Study of IT Reinforced Supply Chain Management Model

8/11/2019 Study of IT Reinforced Supply Chain Management Model

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PROJE T REPORT

For

Study of IT Reinforced Supply Chain Management Model

Of

ABC Corporation


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INDEX

TITLE PAGE NO.

INTRODUCTION TO SUPPLY CHAIN MANAGEMENT 4

Supply Chain and Bullwhip Effect 5

Push versus Pull- Based Supply Chain Models 6

INTRODUCTION OF THE COMPANY 7

COMPANYS SCM MODEL 9

KANBAN STRATEGY 10

PROBLEMS PRIOR TO IT IMPLEMENTATION 12

IT IMPLEMENTATION 13

Product portfolio Management 13

Supplier Management1 14

Demand Management 16

SOFTWARE IMPLEMENTATION CHALLENGES 21

ANALYSIS 22

SUGGESTIONS 23

REFERENCES 24


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Introduction to Supply Chain Management

Supply chain management(SCM) is the management of an interconnected or interlinked

between network, channel and node businesses involved in the provision

of product and service packages required by the end customers in a supply chain. Supply

chain management spans the movement and storage of raw materials, work-in-process

inventory, and finished goods from point of origin to point of consumption. It is also defined

as the "design, planning, execution, control, and monitoring of supply chain activities with

the objective of creating net value, building a competitive infrastructure, leveraging

worldwide logistics, synchronizing supply with demand and measuring performance

globally."

SCM draws heavily from the areas of operations management, logistics, procurement,

and information technology, and strives for an integrated approach.

Supply Chain Model

Supply Chain Management addresses the following areas:

Distribution network configuration

Distribution strategy

Trade-offs in logistical activities

Information

Inventory management

Cash flow

Supply chain execution means managing and coordinating the movement of materials,

information and funds across the supply chain. The flow is bi-directional. SCM applications


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provide real-time analytical systems that manage the flow of products and information

throughout the supply chain network.

Supply Chain and Bullwhip Effect

The bullwhip effect(or whiplash effect) is an observed phenomenon in forecast-

driven distribution channels. It refers to a trend of larger and larger swings in inventory in

response to changes in demand, as one looks at firms further back in the supply chain for a

product. The concept is also known as the Forrester effect. Since the oscillating demand

magnification upstream of a supply chain is reminiscent of a cracking whip, it became known

as the bullwhip effect.

Causes of Bullwhip Effect:

Because customer demand is rarely perfectly stable, businesses must forecast demand to

properly position inventory and other resources. Forecasts are based on statistics, and they are

rarely perfectly accurate. Because forecast errors are a given, companies often carry

an inventory buffer called "safety stock".

Moving up the supply chain from end-consumer to raw materials supplier, each supply chain

participant has greater observed variation in demand and thus greater need for safety stock. In

periods of rising demand, down-stream participants increase orders. In periods of falling

demand, orders fall or stop, thereby not reducing inventory. The effect is that variations are

amplified as one move upstream in the supply chain (further from the customer).


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Push- Versus Pull-Based Supply Chain Models

Push Supply Chain:

Under Push model, products are manufactured or procured based on anticipated customer

orders (speculative). This model is also known as Built to Inventory or Built to Stock. The

name itself reveals its functionality. Products are manufactured in anticipation of customer

needs. Some of the key challenges and characteristics could include:

1. High inventory costs

2. Challenging working capital requirements due to low inventory turns

3. Huge warehousing and distribution costs

4. Inability to meet dynamic market conditions

5. Seasonal demand and off the shelf product

Push programs represent a top down approach. The core assumption of push programs is that

demand can be anticipated and that it is more efficient and reliable to mobilize resources in

pre-specified ways to serve this demand.

Pull Supply Chain:

Under pull supply chain, products are manufactured or procured based on specific customer

requests. We also know it as Built to Order or Configured to Order model. The objective

of this model is to minimize the Inventory carrying and optimize supply. Pull model is as a

response to growing uncertainty in demand and short product cycle. Some of the

characteristics of this model include:

1. Volatile demand situation

2. High rate of Customization

3. Minimal Inventory Carrying

4. No off the shelf product

5. Highly dynamic and effective distribution network

Push- Versus Pull-Based Supply Chain Models


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Introduction of the Company

ABC Corporationis an American multinational conglomerate company with 50 billion

turnovers that produces a variety of commercial and consumer products, engineering

services, and aerospace systems for a wide variety of customers, from private consumers to

major corporations and governments.

The company focuses on 4 verticals:

Aerospace

Transportation Systems

Automation and Control Solutions

Specialty Management-Performance Materials and Technologies

Aerospace:

Aerospace mechanical and electrical product offerings are used today on virtually every

commercial and defense related aircraft platform. The division invents and integrates

thousands of products and services that deliver safe, efficient, productive and comfortable

experiences worldwide.

Transportation Systems:

Transportation Systems provides world-class technologies and solutions to automakers, their

suppliers and consumers. This division enhances the performance and efficiency of passenger

and commercial vehicles worldwide.

Automation and Control Solutions:

ACS incorporates environmental controls, life safety, security, sensing, scanning, and

mobility products, as well as building and process solutions, are at work in homes, buildings,

industrial facilities, and public and private utilities around the world

Performance Materials and Technologies:

ABC Corporation is a global leader in developing and manufacturing high-purity, high-

quality performance chemicals and materials. This division manufactures materials which

reduce emissions, stop bullets, enable the production of cleaner, more efficient fuels, increase

capacity in oil refineries, speed drug discovery and protect medicines.


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We are focusing on Automation and Control Solutions.

Automation and Control Solutions (ACS) is a $12.5 billion strategic business group applying

sensing and control expertise that helps create safer, more comfortable, more secure, and

more productive environments. ACS provides customers controls for heating, ventilating, and

air conditioning, security systems, fire alarm systems, and energy management solutions.

From thermostats to large commercial building management systems, ABC Corporation ACS

is a global leader.


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Companys SCM Model

ABC Corporation classifies product on the basis of demand as follows:

1.

Products with stable Demand.

2.

Products with variable demand

Products with Stable demand are defined as products which have low variance whereas the

ones with high variance are taken as the products with variable demand.

The company does this classification so that it can implement the appropriate forecasting

techniques to its Supply Chain Models.

The company uses two Supply Chain Models:

1.

Push Model

2. Pull Model

Each Model is used to forecast different kinds of products, as described below.

In Push Model, supply of product is based on Anticipation of demand by the company. In this

model company uses various techniques to forecast the demand of products for which

variance is high.

In Pull Model, supply of product is based on Consumer Demand. The strategy used in Pull

Model is KANBAN, which would be explained later.


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KANBAN Strategy

ABC Corporation has a strategy to implement their Pull model of SCM. It is calledKANBAN

As we know Pull Model works on anticipation of demands from consumer, KANBAN is astrategy which anticipates demand through various trigger points and fulfills it throughappropriate channels.

KANBAN is Japanese word literally meaning signboard or billboard is a scheduling systemfor lean and just-in-time (JIT) production. Kanban is a system to control the logistical chainfrom a production point of view, and is not an inventory control system. Kanban wasdeveloped by Taiichi Ohno, at Toyota, to find a system to improve and maintain a high levelof production. Kanban is one method through which JIT is achieved.

In the initial days, as shown in the above figure, when the inventory levels went down acertain level or below red zone the consumer would deliver a Kanban card to manufacturermanually to intimate him about the requirement. This would obviously consume a lot oftime.

Prior to IT implementation, KANBAN was implemented by mechanical systems, which werelaser guided systems, which would generate a trigger when the inventory levels went down acertain limit. And then the inventory would be updated manually by the concerned person in

books or stand alone systems. This meant problems in integrating.

After IT implementation

After implementation of Oracle all processes were automated. The system checks theinventory levels and an automatic order is the generated, very much similar to the cardsearlier.This ensures:


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Real time inventory levels to be updated in the system, which means no problem inintegrating the data.

Generating orders as and when required, without any delays like in the older dayswhen the cards were delivered manually.

Turnaround time has decreased to a great extent.


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Problems prior to IT Implementation

Some of the problems that arise when portfolio management is lacking are:

Portfolio has a poor balance in product types.

Resource breakdown does not reflect the product innovation strategy

A poor job is done in ranking and prioritizing products

There is a poor balance between the number of products underway and the resources

available

Products are not aligned with the business strategy

As a result too many companies have:

Too many products underway (often the wrong ones)Resources are spread too thin and across too many products

Products are taking too long to get to market, and

The pipeline has too many low value products

Portfolio Management is about choosing the right products. If right products are picked, the

result is an enviable portfolio of high value products: a portfolio that is properly balanced and

most importantly, supports business strategy.


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IT Implementation

I. Product Portfolio Management

Product portfolio management helps in making better resource allocation, marketing activity,

and product strategy decisions by providing an overall picture (both current and projected) of

the market positions (both absolute and relative) of all products.

Regular and rigorous portfolio management leads to:

Maximize the value of products: Different products contribute to companys bottom line

differently. Product portfolio that is structured to contribute as much as it can and continue

for several years down the road.

Identify the optimal product mix: A portfolio that spans multiple market segments,

product categories, and technologies helps to protect company against marketplace changes.

Investing the returns from current products into longer-term products helps to stabilize

companys returns over time. Established, low-risk products help offset riskier ones.

Ensure internal strategic alignment: Companys success is in jeopardy if product

portfolio fails to support broader business strategies, priorities and objectives; both today and

in the immediate future.

Allocate resources properly: Companies have limited human and financial resources.

Investing in the right products has an immediate and significant impact on profitability.

Through Portfolio Management the organization synchronizes all the organizations involved

in product development. It allows the organization to recognize the profitable products and

accelerate their introduction.

Portfolio Management lets you automatically update the activity status on the project plan

for all cross-functional team members, dramatically reducing prototype errors, tooling

changes, erroneous shipments, and validation problems.

Lifecycle Analytics in Portfolio Management

Lifecycle Analytics delivers visibility into product changes that helps companies to closely

measure, monitor and accelerate justified product changes resulting in quicker turnarounds

and improved time to market. At the same time, companies can also monitor the reasons for

un-warranted and preventable changes to minimize costly re-work.


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Lifecycle Analytics helps establish the most effective priorities by providing insight into vital

product issues impacting key customers and markets, helping companies respond fastest to

the most important problems.

II. Supplier Management

Oracle Supplier Portal makes the Company and the suppliers more efficient with a

powerful platform for online collaboration. Oracle iSupplier Portal removes barriers to

collaboration because suppliers need nothing more than a web browser to get onboard.

Suppliers can access the latest information that includes:

Purchase orders (POs)

Delivery information

Payment status

The two-way collaboration enables suppliers to:

Submit change requests

Process ship notices

Review payments

Update profile data

Submit work confirmations

Use purchase order details to create online invoices.

Hence they get,

Better service

lower processing costs

Easily Manage Order Changes

Oracle iSupplier Portal manages supplier-initiated change requests, so you and your

suppliers are always on the same page. Suppliers request PO changes online, from

splitting a shipment to modifying order details such as quantity, delivery date andsupplier part number. By establishing specific tolerances, the purchasing team can

enable some requests to be approved automatically or they can opt to divert the change

request to the original requester rather than burdening a buyer.

Approved changes propagate to the purchasing document, creating formal and auditable

revisions. With iSupplier Portal, both buyer and seller have immediate access to all of

the information they need to manage and track change.


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Accelerate Receiving with Advance Shipment Notices

Through the user friendly iSupplier Portal web interface, suppliers can enter Advance

Shipment Notices (ASNs) online to make sure that the Organization is prepared to

receive shipments. When the shipments arrive at your company, you can quickly and

accurately receive using information from the ASN.

Better Management of Contracts for Services with Complex Payment

Terms

iSupplier Portal allows suppliers to review and execute against complex payment

arrangements that may include milestone payments, progress payments, advances, retain age

and recoupment. Suppliers can review contractual deliverables for the project and their

associated progress payments. They are able to create work confirmations in order to trigger

the payment authorization process.

Vendor Managed Inventory and Consignment Support

Oracle iSupplier Portal reduces inventory cost through Vendor Managed Inventory (VMI)

processes that let authorized suppliers manage inventory for the organization. By accessing

the organizations forecasts, on-hand stocks and in-process shipments, suppliers can initiate

replenishments on the organizations behalf.

The software also makes consignment relationships easy for the organization and its suppliers

by providing visibility into consigned inventory and any transactions that affect it, from

procurement to payment. Oracle iSupplier Portal data also improves the accuracy of the

companys planning and scheduling, further reducing inventory levels while avoiding stock-

outs.

Supplier Hierarchy Management

A crucial part of supply base analysis is to understand the relationships that exist between the

different suppliers that are doing business with different parts of the buying organization.

This allows an organization to leverage aggregated spend information within the negotiationprocess with the supplier.

In addition to the basic parent /child relationship, the Hub allows business users to define an

unlimited number of custom supplier relationship types and then use these to track relations

between different suppliers. The custom hierarchy information can be viewed in a tree

structure and can be utilized for various reporting and supplier management purposes.


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III. Demand Management

Forecasting

As shown below, the forecast creation process at ABC Corp. begins with whateverinformation is available to the systemorders, point-of-sale data, and shipments. From there,

a demand history is maintained on a perpetual basis. Some adjustments are performed, based

on market and customer intelligence.

The forecasting uses following statistical forecasting tools for making adjustments in the

Push Model:

1. Simple average method: A simple average of demands occurring in all previous time

periods is taken as the demand forecast for the next time period in this method.

2. Simple moving average method: Demands from most recent periods is used to

forecast demand for the next time period. The number of past periods to be used in

calculations is selected in the beginning and is kept constant .Mostly it is kept

constant to 3 i.e. 3-period moving average.

3. Weighted moving average method: Weights assigned are unequal to the past

demand data. In this method while calculating simple moving average as the demand

forecast for next time period. Usually most recent data is assigned the highest weight

factor.

4. Exponential smoothing method: Weights are assigned in exponential order which

leads to better results. The weights decrease exponentially from most recent demand

data to older demand data.


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5. Regression analysis method: Past demand data is used as a reference for establishing

a functional relationship between two variables. One variable is either known or

assumed to be known and it is then used to forecast the value of other unknown

variable which is usually demand.

Error in Forecasting

The numeric difference in the forecasted demand and actual demand are termed as Errors.

Technique is being used by the system to remove the errors is Mean Absolute Deviation.

Mean Absolute Deviation (MAD): It may be noted that MAD expresses the magnitude but

not the direction of the error.

IT Implementation

Oracle Demand Management senses demand from multiple data sources including point of

sales and syndicated data, and analyzes demand data at various levels to understand the

detailed behavior of demand. Such detailed understanding of origin and relative contribution

of various demands both improves the ability to predict the detailed behavior of the demand

and enables demand shaping activitiesprograms and events designed to stimulate sales and

grow market share for individual products or groups of products.

All of the data used for analysis in Demand Management can be shared with the rest of the

organization in self-service dashboards. Oracle Advanced Planning Command Center enables

comparison of key performance metrics for your business strategies and alternatives asrepresented in your strategic and tactical plans.

Oracle Demantra Demand Management along with Bayesian analytical forecast engine

generates the most accurate forecasts as far as possible.

Automated algorithms automatically combine industry-standards and proprietary forecasting

models, mixed in an infinite number of combinations to handle a wide range of product life

cycles and demand patterns including intermittent demand. This produces a forecast that

accommodates seasonality, promotions, and trends. Self-learning and self-adapting

algorithms combine the different models to maximize predictive accuracy and to respond to

changing market conditions.

In Push Based System:

Forecasting of Spare Parts

The company has implemented Oracle Demand Managements. It supports powerful

forecasting techniques and models to improve forecasting of spare parts for Service

Operations. Many types of forecasting is used in it like population and failure rate based

forecasting, usage based forecasting, and chain history of multiple revisions, compositeforecasting, forecasting based on unique parts characteristics, returns forecasting, and


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forecasting based on causal factors which improve spare forecast accuracy. Methods used for

improving the accuracy include moving average, single exponential smoothing, seasonal

causal regression and regression with seasonal causal for intermittent, Monte Carlo regression

with seasonal causal for intermittent demand. There is a option to select expert mode to

automatically select the best blended statistical method for every service parts, especiallyuseful when scaling to handle large volumes of parts.

Integration with Oracle Demand Signal Repository to leverage Point of Sales data

The module includes a Demand Signal Repository which enables the system to receive data

directly from the point of sale which enables a real-time demand sensing paradigm that

captures demand signals closer to the point of consumption.

High Degree of Automation

Tools included in the module like alerts, flexible worksheets, color coding to highlight areas

of interest enable a high degree of automation of the evaluation of demand data with tools.

These facilities enabled the management by exception driven process which led to efficient

and effective monitoring and responding to customers in less time.

Flexibility

Demantra Demand Management serves as the central system for automating all demand-

driven business processes by providing personalized dashboards with tasks, alerts, and KPIs;

configurable spreadsheet-like user-specific worksheets with tables and graphs; and fully

configurable, role-based workflows to automate collaboration and the resolution and

escalation of problemsBusiness rules are well documented and thus can be configured to enable users to spot trends,

identify forecast variances, and respond to other demand stream changes easily and

efficiently.

Demand Management enables to bring in, and distinctively maintain, demand data from

multiple ERP source and legacy systems. Different regional or business line users

individually or as a group can selectively access the data specific to their region, business

line, or responsibility. The users do not require to be connected to the Internet continuously

and can work off-line as needed.

Promotions and New ProductNew products can be added and their demand forecast is based on the sales history and

characteristics of like products. New products can be introduced in selective channels and

locations first and then expanded globally in phased manner. You can manage the

introduction and lifecycle of new products, as well as the end of life and associated

cannibalization of superseded products. Oracle Advanced Forecasting and Demand

Modeling, an option to Oracle Demand Management, can extend the functionality to

statistically model the forecast shape of new product introductions.

Oracle Advanced Forecasting and Demand Modeling can also extend the demand shaping

functionality to promotions planning and enhanced causal factors and attribute-basedanalysis.


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Performance Management

Wide variety of key performance indicators (KPIs) are being calculated in this Demand

Management System that highlight the true effectiveness and efficiency of all planning

process in place as well as their results. These KPIs include statistical measures of forecastaccuracy such as mean absolute deviation (MAD), mean and absolute percentage error

(MAPE), and weighted MAPE. Tracking signals and measures of forecast bias are also

calculated and combined with extensive reports and exception alerts to show you areas for

improvement and to let you track the benefits of continuous improvement programs.

In Pull Based System:

The company to move towards a pull-based Supply Chain used Oracle modules which

enabled the company to accommodate, manufacture and distribution with valid customer

demand. Effective information flow about customer demand minimizes inventories which in

turn reduces the Bullwhip effect. Pull system allows lead time diminution due to better

anticipation and diminishing in variability and as a result the efficiency increases and Just-in

Time is also achieved.

Thus, benefits of pull based system if summarized improve the ability to manage and allocate

resources, reduce the inventory the company needs to maintain and reduces system costs

compared to similar push system. Considering the cons of pull based system we find that is

complicated to implement specifically in the cases where lead times are long making reaction

to demand information impracticable. Making an economic benefit is more complicatedwhile following a pull-based system in manufacturing and transportation since they are not

designed far ahead in time. The modules used include:

Demantra Advanced Forecasting and Demand Modeling

Analysis of complex demand patterns are automated by using Demantra, the advanced

forecasting and Modeling. In Demantra unlimited numbers of demand shaping scenarios are

simulated and by using the power of advanced analytics more accurate demand forecasting is

achieved. With better insights to the true drivers of demand, organization is equipped to

better sense and shape demand.

Some of its important functionalities include:

Demand Sensingimproved by built-in-analytics

Data architecture of this module is common, flexible and multidimensional and is shared to

provide slice and dice analytic capabilities along any dimension and level of granularity.

Data is organized in all departments according to hierarchies. The organization is such

that every department is capable of viewing their up to date plans and generate their

own preferred views while they are sharing the same granular base data.


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Demantra enables dynamically reading and editing data with changes automatically

split and rolled up or down appropriatelyknown as live read-write capability, this

facility is not supported by conventional business intelligence tools that only allow

viewing data and no further editing is allowed.

The unique middle-out capability is specially incorporated for planners so that theyare capable of making plan changes at the appropriate level of the hierarchy and then

automatically applying those changes up and down the entire hierarchy.

Analyze Demand Shaping Activities

Providing customers with Price reductions, investing in promotions, sales incentives,

additional services and advertising etc. are various demand shaping activities. These activities

have both effects that we want to occur from these Demand shaping activities, such as

increased sales, and the effects that are topsy-turvy of what is expected to occur, such as

cannibalization. Advanced Forecasting and Demand Modeling analyses these demandshaping activities using a powerful analytic engine.

It enables supply chain and distribution planners to better align supply plans with promotions

for both the promoted items and other items that might be cannibalized or see sales increases.

Shape Forecasts for new Products

The new product launch was one of the most risk prone areas for the company as it had no

prior historical data on which the results could be placed. The new product production

introduction functionality in Demand Management enabled the company to statistically

estimate shape of the new product introduction curve which based product launch rate and onprior learning. Shape modeling and attribute-based forecasting enabled a more accurate new

product history to be created and used as the basis for a phase-in and phase-out forecast.


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Software Implementation Challenges

Scope of the ProjectDefining the scope of the project was a big task.

Training the staffTraining the staff was in itself was a challenge. The company was earlier using Polarissystem which had only billing and inventory modules therefore moving over to Oracles

Solutions required the company to train its business users to :

Understand new modules example forecasting techniques used by the system and howit can be leveraged.

Recognizing which business processes and understanding how they can align the

business process with the package provided by the Oracle for example implementingKanban strategy using Oracle i.e. a shift from cards to Automatic order processing.

This took lot of time, effort and which increased the cost.

Data Integration and Cleansing

As mentioned above, the company was earlier using Polariss inventory and billing module,

implementing new package meant new designs and processes. This led to new data set being

created. Integrating data from Polaris and the new system was a great challenge. In some

cases data had to be converted or cleansed in order to be used with the new system.

Solution Validation/Gap analysis

Since Oracles SCM module is a large package, including forecasting, inventory, supplier

management; and the company has large operations, a lot of time was devoted to test if the

intended workflow has been achieved or not.

Gestation Period

The transition from an earlier implemented system to new system often takes time, which

increased the gestation period of the new system. This means that the system availability is

delayed. Company had to constantly keep check on the project timelines to avoid delay in

gestation period or in other words to avoid delay in return on investments.


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Analysis

The organization has a flat structure and follows a open door policy for its employees which

lead to people in the organization communicating openly with each other as well as the

management. Open forums were set up which discussed the threats and expectations of theemployees at regular intervals. The people were cleared about the impact IT implementation

will have on their working style and thus were prepared beforehand mentally. The threats

were also acknowledged by the management and were evaluated and done away with through

personal meetings. The open and flat culture makes politics and grapevine communication

work positively for the organization. Moreover, ABC Corporation is a mature company so

the business processes it had to implement through IT were mature enough and were

documented so it was not that difficult to understand those.

The management had to undergo a lot many challenges before implementing supply chain IT

solution. From making the plans and making them accept throughout the organization it

required a lot of efforts, time and energy. The Management accessed different available

options to implement this simultaneously accessing the pros and cons of the approach of

implementation. The management had to decide which packages of the SCM solution to

implement and what percentage of resources were to be allotted to each one of them.

The company already had a separate and efficient IT department which sailed the company

well through tough times of implementing the IT based solutions. Considering the hardware,

the company was a well to do company and had much of the required software along with the

budgets to meet new ones. The company implemented a packaged software solution from avendor which provided ample support to the company. Moreover, the company had a already

well established and well maintained network at its suppliers and distributors side making it

easy to work through the networking aspect of the implementation. Although, for data

management the company had to invest in short run data mart building into data warehouses

in the long run.


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Suggestions

Requirement for Unified Solution

The Portfolio management system which helps in classifying products such as high revenue

products from the rest of the products is not integrated with Demand Management system

which is responsible for Forecasting of products. They work independently with manual

interventions. It is suggested to integrate the data flow from Portfolio management unit to

Demand management unit so that they work in tandem and to have singular view of data.

Need for automation

Qual i ty Checks

Many of the products sourced are third party certified which have appropriate holograms and

marks in place. Instead of checking each and every product manually, the company can have

a optical scanner or a hologram reader which automate the processes to quite an extent and

avoid manual intervention every time.

Investing in Mobile Supply Chain Applications

Using hand held radio frequency (RF) devices, PDAs, and lift truck mounted RF scanners,

and other mobile devices will result in improved data accuracy and increased mobility and

convenience thereby streamlining movement and reducing human errors. It will also help in

reducing latency as transaction validation takes place online, identifying invalid data

immediately and providing real time inventory information.

Moving to Cloud Services

Company should plan to move to its Supply Chain Management to Cloud. Moving to Cloud

would provide the company whole lots of benefits:

1. Reduce Infrastructure costs

2. Reduce Maintenance and Up gradation costs.

3. Provide Mobility, as the services are on cloud, it can be accessed through any mobile

device.

4. No hassles of integration

One example of such service providing company would be JDA Cloud Services.


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REFERENCES

http://www.oracle.com

http://www.ascinstitute.com Management Information System, Kenneth C. Laudon and Jane P. Laudon

Study of IT Reinforced Supply Chain Management Model

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