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Notes on progress in structuring a research project measuring energy inputs into New Zealand apple production--combining hard and soft systems methods.


Projects that measure energy use in food chains following the general life cycle analysis (LCA) methodology typically follow one of the two methods (Nielsen and Weidema, 2001). Input-output analyses utilize economic data, while process-based methods derive metrics from the processes within the production system. Both methods are effectively scientific accounting methods that generate numerical indicators providing a comparison of different production systems. The LCA methodology is used to identify environmental 'hotspots' in a production system. A specific process-based variation derived from lean thinking has been proposed as an appropriate method for the present research. A premise of this paper is that the application of scientific methodologies to complex systems has inherent limitations that should be explicitly acknowledged by the researcher, and reflected in both the experimental design and the presentation of findings.

New Zealand apple production operates in the global marketplace. It therefore exists within global food supply and energy systems. The present energy study requires a conceptual model of the system in which to locate the research, and define the research boundaries. An important preliminary component of this research has been to explore holistic models that best represent the systemic nature of the industry. To describe the research context, a method or a view is required that allows the apple industry to be visualized as a coherent whole, and the problems to be structured appropriately and meaningfully. In addition, a broad view of the context of the research itself is required, and it is progress in structuring this view that is reported in this paper. Systems literature is recognized as providing a basis for metal-level problem structuring (Checkland and Scholes, 1990; Rosenhead and Mingers, 2001).

The specific problem that is addressed here is the need to utilize a scientific method (derived from lean thinking) that can be criticized as linear and 'reductionist' to gain understanding about a complex system. Issues derived from the method itself are examined, and a broad context for conducting the research and presenting its findings is proposed.

To provide a general systems context for the present research we can draw from Churchman (1979). In a discussion of scientific research, this author confirms the location of disciplines such as astronomy, geology and archaeology in which there 'appears to be no laboratory as such' and in which the scientist has 'no feasible way of manipulating the variables', within the context of scientific research. In the present research there is no laboratory, but the researcher must attempt to apply Churchman's 'careful controls' and attempt to eliminate 'nuisance variables and observer interference' in order to develop an understanding of the system. Churchman (1979) goes on to warn that the extension of the scientific method into the planning arena through experimental interventions is dangerous and potentially immoral. As the purpose of the present research is to provide a basis for strategic planning, this warning must be heeded.

However, the immediate objective of generating a comparative metric for energy usage requires a focussed scientific method. The word 'require' implies an imperative that can be expressed as the socio-economic and political justification of the activities of a production system. The beauty (and Achilles heel) of deploying scientific methods to study complex systems is that the scientific method reduces and simplifies the complex system to metrics that invite the observer to form value judgements. The arena of energy usage and carbon emissions is globally topical, and the risk is that value judgements beyond the authority of the actual research may be formed from research findings by popular press or political interests. Although not a deliberate experimental intervention, the simple act of reporting data may engender a response that is unexpected and inappropriate. Churchman (1979) articulates this danger in the statement:

'all this amounts to saying that the planning laboratory cannot be decoupled from the rest of society'.

Literature has been published offering values for energy inputs in apple production (Jones, 2002; Mila i Canals, 2003; Simons and Mason, 2003; Blanke and Burdick, 2005; Saunders et al., 2006). A criticism of this style of analysis is that the functionality and practicality of the method can arguably take precedence over a holistic, systemic viewpoint. Advocates of the LCA method would no doubt dispute this criticism, as the rationale for the development of the LCA method was to provide a holistic understanding of production systems. However, now that the method exists, the danger is that it is followed prescriptively without recourse to broader systemic enquiry.


The systems component of the present research project could be regarded as counterbalancing the risk of inappropriate interpretation by providing a broad context for the research project. An examination of the experimental methods through systemic filters should place explicit limitations on subsequent value judgements. However regarding a systems viewpoint as a counterbalance to a scientific approach implies that the two approaches can sit comfortably at the same level. Churchman (1979) appears to view science as a subordinate of the systems approach. He states:

'the ambitions of the systems approach are enormous, going far beyond the classical laboratory's ambition to measure and test hypotheses.'

The systems viewpoint appears to sit hierarchically at a higher level than scientific methodology, scientific study falling within a systems approach rather than alongside it. If systemic understanding is the end, then scientific analysis is a means.

Midgley (2003) discusses the role of science in systemic enquiry from the starting point of intervention rather than observation. He argues that:

'the construction of scientific observation should be regarded as a form, but by no means the only valid or useful form, of intervention.'

This author argues that systems thinking recognizes the interconnection of everything in the universe, and from this he develops an argument that scientific observation is constructed by the observer. Since the observer cannot ever be entirely separated from the subject being observed, then observation is a form of intervention. Midgley (2003) concludes that:

'we should welcome scientific techniques of observation into a pluralistic armoury of intervention methods.'

In the present research, the observation, and particularly the reporting of energy data can clearly be seen to be an intervention.

Midgley (2003) also warns that social purposes should not be subordinated to methodological purity. In the present context, the social purpose is the desire to improve local production systems in order to mitigate potentially harmful environmental consequences and to maintain competitiveness in global markets. The methodological purity in question is the LCA method and its derivatives. The danger is if the scientific method is followed prescriptively, the observations and the reporting of them may constitute a significant and unpredictable intervention. Midgley (2003) balances this warning by conceding that it is better to base organizational decisions on imperfect data than no data at all.


A recurring theme in systems literature (Midgley, 2000; Midgley, 2003; Ulrich, 2000) is the proper consideration and attention to boundaries. In the context of the present study of energy in apple production, an examination of the selected scientific method suggests that the method itself may constitute a lens that impacts on the boundaries of the reference system.

The application of the process flow mapping method (Simons and Mason, 2003; Hines and Rich, 1997) has been reported in a study of carbon emissions in an apple supply chain. This method is adapted from lean thinking (Womack and Jones, 1996), a methodology that can be extended to provide both qualitative analysis and quantitative metrics associated with research objectives. However lean thinking incorporates a set of assumptions and philosophies that may impinge on the research outcomes.

Lean thinking emerged from the chaos of late 20th century quality methodologies as a set of tools and concepts that can be usefully applied across all levels of manufacturing industry. A core concept of lean thinking is waste reduction. Kaizen literature describes the identification and elimination of waste in industrial processes, crediting many of the concepts to former Toyota Vice President Taiichi Ohno and quality guru Kaoru Ishikawa (Imai, 1986; Imai, 1997). The seven wastes identified by Ohno and accepted as core elements of lean thinking are:

1. Overproduction

2. Waiting

3. Transporting

4. Inappropriate Processing

5. Unnecessary/Excess Motion

6. Defects.

Energy usage, the focus of the present research, can be argued to be a cost but not waste per se. In environmental literature, waste is synonymous with emissions to the environment (Mila i Canals, 2003). Energy usage certainly results directly and indirectly in emissions to the environment, some of which can be regarded as waste. In adopting the lean methodology, we have to be aware of the distinction between the word waste in lean terminology, and the perhaps less precise use, and with quite a different emphasis, in environmental literature. In these notes the word 'waste' will be used in the lean sense.

In lean thinking waste is intrinsically linked to value creation (Womack and Jones, 1996). Lean has been interpreted as 'doing more with less' (Simons and Mason, 2003). These authors argue that the lean method value-stream-mapping can be adapted to 'operationalize green thinking'. However, before this method is adopted more widely as an environmental technique, the pre-suppositions of lean thinking should be examined in order to expose boundary judgements that they may impose on a systemic viewpoint.

Lean thinking was proposed as a means for industries to adopt the principles observed within the Toyota Motor Company by the MIT International Motor Vehicle Program team. Toyota has been described (Womack et al., 1990) as managing its enterprise within a holistic system that integrates human resources management, supply chain structure and product development with the low inventory 'pull' system of just-in-time (JIT). The word 'holistic' is used here as a descriptor for methods that are expansive or outward looking, but fall short of a rigorous systems approach. Churchman (1979) insists that a key aspect of the systems approach is its recognition not only of the desirability of the ends resulting from a course of action, but whether the intervention is ethically defensible. The ethics of the lean thinking approach have been examined closely, particularly where 'lean' is being applied in industries such as healthcare where human well being is a primary objective (Nelson-Peterson and Leppa, 2007). In the present research, the ethical issues at stake include the rights and well being of individuals and organizations, plus local, national and global environmental concerns.

The roots of lean thinking can be traced back through various disciplines including management science and operations research (MS/OR), industrial engineering (IE) and total quality management (TQM). Most of the lean principles are consistent with the teachings of the early American quality gurus Deming and Juran (Beckford, 1998). However, there exists a case for lean thinking evolving almost entirely through the historical circumstances of the Toyota Motor Company, and the innovative approach of its managers (Womack et al., 1990).

Can we apply lean thinking to the measurement of carbon emissions in apple production? The simple answer to this question is yes based on the academic precedent (Simons and Mason, 2003). However, this justification may offend the tenet (Midgley, 2003) that social purposes should not be subordinated to methodological purity, or the more contentious principle (Ulrich, 2001) that methodology should not take precedence over boundary judgements. The question remains as to whether we should, and whether the results we achieve are useful. The 'moon-ghetto' metaphor (Rosenhead and Mingers, 2001) exposes the questionable assumption that the methods that got man to the moon are appropriate for solving the problems of inner city ghettos. This metaphor is used to criticize interventions that have proven ineffectual rather than challenging the legitimacy of a demonstrably effective method, so although the metaphor requires the practitioner to proceed with caution, it does not answer the question definitively.

To answer the question, and to provide a rationale for proceeding with (or rejecting) a method that stems from an entirely different context from the present problem, we can draw from problem structuring literature. An argument is constructed (Rosenhead and Mingers, 2001) in support of a problem structuring method adopting formulations of a dichotomy in situation types characterized by five different authors: Ackoff distinguishes between problems and messes, Rittel between wicked versus tame, Schon between swamp versus high ground, Raverts between practical versus technical and Checkland between hard versus soft systems. Selecting 'hard and soft systems' as a representative of these dichotomies we can pose two questions:

1. Is lean thinking primarily a hard systems methodology or a soft systems methodology?

2. Is the issue of energy use in apple production primarily a hard technical issue, or primarily a soft systems issue?

Some lean methods are certainly hard system problem-solving methods, having roots in statistically based quality methodologies. Quality science and TQM practices developed out of a genre of methods that are more closely associated with the problem/tame/high ground/ technical/hard system side of the dichotomy. Lean thinking claims to consider the value stream as a whole, and succeeds in as much as it avoids focussing on local process silos. This holistic view is consistent with soft systems approaches. However, the boundaries of lean thinking are deliberately constructed as close to the value stream as possible. This lean philosophy is encapsulated in the powerful concept of gemba, which is defined as the point at which value is added (Womack and Jones, 1996; Imai, 1997). The points in the value stream at which the product undergoes a transition that brings it closer to customer-defined value are gemba. In lean thinking, activities that do not add value are muda or waste. The difficulty with this concept as a systems tool is that the value frameworks of the end consumer predetermine some of the boundary judgements of the analysis. That is, the lean methodology excludes those components of the system that are not valued by the end consumer. Systems thinking does not sit well with a methodology that deliberately excludes some categories of stakeholders. Contrast this with the soft systems method SAST (Mitroff, 1979) that is based around an examination of assumptions about stakeholders, and is inclusive with respect to stakeholder groups.

Lean thinking has adopted methods such as the seven new management and planning tools (Brassard, 1996), which can be considered soft systems methods. However the specific lean method under examination is sustainable value stream mapping, which is clearly weighted toward the technical, hard system side of the dichotomy.

The terms 'value stream mapping' and 'process flow mapping' are used more or less interchangeably in lean literature. Some discipline has been imposed on what is described as an 'ill-defined and ill-characterized toolkit' (Hines and Rich, 1997). These authors offer a typology of seven tools that they regard as comprising value stream mapping. The seven tools, including demand amplification mapping which stems from systems dynamics methodology, deal with processes and data and confirm value stream mapping as constituting a hard systems analysis method. Returning to the broad context derived from Churchman (1979), we can now confirm lean thinking as a scientific tool, whose products should be subject to, and presented in the context of a systemic examination.

Having considered the nature of the tools, we turn to a consideration of the nature of the industry being examined. The apple production industry is built from a base of horticultural science, which although complex is firmly seated in the technical arena. The mechanisms for distributing apples are also technically based. Marketing fruit can be understood in terms of MS, and the individual preferences of the end consumer understood within the bounds of human psychology. Our focus on energy with its inevitable link to global climate change is also essentially a scientific problem, and although the issues are complex and difficult, the literature appears to support a technical approach.


However, when these hard systems are assembled into a whole, a fundamental tenet of systems theory, that the whole is greater than the sum of its parts, becomes apparent. The emergent properties of the apple production system are not as spectacular as the emergent properties of an organism for example, but they are still evident. The New Zealand apple production system provides social and economic benefits (for New Zealand) and poses regional conundrums that none of the parts or the sum of them generates.

The apple industry in New Zealand provides casual seasonal employment. This provides an opportunity for low-income families from the Pacific region. In the global warming scenario, these very Pacific communities are at risk from rising sea levels and climatic change. Apple production is contributing to the economic welfare of these communities, but is also dependent on global energy supply systems. These complex interrelated issues are much more consistent with low ground, mess or soft system representations. It is argued (Rosenhead and Mingers, 2001) that:

'there is a type of problem context for which 'hard' methods are unhelpful' and 'appropriate methods for problem situations of this kind need to mesh with their interactive decision processes'.

The characteristics of 'swamp' conditions (after Schon) are described as having multiple actors, multiple perspectives, incommensurable or conflicting interests and prominent intangibles. The issues of energy usage in the apple industry are consistent with some of these descriptions, although not to the extent of the examples provided by those authors.

The system of apple production has characteristics that can, and arguably should, be studied and represented by a range of methods. Support is found (Mingers, 2000) for adopting a range of appropriate methodologies. This author specifically advises the use of a combination of appropriate methods, in this context from the MS/OR disciplines. He provides general principles for designing an appropriate research structure. The system of systems methodologies (SOSM) typology (Jackson and Keys, 1984) describes three categories:

1. Unitary-general agreement of stakeholder assumptions.

2. Pluralist-differing but reconcilable stakeholder assumptions.

3. Coercive-differing and irreconcilable stakeholder assumptions.

The apple industry supply chain has characteristics that arguably fit the pluralist category better than unitary or coercive. However even in making this pre-analytical judgement we run into difficulties. We are warned (Ulrich, 2001) against assuming a problem situation to be non-coercive, and therefore not requiring a systematic process of boundary critique.


So, if we are to use sustainable value stream mapping to study the apple industry, we must proceed with some caution, as while the system itself is messy, the lean analytical process is logical if not linear. Caution can be achieved by subjugating the lean methodology to methods derived from soft systems thinking, with particular attention to boundary critique. Various authors (Jackson, 2000; Rosenhead and Mingers, 2001) provide compilations of methods that are useful in the creative design of methods. In addition the seven management and planning tools, which are accepted within the lean methodology, could be considered useful in studying both hard problems and soft issues.

In the present environment in which energy use and associated carbon emissions are coming under intense scrutiny, it is imperative that methodologies selected to study and report those issues are well designed and robust. The use of hard systems methods alone may well provide metrics that appear to be useful, but the use of those metrics to drive organizational strategy and policy must be questioned. Locating hard systems methods, and reporting results derived from them, within an overarching soft systems approach should provide a structure and mechanism for examining global supply streams in an holistic and robust manner.


Research Sponsor Pipfruit NZ Ref MA04P09.01


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Thomas Gregory Frater (1) and Donald James Houston (2) *

(1) School of Engineering and Advanced Technology, Massey University, New Zealand

(2) Staff Development and Training Unit, Flinders University, Adelaide, Australia

* Correspondence to: Donald James Houston, Staff Development and Training Unit, Information Science & Technology Building, Flinders University, Room 321a, GPO Box 2100, Adelaide, SA 5001, Australia.

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Title Annotation:Research Note
Author:Frater, Thomas Gregory; Houston, Donald James
Publication:Systems Research and Behavioral Science
Date:Nov 1, 2008
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