Implementing Lean Control for Complex, High-Variety Shops

Matthias Thürer

Jinan University, Guangzhou, PR China;

Martin J. Land

Department of Operations, Faculty of Economics and Business, University of Groningen, The Netherlands;

Mark Stevenson

Department of Management Science, Lancaster University Management School, Lancaster University, UK;

Lawrence D. Fredendall

Department of Management, Clemson University, USA;



Short, predictable and reliable lead times are as important to winning orders as price but it is a major challenge to manufacture high-variety, customized products both quickly and cost effectively. Repetitive manufacturers may overcome this trade-off through lean implementation. However, high-variety manufacturers have found that lean’s planning and control techniques cannot be applied directly to their shops. This is because:

  • Production is not to-stock – it is largely customer order driven;
  • Lead times are not standard – the lead time depends on the order specifications; and
  • Orders can be one-offs, with companies entering a competitive bid process to win each order.


To provide complex, high-variety shops with a means of achieving similar benefits provided to repetitive manufacturers by lean, we have designed “Workload Control”. Workload Control regulates the input of work to the system in accordance with the output rate. It integrates two control levels as follows:

  • Customer enquiry management, which controls the acceptance/rejection of orders through pricing and due date quotations, converting the variable input rate of customer enquiries into a set of confirmed orders (the planned workload) that reflects the operational capabilities of the shop; and,
  • Order release, which uses a pre-shop-pool of orders to decouple the shop floor from the incoming workload – orders are released from the pool onto the shop floor in time to meet their due dates while limiting and balancing the shop floor workload.


The idea is to focus on load balancing seeks to reduce the variability of the incoming workload rather than to limit variation in the product mix itself. This allows complex, high-variety shops to manufacture customized products quickly and cost effectively.

A firm supplying customized products needs to be able to produce a high variety of products quickly and cost effectively. Achieving both objectives simultaneously is a major challenge since the company may only be able to deliver at short notice by maintaining a large capacity buffer of people and machinery. This means many resources are seldom fully utilized, unit costs rise and customers are charged a premium price. Workload Control – with its focus on load balancing – has the potential to overcome the trade-off between speed and cost. It provides manufacturers of highly customized products with the same leveling of workload to capacity achieved in repetitive manufacturing by lean tools. Workload Control is of particular importance to these shops, since it:

  • Allows lead times to be short, predictable and feasible;
  • Allows capacity to be controlled and used cost effectively;
  • Controls work-in-process, resulting in a lean shop floor and improved quality; and
  • Is simple in use and application.


How to Carry out Workload Control Effectively

Workload Control protects the shop from fluctuations in the incoming workload with its varied requirements. The intended impact of its two control levels – customer enquiry management and order release – is illustrated in Figure 1 in the form of input/output curves, which give the cumulative arriving and completed workload over time. While either control levels can be implemented independently, the full power of Workload Control is realized through their combined use.



Figure 1: Workload Control’s Intended Impact on the Shop’s Workload Over Time: Protecting the Shop from Fluctuations in the Incoming Workload


Customer Enquiry Management under Workload Control

Being able to quote lead times that are both short and reliable is made possible by fitting the planned output of the shop to the available capacity over time. This is achieved by setting operation due dates that are based on the input/output curves of each station in the routing of an order, with the final operation due date representing the estimated completion date of the order. The due date calculated based on this approach naturally reflects a firm’s actual operational capabilities and allows the planned workload to be stabilized (Thürer et al., 2014). For example, when the workload increases, available capacity reduces and the due dates offered to customers become longer. This reduces the probability that a company will win an order. But as the workload gradually decreases, available capacity increases and shorter, more competitive due dates can be offered, which increases the order-winning probability. This smoothens or balances the workload over time, which corresponds to one of the main principles of heijunka in lean operations – to prevent surges in work that temporarily deplete the capacity buffer and/or increase the time buffer.

To implement this approach in practice, it is important to maintain information on the output curve of each station on the shop floor. This relies on accurate feedback on the realized operation completion dates, e.g. via barcode scanners.


Order Release under Workload Control

Order Release is one of the main functions of production planning and control. Well-known approaches include Kanban, Drum-Buffer-Rope, and Constant Work-in-Process (ConWIP). But all of these concepts require a certain degree of repetitiveness in the product mix, since they lack workload balancing capabilities. In contrast, Workload Control’s order release method was developed to achieve a balanced workload in high-variety contexts like the make-to-order job shop.

To both limit and balance the workload on the shop floor, many studies have focused on mechanisms that release orders from the pre-shop pool periodically. This periodic release decision can be divided into two parts: (i) a sequencing decision that establishes the order in which jobs are considered for release; and, (ii) a selection decision that determines the criteria for choosing a particular job for release from the pool. Prior studies assumed that the sequencing decision is responsible for the timely release of jobs and the selection decision for load balancing. But significant performance improvements can in fact be realized by including load balancing considerations in the sequencing decision (Thürer et al., 2015). However, an effective sequencing rule should only activate load balancing when there is increased urgency among jobs.

The job selection decision proceeds by summing, for each station, the current load contribution of released orders and the load contribution of the job being considered for release. The sum of the two is then compared against predetermined workload limits or norms for each station. A job is released if the new workload at each station in its routing is below this workload norm; otherwise, the job is retained in the pre-shop pool. In the example release decision illustrated in Figure 2 – which provides a screenshot from a recently implemented Workload Control system – the job is not released since it violates the norm at the inspection station (INSP).




Figure 2: Screenshot from the Order Release Control Level of a Workload Control Software System (with an Example Order Release Decision)


Order release reinforces the principles of heijunka established by customer enquiry management as the workload is balanced across resources. In fact, the company in which the system in Figure 2 was implemented reported significant improvements in tardiness performance in addition to reduced work-in-process. However, the strict enforcement of workload norms can starve a station even though work may be waiting in the pool, e.g. if the norm/limit at another station in the routing of the order is violated. Substantial performance improvements can therefore be achieved if periodic release is combined with a continuous pull mechanism that releases orders to a starving station in-between periodic releases irrespective of the workload norm (Thürer et al., 2012).

Order release can be initially implemented without restrictive workload norms as benefits will start to accrue as soon as workload fluctuations on the shop floor are visualized. The norms can then be gradually tightened. As is well known from earlier lean implementations – inventory may hide problems. Therefore, as work-in-process starts to reduce, other improvement opportunities may present themselves. Once such problems have been resolved, it may be possible to tighten the workload norms again and achieve further work-in-process reductions.


Thürer, M., Stevenson, M., Silva, C., Land, M.J., and Fredendall, L.D., 2012, Workload Control (WLC) and Order Release: A Lean Solution for Make-to-Order Companies, Production & Operations Management, 21, 5, 939-953.

Thürer, M., Stevenson, M., Silva, C., Land, M.J., Fredendall, L.D., and Melnyk, S.A., 2014, Lean Control for Make-to-Order Companies: Integrating Customer Enquiry Management and Order Release, Production & Operations Management, 23, 3, 463-476.

Thürer, M., Land, M.J., Stevenson, M., Fredendall, L.D and Godinho Filho, M., 2015, Concerning Workload Control and Order Release: The Pre-Shop Pool Sequencing Decision, Production & Operations Management, DOI: 10.1111/poms.12304.

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Combining Price, Rebate and Returns in Retailer-Supplier Contracts

Chun-Hung Chiu

Sun Yat-sen Business School, Sun Yat-sen University, No.135, Xingang West Road,

Guangzhou, China, 510275.


Tsan-Ming Choi[1]

Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University,

Hung Hom, Kowloon, Hong Kong.


Christopher Tang

UCLA Anderson School, UCLA, Los Angeles, CA90095, USA;



First version: December 13, 2014. Revised: March 24, 2015. Sep. 22, 2015.

An invited paper for POM Review.



Retail supply chains may be inefficientl for two key reasons.  First, there is no central coordinator who can “dictate” the decision of each member because different members (e.g., upstream suppliers, downstream retailers, etc.) are separate entities.   Second, each supply chain member will select the decision that is best for itself and such uncoordinated decisions often lead to poor performance.


To improve the operational performance in a decentralized retail supply chain, different incentive mechanisms are needed to entice the different supply chain members to make ordering decisions that are good for the entire supply chain, thus achieving coordination (Chiu et al. 2011). For example, suppliers can attract the retailers order more by (1) accepting returns and (2) offering partial refund for their products under the returns policy (commonly seen in the publishing industry). They can also provide cash incentives to the retailers to push up the sales amount and also the ordering quantity under the rebates policy (exercised by companies such as Rolex, Xerox, etc).


It is known that either the returns policy or the rebates policy alone is sufficient to help coordinate the supply chain with inventory decisions. However, retail pricing is also a critical decision in retailing and when the underlying market demand depends on the retail price, a simple incentive contract such as rebate or returns does not necessarily improve supply chain performance. This observation has motivated us to explore other incentive contracts.  Consider the one adopted by Marathon Sports.


Marathon Sports is one of the largest sportswear chain-store retailers in Hong Kong. It sells multiple nationally branded sportswear and footwear products such as Nike or Adidas.  Different manufacturers offer different “target sales rebate” programs, each of which stipulates that, Marathon Sports would earn a sales rebate value for each item (approximately 1% to 1.5% of the wholesale price) only when the company’s sales volume exceeds a certain pre-specified sales target. Interestingly, at the same time, in order to reduce the risk of overstocking due to this class of target sales rebate programs, we learn that Marathon Sports can return some unsold items at the end of the season. Thus, in Marathon Sports’ case, the incentive contract includes not just the channel rebates, but also the returns policy.


Motivated by the observations of various retailing cases on companies such as Marathon Sports, we have found that the use of a sophisticated contract can enable a manufacturer to coordinate the pricing and ordering decisions along a decentralized supply chain so that the manufacturer can entice the retailer to make the right decision that is good for both parties.


We call this a Price, Rebate, and Returns (PRR) supply contract, combining the channel rebate contract, the returns contract, and the wholesale pricing contract. In fact, one can well-imagine that in order to coordinate the inventory decision, the supply chain requires the implementation of one incentive alignment contract and this is done by the returns policy (in which both the wholesale price and the refund rate for the returns are decisions). Since retail pricing is also a decision, there is a need to include another contract and hence the rebates contract plays the role. These contracts together form the PRR supply contract. Overall speaking, we find that the PRR contract is highly versatile. It provides enough degree of freedom for the seller (e.g. the manufacturer) and the buyer (e.g. the retailer) to negotiate on the right contractual terms which can coordinate the supply chain and satisfy each member’s own profit preference simultaneously.   More importantly, we find that the PRR contract can lead to a win-win situation. Figure 1 shows an illustration on the use of simple and sophisticated supply contracts.


Traditionally, both practitioners and researchers focus on the use of simple contracts for supply chain coordination.  However, with the advance of information technology and the stronger emphasis on supply chain integration and partnership, sophisticated contracts such as PRR have been implemented in practice.  Other companies should consider using more sophisticated contracts because they can improve the overall supply chain performance.  More importantly, they can facilitate a win-win situation, which is a great way to foster stronger partnerships among different supply chain members.



Figure 1. Supply contracts: simple contracts vs. sophisticated contracts.





Chiu, C.H., T.M. Choi, C.S. Tang. Price, rebate, and returns supply contracts for coordinating supply chains with price dependent demands. Production and Operations Management, 20, 81-91, 2011.

[1] Corresponding author: Tsan-Ming Choi

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Buttressing Supply Chains against Floods in Asia for Humanitarian Relief and Economic Recovery


ManMohan Sodhi – Cass Business School; Christopher Tang – Anderson School, University of California Los Angeles

Industry: Consumer and Retail

For the decade ending in 2010, floods accounted for nearly half of all natural disasters. Floods affected a large number of people, especially in Asia. Despite the fact that the number of floods per year has been increasing exponentially since 1900, there is very little in the operations literature on humanitarian supply chains that deals with floods. Compared to earthquakes, floods are more predictable in terms of timing and location. Therefore, there is an opportunity to involve “local entities” for better preparedness and mitigation. Thus, we seek to answer the question: what type of supply chain can facilitate humanitarian relief and hasten economic recovery in case of floods, especially in the Asian context?

The gap in existing solutions

We find three gaps in the existing solutions: (1) preparedness against floods that occur frequently especially at the ‘last mile’ areas, (2) response to medium-sized floods that do not attract the attention of international NGOs or central government but create economic havoc for the people in the affected areas, and (3) recovery of the affected areas. Firstly, there is a gap in preparedness efforts. Greater attention needs to be paid to preparedness at the ‘local’ level to ensure people continue to have access to essential goods during a flood. Given the recurrence and the predictable nature of general floods, such preparedness should be semi-permanent rather than one-off events. Secondly, there is a gap in response as regards ‘medium-sized’ floods that are not large enough to attract the attention of the international or even national NGOs but still large enough to disrupt the local economy. For a massive flood with a 2% chance of occurrence in a given year, the central government or even international humanitarian relief organisations are likely to be involved in responding to the resulting humanitarian crisis. For a small flood with a 20% chance of occurrence in a given year, local communities in flood-prone areas have to devise local solutions to assist affected people. However, in the case of a medium-sized flood, international or central government humanitarian relief is unlikely to be available. At the same time, local solutions would be inadequate because normal supply chain operations would be disrupted, and relief efforts would require a coordinated region-wide effort possibly involving NGOs, local government and manufacturers of essential goods. In this case, who should organise the response for medium-sized flood?

Finally, there continues to be a gap in solutions for economic recovery, especially when the economic disruption and losses occur almost annually. Economic solutions have to be tailored to the local economy.


We examine the role micro-retailers could play in the minimisation of impact and loss during such an event. Micro-retailers are the ‘last mile’ nodes in traditional retail supply chains in many Asian countries, and we propose the use of social enterprise to buttress these supply chains for distribution of essential goods by coordinating with micro-retailers before and after floods.

Proposed solution

Our proposed solution is: (1) to ensure that the distribution of goods to micro-retailers is not disrupted; and (2) to engage micro-retailers in flood relief efforts in a coordinated manner. This calls for buttressing existing traditional supply chains by having a “social enterprise” to work with micro-retailers, benefiting from their reach into vulnerable communities with the relief.

To ensure that the availability of goods to micro-retailers is not disrupted during and after the flood, the social enterprise needs to do certain preparatory activities. To begin with, the social enterprise will need earmarked land in order to make temporary use of for setting up makeshift warehouses. These warehouses will be used to replenish the inventories for micro-retailers during the flood. Once the emergency is over, the use of makeshift warehouse space would end, but that space would remain earmarked for use in the next flood. Note that our proposal is different from land set aside by governments for natural disasters in three ways. Firstly, we would like public (or private) land earmarked before, not during or after, a disaster to allow pre-placing inventory based on the anticipated intensity of the flood. Secondly, these plots of land/warehouse spaces should be small and distributed to allow for easy replenishment of goods to micro-retailers. Thirdly, the actual release of earmarked land by the local government to the social enterprise would be contingent on the anticipated intensity of the flood.

Another preparatory activity for the social enterprise would be to buy goods directly from the manufacturers (or from large distributors) and deliver-and-sell to the micro-retailers, using a temporary supply chain network of makeshift warehouses and flood appropriate transportation links. Furthermore, to engage micro-retailers in flood relief, the social enterprise should work with regional government, manufacturers and micro-retailers to coordinate ‘last mile’ effort to distribute essential goods. Specifically, the social enterprise can leverage the traditional retail supply chain that operates during normal times to establish a temporary supply chain involving manufacturers/distributors and micro retailers during the abnormal time around a flood event. After the flood related crisis issues subside, the regular supply chain should take over. By engaging micro-retailers with local knowledge in rural areas, the social enterprise can enable these micro-retailers to resume their business operations soon after a flood. While there are additional logistics, communication, and coordination costs for establishing and operating the proposed temporary supply chain, buttressing can enable: (1) faster and more effective humanitarian relief because these micro-retailers are already embedded in the community of affected people; and (2) speedier economic recovery by helping the affected micro retailers restore their business operations quickly after a flood.

Our research then goes on to examine our solution through the lens of supply chain flows and disaster relief efforts, before quantifying the benefits using our stylised model and finally drawing our conclusions.

The full research article, that appeared in Production and Operations Management can viewed here.

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