A DESIGN FOR BUSINESS INTELLIGENCE SERVICE IN

DEMAND DRIVEN SUPPLY CHAIN MANAGEMENT

T. He

†

, P. Ribbins

†

, and R. Brown

†

†Orchestr8 Ltd., United Kingdom

L. Sun

‡

and C. Gurr

‡

‡School of Systems Engineering, University of Reading, United Kingdom

Keywords: Demand driven supply network, business intelligence services, metrics reporting service, and supply chain

management processes.

Abstract: This paper discusses the problems inherent within traditional supply chain management’s forecast and

inventory management processes arising when tackling demand driven supply chain. A demand driven

supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its

advantages over traditional supply chain management. Within this architecture, a metrics reporting system is

supply activities over supply chain health.

1 INTRODUCTION

Supply chain management has been evolving since

the 1980s through various stages, such as cost

realignment, business process reengineering, and

vertical integration in the value chain. Recently there

has been an increasing concern regarding an

emergence of demand-driven supply chain

management methodology. Traditional supply chain

management improvement approaches in the

manufacturing industry are based mostly on

improving capacity and internal efficiency and

attempting to increase forecasting accuracy to

support better inventory planning using MRP

systems. However, to deal with the challenges of

managing today’s supply chains, characterised by

ever decreasing lead time demands from customers

allied to a need for greater choice and customisation,

responsiveness and agility have to be considered as

part of the main principle.

Adjusting to this change in supply chain

management, certain supply chain processes need to

be redesigned, e.g., sales and operations planning,

pull replenishment logic, and timely demand capture.

The U.K. based supply chain management

consulting company, Orchestr8, has developed a

demand-driven supply chain management

methodology which is now being implemented with

a number of its blue chip multi-national clients. The

development of the demand driven supply chain

management system with these major clients has

produced a range of business and technical

components which advance the management of the

supply chain from supply-driven to demand-driven.

The software system has benefited its clients to align

its daily supply chain operations with long-term

supply chain strategies which in return reduces

inventory cost and builds up stable relationship with

their suppliers. This paper describes the architecture

of Orchestr8’s demand-driven supply chain

management system and its conceptual design

toward a business intelligence based metrics

reporting service.

2 SUPPLY CHAIN

MANAGEMENT PROCESSES

Supply chain is featured by Lambert et al. (Lambert

et al , 1998) as a supply network which coordinates

organisations, people, activities, information and

resources involved in moving a product or service

He T., Ribbins P., Brown R., Sun L. and Gurr C. (2007).

A DESIGN FOR BUSINESS INTELLIGENCE SERVICE IN DEMAND DRIVEN SUPPLY CHAIN MANAGEMENT.

In Proceedings of the Ninth International Conference on Enterprise Information Systems - SAIC, pages 20-25

DOI: 10.5220/0002412700200025

 SciTePress

from supplier to customer. Judging the effectiveness

of supply chain management normally includes

monitoring delivery and order fulfillment

performance, production flexibility, warranty and

return’s processing costs, inventory and asset turns,

and other factors in evaluating the overall

performance of a supply chain (Poluha, 2006). To

achieve excellent supply chain management, it is

important to understand the supply network and its

detailed processes.

Figure 1: Structure of Supply Network (Lambert et al.,

1998).

A supply network as shown in Figure 1 consists

of a focal entity of a manufacturing company

networked by downstream entities of customers and

upstream entities of suppliers. In the current

information era, the supply network becomes more

complex and challenging when dealing with the

dynamics of upstream suppliers and highly uncertain

international markets’ demands. Therefore, the

supply chain management is seen as an information-

intensive process, where material/products delivery

and demands have to be effectively managed in

order to maintain supply chain’s visibility.

Because of the large amount of business data in

supply chain management, most companies

implement enterprise information systems such as

ERP, MRP or supply chain management modules to

improve supply chain workflow and efficiency.

However, these systems have not provided sufficient

impact on the effectiveness in the workflow, as two

influential functions, i.e., forecasting and inventory

management, play limited roles in the supply

network.

Forecasting concerns the issues such as how to

project historical data; how to deal with the change

of lead time; and how to recognise different demand

patterns regarding various components (Donald,

2003). Warwick Manufacturing Group (WMG, 2003)

points out that the critical reasons for failing in

getting quality forecasts are:

 Fails to have a single formal forecast

process by all of the management and all the

parties;

 Fails to monitor forecast accuracy

over different time periods and constantly

review the forecast as it changes from time to

time.

More often than not, in manufacturing business,

an ineffective forecast can cause a production plan

ending up with either pushing too much production

and excessive stock, or totally running out of

products.

Inventory is summarised by Richards (Richards,

1982) that time, discontinuity, uncertainty, and

economy feature in the existence of inventory.

Inventory is expected to work as a buffer between

supply and demand to minimise the risk of

investment. Therefore, there are problems

concerning what to stock, when to stock and how to

stock. It is no doubt that a holistic view over parts’

behaviour and aligning that with an appropriate

supply chain management strategy could take

inventory management into a more strategic level

and thereby enhance the effectiveness in setting

stock policies. However, some companies find that

this process, normally called inventory or stock

management, is complex in terms of the diversity of

parts and the time involved.

These limitations of the current common

approach to supply chain management may hinder a

company’s ability to achieve its business goals.

Consequently, companies may find themselves

losing their competitive advantages. Inspired by its

various experiences in tackling supply chain

management difficulties and issues, Orchestr8

realises that the traditional supply network needs to

be driven by real-time demand.

3 DEMAND DRIVEN SUPPLY

CHAIN MANAGEMENT

ARCHITECTURE

Demand driven supply network (DDSN) is a system

of coordinated technologies and processes that

senses and reacts to real-time demand signals across

a network of customers, suppliers, and employees. It

enables organisational efficiency, streamline new

product development and launch, and maximise

A DESIGN FOR BUSINESS INTELLIGENCE SERVICE IN DEMAND DRIVEN SUPPLY CHAIN MANAGEMENT

margin (Askegar, 2004). The main characteristics of

DDSN are featured as follows (Laura, Kevin and et

al, 2004).

 Business manufactures to demand, not

inventory or capacity

;

 Processes are to be integrated across the supply

chain

Orchestr8 adapted this approach and developed a

demand driven supply chain management

architecture (see Figure 2). One of its clients, who is

a market leading manufacturer and retailer focusing

on healthcare products with turnovers in excess of

£5 billion, has benefited from the demand driven

supply chain services. This client is based in the

United Kingdom and having branches in Australia,

Canada and many other countries; and its supply

network extends from European countries to East

Asia. As a typical large scale international

manufacturing and retailing company, the client

found it becoming increasing difficult to maintain its

competitive advantages in the value chain. High

percentages of excess stocks, low efficiency in

managing supplier’s delivery and not having the

right stock at the right time in the right place

jeopardise the manufacturing effectiveness.

Orchestr8 took on these problems of this client and

provided the solution based on a demand driven

supply chain management process.

Figure 2: Orchestr8’s DDSC Management Architecture.

Supported by Orchestr8’s three tier service

model, its demand driven supply chain management

process assimilates the data integration, Sales and

Operations Planning, replenishment planning and

supply chain integration. Orchestr8’s business

intelligence based metrics reporting system

facilitates their forecasting and real-time inventory

monitoring within the supply network.

3.1 Service Model

The service model (Figure 3) in the architecture

provides a supply chain management infrastructure

on which stock turnover, supply and demand

stability and other metrics can be measured. In order

to establish a holistic view on the supply network, a

planning for demand driven supply should be carried

out at the strategic, tactical, and operational levels.

Sales & Operations Planning (S&OP) enables

Orchestr8’s clients and their suppliers to build a

mutual understanding of the inventory strategies

selected for all the stock items.

Figure 3: Orchestr8 Service Model (Orchestr8 Ltd., 2005).

Important changes in product life cycle or market

demand will also be drawn for attention to reach a

better demand visibility. Based on the inventory

strategies formulated by the S&OP process, daily

replenishment is then planned at the operational

level that triggers orders when necessary. A web-

based metrics system monitors the supply activities

by producing timely analysis in reports for decision

making processes.

3.2 Process Model

The process model (Figure 4) is designed to

streamline the inventory management process.

Figure 4: Orchestr8 Process Model (Orchestr8 Ltd., 2005).

ICEIS 2007 - International Conference on Enterprise Information Systems

From the diagram, it can be seen that the monthly

process is the one where the inventory strategies are

defined for the next period. These strategies are

created based on the intelligence gathered as part of

the S&OP process. An automated replenishment

order-generating process then ensures that the

inventory is managed in accordance with the policies.

3.3 Sales and Operations Planning

The importance of the S&OP process arises from its

ability in gathering all the stakeholders’

requirements to reach a common understanding of

the most effective inventory strategies. The S&OP

process also provides the opportunity of realigning

the clients’ forecast by ensuring that the ‘plan’ is

conditioned to incorporate other influences such as

seasonality or promotions management. Orchestr8’s

forecast models allow these options to be tested

through various what-if simulations which can be

done at various levels e.g. by individual item, by

product family or by common grouping.

3.4 Demand-Pull Replenishment

Planning

The replenishment planning process incorporates

inventory items’ historical demand patterns with

their current replenishment rules. Figure 5 shows the

analysis of parts regarding their daily usage and

demand variability based on historical archives.

Figure 5: Volume & Variability Analysis (Orchestr8 Ltd.,

2005).

The rules can be applied by product family or

individual item to achieve most effective

replenishment planning. Vendor Managed Inventory

and Kanban replenishment logic are deployed where

appropriate to enhance lean manufacturing which

results in benefits such as lead time improvement

and stock reduction.

3.5 Business Data Integration

Business data, including order information and part

master, is essential to the successes of effective

forecasting and inventory management. Orchestr8’s

system can be integrated with most ERP, MRP and

other workflow systems and carries out a validation

function on the data imported to ensure that the

necessary data is in complete and accurate which in

turn improves the consistency within the supply

chain management processes. During the restrict

data validation process, the system filters corrupted

data out with relevant implication about its problems

and meanwhile, allows correct data to pass through

for further planning which dramatically reduces

potential problems in the supply chain management

process.

3.6 Supply Chain Integration

Table 1: Traditional SCM vs. Demand-driven SCM.

Topic

Traditional SCM

v.s.

Demand-driven SCM

Scope of

Management

Focus on

internal process

Focus on supply

chain as a whole

Forecast

Effectiveness

Inaccurate and

not understood

by all of the

management

Using demand

driven forecast

model & agreed

by all of

management

Demand

Capture

Push and

produce to

production plan

method

Pull and produce

to demand

Inventory

Management

Efficiency but

not managed as

per various parts’

behaviour

Effective and

detailed to each

product family or

individual item

React to

Change

Difficult to

achieve as the

core calculation

is rigid

Flexible based

on improved

supply network

with lean

inventory &

shortened lead

time

Organisational alignment is always a key

concern of demand driven supply chain management.

Orchestr8 encourages the collaboration amongst

stakeholders across the supply networks. Inventory

strategies are clearly formulated and monitored by

all the stakeholders periodically. Great efforts are

made on building good relationships with the

suppliers to ensure the supply chain is aligned to

A DESIGN FOR BUSINESS INTELLIGENCE SERVICE IN DEMAND DRIVEN SUPPLY CHAIN MANAGEMENT

their capabilities and customers’ expectations.

The demand driven supply chain management

architecture focuses on improving supply chain

management effectiveness in an extensive sense

across the value chain. Table 1 summarises its

business value in comparison with the non-demand

driven approach in supply chain management.

4 CONCEPTUAL DESIGN FOR

BUSINESS INTELLIGENCE

METRICS REPORTING

SERVICES

Business Intelligence (BI) Metrics Reporting Service

plays a strategic role in Orchestr8’s demand driven

supply chain management architecture. It produces

reports and dashboards which support the

collaboration between Orchestr8’s clients and their

suppliers in a real-time supply network. The design

of the metrics reporting system has adopted an

advanced business intelligence approach based on

Kimball’s model (Mundy, 2006) to ensure that this

system has agility.

Various performance measures’ mechanisms

from business intelligence methods have been

critically assessed by this development. The

technologies, such as data warehousing, Online

Analytical Process (OLAP) (Sandeep and Sourabh,

2006), and Microsoft integration and reporting

services have been adopted in the design of the

metrics reporting system (see Figure 6).

Figure 6: Data Transformation (Orchestr8 Ltd., 2006).

The operational data of the clients and its

suppliers is transformed from the Online

Transactional Process (OLTP) database into a data

warehouse which schematically structures the

information for report generation. The cubes

facilitate the execution of the reporting process

which takes the user’s request on visualising their

supply chain performance measures.

The operational data of the clients and its

suppliers is transformed from the OLTP database

into a data warehouse which schematically

structures the information for report generation. The

BI capable cubes facilitate the execution of the

reporting process which takes the user’s request on

visualising their supply chain performance measures.

Figure 7: The Metrics Reporting Services’ Structure.

A schema of the metrics reporting services,

shown in Figure 7, represents S&OP, supply,

demand and inventory. The S&OP is mainly

represented by forecast and target in its granularity.

The supply, inventory, and demand cover the

relevant information in their functionalities in the

supply network.

Similar to Debra’s method of organising supply

chain metrics hierarchically, the metrics provided by

the reporting service are designed to demonstrate

different degrees of detail at various business levels.

In other words, the structure of the metrics

represents details of the supply chain management

process at its granularity. Figure 8 illustrates a

process of evaluation for a client’s total inventory on

hand performance (Orchestr8, 2006).

This process produces the inventory turns at the

upper level, total inventory value at the middle level,

and the inventory policies by part at the lower level

in the metrics. The inventory turns illustrates the top

level effectiveness of the stock management process

by looking at the ratio between the value of total

usage of the stock and the average value of all the

stock on hand in a certain time period. Indicated by

this measure, managers then can use the inventory

on hand reports which are categorised by suppliers

or by product families or by inventory policies at

their preference to investigate the efficiency of their

inventory strategies. To help clients to obtain further

insight into an individual item or exceptional items,

some special analysis driven reports are available to

cater various decision-making needs.

ICEIS 2007 - International Conference on Enterprise Information Systems

Figure 8: A breakdown structure in Inventory Management

performance evaluation.

All in all, the information presented in the

metrics reporting service can support the managers

to assess the overall supply chain health, diagnose

problems, and plan actions progressively.

5 CONCLUSION AND FUTURE

WORK

With respect to the traditional supply chain

management methodology, Orchestr8 in

collaboration with its academic partner has

developed and deployed the demand driven supply

chain management methodology. The development

has delivered the demand driven supply chain

management architecture with the software tools to

perform real-time forecast modelling, inventory

monitoring and supply planning. Clients of

Orchestr8 have benefited by managing their supply

chain on demand. This development has also

provided the client with strategic impact on

redesigning their supply chain planning process.

There are still some further work and

improvements need to be carried out, such as

deploying business intelligence using advanced

analyst methods, incorporating ad-hoc reports in the

metrics reporting services and designing formal

performance management processes. Effectiveness

of the demand driven supply chain management

process will be under close monitor as well for

continuous improvement purpose.

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A DESIGN FOR BUSINESS INTELLIGENCE SERVICE IN DEMAND DRIVEN SUPPLY CHAIN MANAGEMENT