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A complex systems theory perspective of leanproductionTarcisio Abreu Saurin a , John Rooke b & Lauri Koskela ba DEPROT/UFRGS (Industrial Engineering and Transportation Department , FederalUniversity of Rio Grande do Sul) , Porto Alegre , Brazilb School of the Built Environment, The University of Salford , Salford , UKPublished online: 19 Jun 2013.

To cite this article: Tarcisio Abreu Saurin , John Rooke & Lauri Koskela (2013): A complex systems theory perspective of leanproduction, International Journal of Production Research, DOI:10.1080/00207543.2013.796420

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A complex systems theory perspective of lean production

Tarcisio Abreu Saurina*, John Rookeb and Lauri Koskelab

aDEPROT/UFRGS (Industrial Engineering and Transportation Department, Federal University of Rio Grande do Sul), Porto Alegre,Brazil; bSchool of the Built Environment, The University of Salford, Salford, UK

(Received 14 July 2012; final version received 11 April 2013)

Lean production (LP) has been increasingly adopted in complex systems, such as healthcare and construction sites.However, little is known of the extent to which the lean philosophy matches the nature of those systems, which havedifferent characteristics of complexity in comparison with manufacturing plants, in which LP was originated. This articleanalyses the extent to which LP is compatible with the nature of complex systems, as a basis for the identification oflearning opportunities for LP from complex systems theory (CST). As a framework for this analysis, both theprescriptions from LP and CST for designing systems are compared in terms of their potential impact on a set of charac-teristics of complex systems. Examples of how LP may learn from CST are identified as well as examples of how CSTmay help to tackle common difficulties in LP implementation.

Keywords: lean production; complex systems; socio-technical systems; system design

1. Introduction

Lean production (LP), which will sometimes be referred to simply as lean throughout this article, may be defined as anintegrated socio-technical system whose main objective is to eliminate waste by concurrently minimising supplier, cus-tomer, and internal variability (Shah and Ward 2007). This definition stresses the far-reaching intended impact of LP aswell as the need for an integrated management of the social and technical systems. As a result of this ambitious intent,LP permeates all elements of a socio-technical system, thus making its implementation difficult and slow (Lian and VanLandeghem 2007, Gelidas 1999). These characteristics imply that the design of the LP implementation process aims atmaking the system components congruent, both among themselves and with the nature of the system (Liker 2004, Cua,McKone, and Schroeder 2001).

Nevertheless, the systemic nature of LP has been so taken for granted by researchers that it has not been explicitlyanalysed from the perspective of theories on systems functioning. The well-known house of the Toyota ProductionSystem (TPS) (Liker 2004) is an example of how simplistically the systemic nature of LP may be portrayed and dis-cussed. Spear (1999) undertook one of the most in-depth qualitative studies of the TPS, which is portrayed by him asan exemplary approach to managing complex socio-technical systems. However, he does not conduct any explicit analy-sis of the TPS from the view of complex systems. Kidd (1994) argues that while the TPS possibly uses correctly theprinciples of systems thinking, it is not apparent that even its creators fully understood the theoretical reasons why andhow this is so. Lane (2007) presents recommendations for adapting lean practices to high-mix and low-volume manufac-turing environments, which are referred to as more complex than low-mix and high-volume ones. However, he does notabstract the recommendations to a point where they could be useful for other complex settings.

This superficial understanding is a particular drawback when implementing LP in sectors other than manufacturing,where lean lacks a fairly long and well-documented history (Womack, Jones, and Roos 1991). Both lack of knowledgeand mistaken assumptions about the strengths and weaknesses of LP in systems of different natures may encourageill-thought-out applications, which lack a deeper reflection on principles and the particular practices which should beadopted, and the best ways to implement them. Moreover, encouragement for simplistic applications of LP may arisefrom the non-critical use of the proliferating literature directed towards practitioners (Farris et al. 2009).

These concerns have become increasingly relevant as LP applications in other sectors have become more frequent.For example, there are reports of lean initiatives in sectors as diverse as construction, healthcare, chemical plants, steelmills and higher education (Doman 2011, Khurma, Bacioui, and Pasek 2008, Abdulmalek and Rajgopal 2007, Koskela

*Corresponding author. Email: saurin@ufrgs.br

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2000). However, these experiences are far from providing evidence of the theoretical and practical generalisation ofLP across a wide variety of domains (such as claimed by Spear and Bowen (1999), for example), since: (a) the useof lean in other sectors is fairly recent, in comparison with earlier applications in manufacturing; (b) the experienceshave usually been limited to the application of a few lean practices and principles, rather than adopting lean as abusiness philosophy (Joosten, Bongers, and Janssen 2009, Khurma, Bacioui, and Pasek 2008); and (c) rather thandescribing applications in real-world settings, a number of studies of lean in other sectors are restricted to computersimulations and theoretical discussions of the potential benefits of lean (Abdulmalek and Rajgopal 2007, Melton2005).

This article sets out an investigation of the extent to which LP is compatible with the nature of complex systems,since some of the sectors in which it has recently been disseminated are widely regarded as primary examples of thosetypes of systems (Bertelsen and Koskela 2005, Hollnagel and Woods 2005, Perrow 1984). This investigation is neces-sary because complex systems require particular styles of management (Rooke et al. 2008, Siemieniuch and Sinclair2002), advocated by complex systems theory (CST). Also, the management of complex systems is often out of step withtheir nature, since those who work in such systems have a tendency to treat working situations simplistically (Blakstad,Hovden, and Rosness 2010). Based on the analysis of compatibility between LP and the nature of complex systems, weidentify learning opportunities for LP from CST, which is the main objective of this article.

2. Characteristics of complex systems

There is substantial variation in the number of characteristics of complex systems presented in the literature as well asin the terms adopted to designate each of them. Indeed, complexity is never easy to define, and the term is often usedwithout definition (Hollnagel and Woods 2005). In this study, the characteristics of complex systems identified by Saurinand Sosa (in press) are adopted as a basis. Differently from other studies that take for granted a list of characteristics ofcomplexity from a single author (e.g. Dekker 2011 and Carayon 2006), Saurin and Sosa (in press) compared the charac-teristics presented by 15 studies of two kinds: (a) studies that emphasise complexity in socio-technical systems, taking itas a basis to question established management approaches (e.g. Perrow 1984); and (b) studies that emphasise complexityfrom an epistemological perspective, suggesting it as an alternative to the so-called Newtonian scientific view (e.g. Cil-liers 1998). They then grouped the existing characteristics into four categories, which are summarised in Figure 1.

3. Prescriptions based on CST

The boundaries of the system in which the prescriptions will be applied should be established beforehand (Checkland1999). Some criteria to define the boundaries are (Hollnagel 2012, Hollnagel and Woods 2005): (a) to include, withinthe boundaries, functions that matter for the analysis; a function refers to what people, individually or collectively, haveto do in order to achieve a specific aim; (b) to include functions that can be controlled and that affect performance; and(c) functions that cannot be controlled, and that do not affect performance, should be out of the boundaries.

In fact, prescriptions based on CST are relatively uncommon (Sheard and Mostashari 2009), and those defined inthis article arise from three sources: (a) disciplines that have used insights from CST for designing socio-technical sys-tems, such as resilience engineering and cognitive systems engineering (Hollnagel et al. 2011, Hollnagel and Woods2005); (b) reports on practical experiences of using CST insights to support process improvement in specific sectors,such as healthcare and construction (Sweeney 2006, Stroebel et al. 2005, Bertelsen and Koskela 2005, Kernick 2004);and (c) theoretical discussions on the possible use of CST to enhance the dimensions of organisational design, such asleadership (Snowden and Boone 2007). Based on these sources, a set of prescriptions was identified and then they weregrouped according to their similarity (Appendix A). The six prescriptions based on CST are as follows.

(a) Give visibility to processes and outcomes: A number of well-known mechanisms can operationalise this prescrip-tion, such as the use of warning lights and switches that read the presence of interactions and transmit relevant informa-tion (Hollnagel and Woods 2005, Perrow 1984). Rather than only emphasising abnormalities, visibility should also begiven to informal work practices, which over time may be regarded as part of normal work, as they often contribute tothe production of expected outcomes. This is necessary since the mechanisms that lead to successful outcomes areusually the same as those that lead to abnormalities, and so a number of learning opportunities might be missed (Hollna-gel et al. 2011). Techniques of task analysis, such as cognitive task analysis (Crandall, Klein, and Hoffman 2006), arefrequently adopted to give visibility to subtle informal work practices and the context that encourages them.

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Although the literature is mostly supportive of giving visibility to processes and outcomes, Bernstein (2012) makesa counter-point. He introduces the notion of a transparency paradox, whereby maintaining observability of workers mayreduce their performance by inducing those being observed to conceal their activities. Conversely, creating zones ofprivacy may, under certain conditions, increase performance. Bernstein (2012) argues that privacy is important insupporting productive deviance, localised experimentation, and distraction avoidance. Of course, it can be argued thatthe trade-off between visibility and privacy is only a major issue if visibility is associated with poor work relations, e.g.managers who enforce the use of ineffective procedures, and punish workers for not following them.

(b) Encourage diversity of perspectives when making decisions: This prescription takes advantage of the diversity ofagents and relations in a complex system, building on this to tackle uncertainty (Snowden and Boone 2007), and there-fore complexity. An assumption of this prescription is that decision-making in complex situations requires teamworkand that the team must be formed by agents holding complementary skills. The effective implementation of this pre-scription has a number of requirements, such as high levels of trust, identification of the most apt decision-makers foreach type of decision and the reduction of power differentials (Dekker 2011, Kernick 2004). As a limitation of this pre-scription, it has little use when decision-making happens under severe time pressure.

Categories of characteristics

Key aspects of the characteristics Sources

A large number of dynamically interacting elements

- The system changes over time

- The interactions are nonlinear, which means that small changes in the cause imply dramatic effects in the outcomes

- The interactions take place among tightly coupled elements (e.g., interdependence in terms of tasks, teams, production sequence), which allow for the quick propagation of errors and create difficulty in isolating failed elements

Vesterby (2008), Snowden and Boone (2007), Williams (1999), Cilliers (1998), Perrow (1984)

Wide diversity of elements

- The elements are differentiated according to a number of categories, such as hierarchical levels, division of tasks, specialisations, inputs and outputs

- The nature of the relations among the elements exhibits variety in terms of aspects such as degree of co-operation, degree of shared objectives and degree of information exchange

Dekker (2011), Vesterby (2008), Williams (1999)

Unanticipated variability

- Uncertainty, which is a result of the richness of the interactions between the elements as well as of the fact that elements receive information from indirect or inferential information sources, especially in highly automated systems

- Complex systems are open, which means that they interact with their environment, which is in itself a major source of variability

- Emergence is a well-known manifestation of unanticipated variability. An emergent phenomenon arises from interactions among the elements, independently on any central control or design

Snowden and Boone (2007), Johnson (2007), Sweeney (2006), Hollnagel (2004), Kurtz and Snowden (2003),Checkland (1999), Cilliers(1998), Perrow (1984)

Resilience

- It is the systems’ ability to adjust their functioning prior to, during, or following changes and disturbances, so that the system can sustain required operations under both expected and unexpected conditions

- Performance adjustment means filling in the gaps of procedures, whatever their extent and reason, such as under-specification for an expected situation or inapplicability for an unexpected situation

- Performance adjustment is guided by feedback, both from recent events and from the organisation’s earlier history. The assumption is that the past of a system is co-responsible for its present behavior

- Self-organisation, which enables a complex system to develop or change internal structure spontaneously and adaptively in order to cope with the environment

Hollnagel et al.(2011), Dekker (2011), Johnson (2007), Cilliers (1998)

Figure 1. Characteristics of complex systems compiled by Saurin and Sosa (in press).

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(c) Anticipate and monitor the impact of small changes: This prescription arises from the nonlinearity and high con-nectivity among the elements of a complex system, which implies that local optimisations may have global undesiredresults (Dekker 2011). The emphasis on small changes is necessary because, unlike major changes, their planning andmonitoring is easily neglected if one assumes linear relationships. If the change is small, it can be mistakenly assumedthat its impacts are predictably small and thus of little relevance (Stroebel et al. 2005). Organisations should define theirown criteria with respect to which small changes are worth being anticipated and monitored, and they should also definewhat counts as a small change. Otherwise, there is a risk of information overload and waste generated by monitoringirrelevant changes.

Some examples of practical advice to apply this prescription are: (i) to identify the starting conditions on whichchanges are made (Snowden and Boone 2007, Kernick 2004), since this provides a benchmark to assess their impacts;(ii) to take advantage of existing change management routines, e.g. when a company purchases new machinery therecan be procedures demanding the anticipation and monitoring of the impacts of this change; (iii) the prescription forencouraging diversity of perspectives may also be useful for the anticipation and monitoring of small changes, since thiscan reduce the probability of taking details for granted; and (iv) to use work permits for changing methods specified inprocedures, especially when the change has safety, quality, environmental or productivity implications, e.g. work permitsmay be necessary when maintenance workers decide to use a step ladder to change bulbs, rather than a podium (Reasonand Hobbs 2003).

(d) Design slack: This prescription is mostly intended to reduce tight couplings in order to absorb the effects of vari-ability. As a result, it aims at softening core characteristics of complex systems. More slack means available spareresources, of any sort, which can be called on in times of need (Fryer 2004). Slack might take on a number of forms,such as redundant equipment, cross-trained workers, underutilised space, excess of labour and machinery, and generoustime margins for task completion. The role of slack is vital where accidents may have catastrophic outcomes and, thus,especially in these situations, management should not be so obsessed with small efficiency gains, since this can pushthe system towards a critical safety state (Dekker 2011, Smart et al. 2003). It is also worth noting that, in tightly cou-pled systems, slack must be designed in, while in loosely coupled systems slack is intrinsic to the system’s nature(Orton and Weick 1990, Perrow 1984).

Of course, the choice of the right type and amount of slack is constrained by the particularities of each domain. Forexample, while the design of time buffers is a fairly common and effective strategy in project management (Bertelsenand Koskela 2005), the same approach is very difficult, and often technically impossible, in some process industries(Hollnagel and Woods 2005).

It is worth noting that this prescription may have a detrimental side-effect on two of the other CST prescriptions.Firstly, slack can contribute to keeping problems hidden, since the effects of disruptions will not be immediately visible,and thus there will be no pressure to control their underlying causes (Shingo 1989). Secondly, the design of slack maydisguise small changes in the system, making their anticipation and monitoring more difficult.

(e) Monitor and understand the gap between prescription and practice: The use of standardised operationalprocedures is a well-known strategy for reducing complexity, to the extent that it reduces unanticipated variability.Complex systems, such as aviation and spaceflight, have relied on the use of procedures to reduce complexity for sev-eral decades, an approach that has recently become a focus in healthcare (Drews et al. 2012, Degani and Wiener 1994).

From the CST perspective, designers and users of procedures should bear in mind that it is impossible for them tocover all possible situations. Thus, the need for filling in the gaps of procedures should not be surprising, but rather beseen as an opportunity for learning (Dekker 2003). A dramatic example of the insufficiency of procedures is reported byParies (2011), who describes improvisations made by the US Airways crew in the successful ditching of an airplane inthe Hudson River. In fact, all previous CST prescriptions should be applied in the management of procedures, to theextent that the design of a procedure is an opportunity to design a small part of a broad system. For example, designersshould take into account the perspectives of several stakeholders in order to design effective procedures (i.e. they shouldconsider the CST prescription ‘b’, mentioned earlier).

A tricky part of the CST view on procedures is that a number of authors suggest that designers should be contentwith setting minimum specifications, establishing boundaries and letting the system self-regulate into a condition thatsatisfies (Snowden and Boone 2007, Kernick 2004, Clegg 2000). Nevertheless, the literature on CST is silent on how todifferentiate between what should be specified and what should not.(f) Create an environment that supports resilience: Although resilience is an inherent property of a complex system,it can be either supported or hindered by system design. The use of the previously discussed prescriptions is a means ofcreating an environment that supports resilience (Figure 2), since: (a) the visibility of processes and outcomes tends to

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make it easier to identify when to adjust performance; (b) the monitoring of the gap between prescription and practicecan provide measures of the amplitude and frequency of the adjustments, besides raising questions about why they hap-pen; (c) the anticipation and monitoring of the impact of small changes helps to track how variability is propagatingthroughout the system, and thus how agents are adjusting to it; (d) the encouragement of diversity of perspectives whenmaking decisions reduces uncertainty in terms of when and how to adjust performance; and (e) the design of slackmakes processes loosely coupled, and thus it can provide time for the exploration of innovative solutions for adjustingperformance. Of course, a number of other prescriptions can support resilience, such as the delegation of relevantdecision-making to lower hierarchical ranks and training of high-level cognitive skills, such as planning and decision-making (Dekker 2011, Patterson and Miller 2010).

4. Prescriptions based on LP

The core principles of LP have been extensively studied, ranging from the classical studies by Japanese authors of theTPS (Shingo 1989, Ohno 1988, Monden 1984), to those that coined the term LP and popularised lean thinking(Womack, Jones, and Roos 1991), books by academics (Liker 2004), by former Toyota managers (Dennis 2002) andabstractions of LP to specific industries (Koskela 2000). Regardless of the different emphasis of each study, there is aconsensus that what characterises LP is essentially a set of management principles, which cannot be easily imitated fromToyota (Spear and Bowen 1999).

In this article, the 14 management principles of Toyota described by Liker (2004) are taken as the main referencefor the LP prescriptions for system design. This choice is due to the broad perspective taken by Liker, which emphasisesthe whole business, as well as to the fact that it is a fairly recent account of TPS. The principles, which from now onare referred to as prescriptions, are organised in four categories: (a) philosophy: base your management decisions on along-term philosophy, even at the expense of short-term financial goals; (b) process: create a continuous process flow tobring problems to the surface; use pull systems to avoid overproduction; level out the workload; build a culture ofstopping to fix problems, to get quality right the first time; standardised tasks and processes are the foundation forcontinuous improvement and employee empowerment; use visual control so no problems are hidden; use only reliable,thoroughly tested technology that serves your people and process; (c) people and partners: grow leaders whothoroughly understand the work, live the philosophy, and teach it to others; develop exceptional people and teams whofollow your company’s philosophy; respect your extended network of partners and suppliers by challenging them andhelping them to improve; and (d) problem solving: go and see for yourself to thoroughly understand the situation; make

Figure 2. Relationship among the prescriptions for managing complex systems.

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decisions slowly by consensus, thoroughly considering all options; implement decisions rapidly; become a learning orga-nisation through relentless reflection and continuous improvement.

In addition to this, it is worth considering two prescriptions of Womack and Jones (1998) that are implicit in thework of Liker: to specify value from the standpoint of the end customer and to eliminate waste along the value stream.It is worth stressing that the lean prescriptions do not necessarily describe observable behaviour, even at Toyota. In fact,they should be understood as a guide or source of orientation (Spear 1999). In the following sections of this paper, moredetails on each of these prescriptions will be introduced as necessary, in order to support the discussion on the compati-bility between LP and the nature of complex systems.

5. Framework for analysing the compatibility between LP and the nature of complex systems

The LP prescriptions are regarded as compatible with complex systems if: (a) they contribute to reducing the portion ofcomplexity which is both detrimental to performance and is largely a result of waste (i.e. unnecessary complexity); and(b) they are not in conflict with the CST prescriptions. In Sections 6 and 7 of this article, an analysis is made onwhether the LP prescriptions adhere to these two criteria, considering their potential impacts on each of the characteris-tics of complex systems presented in Section 2.

Of course, a drawback of these criteria is that it is not possible to strictly separate which characteristics of complex-ity, and to which extent, are necessary and desirable and which are not. Nevertheless, all socio-technical systems have aportion of unnecessary complexity, or waste (Pennanen and Koskela 2005). In fact, complexity is inherent in someforms of production simply because we do not know how to produce the output through linear systems, rather thanbecause complexity is intrinsically good (Perrow 1984). In other words, Perrow’s insight is that a portion of complexitycan be regarded as waste, although usually in hindsight, once the system design is improved.

6. The potential impacts of LP prescriptions on complex systems

6.1 A large number of dynamically interacting elements

Initially, it is worth recognising that the number of elements in a complex system is dependent on a myriad of factors,which are independent of whether it is designed based on LP or CST prescriptions. For example, the size of the facility,the number of employees and the type of equipment may be the result of technological constraints, customer demandand regulations, among other factors.

Nevertheless, the use of LP is likely to reduce the number of elements (a well-known adage of LP is to make morewith less), once many of them do not add value (Marley and Ward in press). As an example of this type of impact,Joosten, Bongers, and Janssen (2009) report operational benefits in hospitals using lean, such as reduced inventories andreduced queues of patients waiting for a doctor. LP can also reduce the number of interactions without reducing thenumber of elements, such as by producing product families in dedicated manufacturing lines or cells, rather than pro-ducing a myriad of different families altogether in a functional department (Hyer and Wemmerlov 2002). Overall, itcould be argued that by eliminating unnecessary elements and interactions, LP contributes to eliminate unnecessarycomplexity.

A potential conflict may arise between the CST and LP prescriptions concerning their views on slack, since the for-mer advises the preservation of slack and the latter encourages its gradual reduction, as a result of the elimination of thewaste that requires its existence. However, this conflict may not necessarily exist, since the reduction of slack promotedby LP often implies a re-allocation of resources, rather than an absolute reduction. Joosten, Bongers, and Janssen (2009)report an example of this re-allocation in a hospital, in which standardisation meant that a smaller number of physicianswas required to carry out routine tasks (i.e. it reduced the number of elements in that sub-system), freeing up the surplusphysicians to provide care to patients with more complicated conditions (i.e. increasing the number of elements inanother part of the system).

6.2 Wide diversity of elements

LP stresses the standardisation of working methods and quality specifications of a product or service, which can beinterpreted as the elimination of unnecessary diversity that causes waste. Although it can be difficult to separate neces-sary diversity from unnecessary diversity, there are reports that the use of LP in hospitals has preserved natural diversityof methods, which is needed to deal with differences between patients and their needs and deliver patient-centred care,e.g. surgical procedures are never performed in exactly the same way, and this is not a drawback (Joosten, Bongers, and

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Janssen 2009). It is also worth noting that LP encourages diversity that tackles waste, such as the use of multifunctionallabour to deal with variations in demand.

6.3 Unanticipated variability

LP supports the reduction of unanticipated variability and the design of means to deal with it. A number of lean pre-scriptions are concerned with the reduction of variability, such as the use of reliable and tested technology, continuousimprovement and the encouragement to go and see for yourself, rather than relying on indirect sources of information.The culture of stopping to fix problems can be cited as an example of a lean prescription to give visibility to unantici-pated variability and to deal with it on the spot. Of course, since the underlying causes of stoppages have been investi-gated and tackled, this prescription can also contribute to reducing unanticipated variability.

Nevertheless, it is worth noting the ambiguous impact of the LP prescription to create continuous flow. When it isapplied to a linear system, this prescription tends to reduce unanticipated variability, since designers can be quite certainon the effects of disturbances. By contrast, continuous flow in a complex system creates more opportunities for unantici-pated variability, due to the tighter couplings among the elements. For example, an insufficient number of staff in an airtraffic control system (i.e. lack of slack, which is a possible result of continuous flow) can encourage controllers to sim-plify communications with pilots in order to maintain an acceptable workload. However, a number of safety hazards canresult from not using standard phraseology.

Also, special attention should be paid to the LP prescription of standardisation. On the one hand, standardisationsupports the identification of unanticipated variability, which by definition encompasses situations not anticipated byprocedures. Standardisation can also provide guidance on which actions workers should adopt when they are confrontedwith unanticipated variability (e.g. stop the line). On the other hand, the main emphasis of standardisation is usually thereduction of unanticipated variability, although a number of tasks have a portion of human performance variability thatcannot be eliminated and another part that should not be. The portion that cannot be eliminated arises from theunpredictability of the environment, such as in the emergency department of a hospital (e.g. a patient may have a healthcondition that arises from a unique combination of illnesses) or in a construction site (e.g. unpredictable changes in theweather play an important role in determining which tasks can be done and how). The portion that should not beeliminated corresponds to the creative solutions found by those who respond to the unpredictability. Such solutions oftenought to be improvised, because the system cannot afford formal data analysis and planning.

6.4 Resilience

Concerning how the LP prescriptions support resilience, the following insights may be stressed.

(a) Considered altogether, the LP prescriptions support resilience to the extent that they provide a shared vision of whatthe expected performance should look like. Thus, although each agent adjusts its performance mostly based on the infor-mation available locally, they all share deeper assumptions (Liker and Meier 2006, Spear 1999). This makes it easierthat individual adjustments are consistent with each other.

(b) LP supports resilience by increasing the company’s responsiveness to variability arising from the external environ-ment. For example, a lean way to deal with variations in customer demand is the use of multifunctional employees.Another example of a lean way to be responsive to external variability is the design of adequate stocks, in terms ofmix, size and position in the value stream (Smalley 2004).

(c) A number of lean practices are strongly connected with resilience, such as: (i) pull production, since a process onlyundertakes a value-adding activity when there is demand from another process, i.e. each system element adjusts its per-formance to that of the other elements; and (ii) visual management, since availability of information through visual con-trols makes it easier to know when and how to adjust performance. Middelton and Joyce (2012) report a case of usingpull production and visual management in the software development process, demonstrating how these practices facili-tated teams’ self-organisation, which is an aspect of resilience.

(d) In a lean system, employees are challenged to pursue continuous improvement according to the plan-do-check-actlogic, which means that they should take a critical view on the procedures (Rother 2010, Liker 2004). In turn, critical

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thinking skills encourage insightful analysis of available information, thus supporting performance adjustment (Klein2011).

Nevertheless, it is worth noting that the LP literature does not stress the development of skills to deal with the unex-pected (a key issue in complex systems), even though it is not contrary to this. This approach makes sense in a leanmanufacturing plant, in which adding-value work is usually as repetitive and monotonous as in a Taylorist environment(Pil and Fujimoto 2007, Berggren 1992). However, in some domains the unexpected strikes more frequently and withmore serious effects than in a manufacturing plant shop-floor, and it usually brings together safety hazards, ambiguityand severe time pressure. When LP is implemented in these environments, designers of training programmes shouldseek advice from other disciplines that have dedicated theories and practices to develop a resilient workforce (Pattersonand Miller 2010, Flin, O´Connor, and Crichton 2008).

7. Discussions and conclusions

7.1 Is lean production compatible with the nature of complex systems?

The analysis of the compatibility between LP and the nature of complex systems is summarised in Figure 3. The LPprescriptions included in Figure 3 are those that were explicitly mentioned in Section 6. The assumption is that the pre-scriptions that were not mentioned in the previous section do not compromise the compatibility.

LP prescriptions Is unnecessary complexity tackled by theprescription?

Is the prescription in conflict withprescriptions from CST?

Eliminate waste Yes NoCreate continuous flow Yes, since continuous flow requires that

waste is tackled No, provided that necessary slack due to safety

reasons is not removed to create flow Standardise tasks and processes

Yes, since standardisation eliminates unnecessary diversity of elements

No, but LP should learn from CST that prescriptive procedures on how to do a task are

insufficient in a complex systemUse visual controls Yes, since visual controls make the system

less complex from the perspective of the observer

No, but LP should learn from CST that visibility should also be given to informal

work practices, rather than only to abnormalities

Use only reliable and tested technology

Yes, since reliable and tested technology reduces uncertainty and unanticipated

variability

No

Go and see for yourself to thoroughly understand the situation

Yes, since going and seeing for yourself reduces relative complexity

No. In fact, this prescription encourages paying attention to details, which is in line with the

CST prescription that recommends anticipating and monitoring the impacts of small changes

Stop production to fix problems, to get quality right the first time

Yes, to the extent that this prescription encourages the reduction of waste

No. In fact, this prescription is aligned with the CST prescription of giving visibility to processes and outcomes. Also, stopping

production to correct problems is a form of performance adjustment, which requires

resilience skills Pull production to avoid overproduction

Yes, pull production strongly relies on visual management, thus making it easier to

identify which items should be produced, how much and when

No. In fact, pull production is a means of designing resilience into a system, which is

desirable from the CST view

Make decisions slowly by consensus

Yes, since uncertainty and unanticipated variability are likely to be reduced

No. In fact, this prescription is fully aligned with the CST prescription of encouraging

multiple perspectives when making decisions Develop exceptional people and teams who follow your company’s philosophy

Yes, the more qualified an individual or team, the more visible the complexity is

likely to seem to them

No. In fact, this prescription is fully aligned with the CST prescription of developing

resilience skills. Moreover, CST provides a vision of what exceptional people and teams

should look like in a complex system (i.e. resilient)

Figure 3. Summary of the assessment of compatibility between LP and the nature of complex systems.

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The overall conclusion that can be drawn from Figure 3 is that LP is compatible with the nature of complexsystems. In fact, LP contributes to tackling both relative and objective unnecessary complexity. Concerning relativecomplexity, it can be reduced through mechanisms such as the use of visual controls. Indeed, the real elements of a sys-tem can remain unchanged when there is visual management, but it becomes easier to make sense of them. Concerningobjective complexity, the most obvious example of reduction through LP consists of reducing the number of elementsin the system.

7.2 What LP can learn from CST?

Based on the discussion presented in previous sections, five examples illustrate how LP can learn from CST.

(a) Giving visibility to informal work practices subtly incorporated into everyday work, rather than only to abnormali-ties. In this respect, it is necessary to distinguish between the CST and LP views on abnormalities. From the LP view,an abnormality is the same as waste, and its identification is expected to be a clear-cut process, involving little or noambiguity (Spear and Bowen 1999). From the CST view, abnormalities only exist in hindsight, being regarded as suchonly after an unexpected outcome (Hollnagel 2012, Dekker 2011).

(b) Emphasising the development of workers’ resilience skills, which help to fill in the gaps of procedures. These skillshave usually been identified from knowledge elicitation from domain experts (Crandall, Klein, and Hoffman 2006). Incomplex systems such as aviation and healthcare, the development of resilience skills has been operationalised throughscenario-based training (SBT), which encourages problem-solving in realistic and complex scenarios, including perfor-mance measurement and feedback (Salas, Guthrie, and Burke 2007). The use of serious games, which is a widespreadstrategy for teaching LP and operations management concepts in general, can be a means of operationalising SBT fordeveloping workers’ resilience skills. However, games for teaching LP usually have a lack of stress on soft skills as wellas a lack of realism (Badurdeen et al. 2010). These are major drawbacks from the CST view, since: in comparison withtechnical skills, soft skills (e.g. interpersonal and social) perform a greater role in dealing with unanticipated variability,as they are relatively less domain-specific, and are thus more generalisable (Saurin, Wachs, and Henriqson 2013); train-ees are unlikely to practice the management of relevant unanticipated variability if the training scenario is unrealistic. Infact, the way SBT is conducted from the CST view can be insightful for serious games aimed at teaching LP. For exam-ple, SBT from the CST view encourages trainees to identify the work constraints (i.e. possible wastes) that create theneed for resilience skills. It also encourages trainees to identify work system design improvements that could eitherfacilitate or minimise the need for resilience skills (Saurin, Wachs, and Henriqson 2013).

(c) Stressing the importance of slack for safety reasons. Regardless of the benefits of lean practices for occupationalhealth and safety (Hafey 2009), LP does not have any formalised view on system accidents, i.e. events involving theunanticipated interaction of multiple failures (Perrow 1984). Assuming that preventing occupational accidents impliespreventing system accidents is a well-known mistake (Baker 2007). Moreover, there are claims that the LP approach tosafety is strongly based on the assumptions of behaviour-based safety (Wokutch and Vansandt 2000), which has beenheavily criticised for its ineffectiveness in dealing with the complexity of system accidents (Hollnagel et al. 2011). Thus,LP implementation in complex systems should provide slack for preventing both occupational and system accidents.

(d) Anticipating the side-effects of introducing slack, such as the creation of new possibilities for undesired interactions.For example, the use of multifunctional workers (i.e. a form of slack) can increase the possibility of some forms ofhuman error, since people are more prone to perform non-routine tasks. This side-effect is more likely if multifunction-ality increases work intensity too much. Similarly, reduction of setup times (i.e. a form of slack of capacity) may simplybe an encouragement for overproduction, rather than for producing smaller batches. This side-effect is more likely ifworkers receive financial incentives to improve the efficiency of the machines under their control (Maskell and Baggaley2003).

(e) Broadening the perspectives on the types of procedures that can be used to control a system. This is necessarybecause the guidance provided by LP on the design of procedures is mostly focused on the work of front-lineworkers doing repetitive tasks (see, for example, Rother and Harris 2001). Thus, designers of procedures incomplex systems using LP may be tempted to take this guidance for granted. Indeed, typical lean procedures aresupposed to include specifications on the content, time, sequence and outcomes of each task (Spear and Bowen

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1999, Monden 1984). However, a number of other types of information could be included in a procedure, such astriggers to identify when to engage an adaptation, how long an adaptation should persist, and when to disengagethe adaptation (Feigh et al. 2012). Moreover, for tasks highly unstructured and subject to much variability, goal-ori-ented procedures could be sufficient, without any specification of the means. Blakstad (2006) presents an exampleof what this kind of goal-oriented procedure looks like. It concerns the provision of resources for maintaining skilllevels in the workforce of the Norwegian railways: “the one who runs railway activities has to decide scope andfrequency for repetition of education for those tasks mentioned in … to ensure that built up knowledge, built-upskills and attitudes are maintained”. The use of random storage, a warehouse management practice, is anotherexample of how procedures can, at the same time, ensure flexibility and rely on decisions made by workers on thespot. While this type of storage is guided by some general rules (e.g. staff uses hand-held scanners to tell the com-puter where goods are located), workers may store most goods on any free shelf, saving space and planning effort(Tompkins et al. 1996).

As a drawback, it is difficult to implement the necessary conditions for goal-oriented procedures to be successful(e.g. a resilient workforce is necessary). If these conditions are not in place, workers are likely to feel uncomfortablewith the absence of detailed procedural guidance (Blakstad, Hovden, and Rosness 2010, Fryer 2004). Moreover, goal-oriented procedures can become as irrelevant as prescriptive ones in a highly unstable system, since operators may haveto trade-off goals under time pressure.

Also, CST may support the control of factors that have been identified as contributors to failed LP implementations,such as the following.

(a) Lack of managers’ ability, experience and knowledge to conduct the LP implementation process (Bhasin 2012, Pan-izzolo et al. 2012). As discussed above, CST supports the identification of the limits of LP, and thus it helps managersto identify when and how lean practices should be adapted.

(b) Lack of workers’ autonomy to make changes (Bhasin 2012, Scherrer-Rathje, Boyle, and Deflorin 2009). The recog-nition of the limits of centralised control is at the heart of complexity thinking, thus granting autonomy and authority tofront-line workers is seen as consistent with the system’s nature. For instance, in a surgery team designed in accordancewith CST, any member of staff, regardless of rank, is trained and encouraged to speak up if he/she detects errors com-mitted by someone else (Brown 2008). This is also an established best practice in aviation cockpits, in which the firstofficer must supervise the work of the captain, and vice versa (Henriqson et al. 2011).

(c) Lack of anticipation of the systemic impacts of LP throughout all areas of the organisation (e.g. human resources,purchasing, etc.), well beyond the shop floor (Hodge et al. 2011). Indeed, the emphasis on managing interactions,managing trade-offs, and anticipating side-effects, is a value of CST. Therefore, a LP implementation process that con-siders CST prescriptions should be naturally concerned with managing wider impacts of individual lean practices andprinciples. These impacts simply cannot be ignored if the system is managed as a complex one.

From a broader perspective, the LP learning opportunities presented in this section indicate that LP implemen-tations should seek theoretical and practical advice from other disciplines, an endeavour that is not encouraged bythe mainly practitioner-oriented literature. In fact, most, if not all, LP prescriptions can be associated with a spe-cific discipline (e.g. decision-making and training), which implies that it can be studied and implemented frommany perspectives. LP prescriptions are underspecified to different degrees, and so they have theoretical and practi-cal gaps that can be filled with support from other disciplines, as illustrated by the examples on standardisationand training.

7.3 Limitations of this study

First of all, a limitation of this study is that it relies on a literature review, and no field study was undertaken to assessthe compatibility in a real setting. Also, if the application of the framework is envisioned for a field study, it should besupplemented by other methods. For example, it may be necessary to characterise the complexity of the system underanalysis, so some guidance should be provided on which data is necessary for such characterisation. Likewise, anassessment of the leanness of the system would also be necessary, which in this case could take advantage of a numberof existing methods for this purpose. Last, but not least, it should be stressed again that the proposed framework isunderspecified in terms of separating necessary from unnecessary complexity, which indeed would be helpful to identifywhether or not LP is tackling the type of complexity it should tackle.

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7.4 Opportunities for future studies

A research agenda may be proposed based on the limitations and insights identified in this article: (a) to use the analysisframework adopted in this article to undertake a deeper analysis of the extent to which specific lean practices are tai-lored to the nature of complexity; (b) to develop methods for managing complex systems that integrate the lean andCST prescriptions, building on their complementarities; (c) to analyse LP from the perspective of other theories on sys-tems functioning (e.g. system dynamics, systems engineering and soft systems methodology), since this can support theunderstanding of the relationships among the lean practices and principles; and (d) to compare the CST and LP perspec-tives on how to describe a system, which is a requirement to design it. As an example of the importance of this line ofinquiry, while a value stream map is a lean way to describe a system, it is mostly a description from a technical per-spective, neglecting social dimensions such as culture and relationships.

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Appendix A: Prescriptions based on complex systems theory

Prescription/sources 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Design slackProvide sufficient time for the agents to do their work XA system needs built-in redundancy XToo much focus on short-term gains can remove adaptivecapacity

X X

Make small experiments with unruly technology XDesign in layers that isolate elements with different rates ofchange from each other

X

Keep multiple options viable; provide clear alternatives forevaluation

X X

Give visibility to processes and outcomesMake complexity visible, so the agents can learn X XSystems should make problems visible XProvide good predictions or support anticipation X

Create an environment that supports resilienceLearning must be based on everyday work, rather than only onfailures

X

Inspections of parts should pursue interconnections withsurrounding parts, even those that are external to the sub-system

X

Increase the variety of the controller X X XOperator knowledge may reduce unexpected interactions XGive feedback to support performance adjustment X XSupport people’s skills at judging when and how to adapt X X XStudy what people actually do and then consider whether it ispossible to support that through design

X

Allow components to be used for uses that were notenvisioned when they were created

X

Vision, mission and shared values guide the change process XCreating time and space for reflection is necessary to adapt tochange

X

Change requires leadership actively involved in the changeprocess, ensuring participation from all members

X

Be attentive to the front-line, where the real work gets done XReallocate slack to create resilience XDifferentiate between normal times, high-tempo times, andemergencies. Decision-making should be different in eachmode

X

Encourage diversity of perspectives when making decisionsEncourage diversity of opinions and perspectives, making surethat there is a consideration of the weighting of their voices

X X X X X X

Connect people and groups as much as possible X XFind the right experts to participate in decision-making X

(Continued)

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Appendix A. (Continued).

Prescription/sources 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Anticipate and monitor the impacts of small changesLocal optimisation may become a global disaster X XManage starting conditions and monitor for emergence X XDo not neglect weak signals XForget the last bit of optimisation and freeze specifications ofsecond-priority components early

X

Monitor and understand the gap between prescription andpractice

Set minimum specifications and let the system self-regulate X X XThere are limits to the ability to design and plan; recognise therole of self-organisation

X X X

Procedures are resources for action, and good performanceresults from people being skillful at judging when and howto adapt

X

Monitor and understand the reasons behind the gap betweenprocedures and practice

X X

(1) Perrow (1984); (2) Clegg (2000); (3) Stacey, Griffin, and Shaw (2000); (4) Weick and Sutcliffe (2001); (5) Dekker (2003); (6) Smart et al. (2003);(7) Kernick (2006); (8) Sweeney (2006); (9) Hollnagel and Woods (2005); (10) Stroebel et al. (2005); (11) Snowden and Boone (2007); (12) Sheardand Mostashari (2009); (13) Dekker (2011); (14) Hollnagel et al. (2011)

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