Florian Klug
Department of Business Administration, University of Applied Sciences Munich, Germany
[email protected]
Balancing inventories between the requirements of the customer and production capacity is the
objective of managing the supply chain. Operations management has to reconcile policies, which meet
a varying and uncertain demand with the minimum of tied-up inventory (Riddalls and Bennett, 2001).
Supply chains are expected to respond rapidly, effectively and efficiently to changes in the
marketplace coupled with minimum reasonable inventory (Towill, 1994). This involves having the
correct amount of proper inventory level in the supply chain where it is needed (Novack et al., 1993).
Operating supply chains cause complex dynamics, involving swings in both production rates and stock
levels commonly known as the bullwhip effect (Towill et al., 1992). Bullwhip refers to the phenomenon
whereby the variance of demand may be amplified dramatically as the orders proceed through each
echelon of a supply chain (Lee et al., 1997). Research on demand amplification in supply chains has
gained interest since the start of the 20 century and is well known to economists (Geary et al., 2006).
Forrester (1958) provided one of the first academic descriptions of this phenomenon by using
industrial dynamic approaches to show such amplification. Since than empirical research has
generated a wide range of conclusions on the existence, causes and suggested remedies of bullwhip
at the level of industry, multi-industry or economy level (Lee and Whang, 2006). The effects of a
smooth material flow associated with transparent information flow can yield significant performance
improvements (Childerhouse and Towill, 2003). The specific contribution of this paper is to examine
the influence of Toyota’s operations principles on the creation of smoothing supply chain dynamics.
Our paper proceeds by first reviewing causes of the bullwhip effect before describing the underlying
relationships between supply chain performance and operations principles according to the “Toyota
Way”. The relations identified to smooth supply chain dynamics will provide a framework, or
understanding, from which a firm can evaluate its inherent options to tame undesirable and costly
oscillations, in order to enhance business performance.
Causes of the bullwhip effect
There are a number of inter-related issues, which can be found in literature concerning the causes of
the bullwhip effect. The fundamental theoretical and practical work started in this field by Jack
Burbidge (1958) and Jay Forrester (1958), which, has been resuscitated and further extensively
developed by Denis Towill (1997) and colleagues. The main findings of our literature review are
summarised in four generic views (Capacity management, Batching, Scheduling/Ordering, Material
flow/Stock control), which characterise the main causes of bullwhip as detailed below.
Capacity management
There is a trade-off between manufacturing operations and logistics operations through the close link
between capacity and the physical movement of goods. Capacity is defined as the potential of the
value added system to allow physical materials to be transported and handled (Novack et al., 1993).
Capacity therefore impacts on the speed and distance of materials movement, while materials
movement impacts effective capacity levels. Sterman (1986) argues that there are inherent oscillatory
tendencies in the adjustment of production capacity within firms due to the inevitable lags in acquiring
factors of production and reacting to changes in demand. He further pointed out that cycles arise from
the interaction of the physical delays in production and capacity acquisition with bounded rational
decision making by individual producers (Sterman, 2000). Taylor (1999) identified fluctuations in
output by a machine, due to variability in reliability, to cause fluctuations in the upstream demand from
that machine. The adjustment of production capacity amplifies unanticipated changes in demand. “It is
well known that factory production rate often fluctuates more widely than does the actual consumer
purchase rate” (Forrester, 1961). The effect is described by Burbidge (1961) as waste of the
production capacity, which is left unused, due to the failure to control the demand cycle. The output is
limited by available capacity at each particular point in the flow stream along the value chain.
A further cause of excessive variation of work orders is repeated batching by time and/or quantity due
to Economic Batch Quantity (EBQ)/ Economic Order Quantity (EOQ) policies at each echelon of the
supply chain. This order batching effect occurs in different forms within a supply chain. Common
examples for batching are:
Order batching: Although customer demand may be relatively continuous, replenishment orders are
batched due to ordering costs or periodic ordering system runs (Metters, 1997). Incoming orders at
each stage do not immediately trigger outgoing orders. Demand will be accumulated until reaching a
pre-determined threshold before issuing an upstream order to be cost effective. Unsynchronised
materials resource planning (MRP) which runs along supply chain partners can be also stated as a
cause of distortions between incoming and outgoing orders.
Transport batching: The pickup of parts from multiple suppliers to generate full truckloads (FTL) varies
and delays the receiving workload compared to supplier call-offs. Freight rates per transport unit
decline with growing transport volume. Therefore the bundling of inbound material and outbound
finished goods, to reduce freight costs is one of the main drivers for bullwhip in material flows.
Production batching: Minimum–cost batch quantity also applies for production where internal orders
are placed for a batch of parts to be produced on a machine (Slack et al., 2007). In the case of
manufacturing the batch quantity produced is determined by optimising the trade-off between
changeover cost and inventory carrying cost (Harrison and van Hoek, 2008). Large lot sizes cause
boom and bust in internal material flows, which enlarges resource demand and lowers stability and
efficiency within organisations.
Inhouse-Logistics batching: The material demand can be differentiated between two fundamentally
different types. The material demand related to point-of-use need and the compensation for logistical
discontinuities by quantity and time. Production material for example is constantly picked at assembly
line whilst the assembly items are delivered from a supplier by truckload, stored in warehouse and
placed at line in larger container quantities and time intervals. All logistics processes like transport,
handling and storage are triggered by capacity utilisation efficiency and usually fulfilled in batches to
gain economies of scale.
Riddalls and Bennett (2001) assessed the impact of batch production costs on bullwhip. They state
that bullwhip levels are related to the remainder of the ratio between average demand rate and batch
size. Potter and Disney (2006) carried out further investigations and outlined an important insight to
minimise on-costs to the supply chain due to batching. They demonstrated that it is possible to reduce
the level of bullwhip generated by selecting a batch size that is a multiple of average demand. In
addition there is less of an impact on variance with a small batch size, which they highlight to opt for
the smallest batch size possible.
Chapman (1990) argues that changing customer requirements and manufacturing complexities are
the main sources of instability in production schedules. Manufacturing complexity, arising from internal
and external sources, must be controlled to provide improved schedule adherence (Frizelle and
Woodcock, 1995). Unplanned changes to the production schedule delay jobs, increase average
throughput times and work in process stocks (Mapes et al., 2000).
A further crucial issue, was posed by Burbidge (1984) about the problem of multi-cycle ordering,
whereby each item has its own ordering cycle and is considered independently of any other required
item. He summarised this effect by the “ordering cycle law” and states that “If the various components
made in a factory are ordered and made to different time cycles, they will generate high amplitude and
unpredictable variations in both stocks and load as the many contributing component stock cycles drift
in and out of phase”. This effect, caused by unsynchronised ordering and production cycles (multicycling), is known as the Burbidge Effect, which can be minimised (but not eliminated) by
synchronisation of reordering and switchover times (single-cycling).
Material flow/ Stock control
Material flow and stock levels lead to manufacturing decisions, which satisfy orders and correct
inventories. Taylor (1999) reports strong pressure from senior management to minimise inventory,
because of failing to identify the trade-off between inventory cost and disruption cost, due to variable
demand. “It was common for stock levels to be set, in order to meet financial targets, rather than in
relation to provision of carefully calculated buffers against quantified variability in demand or supply”.
Forrester (1961) investigated systems of information feedback control to explain how decisions, delays
and predictions can produce either good control or dramatically unstable operation with production
swings and inventory fluctuations. Burbidge (1961) pointed out that stock control systems triggered by
pre-determined reorder levels generate extremely variable multi-cycle, multi-phase flow leading to
highly fluctuating inventories (Towill, 1997). Considerable swings in inventory levels cause additional
orders, if safety stock levels are breached. Hence, the internal bullwhip effect is strongly related to
stock control ordering, according to the “law of industrial dynamics” coined by Burbidge (1984): “If
demand is transmitted along a series of inventories using stock control ordering, then the amplitude of
demand variation will increase with each transfer”. Originally applied to fixed-point reordering systems
it is applicable to the external as well as the internal material stocks (Wikner et al., 1991). Based on a
flow shop model with fixed sequence Crandall and Burwell (1993) argue that increases in process
variability cause corresponding increases in work-in-process if reduction in throughput is to be
avoided. This relation is supported by many empirical studies (Flynn et al., 1995; Taylor, 1999), which
indicated variability in process capability and subsequent product quality as an inherent source of
process variability.
Toyota´s lean logistics principles to tackle bullwhip
The Toyota Motor Corporation is well known as one of the innovators in the field of lean management
and sets the standard in efficiency and productivity in the auto manufacturing industry (Womack et al.,
1990). After World War II Japanese car industry led by Toyota developed a new approach to compete
against the mass production concept successfully applied by Henry Ford since the beginning of the
20 century. Whilst Ford’s mass production system was designed to focus on large-scale production,
Toyota needed to churn out low volumes of many different models using the same assembly line,
because consumer demand was too low to support dedicated assembly lines for one car model. The
starting point of the Toyota Production System was in recognition of Japan’s distinguishing features,
like post-war shortages and lack of natural resources (Sugimori et al., 1977). To contrast the new
approach to manufacturing management used by Japanese vehicle manufacturers (e.g. Toyota,
Honda, Nissan) with the mass production methods used by most Western manufacturer the term lean
management was coined (Krafcik and MacDuffie, 1989). The central philosophy behind the lean
concept is waste reduction, which is described by Taiichi Ohno (1988) as: “All we are doing is looking
at the time line from the moment the customer gives us an order to the point when we collect the cash.
And we are reducing that time line by removing the non-value-added wastes.” Lean thinking can be
seen in a wider context as continuous improvement cycle to seeking perfection by eliminating waste.
Gradually the lean principles spread from the shopfloor to the entire company and further on to the
whole supply chain. Lean thinking under a manufacturing perspective has been well described in
literature over many years. The specific contribution of this paper is to examine the application of lean
principles to tackle bullwhip. We therefore concentrate on logistics, as the task of coordinating material
flow and information flow across the supply chain (Harrison and van Hoek, 2008).
To gain insight into the contributions of Toyota to dampen bullwhip, we first performed a literature
review of research and practitioner articles. The existing related research is based on the fundamental
work started in this field by Taiichi Ohno and Shigeo Shingo, which was further developed by a
number of colleagues working directly or indirectly for Toyota. Toyota provides a vast number of
concrete methods to eliminate or at least to dampen the bullwhip effect. Starting with the pioneering
works about just-in-time management, group orientation, work structure, plant layout and supplier
integration at Toyota City, many approaches have been developed so far to respond rapidly,
effectively and efficiently to perturbations. The main thrust of this paper examines the connection
between logistics systems and bullwhip. Fundamental properties and characteristics were summarised
in seven generic lean logistics principles (see Table 1) proposed by the “Toyota Way” to mitigate
demand amplification.
Synchronisation Principle
In order to prevent local build-ups of inventory, material flow must be harmonised so that parts move
in a coordinated fashion (Harrison and van Hoek, 2008). The goal is that material flows without
interruptions in a highly orchestrated process between the individual nodes of a value stream.
Synchronising upstream operations with downstream operations allows responding to changing
requirements and helps to dampen bullwhip tremendously. Coordination of material flows by both
volume and time is aimed at processing the quantity needed by one process from the one that
precedes it. Each partner is fed from the next stage up the chain in just the quantity needed at
precisely the right time. Perhaps one of the most significant Toyota principles of becoming widely
adopted and practised is that of just-in-time (JIT) supply, where all elements of the supply chain are
synchronised. “Synchronous supply is essentially a system where components supplied are matched
exactly to the production requirements of the buyer” (Doran, 2001). “The goal of JIT is to produce and
deliver goods just in time to be sold, subassemblies just in time to be assembled into finished goods,
fabricated parts just in time to go into the subassemblies and purchased materials just in time to be
transformed into fabricated parts” (Schonberger, 1982). The creation of a synchronised logistics
system aims to dramatically reduce inventories while greatly enhancing responsiveness. Complex
parts with growing variant number such as seats, bumper systems or front and rear axles require late
configuration and demands that suppliers deliver in sequence to the vehicle manufacture plant.
Nowadays sequenced in-line supply (SILS) is a standard delivery approach in synchronous supply. In
this concept, the entire vehicle assembly process is dependent upon the timely delivery of
components. SILS requires suppliers to deliver customer-ordered components and modules in the
same sequence and synchronised with the final assembly process (Lyons et al., 2006). Resultant
orders and call-offs are processed sometimes just hours ahead of when the car is built. Therefore
information flows and systems must be synchronised, so that information replaces the need for
inventories. Synchronous supply necessitates an integrated information system which can
accommodate the time-critical transfer of data and activate the synchronous manufacturing process to
deliver zero defect goods, at the right time, at the right place and at the right cost (Doran, 2001). It
enables the supply chain partners to share logistics information such as production-plans and
capacities, delivery-orders and stock levels in real time. Transparency of information upstream and
downstream maintains the flow of materials in time to the rhythm of the production process. Freight
forwarders are integrated as well into the information process and are provided with collection advices
including quantities for collection and collection date per supplier and plant. Loading and unloading
times have to be synchronised because there are no inventory buffers on the assembly line, which
could compensate delays in inbound delivery.
Whilst SILS is focused on high-volume, high-variants delivery, Toyota is also using synchronisation
principles in medium- and low-volume segments with the use of multi-tier transport networks. Whereas
in the past weekly deliveries for lower volume parts were common, there has been a significant shift
toward daily and hourly deliveries and thus toward reducing inventory (Liker and Wu, 2000). Crossdocks act as nodes in a high frequency mixed-item supply system. They transform truckloads of
incoming materials from individual suppliers or milk runs into outgoing mixes of loads and ships
leaving the other side. Each load is about 1.5 hours’ worth of exactly the material Toyota needs in its
assembly plants (Liker and Wu, 2000).
Takt Principle
Synchronisation needs a common beat, which coordinates the activities of all the partners in a value
stream. This signal is generated by takt time (“takt” is a German word for rhythm or meter), which
ensures that each operation performs equally. If workers are going faster, they will overproduce; if
they are going slower, they will create bottleneck operations (Liker, 2004). The takt time is used to
synchronise the pace of production with the pace of customer sales. Takt is derived by customer
demand – the rate at which the customer is buying product. In terms of calculation, it is the available
time to process parts within a specified time interval, divided by the number of parts demanded in that
time interval (Liker and Meier, 2006). Customer demand and the derived takt time can be seen as a
pacemaker for the whole manufacturing and logistics process.
Flow Principle
Flow is at the heart of Toyota’s lean philosophy that shortening the elapsed time from raw materials to
finished goods will lead to the best quality, lowest cost, and shortest delivery time (Liker, 2004). The
aim is to get parts and data to flow through processes evenly and in harmony without interruptions and
stagnation (Harrison and van Hoek, 2008). Whilst Henry Ford applied successfully low-variety
assembly flow systems at his Highland Park plant in 1913, Toyota transferred this concept to the highvariety one-piece flow system. One-piece flow is characterised by manufacturing and moving just one
piece at a time. Parts are consistently interchanged so that cycle time is stable for every job. Onepiece flows in combination with production levelling (see Stability Principle) reduce operation and lot
delays (Shingo, 1981). Schonberger (1982) argued that overlapped production, where small quantities
up to single pieces being passed from work station to work station, cuts down the lot-size inventories
in process. The Theory of Swift, Even Flow by Schmenner and Swink (1998) summarises the crucial
relations between material flow, speed and variation. “Thus, productivity for any process – be it labor
productivity, machine productivity, materials productivity, or total factor productivity – rises with the
speed by which materials flow through the process, and it falls with increases in the variability
associated with the demand on the process or with steps in the process itself”.
The size of the processing lot is determined principally by the trade-off between inventory holding
costs and costs involved through setup changeovers (Shingo, 1981). The aim for small batches leads
inevitably to an increase in the number of set-up operations that must be performed and therefore
drastically reduced by quick changeovers. One of the most effective ways of cutting set-up time is the
single-minute exchange of die (SMED) concept promoted by Shigeo Shingo (1985), referring to the
aspect that any set-up could be performed in less than ten minutes. Set-up times are considerably
reduced by, separating and converting an internal set-up operation (operations that can be performed
only when the machine is stopped) to an external set-up operation (operations that can be completed
while the machine is running) and streamlining all aspects of the whole set-up process. Shingo (1981)
states that process stability can be performed by quick product changeovers, where production and
transport takes place in the smallest lot sizes using short set-up routines. This high batch frequency
enables a smooth material flow with minimum lead times and high throughput rates.
Frequent shipments from suppliers, is a further key to generating material flow. High frequency
delivery with small transport batches reduces inventory holding costs and releases valuable space.
Traditional point-to-point delivery works well for high volume single product supply but not for mixedload, small-lot deliveries in geographical distance. Here, this requires cross-docks to accept large
loads for redistribution into smaller loads and milk runs to consolidate less than truckload (LTL)
deliveries in combining them by stopping at several suppliers to generate in the end a full truckload.
Pull Principle
Svensson (2003) outlines that “there is a potential bullwhip effect between inbound and outbound
logistics flows”. This implies that the companies in a managerial context have to consider upstream
activities in the supply chain when they are striving to improve their performance in the interface
towards their present and potential customers, and vice versa. “Very early on, Toyota starting thinking
in terms of pulling inventory based on immediate customer demand, rather than using a push system
that anticipates customer demand” (Liker, 2004). Inspired by the first U.S.-style supermarkets in Japan
in the mid-1950s Taiichi Ohno transferred a customer-driven supply system to factories. “A
supermarket is where a customer can get what is needed, at the time needed, in the amount needed”
(Ohno, 1988). Pull logistics is a demand-driven system where downstream operation, whether within
the same facility or in a separate facility, provides information to the upstream operation. Parts are
only produced, transported and delivered when an external or internal customer signals a need. The
application of pull systems implies that demand information is made available across the supply chain
(Harrison and van Hoek, 2008). A typical pull system is a kanban system. Kanban uses a
decentralised statistically-based approach to control internal and external material flows. The aim is to
process no more than the required quantity and when the amount of materials at the downstream
stage approaches critical levels, it is fed from the next stage up the chain in just the quantity needed at
precisely the right time. The use of kanban systems necessitates that material demand does not
exceed a critical variation threshold, which is needed to operate smooth and stable kanban systems
with minor inventory. Shingo (1981) addresses the practical need to control the dynamic interactions
between material movements variation and kanban systems. In addition the degree of amplification
becomes larger in proportion to the lead time between the moment when a kanban signal is set and
the moment of replenishment (Kimura and Terada, 1981). “In ordinary order point systems, minimum
inventory serves to absorb these fluctuations. A kanban system, however, lacks this cushion because
the inventory has been eliminated. Fluctuations beyond a certain magnitude, however, cannot be
absorbed in this fashion, and levelled production becomes necessary” (Shingo, 1981).
Stability Principle
To make pull-driven logistics work, material flow stability is needed. There are innumerable reasons
for disturbing material flows, like “mistaken estimates, clerical errors, bad or defective parts,
equipment failures, absenteeism and so on and so forth” (Ohno 1984). The planning issue to ensure
stability is the principle of levelled production. This is where the production of different items (product
mix) is distributed evenly to minimise uncertainty for upstream operations and suppliers. Volume and
variety of items produced are levelled over the span of production during the assembly process so that
suppliers have a smooth, stable demand stream (Liker and Wu, 2000). Toyota’s mixed production
system is the distinctive feature of schedule levelling to adjust surplus capacity and rejects stock
(Shingo, 1981). Production levelling by both volume and product mix is aimed at producing the
quantity and variety taken by one process from the one that precedes it. It does not process products
according to the actual flow of customer orders, which can swing up and down wildly, but takes the
total volume of orders in a period and levels them out, so the same amount and mix are being made
each scheduling period (Liker, 2004). Harrison (1997) pointed out that fixing levelled production
schedules prior to build day avoids last-minute panics and confusion causing turbulences to material
flows. Schedule stability translates into stable material call-offs, which means a smooth material flow
pipeline and improved performance in plant operations. This is partly performed by low buffer stock
according to the rigorous synchronisation between scheduling and material delivery, handling,
transport and placement at the point-of-use. An even flow of work and material throughout the shift
requires also frequent supplier deliveries with tightly scheduled windows for delivery and dispatch of
inbound materials throughout the day. Toyota’s levelling concept critically depends on transporting
and delivering parts more frequently and in small-lot deliveries. Delivery time windows, during which
all parts must be received at the delivery plant, lead to stable inbound flows. In addition the use of lean
transportation systems to handle mixed-load, small-lot deliveries in combination with a cross-docking
system enable a high frequency delivery with small quantities. By focusing on a small group of
selected carriers (core carriers) which provide reliable service in such areas as consolidation, tightly
scheduled deliveries, shipment tracing and effective communication a lean transportation and delivery
system can be fulfilled (Liker and Wu, 2000).
Standardisation Principle
Standardisation means creating a disciplined system with standardised times and methods for internal
and external operations, assuring quality and the most cost-effective way to do the job. The wellknown concept of time and motion studies, based on the principles of industrial engineering first set
forth by Frederick Taylor, has been flexibilised by Toyota. The critical task is to find the balance
between providing employees with rigid procedures to follow and providing the freedom to innovate
and be creative to meet challenging targets (Liker, 2004). Standardisation allows reducing a high
variety of low-volume processes to a manageable number of high-volume processes. Metaroutines
are needed to make non-routine tasks more routine, with the direct effect of increasing efficiency
(Adler et al., 1999). Standardised logistics activities, such as picking, sorting and transporting, are the
order of actions that each worker must perform within a given cycle time (Monden, 1998). It raises the
number of repetitions and reduces costs according to learning curve effects. In addition standardised
logistics processes guarantee identity between an intra-logistics and inter-logistics process (Klug,
2010b). For instance standards concerning transport allow establishing stringent delivery requirements
regarding delivery frequency and time windows, loading and unloading operations at delivery docks,
container handling and so forth. Standardisation generates repeatable processes in which operations
can be written out and waste identified and eliminated to reduce variance in process time. This is also
necessary to apply the concepts of flow in which the jobs are highly repetitive with consistency in the
cycle time per unit (Liker, 2004). In addition it is impossible to improve any process until it is
standardised. Imai (1997) states that “Successful management on a day-to-day level boils down to
one precept: Maintain and improve standards. This not only means adhering to current technological,
managerial, and operating standards, but also improving current processes in order to elevate current
standards to higher levels”. The core concept of Toyota’s standardisation is based on three elements
described by former Toyota President Cho (Liker, 2004). “Our standardised work consists of three
elements – takt time, the sequence of doing things or sequence of processes, and how much
inventory or stock on hand the individual worker needs to have in order to accomplish that
standardized work”. Standardised work therefore acts as an enabler for lean logistics as a
synchronised, flow-orientated and cycled material flow, guided and pull-driven by customer demand
(Klug, 2010a). This dampens the boom-and-bust behaviour of material flows and helps to perform the
high productivity of a lean factory. Individual processes need to be stabilised to give the customers
what they want, in the amount they want, when they want it, which will mean virtually tackling bullwhip.
Integration Principle
The once narrow subject of logistics has become a comprehensive topic that now spans a wider value
system. Hence integrating operations with suppliers and customers in supply chains shows
association with performance improvement (Frohlich and Westbrook, 2001). As a consequence
integration takes place over the whole supply chain from customer, to dealer, over production to
supplier including the logistics service provider. As Harrison and van Hoek (2008) stated: “We can
propose that broader integration reduces uncertainty of material flow through the supply network. In
turn, this improves efficiency and reduces the P-time (total logistics lead time)”. It is commonly
accepted that supply chain integration is a desirable goal when applied in combination with tailored
operational applications (Towill et al., 2002). Toyota uses various and manifold operation principles
and techniques to achieve internal and external supply chain integration. Internal integration is the key
starting point for broader integration across the value stream (Harrison and van Hoek, 2008). Toyota
achieves production levelling – as described above - by utilising a heavily integrated and embedded
social-technical system. Production levelling would not exist without a strong interdepartmental
cooperation, employee relations and management development. Managers will have to be open and
willing to spend significant time outside their department and be convinced that helping other
managers benefits them and the company overall (Marksberry et al., 2011).
One external integration strategy is removing an echelon within the supply chain by acquisition.
Toyota acquired its dealerships in Japan because of long lead times. It took longer to move a car
through the distribution network than was needed to manufacture it (Towill, 1993). This enabled
Toyota link to sales data taken by their own dealers without distortion and delays. A further very
successful form of integration is to build up and to strengthen partnerships on the supply side. One
key driver to Toyota’s success is their highly effective supplier integration process that has enabled
the excellence of the Toyota Production System (Bennett and O’Kane, 2006). Besides very effective
consulting and human resource programmes, which enables know-how and personnel to be
interchanged (Dyer and Nobeoka, 2000), Toyota started as far back as the late 1930’s to concentrate
their suppliers on the southern fringe of Nagoya, as its centre of production (Larsson, 1999). This
green-field automotive town, which was renamed Toyota City in 1959, allowed Toyota to push the JIT
system to an extreme (Hayter, 1997). Inspired by the Toyota experience and growing outsourcing
tendencies many automotive manufacturers started to concentrate their suppliers in close proximity to
the assembly lines (Bennett and Klug, 2009). The close proximity of suppliers makes it economical to
deliver several times a day and keep minimal inventories. Larsson (1999) showed that the higher the
deliver frequency the more important the geographical and temporal supplier proximity in order to
minimise transport costs and maximise reliability. Geographical supplier integration improves
responsiveness as the transport time from finished component to assembly is very short (Larsson,
2002), which enables meeting customer orders in short lead times, react quickly to quality or delivery
problems without building stocks. Distant suppliers are more likely to experience disruptions in
delivery, for instance, as a result of the transport infrastructure or from weather and traffic conditions
(Svensson, 2000). Therefore integrated suppliers can raise the reliability of delivery while taming
undesirable and costly oscillations to enhance business performance.
Demand fluctuations from the bottom of the supply chain to the top are caused by external as well as
internal forces; or by both acting together or in opposition (Towill, 1994). One major goal of the Toyota
Production System is to dampen or eliminate demand fluctuations by means of lean logistics as a
synchronised, flow-orientated and cycled material flow, guided and pull-driven by customer demand.
The used lean principles include management, technical and economic influences, as well as
distributor and supplier relationships (Gupta et al., 1999). There is still much work to be completed, in
order to more fully understand the sophisticated link between Toyota’s Production System and
bullwhip. There is a need to develop more rigorous research methodologies and approaches that can
quantitatively explore this relation. Consequently, such techniques need to be used over many years
to understand the complex cause-and-effect network. It is known that Toyota’s lean principles take
time to implement correctly (Marksberry et al., 2011). Although most car manufacturers claim to
embrace a lean philosophy, most of them are missing key elements of the discipline needed to make it
work. Toyota uses a complex set of highly integrated practices, that are all interdependent and their
application is coordinated across the entire company. It must be remembered that it took Toyota
decades to develop and implement these practices that western suppliers are trying to introduce in a
few years (Bennett and O’Kane, 2006).
• Adler, P.S., Goldoftas, B., Levine, D.I. (1999), ‘Flexibility Versus Efficiency? A Case Study of
Model Changeovers in the Toyota Production System’, Organization Science, Vol. 10 (1),
• Bennett, D., O’Kane, J. (2006), ‘Achieving business excellence through synchronous supply in
the automotive sector’, Benchmarking: An International Journal, Vol. 13 (1/2), pp.12-22.
• Bennett, D., Klug, F. (2009), ‘Automotive Supplier Integration from Automotive Supplier
Community to Modular Consortium’, Logistics Research Network Conference, Cardiff
University, pp.698-705.
• Burbidge, J.L. (1958), ‘A new approach to production control’, Institute of Production
Engineers Journal, Vol. 37 (3), pp.288-302.
• Burbidge, J.L. (1961), ‘The new approach to production’, Production Engineer, Vol. 40 (12),
• Burbidge, J.L.
(1984), ‘Automated production control with a simulation capability’,
Proceedings IPSP Conference WG 5-7, Copenhagen, pp.1-14.
• Chapman, S.N. (1990), ’Schedule stability and the implementation of JIT’, Production and
Inventory Management Journal, 3rd Quarter, pp.66-70.
• Childerhouse, P., Towill, D.R. (2003), ‘Engineering the Seamless Supply Chain’, The
International Journal of Logistics Management, Vol. 14 (1), pp.109-120.
• Crandall, R.E., Burwell, T.H. (1993), ‘The effect of work-in-process inventory levels on
throughput and lead times’, Production and Inventory Management Journal, 1st Quarter, pp.611.
• Doran, D. (2001), ‘Synchronous supply: an automotive case study’, European Business
Review, Vol. 13 (2), pp.114-120.
Dyer, J., Nobeoka, K. (2000), ‘Creating and Managing a High Performance KnowledgeSharing Network: The Toyota Case’, Strategic Management Journal, Vol. 21, pp.345-367.
Flynn, B.B., Sakakibara, S., Schroeder, R.G. (1995), ‘Relationship between JIT and TQM:
practices and performance’, Academy of Management Journal, Vol. 38 (5), pp.1325–1360.
Forrester, J.W. (1958), ‘Industrial dynamics - a major breakthrough for decision makers’,
Harvard Business Review, Vol. 36 (4), pp.37-66.
Forrester, J.W. (1961), Industrial Dynamics, MIT Press, Cambridge.
Frizelle, G., Woodcock E. (1995), ‘Measuring complexity as an aid to developing operational
strategy’, International Journal of Operations & Production Management, Vol. 15 (5), pp.2639.
Frohlich, M.T., Westbrook, R. (2001), ‘Arcs of integration: an international study of supply
chain strategies’, Journal of Operations Management, Vol. 19 (2), pp.185-200.
Geary, S., Disney, S.M., Towill, D.R. (2006), ‘On bullwhip in supply chains – historical review,
present practice and expected future impact’, International Journal of Production Economics,
Vol. 101 (1), pp.2-18.
Gupta, S., Al-Turki, Y., Perry, R. (1999), ‘Flexible kanban system’, International Journal of
Operations & Production Management, Vol. 19 (10), pp.1065-1093.
Harrison, A. (1996), ‘An Investigation of the Impact of Schedule Stability on Supplier
Responsiveness’, The International Journal of Logistics Management, Vol. 7 (1), pp.83-91.
Harrison, A. (1997), ‘Investigating the Sources and Causes of Schedule Instability’, The
International Journal of Logistics Management, Vol. 8 (2), pp.75-82.
Harrison, A., van Hoek, R. (2008), Logistics Management and Strategy, 3rd edition, FT
Prentice Hall, Harlow.
Hayter, R. (1997), The Dynamics of Industrial Location: The Factory, the Firm and the
Production System, John Wiley, Chichester.
Imai, M. (1997), Gemba Kaizen – A commonsense, low-cost approach to management,
McGraw-Hill, New York.
Kimura, O., Terada, H. (1981), ‘Design and analysis of Pull System, a method of multi-stage
production control’, International Journal of Production Research, Vol. 19 (3), pp.241-253.
Klug, F. (2010a), Logistikmanagement in der Automobilindustrie – Grundlagen der Logistik im
Automobilbau, Springer Verlag, Berlin.
Klug, F. (2010b), ‘Logistics implications of global production networks in car manufacturing’,
Cambridge International Manufacturing Symposium, University of Cambridge, pp.13-24.
Krafcik, J.F., MacDuffie, J.P. (1989), Explaining High Performance Manufacturing: The
International Automotive Assembly Plant Study, International Motor Vehicle Program, MIT
Press, Cambridge.
Larsson, A. (1999), Proximity Matters? Geographical aspects of changing strategies in
automotive subcontracting relationships: the case of domestic suppliers to Volvo Torslanda
assembly plant, Department of Human and Economic Geography, University of Göteborg,
Larsson, A. (2002), ‘The development and regional significance of the automotive industry:
supplier parks in Western Europe’, International Journal of Urban and Regional Research, Vol.
26 (4), pp.767-784.
Lee, H.L., Whang, S. (2006), ‘The Bullwhip Effect: A Review of Field Studies’, in: Carranza
Torres, O.A., Villegas Morán, F.A. (Eds.), The Bullwhip Effect in Supply Chains – A Review of
Methods, Components and Cases, Palgrave Macmillan, New York, pp.57-70.
Lee, H.L., Padmanabhan, V., Whang, S. (1997), ‘Information distortion in the supply chain: the
Bullwhip Effect’, Management Science, Vol. 43 (4), pp.546–558.
Liker, J.K. (2004), The Toyota Way – 14 Management Principles from the World’s Greatest
Manufacturer, McGraw-Hill, New York.
Liker, J.K., Wu, Y.-Ch. (2000), ‘Japanese Automakers, U.S. Suppliers and Supply-Chain
Superiority’, MIT Sloan Management Review, Vol. 21 (1), pp.81-93.
Liker, J.K., Meier, D. (2006), The Toyota Way Fieldbook – A Practical Guide for Implementing
Toyota’s 4Ps, McGraw Hill, New York.
Lyons, A., Coronado, A., Michaelides, Z. (2006), ‘The relationship between proximate supply
and build-to-order capability’, Industrial Management and Data Systems, Vol. 106 (8),
Mapes, J., Szwejczewski, M., New, C. (2000), ‘Process variability and its effect on plant
performance’, International Journal of Operations & Production Management, Vol. 20 (7),
Marksberry, P., Badurdeen, F., Maginnis, A. (2011), ’An Investigation of Toyota’s Social and
Technical Systems in Production Leveling’, Journal of Manufacturing Technology
Management, Vol. 22 (5).
Metters, R. (1997), ’Quantifying the bullwhip effect in supply chains’, Journal of Operations
Management, Vol. 15 (2), pp.89–100.
Monden, Y. (1998), Toyota Production System – An Integrated Approach to Just-In-Time,
Engineering & Management Press, Georgia.
Novack, R.A., Rinehart, L.M., Fawcett, S.A. (1993), ‘Rethinking Integrated Concept
Foundations: A Just-in-Time Argument for Linking Production/Operations and Logistics
Management’, International Journal of Operations & Production Management, Vol. 13 (6),
Ohno, T. (1984), ‘How the Toyota Production System was created’, in: Sato, K., Hoshino, Y.
(Eds.), The Anatomy of Japanese Business, Croom Helm, Beckenham, pp.197-215.
Ohno, T. (1988), Toyota Production System – Beyond Large-Scale Production, Productivity
Press, New York.
Potter, A., Disney, S.M. (2006), ‘Bullwhip and batching: An exploration’, International Journal
of Production Economics, Vol. 104 (2), pp.408-418.
Riddalls, C.E., Bennett, S. (2001), ‘The optimal control of batched production and its effect on
demand amplification’, International Journal of Production Economics, Vol. 72 (2), pp.159-168.
Schmenner, R.W., Swink, M.L. (1998), ‘On Theory in Operations Management’, Journal of
Operations Management, Vol. 17 (1), pp.98-113.
Schonberger, R.J. (1982), Japanese Manufacturing Techniques – Nine Hidden Lessons in
Simplicity, The Free Press, New York.
Shingo, S. (1981), Study of Toyota Production System from Industrial Engineering Viewpoint,
Japan Management Association, Tokyo.
Shingo, S. (1985), A Revolution in Manufacturing: The SMED System, Productivity Press,
New York.
Slack, N., Chambers, S., Johnston, R. (2007), Operations Management, Fifth edition, FT
Prentice Hall, Harlow.
Sterman, J.D. (1986), ‘The Economic Long Wave, Theory and Evidence’, Systems Dynamics
Review, Vol. 2 (Summer), pp.87-125.
Sterman, J.D. (2000), Business Dynamcis – Systems Thinking and Modelling for a Complex
World, McGraw-Hill, Boston.
Sugimori, Y., Kusunoki, K., Cho, F., Uchikawa, S. (1977), ‘Toyota production system and
Kanban system Materialization of just-in-time and respect-for-human system’, International
Journal of Production Research, Vol. 15 (6), pp.553-564.
Svensson, G. (2000), ‘A conceptual framework for the analysis of vulnerability in supply
chains’, International Journal of Physical Distribution and Logistics Management, Vol. 30 (9),
Svensson, G. (2003), ‘The bullwhip effect in intra-organisational echelons’, International
Journal of Physical Distribution & Logistics Management, Vol. 33 (2), pp.103-131.
Taylor, D.H. (1999), ‘Measurement and Analysis of Demand Amplification Across the Supply
Chain’, The International Journal of Logistics Management, Vol. 10 (2), pp.55-70.
Towill, D.R. (1993), ‘System dynamics – background, methodology and applications’,
Computing & Control Engineering Journal, December 1993, pp.261-268.
Towill, D.R. (1994), ‘1961 and all that; The Influence of Jay Forrester and John Burbidge on
the Design of Modern Manufacturing Systems’, Proceedings of International Systems
Dynamics Conference on Business Decision-Making, Stirling, pp.105-115.
Towill, D.R. (1997), ‘Forridge – Principles of good practice in material flow’, Production
Planning & Control, Vol. 8 (7), pp.622-632.
Towill, D.R., Naim, M.M., Wikner, J. (1992), ‘Industrial Dynamics Simulation Models in the
Design of Supply Chains’, International Journal of Physical Distribution & Logistics
Management, Vol. 22 (5), pp.3-13.
Towill, D.R., Childerhouse, P., Disney, S.M. (2002), ‘Integrating the automotive supply chain:
where are we now?’, International Journal of Physical Distribution & Logistics Management,
Vol. 32 (2), pp.79-95.
Wikner, J., Towill, D.R., Naim, M. (1991), ‘Smoothing supply chain dynamics’, International
Journal of Production Economics, Vol. 22 (3), pp.231-248.
Womack, J.P., Jones, D.T., Roos, D. (1990), The Machine Changed the World, Mandarin
Books, London.