COOPERATIVE RESEARCH CENTRE FOR COAL IN SUSTAINABLE DEVELOPMENT (CCSD)
PROGRAM P1.2: SUSTAINABILITY DIMENSIONS AND IMPACTS
Dear CCSD Industry Partner:
What follows is an industry discussion paper that considers the development of key performance
indicators for the adaptiveness approach to sustainability currently under development within
programme P1.2. This is the seventh in the series of brief discussion papers specifically for
industry partners. They are designed to explain the key ideas behind the approach that programme
P1.2 is taking to sustainable development, discuss the consequences for coal-chain industries, and
provoke dialogue and feedback.
Discussion papers 1 to 6 are available at http://www.ccsd.biz/research/project1.2.cfm
(See also http://www.newcastle.edu.au/centre/casrg/research/ccsd.html for these and for a brief
overall description of the P1.2 project).
This seventh paper considers the problem of developing performance indicators for adaptiveness,
particularly from the point of view of the adaptiveness of the coal industry itself, as well as the
impact that it has on the adaptiveness of the Australian economy.
As for previous discussion papers, the concepts and principles involved here are often recently
emerged and may be novel to your thinking. You may wish to inquire further about how these
ideas may be applied. Alternatively, you may be able to provide us valuable examples of how
they fit your company or industry, and/or provide welcome improvement to our understanding
and application of them. On both counts we welcome your feedback.
We thank you for attending.
C.A. Hooker, project leader
T.S. Brinsmead, postdoctoral research fellow
C. A. Hooker: Email: Cliff.Hooker@newcastle.edu.au , Phmail: +612 4921 5185,
T.S. Brinsmead: Email: Thomas.Brinsmead@newcastle.edu.au , Phmail: +612 4921 7247
For both people:
Fmail: +612 4921 6928,
POmail: School of Liberal Arts, McMullin LG27,
University of Newcastle, Callaghan, NSW, Australia 2308
COOPERATIVE RESEARCH CENTRE FOR COAL IN SUSTAINABLE DEVELOPMENT
PROGRAM P1.2: SUSTAINABILITY DIMENSIONS AND IMPACTS
Director: Professor C.A. Hooker, PhD (physics) PhD (philosophy) FAHA
University of Newcastle, Newcastle, Australia
SUSTAINABLE DEVELOPMENT: UNDERSTANDING & ISSUES FOR INDUSTRY
An occasional series of brief papers designed to explain key ideas and provoke
PERFORMANCE INDICATORS FOR ADAPTIVENESS
“An organization's ability to learn, and translate that learning into action
rapidly, is the ultimate competitive business advantage.”
Jack Welch: Chairman and Chief Executive of General Electric
In a dynamic and uncertain world, adaptiveness is a minimum necessary condition for
continued survival. Agile creatures that can intelligently learn (such as humans) to exploit
new ecological niches or evolve (such as bacteria) to meet new climate and interspecies
interactions will survive in the natural environment. Agile firms that can move quickly
into new markets or innovate new production processes will survive in a competitive
industry. Future technological and policy developments in the energy sector are both
highly uncertain and potentially subject to rapid change. This requires a broad suite of
economic and social adaptation options so that, across the broadest possible range of
likely future developments, the sector is able to supply the energy requirements of
Australian society both securely and cost-effectively.
But resources are limited, and investing in developing and maintaining options for
adaptation will often compete for resources that could otherwise be dedicated to
becoming more efficient at what is presently done. There is thus a trade-off between
performing current activities efficiently and developing, in anticipation of future changes,
the adaptive capacity to potentially perform alternative activities efficiently. So, how
should relevant adaptiveness be identified and evaluated, and how much adaptiveness is
This discussion paper addresses the question of developing indicators for adaptiveness.
The main message here is that there will be no key performance indicators for
adaptiveness that are completely general. Rather the particular indicators will be specific,
not only to the adaptive entity, but also to the particular environmental conditions in
which it is operating.
There would be no need for peaking plant to be part of the electricity supply system,
providing for short term peaks in energy demand, if the demand for electricity were
constant over 24 hours or if there were no commitment to meet all electricity demands.
And in the absence of a climate change threat, the carbon capture and storage retrofit
readiness of a coal fired electricity plant would not be relevant. This paper therefore does
not prescribe particular adaptiveness sustainability indicators for the coal industry,
although it does describe a general process for generating candidate indicators,
illustrating this with a number of examples.
I: Performance envelopes and adaptiveness indicators
A key concept for characterising adaptiveness with a view to developing indicators is the
performance envelope. The concept originated in aerospace engineering, where it can be
defined as the range of flight conditions safely realisable by a given aircraft. Generalised,
it is the range of relevant behaviours realisable by a given entity. Indicators of
adaptiveness of a given technology, organisation, or technological network characterise
the performance space of possibilities open to it.
For example, consider a bread baker with a very efficient, though also highly specialised,
bread mixing machine and oven. These supply only a limited range of products to her
bakery, but do so quickly and cheaply. In fact, suppose she has only two bread products:
500g loaves and 250g rolls; and a maximum mixing capacity of 50kg per day. Even so,
with this quite limited range of products there is still some flexibility in the production
schedule: any combination of loaves and rolls not exceeding the maximum mixing
machine capacity can be produced, for example 100 loaves and no rolls, 80 loaves and 40
rolls, or no loaves and 200 rolls. And if demand is low the equipment can be rested for
the whole or part of the day so as little as nothing at all is baked.
The entire range of combinations of loaves and rolls that can be created within this
bakery we might call its “performance space”, and its maximum production frontier the
“performance envelope”. Depending on the choices made by the baker, any product
combination within the performance space can be realised. Here the ranges of quantities
of loaves and of rolls, and of their sum (#loaves + #rolls), and the ‘size’ of the
performance space, are all obvious, if partial and naive, indicators of the degree of the
adaptability of the bakery production. (See further below.) In sum, indicators of
adaptiveness of a given technology, organisation, or technological network characterise
the performance space of possibilities open to it.
Performance space adaptiveness has aspects of scope, timeliness and dependence on
external contingency. It is also limited by coordination capacity. These are discussed in
Scope. The performance envelope of alternative technological arrangements can vary
qualitatively or quantitatively. For example, consider adding an extra 25kg specialist
mixing machine that is suitable for producing bread dough, but nothing else. It can easily
been seen that this addition of capacity quantitatively increases the performance space by
pushing out the performance envelope.
As an alternative option for expansion, consider a more expensive mixing machine that
can also produce 25kg/day of bread dough, but is also suitable for mixing the batter
required to make up to 25 wedding cakes per day. To characterise the performance space
of the alternative setup we can add an additional bakery output indicator: “wedding cake
production”. Now the performance space has expanded qualitatively from two to three
dimensions and also been quantitatively extended, because the performance envelope has
been extended, e.g. to include producing 110 loaves, 40 rolls and 10 cakes. Thus
performance envelopes can be extended quantitatively, by improving the quantitative
range of performance that can be achieved by one or more outputs while maintaining the
others, and/or extended qualitatively, by adding an extra production dimension.
Comparing technologies in terms of their performance envelopes allows for consideration
of a fuller range of their capacities than narrowing attention to a small set of performance
evaluation criteria that are universal. For instance, it simply doesn't make sense to
compare spreadsheet software to digital calculators, or mobile phones to land lines, solely
on the basis of cost alone. A net cost-benefit criterion identifies just a single point in the
performance space: that production point (e.g. total bread quantity and mix) that is
optimal according to some economic objective, ignoring the value of the alternative
options expressed in the performance space. Similarly, compared with a traditional
efficiency measure, which again identifies a single optimal point (the most efficient
production configuration), the concept of performance possibility space is much broader
Similarly, a less extensive life-cycle analysis might investigate only a single process
configuration based on actual past performance, which is a single point in the
performance space. However, a full life-cycle analysis devoted to uncovering system-
wide relationships among mass-energy flows would also cover the full performance
space and thus disclose, as performance analysis does, all that is prospectively possible
for the system should it prove relevant - that is, should it prove efficient in some larger
Correlatively, however, comparing performance envelopes will require making
comparisons across qualitatively distinct criteria. This is particularly advantageous for the
comparative evaluation of breakthrough technologies, since they frequently offer
functions unavailable to traditional devices - qualitative changes in the performance
space. There isn't any simple way of evaluating the importance of mobile phone
flexibility of location of service provision or ability to take and send digital images
against its requirements for regular recharging and higher service charges compared to
land-line technology. However the performance space concept does at least allow these
extra functional capabilities to be recognised and a wider range of values to be attached
to them. Using traditional performance criteria like cost to evaluate an innovative
technology in order to preserve an overly narrow sense of comparability can result in an
under-appreciation of its novel capabilities. Because the capacity of truly breakthrough
technologies is incommensurate with existing ones, qualitative comparison of
performance spaces is a less biased starting point.
In principle then, the performance space characterises the total space of possible adaptive
performance. As the above examples demonstrate, the multi-dimensional nature of the
space can very quickly become quite complicated. In practice it will be rarely possible to
provide a complete characterisation of this performance space. However, as illustrated in
the bakery example, the notion provides a useful conceptual tool for exploring
adaptiveness performance indicators.
Timeliness. Not only can adaptiveness be improved via quantitatively or qualitatively,
increasing the range of scope of performance, it could alternatively be improved by
increasing the rate at which it is possible to move from one point to another. For example,
if there is a lot of inertia in the bakery ingredient supply chain, it might require several
day’s notice to order the icing sugar required to make wedding cakes, so that wedding
cake production agility is thus limited. However, an in-house stockpile of icing sugar
might reduce the time for switching production schedules from a few days to a few hours.
Thus timeliness is also a dimension of adaptiveness.
The scope and timeliness dimensions of performance space apply equally to energy
technologies. The quantitative scope of power output for a coal fired power station
corresponds to the range between its minimum and maximum output capability. The
qualitative scope of the output of an integrated gasification combined cycle plant includes
both electricity and syngas, since varying quantities of each can be produced. The
timeliness of a peaking natural gas plant corresponds to the power ramp rate.
Scope and timeliness characterise the performance space inherent in a technological
arrangement, a bakery, pulp and paper mill, and so on. Call this the production
performance space. It comprises those performance conditions that are logically and
physically possible given the materials available. Now we deal with two kinds of
important constraints on the accessibility of the production performance space: external
contingencies and internal coordination.
External contingency. Observe that performance possibilities can be made more or less
dependent on the existence of particular environmental conditions that are necessary to
enable those possibilities to be realised. For example, the ability to produce wedding
cakes at all ultimately depends on the existence of an icing sugar supplier, along with a
corresponding supplier of each other ingredient, and the characteristics of those suppliers
may constrain what parts of the performance space are accessible. Most obviously, if
icing cannot be supplied at all, then the wedding cake dimension of the bakery
performance space is not accessible to it. But if the quantity of icing provided per unit
time is limited then the performance domain beyond the corresponding maximum
wedding cake production rate is inaccessible, while if there is a significant time delay
between ordering icing and its supply, then the agility of ramping up wedding cake
production is limited. An in-house stockpile of icing sugar can ameliorate these last two
constraints to varying degrees depending on the stockpile size relative to the demand
schedule. At the cost of creating it, a stockpile internalises external dependencies, thereby
adding to the adaptability of production. 1
See industrial discussion paper #1, Introducing three basic concepts: system efficiency, resiliency,
adaptability, at www.ccsd.biz.
Label the associated external contingency conditions necessary to enable the full
technical performance space to be available for use, the full external operating conditions.
Then the access available to the production performance space is determined by the
proportion of the full external operating conditions that are satisfied. A solid fossil fuel
power station requires timely supplies of coal and water, adequate water and gaseous
effluent discharge channels and connection to the electrical power grid, many other
contributing requirements; constraints in any of these may limit the operating regime of
the power station.
Internal coordination. A bakery without a baker to manage the process can produce
nothing: its production performance space is inaccessible. And if the baker hasn't been
trained to make icing (and it can’t be bought in from another supplier), or is unable to
imagine how a wedding cake should look, then wedding cakes are not part of the
accessible performance space. An adaptive performance space needs some appropriate
form of coordination capacity. And when that coordination capacity is embodied in
human form, such as in a company manager and workforce teams, that coordination
capacity also includes the ability and willingness to imagine possible production
performance conditions and to carry them out.
Coordination capacity includes the capacities both to manage production at each point in
the performance space, as well as to manage changing production settings from point to
point. For example, the baker's coordination capacity requires not only the ability to make
loaves, rolls and cakes, it also requires the ability to switch from - for example - the
production of loaves and rolls to the production of some cakes as well.
In parallel with the external constraints, label the range of coordination conditions that
need to be successfully selected and managed to enable the full production performance
space to be available for use, the full internal operating conditions. Then the access
available to the technical performance space is determined by the proportion of the full
internal operating conditions that are satisfied. A national electrical power grid that
cannot effectively coordinate supply from diverse sources to demand from diverse users
will operate far inside its technical performance envelope. Coordination constraints can
appear in any situation, but typically become important whenever the situation is
sufficiently complex. The coordination capacity may also be hard to characterise and
measure, especially when the coordination is emergently self-organising, as it is in
market economies and may be in ecosystems.
The actual performance space in any situation is the common overlap between the
production performance space and the external and internal operating conditions.
Context dependence. The above examples suggest that what are relevant performance
indicators will depend significantly on the context. This is generally true for any
performance indicator, not just indicators of adaptiveness. For instance, SOx, NOx and
heavy metal pollutant outputs are simply not relevant indicators for wind powered
electricity generation, though they are for coal-fired generation, while demand for
agricultural land and water are relevant indicators for a biomass energy process, but not
for a gas-cooled natural gas generator. More broadly, the very successful South-East
Queensland Healthy Waterways sustainability assessment started with a vision for the
region of “A healthy ecosystem supporting the lifestyles of residents and visitors” and
only later were specific performance indicators such as nitrogen nutrient pollution and
duck population developed, based on the specific details of particular catchment regions. 2
These considerations equally apply to the construction of adaptiveness indicators. The
adaptability of the energy sector has many facets, from the suite of diverse technologies
available and the suite of fuels utilisable, at the whole-sector level, all the way down in
scale to the ease with which a particular power plant can respond to demand changes, be
retro-fitted to reduce pollutants or accept solar boosting, or even be turned over to non-
energy uses. The many adaptabilities applicable to the energy sector are not mutually
independent, sometimes they go together (e.g. gas-fired generators are both adaptable
load-followers and adaptable fuel acceptors through solar boosting and coal gasification)
and sometimes adaptabilities partially conflict with one another (e.g. solar technologies
are more adaptable to distributed generation than are fossil-fired generators but, without
storage, much less adaptable to load-following). In addition, a capacity to adapt is a real
physical capacity costing real resources (money, materials, skilled employees) to
implement. The finite supply of resources alone ensures that cross-sectoral competition
will mean that not all potential adaptabilities can be pursued, and within-sector
competing efficiency considerations may further reduce the desirable suite of
adaptabilities (note 1). The issue then becomes one of deciding what are the most
important adaptabilities to pursue in any given situation or context.
One obvious consideration here is what conditions are externally imposed on the system
because they are required for performance to be considered satisfactory or acceptable.
The load-following capacity of a peaking electricity generation plant is a relevant
adaptive feature only because it is deemed to be a requirement for electrical power to be
available on demand. A flue gas desulfurisation retrofit alternative in a coal fired power
plant is important because of the undesirability of SOx emissions.
Relevant performance indicators for adaptiveness will also depend on the particular
uncertainties and projected changes that are currently operative. For example, it is the
unpredictable and rapidly changing nature of electricity demand that makes the load
following capacity of a peaking plant a relevant adaptive feature to consider. It is only
due to the uncertainty in the long term price and availability of oil for transport that a
coal-to-liquids technological capability might be a desirable adaptive option for
Australia. Uncertainties associated with drought make it important for Australian cattle
farmers to have feeding options of pasture versus hay, or options to retain stock for
breeding or to sell them on international or domestic markets. In the absence of those
uncertainties, or changes in future conditions, the adaptive features mentioned above may
See Dennison WC and EG Abal (1999), Moreton Bay Study: a scientific basis for the Healthy Waterways
Campaign, SEQRWQMS, Brisbane Australia. See also Moreton Bay Waterways and Catchment Partnership (2001),
South East Queensland Regional Water Quality Management Strategy, September (Appendix A in particular)
be of little consequence.
II: Developing Adaptiveness Indicators
The following outlines a procedure for generating adaptiveness indicators. The starting
point is clearly identifying particular relevant adaptive capacities. For this it is necessary
to specify the system that has the capacity, the kind of changes to which adaptation is
being made, the overall aim in making the adaptation, the adaptive options available and,
to get beyond a ‘black box model’, the mechanisms of adaptation – that is, respectively
specify adaptability of what, to what, for what, between what, by what. Once this is done
it is then possible to consider relevant adaptability indicators as a function of these
The first specification is that of the adaptive object being considered. For example, is it a
single technology - such as a motor car, and electrical motor, or a steam turbine, an
organisation - such as an electrical generating company, a school or a software firm, or a
network of technologies - such as a transport system, a silicon chip fabrication plant, or
an electricity supply network. This choice determines the scale of analysis. For the sake
of an example, suppose that we select an electrical generation company.
The next task is to identify the relevant criteria that characterise adequate functioning and
identify the key uncertainties where potential changes can affect that functioning. For an
electrical generator, adequate functioning could be characterised simply as making a
profit and meeting environmental and industrial regulation requirements. (A stricter
condition – making a profit from the supply of electrical power - is possible, although this
may overly restrict the scope of the analysis.) In the current situation, some of the key
uncertainties whose change may affect future profitability include the cost of renewable
energy technologies, the technical and economic feasibility of carbon capture and
storage, and greenhouse gas emissions policy.
The following step involves identifying the alternative options available to ameliorate the
consequences of the uncertain contingencies that threaten satisfactory functioning, along
with the mechanisms for carrying out the adaptation processes. This is less
straightforward and, like the preceding tasks, requires a reasonable degree of familiarity
with the situation.
For our example case-study we begin by specifying two broad categories of options, the
installation of alternative electricity generation technologies or changing the business
model from focussing solely on the generation and sale of electricity. It is within these
categories of adaptation options that adaptive performance will be specified more
precisely. Just how difficult and costly any specific option would be to implement will
depend in part on its inherent costs and in part on the change planning and management
processes in place in the company, that is, on the cost structure of its coordination
performance space. For the sake of simplicity we do not pursue these latter details further
here, but readers will appreciate that, poorly realised, they can prove very disruptive and
It is now possible to be more specific about the particular adaptive options that ought to
be considered more closely within the broad categories. For alternative electricity
generation technologies, candidates might include coal driving high temperature
(supercritical) steam cycles, natural gas, and hybridisation of coal with solar thermal or
biomass. Changing the business model might involve selling hydrocarbon based
chemicals as well as electricity with the acquisition of integrated gasification technology,
or integration with a retailer seeking opportunities to market thermal energy and/or
energy efficiency measures. It might involve trading in carbon credits and associated
activities such as afforestation or the promotion of low emissions technology measures
both internationally and domestically.
In this step it is important to identify only those alternatives that either already are, or
have a reasonable prospect of becoming, a realistic possibility. In principle, nuclear
fusion generation is “possible”, generously understood, but the other technologies
mentioned above are much more realistic candidates and have higher priority for
consideration. Similarly, changing the business model to become a motor vehicle
manufacturer is “possible”, but unrealistic.
For the identification of key performance indicators, it now remains to select relevant
measures of the adequacy, given the uncertainties, of the range of possible adaptive
options identified. Adequacy measures may include measures of the quantitative and/ or
qualitative scope of the options, the timing and/or cost of realising them, and the extent to
which they are contingent on external factors.
Scope. A company that has enough capital to install an advanced supercritical coal plant
of 1000MW has a greater quantitative scope than one that could install only 400MW. A
company that can profitably install as little as 10MW of wind turbines (because it already
has 40MW and experienced personnel to operate them) has a greater quantitative scope
than one that requires a minimum scale of 50MW installation in order to justify the
investment economically. A company that could realistically operate either a coal-fired
power plant, a solar thermal plant hybridised with coal, or a stand alone solar thermal
plant has greater qualitative scope than if it were only capable of operating a coal-fired
Timing. A company that could realistically expect to have the technical capability of
storing carbon underground within eight years has superior adaptiveness along the timing
dimension than if this prospect were twelve years away. A proxy indicator for the timing
of a technology would be how advanced it is on its technological development pathway –
whether it is at the laboratory demonstration stage, is a pilot plant, fully commercialised
or is a mature technology.
Cost. If a generating company develops customised solar thermal technology that enables
lower cost hybrisation with its particular existing stock of fossil generated power plants,
then its adaptiveness has improved (quantitatively) along the cost dimension.
External contingency. A compressed air or hydroelectric pumped storage capability
associated with a wind turbine farm enables the meeting of electricity demand to be less
contingent upon the timing of the wind regime and the ability of the rest of the generating
network to balance the load.
Which particular type of adaptiveness measure might be the most relevant will again
depend on the particular strategic circumstances – the scope, timing and significance of
the uncertainties that are being faced. A technical capacity to install and operate an
integrated gasification combined cycle generator within two years is not required at the
current stage in that technology's development – a ten to fifteen year commercialisation
time scale should be sufficient. Once the key dimensions of the adaptive response have
been selected – for our generator company, for instance, it might be the range of
renewable hybridisation technologies accessible to it and the speed with which it can take
these up – then measures for these same features form the leading or key performance
indicators in that situation. Other features of the options – for instance, how costly a
specific hybrid option is to install, or how dependent it is on local weather – might then
form secondary performance indicators in the situation.3
III: Is the performance space adequate?
The concept of performance space has the merit of making necessary a clear conceptual
distinction between a system's capacity (the performance envelope), and any performance
or task requirements. Requirements are often better conceived of as being imposed
externally due to the characteristics of the environment.
For example, let us suppose that an energy generating company has a performance
requirement imposed on it to profitably make a reasonable return on invested capital.
This depends not only upon the inherent performance space of the company, but also
upon external constraints of the economic environment which are beyond the company's
direct control - conditions such as the continued availability of resource inputs at
sufficiently low cost and a market for its products at sufficiently high prices. A sufficient
condition for the adaptiveness of the company to be adequate to the profitability
requirement is that its performance space meet or exceed the profitability requirements
imposed by the external economic conditions, over a range of feasible conditions. That is,
it must be that for each feasible economic market condition in the uncertainty range, there
is somewhere within the production performance space where profit performance is
satisfactory (that is, the production performance envelope must be adequate).
Furthermore the company management must be able to select that location in the
production performance space contingently upon the particular actual market conditions
(that is, the coordination performance space must also be adequate).
For example, assume that it is possible to guarantee that the market environment will be
such that the price of carbon will range up to $40/tonne of CO2 over the next ten years
Under some circumstances all performance indicators might be treated as variables in an encompassing
‘adaptation production function’ which is to be maximized. That would allow, and mandate, specific kinds
of trade-offs among performance indicator values, rendering any key/non-key distinction moot.
and range up to $80/tonne afterwards, that electricity demand growth will be between 1%
and 3% per annum for the next fifteen years, but that it is unknown whether carbon
capture and storage will be possible. What range of technological options does a
company need to be able to possibly bring on-line, and at what rates, in order to ensure
ongoing survival? Will it be sufficient to rely on developing a small amount of expertise
in carbon capture and storage and wind generating technology alone? Or would it be also
required to have expertise in biomass and solar thermal generation options as well, in
order to maximise the likelihood of ongoing profitability. These questions cannot be
answered without detailed knowledge of the specific siting opportunities and technical
expertise available to each firm.
For the purposes of this thought experiment, assume that some hypothetical energy
company is currently operating several large coal-fired power stations, and is fortunate
enough for one of them to be sited near a suitable location for carbon storage. Technical
assessments show that the additional cost of capture and storage at this site will be
between $20 and $35 per tonne, depending on whether infrastructure costs can be shared
with other industry players. The company also has a small number of experimental wind
turbines, and an option to purchase a number of sites for larger scale development of its
wind generating capacity.
Due to its continued access to low cost fuel (coal) and the expectation that there will be
no CO2 restrictions for the next six years, the company is confident of remaining
profitable for that period of time. In fact, the existing portfolio of coal generators will
remain profitable up to $40/tonne of CO2 (noting that the wholesale price of electricity
increases with the carbon penalty). Fortunately, one of the wind sites becomes profitable
at $30/tonne and the remainder are profitable at $50/tonne, assuming the availability of
adequately trained personnel. Thus, the following adaptive strategy is decided upon.
Plans to develop the most likely wind site will be drawn up and a sufficient number of
personnel to operate that site will be given experience with the currently existing
experimental turbines. Meanwhile, plans to install carbon storage infrastructure at the
suitable site can also be drawn up.
If a carbon penalty remains low or zero over the next decade, then neither plan is
implemented. If it creeps up to the level at which carbon capture and storage becomes
cost effective, and its technical feasibility has been demonstrated, then those plans can be
realised. At higher carbon penalty rates the most attractive wind site can be developed,
with further personnel trained on that operating site if the carbon price looks to remain
elevated - with a view to developing the remaining sites and mothballing the existing coal
plants. On the other hand, if the carbon penalty rate remains moderate, then only the one
wind site would be developed in addition to the continued operation of the existing plant.
The above scenario makes explicit that in order to achieve satisfactory performance, a
certain degree of adaptiveness of the surrounding (economic) environment is required. In
particular the industrial environment has to be sufficiently adaptive to be able to provide
(or not provide) suitable carbon capture and storage plant, and wind turbines at sufficient
rates to keep the existing workforce occupied and maintain enough revenue for the
company to survive the transition. This may not be the case if the demand for such
developments increases simultaneously all over the globe.
Performance indicators for adaptiveness in these circumstances will be highly situation
specific. What percentage of the workforce is trained to operate the prospective
alternative technologies (wind and carbon capture) relative to potential requirements?
How quickly could the wind site be developed? What is the prospective cost of carbon
storage? What range of technological options is under serious consideration (in the above
example, there are only the two)?
We can then see reasonably intuitively how research & development can result in
increasing the range of satisfactory performance. On the one hand, research &
development can improve the performance space of a new technology directly, or
indirectly by reducing its cost or construction time. On the other hand, research and
development can reduce the range of uncertainty due to ignorance associated with the
environmental conditions. For an example of the former, the development of compressed
air energy storage for wind turbines will expand the range of energy demand profiles that
can be met, thereby extending the performance space of the wind farm. As an example of
the latter, research identifying that the carbon price will be within the range of $20-
$40/tonne over the next twenty years narrows the range of uncertainties that must be dealt
IV: Some examples: adaptiveness indicators for the coal industry
The following describes the development of some adaptiveness performance indicators
for the coal and energy industries, at varying scales of analysis: from individual
technologies, to processes composed of technological networks, to entire organisations,
to industries (coal - including steel and electricity and/ or energy - including transport), to
national and global economies.
The operational performance space of a coal boiler, an individual technology, can be
expressed in terms of its thermal power and temperature output, range of acceptable fuel
inputs (coal – or other fuel such as biomass and oil – type, and particle size) as well as
pollutant outputs (for example, lower NOx might be achievable at lower temperatures).
The scope of this space will be described in kW and degrees for power and temperature,
specific identification for fuel type, and for pollutants, mass density and flow rate.
Timeliness will be described in terms of how quickly its power output can be raised or
lowered to meet demand requirements, or how quickly the switching of fuel can be
achieved. And it is not simply the technical feasibility of the performance that matters. In
order to achieve its full range within the technical performance space the boiler requires a
regulator, whether that takes the form of automatic control equipment, skilled operators,
or a combination of both. Only those performance conditions that the plant personnel are
confident to operate in can be achieved.
A technological process network, such as an integrated gasification combined cycle
process, has both an operational performance space and a process development
performance space. Analogously to the operational performance space of an individual
technology, this can be expressed in terms of its range (quantitative upper and lower
capacity bounds and type) of output products - without further chemical processing plant
to convert the syngas into other hydrocarbons the range of product types includes
electricity, thermal energy, hydrogen, CO and CO2 in varying ratios. The performance
space will also include a range of acceptable input fuels (various acceptable combinations
of coal, syngas,and natural gas). Operational timeliness will describe how quickly the
operating point can be changed.
The process development performance space describes the range of possible capital
improvement retrofit options that are available – such as carbon capture equipment, or
further chemical processing plant suitable for the production of synthetic fuels such as
hydrogen, methanol or diesel. Each possible retrofit option will be associated with its
own individual operational performance space. Process development timeliness will
describe how quickly such capital improvement retrofit (and necessary associated
operator training) can be implemented. In order to achieve the full range within the
process development performance space, skilled design engineers, who have an
understanding of how to optimise the process design, are required. The process
development “coordination performance space” will characterise how well the design
engineers understand the process development possibilities.
It is similarly possible to describe the performance space of the organisation that owns
and operates such engineering processes. It will also have both operational and process
development performance spaces corresponding to the aggregation of those of its
constituent technologies and technological process networks. Its operational performance
space represents immediately available, typically inexpensive, options for changing the
production schedule and might be characterised by fuel resources and other materials
used, labour required and energy services delivered. Its process development
performance space represents more significant alternatives for process augmentation and
other modifications, though ones that retain essentially the same character of process.
These might include options such as boiler modification to accommodate an integrated
drying process with brown coal fuel, the upgrade of sulfur control equipment, retrofitting
a coal boiler with the injection of oxygen enriched air, or adding a solar thermal process
that preheats recondensed steam before the heating cycle is completed in the boiler.
As the process modifications become more and more significant, they eventually
encompass the possibility of entirely different technological processes and/or business
models. Such possibilities have been discussed above, and can also be described in terms
of scope and timeliness. Is it a realistic possibility for the organisation to invest in modern
supercritical generation, or in solar thermal plant? How quickly could this be achieved,
taking into account the requirement for regulatory approval, financing, workforce training
and construction? Is there are realistic possibility for the organisation to invest in
sequestration activities or perhaps to focus business activity around expertise in
emissions reductions? One possible indicator of organisational innovativeness might be
the number and significance of new technical processes (or business models) introduced
in the last five years.
At the scale of the wider energy sector, the adaptiveness performance space includes new
industries and products that are synergistic with existing technological capacities and
personnel skills (that is, qualitative scope) as well as export market potential (quantitative
scope). Both the coal and uranium mining industries have high export market potential
(uranium arguably more so than coal in a carbon constrained global economy). However
coal-based electricity generation technologies can be hybridised synergistically with solar
thermal, which also has export potential. If wind turbines are manufactured locally, this
will enhance Australia's technical capacity to make small-scale electrical generators and
drives. A biofuels industry represents an opportunity to take advantage of existing
agricultural capacity. This observation emphasises that energy supply technologies
should not be evaluated solely in terms of their cost, but also in terms of the industrial
development possibilities that are enabled by the technical skills that they support.
Consideration of timing as an indicator is necessary because some technologies, such as
nuclear for example, require decades of advance planning, in this case to establish
appropriate regulatory institutional arrangements and technically trained personnel.
Hence at the scale of the energy sector of the national economy, performance indicators
might include, for example, the extent (and diversity) of economic exchanges with other
sectors, the skill levels (as well as quantity) of employment promoted (the coal industry
does well here), or the extent to which the technology could be part of an Australian
export industry (concentrating solar thermal does well here).
Thus adaptiveness indicators will provide answers to questions like the following.
Timeliness: How quickly would it be possible to replace less thermally efficient power
plants with more efficient higher temperature versions? Improvements will be obtained if
this installation time can be shortened through clever retro-fitting designs. How long
would it take to develop an export industry in concentrating solar thermal technology?
Improvements will be obtained if this time can be shortened through domestic industrial
involvement in demonstration projects. Quantitative scope: What is the present capacity
for biomass cofiring with coal? How stringent is the requirement that energy is generated
simultaneously to demand, that is, what is the potential storage capacity of the energy
system? Improvements will be obtained if these capacities can be increased. Qualitative
scope: What is the range of responses available to Australia in response to the doubling
of the price of oil? Improvements will be obtained if extra potential responses can be
developed (preferably without too much redundancy).
Thus there are many potential indicators of the scope and timelinesss of the performance
space of coal industry related technologies and organisations. Which are the most
relevant for any particular case will depend on the scale of analysis, the characterisation
of acceptable outcomes, and the most significant uncertainties. For the energy industry
the most obvious significant uncertainties include the potential impact of carbon
constraints on energy policy and economics, the technical and political feasibility of
carbon capture and storage, the availability and security of oil and natural gas supplies
(both domestically and internationally) and the economics of ongoing developments in a
wide array of energy technologies. Corresponding relevant adaptive options will include
the capacity to reduce carbon emissions quickly and cost-effectively if necessary,
including options for capture and storage, the options to lower demand - or produce
substitutes - for oil, low cost options to use - or not use - natural gas depending on
availability, and the ability to quickly exploit new supply technologies as they become
Note that some adaptive capacities of an aggregated system of components will depend
on the corresponding adaptive capacities of the components. For example the total
quantitative range of energy supply capacity of an energy network will be composed of
the corresponding supply ranges for each of its existing component supply technologies.
More significant adaptive capacities include the ability to remove, add, or modify
component subsystems - for example the ability for the energy industry to decommission
generating plant, retrofit new advanced processes (such as oxy-PF, post-combustion
capture, coal dewatering pretreatment), or commission new plant (such as advanced
thermal coal, integrated gasification, wind, concentrating solar thermal).
V: Industrial networks and adaptiveness
Industrial and technological networks operate at scales between firm and sector (though
in some cases may cross industry sectoral boundaries) and are here discussed in some
detail focusing on the different ways in which the performance space is affected by the
elaboration of network linkages. Indeed, the concept of performance space permits a
more precise description of how industrial networks can impact on adaptiveness.
For example, when BHP sources hydrochloric acid for cleaning steel from the waste by-
product of Orica's production and recycles the spent acid back through Orica
(note 1), the external contingency requirements of the performance spaces of both
organisations are reduced. In particular, neither process now relies exclusively on an
external supply of raw materials, but has a choice of whether or not to source it from their
network partner as an alternative. However, performance space analysis also reveals that
sufficient buffer storage capacity for both the raw and spent hydrochloric acid is required
in order that there is mutually independent flexibility in production rates of the two
In the absence of such storage capacity, the rates of the two processes would be mutually
coupled and thus mutually constraining. The performance space of the coupled network
is smaller without the buffer storage than with it. On site storage also improves the timing
responsiveness of the production processes. The mutual trading of wastes for resources
provides an example of a purely quantitative modification to the performance space scope
of the two production processes. The types of product and resource input requirements
remain the same, only the range of quantities supplied and demanded is altered.
Note that if, as a result of the new network interconnection, the relationships with the
original resource suppliers are permitted to atrophy, then the external contingency
requirements that are assumed to be operative no longer hold. Making a fair adaptiveness
comparison between the original case (external supplier links but no interconnection) and
this alternative (network interconnection but poor external links) requires the relevantly
distinct components of the external environment (that is, the supplier links) to be brought
within the boundary of analysis. In other words, fair comparison requires analysis of the
performance space of network partners plus suppliers. This illustrates an important
general lesson about choice of relevant system for proper adaptiveness comparisons.
The elaboration of the Werribee sewage treatment works network 4 , on the other hand,
where sewage cascades through a sequence of fields marked by extracting useful
products from its contents, represents an extension of the qualitative scope of the
performance space. Adding methane, grass and cattle to the range of products that
formerly included only treated sewage adds extra dimensions to the space. Feeding back
the produced methane to reduce the electricity requirements of the treatment works also
makes a quantitative modification to the resource input demand of the original
performance space. Export of clean effluent for the irrigation of market gardens and
recognition of the bird habitat function of the wetlands may also be regarded as
qualitative extensions of performance space scope. Here we have an example of an
extension of qualitative scope of performance space due to the addition of qualitatively
distinct technological components in the network. 5
However, qualitatively distinct options need not be mutually technically interconnected
or have wider network effects. Consider a case where the energy industry had access to a
portfolio of independent electricity generation technologies (eg: wind, biomass, advanced
supercritical coal, integrated gasification, natural gas and nuclear) that could each
potentially be deployed over reasonably short time periods (say 7 years or less), the
actual deployment of any one technology acting as a substitute for the deployment of the
others. Here, the development performance space is composed of qualitatively distinct
elements that are essentially simply redundant on one another. The redundancy confers
an adaptive capacity (the choice among the technologies as circumstances dictate), but
not network interconnectedness.
On the other hand there can be significant interdependencies among suites of energy
technologies 6 which mean that their contingent opportunities for adaptive deployment
must be considered together. For example, the development of a market for coal derived
synthetic liquid hydrocarbons for transport fuel requires modification both to the motor
vehicle fleet so that it is more adaptable to alternative fuel sources, and to the fuel
distribution network so that it is more adaptable in the range of products it can supply.
But such a development towards multi-fuelling will also provide a market for biofuels
such as methanol, ethanol and bio-diesel. Thus the potential adaptive capacity of both a
biofuels and synthethic liquid hydrocarbons industry depends on the composition of the
See industrial discussion paper #6, Industrial networks - an important framework tool for sustainable
policy and planning, at www.ccsd.biz.
Note that due to the interconnected and dynamic nature of the relationships among the effluent cleansing,
methane producing, grass growing and cattle grazing processes, the quantitative performance space of this
network may not be simple to describe completely.
See industrial discussion paper #3, Adaptiveness evaluation of Coal21 report, at www.ccsd.biz.
motor vehicle fleet, which in turn depends on the reliable and cost-effective availability
of alternative fuels. In contrast to the development of a domestic oil field producing
standard fuels, both synthetic liquid hydrocarbon and biofuels technology have a
qualitatively distinct impact on the adaptive possibilities for the development of the
transport fuels industry. Either technological suite could synergistically open up the
adaptive options for development of the other. The scope and range of the input fuel
performance space of the domestic motor vehicle fleet and the scope and range of the fuel
distribution performance space of the fuel distribution network might be a useful
adaptiveness indicator in this case.
Similarly, concentrating solar thermal plant can be hybridised with thermal coal in the
provision of base-load generation. A combination of coal and solar thermal plant with
heat storage could provide a load-following capability that matches demand more closely
than a single-technology generation portfolio of either option. 7 The deployment of
concentrating solar thermal generating capacity in hybridised form will develop
Australian operating capability in the technology. It may lead to Australian
manufacturing capacity and will, due to encouragement for technological development in
the area, also enhance the economic feasibility of the technology as a non-hybridised,
stand-alone plant, and for export in both forms. The qualitative and quantitative scope of
domestic operations and manufacturing capability for energy technology might be useful
performance indicators in this case.
In sum, enhancing network linkages can result in extending the quantitative, but not
qualitative, scope of the performance space (BHP-Orica example) and/or in extending the
qualitative scope of the performance space (Werribee example). However, if the adaptive
options are mutually independent redundancies no network linkages are formed.
Nevertheless, there are a number of energy technologies that are technologically
interdependent either via network effects involving modifications to the wider supply
chain, or due to the potential for hybridisation producing novel capabilities not realisable
by single technologies alone. In all these cases the features of the resulting performance
space suggest the choice of adaptability indicators.
Finally we are reminded of the substantial cost consequences of maintaining real adaptive
options. Retrospectively, preceding investment in adaptive capability will appear to have
been wasted. However, this will not be the case because it will have been impossible to
know in advance which particular capabilities will prove valuable, and the preparedness
to respond as the occasion demands will have its own (real option) value. 8
VI: Performance Space and Ecological Systems
The concept of performance space provides an understanding of why, within an
Coal can provide twenty-four hour base load generation while solar provides an extra power boost during
daylight hours when demand is greater. Heat storage capacity provides flexibility to modify the generation
profile in order to follow demand even more closely.
See industrial discussion paper #2, Introducing adaptive sustainable development - a framework for
policy and planning, at www.ccsd.biz.
ecosystem, a range of functionally redundant species with a diversity of responses to
environmental disturbances can result in functional resilience of the ecosystem. The
performance space of an ecosystem corresponds to the range of possible species
distributions, contingent externally on climate variables and internally on biochemical
signalling and other coordinating variables. Interaction among species transforms the
ecology into a production network. It is on the network dynamics that much of the
characteristics of an ecology, including its resilience to change, depend. 9
If there are no interactions among species then this can be regarded as a simply redundant
ecosystem structurally analogous to having available a range of independent
technological options, e.g. Australian inland dry grasslands. An ecosystem with few
species has a performance space that is qualitatively limited in scope and relatively
narrow in the range of environmental conditions within which relevant functions are
preserved. On the other hand, an ecosystem with many species often has accessible to it a
much wider range of species distributions, and shows more resilience to perturbations.
Though often very complex and not well understood, both effects are largely due to the
ways that species serve to support each other directly through food webs and indirectly
through their contributions to such shared resources as soil conservation, water retention
and humic content in soils. These network interdependencies both support larger species
numbers and population sizes, and resilience, through complex feedback loops that
stabilise ecosystem functioning in the face of perturbations (such as fire or disease).
Though not identical, these ecosystem network features have analogues in the ways that a
primary energy technology (such as coal) becomes embedded in a complex economic
network of industries (see V above), with financial and production feedback
interdependencies that will largely stabilise macro-economic functioning against even
substantial changes in energy sources (cf. change in photosynthetic sources in food
An unpredictably changing world requires a broad suite of relevant adaptive options to
meet a broad range of possible contingencies. That suite of adaptive options realises a
multi-dimensional performance space of performance possibilities. A narrow
performance space will be risky if only a narrow range of possible contingencies can be
acceptably accommodated. While developing a broader performance space will divert
resources away from being highly efficient (narrowly conceived), it will also result in a
more moderate strategic risk profile. Sustainability – of any valued condition – whether it
is the ability for human technical and economic development to meet human needs, or
whether it is the integrity of natural ecosystems, requires a minimum sufficient degree of
See, e.g., Gunderson L.H. and C.S. Holling (eds. 2002), Panarchy: Understanding Transformations in
Human and Natural Systems, Island Press, Washington; Walker B., et al. (2002), “Resilience Management
in Social-ecological Systems: a working hypothesis for a participatory approach”, Conservation Ecology,
Future technological and policy developments in the energy sector are highly uncertain
and also potentially subject to rapid change. By the above argument, this requires a broad
suite of economic and social potential adaptations to ensure that the energy sector not
only continues to securely and cost-effectively supply the energy requirements of
Australian society across the broadest possible range of likely future developments, but
also supports the industrial basis of the economy via the maintenance and development of
innovative and productive technical skills. What is the currently accessible performance
space of the Australian energy industry - or that of particular energy organisations? On
what key external contingencies and internal coordination is its functionality dependent?
Does the energy industry realistically have only a small number of technological options
and business models that it could genuinely move towards within a reasonably short
period of time - or is it actually capable of realising a broader range of technological
futures if the opportunities were to arise? What is the performance space of industrial
development opportunities in other economic sectors that is supported by its current mix
of skills and technical capacities?
Indicators for a performance space will be measures of its scope, the timeliness of the
ability to move quickly within the space, or the stringency of external conditions and
internal coordination that must hold for the performance space to be accessible.
Improvements in adaptiveness will be recognised when the performance space scope is
extended (quantitatively or qualitatively), when the time that would be required to reach
various points in the space is reduced, or when the achievement of the performance
possibilities is made less dependent upon external conditions. Internal coordination
capacity becomes especially important when, as in the current energy technology
circumstances, resilient response calls for a coherent sector capacity to experiment, learn
and grow adaptive options nationally in the face of recent industry fragmentation in the
pursuit of increased market competitiveness. However, constructing relevant
adaptiveness indicators requires an appreciation of the wider external context - the most
significant uncertainties and the key criteria for judging the adequacy of outcome.
Furthermore, there will rarely be a definitive answer to the question of how much
adaptiveness is sufficient – this will ultimately depend on wise judgment based on the
relative costs of acquiring a relevant portfolio of adaptive capacities and an appreciation
of the plausibility of scenarios in the recognised uncertainty range.
We have noted that developing suitable network interlinkages can extend the
performance space of the wider interlinked system - improving adaptiveness
quantitatively and/or qualitatively. Furthermore, the realisation of some technological
options (such as fossil derived synthetic fuels) can synergistically improve the adaptive
capacity of the economy to realise other technological opportunities (such as biomass
derived synthetic fuels) via its impact on the wider industrial network. Thus not all
adaptive capacities relevant to new technologies will be inherent within them - their
adoption can have spillover effects, contributing to the adaptive capacity of the wider
industrial or economic network.
The complexity of natural and human cultural and economic dynamics means that it will
always be somewhat uncertain whether or which specific ecological and socio-economic
conditions are absolutely necessary for the sustainability of continued functioning. In
such circumstances it is prudent to seek to expand the range of relevant options available
and to shorten their potential realization time, and to avoid either eliminating options or
allowing preparedness for their timely realization to lapse. The space spanned by the
performance realized by the set of available options then represents the adaptive capacity
that should be preserved or enhanced for adaptive sustainability – in technologies,
industries, economies, ecologies and in our societies and culture.