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The New Era in Managing
Supply Chains- Lessons from
Industrial Dynamics
Submitted to
20" International Conference of the System
Dynamics Society
April 10, 2002
J ohn Barton
Director
Marshall Place Associates
Level 4, 114 William Street
Melbourne, 3000
Australia
Tel: +61 3 9640 0099
Fax: +61 3 0640 0099
Email: jabarton@ ozemail.com.au
The New Era in Supply Chain Management- Lessons from Industrial Dynamics
The New Era in Managing Supply Chains- Lessons from
Industrial Dynamics
Outline
Developments in technology have led to a revolution in how we can conceive
and manage supply chains. Despite the success of companies like Dell, and
the availability of an extensive literature and of consulting services etc, the
performance of many supply chains has not improved.
System Dynamics in its earlier guise as Industrial Dynamics has much to offer
in understanding this apparent dilemma. Evidence suggests the lessons of the
Beer Game are as relevant today as they were 40 or 50 years ago!
This paper outlines recent developments in supply chain thinking and
demonstrates the important contribution that System Dynamics can make to
resolve a number of current supply chain debates.
Key Words
Supply chain management; beer game effects; system dynamics; action
learning; 6-Sigma; knowledge management.
Introduction
| recently had my bathroom renovated necessitating the installation of a new
shower screen. After considerable search across a bewildering number of
options of designs and price etc, | settled on a reasonable quality screen from
what seemed to be a reputable company.
Following a call to the screen company, a salesman visited to do a “measure
and quote”. Following this visit a deposit was paid and the company
contracted to make and install the screen within 7 to 10 working days from the
receipt of the deposit. However, before anything could proceed a person from
the screen manufacturer had to visit to make exact measurements. This
occurred two days after the visit from the salesman. Unfortunately the
measurer found a problem in the design the salesman had set out (the screen
needed to be 10 cm higher!), so we had to contact the salesman to have the
order specifications changed. This didn’t present any problems and the
salesman agreed to organise the change with the manufacturer. Several days
passed and on the last day of the contract period the installer arrived to install
the screen. The only trouble was that the screen was made to the original
(smaller) specifications! Following the refusal of a generous offer from the
factory manager to supply this screen at half the quoted price, plus a supply of
cotton wool to help ease the impact every time | struck my head on the top of
the screen, we were informed it would take a week for the manufacturer to
obtain the new sheets of plate glass required to make the screen. Perhaps
foolishly, | agreed and a week later a new screen arrived. The trouble this
time was that the two screens had got mixed up and so this delivery had two
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 2
panels from the original specification and one panel from the revised order.
The next day the correct panels were finally assembled and installed to our
satisfaction, albeit eight days outside the contract period of10 days.
Now, it will be obvious to most that there was a problem with communication
between each of the individuals involved in this saga- the salesman, the
manufacturer, the glass supplier, and the installer. Furthermore, you may
have also guessed that they were all individual contractors attempting to
integrate their contributions to the supply chain. One can only wonder on the
variability of successful installation times or some other performance
measure. But it seems likely that it will be much greater than what seems
reasonable.
On the surface this supply chain should operate very efficiently, and
effectively- itis based on the “demand pull” principle as distinct from “supply
push”, largely eliminating the need for inventories; it uses market competition
to select from a large number of contractors; given the lead times on house
construction approvals and renovations, market demand for screens is
probably fairly predictable; screen technology is relatively stable; raw
materials and supplies are locally available; simple computer systems are
exist to track orders etc; and in general terms, this market situation could be
described as being reasonable mature.
In fact this story highlights a number of characteristics of many supply chains
as illustrated by recent examples from industries as diverse as automotive
manufacturing, telecommunications, and agriculture- see Figure 1.
Anecdotal evidence suggests that typical industry reactions to these types of
supply chain problems include:
« A demand for improved forecasts resulting in the application of
increasingly sophisticated time series and econometric methods.
¢ Setting targets for both levels of performance and variability that are
beyond the capability of the existing supply chain system and then
driving short term increases in performance under the threat of
sackings
¢ Increased attempts to centralise the control of the supply chain, despite
the availability of technologies to facilitate more decentralised and
flexible supply chains.
* Attempts to optimise parts of the supply chain without due
consideration of the whole.
¢ Increased collection of data and publication of largely unrelated
statistical reports.
In fact, these responses are largely maladaptive and exacerbate the situation.
This outcome is confirmed by, Marshall L. Fisher (1997), who, following ten
years of supply chain research observes that:
“Never has so much technology and brainpower been applied to improving
supply chain performance. Point-of-scale scanners allow companies to
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 3
capture the customer's voice. Electronic data interchange lets all stages of
the supply chain hear that voice and react to it by using flexible
manufacturing, automated warehousing, and rapid logistics. And new
concepts such as quick response, efficient consumer response, accurate
response, mass customisation, lean manufacturing, and agile
manufacturing offer models for applying the new technology to improve
performance.
Nonetheless, the performance of many supply chains has never been
worse. In some cases, costs have risen to unprecedented levels because
of adversarial relations between supply partners as well as dysfunctional
industry practices such as the over reliance on price promotions”.
So we can conclude that the circumstances of the “Beer Game” are alive and
welll". So what goes wrong and can System Dynamics help?
Bullwhip Effects: Motor Industry
Orders
| Ws =
1 Also see Lee, Padmanabhan, and Whang, 1997
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 4
Annual Production of Wheat in Australia 1950-2000
(by 1000 tonnes)
30,000
25,000
20,000
15,000
10,000
5,000
0
a
Figure 1.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics
Recent Developments in Supply Chain Thinking
Supply chain management has a great strategic importance. For example, in
the motor vehicle industry, the urgency to better manage supply chains is
being driven by the factors including:
1. Competitive pressures arising from a global reorganisation of the
industry arising largely from a current over-investment in the industry. A
1998 estimate sets excess global capacity at nearly 30%.
2. A trend towards mergers and globalisation of suppliers and a shift
towards modularisation of components.
3. A perception of a changing manufacturing industry dynamic that
involves a cycle of shifts between vertically integrated businesses and
horizontally/ modularised businesses.
Increasing speed of product and supply chain cycle times
Technological changes in information technology and communications.
Technology changes in the motor industry, particularly relating to
telematics and engine design. (US estimates indicate that telematic
equipment installed in new cars sold will rise from 18% in 1999, to 90%
in 2004 (nearly 15 million cars).
7. The effects of changing energy prices and environmental concerns, for
example, greenhouse gases.
OS OEP
These types of forces demand a re-think on how we approach supply chain
management.
The concept of a supply chain has changed from the simple sequential view in
which the various stakeholders add value along the supply chain, to a more
contemporary view that supply chains are value constellations or networks
centred around the consumer. Furthermore, it is now realised that total supply
chains extend well past the supplier and customer boundaries, into supplier
markets and the secondary after-markets for goods. See Figure 2.
Generic Supply Chain
~
Forecasting & tC) Corporate Strategy
Allocations —
Al
[Productidn/_, bistributidn
Processing >| Markets
\Supplies
Figure 2. The Traditional Supply Chain
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 6
Accordingly, the supply chain can be defined as the network of organisations
that develop new ideas, source raw materials, manufacture products (or
develop services), store and distribute goods, and ultimately deliver the
products and services to customers and consumers.
The objective of supply chain management is to achieve a customer outcome
from the supply chain that is greater than that possible from just managing the
individual parts- we want the whole to be greater than the sum of the parts.
Clearly, supply chain management is not only about the operational logistics
of manufacture and distribution, a perspective recognised by the established
logistics industry- for example, a prominent logistics research group from
Michigan State University identify ten “Megatrends that will revolutionise
Supply Chain Logistics”:
1. Customer service to relationship management
2. Adversarial to collaborative (alliances etc)
3. Forecast to endcast
4. Experience to transition strategy (moving past experience curves)
5. Absolute to relative value
6. Functional to process integration
7. Vertical to horizontal integration
8. Information hoarding to information sharing
9. Training to knowledge-based learning
10.Managerial accounting to value-based management.
Consequently, organisations that have traditionally structured along functional
lines such as operations, distribution, marketing, finance and human
resources- the “functional silos”- are being forced to shift much more towards
organising around their supply chains. For many organisations this is clearly a
difficult task because power structures, operating systems and reward
systems have evolved that are centred on the traditional functions. This is less
of a problem for newer organisations that have self-organised around supply
chain projects to start with. This is the case in the information technology
industries. Consequently, many of the lessons to be learned come from this
sector.
Poirier (1999) identifies four stages of change organizations need to move
through to improve supply chain management:
1. The improvement of individual process along the supply chain. The
emphasis is on sourcing and logistics.
2. Coordinating the individual improvements to improve the chain as a
whole. The emphasis is on internal excellence.
3. Developing a network and emphasising the management of alliances
and partnerships.
4. Establishing an industry leadership role and being in a better position
to leverage off the information structures that reside in the network.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 7
The movement through these stages is closely associated with the degree of
uptake of information technologies and the adoption of e-business and e-
commerce technologies.
Two recent contributions to supply chain management are of particular
significance to this discussion because the first emphasises the importance of
thinking about a single design principle for the whole supply chain, and the
second emphasises supply chain dynamics and the role of knowledge
management:
1. Fisher (op cit) conclusion that the problems of supply chains are
associated with mismatches between the types of supply chain-
demand-pull (requiring product effectiveness) Vs supply-push
(requiring logistical efficiency)- with the wrong type of product.
Consequently, Fisher advocates strategies based on classifying
products as being either functional or innovative. Functional products
are products like groceries that have stable, predictable demand and
long lead-times. They usually incur low margins and are subject to
intense competition driving suppliers into various forms of
differentiation (Fisher quotes 26 types of toothpaste from one supplier).
Innovative products require consumers to change some aspect of their
lifestyle and are associated with short life-cycles.
Most problems arise when suppliers emphasise logistical efficiency
when attempting to supply innovative products. Consequently, they
need to decide whether to simplify the product back to a functional
level, or adopt strategies that reduce uncertainty, cut lead times and
improve flexibility, and/or develop better hedging policies.
2. Fine's emphasis on supply chain dynamics based on his concept of
“clockspeed”. (Fine, 1999; Fine, Vardan and El-Hout, 2002). Fine et al
argue that, given the speed with which competitive advantage is won
and lost in today’s markets, “on-going value chain assessment and
design at the corporate level have become a necessity”.
Fine applies the concept of “clockspeed”, that is, the rate of evolution of
products, processes and customer requirements to argue that “the
faster the industry clockspeed, the shorter the half-life of any given
competitive advantage. A company’s real core capability- perhaps its
only sustainable one- is its ability to design and redesign its value chain
in order to continually find sources of maximum, albeit temporary,
advantage”.
Fine etal then develop a “Strategic Value Assessment (SVA) model” to
help identify (qualitative) contributions to customer value along the
supply chain and, by correlating these to an economic performance
measure, establishes a decision criteria for decisions such as
outsourcing/in sourcing supply chain processes. Importantly, the SVA
model distinguishes between knowledge assets- “those related to the
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 8
design and engineering of products, processes and services- and
supply assets relating to “manufacturing and delivery capabilities”.
By advocating the adoption of different internal structures depending on the
nature of customer demand, Fisher's strategy provides an example of the
application of the endogenous principle advocated in system dynamics-
supply chains can be made more robust by adopting appropriate internal
structures and policies. But, on his own admission, Fisher’s somewhat static
framework tends to break down in the dynamics of product innovation,
competition and product differentiation. These issues are addressed by Fine’s
clockspeed dynamics and his SVA tool, and lead directly to the need for
simulation modelling.
Fisher also identifies the very real problem of “the adversarial relations
between supply chain partners”. This points to the need for the adoption of an
appropriate action learning framework within which to manage supply chain
relationships: an essential aspect of the System Dynamics method.
Lessons from Industrial Dynamics.
In his preface to Industrial Dynamics, Forrester (Forrester 1961)? describes
Industrial Dynamics as:
“...a way of studying the behaviour of industrial systems to show how
policies, decisions, structure, and delays are interrelated to influence growth
and stability. It integrates the separate functional areas of management-
marketing, investment, research, personnel, production, and accounting. Each
of these functions is reduced to a common basis by recognizing that any
economic or corporate activity consists of flows of money, orders, materials,
personnel, and capital equipment. These five flows are integrated by an
information network. Industrial dynamics recognises the critical importance of
this information network in giving the system its own dynamic characteristics”.
After establishing the basic philosophies and tools of Industrial Dynamics,
Forrester demonstrates his approach using two models:
* asimple distribution system involving inventories and flows of orders
and goods, extended to include “a simple aspect of the market and
sales effort” (Ch 2, 15 and 16)
* a model that explores the interaction between a customer-supplier loop
and a supplier-labour loop, inclusive of money flows (Ch 17,18),
? This is not to suggest that current versions of System Dynamics are not important, but to
recognise that Forrester’s early work was essentially stimulated by what we now identify as
supply chain problems. It is possible that Industrial Dynamics contains a number of insights
that have been past over by the broader applications of System Dynamics. One example is
the explicit articulation by way of alternate symbols for each of the five flows. But
fundamentally, there is a certain irony in pointing out that an arguably superior approach to
managing supply chains has been available for over 40 years.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 9
Possible extensions are discussed in Ch 19 to include consideration of market
dynamics, growth, commodities, research and development, top management
structure, money and accounting, competition, forecasting and long-range
planning, and industry models’.
Of particular interest on this occasion‘ is Forrester’s treatment of information.
While obviously stimulated to look in this direction from his background in
servo-mechanism theory, Forrester is careful to make the distinctions
between an economic/industrial system and a purely mechanical system:
“our economic systems have a “distributed error function” represented by the
individual goals of many participating persons”. (as compared to a
servomechanism that is often treated as having a single “error function”, ie,
the difference between actual and desired results. “The control function is
likewise dispersed, so that it exists in part at each decision point in the
system” (p61).°
Elsewhere Forrester makes the distinction between numerical
data/information, written information, and mental information, and, pre-
empting a key aspect of knowledge management, stresses the importance of
using mental information. He stresses the information feedback nature of
economic and industrial systems and the need for models to preserve closed-
loop structures. It is this feature that gives rise to ‘the instability that is the
counterpart of “hunting” in mechanical servomechanisms”. He goes on to
discuss the importance of time relationships (delays), amplification and
information distortion.
In Appendix J , Forrester discusses the value of information and demonstrates
the way in which a changed information flow can affect the system. He points
out that inefficiencies can occur when random-noise variation in market data
is “imposed directly on the production system” encouraging managers to
stress short-term decisions- note Fisher’s comment about point of sale
scanning. His models indicated that system improvements “did not result so
much from changing the type of information available or its quality nearly as
much from changing the sources of information used and the nature of the
decision based on the information”(p427). This is demonstrated in explicit
terms by using his Ch15 model to show that when data on retail sales is
available at the factory level, less than expected improvements are achieved’,
He suggests that a “detailed study of such a system might lead to the
conclusion that the solution to better system behaviour lies not in more
information at the factory but rather in a change in the operating policies of the
distribution system” (p429).
These observations can be further understood in knowledge management
terms by reference to Figure 3 which shows the relationships between data,
information, knowledge and decisions, and their interdependence with mental
> A research students dream section!
* See later discussion of knowledge management.
> This suggests some form of Agent Based Modelling.
® This point can be validated when playing the Beer Game by giving participants customer
order data from week 30 onwards.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 10
models (world views). Most importantly, System Dynamics models make
“world views” explicit and clarify decision assumptions.
The knowledge creation process:
A Feedback View
interprets Worldview
Events > Data > Information > Knowledge > Wisdom
JL
Actions Decisions
Figure 3.
When compared to one of the better researched studies of “value stream
management” (Hines, Lamming, J ones, Cousins & Rich, 2000), Industrial
Dynamics provides at least two distinct advantages- an integrated framework
and a dynamic framework.’ In fact Hines et al propose the use of System
Dynamics as a tool for studying demand amplification, but fail to recognise the
wider implications of the method. In particular:
¢ Mapping supply chains using the stock-flow structure provides a
superior means of representation than either the often-used data flow
diagrams associated with information systems, or the schematics and
time-delay diagrams used in lean manufacturing. The reason for this is
that System Dynamic’s diagrams identify material and resource flows
as well as information and decision structures. Consequently, they
more clearly capture the economics of the supply chain as well as
logistics etc.
¢ Simulation modelling addresses supply chain logistical problems of
balancing inventories etc and understanding the impacts of delays and
policies in a much more holistic way.
T Hines et al define seven value mapping tools- Process activity mapping; supply chain
response matrix; production variety funnel quality filter mapping; demand amplification
mapping; decision point analysis; and physical structure by volume and value. These tools
are then correlated with seven forms of waste identified with Toyota’s lean manufacturing
system- overproduction; waiting; transportation; inappropriate processing; unnecessary
inventory; unnecessary motion; defects.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 11
* The system dynamics action learning structure (see Figure 4) helps
address the problems of stakeholder communication and information
sharing. Indeed, some of the biggest improvements in supply chain
management have resulted from learning and growth relating to
improved communication processes and knowledge management’,
A SYSTEM DYNAMICS ROADMAP WITH 4 LEARNING CYCLES
CONTINUOUS IMPROVEMENT - EVALUATION CYCLE
MENTAL MODELS
MODEL VALIDATION CYCLE
Figure 4.
In summary, Table 1 correlates recent developments in supply chain
thinking with Industrial Dynamics method.
® The learning structure inherent in the Toyota production system has been described as the
“DNA" of the Toyota system- see Spear and Bowen, Decoding the DNA of the Toyota
Production System. HBR Sept-Oct 1999.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 12
Table 1.
Supply Chain Development
Industrial Dynamics Response
Recognition of strategic importance
Industrial Dynamics and its extent forms in
System Dynamics and Strategy Dynamics
etc, complement the ‘What, How, & For
Whom” questions of traditional (static)
strategic thinking by adding the “When”
question using its dynamic framework .
The value constellation concept.
Clearly Industrial Dynamics maps material
flows in an episodic manner, so to this
extent it reinforces the “linear view” of
supply chains. Buta little reflection shows
that the feedback structure rapidly breaks
down this perception and, as becomes
more graphically apparent, quickly adopts
the persona of a value constellation when
causal maps are developed.
Extension past the traditional logistics view
of supply chains with an emphasis on
procurement, production and distribution to
include research and development, tertiary
suppliers, customer relations and after
market activities.
Forrester and subsequent work by Roberts
demonstrate an early concern with aspects
such as research and development and
customer dynamics. The methodology of
Industrial Dynamics is flexible as to what
part of the industrial system is included and
provides for exogenous effects for what is
excluded. Eg, compare the exogenous
effects of customer decisions in the Beer
Game with models that make customer
effects endogenous. Forrester’s work is one
of the most dramatic attacks on the silo
mentality of functional management.
Poirier’s four stage change process
These stages can be considered as action
learning cycles as described in Figure 3.
Fisher's model based on the distinction
between supply-push and demand-pull
This provides an example of the
“endogenous view” in which system
structure is designed for robustness.
Fine’s concept of “clockspeed”
As Fine acknowledges, System Dynamics
in an ideal framework within which to
understand the dynamic implications of
clockspeed.
Fine’s articulation of knowledge and
supply, and the resulting construction of
SVA.
Forrester pre-empts much of the current
discussion of knowledge management by
emphasing the importance of tacit
knowledge and by providing a framework
and learning process for making tacit
knowledge explicit. His use of an
information networks to integrate flows of
money, orders, materials, personnel, and
capital is central to the Industrial Dynamics
method.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 13
Can We Help Our Shower Screen Supplier? Yes We Can!°
Applying the method of Industrial Dynamics to the case of the shower
screen supply chain, possibly complemented with some of the summary
charts advocated by Hines et al and Fine etc, provides a comprehensive
framework for better managing this supply chain. As an indication of the
method, only the first couple of stages of the System Dynamics roadmap
will be applied.
Stage 1. Formation of an action learning team?” and definition of problem.
This stage involves getting to key stakeholders together and discussing
key performance measures for the supply chain. This may be based on
Balanced Scorecard thinking, but in the first instance may concentrate on
meeting contracted delivery times, quality measures and financial
performance. Consideration of related reference modes and competitive
performance can then provide the basis for establishing gaps between
actual and desired performance.
Stage 2. Mapping the existing supply chain.
Figure 5 describes a first attempt to map the supply chain. In auditing this
map, inclusion of money, orders, materials, personnel, and capital flows
need to be checked. Clearly this map is deficient in this respect- only order
and material flows are included. Cash flows will be critical to this system
and need to be included. Capital and personnel flows may be less
significant at least in the short run.
Similarly, delays and their possible variability should be carefully
measured and cumulative delays graphed against project time elapsed.
To more clearly articulate stakeholder accountabilities it may be worth
colour coding key decisions for which particular stakeholders are
accountable, This has the further advantage of making individual
stakeholders aware of the required information flows relevant to their
decision making.
At the conclusion of this stage, a basic framework for on-going
communication has been established. The ground is now set for applying
tools such as Fine’s SVA framework, and moving towards completing the
simulation model ready for starting Stage 3.
Conclusions.
The problem of improving the management of supply chains has been
presented and recent developments in supply chain thinking presented.
After reviewing key elements of the Industrial Dynamics method developed
by Forrester in the 1950s and 60s, a case is made that this methodology
° The model and further discussion in this section are still to be completed.
1 If the language of “action learning” seems inappropriate, the DMAIC problem solving
process related to the 6-Sigma approach should be considered.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 14
provides both a dynamic and integrated approach to supply chain
management.
This contrasts with the problems of the reductionist approach to managing
supply chains with its emphasis on optimisation of parts, static analysis,
and inflexible centralised control aimed at trying to keep the parts together
but with an inadequate requisite variety to succeed in the long run”.
The Industrial Dynamics/ System Dynamics approach has the additional
advantage that it establishes the foundation for a knowledge management
approach to managing supply chains.
Percent reorders
Time to comple®
Percenterror
Pie er Discalp rate
nesies Production Comfleted Installed
X Orders
Messe rae: letion rate instar
Installers
installations per installer per day
eto measure Plate glass in productign
Sales Rate thr Poyduct X 2
Glass ordebyate Glass delitery rate
Market share
BCH | nanersacien
Build Rate
Production time
Time to order
Renovalfon rate
Figure 5. Initial Stock-Flow Diagram
1 walmart is possibly one organization that has been successful in centralising control.
The New Era in Supply Chain Management- Lessons from Industrial Dynamics 15
References:
Fisher, Marshall L. What is the Right Supply Chain for Your Product?
HBR March-April, 1997 99 105-116
Forrester, J ay. Industrial Dynamics. MIT Press. 1961.
Hines, Peter; Lamming, Richard; J ones, Dan; Cousins, Paul; & Rich,
Nick, Value Stream Management? rentice Hall 2000.
Lee, Hau L, Padmanabhan, V and Whang, Seungjin. The Bullwhip Effect
in Supply Chains. Sloan Management Review. Spring 1997. Pp 93- 102
Poirier, Charles C. Advanced Supply Chain Management, Berrett-
Koehler. 1999.
Sterman, J ohn. Business Dynamics. McGraw Hill-Irwin. 2000
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