t801 msc in manufacturing: management and technology. chain dossier/supply_chain... · t801 msc in...

Don Carmichael P5893614

T801 MSc in MANUFACTURING: MANAGEMENT AND TECHNOLOGY

Name: Don Carmichael

Personal Identifier: P5893614

Title of Dissertation: Supply chain planning systems in

manufacturing.

Date: September 1998

Don Carmichael P5893614

Project Title : Supply chain planning systems in manufacturing.

A dissertation submitted in partial fulfillment of the requirement for the MSc in

Manufacturing : Management and Technology.

The complementary fulfillment of the requirements for the MSc being the following

Diploma Courses :

Course Title Reg. Result Points

Year

PT613 Manufacturing Management 1994 Pass 30

PMT605 Project Management 1994 Merit 15

T833 Implementation of New Technologies 1995 Merit 30

PT611 Structure & Design of Manufacturing 1995 Merit 30

Systems

M866 Relational Database Design 1996 Pass 15

Don Carmichael Page i P5893614 List of Contents

List of tables iii

List of figures v

Glossary of abbreviations vi

Preface vii

CHAPTER 1 Summary 1

CHAPTER 2 Introduction to the project 3

2.1 The aims and objectives of the project 3

CHAPTER 3 Background and literature review 5

3.1 Introduction to Supply Chain Planning (SCP) 5

3.2 The manufacturing interface 15

3.3 Finite Capacity Scheduling (FCS) 17

3.4 The ‘leaner’ issues 25

CHAPTER 4 SCP packages 33

4.1 Introduction 33

4.2 Survey of SCP packages 34

4.3 Commonalities 35

4.4 Analysis 39

4.5 Future directions 39

4.7 Conclusions 40

CHAPTER 5 Survey 41

Don Carmichael Page ii P5893614

5.1 Introduction to the survey 41

5.2 The survey and the methodology 41

5.3 Results of the survey 47

5.3.1 Analysis of the results 56

5.4 Conclusions 59

CHAPTER 6 Discussion and conclusions 60

6.1 Discussion 60

6.2 What does industry want ? 69

6.3 How are SCP packages helping ? 70

6.4 Future directions 72

6.5 Main Conclusions 72

CHAPTER 7 Future work 74

7.1 The broad SCP arena 74

References 75

Appendices 79

Appendix A - The Questionnaire 79

Appendix B - Questionnaire Response Analysis 82

Appendix C - Supply Chain Planning package features 103

Bibliography 112

Fundamental Readings in Supply Chain Management 112

Production Aspects of Supply-Chains 114

Organisational Contexts 118

Don Carmichael Page iii P5893614

List of tables

The following are a list of the tables found in the main body text of this dissertation.

Table Page

Table 3.3 Areas of conflict in the supply chain [3] 21

Table 5.3.0.1 Tabular summary of questionnaire results with

respondent number versus question number with answers. (1

of 5)

51



of 5)

52



of 5)

53



of 5)

54



of 5)

55

Table 5.3.1.1 Results of MCS/CA survey as reported in

Manufacturing Computer Solutions January 1997 showing

selected issues and the number of companies seeing this as

a priority as a percentage.

56

Don Carmichael Page iv P5893614

Table 5.3.1.2 The results of table 5.3.1.1 with the

corresponding project survey question number and

percentage of respondents claiming each issue as a problem

or serious business problem.

57

Don Carmichael Page v P5893614

List of figures

The following is a list of figures found in the main body of this dissertation.

Figure Page

Figure 3.1.1 The scope of supply chain management. Supply

chain management covers the flow of goods from supplier

through manufacturing and distribution chains to the end

user. (From[13]).

7

Figure 3.1.2 A more manufacturing related order driven

supply chain. (From [3]).

14

Figure 3.1.3 The author’s own model of a single business

internal supply chain

15

Figure 3.4.1 The overall aim of manufacturing business

improvement

25

Figure 3.4.2 Suppliers organised into functional tiers 29

Figure 6.1 Number of weeks stock by country from the

European Logistics Comparative Survey 1998. [22]

66

Don Carmichael Page vi P5893614 Glossary of abbreviations

SCM Supply Chain Management

SCP Supply Chain Planning

MRP Materials Requirements Planning

MRP II Manufacturing Resource Planning (an extension of MRP)

ERP Enterprise Resource Planning (an extension of MRP II)

CBP Constraint Based Planning

JIT Just-In-Time; a method of production, developed by Toyota,

whereby only the parts needed are produced and only delivered

to the next operation when required. This cuts out wastes in

inventory, storage and over-production.

BPR Business Process Reengineering

CPG Consumer Packaged Goods; an industry sector

FCS Finite Capacity Scheduling is a process whereby a production

plan consisting of a sequence of operations to fulfill orders is

generated based on the real capacity of resources. These can

be machines, operators, tooling or anything which is a constraint

on the production process.

ECR Efficient Consumer Response

There are several companies mentioned and referenced throughout this dissertation.

These companies are the market leading developers of two types of software system

being :

Don Carmichael Page vii P5893614

• Supply Chain Planning vendors; the two leaders being ‘i2’ Technologies with the

Rhythm product and Manugistics. Other vendors, such as Numetrix and SynQuest

are recognised as contenders for third place [16].

• ERP vendors; the four market leaders are conveniently covered by the acronym

‘BOPS’ meaning BAAN (with the BAAN IV product), Oracle (with the Oracle

Financials, Oracle Manufacturing, GEMMS and CPG package offerings),

Peoplesoft (including it’s ‘Red Pepper’ supply chain optimisation system) and SAP

(with the R/3 product). Other players and leaders in the American mid-market

sector according to the authoritative industry analysts Gartner Group, are SSA

(with the BPCS product) and QAD (with the MFG/PRO package).

Preface

Thanks are extended to the authors supervisor Dr. John Wright for his help and

enthusiasm throughout the project.

Don Carmichael Page 1 P5893614

CHAPTER 1 Summary

‘The best company cannot be competitive if it is part of a supply chain which is

inefficient and ineffective’. [1]

Dr. Canadine, of the Institute of Logistics, believes that leading edge companies are

beginning to understand that competition and competitive advantage is not being

played out between individual companies but by competing supply chains.

In support of this a new breed of software vendors have developed supply chain

planning (SCP) software packages which utilise concurrent optimisation algorithms

to produce the optimum supply chain configuration and schedule. The optimum

configuration and schedule may be based on lowest cost, material or capacity

constraints, customer due date adherence or a user defined combination of optima.

This dissertation describes the basic functionality to be found in supply chain

planning systems and the often confusing coexistence of supply chain management

systems.

A survey by questionnaire across a random sample of manufacturing companies

was undertaken and the dissertation analyses the data to come to a number of

conclusions. Certainly, in the U.K, most manufacturers are still concerned with

internal issues such as cost savings within manufacturing. There is little

comprehension of the effects of each manufacturer’s (or supplier’s) place within the

Don Carmichael Page 2 P5893614 supply chain apart from specific industries such as the Automotive industry where

lean manufacturing methods have led to strong partnerships between automotive

companies and their tiers of suppliers.

The dissertation continues by exploring the reasons why the mainly American supply

chain planning vendors have experienced such explosive growth in the USA. This

growth is mainly to do with the immense potential for cost savings in the long lead

times found in US supply chains, 105 days average replenishment times as

compared to 38 days in the UK. This potential is further enhanced when

consideration is given to the vast US geography and thus the large transportation

costs. The US tends to be supply constrained, controlled by the manufacturer /

supplier, rather than demand constrained, controlled by the retailer / customer, as is

the situation in the UK. This means that manufacturers / suppliers in the US have the

opportunity to optimise their own supply chains to their customers.

The dissertation concludes by agreeing in part with some of the SCP vendors, such

as Manugistics, who believe that their biggest task in the short term is education.

The results of the author’s survey and other sources suggest that in the U.K, and

perhaps in most of the EC, SCP vendors may find that there are neither the supply

chain inefficiencies to justify the high SCP package costs nor the level of interest in

SCP systems in America.

Don Carmichael Page 3 P5893614 CHAPTER 2 Introduction to the project

2.1 The aims and objectives of the project

It is now widely recognised that companies are no longer competing against other

companies. Whole supply chains are now competing against each other.

The pressures of modern business, the global community, customers expectations of

personalisation and rapid delivery and the continuing need to reduce costs are all

changing the way companies view themselves. The challenge now is to optimise and

employ ‘lean’ principles across all a company’s relationship boundaries.

The project concentrated itself on the rise of the supply chain planning software

package, it’s roots in Finite Capacity Scheduling software products and the ‘softer’

issues of the ‘lean’ enterprise.

The aims of the project were to :

1. gather together the current academic and recognised industry analyst knowledge

to produce a picture of where supply chains are changing, and why. The focus of

this was the effects on manufacturing with special emphasis on the ‘lean’

manufacturing / enterprise revolution.

2. match this against the experiences of real manufacturers coping with the

demands placed on them by the great shift in supply chain complexity. The aim

here was to find any conflicts in perceptions and views and compare these against


the book research results. This was achieved through the use of a survey by

questionnaire and ultimately through comparison with the results of other similar

surveys.

3. generally describe Supply Chain Planning (SCP) package functionality and then to

discuss how such a package addresses the supply chain pressures manufacturing

and distribution companies are facing.

4. detail further work required in this subject area and to surmise on the functionality

requirements future SCP packages should include.


CHAPTER 3 Background and literature review

3.1 Introduction to Supply Chain Planning (SCP)

Supply chains are the supplier / manufacturer / distributor channels, networks and

relationships [3] in manufacturing or services supply. A good short-hand describing

some food supply chains would be the ‘plough to plate’ analogy, recently used in

British food hygiene political discussions.

The complexity and length of supply chains is increasing, as for example in the

automotive industry. The Society of Motor Manufacturers and Traders (SMMT)

‘Passenger Car Logistics Survey’ [4] results show that by the year 2000 the average

number of components or sub-assemblies car manufacturers believe a car will be

assembled from is nine. This will have a massive impact along the automotive supply

chain from Tier 1 (direct to car manufacturer) suppliers to Tier 3 (electrical sub

components for dashboard assemblies, for example) and beyond. Design,

manufacturing and assembly responsibility will be passed down automotive supply

chains through closer and closer partnerships with suppliers. This, along with other

‘lean thinking’ ideas, was predicted in Womack et al’s ‘The Machine That Changed

The World’ [5]; the lean production book.

Manufacturing and supply planners are now having to consider a complex supply

chain network as opposed to a single supplier / customer relationship [6]. The flow of

Don Carmichael Page 6 P5893614 information up and down supply chains is becoming more important than anything

else.

‘The economy is changing structure. From being organised around the flow of things

and the flow of money, it is becoming organised around the flow of information [7].’

This statement by Peter Drucker is emphasised in the report on ‘ICL’s Logistics

Strategy’ in the ‘International Journal of Logistics Management’ [3].

ICL believe the most important feature of their supply chain is the flow of information.

Excess inventory (stock) is seen as an undesirable result of imbalanced processes

and the cost of that inventory is seen as being greater than the cost of managing the

flow of information effectively. ICL’s predominant emphasis within their logistics

strategy is to develop Information Technology (IT) applications that enhance logistics

performance. Information must be substituted for inventory as the main trade-off for

achieving customer service all along the supply chain.

Figure 3.1.1 below is a good demonstration of a possible simplistic internal supply

chain showing all of the potential inventory stocking points within one company and

thus all of the points where excess inventory can be held. If this is multiplied by the

network of different companies making up supply chains, one can see how big a

potential problem excess inventory can be.


S u p p lie r s

O rd e r s

P r o c u r e m e n t M a n u fa c tu r in g F a c to r y D is tr ib u t io n C u s to m e r E n d u s e r s

R a w m a te r ia l

In -p ro c e s s

D is tr ib u t io n S e ll in g p o in t

Figure 3.1.1 The scope of supply chain management. Supply chain management

covers the flow of goods from supplier through manufacturing and distribution chains

to the end user. (From[13]).

On top of all the above, business transactions are becoming faster and faster [8].

Customer requirements have become more sophisticated. Product life cycles have

reduced dramatically in most industries and competition has become global.

In the past, focus on output value (local optima, as Goldratt puts it [9]), led to

performance measures such as those based on standard hours, direct labour

efficiency, factory output value and overhead recovery on direct labour. It was

identified that the focuses on inventory and customer service were missing.

This is highlighted when it is noted both that :

Don Carmichael Page 8 P5893614 1. ICL identify 80% of their costs as being material (other sources seem to average

material costs across all manufacturing to about 58%) and that

2. customer service features highly in modern supply chain techniques such as

Efficient Consumer Response (ECR) [10].

The major task for ICL is the management of material within an efficient international

logistics chain.

If companies such as ICL have identified the need for both an efficient logistics chain

and IT applications to enhance the logistics performance, it is perhaps a surprise to

learn that only 20% of U.S logistics professionals believe that IT systems are well

integrated with the logistics processes in their company [11].

This is not to say that U.S logistics professionals are against IT; most respondents of

the KPMG survey [11] said that they thought IT was an ‘important tool’ and would

‘significantly improve logistics’. It can be seen that even in the U.S, who tend to be

ahead of the UK in the take-up of IT systems, there is still a requirement and a

market gap for IT systems to fully support supply chain logistics.

At this point it is worth resolving the difficulties and confusion that may arise from

using ‘supply chain’ terms and ‘logistics’ terms.

During the literature review for this dissertation several sources defined the link

between supply chain terminology and logistics thinking. ‘Supply chain’ terminology

Don Carmichael Page 9 P5893614 is a fairly recent invention as opposed to ‘Logistics’ terms and terminology, which is

much older coming from the Napoleonic campaigns.

Greenwood in the Institute of Logistics journal [12] believes that

‘if we analyse what the experts are calling supply chain management we find that

they are really talking logistics but driven by the requirement of the decade’.

Greenwood believes that supply chain management would be called ‘Demand Chain

Management’ if the process were more fully understood. Further, Bowersox believes

that the issues of logistics and supply chain management are practically

synonymous [2]. The American magazines Distribution (January, 1996) and

Purchasing both define Supply Chain Management (SCM) as interchanges or

combinations of logistics processes.

Many Manufacturing Resource Planning (MRP II) systems (especially those that

have migrated into Enterprise Resource Management (ERP) systems to handle

multiple currencies, multiple companies and multiple sites) are now calling their

products Supply Chain Management (SCM) systems. As an example, the MRPII

product the author used to work with, MFG/PRO by QAD, now calls itself a Global

Supply Chain Management system.

It is important to distinguish between two clearly definable IT systems solutions that

address supply chain issues :

Don Carmichael Page 10 P5893614 1. the MRP II/ERP products, ‘relabeled’ as SCM products. For example, BAAN IV

(Series), Oracle Manufacturing, SAP R/3 and SSA’s BPCS, are ‘transaction’

systems; handling, for example, purchasing, sales and forecasting, shop floor

production, quality and inventory transactions.

2. true Supply Chain Planning (SCP) products, aimed at planning the supply chain

as a whole. The system vendors here, such as Numetrix [13], Red Pepper,

Manugistics and SynQuest believe that their products are the true supply chain

management products.

The key to the real definition, for these SCP vendors, revolves around the system’s

ability to understand, integrate and optimise the complete supply chain from

supplier’s supplier to customer’s customer; to create the optimal sourcing, production

and distribution plan. The aim of these SCP products is to react to the speed of

change of business across the supply chain and create, for example,

• the best splits across suppliers considering supplier capacity and availability.

• the least ‘total acquisition’ cost distribution solution.

• the best customer service level that can be achieved with the current demand plan

and workforce resourcing rules.

Keith Burgess, a consultant with KPMG’s Supply Chain Management Systems

Group, [14] defines the goals of advanced supply chain planning systems as being:


• rapid optimisation of the total supply chain,

• making available ‘what-if’ functionality – to test the effect of possible events on

the total supply chain,

• the ability to cope quickly with unforeseen problems,

• flexible scheduling – allowing for more than the first-in-first-out (FIFO) approach

adopted by most MRP systems, and

• the ability to provide accurate and flexible information about the supply chain.

These products logically sit above MRP II/ERP systems but require these transaction

based systems to enact, record and feedback the optimised demand, supply and

production plan.

Most MRP II / ERP packages still rely on the Materials Requirement Planning (MRP)

algorithms, invented in the 1960’s and defined by Orlicky [15], as the only constraint

planning mechanism. However, the recognition of the importance of SCP products

by the MRP II/ERP product vendors has arrived by a number of announcements

reported over the last few months via the AMR Alert on Supply Chain Management

Email series [23] being that :

Don Carmichael Page 12 P5893614 • Peoplesoft bought the SCP vendor Red Pepper to use a basis for a full ERP

offering.

• BAAN announced a constraint based planning (CBP) module, based on a product

BAAN bought called MOOPI.

• SAP announced a new module developed in-house within SAP called the

Advanced Planner and Optimiser (APO) within SAP’s Supply Chain Optimisation,

Planning and Execution (SCOPE) Initiative.

• Both BAAN and SAP announced strategic alliances with the three top SCP

product vendors ‘i2’ Technologies, Manugistics and Numetrix [16].

Confusion still exists over the definition of supply chain management. Even

Advanced Manufacturing Research (AMR), the leading industry analysts along with

Gartner Group, still call SCP products SCM systems [16].

For the rest of this dissertation the author will try to avoid any confusion by using the

term ‘Supply Chain Planning (SCP)’ system to differentiate these supply chain

optimisation products.

White in Control [17] defines Supply Chain Planning (SCP) as

‘a constraint- based ‘decision support’ or planning tool that includes the following:

Item Forecasting; Promotion and Event Planning; Item Inventory Planning;

Don Carmichael Page 13 P5893614 Replenishment Planning, incorporating Distribution Requirements Planning (DRP)

and various Continuous Replenishment Strategies; Manufacturing Planning and

Scheduling’.

White sees Supply Chain Planning as the keystone to Supply Chain Management.

The dissertation will investigate the effects that recently available Supply Chain

Planning (SCP) software packages will have on manufacturing issues. This will be

achieved by :

• book research,

• a survey by questionnaire,

• and an investigation into the general functionality of a range of these packages

As the dissertation confines itself to the effects of SCP on manufacturing, the scope

of what is meant by manufacturing should be defined. Bowersox [2] defines

manufacturing support within logistical integration as being

‘… managing work-in-process inventory as it flows between stages of

manufacturing’.

Figure 3.1.2 shows a more order related view of a supply chain and where in-

process inventory sits within this environment.


The overall concern is not how production occurs but the what, when and where

products are manufactured. Bowersox believes that whereas physical distribution

must accommodate the uncertainty of consumer and industrial demand,

manufacturing is under the control of the manufacturing enterprise.

From Supplier Throughmanufacturing

And distributionchain

To the end user

Supply chain

Pro-curement

order

Rawmaterialinventory

Shoporders

In-processinventory

MPS orders

Finishedfactory

inventory

Factoryorders

Distributioninventory

Distri-butionorders

Sellingfrom

inventory

Cust-omerorders

Supplier Customer

Figure 3.1.2 A more manufacturing related order driven supply chain. (From [3]).

Figure 3.1.3, below, is a simplistic version of the supply chain diagrams used by the

author to explain how information and inventory flow through a business.

The company is the box split into information flow from right to left and material flow

from left to right. To the right hand side of the box is the direct customer and to the

left the supplier. The planning function is basically a balancing function to take the

demand, in whatever form it is presented (sales orders, forecasts, planned inventory

levels etc.), and convert the demand into

Don Carmichael Page 15 P5893614 1. What to make (produce, convert, pack, assemble etc.) and

2. What to buy

The box is used to demonstrate that a company is one unit and not a series of

departments. Information generally flows from the front of the business to the back

and materials the opposite direction.

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Planning

What-to-buy

What-to-make

INFORMATION FLOW

MATERIAL FLOW

ValueAdded

Purchasing

Supply Dispatch and Distribution

Demand

Figure 3.1.3 The author’s own model of a single business internal supply chain.

3.2 The manufacturing interface

Dr. Canadine, the Director-General of the Institute of Logistics [1], calls

manufacturing a ‘micro-logistics’ process, an individual section of a much larger

supply chain. Micro-logistical thinking, says Canadine, has led to the development of

Kanban, Just-in-Time, MRP and MRP II. Thinking of a manufacturing ‘interface’ is

Don Carmichael Page 16 P5893614 actually unhelpful as organisational boundaries are the enemy of the cross functional

thinking that is required to optimise and understand supply chains.

In Hill’s book ‘Manufacturing Strategy’ [28] there is much to convince the reader that

business, marketing, manufacturing and thus all supply chain strategic issues all

have to be considered at once. The traditional view is of business plans being split

into sales / marketing plans and then handed to manufacturing to consider how the

production targets can be met.

There is a ‘macro-logistics’ strategic level where the design and control of the supply

chain takes place and where issues such as :

• the location of markets,

• where to place manufacturing capacity,

• which components to outsource and which to manufacture,

• and how to resource service and maintenance

are considered.

So, in conclusion, manufacturing has to be considered as part of the whole supply

chain and not spilt off as a separate entity as it is in ‘traditional’ logistics thinking

within some companies.


3.3 Finite Capacity Scheduling (FCS)

Production planners invariably claim to have picked the optimum production plan

considering customer due date adherence, optimal throughput, mix and optimal cash

usage. In manual production planning environments which require anything more

than simplistic optimisation rules using ‘rules of thumb’ and experience, humans

cannot, or rarely, actually achieve optimisation.

A series of highly graphical software products have been developed to enable

complex optimisation to be achieved. These are called finite capacity scheduling

(FCS) products (or finite schedulers) with product names such as Preactor, CIM

Leitstand, FI-2, and ‘i2’-Rhythm, SAP-APO for the supply chain variants .

As of the middle of 1996 it was reported in an Aston Business School manufacturing

technology survey [18] that about 19% of respondents used FCS products.

One vendor of FCS products defines FCS as :

‘a process whereby a production plan consisting of a sequence of operations to fulfill

orders is generated based on the real capacity of resources. These can be

machines, operators, tooling or anything which is a constraint on the production

process.’

The reason FCS came into being was that most manufacturing planning systems

assume sufficient resources are available when required, i.e. resources have infinite

Don Carmichael Page 18 P5893614 capacity. An MRP system typically takes the orders for products, breaks them down

into component parts and calculates when to start making them based on the

individual lead times. No account is taken of the current available capacity of

resources.

At the same time that the production order start times are calculated, the materials

needed are ordered to arrive in time for the work to start. If there is a delay in

production upstream of a particular operation then the materials will be ordered too

early. With no concept of bottlenecks available to the planning system, resources

become overloaded, queues of work get longer and work in progress increases.

Because jobs must join the queues at each process step, orders take longer to make

progress, expected lead times are too optimistic and deliveries are late.

FCS software tools are commonly integrated or interfaced into the MRP II business

systems. An FCS tool requires information on resource and work centre capacity,

shift calendars, the current usage of that capacity and the Master Production

Schedule (MPS), or list of production orders. The FCS generally either

• returns an optimised version of the MPS back to the MRP II system for execution

or

• takes control of the MPS where the execution system is linked directly to the

FCS.

Don Carmichael Page 19 P5893614 Here, the execution system is the shopfloor control and feedback mechanism

initiating and recording production actuals.

Simpler FCS systems consider all constraints or bottlenecks in production as ‘hard’

constraints. This means that if the right machine, operator and tooling have to be

available at the same time to produce a particular production order then the FCS

system has to determine a time when all three resources are free. It is worth pointing

out that the more constraints defined for a FCS, the more complex the calculations

become. Each constraint can be thought of as a dimension of calculation.

More complex FCS systems and certainly those built into the Supply Chain Planning

systems considered in this project have the concept of ‘soft’ constraints built in.

In the author’s experience, if manufacturing planners are asked how they resolve a

scheduling conflict if a rush order arrives and tools, for example, are not available,

they tend to suggest buying in additional tooling. Thus tooling, in this case, can no

longer be described as a constraint, merely a cashflow ‘penalty’ for having to

purchase the tools.

The machine or plant required to run the rush order was a ‘hard’ constraint but the

tools were a ‘soft’ constraint. It can be seen then that the optimal plan across a

series of resources may be a compromise that produces the least penalty.

Don Carmichael Page 20 P5893614 The penalty may be simply in cash terms say or if we now consider the FCS

functionality (or ‘simultaneous constraint optimisation’ as the SCP vendor Red

Pepper calls it) in SCP systems, the constraints and thus penalties could include :

• Promise dates,

• Request dates,

• Inventory shortages,

• Aggregate capacity,

• Safety stocks,

• Excess stocks and

• Raw material shortages.

On top of these ‘hard’ and ‘soft’ constraints there are other scheduling complexities

that the better products have to consider such as sequencing environments, colour

sequencing for example.

This is where the optimal plan for producing a product made in different colours is

usually to produce the lighter coloured products first and then the progressively

darker colours thus minimising the cleaning time between colours.

Other constraints can include

• Shelf life,

• Ramp up curves and

• Scheduled maintenance.


Impact of objectives on …

Functional objectives

Inventory

Customer

service

Total costs

High customer service

Low transportation costs

Low warehousing costs

Reduce inventories

Fast deliveries

Reduce labour costs

Desired results

Table 3.3 Areas of conflict in the supply chain [3]

In the above table 3.3, the arrows point upwards for increases in inventory, customer

service and total costs and downwards for resulting decreases in the set objectives.

The darker arrow signifies the main desired impact of a functional objective, for

example, the desired impact of a functional objective to reduce labour costs will

reduce total costs but will also have the effect of increasing inventory and decreasing

customer service.

The table is trying to demonstrate the essential conflict of management objectives

and measures across organisational boundaries across the supply chain.


Some SCP packages attack some of these conflicting objectives by presenting users

with a mechanism to tell the SCP package the weighting the business places on

particular management objectives. Thus, if the business objectives of customer

service should be considered more important than excess stock then the SCP’s

optimisation engine will determine that there is a higher ‘soft’ penalty for customer

service and will therefore produce a stocking plan that may require more stock than

absolutely necessary because there is a lower ‘soft’ penalty for excess stocks.

Within the SCP product ‘Red Pepper’, there is a screen called the ‘ResponseAgent’

Control Panel where the user moves a pointer up and down a meter representing 0

to the left and 100 to the right to signify the weighting to be applied to :

1. Request Dates,

2. Promises Dates,

3. Inventory Shortages,

4. Aggregate Capacity,

5. Safety Stocks,

6. Excess Stocks and

7. Raw Material Shortages.

The ‘ResponseAgent’ tool uses all the meter readings to determine the relative

penalties to be applied to each objective (or constraint as ‘Red Pepper’ call it) and

then optimises all the constraints concurrently.

Don Carmichael Page 23 P5893614 Appendix C covers the detailed scheduling features of one SCP vendor’s package.

The reason only one package is covered at the detail given is that the vendor,

Numetrix, was the only company willing to detail the constraints covered.

As a comparison, another SCP vendor, Logility, limits it’s description of the

constraints covered to

‘equipment capabilities, intermediate storage limitations, shop calendars and

production constraints such as synchronisation of multi-step operations, product

sequencing, changeovers and inventory policies.’

This comes back to a reoccurring theme with all SCP vendors in that they all

complain that there is a broad lack of understanding of the SCP issues, benefits and

product capabilities and yet hardly any of them will release information at a detailed

enough level to examine the exact capabilities of each product.

In the SCP vendors defence, they are competing in a extremely fast-moving and

growing marketplace where functionality evolves almost weekly. Most SCP vendors

seem to sell by :

• fighting for the opportunity to develop a proof of concept pilot at the sales

prospect’s plant,

• using reference sites (current SCP customers) with proven demonstrable benefits

realised through the SCP products.

Don Carmichael Page 24 P5893614 It may be that giving away too much information at the start of the sales cycle allows

prospects the opportunity to perform direct functionality comparisons which the SCP

vendors are unwilling to take part in.


3.4 The ‘leaner’ issues

Through-put

Produc-tivity

Quality Morale

Inventory WIP Operating Costs

IMPR

OVE

RED

UC

E

Figure 3.4.1 The overall aim of manufacturing business improvement

The main objectives of a manufacturing business improvement exercise are shown

in Figure 3.4.1.

However, Figure 3.4.1 shows the utopian view of the business objectives. As we

have seen, there are internal and external conflicts which may mean that a reduction

in inventory, say, increases overall operating costs. One reason for this may be

because the resulting reduction in customer service levels mean that more cost is

required to replace the lost customers.

So far this project has dealt with the ‘hard’ or more technical issues surrounding

SCP. For supply chain planning to be effective, the ‘soft’ issues, i.e. relationships

Don Carmichael Page 26 P5893614 with the customer / consumer and the supplier, need to be developed. To achieve

the utopian view in Figure 3.4.1, business improvement needs to address both the

hard and soft issues simultaneously. This section deals with the ‘soft’ issues by

examining the lean production revolution and the focus on relationship and value.

In ‘The Machine That Changed The World’ [5], the lean production book, Womack et

al. stress how important organisation, communication and relationships throughout

the supply chain were to Eiji Toyoda and the production ‘genius’ Taiichi Ohno (the

originators of the Toyota Production System which ultimately developed into lean

production ideas).

In considering an alternative to the mass-production method of car manufacture,

Ohno and others at Toyota saw many problems with the traditional supply chain

relationships :

• component suppliers had little incentive to improve or optimise their parts as the

design information on the rest of the vehicle was seen as proprietary.

• ‘organising suppliers in vertical chains and then playing them against each other

in search of the lowest short-term cost blocked the flow of information between

suppliers.’ Suppliers were unable to share organisational and process /

technological improvements.


The car assembler ‘might ensure that suppliers had low profit margins, but not

that they steadily decreased the cost of production through improved organisation

and process improvement’.

• if the car assembler knew little of the component suppliers production techniques

then it would be difficult to improve quality beyond specifying maximum levels of

defects. It would be difficult to raise the quality level if most other suppliers

achieved similar levels. Of course, quality of the components impacted the quality

and perception of the finished good, in this case the car.

• the coordination of day-to-day supplies from the supplier proved to be very

difficult. Because of the inflexibility of suppliers’ tooling and the uneven demand

from the car assembler, the suppliers built up large stocks into warehouses

resulting in high inventory costs and the ‘routine production of thousands of parts

that were later found to be defective’ when assembled into the cars.

Toyota’s answer to the inflexibility of their own and their supplier’s tooling

changeovers developed ultimately into the SMED (Single Minute Exchange of Dies)

techniques which allowed rapid changeovers from production of one type of part on

a press, say, to another. This technique was certainly critical to the whole ‘Just-In-

Time’ or kanban system of which so much has been written.

The kanban technique is a ‘pull’ system whereby a customer buys a product and

only a minimum quantity of the product or components (the aim being a single

instance of a product) is made at each stage to replenish the product pulled from the

Don Carmichael Page 28 P5893614 stage in front. The mechanism to control this was the product container carrying the

parts to the next stage. As this technique was to be used across the whole supply

chain, almost all inventories were eliminated at Toyota’s and Toyota’s suppliers

plants and warehouses and the full fragility of the ‘JIT’ supply chain was exposed.

Because there was no or minimal buffer stock between each supplier and process,

as soon as a single process failed the whole system came to a stop. The idea was

that any quality or process failure should have been anticipated.

Certainly, Womack’s book [5] reports that lean manufacturers using these

techniques rapidly focus on process and component quality and generally achieve

quality figures 3 times better than traditional mass production plants.

Toyota’s answers to the ‘softer’ issues being supplier organisation, communication

and relationship problems, resulted in the development of a new lean-production

approach to component supply.

This new approach meant that suppliers would now be intimately involved in

Toyota’s product development, have interlocking equity with Toyota group members,

rely on Toyota for outside financing of capital investment projects and accept Toyota

people as their own personnel.

The suppliers were organised into functional tiers, whatever the legal or formal

relationship. First tier suppliers became an integral part of the product development

team and were given overall performance and cost specifications for major sub-

assemblies. The supplier was given free reign on the engineering decisions and was

Don Carmichael Page 29 P5893614 expected to interrelate with the other tier 1 suppliers. Tier 1 suppliers were expected

to form tier 2 supplier organisations or associations which would concentrate on the

fabrication of the individual components making up the major sub-assembly.

Automotive Supplier 1

Tier 1 Supplier

Tier 1 Supplier

Tier 2 Supplier

Tier 2 Supplier

Tier 2 Supplier

Automotive Supplier 2

Figure 3.4.2 Suppliers organised into functional tiers

In Figure 3.4.2 above the Automotive suppliers are seen at the top of the supply

chain and their suppliers organised into :

• Tier 1 suppliers who supply major sub-assemblies direct to the automotive

supplier;

• Tier 2 suppliers, usually specialist manufacturers, who supply the Tier 1

suppliers.

• Tier n suppliers exist beneath this structure (not featured in the Figure 3.4.2

above); ultimately, down to the raw material extractors, rubber plant for tyres, ore

for metals etc.

Don Carmichael Page 30 P5893614 A point to note about Figure 3.4.2 is that Tier 1 suppliers will often be supplying

multiple car assemblers. In Toyota’s case, Tier 1 suppliers, which may be part

owned by Toyota or have previously been Toyota in-house assembly operations, are

encouraged to perform work for other industries or assemblers. This would generally

be seen as producing higher profit margins.

Womack’s ‘lean manufacturing’ book [5] reports that Nippondenso, a $7 billion

company, is the largest manufacturer of electrical and electronic systems and engine

computers. Toyota holds 22 % of its equity and Nippondenso does 60% of its

business with Toyota. Another 30% of the equity is held by the Toyota supplier group

of companies, and 6% by Robert Bosch, the giant German components firm.

The cross ownership that proliferates within Toyota’s supply chain has some

parallels outside Toyota such as Ford’s purchase, or part ownership, of the Eastern

European Autopal headlamp manufacturing plants.

Toyota also shares personnel with it’s suppliers and helps out with workload surges.

In summary, it can be seen that Toyota, as the original lean manufacturing company,

has developed very high levels of communication, resource and fiscal interaction

with it’s suppliers. Toyota’s suppliers can be seen as sharing Toyota’s destiny.

Of course, it must be remembered that although automobile manufacturing is an

important business activity it cannot be seen as representative of all industries, types

of production or manufacturers place within the supply chain. Toyota, in common

Don Carmichael Page 31 P5893614 with other car manufacturers, lives at the top of the supply ‘food chain’ and therefore

has the opportunity and power to change their suppliers and supply chains. Without

the help of the ultimate car assembler, it can sometimes be difficult for Tier 2

suppliers to develop the levels of communication and relationships required to

achieve a lean supply chain with their own suppliers.

The Odette ‘Passenger Car Logistics Survey’ [4] showed that Tier 2 or 3 suppliers

can often be larger than the direct, Tier 1, suppliers. An example here could be a

dedicated dashboard assembly supplier to two or three automobile assemblers with

a company like Lucas, say, supplying the instrumentation to the dashboard

assembler.

It is interesting to note the similarities between Lean Manufacturing principles (as

derived from the Toyota Production System), Value Engineering and business

process re-engineering.

A definition of business process re-engineering (BPR) from Thomas Gunn’s real-time

enterprise book [8] is:

‘The improvement of business processes by a cross-functional team that first seeks

to understand and document the entire process, then simplifies and removes the

waste from it, then applies information systems to improve the speed and quality of

the process as well as improve it’s flexibility and the productivity of the people

associated with it.’

Don Carmichael Page 32 P5893614 It seems a core principle in Value Engineering, Lean Manufacturing and BPR is the

reduction of waste and the concentration on the value added functions.


CHAPTER 4 SCP packages

4.1 Introduction

Investigating the functionality of Supply Chain Planning (SCP) packages proved very

difficult. Most SCP suppliers are willing to provide high level glossy brochures and

impeccable references but have no detailed system or functionality descriptions. The

reasons for this appears to be that the SCP sales environment is highly competitive

and functionality is rapidly expanding, especially with the two market leaders

Manugistics and ‘i2’.

A SCP sales cycle involves the use of reference sites and paid proof of concept

projects. These projects are short-term, limited implementations of the product within

the customers own site. The SCP software package will be configured to represent a

limited version of the customer’s supply chain and manufacturing environment and

then loaded with a sub-set of the customer’s business data so that the concept,

feasibility, justification and potential cost savings can be demonstrated. The

customer can then decide whether to commit to the whole project.

As a result of the above, SCP vendors feel they do not have to provide highly

detailed system descriptions.

Don Carmichael Page 34 P5893614 4.2 Survey of SCP packages

As of late 1997 the main SCP suppliers competing in Europe were:

• ‘i2’ -Rhythm – primarily focused on the Electronics sector

• Manugistics – focused on the Consumer Packaged Goods (CPG) sector

• Numetrix – focused on the Process sector

• ‘Red Pepper’ / Peoplesoft

• SynQuest

• American Software

Materials gathered and analysed include the sales literature from Manugistics,

Numetrix with it’s ‘Supply Chain Visibility / Integrator’ and ‘i2’ with the ‘Rhythm’

product (the big three according to AMR [16]) with the addition of SynQuest

materials.

It was initially thought that there could have been difficulty in getting even access to

SCP system vendors high level glossy brochures. However, the author’s employer is

an MRP II systems house, and thus a potential partner for SCP vendors. The author

has been able to use this influence to source a set of product literature for each of

the major SCP packages.

Don Carmichael Page 35 P5893614 4.3 Commonalities

All SCP packages extend finite capacity scheduling (FCS) concepts into supply

chain and distribution concepts, for example by being able to consider a single

machine capacity bottleneck and it’s impact across a whole supply chain. All the

packages are capable of simultaneous optimisation against a range of factors

including set business goals; particular service level commitments, inventory value

limits, supply limitations and overtime constraints. Some packages talk about using

‘life’ type random algorithms to produce the best optimisation across all constraints.

The better packages have extended their functionality into Transportation

Management, Demand Management and specific ‘improvement’ algorithms for

particular industry sectors. This may mean specific sequence dependant

optimisation algorithms for paint mixing plants say, where if a darker colour follows a

lighter coloured paint less cleaning time is needed than when a lighter colour follows

a darker where a complete clean-down is required.

The more sophisticated packages cope with ‘soft’ penalty optimisation where the

‘best’ plan may be the one where the least amount of overtime payments are made.

Most packages appear to have sophisticated graphics that can visually show the

effect of different ‘what-if’ distribution plans and their effect on cash-flow and

machine capacity. Certainly, most packages allow users to graphically describe

machines, interdependencies and geographical locations of plants and warehouses.

This capability was ably demonstrated by SynQuest at the CIM 97 show at the

Birmingham NEC.

Don Carmichael Page 36 P5893614 Most SCP packages were originally built on UNIX computer operating system

platforms. The reason for this is that SCP packages achieve their characteristically

rapid and near ‘real-time’ scheduling responses by utilising fast stand-alone

computers with huge amounts of Random Access Memory (RAM) memory. In the

early days of SCP developments, UNIX was ideally suited for this. Additionally,

UNIX, in most of it’s versions and variants, had a graphical user interface that can be

used on UNIX workstations.

Most SCP products are ‘client server’ products. This means that there is a powerful

central ‘server’ computer (or computers) performing the intensive calculations and

data transactions for the multiple graphical ‘client’ workstations (or more usually

Personal Computers). This can be imagined as a star configuration with many

‘clients’ connected to the central ‘server’ computer. As the client computers are,

themselves, moderately powerful, some of the computing load is offloaded from the

server onto the client. This is especially the case for intensive graphical tasks.

The reason for the large computer memory requirement is that SCP products place

as much of the business data (sales orders, stock values and transportation

networks etc ) as possible into memory so that the disk drives (which are mechanical

and thus slower than electronic computer memory) are used as little as possible. The

idea is that all of the SCP calculations are performed in memory.

Nowadays, almost all SCP vendors have a Microsoft NT platform offering (although

vendors such as Numetrix have struggled to develop an NT offering). Because

Microsoft NT is usually supplied on high powered PC (personal computer) hardware,

Don Carmichael Page 37 P5893614 and is therefore a mass produced commodity item, there is a cost advantage in

buying ‘NT based software packages for potential SCP customers.

One SCP supplier, American Software (with their product Logility), did have an

AS/400 offering that only seemed to be available in the U.S. American Software also

have a Windows 95 version of their product but this can only be used in specific

scenarios where there are a limited number of transactions.

In SAP’s case, with it’s SCOPE (Supply Chain Optimisation, Planning And

Execution) initiative, the SCP product was designed and developed for NT and is

intended to run on it’s own networked server NT box. The actual SCP product within

the SCOPE initiative is called the APO (Advanced Planner and Optimiser) module.

SAP have developed a memory based environment for the APO module called

‘liveCache’ which manages the large amount of NT memory required.

None of the SCP vendors would quote typical prices for their solutions, reasoning

that the price depended on a series of factors including the number of users, the

scope, the level of integration with an ERP package and who was asking. However,

on further inquiry a common consensus was that SCP vendors generally target

companies with a turnover greater that £200 million. Their argument being that

companies with a turnover less than this figure would find the costs of buying,

implementing and integrating a SCP product excessive.

Don Carmichael Page 38 P5893614 Companies with a turnover higher than £200 million would possibly be outside the

definition of SMEs (Small to Medium size Enterprises) used by ERP vendors. It is

probably fair to say that, at the present, SCP vendors are only targeting large

companies.


4.4 Analysis

The claim for all the SCP packages is that they can and are reducing millions of

pounds from supply chain costs including warehousing, transportation and lost

business. This is achieved by optimising the supply chain in almost real-time by

reacting to major events as they occur, e.g. by re-routing stock or re-planning

transportation routes to meet the company’s defined service levels.

A key issue is the comparison of supply chain optimisation with improvement

methodologies such as those based on ‘lean’ principles. SCP products cannot

reorganise the factory layout, investigate set-up reduction techniques or improve

supplier relationships. SCP products are as helpless as MRP products in that they

are software based and therefore can only work with the information they are given.

SCP systems cannot compete with ‘lean’ solutions and, on occasions, can actually

stop companies from taking the steps towards a ‘lean’ enterprise in instances when

they are seen as a ‘panacea’. An ideal solution would be one where SCP systems

could co-exist with ‘lean’ solutions.

4.5 Future directions

Already, leaders in the ERP / MRP II marketplace have seen the potential of SCP

and are at least partnering with the SCP vendors and, in the case of SAP, writing

their own SCP product to sit on top of their ERP business systems.


PeopleSoft, who didn’t have an ERP product based on MRP principles previously, is

now trying to change the paradigm by publicising their belief that Enterprise

Resource Planning (ERP) systems are dead, to be replaced by Enterprise Resource

Optimisation (ERO) systems based on SCP technology (in PeopleSoft’s case Red

Pepper).

In the short term, SCP systems will really only appeal to larger companies with big

budgets and lots of resources. In the longer term though, medium sized companies

may feel the pressure to purchase SCP systems in order that their customers, the

larger companies, can include them in their supply chain optimisation calculations.

4.7 Conclusions

SCP systems are expanding everyone’s view as to the potential for cost savings and

control over the speed and uncertainty of modern business.

One conclusion from the analysis could be that supply chain planning systems are

providing a ‘crutch’ for companies who cannot face or do not believe in going down

the ‘lean enterprise’ route.


CHAPTER 5 Survey

5.1 Introduction to the survey

Originally, the research part of the dissertation was to have been a series of

interviews with logistics and manufacturing professionals currently dealing with

supply chain issues. Thus the research would have been qualitative rather than

quantitative. However, the literature review turned up a number of surveys examining

supply chain issues in the manufacturing context and the focus of the research part

of the project changed to a questionnaire based approach.

The first of these was a survey by Benchmark Research for Computer Associates

[19], the second a survey by Warwick Business School [20] and the third a 1995

survey by AT Kearney, UMIST and the Institute of Logistics [21]. As these surveys

had already explored similar areas, it was felt that constructing the author’s own

questionnaire would allow the author the opportunity to both compare and contrast

the results obtained in the other surveys and build upon and focus upon the

manufacturing related supply chain issues.

5.2 The survey and the methodology

Before building the survey questionnaire, the author investigated the possibility of

using his (then) employer, Largotim’s resources to provide the logistics and funding

for the 1000 questionnaires that were felt to be required to gain an adequate

response level to the survey. The Sales Director at Largotim agreed but decided that

Don Carmichael Page 42 P5893614 it should be a joint questionnaire; the employer would add certain questions of

interest to the MRP II business onto the supply chain questionnaire. Some of these

questions were to investigate the requirement for third party software additions to the

MFG/PRO business system package. MFG/PRO, from the U.S company QAD, was

Largotim’s MRP II offering.

These questions can be clearly seen in the second part of ‘Appendix 2 - The Supply

Chain Questionnaire’. Questions about desktop integration have only an indirect

relationship with the supply chain systems issues. The questions relating to project

timescales (‘How soon will this be addressed’, 1-5) were related to the employer’s

wish to see if any new business could be developed with the questionnaire

respondent.

This issue of the dual purpose of the questionnaire should be emphasised as it may

have made the questionnaire too complex and unfocused and thus resulted in a

lower quality and quantity of response.

As the author was trying to compare and contrast some previous research by

Robertson, Swan and Newell from the University of Warwick [20], some of the style

of questions were based on the same problem scale as that research, from 1, not a

problem, to 5, a very serious business problem. These can be seen in the second

part of the questionnaire in ‘Appendix 2 - The Supply Chain Questionnaire’.

In building the questionnaire, the author received help from one of the Largotim

marketing team to ensure the questions were unambiguous and without the author’s

Don Carmichael Page 43 P5893614 bias as to the desired answers. The format of the questionnaire was based on an

insurance questionnaire from Barclays Bank which had been extensively market

researched while being developed.

Since the Initial Report the main complication affecting the project plan had been the

extended negotiations and efforts required to get the questionnaire through the

employer’s marketing department. One of the reasons why it seemed difficult to gain

agreement on the format and logistics of the survey became evident only at the

beginning of May, when it was announced that the author’s employer had been

bought out by a large American corporation. This had been distracting the attentions

of the senior management at Largotim.

Other reasons for the delay centered around the legalities of running the prize

competition being used to leverage a higher rate of returns. Largotim’s marketing

department believed that 4% was a good response rate to this type of questionnaire

and that the addition of the prize could boost the response up to 10% giving about

100 responses from a mailshot of 1000. As Largotim provided manufacturing and

business systems to one of the bigger Formula 1 racing teams, Williams Grand Prix

Racing, the prize offered was two tickets to a test session at Silverstone as a guest

of Williams and Largotim.

This was the first time the employer had actually run a competition open to external

scrutiny and there was some hesitancy as to how prize competitions should be run.

Don Carmichael Page 44 P5893614 The database used by the author’s employer was a ‘random’ one bought from Dun &

Bradstreet two years ago. The age of the database was a concern as names,

addresses and job titles of the questionnaire’s target audience would not be

particularly accurate. The targeted audience was Managing Directors, Operations

Directors and Senior Production Managers. The ‘randomness’ of the database

contacts could not be validated as the marketing department could only be certain

that the database held at least five thousand manufacturing companies which they

believed were represented across all business sectors and across all regions of the

UK in equal proportions. This could not be tested and so should be taken into

account in the analysis of the results.

The questionnaire was tested by two of the author’s best customer contacts. The

contacts, one being an IT Manager in a Tier 1 automotive supplier and the other a

Business Analyst in a large communications company, were initially informed of the

intended purpose of the questionnaire analysis and were then given the chance to

comment on the both the format and the questions within the questionnaire.

Initial responses from the two ‘testers’ revolved around issues on the complexity of

the questionnaire and specific questions which were felt to be missing. One of the

‘testers’ felt that question 2 on the questionnaire, regarding the use of third party

warehousing, needed to split into three questions looking at the proportion of third

party warehousing being used. In retrospect, of course, this type of feedback only

added to the complexity of the questionnaire.

Don Carmichael Page 45 P5893614 The complexity issue was again raised with the Largotim Sales Management but

there was a lack of interest. The Marketing Manager was keen to progress with the

mailing of the existing questionnaire, more as a method of completing the task which

she was beginning to regret she had agreed to.

Following an update to the questionnaire based on the two customer responses, the

contacts were then asked to fill in the questionnaire. The results were then analysed

to see if any further improvements could be made to the questionnaire. Their

responses were mapped onto a single spreadsheet designed by the author to allow

ease and accuracy of results recording and then later ease of analysis.

After some experimentation a template version of the questionnaire was built. The

template version included more and clearer numbering to improve the accuracy of

the recording of the returned questionnaires onto the spreadsheet.

Finally, once a covering letter had been designed, a Freepost address set-up and

the mail merge addresses loaded out of the marketing database, the mail shot

began. This happened on Wednesday 14th May.

Because of the prolonged design and planning period for the questionnaire, it was

decided that a window of only one and a half weeks should be allowed for

responses. This was managed by emphasizing a closing date for the prize

competition as the 23rd May. It was felt by members of the marketing department that

if the respondent did not fill in the questionnaire either the day of receipt or the day

after the likelihood was that the questionnaire would probably be binned or put to the

Don Carmichael Page 46 P5893614 bottom of an in-tray. As a reply paid (Freepost) envelope was included with the

questionnaire there was minimal effort required from the respondent after the

questionnaire was filled in, i.e. folding into the envelope and posting into a mail tray.


5.3 Results of the survey

Unfortunately, there was a very low response rate to the survey. There were 21

responses from the 1000 questionnaires posted. There were various reasons

hypothesized as to the reasons for this but they could be summarised as the :

• complexity of the survey

• length of the survey

• negativity of the questions

• short response time

• lack of profile of the company sending the questionnaire

• age and inaccuracy of the mailing list

• requirement for the respondent to give their name and address

• lack of telephone follow-up

A major psychological factor was the questionnaire’s requirement for respondents to

rate the severity of particular business problems. From the respondent’s viewpoint

this could have been seen as a reflection on the individual or possibly a criticism of

the respondents company. This would give weight to the argument that the questions

should have been phrased in a more positive manner.

In addition to the above, some companies have a policy of not filling in

questionnaires. On investigation, most of these companies believe that time

consumed by individuals interpreting then researching, investigating and finally filling

Don Carmichael Page 48 P5893614 in the questionnaire does not warrant the effort or any expected research gains.

There was also the suspicion that these particular companies trusted neither the

promises of anonymity given in the questionnaire nor the authority or standing of the

company requesting the information.

This may have been different if the questionnaire had been compiled by say one of

the ‘Big 5’ consultancies and the research perhaps destined for a focused

benchmarking tome.

The randomness and suitability of the mailing list has been questioned elsewhere in

this project but it is worth noting here that the best surveys, analysed by the author,

used mailing lists from two sources:

• either the Institute of Operations Management’s membership list;

• or a Management Consultancies client list.

The competition part of the survey produced a number of negative affects being that

some of the potential respondents were sceptical about a questionnaire purporting to

be anonymous and yet seeming to trick the respondent into giving their name,

address, title, company and telephone number.

Also, some respondents did not believe the legitimacy of the Williams Grand Prix /

Silverstone prize draw. Largotim, being a mid-range MRP II vendor and thus not

Don Carmichael Page 49 P5893614 having a vast marketing budget or market presence, was probably not associated

with Williams Grand Prix.

On reflection, the author’s experience is that many sales ‘pitches’ start with a

telephone caller asking if the respondent would mind taking part in some

independent research questionnaire. These generally turn into sales ‘pitches’ once a

few qualifying questions have been answered and the respondent either realises

they are speaking to, or the telephone caller reveals themselves as, a telesales

person

The likely motive of the Sales Management who influenced the format and agreed

the logistics of the questionnaire was to use the contact list generated and a brief

analysis of a few qualifying questionnaire responses to drive a telesales campaign.

The reader can rightly assume from this that the Marketing department reported

directly into the Sales Management and thus there was never any intention of

guiding the questionnaire to simply produce some focused yet anonymous research

that might be fed into the MRP II research and development program.


Question Nmbr I II III IV V VI VII VIII

Response Format Nmbr Nmbr Nmbr Nmbr Nmbr Option £ Option

Respondents

1 2400 700 10 15 30 Globally 220M Industrial/Electronics2 1400 700 8 8 8 Globally 80M Automotive3 550 3 9 0 0 Internat. 72M Process4 5250 2100 3 2 5 Globally 640M Industrial/Electronics5 400 150 2 2 2 Globally 50M Medical6 135 135 10 17 17 Inernat. 150M Industrial/Electronics7 1700 1200 4 4 9 Globally 150M Industrial/Electronics8 2250 1400 9 3 4 Internat. Food & Beverage 9 1814 290 17 17 Globally 291M Industrial/Electronics

10 180 180 1 1 Internat. 7.5M Automotive11 800 200 4 Internat. 100M Consumer Packaged Goods 12 1100 125 1 1 47 Nationally 39M Food & Beverage 13 1000 650 4 2 3 Nationally 120M Consumer Packaged Goods14 312 304 3 3 3 Internat. 57M Industrial/Electronics15 430 400 1 3 2 Internat 230M Food & Beverage

16 140 135 1 1 1 Globally 10M Industrial/Electronics

17 750 420 4 4 4 Nationally 280M Food & Beverage

18 2500 200 16 16 Nationally 1500M Medical

19 500 220 1 2 Globally 200M Medical

20 275 190 1 2 1 Globally 20M Industrial/Electronics

21 410 390 3 0 1 Nationally 40M Automotive

Table 5.3.0.1 Tabular summary of questionnaire results with respondent number versus question number with answers. (1 of 5)


Question Nmbr 1a b 2a B c 3 4 5 6 7 8 9a 9b 10 11 12a 12b 13

Response Format Mfg % Dist % Y/N Nmbr % Y/N Y/N Y/N Y/N Y/N Y/N Y/N Y/N Y/N Y/N Y/N Y/N Option

Respondents

1 90 10 Y 5 20 N N Y Y Y Y N Y AS4002 95 5 N N Y Y Y Y Y Y AS400 3 100 0 N Y N Y N Y N Y N N N N N Mainframe4 70 30 N N Y Y Y N Y N Y UNIX5 75 25 N N N Y Y N N N UNIX 6 85 15 N N N Y N N N N UNIX 7 100 0 N N N Y Y Y Y Y UNIX/NOVELL 8 95 5 Y 4 25 Y Y Y N Y Y Y N N N N N Windows NT9 100 0 N N Y Y N N N N N Mainframe

10 100 0 N N N Y Y N N N Windows NT 11 100 0 Y 2 10 N Y Y Y Y Y Y AS/400 12 50 50 N Y Y Y N Y N Y Y N Y Y Windows NT 13 8 20 N N N Y N N Y N N AS/40014 100 0 N N Y Y Y N N N Y AS/40015 84 16 Y 4 5 N Y Y N Y Y N Y UNIX

16 40 5 N N Y Y Y N Y N N AS400

17 80 20 N Y - - - - N Y N N N Y N UNIX

18 0 100 N N Y Y N N N N N UNIX/Windows NT

19 0 20 Y 1 100 Y N Y N Y Y Y Y N N N Y Windows NT

20 10 90 N N N Y Y Y N Y Windows NT

21 95 5 Y 1 5 N Y Y N N Y UNIX



Question Nmbr 14a b 15a b 16a b 17a b 18a b 19a b 20a b 21a b 22a b 23a b

Response Format 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5

Respondents

1 3 2 2 5 3 2 4 4 4 3 2 4 2 4 4 4 2 4 2 52 5 1 5 1 2 2 2 1 4 1 4 1 5 1 4 1 4 1 4 13 1 1 1 1 1 1 6 1 6 1 1 1 1 1 1 1 6 1 1 14 1 1 1 1 2 2 1 1 1 1 3 3 2 2 3 4 1 2 1 15 3 4 1 1 1 1 2 1 2 5 1 5 2 5 6 5 1 1 2 16 2 5 2 2 1 2 2 2 2 5 2 5 2 5 1 5 1 1 2 57 3 2 1 6 1 6 3 2 1 3 2 3 2 3 38 3 3 3 4 1 1 2 2 1 1 1 1 2 2 6 5 1 1 2 59 3 4 3 4 2 5 1 5 1 5 1 5 1 5 1 5 2 5 1 5

10 3 4 4 4 3 4 3 4 4 4 3 4 3 4 3 4 3 4 4 411 1 1 4 2 1 1 1 1 1 1 6 1 3 3 1 1 2 2 1 112 1 1 1 1 1 2 1 1 2 3 2 1 3 3 2 2 1 1 1 213 2 3 1 1 1 1 3 4 1 1 1 1 1 1 1 1 2 3 3 414 3 4 2 2 3 1 2 4 1 1 3 4 1 1 3 4 3 2 1 115 4 2 3 2 1 1 3 4 3 2 4 2 2 4 4 2 2 2 4 2

16 4 2 3 2 1 1 1 1 2 2 1 0 1 0 6 0 3 4 3 3

17 4 4 4 4 2 5 4 5 4 3 3 5 2 5 3 5 3 3 3 5

18 6 5 3 4 2 2 3 2 3 2 3 2 6 5 6 5 3 2 3 4

19 3 4 2 3 1 5 2 2 2 1 6 6 6 2 2 2 3

20 2 2 1 1 1 2 1 1 2 2 1 1 1 1 1 1 6 6 3 2

21 1 1 2 4 2 4 1 1 1 1 1 5 6 5 6 5 3 2 2 5



Question Nmbr 24a b 25a b 26a b 27a b 28a b 29a b 30a b 31a b 32a b 33a b

Response Format 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5

Respondents

1 3 3 1 5 1 5 3 4 3 4 1 5 1 5 1 5 4 2 3 32 1 1 2 2 6 5 4 1 4 1 4 1 4 1 4 2 4 2 4 13 1 1 6 1 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 14 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 15 1 1 2 1 6 5 1 1 2 2 3 1 1 5 2 5 2 5 6 56 1 1 2 2 1 5 2 5 2 2 2 5 1 5 1 5 2 5 2 57 6 2 2 1 2 2 3 2 2 2 6 1 3 2 6 8 1 1 1 1 6 5 1 5 1 1 1 1 6 5 6 5 6 5 6 59 6 5 2 4 6 5 1 5 1 5 2 2 1 1 1 1 1 5 1 5

10 3 4 3 4 6 5 2 2 3 2 3 2 1 5 3 2 3 2 4 211 1 1 6 6 6 1 1 1 1 1 1 1 1 1 1 6 12 1 2 2 2 1 1 1 1 2 3 1 2 2 2 1 1 1 1 1 213 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 4 1 1 1 114 3 4 2 2 1 1 1 1 2 2 2 2 3 4 1 1 3 4 1 115 5 2 1 1 3 2 3 2 3 1 3 1 1 5 1 2 1 2 1 2

16 2 2 1 0 1 0 3 2 3 2 4 2 1 0 3 3 3 3 3 3

17 3 2 2 2 1 1 1 1 3 2 3 2 1 1 3 4 4 2 2 5

18 4 2 3 2 2 5 3 2 3 2 3 4 6 5 2 2 1 1 2 5

19 2 2 6 2 2 6 3 4 6 6 6 6 6

20 1 1 1 1 2 3 3 2 3 2 1 1 2 1 2 2 3 2 2 2

21 2 5 1 1 6 5 6 5 2 2 2 2 2 2 2 1 2 2 22



Question Nmbr 34a b 35a b 36a b 37a b 38a b 39a b 40a b

Response Format 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5 1-6 1-5

Respondents

1 4 4 4 4 4 4 3 3 3 4 4 3 4 22 4 1 4 2 4 1 4 2 5 1 4 1 5 13 1 1 1 1 1 1 1 1 1 1 1 1 1 14 2 5 2 2 1 1 1 1 1 2 2 2 1 15 6 5 2 5 4 2 1 5 2 5 6 5 2 56 1 5 2 2 2 2 3 3 2 5 2 5 2 57 6 3 2 4 2 6 2 3 6 2 38 1 1 1 1 3 2 3 2 1 1 1 1 6 59 1 1 1 1 1 2 6 5 1 2 1 1 1 1

10 2 1 3 4 4 2 3 4 3 4 6 5 3 211 6 6 3 4 1 1 4 4 1 1 2 512 1 1 1 1 1 1 1 1 2 2 2 2 1 113 1 1 1 1 3 4 1 1 1 1 1 1 1 114 1 1 3 4 3 2 3 2 3 2 2 2 3 315 5 3 3 2 3 2 3 2 4 2 3 2 4 2

16 1 0 2 4 3 2 4 2 4 3 2 2 3 2

17 1 1 1 1 4 4 2 5 3 2 3 5 4 2

18 6 5 2 2 6 5 6 5 3 2 6 5 6 5

19 2 1 3 3 3 5 1 5 3 4 2 3 1 5

20 6 6 3 2 2 2 2 2 3 2 2 2 3 2

21 6 5 2 2 2 2 1 1 1 1 6 5 2 2

Table 5.3.0.5 Tabular summary of questionnaire results with respondent number versus question n

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