or-project supply chain

7/31/2019 Or-Project Supply Chain

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Demand forecasting insupply chain

management

Prepared By:

1.Amith .M2.Chetan C.S3.Sanjay bagriya4.Yogeshkumar Joshi


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Introduction

Supply Chain Management (SCM) can be best described as the natural

extension of the downsizing (right-sizing) and re-engineering performed by

the organization(s) in the past. Downsizing and re-engineering transformed

the enterprises into lean and mean competitive units, by cost cutting and

process simplifications. These operations (of downsizing and re-engineering)

involved the optimization (in terms of the number of persons involved, the

time taken, the complexity of the work etc.) of business units (functional

and/or administrative domains) over which the organizations had full control.

These strategies did lead to increased productivity and profitability of the

organizations but as the benefits of these leveled off, it was realized that the

approach to the way organizations work needed to be changed. The above

changes were a by-product of the isolationist (closed system) world picture

of the enterprises involved in the full value chain; with organizations (the

system) trying to survive in an hostile environment; assuming that all other

participants in the value chain were adversaries with whom the organization

must compete, even though the operations performed by the separate

organizations may be supplementary in nature rather than complementary.

The realization that this world picture was an impediment to the growth of

organizations prompted the enterprises to start seeking strategic alliances

with other organizations. The formation of these alliances required a basis (a

common ground) which would be acceptable to each and every partner in thealliance. This common basis is/was supplied by the participation of the

organizations in the value chain (the demand-supply chain). The participants

in the chain, suppliers, sub-contract suppliers, in house product processes,

transportation, distribution, warehouses, and the end customer, generally,


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perform mutually exclusive tasks and thus do not compete directly with each

other.

Issues in SCM

A supply chain encompasses all the activities, functions and facilities

involved in producing and delivering a product and/or service, from suppliers

(and their suppliers) to the customers. The supply chain management (SCM)

paradigm is geared towards optimizing each component of what used to be

called (Production and) Operations management (production, warehousing,

inventory, transportation and distribution etc.) and the inter-links between

these components synergistically. In the 70s and the 80s, various models for

production and operations control and management were developed: Just-In-

Time (JIT) Inventory management model, Vendor Managed Inventory (VMI)

model, Zero Inventory (ZI) model, Total Quality Management (TQM) etc.

These models focused on the various components of the supply chain in

isolation, this implies that these models were oriented towards the

optimization of a sub-part of the system whereas the SCM paradigm aims at

the optimization of the full chain. This leads to trade-offs among the different

components of the supply chain. For example, JIT would require a factory to

keep inventories low and produce and distribute products in a timely manner,

however JIT ignores many other aspects which cannot be seen independently,

e.g. if the availability of the input materials is uncertain and irregular, the

factory may need to insure smooth and continuous production. Similarly,

regional stocking may permit reductions in transportation costs through

increased shipment consolidation, as well as expanded sales through better

delivery performance. These improvements may be accomplished with only

moderate increases in inventory and warehousing cost(s). However, in an


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environment where different functional units manage the various logistics

activities independently, an organization is less likely to properly analyze such

important trade-offs.

Fig. -1 : Interdependence of supply chain with other functional domains

in an enterprise.

Moreover, these models also ignore the interdependency of production

and operations functions with other domains within an organization, such as

marketing and finance. Marketing decisions have serious impact on logisticsfunction and vice-versa. For example, a marketing promotion campaign

should be coordinated with production planning, since a higher demand may

be expected. On the other hand, when raw materials are cheap, or when the

factory temporarily has an over-capacity, the marketing department may

decide to cut prices and/or start other promotion campaigns during these

periods to increase demands. Also, financial decisions are driven by

production and logistics decisions. Production of new products requires the

investment in raw materials and consumes other change-over costs. Financial

managers have to be aware of the increased demand for capital to finance the

production plan. Likewise, the delivery of finished products generates


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financial income, so the forecast demand can be used to calculate/forecast the

accounts payable and receivable in the future. The above description means

that production, finance and marketing decisions cannot be made

independently (fig.1). All these decisions are driven by the activities in the

supply chain of a manufacturing company. Fig.-1 shows a simple

representation of the interdependence of the supply chain and the other

functional domains in the organization. The links between the (other)

functional domains - marketing, sales, human resources etc. - are not shown.

The linkage between the supply chain components and the other functional

domains relies heavily on information sharing to have an effective impact.

One other major factor in the current scenario is the globalization of the

supply chain. With the fall of the East-European socialist bloc and the opening

of the Asian market, the trade barriers began falling in the 1980s and the 90s.

This lead to organizations having a supply chain that criss-crossed the globe.

The proliferation of trade agreements - EC, ASEAN, NAFTA, APEC, etc. - has

changed the global market. SCM now has become not only a problem oflogistics but also demands that supply chain management must look into the

ramifications of these agreements on the cost of transportation (including

tariffs or duties) of products within a trade zone and outside it[1].

Furthermore, organizations now acknowledge that efficient consumer

response (ECR) can lead to competitive edge. SCM is tantamount to

coordinating all the operations of an organization with the operations of the

suppliers and customers. Effective SCM strategies are essential for successful

implementation of ECR programmers. Thus, a production planning and

control model that focuses on all the aspects of the operations and

distribution activities and links with other functional domains such as finance


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and marketing is needed. The supply chain management model should also

perform the task of managing and coordinating activities upstream and

downstream in the supply chain. Of course, such a model in its entirety

becomes very complex and cannot be used without a sufficient computational

infrastructure.

Supply-Demand Nexus

To have an effective supply chain management framework;

organizations must have a clear understanding of the supply - demand nexus

and its implications for strategy and implementation. There is an

interdependent relationship between supply and demand; organizations need

to understand customer demand so that they can manage it, create future

demand and, of course, meet the level of desired customer satisfaction.

Demand defines the supply chain target, while supply side capabilities

support, shape and sustain demand.

When one considers how tangentially marketing and operations area of

an organization typically interact (in practice), it becomes obvious that

putting together the supply-demand can only occur in the context of overall

perspective. The wide gap between the supply and demand sides of an

organization can only be bridged by a comprehensive umbrella strategy. This

can be done by developing a holistic strategic framework that leverages the

generation and understanding of demand effectiveness with supply efficiency.

Such a framework provides a strategic anchor to prevent the supply and

demand components of a business from drifting apart.

The basis of such a holistic strategy framework is the integrated supply

and demand model (Fig.-2). The model is designed around two key principles.


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First, in the present scenario where vertically integrated supply chains (VISC)

are a rarity, if not non-existent; organizations must bring a multi-enterprise

view to their supply chains. They must be capable of working co-operatively

with other organizations in the chain rather than seeking to outdo them.

Secondly, they must recognize the distinct supply and demand processes that

must be integrated in order to gain the greatest value.

Fig. -2 : The Integrated Demand-Supply Model

Thus involving three key elements:

The core process of the supply and demand chains viewed from a broadcross-enterprise vantage point rather than as discrete function. To gain the

maximum benefits, organizations need to identify the core processes

across the demand and supply chain, as well as exploring the impact of

each of these processes on the different functions.


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Fig. -3 : Integrating processes in the supply and demand chains

The integrating processes that create the links between the supply anddemand chains (fig - 3). This implies that the planning processes (which

involves development of channel strategies, planning of manufacturing,

inventory, distribution and transportation, demand planning and

forecasting; and marketing and promotional planning) and service

processes (which includes functions such as credit, order management,

load planning, billing and collection, etc.) must be integrated. This

integration must be done across the boundaries of the enterprises. If each

participating organization in the chain formulates its own plans on the

basis of its own private information, then there is no way to integrate the

supply and demand chain processes that they share.


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The supporting information technology (IT) infrastructure that makes suchintegration possible. While information technology is needed to handle

routine transactions in an efficient manner, it can also play the a critical

role in facilitating the timely sharing of planning, production and

purchasing information; capturing and analyzing production, distribution

and sales data at new levels of detail and complexity. Information

technology provides an integrating tools that makes it possible to convert

data into meaningful pictures of business processes, markets and

consumers that are needed to feed company strategies in order to develop

competitive advantage.

On the administrative side, such elements as flow path economics, which

help organizations understand the real drivers of costs, and new performance

and measurement standards that align functions in accordance with total

process goals that are critical to achieving integration.


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SCM Framework

A framework to understand the various issues involved in SCM is provided

by the pyramid structure for the SCM paradigm The pyramid allows issues to

be analyzed on four levels:

Strategic: On the strategic, level it is important to know how SCM cancontribute to the enterprises basic value proposition to the customers.

Important questions that are addressed at this level include: What are the

basic and distinctive service needs of the customers? What can SCM do to

meet these needs? Can the SCM capabilities be used to provide unique

services to the customers? Etc.

Structural: After the strategic issues are dealt with, the next levelquestion(s) that should be asked are: Should the organization market

directly or should it use distributors or other intermediaries to reach the

customers? What should the SCM network look like? What products should

be sourced from which manufacturing locations? How many warehouses

should the company have and where should they be located? What is the

mission of each facility (full stocking, fast moving items only, cross-docking

etc.)? etc.

Functional: This is the level where operational details are decided upon.Functional excellence requires that the optimal operating practices for

transportation management, warehouse operations, and materials

management (which includes forecasting, inventory management,

production scheduling, and purchasing) are designed. These strategies

should keep in view the trade-offs that may need to be made for the overall

efficiency of the system. Achieving functional excellence also entails


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development of a process-oriented perspective on replenishment and

order fulfillment so that all activities involved in these functions can be

well integrated.

Implementation: Without successful implementation, the development ofSCM strategies and plans is meaningless. Of particular importance are the

organizational and information systems issues. Organizational issues

centers on the overall structure, individual roles and responsibilities, and

measurement systems needed to build an integrated operation.

Information systems are enablers for supply chain management

operations and therefore must be carefully designed to support the SCM

strategy. Supply chain managers must consider their information needs

relative to decision support tools, application softwares, data capture, and

the systems overall structure.

It is important to note that the decisions made within the SCM strategy

pyramid are interdependent. That is, it must be understood what capabilities

and limitations affect the functional and implementation decisions and

consider those factors while developing a supply chain management strategy

and structure.

The SCM models used in practice lie in a continuum between two extreme

models: on one end of the spectrum lies the vertically integrated supply chain

model in which the organization has direct control over each and every

component of the supply chain, while on the other end of the spectrum lies the

horizontally diversified supply chain model (ideally) in which the number of

participant is as large as the number of distinct parts of the supply chain. In a


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vertically integrated supply chain system, the organization can control every

component of the chain and can make various changes to the system to

optimize the chain very easily. But in a horizontally diversified supply chain

the tendency will be to optimize only the functions that the organization is

involved in, thus conscious efforts must be made by the various participants in

the supply chain for the integration of their respective components in the

supply chain. If an organization can be identified as the major/dominant

partner in the supply chain, then this organization has to take an initiative in

seeking the co-operation of the other participants in the supply chain.

The type and structure of the supply chain that is established depends on

many factors, some of the major factors are:

Geographical: If the supply chain is stretched across the globe then it maynot be possible to incorporate some of the principles of lean production

like JIT delivery, flexible manufacturing, and co-ordination among

suppliers and customers. It can lead to uncertain transportation schedules,

unpredictable lead time and may need larger inventory carriage.

Cultural:The difference in the culture of the participants in the chain(the difference can be due to geographical factors or corporate practices)

can lead to friction and distrust. This may hamper the development of close

ties.

Government Legislation: The laws of the country may prohibit thesharing of information about some facet of the supply chain and thus, may

lead to a restrictive participation by one or more participant in the supply

chain.


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Time: Just as among individuals, organizations require time before trustcan be built up. The first phase in any relationship is manifest as

confrontation that essentially means that participants in the chain try to

win at the cost of other participants. And, the last phase is exemplified by

total trust and working together of organizations. The information sharing

behavior in the first phase is almost zero, while in the integrated

relationship the information sharing is mutual and free about the common

concerns. In between the two phases lies a continuum of phases.


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Demand Forecasting

What is a demand forecast?

Demand forecasting is the activity of estimating the quantity of a

product or service that consumers will purchase. Demand forecasting involves

techniques including both informal methods, such as educated guesses, and

quantitative methods, such as the use of historical sales data or current data

from test markets. Demand forecasting may be used in

making pricing decisions, in assessing future capacity requirements, or in

making decisions on whether to enter a new market.

A demand forecast is the prediction of what will happen to your

company's existing product sales. It would be best to determine the demand

forecast using a multi-functional approach. The inputs from sales and

marketing, finance, and production should be considered. The final demand

forecast is the consensus of all participating managers. You may also want to

put up a Sales and Operations Planning group composed of representativesfrom the different departments that will be tasked to prepare the demand

forecast.

Determination of the demand forecasts is done through the following steps:

Determine the use of the forecast

Select the items to be forecast

Determine the time horizon of the forecast

Select the forecasting model(s)

Gather the data


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Make the forecast

Validate and implement results

Objectives of Demand Forecasting

1.Helping for continuous production

2.Regular supply of commodities

3.Formulation of price policy

4.Arrangement of finance

5.Labor requirement

Factors Involved In demand Forecasting

1.Time period

2.Levels of forecasting-- International level-- Macro level-- Industry level--

Firm level

3.Purpose - General or Specific

4.Methods Of Forecasting

5.Nature Of Commodity

6.Nature Of Competition

Need for Demand Forecasting

The significance of demand or sales forecasting in the context of

business policy decisions can hardly be overemphasized. Sales constitute the


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primary source of revenue for the corporate unit and reduction for sales gives

rise to most of the costs incurred by the firm.

Demand forecasting is essential for a firm because it must plan its

output to meet the forecasted demand according to the quantities demanded

and the time at which these are demanded. The forecasting demand helps a

firm to arrange for the supplies of the necessary inputs without any wastage

of materials and time and also helps a firm to diversify its output to stabilize

its income overtime.

The purpose of demand forecasting differs according to the type of

forecasting.

(1) The purpose of the Short term forecasting:

It is difficult to define short run for a firm because its duration may

differ according to the nature of the commodity. For a highly sophisticated

automatic plant 3 months time may be considered as short run, while for

another plant duration may extend to 6 months or one year. Time duration

may be set for demand forecasting depending upon how frequent the

fluctuations in demand are, short- term forecasting can be undertaken by

affirm for the following purpose;

Appropriate scheduling of production to avoid problems of over productionand under- production.

Proper management of inventories Evolving suitable price strategy to maintain consistent sales Formulating a suitable sales strategy in accordance with the changing

pattern of demand and extent of competition among the firms.


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Forecasting financial requirements for the short period.(2) The purpose of long- term forecasting:

The concept of demand forecasting is more relevant to the long-run that

the short-run. It is comparatively easy to forecast the immediate future than

to forecast the distant future. Fluctuations of a larger magnitude may take

place in the distant future. In fast developing economy the duration may go up

to 5 or 10 years, while in stagnant economy it may go up to 20 years. More

over the time duration also depends upon the nature of the product for which

demand forecasting is to be made. The purposes are;

Planning for a new project, expansion and modernization of an existing unit,diversification and technological up gradation.

Assessing long term financial needs. It takes time to raise financial resources. Arranging suitable manpower. It can help a firm to arrange for specialized

labour force and personnel.

Evolving a suitable strategy for changing pattern of consumption.

Challenges Faced in Demand Forecasting

A small retailer may not need and afford a full-fledged demand forecasting

analysis. However, with increasing number of bigger retailers entering the

market demand forecasting becomes feasible. Firms face a multitude of

challenges due to the following factors:

1. Scale of forecast (how many goods to include in the forecast?)2. sporadic demand (erratic sales for many items in the store)3. introduction of new goods


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4. changing prices and promotions

Large scale forecasting. A big retailer may have thousands of items per shop.

Since forecasting is an important yet expensive task, the retailer can not

forecast for all goods it sells. Though it is infeasible to manually forecast the

demand of all the products, it is possible to use automated tools to do so. In

most cases, quality forecasts can be obtained from the automated tool and the

expert analysts can be employed to forecast few of the most important

products. This reduces the burden from the humans but requires lot of

compute power available.

What to optimize. Total sale volumes, total revenue earned, total profits,

maximize margin are many different objectives that a firm may use and may

receive optimized goods in stock. Creditability of such optimization

decisions pivots on the ability to correctly predict the sales. This is usually

based on prior data about the same product or close substitutes. It may also

be based upon analysis done at another location with similar buyer patterns.

When to restock. Slow moving goods may be restocked leisurely compared

to fast moving goods. It is important for retailers to provide the customers the

specific goods that the customer asks of the retailer. Under stocking would

cause unsatisfied customers who may quickly move to other stores. Over

stacking may increase the money locked up in inventory. Hence, the retailer

should aim at a replenishment policy by which the rack never gets empty and

never overflows. When close substitutes are available for some products, the


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retailer may compensate for a lower current stock in one good with another

one.

JUDGEMENTAL

The main methods in these categories are as follows:

Unaided Judgement:

It is common practice to ask experts what will happen. This is a good

procedure to use when,

Experts are unbiased,

Large changes are unlikely,

Relationships are well understood by experts (e.g., demand goes up when

Prices go down),

Experts possess privileged information,

Experts receive accurate and well-summarized feedback about their

forecasts.

Delphi:

To forecast with Delphi the administrator should recruit between five

and twenty suitable experts and poll them for their forecasts and reasons. The

administrator then provides the experts with anonymous summary statisticson the forecasts, and experts reasons for their forecasts. The process is

repeated until there is little change in forecasts between rounds - two or three

rounds are usually sufficient. The Delphi forecast is the median or mode of the

experts final forecasts.


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Judgemental Decomposition:

The basic idea behind judgemental decomposition is to divide the

forecasting problem into parts that are easier to forecast than the whole. One

then forecasts the parts individually; using methods appropriate to each part.

Finally, the parts are combined to obtain a forecast.

Expert Systems:

As the name implies, expert systems are structured representations of

the rules experts use to make predictions or diagnoses. For example, if local

household incomes are in the bottom quartile, then do not supply premium

brands.

Expert systems forecasting involves identifying forecasting rules used

by experts and rules learned from empirical research.

Developing an expert system is expensive and so the method will only

be of interest in situations where many forecasts of a similar kind are

required. Expert systems are feasible where problems are sufficiently well-structured for rules to be identified.

Simulated interaction:

Simulated interaction is a form of role playing for predicting decisions

by people who are interacting with others. To use simulated interaction, an

administrator prepares a description of the target situation, describes the

main protagonists roles, and provides a list of possible decisions. Role players

adopt a role and read about the situation. They then improvise realistic

interactions with the other role players until they reach a decision; for


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example to sign a trial one-year exclusive distribution agreement. The role

players decisions are used to make the forecast.

Intentions and Expectations Survey:

With intentions surveys, people are asked how they intend to behave in

specified situations. In a similar manner, an expectations survey asks people

how they expect to behave.

To forecast demand using a survey of potential consumers, the

administrator should prepare an accurate and comprehensive description of

the product and conditions of sale. He should select a representative sample of

the population of interest and develop questions to elicit expectations from

respondents. Bias in responses should be assessed if possible and the data

adjusted accordingly. The behavior of the population is forecast by

aggregating the survey responses.

How is demand forecast determined?

There are two approaches to determine demand forecast (1) the

qualitative approach, (2) the quantitative approach. The comparison of these

two approaches is shown below:

Description Qualitative Approach Quantitative Approach

Applicability Used when situation is

vague & little data exist

(e.g., new products and

technologies)

Used when situation is

stable & historical data

exist

(e.g. existing products,


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current technology)

Considerations Involves intuition and

experience

Involves mathematical

techniques

Techniques Jury of executive opinion

Sales force composite

Delphi method

Consumer market survey

Time series models

Causal models

Qualitative Forecasting Methods

Your company may wish to try any of the qualitative forecasting

methods below if you do not have historical data on your products' sales.

Qualitative Method Description

Jury of executive

opinion

The opinions of a small group of high-level

managers are pooled and together they estimate

demand. The group uses their managerial

experience, and in some cases, combines the

results of statistical models.

Sales force

composite

Each salesperson (for example for a territorial

coverage) is asked to project their sales. Since

the salesperson is the one closest to the


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marketplace, he has the capacity to know what

the customer wants. These projections are then

combined at the municipal, provincial and

regional levels.

Delphimethod A panel of experts is identified where an expert

could be a decision maker, an ordinary

employee, or an industry expert. Each of them

will be asked individually for their estimate of

the demand. An iterative process is conducteduntil the experts have reached a consensus.

Consumer market

survey

The customers are asked about their purchasing

plans and their projected buying behavior. A

large number of respondents is needed here to

be able to generalize certain results.

Quantitative Forecasting Methods

There are two forecasting models here (1) the time series model and

(2) the causal model. A time series is a s et of evenly spaced numerical data

and is obtained by observing responses at regular time periods. In the time

series model, the forecast is based only on past values and assumes that

factors that influence the past, the present and the future sales of your

products will continue.

On the other hand, t he causal model uses a mathematical technique

known as the regression analysis that relates a dependent variable (for


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example, demand) to an independent variable (for example, price,

advertisement, etc.) in the form of a linear equation. The time series

forecasting methods are described below:

Time Series Forecasting

Method

Description

Nave

Approach

Assumes that demand in the nextperiod is the same as

demand in most recentperiod; demand pattern may

not always be that stable

For example:

If July sales were 50, then Augusts sales will also be

50

Time Series Forecasting

Method

Description

Moving

Averages (MA)

MA is a series of arithmetic means and is used if little

or no trend is present in the data; provides an overall

impression of data over time

A simple moving average uses average demand for a

fixed sequence of periods and is good for stable

demand with no pronounced behavioral patterns.

Equation:


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F 4 = [D 1 + D2 + D3] / 4

F forecast, D Demand, No. Period

A weighted moving average adjusts the movingaverage method to reflect fluctuations more closely by

assigning weights to the most recent data, meaning,

that the older data is usually less important. The

weights are based on intuition and lie between 0 and 1

for a total of 1.0

Equation:

WMA 4 = (W) (D3) + (W) (D2) + (W) (D1)

WMA Weighted moving average, W Weight, D

Demand, No. Period

Exponential

Smoothing

The exponential smoothing is an averaging method

that reacts more strongly to recent changes in demandby assigning a smoothing constant to the most recent

data more strongly; useful if recent changes in data are

the results of actual change (e.g., seasonal pattern)

instead of just random fluctuations

F t + 1 = a D t + (1 - a ) F t

Where

F t + 1 = the forecast for the next period

D t = actual demand in the present period


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F t = the previously determined forecast for the

present period

= a weighting factor referred to as the smoothing

constant

Time Series

Decomposition

The time series decomposition adjusts the

seasonality by multiplying the normal forecast by a

seasonal factor

Forecast Accuracy and Key Performance Indicators (KPIs)

In inventory control operations, demand forecasting is usually

performed for each stock item SKU stock keeping unit. Different metrics,

called KPIs (key performance indicators), can be used to ensure that

customer service remains at or above acceptable levels for each SKU. Common

KPIs include case fill and order fill.

To fulfill these objectives, its necessary to keep a certain level of safety

stock . However, holding excess safety stock can lead to higher inventory

costs, and furthermore, increases risk that some inventory will have to be

written off during the later stages of the product lifecycle.

If supply chain managers are interested in reducing safety stock, there

are several methods they can use, foremost of which is demand planning.

Increasing forecasting accuracy, then, is a primary goal in the supply chain.
http://skylergreene.hubpages.com/hub/Demand-and-Supply-Planning-Demand-Classification-and-Paretos-Lawhttp://skylergreene.hubpages.com/hub/Demand-and-Supply-Planning-Demand-Classification-and-Paretos-Law


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Forecast accuracy can be calculated using a formula called MAPE Mean

Absolute Percent Error. The equation is as follows:

Error % = |Actual Forecast|/Actual

(note that |x| means the absolute value of x)

The reason that absolute value bars are used in mean absolute percent error

is because for statistical reasons, magnitude of error is often more important

than the sign.

Forecast accuracy is a metric that is inversely related to MAPE (as MAPE

increases, FA decreases). The equation for forecast accuracy is:

FA = 100 MAPE

(expressed as a percentage)

SCM Disaster

Businesses now not only need to operate at a lower cost to compete, it

must also develop its own core competencies to distinguish itself from

competitors and stand out in the market. Supply chain management

plays an important role in successful running of any business. SCM

has allowed company to rethink their entire operation and restructure it so

that they can focus on its core competencies and outsource processes

that are not within the core competencies of the company.

But the opposite effect of the SCM also comes into the view at times.

There have been m a n y c a s e s i n t h e p a s t i n w h i c h t h e S C M

h a v e p r o v e d t o b e a r e a s o n f o r p o o r f i n a n c i a l performance of

the company.


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SCM Disaster at Nike

Nike Rebounds: How (and Why) Nike Recovered from Its

Supply Chain Disaster

Nike Inc.

Nike Inc. is a major publicly traded sportswear and equipment

supplier based in the United St ate s. Th e co mpa ny is

hea dqua rtered in Bea verton , Oregon, whic h is p a rt of the

Po rt l an d metropolitan area. It is the world's leading supplier

of athletic shoes and apparel and a major manufacturer of sports

equipment with revenue in excess of $18.6 billion USD in its fiscal year 2008

(ending May 31, 2008). As of 2008, it employed more than 30,000 people

worldwide. Nike an d Pr ec is io n Ca st pa rt s ar e

the only F ortune 500 c omp a nies hea dqua rtered in the s ta te

of Oregon, according to The Oregonian. The company was founded on

January 25, 1964 as Blue Ribbon Sports by Bil l Bower man and Philip

Knight, and officially became Nike, Inc. in 1978. The company takes its name

from Nike, the Greek goddess of victory equipment; the company operates

retail stores under the Nike town name. Nike sponsors many high profile

athletes and sports teams around the world , with the highly recognized

trademarks of "Just do it" and the Swoosh logo.

Nikes Supply Chain: Failure and Eventual Success

During the 1970s retailers would make their orders with Nike 9 months

in advance before their delivery date. The orders were then sent to Nikes

manufacturers all over the world. At the beginning this process worked well


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and allowed Nike to deliver its orders on time. However, during the 1980s and

1990s Nikes business grew dramatically and customers became more

demanding about style, comfort and variety leading Nikes forecasting,

manufacturing and distribution to become very complex.

In 1999, profits dropped by 50 percent due to supply chain factors. The

situation led to the adoption of Nikes supply chain project called NSC. The

project attempted to improve the failing forecasting and order activities in

Nike. However this didnt work well for Nike, so it acquired and implemented

i2 technologies demand forecasting system at a cost of $40 million. The

objectives of this project were to forecast over 1 million stock keeping units

(SKUs). Algorithms were used to generate Nikes forecasts for manufacturing.

However, later in 2000, the forecasts were found to be faulty, causing Nike to

over manufacture some products while struggling to meet the demand for

other products. It took Nike between 6 and 9 months to overcome its

manufacturing problems and more than 2 years to make up for its financial

loss.

After analyzing its i2Technologies, Nike learned that it needed a more

adequate training of users, more comprehensive testing for the application

and a more careful integration of the application with other information

systems. The review of the project found that there was too much reliance on

forecasts generated by algorithms without using any judgment to evaluate the

forecasts.

By 2004, Nike had an integrated and efficient supply chain with i2

technologies forecasting system, SAPs ERP system, and Siebels CRM systems.

Nike spent 6 years and $800 million on the project.


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Nikes 2001 Planning System Perplexity

The companys headquarters are located in Beaverton, Oregon

in the US. The company had a good supply chain management wherein the

company was in a practice of never manufacturing the products. Instead

the company used to outsource the manufacturing process directly to

the suppliers. These suppliers were known as the contractors.

Future program:

It was in the year 1975 when the Nike introduced the Future Program.Under this program the Nikes global operations were broadly divided into 5

geographic regions. This was aimed towards obtaining better operations and

effective systems. During this era, toward the end of the 1990s the supply

chain management seemed to be ineffective and inadequate. There

were problems like ineffective forecasting and managing the changing trends.

NSC Project:

Further in the year 2000 Nike launched the New Safe

Confinement (NSC) project. This project aimed at implementing its ERP,

Supply Chain, & CRM Software onto a single SAP Platform. This project

ultimately proved to be a big disaster for the Nikes operations.

The Failure:

I n the s p r ing of 2001, N ike b la med i2 Tec hnologies for a

ma ss iv e sa le s- an d- earnings shortfall. Nike posted a profit of only

$97 million that quarterat least $48 million below forecast. Nike said

the culprit was i2's demand-forecasting and supply-chain-management


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systems. The supply-chain software was supposed to reduce the

amount of rubber; canvas and other materials that Nike needed to

produce its shoes. It was also supposed to help make sure Nike built

more of the shoes customers wanted and fewer of the ones they didn't.

Instead, Nike was left with far too many of the wrong shoes and not nearly

enough pairs of its hottest sellers.

The Reason:

The total cost of i2's demand-forecasting and supply-chain-management

software was only about $40 million. The other $360 million was

spent over five yearson customer-relationship and enterprise-planning

software from SAP. This whole project aiming at effective forecasting proved

to be a big SCM failure for the company. This meant huge financial losses

for the company. The reasons for the i2s software implementation were

finally designated over the following reasons:

1. Third party integrator2. Inexperience of i23. Customization4. Trying to forecast too far out ahead5. Pilot test6. Lack of training,7. Inadequate information8. Problems in smooth integration9. Changing market conditions10. Complication of NSC project11. Review meetings


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The Result:

This res ulted in huge p rof i t los s for the c omp a ny.

It ef fec te d th e co mpa ny reputation a lot. Massive sales

and earnings shortfall were observed. Nike was left with far too many

of the wrong shoes and not nearly enough pairs of its hottest sellers. Thus

company understood the importance of the SCM and forecasting. Forecasting

for the Nike was extremely important. It was important for them to

determine the quantities. An important feature that the company

understood regarding its SCM was that it needed to lay attention on the make

to order rather than the make to stock policy. Company also understood

that in a type of business that the company is in, forecasting plays an

important role in reducing the supply time. For all this to obtain it was

important for the company to obtain the best forecasting. Nike further

improved its supply chain management by installing well equipped and

competent system. Its continuous interaction with the consumers on

the web portal proved to be the best feature. Herein the consumers

achieve the supreme level of customization of the products. Nike also

improved itself by proper analysis of the data and implementation. Feedback

as in any other industry plays an important role in Nike today. Nike

obtains continuous feedback from the suppliers and the consumers.


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Conclusion:

Hence supply chain management for any company plays an important

role in successful running of a company. The reverse effect of the SCM

can also be experienced if the implementation of the SCM processes is

not done in the best way. Implementation is a complex procedure and

it must be tackled in the best way. Evaluating pros and c ons of any

project beforehand is also equally important. A pilot project can

be turn around the fate of any business if handled correctly

Bibliography

Nike Report:- http://www.scdigest.com/assets/reps/SCDigest_Top-11-SupplyChainDisasters.pdf

or-project supply chain

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