value terms. Most commonly, the discount rate used for present-value calculations is an interest rate taken from financial markets (R.H. Frank 2000). This can be very controversial - for example, a high discount rate implies a very low value on the welfare of future generations, which may have a huge impact on the desirability of interventions to help the environment, and so on. Empirical studies have suggested that in reality, people's discount rates do decline over time. Because CBA aims to measure the public's true willingness to pay, this feature is typically built into studies.

During cost-benefit analysis, monetary values may also be assigned to less tangible effects such as the various risks which could contribute to partial or total project failure; loss of reputation, market penetration, long-term enterprise strategy alignments, etc. This is especially true when governments use the technique, for instance to decide whether to introduce business regulation, build a new road or offer a new drug on the state healthcare. In this case, a value must be put on human life or the environment, often causing great controversy. The cost-benefit principle says, for example, that we should install a guardrail on a dangerous stretch of mountain road if the dollar cost of doing so is less than the implicit dollar value of the injuries, deaths, and property damage thus prevented (R.H. Frank 2000).

Cost-benefit calculations typically involve using time value of money formula. This is usually done by converting the future expected streams of costs and benefits to a present value amount.

Application

Cost-benefit analysis is mainly, but not exclusively, used to assess the value for money of very large private and public sector projects. This is because such projects tend to include costs and benefits that are less amenable to being expressed in financial or monetary terms (e.g. environmental damage), as well as those that can be expressed in monetary terms. Private sector organisations tend to make much more use of other project appraisal techniques, such as rate of return, where feasible.

The practice of cost-benefit analysis differs between countries and between sectors (e.g. transport, health) within countries. Some of the main differences include the types of impacts that are included as costs and benefits within appraisals, the extent to which impacts are expressed in monetary terms and differences in discount rate between countries.

Basic cost-benefit techniques were applied to the development of the motorway network in the 1950s and 60s. An early, and often quoted, more developed application of the technique was made to London Underground's Victoria Line. Over the last 40 years, cost-benefit techniques have gradually developed to the extent that substantial guidance now exists on how transport projects should be appraised in the UK. TheDepartment for Transport (DfT) and its agencies have made extensive use of a number of key cost-benefit indicators, including:

PVB (present value of benefits);
PVC (present value of costs);
NPV (PVB less PVC);
NPV/k (where k is the level of funds available) and
BCR (benefit cost ratio, PVB divided by PVC).

In 1998 the New Approach to Appraisal (NATA) was introduced by the then Department for Transport, Environment and the Regions. This brought together cost-benefit results with those from detailed environmental impact assessments and presented them in a balanced way. NATA was first applied to national road schemes in the 1998 Roads Review, but subsequently rolled out to all modes of transport. It is now a cornerstone of transport appraisal in the UK and is maintained and developed by the Department for Transport.

The EU's 'Developing Harmonised European Approaches for Transport Costing and Project Assessment' (HEATCO) project, part of its Sixth Framework Programme, has reviewed transport appraisal guidance across EU member states and found that significant differences exist between countries. HEATCO's aim is to develop guidelines to harmonise transport appraisal practice across the EU.[1

Much of the early development work on cost-benefit analysis as a discipline was the result of problems faced by the US Army Corps of Engineers in deciding how and where to build bridges in supporting combat operations.^{[citation needed]}

Cost-benefit analysis is now a well established discipline in the US. California's Department of Transportation (Caltrans) provide detailed guidance on how Cost-benefit analysis should be applied to transport projects.

Accuracy problems

The accuracy of the outcome of a cost-benefit analysis is dependent on how accurately costs and benefits have been estimated. A peer-reviewed study [2] of the accuracy of cost estimates in transportation infrastructure planning found that for rail projects actual costs turned out to be on average 44.7 percent higher than estimated costs, and for roads 20.4 percent higher (Flyvbjerg, Holm, and Buhl, 2002). For benefits, another peer-reviewed study [3] found that actual rail ridership was on average 51.4 percent lower than estimated ridership; for roads it was found that for half of all projects estimated traffic was wrong by more than 20 percent (Flyvbjerg, Holm, and Buhl, 2005). Comparative studies indicate that similar inaccuracies apply to fields other than transportation. These studies indicate that the outcomes of cost-benefit analyses should be treated with caution, because they may be highly inaccurate. In fact, inaccurate cost-benefit analyses may be argued to be a substantial risk in planning, because inaccuracies of the size documented are likely to lead to inefficient decisions, as defined by Pareto andKaldor-Hicks efficiency ([4] Flyvbjerg, Bruzelius, and Rothengatter, 2003).

These outcomes (almost always tending to underestimation, unless significant new approaches are overlooked) are to be expected, since such estimates:

1. rely heavily on past like projects (frequently differing markedly in function or size, and certainly in the skill levels of the team members),

2. rely heavily on the project's members to identify (remember from their collective past experiences) the significant cost drivers,

3. rely on very crude heuristics ('rules of thumb') to estimate the money cost of the intangible elements, and

4. are unable to completely dispel the usually (unconscious) biases of the team members (who often have a vested interest in a decision to 'go ahead') and the natural psychological tendency to "think positive" (whatever that involves).

Another challenge to cost-benefit analysis comes from determining which costs should be included in an analysis (the significant cost drivers). This is often controversial as organizations or interest groups may feel that some costs should be included or excluded from a study.

In the case of the Ford Pinto (where, due to design flaws, the Pinto was liable to burst into flames in a rear-impact collision), the Ford company's decision was not to issue a recall. Ford's cost benefit analysis had estimated that: based on the number of cars in use and the probable accident rate, deaths due to the design flaw would run about $49.5 million (the amount Ford would pay out of court to settle wrongful death lawsuits). This was estimated to be less than the cost of issuing a recall ($137.5 million) [5]. In the event, Ford overlooked (or considered insignificant) the costs of the negative publicity so engendered, which turned out to be quite significant (since it led to the recall anyway and to measurable losses in sales).

Specifically in the field of Health Economics, cost-benefit analysis is viewed as an inadequate measure by extra-welfarists, as willingness-to-pay methods of determining the value of human life are subject to bias according to income inequity. This is due to the inherent nature of "ability to pay," which weighs heavily in the willingness-to-pay question (i.e. one's willingness-to-pay is constrained by one's ability-to-pay). For this reason, extra-welfarists support use of cost-utility analysis and the QALY to analyze the effects of health policies.

Sources and further reading

Sukhamoy Chakravarty (1987). "cost-benefit analysis," The New Palgrave: A Dictionary of Economics, v. 1, pp. 687-90.
Bent Flyvbjerg, Nils Bruzelius, and Werner Rothengatter, Megaprojects and Risk: An Anatomy of Ambition (Cambridge University Press, 2003). [6]
Bent Flyvbjerg, Mette K. Skamris Holm, and Søren L. Buhl, "Underestimating Costs in Public Works Projects: Error or Lie?" Journal of the American Planning Association, vol. 68, no. 3, Summer 2002, pp. 279-295. [7]
Bent Flyvbjerg, Mette K. Skamris Holm, and Søren L. Buhl, "How (In)accurate Are Demand Forecasts in Public Works Projects? The Case of Transportation." Journal of the American Planning Association, vol. 71, no. 2, Spring 2005, pp. 131-146. [8]
Tevfik F. Nas, Cost-Benefit Analysis: Theory and Application (Thousand Oaks, Ca.: Sage, 1996). [9]
Folland, Sherman, Allen C. Goodman and Miron Stano. The Economics of Heath and Health Care. Fifth ed. Pearson Prentice Hall: New Jersey, 2007. pg 83, 84.

Ascott, Elizabeth. 2006. Benefit Cost Analysis of Wonderworld Drive Overpass in San Marcos, Texas. Applied Research Project. Texas State University. http://ecommons.txstate.edu/arp/104/

http://en.wikipedia.org/wiki/Cost-benefit_analysis

Customer-driven supply chain

2008-09-19T19:03:00.001-07:00

Customer-driven supply chain

In a customer driven supply chain, end-user demand drives all activities among trading partners.
Customer driven supply chain distinguishes between actions that provide customers with real value, and actions which just add costs. It facilitates and possibly maximizes collaboration with suppliers. It reduces throughout time, touch points and decision points. It increases machine and transport effectiveness. It provides quick and easy access to inventory for sales and service. It reduces excess inventory, stock-outs, shrinkage, and order delays, as well as automates inventory data transfers between stores and warehouses. It reduces purchase order errors. It accelerates time to market.

Demand chain management

Demand Chain Management is the management of upstream and downstream relationships between suppliers and customers to deliver the best value to the customer at the least cost to the demand chain as a whole. The term demand chain management is used to denote the concept commonly referred to as supply chain management, however with special regard to the customer pull [1]. In that sense, demand chain management software tools bridge the gap between the customer relationship management and the supply chain management [2]. The organization's supply chain processes are managed to deliver best value according to the demand of the customers. A study of the university inWageningen (the Netherlands) sees DCM as an extension of supply chain management, due to its incorporation of the market orientation perspective on its concept[3].

Demand-Driven Supply Network

A Demand-Driven Supply Network (DDSN) is one method of supply chain management which involves building supply chains in response to demand signals. The main force of DDSN is that it is driven by customers demand. In comparison with the traditional supply chain, DDSN uses the pull technique. It gives DDSN market opportunities to share more information and to collaborate with others in the supply chain. This results that companies have a better view of customers demand.

DDSN uses a capability model that consist of four levels. The first level is Reacting, the second level is Anticipating, the third level isCollaborating and the last level is Orchestrating. The first two levels focus on the internal supply chain while the last two levels concentrate on external relations throughout the Extended Enterprise[4].

An important component of DDSN is DDM ("real-time" demand driven manufacturing). DDM gives customers the opportunity to say what they want, where and when.

Competitive advantages
To create sustainable competitive advantages with DDSN, companies have to do deal with three conditions: Alignment (create shared incentives), Agility (respond quickly to short-term change) and Adaptability (adjust design of the supply chain)[5].

Misconceptions
There are five common made misconceptions of demand driven (DDSN). Companies might think they are demand driven because they have a good forecast of their company; they have implemented lean manufacturing; they have great data on all their customers; they think it is a technology project and the corporate forecast is a demand visibility signal. Organizations need to recognize this and that they won't make the same mistake [6].

have a better view of customers demand.
DDSN uses a capability model that consist of four levels. The first level is Reacting, the second level is Anticipating, the third level isCollaborating and the last level is Orchestrating. The first two levels focus on the internal supply chain while the last two levels concentrate on external relations [7].

An important component of DDSN is DDM ("real-time" demand driven manufacturing). DDM gives customers the opportunity to say what they want, where and when.

be aware of different implementations to realize DCM

DCM based on forecasts and plans
Some approaches combine business intelligence software and POS-data analysis to predict customers demand based on historical data. Highly sophisticated Forecast-systems try to generate better reorder data based on existing sales-data combined with other key factors like Holidays, Events (sports, Olympia, car races ..) to react on possible future customers demand.

DCM based on monitoring the reality
A different approach is to record every event related to stock changes like sales and replenishment in real time. Real time DCM can calculate sales trends on the fly and generate reorder signals our out-of-stock signals, and the best based on sales trends it is possible to generate warnings about near future out-of-stock situations on thy fly. If this signal raises early enough the supply chain can avoid the out-of-stock-situation.

The difference between both approaches is very clear:
Forecasts or planning systems are good to do better in future, but this approach doesn't show you the actual reality. It seems to be impossible to have real time forecasts for every shelve in every store all over the world.

Monitoring is perfect to avoid Out-of-Stock situations and enables to be proactive supporting your customers. These systems are much more adaptive to actual events/demands but this systems don't provide any forecasts.

The most perfect system might be set up if both approaches are implemented. Data of real time DCM helps to have much better historical data quality if OOS is avoided. The planning system can provide much better forecasts because of better data quality and this system might provide dynamic high/low watermarks for stock levels which are to be monitored by the real time DCM.

Supply chain

A supply chain or logistics network is the system of organizations, people, technology, activities, information and resources involved in moving a product or service from supplier to customer. Supply chain activities transform natural resources, raw materials and components into a finished product that is delivered to the end customer. In sophisticated supply chain systems, used products may re-enter the supply chain at any point where residual value is recyclable. Supply chains link value chains[1].

A typical supply chain begins with ecological and biological regulation of natural resources, followed by the human extraction of raw material and includes several production links, for instance; component construction, assembly and merging before moving onto several layers of storage facilities of ever decreasing size and ever more remote geographical locations, and finally reaching the consumer.

Many of the exchanges encountered in the supply chain will therefore be between different companies who will seek to maximize their revenue within their sphere of interest, but may have little or no knowledge or interest in the remaining players in the supply chain. More recently, the loosely coupled, self-organizing network of businesses that cooperates to provide product and service offerings has been called the Extended Enterprise.[2]

Supply chain modelling

here are a variety of supply chain models, which address both the upstream and downstream sides.
The SCOR (Supply Chain Operations Reference) model, developed by the Supply Chain Council, measures total supply chain performance. It is a process reference model for supply-chain management, spanning from the supplier's supplier to the customer's customer.[3]. It includes delivery and order fulfillment performance, production flexibility, warranty and returns processing costs, inventory and asset turns, and other factors in evaluating the overall effective performance of a supply chain.

The Global Supply Chain Forum (GSCF) introduced another Supply Chain Model. This framework [4] is built on eight key business processes that are both cross-functional and cross-firm in nature. Each process is managed by a cross-functional team, including representatives from logistics, production, purchasing, finance, marketing and research and development. While each process will interface with key customers and suppliers, the customer relationship management and supplier relationship management processes form the critical linkages in the supply chain.

Supply chain management

In the 1980s the term Supply Chain Management (SCM) was developed, to express the need to integrate the key business processes, from end user through original suppliers. Original suppliers being those that provide products, services and information that add value for customers and other stakeholders. The basic idea behind the SCM is that companies and corporations involve themselves in a supply chain by exchanging information regarding market fluctuations, production capabilities.

If all relevant information is accessible to any relevant company, every company in the supply chain has the possibility to and can seek to help optimizing the entire supply chain rather than sub optimize based on a local interest. This will lead to better planned overall production and distribution which can cut costs and give a more attractive final product leading to better sales and better overall results for the companies involved.

Incorporating SCM successfully leads to a new kind of competition on the global market where competition is no longer of the company versus company form but rather takes on a supply chain versus supply chain form.

The primary objective of supply chain management is to fulfill customer demands through the most efficient use of resources, including distribution capacity, inventory and labor. In theory, a supply chain seeks to match demand with supply and do so with the minimal inventory. Various aspects of optimizing the supply chain include liaising with suppliers to eliminate bottlenecks; sourcing strategically to strike a balance between lowest material cost and transportation, implementing JIT (Just In Time) techniques to optimize manufacturing flow; maintaining the right mix and location of factories and warehouses to serve customer markets, and using location/allocation, vehicle routing analysis, Dynamic programming and, of course, traditional logistics optimization to maximize the efficiency of the distribution side.

There is often confusion over the terms Supply Chain and Logistics. It is now generally accepted that the term Logistics applies to activities within one company/organization involving distribution of product whereas the term Supply Chain also encompasses manufacturing and procurement and therefore has a much broader focus as it involves multiple enterprises, including suppliers, manufacturers and retailers, working together to meet a customer need for a product or service.

Starting in the 1990s several companies choose to outsource the logistics aspect of supply chain management by partnering with a 3PL, Third-party logistics provider. Companies also outsource production to contract manufacturers.

There are actually four common Supply Chain Models. Besides the two mentioned above, there are the American Productivity & Quality Center's (APQC) Process Classification Framework and the Supply Chain Best Practices Framework. Critics has questioned the validity of all these models.

http://en.wikipedia.org/wiki/Supply_chain

Supply Chain Management

2008-09-19T13:26:00.000-07:00

Supply chain management (SCM) is the process of planning, implementing and controlling the operations of the supply chain as efficiently as possible. Supply Chain Management spans all movement and storage of raw materials, work-in-process inventory, and finished goods from point-of-origin to point-of-consumption.

The definition one American professional association put forward is that Supply Chain Management encompasses the planning and management of all activities involved in sourcing, procurement, conversion, and logistics management activities. Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third-party service providers, and customers. In essence, Supply Chain Management integrates supply and demand management within and across companies. More recently, the loosely coupled, self-organizing network of businesses that cooperates to provide product and service offerings has been called the Extended Enterprise.^[1]

Supply Chain Management can also refer to Supply chain management softwarewhich are tools or modules used in executing supply chain transactions, managing supplier relationships and controlling associated business processes.

Supply chain event management (abbreviated as SCEM) is a consideration of all possible occurring events and factors that can cause a disruption in a supply chain. With SCEM possible scenarios can be created and solutions can be planned.

Supply Chain Management Problems

Supply chain management must address the following problems:

Distribution Network Configuration: Number, location and network missions of suppliers, production facilities, distribution centers, warehouses, cross-docks and customers.
Distribution Strategy: Including questions of operating control (centralized, decentralized or shared); delivery scheme (e.g., direct shipment, pool point shipping, Cross docking, DSD (direct store delivery), closed loop shipping); mode of transportation (e.g., motor carrier, including truckload, LTL, parcel; railroad; intermodal, including TOFC and COFC; ocean freight; airfreight); replenishment strategy (e.g., pull, push or hybrid); and transportation control (e.g., owner-operated, private carrier, common carrier, contract carrier, or 3PL). Trade-Offs in Logistical Activities

The above activities must be coordinated well together in order to achieve the least total logistics cost. Trade-offs exist that increase the total cost if only one of the activities is optimized. For example, full truckload (FTL) rates are more economical on a cost per pallet basis than less than truckload (LTL) shipments. If, however, a full truckload of a product is ordered to reduce transportation costs there will be an increase in inventory holding costs which may increase total logistics costs. It is therefore imperative to take a systems approach when planning logistical activities. These trade-offs are key to developing the most efficient and effective Logistics and SCM strategy.

Information: Integration of and other processes through the supply chain to share valuable information, including demand signals, forecasts, inventory, transportation, and potential collaboration etc.
Inventory Management: Quantity and location of inventory including raw materials, work-in-process and finished goods.
Cash-Flow: Arranging the payment terms and the methodologies for exchanging funds across entities within the supply chain.

Supply chain execution is managing and coordinating the movement of materials, information and funds across the supply chain. The flow is bi-directional.

Activities/functions

Supply chain management is a cross-functional approach to manage the movement of raw materials into an organization, certain aspects of the internal processing of materials into finished goods, and then the movement of finished goods out of the organization toward the end-consumer. As organizations strive to focus on core competencies and becoming more flexible, they have reduced their ownership of raw materials sources and distribution channels. These functions are increasingly being outsourced to other entities 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 management control of daily logistics operations. Less control and more supply chain partners led to the creation of supply chain management concepts. The purpose of supply chain management is to improve trust and collaboration among supply chain partners, thus improving inventory visibility and improving inventory velocity.

Several models have been proposed for understanding the activities required to manage material movements across organizational and functional boundaries. SCOR is a supply chain management model promoted by the Supply Chain Management Council. Another model is the SCM Model proposed by the Global Supply Chain Forum (GSCF). Supply chain activities can be grouped into strategic, tactical, and operational levels of activities.

Strategic

Strategic network optimization, including the number, location, and size of warehouses, distribution centers and facilities.

Strategic partnership with suppliers, distributors, and customers, creating communication channels for critical information and operational improvements such as cross docking, direct shipping, and third-party logistics.

Product design coordination, so that new and existing products can be optimally integrated into the supply chain, load management

Information Technology infrastructure, to support supply chain operations.

Where-to-make and what-to-make-or-buy decisions

Aligning overall organizational strategy with supply strategy.

Tactical

Sourcing contracts and other purchasing decisions.

Production decisions, including contracting, scheduling, and planning process definition.

Inventory decisions, including quantity, location, and quality of inventory.

Transportation strategy, including frequency, routes, and contracting.

Benchmarking of all operations against competitors and implementation of best practices throughout the enterprise.

Milestone payments

Focus on customer demand.

Operational

Daily production and distribution planning, including all nodes in the supply chain.
Production scheduling for each manufacturing facility in the supply chain (minute by minute).
Demand planning and forecasting, coordinating the demand forecast of all customers and sharing the forecast with all suppliers.
Sourcing planning, including current inventory and forecast demand, in collaboration with all suppliers.
Inbound operations, including transportation from suppliers and receiving inventory.
Production operations, including the consumption of materials and flow of finished goods.
Outbound operations, including all fulfillment activities and transportation to customers.
Order promising, accounting for all constraints in the supply chain, including all suppliers, manufacturing facilities, distribution centers, and other customers...

Supply chain management

Organizations increasingly find that they must rely on effective supply chains, or networks, to successfully compete in the global market and networked economy.^[2] In Peter Drucker's (1998) management's new paradigms, this concept of business relationships extends beyond traditional enterprise boundaries and seeks to organize entire business processes throughout a value chain of multiple companies.

During the past decades, globalization, outsourcing and information technology have enabled many organizations, such as Dell and Hewlett Packard, to successfully operate solid collaborative supply networks in which each specialized business partner focuses on only a few key strategic activities (Scott, 1993). This inter-organizational supply network can be acknowledged as a new form of organization. However, with the complicated interactions among the players, the network structure fits neither "market" nor "hierarchy" categories (Powell, 1990). It is not clear what kind of performance impacts that different supply network structures could have on firms, and little is known about the coordination conditions and trade-offs that may exist among the players. From a system's point of view, a complex network structure can be decomposed into individual component firms (Zhang and Dilts, 2004). Traditionally, companies in a supply network concentrate on the inputs and outputs of the processes, with little concern for the internal management working of other individual players. Therefore, the choice of an internal management control structure is known to impact local firm performance (Mintzberg, 1979).

In the 21st century, there have been a few changes in business environment that have contributed to the development of supply chain networks. First, as an outcome of globalization and the proliferation of multi-national companies, joint ventures, strategic alliances and business partnerships, there were found to be significant success factors, following the earlier "Just-In-Time", "Lean Management" and "Agile Manufacturing" practices.^[3] Second, technological changes, particularly the dramatic fall in information communication costs, which are a paramount component of transaction costs, have led to changes in coordination among the members of the supply chain network (Coase, 1998).

Many researchers have recognized these kinds of supply network structures as a new organization form, using terms such as "Keiretsu", "Extended Enterprise", "Virtual Corporation", "Global Production Network", and "Next Generation Manufacturing System".^[4] In general, such a structure can be defined as "a group of semi-independent organizations, each with their capabilities, which collaborate in ever-changing constellations to serve one or more markets in order to achieve some business goal specific to that collaboration" (Akkermans, 2001).

Developments in Supply Chain Management

Six major movements can be observed in the evolution of supply chain management studies: Creation, Integration, and Globalization (Lavassani et al., 2008^a), Specialization Phases One and Two, and SCM 2.0.

1. Creation Era

The term supply chain management was first coined by an American industry consultant in the early 1980s. However the concept of supply chain in management, was of great importance long before in the early 20th century, especially by the creation of the assembly line. The characteristics of this era of supply chain management include the need for large scale changes, reengineering, downsizing driven by cost reduction programs, and widespread attention to the Japanese practice of management.

2. Integration Era

This era of supply chain management studies was highlighted with the development of Electronic Data Interchange (EDI) systems in the 1960s and developed through the 1990s by the introduction of Enterprise Resource Planning (ERP) systems. This era has continued to develop into the 21st century with the expansion of internet-based collaborative systems. This era of SC evolution is characterized by both increasing value-added and cost reduction through integration.

3. Globalization Era

The third movement of supply chain management development, globalization era, can be characterized by the attention towards global systems of supplier relations and the expansion of supply chain over national boundaries and into other continents. Although the use of global sources in the supply chain of organizations can be traced back to several decades ago (e.g. the oil industry), it was not until the late 1980s that a considerable number of organizations started to integrate global sources into their core business. This era is characterized by the globalization of supply chain management in organizations with the goal of increasing competitive advantage, creating more value-added, and reducing costs through global sourcing.

4. Specialization Era -- Phase One -- Outsourced Manufacturing and Distribution

In the 1990s industries began to focus on "core competencies" and adopted a specialization model. Companies abandoned vertical integration, sold off non-core operations, and outsourced those functions to other companies. This changed management requirements by extending the supply chain well beyond the four walls and distributing management across specialized supply chain partnerships.

This transition also refocused the fundamental perspectives of each respective organization. OEMs became brand owners that needed deep visibility into their supply base. They had to control the entire supply chain from above instead of from within. Contract manufacturers had to manage bills of material with different part numbering schemes from multiple OEMs and support customer requests for work -in-process visibility and vendor-managed inventory (VMI).

The specialization model creates manufacturing and distribution networks composed of multiple, individual supply chains specific to products, suppliers, and customers who work together to design, manufacture, distribute, market, sell, and service a product. The set of partners may change according to a given market, region, or channel, resulting in a proliferation of trading partner environments, each with its own unique characteristics and demands.

5. Specialization Era -- Phase Two -- Supply Chain Management as a Service

Specialization within the supply chain began in the 1980s with the inception of transportation brokerages, warehouse management, and non asset based carriers and has matured beyond transportation and logistics into aspects of supply planning, collaboration, execution and performance management.

At any given moment, market forces could demand changes within suppliers, logistics providers, locations, customers and any number of these specialized participants within supply chain networks. This variability has significant effect on the supply chain infrastructure, from the foundation layers of establishing and managing the electronic communication between the trading partners to the more-complex requirements, including the configuration of the processes and work flows that are essential to the management of the network itself.

Supply chain specialization enables companies to improve their overall competencies in the same way that outsourced manufacturing and distribution has done; it allows them to focus on their core competencies and assemble networks of best in class domain specific partners to contribute to the overall value chain itself thus increasing overall performance and efficiency. The ability to quickly obtain and deploy this domain specific supply chain expertise without developing and maintaining an entirely unique and complex competency in house is the leading reason why supply chain specialization is gaining popularity.

Outsourced technology hosting for supply chain solutions debuted in the late 1990s and has taken root in transportation and collaboration categories most dominantly. This has progressed from the Application Service Provider (ASP) model from approximately 1998 through 2003 to the On-Demand model from approximately 2003-2006 to the Software as a Service (SaaS) model we are currently focused on today.

6. Supply Chain Management 2.0 (SCM 2.0)

Building off of globalization and specialization, SCM 2.0 has been coined to describe both the changes within the supply chain itself as well as the evolution of the processes, methods and tools that manage it in this new "era".

Web 2.0 is defined as a trend in the use of the World Wide Web that is meant to increase creativity, information sharing, and collaboration among users. At its core, the common attribute that Web 2.0 brings is it helps us navigate the vast amount of information available on the web to find what we are looking for. It is the notion of a usable pathway. SCM 2.0 follows this notion into supply chain operations. It is the pathway to SCM results the combination of the processes, methodologies, tools and delivery options to guide companies to their results quickly as the complexity and speed of the supply chain increase due to the effects of global competition, rapid price commoditization, surging oil prices, short product life cycles, expanded specialization, near/far and off shoring, and talent scarcity.

SCM 2.0 leverages proven solutions designed to rapidly deliver results with the agility to quickly manage future change for continuous flexibility, value and success. This is delivered through competency networks composed of best of breed supply chain domain expertise to understand which elements, both operationally and organizationally, are the critical few that deliver the results as well as the intimate understanding of how to manage these elements to achieve desired results, finally the solutions are delivered in a variety of options as no-touch via business process outsourcing, mid-touch via managed services and software as a service (SaaS), or high touch in the traditional software deployment model.

Supply chain business process integration

Successful SCM requires a change from managing individual functions to integrating activities into key supply chain processes. An example scenario: the purchasing department places orders as requirements become appropriate. Marketing, responding to customer demand, communicates with several distributors and retailers as it attempts to satisfy this demand. Shared information between supply chain partners can only be fully leveraged through process integration.

Supply chain business process integration involves collaborative work between buyers and suppliers, joint product development, common systems and shared information. According to Lambert and Cooper (2000) operating an integrated supply chain requires continuous information flow. However, in many companies, management has reached the conclusion that optimizing the product flows cannot be accomplished without implementing a process approach to the business. The key supply chain processes stated by Lambert (2004) ^[5] are:

Customer relationship management
Customer service management
Demand management
Order fulfillment
Manufacturing flow management
Supplier relationship management
Product development and commercialization
Returns management

One could suggest other key critical supply business processes combining these processes stated by Lambert such as:

Customer service management
Procurement
Product development and commercialization
Manufacturing flow management/support
Physical distribution
Outsourcing/partnerships
Performance measurement

a) Customer service management process

Customer Relationship Management concerns the relationship between the organization and its customers. Customer service provides the source of customer information. It also provides the customer with real-time information on promising dates and product availability through interfaces with the company's production and distribution operations. Successful organizations use following steps to build customer relationships:

determine mutually satisfying goals between organization and customers
establish and maintain customer rapport
produce positive feelings in the organization and the customers

b) Procurement process

Strategic plans are developed with suppliers to support the manufacturing flow management process and development of new products. In firms where operations extend globally, sourcing should be managed on a global basis. The desired outcome is a win-win relationship, where both parties benefit, and reduction times in the design cycle and product development are achieved. Also, the purchasing function develops rapid communication systems, such as electronic data interchange (EDI) and Internet linkages to transfer possible requirements more rapidly. Activities related to obtaining products and materials from outside suppliers requires performing resource planning, supply sourcing, negotiation, order placement, inbound transportation, storage, handling and quality assurance, many of which include the responsibility to coordinate with suppliers in scheduling, supply continuity, hedging, and research into new sources or programmes.

c) Product development and commercialization

Here, customers and suppliers must be united into the product development process, thus to reduce time to market. As product life cycles shorten, the appropriate products must be developed and successfully launched in ever shorter time-schedules to remain competitive. According to Lambert and Cooper (2000), managers of the product development and commercialization process must:

coordinate with customer relationship management to identify customer-articulated needs;
select materials and suppliers in conjunction with procurement, and
develop production technology in manufacturing flow to manufacture and integrate into the best supply chain flow for the product/market combination.

d) Manufacturing flow management process

The manufacturing process is produced and supplies products to the distribution channels based on past forecasts. Manufacturing processes must be flexible to respond to market changes, and must accommodate mass customization. Orders are processes operating on a just-in-time (JIT) basis in minimum lot sizes. Also, changes in the manufacturing flow process lead to shorter cycle times, meaning improved responsiveness and efficiency of demand to customers. Activities related to planning, scheduling and supporting manufacturing operations, such as work-in-process storage, handling, transportation, and time phasing of components, inventory at manufacturing sites and maximum flexibility in the coordination of geographic and final assemblies postponement of physical distribution operations.

e) Physical distribution

This concerns movement of a finished product/service to customers. In physical distribution, the customer is the final destination of a marketing channel, and the availability of the product/service is a vital part of each channel participant's marketing effort. It is also through the physical distribution process that the time and space of customer service become an integral part of marketing, thus it links a marketing channel with its customers (e.g. links manufacturers, wholesalers, retailers).

f) Outsourcing/partnerships

This is not just outsourcing the procurement of materials and components, but also outsourcing of services that traditionally have been provided in-house. The logic of this trend is that the company will increasingly focus on those activities in the value chain where it has a distinctive advantage and everything else it will outsource. This movement has been particularly evident in logistics where the provision of transport, warehousing and inventory control is increasingly subcontracted to specialists or logistics partners. Also, to manage and control this network of partners and suppliers requires a blend of both central and local involvement. Hence, strategic decisions need to be taken centrally with the monitoring and control of supplier performance and day-to-day liaison with logistics partners being best managed at a local level.

g) Performance measurement

Experts found a strong relationship from the largest arcs of supplier and customer integration to market share and profitability. By taking advantage of supplier capabilities and emphasizing a long-term supply chain perspective in customer relationships can be both correlated with firm performance. As logistics competency becomes a more critical factor in creating and maintaining competitive advantage, logistics measurement becomes increasingly important because the difference between profitable and unprofitable operations becomes more narrow. A.T. Kearney Consultants (1985) noted that firms engaging in comprehensive performance measurement realized improvements in overall productivity. According to experts internal measures are generally collected and analyzed by the firm including

Cost
Customer Service
Productivity measures
Asset measurement, and
Quality.

External performance measurement is examined through customer perception measures and "best practice" benchmarking, and includes 1) customer perception measurement, and 2) best practice benchmarking. Components of Supply Chain Management are 1. Standardization 2. Postponement 3. Customization

Theories of Supply Chain Management

Currently there exists a gap in the literature available in the area of supply chain management studies, on providing theoretical support for explaining the existence and the boundaries of supply chain management. Few authors such as Halldorsson, et al. (2003), Ketchen and Hult (2006) and Lavassani, et al. (2008^b) had tried to provide theoretical foundations for different areas related to supply chain with employing organizational theories. These theories includes:

Resource-based view (RBV)
Transaction Cost Analysis (TCA)
Knowledge-based view (KBV)
Strategic Choice Theory (SCT)
Agency theory (AT)
Institutional theory (InT)
Systems Theory (ST)
Network Perspective (NP)

Components of Supply Chain Management Integration

The management components of SCM

The SCM components are the third element of the four-square circulation framework. The level of integration and management of a business process link is a function of the number and level, ranging from low to high, of components added to the link (Ellram and Cooper, 1990; Houlihan, 1985). Consequently, adding more management components or increasing the level of each component can increase the level of integration of the business process link. The literature on business process reengineering,^[6] buyer-supplier relationships,^[7] and SCM^[8]suggests various possible components that must receive managerial attention when managing supply relationships. Lambert and Cooper (2000) identified the following components which are:

Planning and control
Work structure
Organization structure
Product flow facility structure
Information flow facility structure
Management methods
Power and leadership structure
Risk and reward structure
Culture and attitude

However, a more careful examination of the existing literature^[9] will lead us to a more comprehensive structure of what should be the key critical supply chain components, the "branches" of the previous identified supply chain business processes, that is, what kind of relationship the components may have that are related with suppliers and customers accordingly. Bowersox and Closs states that the emphasis on cooperation represents the synergism leading to the highest level of joint achievement (Bowersox and Closs, 1996). A primary level channel participant is a business that is willing to participate in the inventory ownership responsibility or assume other aspects of financial risk, thus including primary level components (Bowersox and Closs, 1996). A secondary level participant (specialized), is a business that participates in channel relationships by performing essential services for primary participants, thus including secondary level components, which are in support of primary participants. Third level channel participants and components that will support the primary level channel participants, and which are the fundamental branches of the secondary level components, may also be included.

Consequently, Lambert and Cooper's framework of supply chain components does not lead us to the conclusion about what are the primary or secondary (specialized) level supply chain components (see Bowersox and Closs, 1996, p.g. 93). That is, what supply chain components should be viewed as primary or secondary, how these components should be structured in order to have a more comprehensive supply chain structure, and to examine the supply chain as an integrative one (See above sections 2.1 and 3.1).

Baziotopoulos reviewed the literature to identify supply chain components.^[10]^[11]^[12]^[13]^[14]^[15]^[16]^[17] Based on this study, Baziotopoulos (2004) suggests the following supply chain components:

For customer service management: Includes the primary level component of customer relationship management, and secondary level components such as benchmarking and order fulfillment.
For product development and commercialization: Includes the primary level component of Product Data Management (PDM), and secondary level components such as market share, customer satisfaction, profit margins, and returns to stakeholders.
For physical distribution, manufacturing support and procurement: Includes the primary level component of enterprise resource planning (ERP), with secondary level components such as warehouse management, material management, manufacturing planning, personnel management, and postponement (order management).
For performance measurement: Includes the primary level component of logistics performance measurement, which is correlated with the information flow facility structure within the organization. Secondary level components may include four types of measurement such as: variation, direction, decision and policy measurements. More specifically, in accordance with these secondary level components, total cost analysis (TCA), customer profitability analysis (CPA), and asset management could be concerned as well.
For outsourcing: Includes the primary level component of management methods, and the strategic objectives for particular initiatives in key areas of information technology, operations, manufacturing capabilities, and logistics (secondary level components).

Reverse Supply Chain Reverse Logistics is the process of planning, implementing and controlling the efficient, effective inbound flow and storage of secondary goods and related information opposite to the traditional supply chain direction for the purpose of recovering value or proper disposal. Reverse logistics is also referred to as "Aftermarket Customer Services". In other words, anytime money is taken from a company's Warranty Reserve or Service Logistics budget, that is a Reverse Logistics operation.

References

^ "Definition of Terms". A Management Consultant @ Large. Retrieved on 2008-02-27.
^ Baziotopoulos, 2004
^ MacDuffie and Helper, 1997; Monden, 1993; Womack and Jones, 1996; Gunasekaran, 1999
^ Drucker, 1998; Tapscott, 1996; Dilts, 1999
^ Lambert, Douglas M.Supply Chain Management: Processes, Partnerships, Performance, 3rd edition, 2008.
^ Macneil ,1975; Williamson, 1974; Hewitt, 1994
^ Stevens, 1989; Ellram and Cooper, 1993; Ellram and Cooper, 1990; Houlihan, 1985
^ Cooper et al., 1997; Lambert et al.,1996; Turnbull, 1990
^ Zhang and Dilts, 2004 ;Vickery et al., 2003; Hemila, 2002; Christopher, 1998; Joyce et al., 1997; Bowersox and Closs, 1996; Williamson, 1991; Courtright et al., 1989; Hofstede, 1978
^ Stevens, 1989
^ Ellram and Cooper, 1993
^ Mills et al., 2004
^ Lewis and Talalayevsky, 2004
^ Hedberg and Olhager, 2002
^ Hemila, 2002
^ Vickery et.al., 2003
^ Yusuf et al., 2003