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Supply Chain Proficiency in Relation to Resilience, Robustness,
Social-Ecological Innovation and Enterprise Sustainability
Rick Edgeman, Professor of Performance & Enterprise Excellence
Interdisciplinary Center for Organizational Excellence & AU-Herning
Aarhus University
Aarhus, Denmark
Zhaohui Wu, Associate Professor of Supply Chain Management
College of Business
Oregon State University
Corvallis, Oregon, USA
Abstract
Purpose – To broadly explore the contributions of supply chain proficiency in relation to
Sustainable Enterprise Excellence, Resilience and Robustness (SEER2).
Design/methodology/approach – A pre-existing SEER2 model, referred to as the Springboard
to SEER2 is put under the microscope to determine specific interactions of supply chain
proficiency with six key areas of the Springboard: triple top line strategy and governance;
strategy execution via policies, processes, and partnerships; financial and marketplace
performance and impact; sustainability performance and impact; human ecology and capital
performance and impact; and social-ecological and general innovation and continuous
improvement performance and impact.
Findings – Supply chain proficiency is integral to attainment of Sustainable Enterprise
Excellence, Resilience and Robustness (SEER2). As such, supply chain proficiency must be
thoughtfully and strategically approached, with success critical to enterprise contribution to
mitigation or solution of wicked global challenges ranging from climate change, to food
insecurity to societal conflict.
Originality/value – This paper reveals in depth the centrality of supply chain proficiency to
Sustainable Enterprise Excellence, Resilience and Robustness, suggesting that such models as
those behind the Malcolm Baldrige National Quality Award and the European Quality Award
might be enhanced by more deeply considering the importance of the supply chain to business
and performance excellence.
Keywords – Assessment, big data analytics, governance, resilience, robustness, social-ecological
innovation, supply chain proficiency, sustainable enterprise excellence, triple bottom line, triple
top line.
Paper type – Research paper
Introduction
Sustainable enterprise excellence, resilience, and robustness (SEER2) are important, desirable,
and related, but not wholly consonant enterprise traits, with objectives that differ in subtle yet
important ways. Multiple enablers of SEER2 have been identified (Edgeman, 2013; Edgeman
and Eskildsen, 2014a; Edgeman and Williams, 2014), among which are governance, big data
intelligence and analytics, operational & supply chain proficiency, general- and social-ecological
innovation (Edgeman and Eskildsen, 2014b), and human ecology.
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SEER2 results from strategic and tactical integration of critical principles and practices from the
business excellence and sustainability movements, where:
Sustainable enterprise excellence, resilience and robustness balance the complementary
and competing interests of key stakeholder segments, including society and the natural
environment and increases the likelihood of superior and sustainable competitive
positioning and hence long-term enterprise success that is defined by continuously
relevant and responsible governance, strategy, actions and performance. This is
accomplished through ethical, efficient and effective (E3) enterprise governance
(Elkington, 2006) and strategy that emphasize superior organization design & function,
innovation, enterprise intelligence & analytics, operational, supply chain, customer-
related, human capital, financial, marketplace, societal, and environmental strategy and
performance. Sustainable enterprise excellence results from driving 3E triple top line
strategy (McDonough and Braungart, 2002a) throughout enterprise culture, processes,
and activities to produce superior triple bottom line 3P performance (Elkington, 1997)
that is simultaneously pragmatic, innovative and supportive of enterprise resilience and
robustness.
While numerous forms of innovation are important to SEER2, both general and – especially -
social-ecological innovation are emphasized in SEER2. Social-ecological innovation (SEI)
occurs at the interface of sustainable innovation and innovation for sustainability. Sustainable
innovation is central to organizational culture when innovation is regular, rigorous, systematic,
systemic, and a focal part of enterprise strategy. Innovation for sustainability explicitly targets
social or environmental outcomes that are tangibly and positively linked to both general and
enterprise financial performance so that SEI partially enables transformation of triple top line
strategy into triple bottom line performance.
SEI is critical to enterprise resilience and robustness where resilience is an enterprise’s capacity
to self-renew through innovation (Reinmoeller and Van Baardwijk, 2005) and adapt its responses
over time to negative shocks or extreme challenges (Contu, 2002). Robustness is resistance or
immunity to such impacts and challenges through formation and execution of an array of
enterprise strategies, policies, partnerships, and practices that maintain enterprise competitive
position or transform extreme challenges into opportunities, thus avoiding any necessity to
rebound. Realizing SEER2 requires tradeoffs between optimal performance, resilience and
robustness, a dilemma that arises since performance of a robust and resilient enterprise rarely
matches the efficiency of less robust and less resilient “optimum” one, but instead delivers
performance that does not deteriorate as precipitously or rapidly (Anderies et al., 2004).
SEER2 and SEI are central to continuously relevant and responsible organizations (Edgeman et
al., 2013) with focus herein directed to elaboration of supply chain proficiency contributions to
and interrelationships with SEER2 and SEI.
Sustainable enterprise excellence, resilience and robustness
Enterprise sustainability is its capacity to create and maintain economic, environmental and
social value for itself, its stakeholders and society at large, in the short term and for the long term
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–sustainability is the capacity to survive. Although survival is attractive in most cases, there are
complementary performance considerations that, when integrated with survival, enhance
enterprise performance including stakeholder perception (Wang and Qian, 2011) that translates
into financial and marketplace performance (Harrison et al., 2010).
What are these complementary considerations?
If sustainability connotes with survival, then excellence is the capacity of the enterprise to
prosper via delivery of superior performance across an array of defined domains. Performance
domains considered vital to enterprise excellence include big and small data analytics and
intelligence, corporate governance and leadership, operations and supply chain management,
innovation, and enterprise human ecology. By human ecology we intend the relationships
between the enterprise and its human capital with its supply chain and extended social, natural,
and built environments (Lozano, 2011), including competition, cooperation and collaboration
among individuals and entities within the enterprise and across boundaries.
Strongly related to sustainability and excellence are resilience and robustness, and though these
are sometimes used synonymously, they have both shared and unique qualities. Though
Reinmoeller and Van Baardwijk (2005) characterize resilience as enterprise capacity to self-
renew over time through innovation, more generally resilience may be thought of as the ability of
an enterprise to continually change, reinvent itself, and adapt its responses to negative shocks or
extreme challenges in a multi-faceted ecosystem that includes political, social, economic and
other aspects of its competitive domain (Contu, 2002). In contrast, robustness is immunity or
resistance to impacts from such shocks or challenges (Scholz et al., 2012) and is gained
principally via formulation and execution of an array of strategies, policies, partnerships, and
practices that maintain enterprise competitive position despite adverse conditions.
Enterprise excellence, sustainability, resilience, and robustness – the components of SEER2 – are
related yet not wholly consonant constructs in the sense that the strategy, policies, and actions set
optimizing one of these is unlikely to optimize the others. Important questions thus include ones
of how significantly optimization of a singular component will lead to departure of each of the
remaining components of SEER2 from their optima, as well as which one of the SEER2
components is best to singularly optimize at the expense of the others. Edgeman and Williams
(2014) provide a conceptual calculus that captures the essence of this argument. They do so
through formulation of a coefficient of enterprise resilience and robustness (CER2) that is
derived by integrating and adapting Isaac Newton’s coefficient of restitution and Leonardo Da
Vinci’s coefficient of friction. Optimization of CER2 and hence enterprise resilience and
robustness include conceptual analogs to steepest ascent and descent methods (Box and Draper,
1987) and formulation of minimax regret strategy (Blackwell and Girshick, 1954).
Mathematically, a solution derived from a holistic approach that simultaneously explores and
harnesses synergies and reconciles dissonances among sustainability, excellence, resilience and
robustness will always dominate solutions derived from optimizing one of the SEER2
components in preference to the others. The extent of dominance depends on the degree to which
overall results are sensitive to the component of SEER2 selected for optimization with the
preference for a holistic approach – e.g. joint, constrained optimization – increasing as
4
dissonance increases. It must be noted that mathematical concepts and language have been used
to describe the inherently qualitative constructs of sustainability, excellence, resilience and
robustness and that such holistic approaches generally derive from “making soft measures
harder” through use of carefully crafted, linguistically expressed maturity scales that are
sensitive to enterprise context and preferences.
From whence SEER2 comes and whither it goes?
The sustainability movement is closely associated with the triple bottom line that stresses a blend
of societal, ecological, and economic benefits (Elkington, 1997), yet the focus of many of its
advocates is inherently social-ecological, dedicating scant attention to the economic performance
dimension that is cornerstone to enterprise excellence. Similarly, enterprise excellence adherents
have historically devaluated the triple bottom line’s social and environmental dimensions.
Sustainable Enterprise Excellence (SEE) targets strategic integration of principles,
methodologies, and standards common to the enterprise excellence and sustainability movements
(Edgeman and Eskildsen, 2013) as a means of realizing Zadek’s (1999) vision of their
unification and subsequent joint, albeit constrained optimization of enterprise performance
across the triple bottom line people, planet, and profit (3P) domains, along with other related
domains.
Prior attempts at SEE have primarily focused on addition of sustainability modules or
perspectives to established excellence models, rather than on full integration of excellence and
sustainability. Although such efforts acknowledge sustainability, they have generally
marginalized its importance and have only poorly leveraged synergies, reconciled dissonances,
or prioritized sustainability performance. Among enterprise excellence models are the balanced
scorecard (Kaplan & Norton, 1992) and those supporting America’s Baldrige National Quality
Award the European Quality Award (Bou-Llusar et al., 2009). Familiar social-ecological
sustainability standards and principles include the 10 Principles of the United Nations Global
Compact (Kell, 2012), ISO 26000 Social Responsibility Standard (Helms et al., 2012), ISO
14000 Environmental Management Standard (Curkovic and Sroufe, 2011), United Nations
Millennium Development Goals (Sachs, 2012), and the Global Reporting Initiative or GRI
(Scherer and Palazzo, 2011).
Resilience, robustness, sustainable enterprise excellence, social-ecological innovation, and big
data intelligence & analytics are subsequently elaborated both separately and in relation to one
another while limiting consideration of other key SEER2 elements. Edgeman and Williams
(2014) introduce Springboard modeling focused on a strategic blend of simplicity and usability
to provide a SEER2 model and associated assessment regime. Their approach delivers insight
into recent organizational performance, including tactical and strategic successes and failures as
well as post-decision surprise areas where performance differed significantly from projections in
either form or magnitude (Smith and Winkler, 2006). Of perhaps greater in value is the ability of
the model and assessment regime to provide enterprise foresight that informs and shapes future
strategy and tactics that in turn lead to next best practices and sources of competitive advantage.
5
Prominent SEER2 enablers in relation to supply chain proficiency
Enterprise governance (Duit et al., 2010), big and small data analytics and intelligence (Teece,
2007), general and social-ecological innovation (Boons et al., 2013; Teece, 2010), enterprise
human ecology (Sheth et al., 2011), superior operations (Edgeman et al., 2014), and supply chain
proficiency (Wu et al., 2014) have been identified as key enablers of SEER2. These are now
discussed in relation to one another, SEER2, and social-ecological innovation (SEI).
By supply chain we intend a system of enterprises, people, activities, information and resources
involved in the production and distribution of a product, service, or information from supplier to
customer. The importance of supply chain sustainability, resilience, and robustness have become
obvious in the wake of the terrorist strikes of September 11, 2001 (Christopher and Peck, 2004),
natural disasters such as the 2004 Indian Ocean tsunami, the 2011 Fukushima Daiichi nuclear
reactor meltdown in Japan, and Superstorm Sandy in 2012 and resulting severe supply chain
disruptions. Owing to sheer size, increasing geographic footprint, and more complex services
and products, firms around the globe are increasingly subject to disruptions that erode or impair
supply chain relationships, operations, and broader performance (Bode et al., 2011) with more
than 90% of companies involved in a survey by Price Waterhouse Coopers (2013) indicating that
such disruptions significantly impact their business and financial performance.
Superior operational and supply chain performance is a key enabler of SEER2 (Cao and Zhang,
2011) so that it must be important to and embedded in enterprise strategy, partnership
cultivation, policies and processes, and its performance relative to other key SEER2 enablers
must be managed, measured and honed. Superior supply chains are fast, cost-effective, agile,
adaptable, and able to ensure that all of the enterprises’ interests remain aligned (Lee, 2004),
robust, and resilient. Such characteristics provide obvious suggestions for assessment,
particularly when they can be directly connected to SEER2 or other of its key enablers in order
to leverage synergies.
Larger, more complex organizations often have larger and more complex ecosystems and supply
chains so that the importance of supply chains to enterprise resilience and robustness can be
profound. Strategies aimed at increasing operations and supply chain resilience and robustness
ordinarily focus on managing and minimizing operational and supply chain risk (known
unknowns) and reducing uncertainty (unknown unknowns) relative to the potential impact on
assets and related services that might result from inadequate or failed internal processes, systems,
technology, actions of people, or external events leading to supply chain or operations corruption
or disruption (Gulati et al., 2010). Operational and supply chain resilience and robustness
strategies thus seek to sustain high-value operations, services or supply sources or to limit
damage to or disruption of these due to risk or uncertainty realization; effectively and efficiently
address results and ramifications of risks and uncertainty in order to restore the organization to
its prior steady state; and fulfill these goals at lowest cost, least negative social consequence, and
least damaging environmental impact. The intent then is to design, create and implement more
resilient and robust operations and supply chains via strategies and approaches that include risk
segmentation; operations and supply chain flexibility and agility; information sharing and
security throughout the supply chain (Cachon & Fisher, 2000); operational and supply chain
maturity and risk management (PricewaterhouseCoopers, 2013); trust and collaborative
6
relationships among supply chain partners (Faisal et al., 2006); corporate social responsibility
(Sydow & Frenkel, 2013), and alignment of incentives and revenue sharing policies across the
supply chain (Tsay, 1999). A sustainability-oriented constraint that may be governance enforced
is that such approaches should support closed loop cradle-to-cradle practice (McDonough &
Braungart, 2002b) wherein end-of-life products supply energy or material for subsequent
products or processes (Maxwell et al, 2006; Souza, 2013).
Government, governance, and supply chain proficiency
Sustainability cannot in the omnibus sense be separated from climate change and this typically
intersects supply chains so that in many cases a sustainable supply chain must of necessity
equate to an ethical and eco-efficient one. Baseline corporate and supply chain governance
expectations are that it should be both ethical and transparent and should embrace the Ten
Principles of the United Nations Global Compact (UNGC) that address human rights, labor,
ecological, and anti-corruption issues that are echoed and added to by the Global Reporting
Initiative or GRI (Rasche and Gilbert, 2012). These areas may be more fully and contextually
elaborated to embed more specific supply chain governance practices – for example business
sectors or activities in which an organization is engaged may dictate adherence to designated
codes of conduct. Similarly, governance in complex supply chains and multinational
corporations may be subject to differing national or regional expectations and hence alternative
governance expressions, a fact supporting the call for third-party supply chain governance
involvement (Bitran et al., 2007).
Two primary actors establish the legal and competitive boundaries inside of which an
organization and its supply chain compete: government and the marketplace. Although many
organizations function globally, governments influence their marketplace. Governments also
function with varying sovereignty levels that are enriched or limited by international alignments
such as the European Union or United Nations, agreements such as NAFTA, or – on some
occasions – by life-and-resource sapping conflicts. While some components of alignments and
agreements are voluntary, others are obligatory and anticipate cooperation, collaboration, or
compliance with failure to supply these resulting in censure or more dramatic disciplines such as
trade embargos. As such, alignments, agreements, and conflicts among nations may either
support or inhibit positive environmental policy and action. This implies societal need to
determine and deliver, and to review and revise the roles, responsibilities, and actions of
government needed to realize the future we desire. Given long term atmospheric persistence of
climate changing greenhouse gases such as carbon dioxide (CO2) and nitrous oxide (N2O), a
desirable environmental future may not be accessible, so that mitigation and limitation of
damage may instead define boundary conditions since we know with near certainty that our
current path is toward global scale environmental catastrophe (New et al., 2010). Positive
organizational and supply chain performance relative to climate change is implicit in SEER2 and
may be made contextually explicit via enterprise selection of performance measures and
subsequent maturity assessment.
At government, corporate, and by extension supply chain governance levels, any future as such
is shaped by the degree of success or failure experienced in aligning private incentives with
societal and environmental considerations that compose the public good. John Locke insinuated
7
this idea in his Second Treatise of Government on property rights in 1689 (Nacol, 2011) in
stating that property owners - corporations in our context – were entitled to the fruits of their
labors, yet obliged to leave “enough and as good” for others. Similarly, created in 1787 and
ratified in 1788, the United States Constitution anticipated the governmental role in what is
referred to as the general welfare clause (Lyons, 1977), that is: “to form a more perfect union,
establish justice, insure domestic tranquility, provide for the common defense, promote the
general welfare, and secure the blessings of liberty to ourselves and our posterity.” If the tack is
taken that the “blessings of liberty to … our posterity” include a safe natural environment, then it
may be argued that the United States is constitutionally obliged – at least domestically – to fulfill
essentially all key elements of the United Nations Post-2015 Sustainable Development Goals
(United Nations, 2013) that generally represent further elaboration of the 1987 World Council on
Environment and Development definition of sustainable development as development that
“meets the needs of the current generation without compromising the ability of future
generations to meet their own needs” (Robinson, 2004).
Centrality of governance to the strategy, policies, and practices of enterprise excellence (Foote et
al., 2010), sustainability (Aras and Crowther, 2008; Martinelli and Midttun, 2010), robustness
and resilience (Carmelli and Markman, 2011) is well-established (Fowler and Hope, 2007) and
governance stimulating supply chain robustness is of value is since enterprises having robust
supply chains tend more generally to be robust. Governance is important to each of the triple
bottom line dimensions of sustainability: people (Jo and Harjoto, 2012), planet (Walls et al.,
2012), and profit (Surroca et al., 2010) and both operational and supply chain robustness are
positively correlated to governance that prioritizes eco-efficiency. As a bonus benefit, the value
differential between more eco-efficient and less eco-efficient enterprises increases over time
(Guenster et al., 2010) so that supply chain participants are wise to place a premium on eco-
efficiency.
Given the relationship of governance to each of the triple bottom line elements, it is natural that
SEER2 incorporates governance. This is perhaps especially necessary in high intensity socio-
technical enterprise environments marked by the need to integrate and govern complex human
ecology and technological interfaces (Smith et al., 2005). Enterprise excellence models do not
directly address governance, whereas SEER2 anticipates the clear causal roles of strategy and
governance in producing and defining the frontier of enterprise performance of all sorts,
including resilience, robustness, sustainability and financial performance and impact so that
SEER2 presumes that triple top line enterprise governance and strategy intersecting
governmental and societal requirements and expectations are deployed and transformed through
people, processes, partnerships, and policies that produce triple bottom line societal, ecological,
financial, and other performance and impact.
Data analytics, intelligence and supply chain proficiency
The broad data-driven decision-making domain of technologies, applications, and processes for
gathering, storing, assessing, analyzing and activating is often referred to as business intelligence
(Chauduri et al., 2011). Enterprise excellence models have long advocated business intelligence
and management as a means of advancing whole system optimization. The game changing
disruption however, is integration of business intelligence with so-called “big data”. Hallmarks
8
of big data (McAfee and Brynjolfsson, 2012) include richer and more numerous data sources;
massive data volume and variety; and quantum leaps in analytic capability and graphic intricacy
that enable discovery, characterization, and management of complex patterns and interactions
that in turn produce strategic intelligence (Kuosa, 2013). The big data era is a result of dramatic
and persistent advances in data storage capacity and processing speed that has long followed
Moore’s law (Schaller, 1997).
In part the role of big data is to support strategic intelligence that enables organizations to
operate differently and more intelligently than their competitors, thus providing additional
avenues to resilience and robustness through delivery of highly efficient, effective, rapid and
customized translation of data into intelligence, intelligence into foresight, and foresight into
value (LaValle et al., 2011). This has motivated a transition away from traditional (small) data
driven decision making toward a blend of tradition with increasing leverage of vastly more
complex concept and computationally-intensive big data analytics that may yield mixed
quantitative, qualitative and visual forms. The power and widespread availability of big data
intelligence and analytics has intensified the importance of comprehensive data confidentiality
and security as means of rendering organizations more robust against cyber-attack and espionage
(Crane, 2005).
Big and small data analytics and intelligence along with other sense-making approaches may be
used for multiple purposes (Angus-Leppan et al., 2010), essentially all of which have the end
goal of deriving financial and other valuable impacts (Chen et al., 2012). Among these purposes
are scanning the competitive and legislative landscape, along with the cascading ones of real- or
near-real-time performance assessment, intervention in and control of associated processes,
strategy refinement and process improvement or innovation, and identification and
implementation of best and next best practices and sources of competitive advantage. Many of
these are elements of a cyclical process aimed at optimizing organization performance relative to
enterprise mission and vision. Mission and vision refers to that emphasized by a given model –
in this case sustainable enterprise excellence, resilience and robustness – and whatever means the
model employs to deliver these so that big and small data analytics and intelligence performance
drivers and results will include contextualized societal, environmental, and financial elements.
Analogous to climate change and related concerns driving sustainability, the big data megatrend
is indicative of fundamental transformation in the global economy wherein few business activity
spheres or application areas will remain untouched (McAfee and Brynjolfsson, 2012) and for
which there are already abundant supply chain management applications (Closs et al., 2011).
Application of big and small data intelligence and analytics to supply chain design and
optimization carries with it the potential to transform connected intelligence into integrated
collective intelligence. Connected intelligence is what might be referred to as “dissipative
additive” in the sense that while knowledge is summative across the chain, anything short of
perfect connectivity results in a certain amount of energy or knowledge loss. Integrated
collective intelligence is in contrast multiplicative. The former case can aid identification and
transformation of best practice into standard practice through knowledge sharing. The latter case
relies on knowledge multiplication through collection of best practice fragments collected across
the chain and recombined in ways that lead to next best practices and sources of competitive
advantage deployed more extensively across the chain to advance supply chain sustainability,
9
resilience, robustness and excellence and hence also shared improvement in financial, societal
and ecological performance and impact. This illustrates one of many ways in which progress
toward SEER2 is enabled by sophisticated analytic transformation and translation of information
into actionable enterprise intelligence and foresight.
Enterprise and supply chain human ecology
Enterprise human ecology refers to the relationships between the organization and its human
capital with the social, natural, and built environments via whatever mediators are pertinent
(Lozano, 2011). In the context of SEER2 enterprise human ecology may be regarded as a natural
extension of enterprise human capital management, which has long been emphasized as a critical
enabler of enterprise excellence (Kim et al., 2010). Strategic management of this ecology to
create specific competencies based on selected cognitive abilities, behavioral traits, and
aggregate these competencies at the organizational level makes it possible for enterprises to
respond to severe shocks in a resilient manner by cultivating ambidextrous learning that enables
enterprises to exploit their existing knowledge domains while exploring new ones (Lengnick-
Hall et al., 2011). Similarly, enterprise human ecology contributes to robustness when this
ecology is configured via appropriate intellectual capital architectures emphasizing ambidextrous
learning (Kang and Snell, 2009), sustainability (Pfeffer, 2010), and enterprise excellence
(Chuang and Liao, 2010). Enterprise human ecology is vital to SEER2 primarily because it
interacts with or “pre-enables” other key enablers of SEER2. As examples, strategic human
ecology practices are central to innovation performance (Chen and Huang, 2009); supply chain
management (Ou et al., 2010); corporate governance (Sharma et al., 2011); and big and small
data analytics and intelligence where it has been noted that for all its power, and potential big
data does note erase the need for vision or human insight (McAfee and Brynjolfsson, 2012).
Innovation, social-ecological innovation, and supply chain proficiency
Sustainability has been identified as a megatrend (Lubin and Esty 2010), source of competitive
advantage (Laszlo and Zhexembayeva 2011), and documented driver of firm value (Al-Najjar
and Anfimiadou 2012). As such it is important to determine key drivers of sustainability, with
innovation documented as not only chief among sustainability enablers (Nidumolu, et al, 2009),
but also of enterprise excellence (Eccles and Serafeim, 2013), resilience and robustness
(Reinmoeller and Van Baardwijk, 2005), and hence of SEER2. We regard innovation in general
and social-ecological innovation (SEI) in particular as chief among enablers of SEER2 and as
part of that, critical to supply chain sustainability and proficiency (Oke et al., 2013).
SEI embeds innovation for sustainability (Rennings, 2000) in a culture of sustainable innovation
(Nill and Kemp, 2009). Such cultures exist when innovation is regular, rigorous, systematic,
systemic, is central to enterprise strategy, and tangibly impacts enterprise financial, societal, and
ecological performance (Edgeman, 2013). More generally, SEI weds social innovation and
institutional entrepreneurship research with research on socio-ecological systems and resilience
thinking and leverages this marriage to explicitly target social or environmental outcomes of
innovation partially enabling transformation of triple top line strategy into triple bottom line
performance. Effective implementation of innovation in enterprise excellence models positively
drives firm performance, including financial performance (Barua et al., 2001).
10
We thus see that effective fusion of innovation with sustainability and enterprise excellence
provides a compounding or synergistic impact for enterprises seeking to become continuously
relevant and responsible. From a SEI perspective, innovation is relevant to the organization,
society, and the natural environment and the organization is relevant and responsible to society
and the natural environment. Positive correlation of SEI with enterprise value (Al-Najjar &
Anfimiadou 2012), affirms the profitability of strategic SEI. Proliferation of SEI throughout an
enterprise ecosystem contributes to socio-ecological resilience (Olsson & Galaz, 2011) with
large-scale SEI deployment possible through a modified form of quality function deployment
(Edgeman & Hensler, 2005).
Serious assessment of SEI performance requires understanding of what SEI is, how and in what
forms it manifests, how developed or mature it is, and how to improve future SEI strategy and
results. Edgeman and Eskildsen (2014) elaborate SEI and maturity scale based assessment
thereof via a combined graphic and narrative format referred to as a SEI News Report. Such
reports provide feedback concerning present SEI performance, while also delivering significant
foresight capable of informing future SEI strategy, priorities, processes, and activities and hence
future SEI performance. Though the SEI approach of Edgeman and Eskildsen provides 20
generic basic and advanced strategies and activities used to advance enterprise SEI performance,
the intent of their overall approach is that it should be contextualized.
Supply chain proficiency in the Springboard to SEER2 model and its assessment
Assessment of supply chain contribution to enterprise financial performance is common practice.
Supply chain relationships with governance, big data analytics and intelligence, innovation and
other SEER2 drivers are equally well established. Of more recent origin is assessment of supply
chain contribution to and impact on environmental performance (Shaw et al., 2010), society
(Hoejmose et al., 2013) and hence sustainability. In combination then, it is clear that supply
chain proficiency plays a sufficiently important role in SEER2 to merit inclusion in the
Springboard to SEER2 model and its associated assessment regimen.
Edgeman and Williams (2014) provide a Springboard to SEER2 model a model that is structured
in a manner recognizable to users of either America’s Malcolm Baldrige National Quality Award
(MBNQA) or the EFQM Model that supports the European Quality Award (EQA). While the
overall structures of these models are similar, the Springboard to SEER2 differs in terms of
specific objectives that explicitly address enterprise sustainability, resilience and robustness in
concert with enterprise excellence. Enterprise excellence is used here as a synonym for the
MBNQA term performance excellence and the EQA term business excellence. Integration of
sustainability, resilience, and robustness as enterprise objectives quite naturally leads to use of
selected enablers not used by the MBNQA or EQA models and to differences in the way that like
enablers are construed, albeit sometimes only minor or subtle distinctions.
Figure 1 provides a high-level summary of the Springboard to SEER2 model. This model
insinuates that the leadership and governance of an enterprise informs its triple top line oriented
strategy; strategy is principally executed via policies, partnerships, and processes; these in turn
11
deliver triple bottom line related sustainability, resilience and robustness performance and
impact, along with more familiar enterprise excellence performance and impact.
Figure 1. Modified Springboard to SEER2 Model. Adapted from Edgeman and Williams (2014)
This model and been elaborated in greater detail (Edgeman and Williams, 2014) as have its
criteria and their assessment, presentation of assessment results, and their ability to provide the
enterprise with both feedback and foresight. Feedback provides the enterprise with a review of
its performance during the most recent appraisal cycle. In contrast, foresight supplies the
enterprise with intelligence used to inform its future strategies and actions through identification
and implementation of relevant best and next best practices and sources of competitive
advantage.
The assessment regiment for the Springboard to SEER2 consists of 24 specific criteria,
distributed as four to each of six major assessment regions. Relative to the model of Figure 1, the
first major assessment region is triple top line strategy; the second is strategy execution via
policy, processes and partnerships; and the remaining four are specific triple bottom line
performance and impact areas: financial and marketplace, sustainability, human ecology and
capital, and SEI and general innovation and continuous improvement. The four criteria assessed
for each region are symbolized by N, E, W and S, with each of these assessed relative to highly
FO
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SIG
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E
NT
ER
PR
ISE
LE
AD
ER
SH
IP &
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VE
ER
NA
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E
W
TRIPLE
TOP LINE
E
N
S
POLICY, PROCESSES
& PARTNERSHIPS
STRATEGY
EXECUTION VIA
W
PERFORMANCE
& IMPACT
SEI & GENERAL
INNOVATION AND
CONTINUOUS
IMPROVEMENT
PERFORMANCE
N E W S
HUMAN ECOLOGY
& CAPITAL
PERFORMANCE
N E W S
SUSTAINABILITY
PERFORMANCE
N E W S
FINANCIAL &
MARKETPLACE
PERFORMANCE
N E W S
TRIPLE
BOTTOM LINE
STRATEGY
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N
12
descriptive 0-to-10 point maturity scales. Although Edgeman and Williams (2014) chose not to
differentially weight these criteria, instead leaving weighting to enterprise competitive context,
we here note that models such as the MBNQA and EQA typically ascribe approximately 50% of
the weight to performance / impact, about 35% to process implementation and execution, and
15% to strategy, governance and leadership.
Given the common association of N, E, W and S with the primary directional points of a
compass, their use to form the word “news”, and the intent of assessment to provide both news
(feedback) and direction (foresight), Edgeman and Williams (2014) organized the assessment
results for each region into an associated graphical NEWS Compass, each augmented by a SWOT
Plot Narrative. The assembly of these across all assessed areas provides an overall assessment,
referred to as a Springboard to SEER2 NEWS Report.
The full set of 24 criteria were derived from a combined literature review and comprehensive
examination of the models, criteria, principles and approaches of the GRI, UNGC, America’s
Baldrige National Quality Award, the European Quality Award, ISO 14000, ISO 26000, and
balanced scorecard and can be found in Edgeman and Williams (2014). Of importance in the
present context is that various contributions of supply chain proficiency to SEER2 are
represented in each of the six “N” criteria, with the N criteria reported in Table 1. As such, the
perspective emerges that supply chain proficiency is integral to SEER2, and not merely
component. We see than, that supply chain proficiency is focal to triple top line strategy, is
deployed via policies, partnerships and processes, and is reflected in financial and marketplace
performance, sustainability performance, human ecology performance, and in innovation and
continuous improvement performance.
Table 1. Springboard to SEER2 Assessment Regions and Associated N Compass Points
REGION: Triple Top Line Strategy
Financial & Marketplace Strategy for SEER2 & Supply Chain Strategy
REGION: Strategy Execution Via Policy, Processes and Partnerships
Financial, Operations & Supply Chain Processes for SEER2
REGION: Financial & Marketplace Performance and Impact
Financial & Marketplace Results Traceable to Supply Chain Performance
REGION: Sustainability (SEER2) Performance and Impact with Embedded
Economic, Innovation and Analytic Impact
Sustainability Results Traceable to Supply Chain Performance & Analytics
REGION: Human Ecology & Capital Performance and Impact
Impact of Human Ecology & Capital on the Supply Chain
REGION: Social-Ecological & General Innovation, Design and Continuous
Improvement Performance and Impact
Impact of Innovation, Design & CI Across and In the Supply Chain on SEER2
13
Summary and conclusions
A classic contribution by Churchman (1967) defines a wicked problem as “that class of social
system problems that are ill-formulated, where the information is confusing, where there are
many clients and decision makers with conflicting values, and where the ramifications in the
whole system are thoroughly confusing.” Other common though not universal characteristics of
wicked challenges include association with highly charged and conflicting political, religious, or
social perspectives and the need for urgent, high stakes resolution. Similarly, Russell Ackoff
(1974) noted the inherent nature of such problems in systems populated by interacting and
inextricably knotted elements or issues. Citing numerous elements that range from climate
change and other components of ecological change to chaotic financial markets to widespread
corruption, Waddock (2013) establishes corporate leadership and governance, along with
collaboration that can include supply chain efficiency and effectiveness as critical to progress in
solving wicked (global) sustainability challenges.
It is in this vein of progress toward enterprise contributions to solution of the wicked global
sustainability challenges that Sustainable Enterprise Excellence, Resilience and Robustness
(SEER2) is evolving. While innovation is foremost regarded as critical to SEER2, attention has
been directed herein to the enabling role of supply chain proficiency in SEER2 and its
relationships to and interactions with innovation and other key enablers of SEER2. Beyond
previously cited roles and relationships, collaborative and co-creatively innovative supply chain
partnerships (Hernández-Espallardo et al., 2010) are able to advance sustainability through
greater resource efficiency (Schliephake et al., 2009) – an issue that in itself is aided by trust-
based governance (Ghosh and Fedorowicz, 2008) and enabled by big data analytics and
intelligence (Trkman et al., 2010).
These elements are embedded in the SEER2 modeling and combined narrative and analytical
assessment approaches presented herein enable not only enterprise progress toward SEER2, but
also supply chain performance as viewed through a SEER2 lens.
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