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Forecasting, backcasting, migration landscapes and strategic planning maps
Futures 37 (2005) 273–285 www.elsevier.com/locate/futures
Forecasting, backcasting, migration landscapes and strategic planning maps Peter J. Dortmans* Land Operations Division, Defence Science and Technology Organisation, PO Box 1500, Edinburgh SA 5111, Australia Available online 19 October 2004
Abstract Forecasting and backcasting are both useful techniques for futures strategic planning. However, attempting to integrate these is problematic as the former constrains what the latter can achieve. Here, development of strategic planning maps to mediate this transition is suggested. These are based on the development of migration landscapes that span the gap between projected trends and aspirational futures, highlighting those intermediate events or indicators that will indicate realisation. This allows the determination of intermediate states assuring viability during the transition and the opportunity to respond to changes in the environment. As such, decision makers can better manage risk and so make better informed decisions. Crown Copyright q 2004 Published by Elsevier Ltd. All rights reserved.
1. Introduction One of the greatest challenges to any organisation that wishes to integrate long-term planning within its development cycle is to be able to provide an effective and efficient process for the identification of and transition to future environments. For industries such as Defence, this is made more challenging by the fact that maintaining an edge in such a technology rich environment can become problematic given the length of time necessary for the identification, development and procurement of new systems, and the long lifetime for most Military equipment. This means that capability procurements are programmed in the order of a decade in advance, with further planning for a (largely incremental) future force extending out a further 10 years. However, the expected operational lifetime of these * Tel.: C61-8-8259-5625; fax: C61-8-8259-4193. E-mail address: [email protected] 0016-3287/$ - see front matter Crown Copyright q 2004 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.futures.2004.07.003
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capabilities extends well beyond that timeframe, a factor exacerbated by the rate of technological change. Even in other industries where procurement cycles are shorter, market dynamics and the ongoing integration of new technologies and operating processes are important. Failing to adapt to them may lead an organisation to become uncompetitive and effectively irrelevant. In both cases, it is the dynamics of the operating environment and of technologyinduced changes (which themselves are interdependent) that provide the greatest opportunity and threats to the viability of the organisation. Therefore, one needs to think towards a future within which the organisation can be recalibrated to operate effectively. Of course, there are usually significant constraints on how such changes can evolve, not the least of which are the legacy organisations or systems we begin with. Coupled with that is a greater level of certainty about the near future. This, however, can lead to two unrelated (and potentially fundamentally different) landscapes of futures, derived either from forecasting or backcasting. So it is important to develop migration landscapes that indicate the relationships and possible paths between these. Such an approach allows identification of multiple contexts (each with their own aspirational future), multiple projected pathways to each and the identification of some key milestones that would suggest a divergence from and/or convergence to particular contexts. In this article, we explore this approach of linking backcasting [7,18] and forecasting through projected migration landscapes as an approach to provide an effective basis for strategic planning development. While developed within a Defence context, we believe it remains applicable to most dynamic strategic planning environments. We discuss the capacity to use current knowledge of legacy systems along with projected technology trends to forecast the evolution of capability into the immediate future. We also consider the strategic goals towards which an organisation may aspire (or even avoid). These, then provide a basis to backcast from. Finally we identify migration (or development) landscapes that provide potential pathways along which an organisation can develop in order to transition from the current state to the future state(s) deemed optimal.
2. Why backcasting and forecasting alone are not enough In order to meet the challenges of strategic planning within a dynamic operating environment, we need the ability to identify (aspirational) visions of the future and backcast from these. However, care must be taken with such a normative approach as fundamental shifts in the global (or local) context can quickly render plans developed against such futures redundant. Indeed, the fall of Communism and rise of terrorism as the major threat to the West happened in barely a decade, a relatively short time in the Defence procurement cycle. It has led many of the major Western powers to attempt to fundamentally change the shape of their Defence Force. Indeed, one might argue that the current attempts at restructuring Defence Forces were a response to the end of the Cold War (and the implicit risk of massed force-on-force confrontations), and the transition into a global policing role for Defence. In that case, the consequences of global terrorism and doctrines such as pre-emptive attack are only just beginning to influence capability development.
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Concurrently, we need also to forecast how to advance towards the future, as any organisation needs to remain relevant (or profitable) as it moves towards its long-term goals. It is futile to be in line to deliver the world’s greatest widget in 10 years if the organisation goes bankrupt in the interim. So an understanding of the potential trends will provide some opportunity to remain solvent while working towards the future vision. To complicate matters further, most organisations have considerable sunk-costs in terms of equipment, people and expertise. Change, therefore, will be restricted because of the very nature of the organisation. Thus, we need to develop migration landscapes that provide the capacity to support the transition and potential intermediate states that facilitate it. Then, through the identification of key indicators within the landscape, we can project where decisions and reassessment are necessary within an auditable process. Given the lack of knowledge of how the future will evolve, and hence, the potential divergence between aspiration and realisation, the migration landscapes provide risk mitigation to strategic planning. Given the interplay between trend and aspiration, a linked bimodal model such as this can consider both the technological push (evolutional momentum driven by individual wants) and the collective community pull (decision-based formalism). The former is chaotic and dynamic and lends itself to forecasting; the latter is controllable once articulated but difficult to forecast [12].
3. Forecasting The art of forecasting is well known and extensively practised, especially in the area of short to medium term strategic planning (e.g. [21], although one could reference literally hundreds of articles). It is evolutionary in nature and based on the extrapolation of current and historical trends to identify potential effects that might evolve. Forecasting has been defined as ‘purposeful and systematic attempts to anticipate and understand the potential direction, rate, characteristics, and effects of technological change, especially invention, innovation, adoption, and use’ [2]. As such, forecasting provides an opportunity to attune organizational strategies and/or workforce practices to create an environment conducive to the realisation of those effects deemed optimal. As it provides forewarning, those employing such a strategy can be proactive in their response to potential (near to medium term) opportunities or threats. In effect, forecasting is a risk management strategy aimed at providing those who employ it with a mechanism to stay one step ahead of their competitors. Forecasting is not, however, purely a linear progression as relationships and interactions between various (potentially inter-dependent) factors can conspire to create complex behaviours, as any observation of weather forecasting can attest. The critical element here is to determine what level of complexity is acceptable given the problem space and hence what level of abstraction is necessary. Returning to the weather forecasting analogy, daily forecasts require significant detailed information pertaining to many atmospheric components from a range of sources (local temperatures, wind speeds, humidity, atmospheric pressure, etc.), whereas long-term forecasting requires more generic information (such as ocean current and temperatures for El Nino). Therefore
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the process for developing forecasts is critically dependent on the problem space under investigation. To forecast futures, whether it is focused on social or cultural changes, emerging strategic environments, or technology innovation, we believe it is advantageous to employ a multimethodology approach by identifying and amalgamating various appropriate techniques. Certainly, the George Washington University (GWU) Forecast [2] uses such a philosophy to forecast possible timeframes for identified technological innovations. This includes environmental scanning, trend analysis, Delphi and scenario building. They profess to make reasoned predictions out to 30 years.1 Certainly analysis of the Japanese NISTEP series of forecasts [9,23] indicates a reasonable success rate can be achieved [13,15]. While these activities have had a particular (technology) focus, they do show the utility in extending any analysis of technology change to the development of effects-based technological concepts that broadly describe the impact of aggregating and synergising technologies. These technological concepts can then form the basis of analysing the impact of technology and highlighting areas of high value or great risk. Technology and futures forecasting have similar requirements. For a telecommunication business designing future systems, the operating environment requires precise knowledge of technology developments and specifications. Importantly, it needs to have some appreciation of realisation timelines, as this can often be the key determinant for success or failure. Certainly, there is significant benefit in entering the market place at a precise time. Enter too early and the market may not be ready for the product, as it gives a competitor the opportunity to develop a more functional product at a later, more appropriate time. On the other hand, enter late and the niche of opportunity may have passed by. Indeed, some suggest this is more an exercise in ‘market research’ in mainstream scientific trends than true forecasting [10]. Industries, such as Defence, have a longer-term view and so require a broader knowledge of the potential capabilities and effects that technologies (integrated within the particular operating environment) might deliver. Indeed, from the technology futures perspective, it has been noted that ‘Decision makers are less interested in the future performance of a specific technology per se, and more interested in the impact that a given technology or trend will have on its business in the future’ [8]. In such cases, it is essential to have a broad strategic direction to aim towards. This should provide the flexibility to incorporate emerging opportunities and/or adapt to changes in the operating environment. This can, however, create a problem, as trend extrapolation can become more problematic over time. Since forecasting is based on incrementalism, it is difficult to establish new strategic directions, if required. It is important, then, to provide a target of some form, and this, then provides a basis for appreciating the value of particular trends beyond the immediate timeframe. Hence, techniques such as backcasting, can be used to provide a normative vision against which we can extend, expand and (re-)focus future forecasts.
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They noted that from their experience, the focus of technology forecasting should be in the realm of 10–30 years as assessments in the less than 10 year timeframe are often overly optimistic while predictions beyond 30 years tend to be pessimistic, in their view.
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4. Backcasting Many of the decisions we have to make today have very long-term consequences. Therefore, it is essential to have some idea of what the future may hold when making major decisions. It is not enough to define a visionary state without first identifying the possible future contexts. While forecasting, can in part, provide a basis for this, there is a growing realisation that “long accepted scientific paradigm procedures such as validation and replication could not be applied to confirm the forecasting tools beyond the near future” [2]. This led, in part to the development of the process called ‘backcasting’ [18]. Here, potential future paradigms that are relevant to the case in question are identified, leading to the selection of normative, desired (or aspirational) future state (or states) [7]. These, then provide a target for strategic planning and for organizational change. Like forecasting, backcasting is “a methodology for planning under uncertain circumstances” [11]. However, backcasting is built around a fundamentally different premise, namely that it is “a method in which the future desired conditions are envisioned and steps are then defined to attain those conditions, rather than taking steps that are merely a continuation of present methods extrapolated into the future” [11]. So while forecasting is about trends analysis, backcasting uses normative future visions to provide a basis to develop the strategies necessary for its realisation. Distinctions between forecasting and backcasting can be made along three axes [7]: † Backcasting is set in a context of discovery whereas forecasting is set in one of justification; † Backcasting is shaped by purpose whereas forecasting is shaped by causality; and † The fundamentals of backcasting are uncertainty and indeterminacy whereas for forecasting they are determinism and predictability. As such, backcasting allows one to move away from the incrementalism prevalent in forecasting, as it can create a desirable future that is fundamentally different than the current conditions. Indeed, it allows an organization to look to make revolutionary changes in the way it operates. The Australian Army has made backcasting a central plank to its continuous modernization program [14,22], whereby an aspirational, notional ‘Army-after-Next’ (AAN), set 30 years into the future, is backcast to identify the capabilities necessary for the Objective Force (OF), set in the 15–20 year timeframe [1]. In this case, the mechanism is the development and evaluation of a series of future warfighting concepts that are tested through a formal experimentation process [22]. This indicates that for organizations that have very long-term planning requirements in a complex and ever-changing environment, the backcasting philosophy can be usefully employed to provide a rigorous and traceable strategic planning process. We believe there are a few minor weaknesses with the backcasting approach, as described within the literature. Certainly, from our experience within the Defence context, divergence from unwanted futures is as critical as convergence to desirable ones. Trending towards a desired future might, under certain circumstances, quickly
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degenerate into an undesired one. One could point, for example, to the nuclear arms race of the latter half of the last century. Here the aspirational future of national and international security was achieved through overwhelming military firepower providing a level of stability between two superpower-blocks. However, changing circumstances have led to a current context where rogue states or terrorism are able to access nuclear devices and may have fewer inhibitions in using them. So while internal analysis may suggest some ‘optimal’ future, limitations in current knowledge or unexpected perturbations of the system may have major ramifications. So from a risk management perspective, the aim is not to seek the optimal future, but one that best delivers the desired outcomes at acceptable levels of risk. Therefore, backcasting requires the capacity to identify a future that is desirable within a number of possible contexts and be able to mediate between wanted and unwanted futures if necessary. Dreborg [7] states that “Backcasting studies typically aim at providing policy makers and an interested general public with images of the future as a background for opinion forming and decisions” with the intent being that “new knowledge and new ideas may lead to the identification of some entirely new options” [7]. This implies that it should be posited within a scenario-based setting. As described later, given the nature of these futures and the need to incorporate forecasting, it is important to be able to establish a chain of interrelated scenarios which transition to the timeframe being considered [19]. Techniques for developing a series of projected future contexts, such as Field Anomaly Relaxation2 (FAR), have great utility [4,17,24]. In particular using FAR, we can develop a range of scenarios from ones extrapolated from the current situation out to those on the periphery of possibility. Importantly, relationships and linkage between these can be proposed. Thus we can achieve Dreborg’s requirement that “the result of a backcasting study is alternative images of the future thoroughly analysed as to their feasibility and consequences.” [7] However, this leaves a set of problems: whether and how these can be realised. Therefore we need to develop a construct that will incorporate this.
5. Migration landscapes One of the major aims on any futures thinking (or foresight) activity is to develop knowledge and understanding of the complex ensemble of possible futures, and so, to provide the opportunity to develop strategies to be best placed to meet the challenges that emerge. Therefore, it would be ideal for any organisation in this circumstance to make decisions proactively and confidently. This requires some appreciation of their level of knowledge and the significance of it; an aspect that futures work is designed to 2 FAR is a systematic technique for describing potential futures where the environment is dynamic and evolved out of attempts to capture the essential factors that describe future scenarios. FAR can be usefully employed to facilitate discrepancy analysis where desirable (strategic) and probable (normative) futures are compared and difference highlighted.
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deliver. If we consider, for a moment, the three classes of knowledge suggested by Schoemaker3 [20]: 1. Things we know we know 2. Things we know we don’t know 3. Things we don’t know we don’t know While the first is trivial, the second is significant, as it sets a basis for expanding our knowledge. In fact, it is the transition from the second to the first class that is at the heart of futures work, and establishes the relationship between forecasting and backcasting. That is, by developing a migration landscape between what we confidently know or project (forecast) and what we desire (backcast), we can identify strategies to either discover what we do not currently know, or at least we can make an assessment cognizant of that. In either case, we are in a position to make better-informed decisions when required. Migration landscapes indicate options for transition in order to provide a road map for development (if we have the freedom to do this) or at least, they indicate potential pathways along which transition can occur, indicating the possible preconditions for change and so allowing for contingency planning to combat these. This means that a migration landscape is not merely an extrapolation of trends. Rather it is a web where possible alternate paths are signified by the interconnected strands of the web. The distinct pathways evolve from changes in the environment or in technology futures terms, to the realisation (or not) of projected discoveries. Therefore, connections between these strands provide the opportunity for making decisions. Identifying the significant points then provides a strategy for planning, in that most major decisions are projected in advance. However, there are risks with developing such migration landscapes. First, our knowledge and confidence of understanding the future decreases as a function of both time and fidelity. The further we think into the future, the more generic our models of it become. Second, there is always the likelihood that there is a discontinuity between that which is forecast and that which is backcast. Indeed, it would be surprising if this were not the case. Therefore, we need to create migration landscapes that focus towards some intermediate (realizable) point (or points) that can mediate between the aspired to and the projected. This point should be sufficiently far into the future to accommodate change but sufficiently well defined so as to allow for the commitment of resources. This philosophy is summarised in Fig. 1. Here, the desired and projected futures (developed through backcasting and forecasting, respectively) are mediated through an intermediate state or states. The basis for developing this intermediate state is the ability to describe a physical capability which can deliver the desired effects necessary to remain competitive at that interim stage and which places the organisation in an advantageous position to realise its future goals. Importantly, however, this does not entail a prescriptive 3
Donald Rumsfeld has received considerable attention recently for discussing knowledge in these terms.
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Fig. 1. Strategic planning map philosophy.
or particular physical solution. For instance, if a consequence of a desired future was to perform a new function, it could suggest significant changes the organisational structure. While we may not know exactly what that future structure should be, we can set an intermediate structure that remains functional and allows for the transition to the desired end-state. This structure, however, would be at a very high level, possibly only including functional groups, estimation of the personnel levels, and key roles. Indeed, the Australian Army’s OF is structured in this way [1]. Within any such intermediate state, there are multiple projected options. Indeed, one should expect that multiple options for a future organisation, product or system should coexist here. These options act as a safety mechanism, providing the flexibility to overcome unforeseen problems or opportunities. They also provide the basis for analysis of which option is the appropriate one to transition towards as time passes by and more information is known. For each, however, it is essential to know what are the success and failure criteria for their realisation along with the intermediate decision points. The importance of this last point cannot be underrated. Knowing in advance which decisions need to be made and when, allows the organisation to collect information and perform analysis pre-emptively, thus encouraging better informed decision making. In short, as Fig. 1 shows, the determination of migration landscapes indicates transition strategies and the associated decisions necessary over time. This identifies choice, and leads to a final, pivotal consequence; that the strategic planning activity is dependent on the context and the opportunity this provides. If we commence with one well developed system (such as an existing organisation) that is determining its long-term strategic vision, circumstances may exist where it is not feasible to develop multiple future contexts. At the other end of the spectrum, the concurrent development of multiple component entities (such as the integration of discoveries from distinct technology domains) where the endsate is unknown, we have multiple start points and potential end-states. In both cases the mapping to migration landscapes and intermediate states provides a basis for developing
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strategies for change that will be continually modified as new knowledge arises. The differentiating factor, then, becomes the determination of the appropriate levels of abstraction and fidelity to optimise the cost-benefit nexus.
6. Strategic planning maps Combining the elements of forecasting, backcasting and migration landscapes leads to the development of what can be defined as strategic planning maps for particular circumstances. As noted, they are dependent on the problem being considered. Indeed, it is possible that a number of layered concurrent maps would be necessary for a particular problem. For instance, within an organisation, there would be an overall strategic map in which the future visions and intermediate constructs are defined in very broad terms. In addition, it may be necessary to map out more focussed and detailed strategic maps whose significant outcomes would appear as decision points on a higher level map. This would allow particular users to design maps of the appropriate detail for particular users. These maps may be configured quite differently, some having single start and end points, other having multiple ones. Therefore, it is important to identify classes of these strategic maps. 6.1. One-to-one mapping The first class of strategic planning maps is one-to-one, that is, from a current singular state evolving into a future singular state. So while we project alternate futures, only one will be realised. Opportunity here, then, is related to influencing which future will evolve by using mechanisms to encourage the trajectory (or trajectories) that best align with the organisational goals. In many cases, the reality is that there is little opportunity to fundamentally change the direction. For instance, one cannot create an environment where there is an abundance of fossil fuels (although one might suggest one where there are bioalternatives). So, in such cases the goal is to preposition oneself to best realise opportunities while minimising threats. One example of this would be the development of future strategic contexts. For understanding future context and the evolution to them, techniques such as FAR have great utility in that they can provide insights into how situations might evolve, and the drivers for such evolution [3,4,5,16]. Significantly, analysis of what drives these transitions can provide operators with warning signals of likely changes in the environment and allow for proactive planning or at least the development of risk mitigation strategies. From this, plans can be developed to close the gap or at least manage the risk associated with it (operational). As such, it can provide a basis for determining the migration landscapes from the current state to the future one along with the key indicators as to the realisation of the desired future(s). 6.2. One-to-many mapping Another possibility is one-to-many mapping. In this case we have a singular entity with a desired end-state, but the opportunity to transform it in a number of ways. In this case,
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the strategic planning maps provide options from which an organisation can choose those that are preferable. Central to this choice would be the selection of those that are sufficiently close so that unforeseen variations pose only a limited problem. In addition, it means that the intermediate state or states are more flexible and responsive to change. An example of this might be for a broadly functional organisation that wishes to transform itself into a more focussed entity. In this case, they have many options to choose from and can select the path that meets their requirements. Of course, there are constraints. Indeed, the basis for identifying the requirements for any options is likely to be the possible contexts. Hence, one might employ a one-to-one strategic map to create an array of contexts from which those scenarios seen to be appropriate are derived. In this case, the options can be identified, developed and evaluated against such a backdrop. One useful application of the one-to-many strategic planning maps is organisational change within an evolving context. For instance, for an organisation that wishes to explore the development of new products, technology-based strategic maps have some utility. Certainly, to adapt to technology innovation, identifying and aggregating enabling technologies to produce a range of technological concepts is not enough. Determination of the viability of such concepts is essential. Therefore an understanding of the likelihood of the enabling technologies being realised, the timeframe within which this should occur and the critical elements on the pathway from our current knowledge to the fielding of a system articulated through the identified concepts all must be considered. One approach is to embed this technology migration landscape within the strategic planning map (other considerations such as the strength of the market place, the marketability of such technologies and competitive pressure are also necessary). This allows one to determine the direction of technological change in parallel to the development of future strategies and long-term visions. It also allows the opportunity to identify multiple trajectories for technological change and the associated indicators as time progresses. In addition, it provides an opportunity to consider revolutionary concepts (such as Quantum Computing) that might fundamentally change the operating environment, but are currently uncertain (both in terms of their realisation and associated timeframe). In such cases, the key indicators provide the mechanism for incorporating such technologies into strategic thinking by identifying the key milestones that must be achieved if these high-risk, high-payoff technologies are to be realised. 6.3. Many-to-many mapping Futures planning involving technology innovation would often take a many-to-many approach. That is to say, there may be many versions of what the current context is. For instance, some projected future technology concepts might be realised in different ways based on different beliefs on what particular technologies can do. In addition, there is often concurrent (although not necessarily competitive) research focussed on the development of products that would deliver the same functionality. For instance, the development of future computing power is concurrently following different streams; further enhancement of current chips (through further miniaturisation and energy efficiency), alternate chip designs (such as asynchronous chips), and alternate chip material properties (through lasing of Silicon), alternate chip types (using other materials such as boron-doped carbon),
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Fig. 2. Notional (simplified) strategic planning map for the army continuous modernisation process (taken from Ref. [6]).
alternate computing philosophies (chemical or quantum computers). One might also include developments in fields such as nanotechnology and biotechnology if the scope of the problem extended to possibilities for bio-computing. While each of these might deliver some unique capability (or not deliver at all), the options for the future computer are many and varied. As with the one-to-many mapping, there remains a need to identify the basic context, although this is likely to be less important as the concurrent developments would, in general, largely ameliorate shifts in context. However, in order to provide a basis for analysis, it is important to understand the context within which these technology concepts would be employed. As such, the determination of specific requirements for an array of options would serve the purpose. 6.4. Notional mapping—Army Continuous Modernisation It is instructive to give a pictorial representation of how a strategic map might look. Fig. 2 represents a way of viewing the progression to possible future force constructs based on contextual (e.g. technological) developments [6]. In this particular case, the army continuous modernisation process is considered. This, of course, is likely to be more simplified that a truly representative map, however, it does indicate the key points. Firstly, there are likely to be many possible future environments, within which particular scenarios are possible. These environments might range from dual competitive superpowers operating conventionally (e.g. Cold War), to a single superpower acting as the lead-global policeman to maintain stability (e.g. immediate post-cold war era), to conventional nation states being challenged by issue-based unconventional non-state actors (e.g. ‘War on Terrorism’). For each of these futures and associated scenarios, there is likely to be an optimal notional future Army (e.g. AAN). At the present time, we have the ‘Army in Being’4 and the challenge is to 4 In reality, we have the current Army plus those capabilities that are currently being procured and integrated into the Land Force. Therefore, the choice of starting point is probably the Army of 5 years hence.
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identify those strategies that will allow a transition to the future conceptual force that minimises risk, maximises functionality continually through the timeframe and is flexible enough to transition as new information occurs. As such we can both identify possible intermediate organisations (or in Australian Army parlance, OF’s), and the migration paths to achieve these. Importantly, there are a number of success indicators or events that will provide further information and assist in determining which path to pursue. Of course, we are not suggesting that all possible contingencies can be identified. However, we can use some analytical tools and techniques that can assist in recognising the trends, opportunities, threats and risks and integrate these. This, then, gives decision makers a level of insight beyond their current boundaries. Importantly, it forces them to think beyond the most likely projected future (which is often just an optimistic or pessimistic re-badging of the present to a future time). It requires them to plan against contingencies that are both possible and uncomfortable.
7. Conclusion Decision making is always an exercise in risk management. It is essentially about managing uncertainty in a structured, transparent and auditable way. Strategic planning provides decision makers with a basis for managing these issues by providing a mechanism to identify future goals and ways to achieve these. But there are always two competing agendas, namely where we desire to be in the future and what we can achieve with the resources we have. So the choice of approach is important. Backcasting and forecasting provide means for extrapolating from the present and towards an optimal future. However, much can be lost if these are not connected in some meaningful way. Therefore migration landscapes between these need to be articulated and analysed to identify those activities necessary for the realisation of a desired end-state. Such analysis might suggest that aiming towards a desired future may be high risk as slight changes in the environment in the interim may lead to the realisation of an undesirable future. In addition, if one is able to foresee important decision or events in advance, preparatory activities could be undertaken to better inform the decision maker as to the optimal path to pursue. Here we describe such a philosophy which links forecasting and backcasting through the development of strategic planning maps. We suggest these maps can be usefully employed to look at strategic contexts, organisational changes and technological innovation opportunities. These maps can have single or multiple starting points, depending on the circumstance of use, and can be embedded within one another to provide the appropriate level of fidelity to the problem. They also provide a basis for the identification of achievable intermediate states. These can provide a basis for determining the continued viability of an organisation during such a transition. We believe they provide the foresight, flexibility and transparency necessary for the realisation of opportunities within a futures strategic planning environment.
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References [1] J. Cantwell, Towards a future force: development of the Australian army objective force 2020, in Land Warfare Conference, Brisbane, 2002, pp. 39–45. [2] V. Coates, et al., On the future of technological forecasting, Technological Forecasting and Social Change 67 (2001) 1–17. [3] G. Coyle, The nature and value of futures studies or do futures have a future?, Futures 29 (1) (1997) 77–93. [4] R.G. Coyle, G.R. McGlone, Projecting scenarios for south-east Asia and the south-west Pacific, Futures 27 (1995) 65–79. [5] R.G. Coyle, Y.C. Yong, A scenario projection for the South China Sea: further experience with field anomaly relaxation, Futures 28 (1996) 269–283. [6] P.J. Dortmans, N.J. Curtis, Linking Scientific and Technological Innovation with Warfighting Concepts: How to Identify and Develop the Right Technologies to Win the Future Land Battle, in Land Warfare Conference—Future Wars: Futuristic Forces, Brisbane, 2002, pp. 59–72. [7] K.H. Dreborg, Essence of backcasting, Futures 28 (1996) 813–828. [8] G.T. du Preez, C.W.I. Pistorius, Technological threat and opportunity assessment, Technological Forecasting and Social Change 61 (1999) 215–234. [9] Future technology in Japan: towards the year 2020: The fifth technology forecasting survey—future technology in Japan. NISTEP Report. Science and Technology Agency—Japan: National Institute of Science and Technology Policy, vol. 25, 1992. [10] W.E. Halal, M.D. Kull, A. Leffmann, Emerging technologies: what’s ahead for 2001–2030, The Futurist November–December (1997) 20–28. [11] J. Holmberg, K.-H. Robert, Backcasting from non-overlapping sustainability principles—a framework for strategic planning, International Journal of Sustainable Development and World Ecology 74 (2000) 291–308. [12] P. Keller, U. Ledergerber, Bimodal system dynamic: a technology assessment and forecasting approach, Technological Forecasting and Social Change 58 (1998) 47–52. [13] T. Kuwahara, Technology forecasting activities in Japan, Technological Forecasting and Social Change 60 (1999) 5–14. [14] Land Warfare Doctrine 1: The Fundamentals of Land Warfare. Land Warfare Development Centre, Puckapunyal, 2002. [15] Matching science and technology to future needs: an international perspective. Australian Science and Technology Council; http://www.astec.gov.au/astec/future/intpers/contents.html, 1994. [16] J.H. Powell, R.G. Coyle, A network-based futures method for strategic business planning, Journal of the Operational Research Society 48 (1997) 793–803. [17] R. Rhyne, Whole-pattern futures projection using field anomaly relaxation, Technological Forecasting and Social Change 19 (1980) 331–360. [18] J.B. Robinson, Futures under glass: a recipe for people who hate to predict, Futures 23 (1990) 820–842. [19] P. Schoemaker, Multiple scenario development: its conceptual and behavioural foundation, Strategic Manaegment Journal 14 (1993) 193–213. [20] P.J.H. Schoemaker, Scenario planning: a tool for strategic thinkers, Sloan Management Review Winter (1995) 25–40. [21] P. Schwartz, The Art of the Long View: Paths to Strategic Insight for yourself and your Company, Australian Business Network, Sydney, 1996. [22] The Army Experimental Framework. Australian Army, 1999. [23] The seventh technology foresight—future technology in Japan towards the year 2030. NISTEP Report. Science and Technology Forecast Center—National Institute of Science and Technology Policy (Japan), vol. 71, 2001. [24] W.C. Wood, A.N. Christakis, A methodology for conducting futures-orientated workshops, Technological Forecasting and Social Change 26 (1984) 281–297.
Forecasting, backcasting, migration landscapes and strategic planning maps Peter J. Dortmans* Land Operations Division, Defence Science and Technology Organisation, PO Box 1500, Edinburgh SA 5111, Australia Available online 19 October 2004
Abstract Forecasting and backcasting are both useful techniques for futures strategic planning. However, attempting to integrate these is problematic as the former constrains what the latter can achieve. Here, development of strategic planning maps to mediate this transition is suggested. These are based on the development of migration landscapes that span the gap between projected trends and aspirational futures, highlighting those intermediate events or indicators that will indicate realisation. This allows the determination of intermediate states assuring viability during the transition and the opportunity to respond to changes in the environment. As such, decision makers can better manage risk and so make better informed decisions. Crown Copyright q 2004 Published by Elsevier Ltd. All rights reserved.
1. Introduction One of the greatest challenges to any organisation that wishes to integrate long-term planning within its development cycle is to be able to provide an effective and efficient process for the identification of and transition to future environments. For industries such as Defence, this is made more challenging by the fact that maintaining an edge in such a technology rich environment can become problematic given the length of time necessary for the identification, development and procurement of new systems, and the long lifetime for most Military equipment. This means that capability procurements are programmed in the order of a decade in advance, with further planning for a (largely incremental) future force extending out a further 10 years. However, the expected operational lifetime of these * Tel.: C61-8-8259-5625; fax: C61-8-8259-4193. E-mail address: [email protected] 0016-3287/$ - see front matter Crown Copyright q 2004 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.futures.2004.07.003
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capabilities extends well beyond that timeframe, a factor exacerbated by the rate of technological change. Even in other industries where procurement cycles are shorter, market dynamics and the ongoing integration of new technologies and operating processes are important. Failing to adapt to them may lead an organisation to become uncompetitive and effectively irrelevant. In both cases, it is the dynamics of the operating environment and of technologyinduced changes (which themselves are interdependent) that provide the greatest opportunity and threats to the viability of the organisation. Therefore, one needs to think towards a future within which the organisation can be recalibrated to operate effectively. Of course, there are usually significant constraints on how such changes can evolve, not the least of which are the legacy organisations or systems we begin with. Coupled with that is a greater level of certainty about the near future. This, however, can lead to two unrelated (and potentially fundamentally different) landscapes of futures, derived either from forecasting or backcasting. So it is important to develop migration landscapes that indicate the relationships and possible paths between these. Such an approach allows identification of multiple contexts (each with their own aspirational future), multiple projected pathways to each and the identification of some key milestones that would suggest a divergence from and/or convergence to particular contexts. In this article, we explore this approach of linking backcasting [7,18] and forecasting through projected migration landscapes as an approach to provide an effective basis for strategic planning development. While developed within a Defence context, we believe it remains applicable to most dynamic strategic planning environments. We discuss the capacity to use current knowledge of legacy systems along with projected technology trends to forecast the evolution of capability into the immediate future. We also consider the strategic goals towards which an organisation may aspire (or even avoid). These, then provide a basis to backcast from. Finally we identify migration (or development) landscapes that provide potential pathways along which an organisation can develop in order to transition from the current state to the future state(s) deemed optimal.
2. Why backcasting and forecasting alone are not enough In order to meet the challenges of strategic planning within a dynamic operating environment, we need the ability to identify (aspirational) visions of the future and backcast from these. However, care must be taken with such a normative approach as fundamental shifts in the global (or local) context can quickly render plans developed against such futures redundant. Indeed, the fall of Communism and rise of terrorism as the major threat to the West happened in barely a decade, a relatively short time in the Defence procurement cycle. It has led many of the major Western powers to attempt to fundamentally change the shape of their Defence Force. Indeed, one might argue that the current attempts at restructuring Defence Forces were a response to the end of the Cold War (and the implicit risk of massed force-on-force confrontations), and the transition into a global policing role for Defence. In that case, the consequences of global terrorism and doctrines such as pre-emptive attack are only just beginning to influence capability development.
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Concurrently, we need also to forecast how to advance towards the future, as any organisation needs to remain relevant (or profitable) as it moves towards its long-term goals. It is futile to be in line to deliver the world’s greatest widget in 10 years if the organisation goes bankrupt in the interim. So an understanding of the potential trends will provide some opportunity to remain solvent while working towards the future vision. To complicate matters further, most organisations have considerable sunk-costs in terms of equipment, people and expertise. Change, therefore, will be restricted because of the very nature of the organisation. Thus, we need to develop migration landscapes that provide the capacity to support the transition and potential intermediate states that facilitate it. Then, through the identification of key indicators within the landscape, we can project where decisions and reassessment are necessary within an auditable process. Given the lack of knowledge of how the future will evolve, and hence, the potential divergence between aspiration and realisation, the migration landscapes provide risk mitigation to strategic planning. Given the interplay between trend and aspiration, a linked bimodal model such as this can consider both the technological push (evolutional momentum driven by individual wants) and the collective community pull (decision-based formalism). The former is chaotic and dynamic and lends itself to forecasting; the latter is controllable once articulated but difficult to forecast [12].
3. Forecasting The art of forecasting is well known and extensively practised, especially in the area of short to medium term strategic planning (e.g. [21], although one could reference literally hundreds of articles). It is evolutionary in nature and based on the extrapolation of current and historical trends to identify potential effects that might evolve. Forecasting has been defined as ‘purposeful and systematic attempts to anticipate and understand the potential direction, rate, characteristics, and effects of technological change, especially invention, innovation, adoption, and use’ [2]. As such, forecasting provides an opportunity to attune organizational strategies and/or workforce practices to create an environment conducive to the realisation of those effects deemed optimal. As it provides forewarning, those employing such a strategy can be proactive in their response to potential (near to medium term) opportunities or threats. In effect, forecasting is a risk management strategy aimed at providing those who employ it with a mechanism to stay one step ahead of their competitors. Forecasting is not, however, purely a linear progression as relationships and interactions between various (potentially inter-dependent) factors can conspire to create complex behaviours, as any observation of weather forecasting can attest. The critical element here is to determine what level of complexity is acceptable given the problem space and hence what level of abstraction is necessary. Returning to the weather forecasting analogy, daily forecasts require significant detailed information pertaining to many atmospheric components from a range of sources (local temperatures, wind speeds, humidity, atmospheric pressure, etc.), whereas long-term forecasting requires more generic information (such as ocean current and temperatures for El Nino). Therefore
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the process for developing forecasts is critically dependent on the problem space under investigation. To forecast futures, whether it is focused on social or cultural changes, emerging strategic environments, or technology innovation, we believe it is advantageous to employ a multimethodology approach by identifying and amalgamating various appropriate techniques. Certainly, the George Washington University (GWU) Forecast [2] uses such a philosophy to forecast possible timeframes for identified technological innovations. This includes environmental scanning, trend analysis, Delphi and scenario building. They profess to make reasoned predictions out to 30 years.1 Certainly analysis of the Japanese NISTEP series of forecasts [9,23] indicates a reasonable success rate can be achieved [13,15]. While these activities have had a particular (technology) focus, they do show the utility in extending any analysis of technology change to the development of effects-based technological concepts that broadly describe the impact of aggregating and synergising technologies. These technological concepts can then form the basis of analysing the impact of technology and highlighting areas of high value or great risk. Technology and futures forecasting have similar requirements. For a telecommunication business designing future systems, the operating environment requires precise knowledge of technology developments and specifications. Importantly, it needs to have some appreciation of realisation timelines, as this can often be the key determinant for success or failure. Certainly, there is significant benefit in entering the market place at a precise time. Enter too early and the market may not be ready for the product, as it gives a competitor the opportunity to develop a more functional product at a later, more appropriate time. On the other hand, enter late and the niche of opportunity may have passed by. Indeed, some suggest this is more an exercise in ‘market research’ in mainstream scientific trends than true forecasting [10]. Industries, such as Defence, have a longer-term view and so require a broader knowledge of the potential capabilities and effects that technologies (integrated within the particular operating environment) might deliver. Indeed, from the technology futures perspective, it has been noted that ‘Decision makers are less interested in the future performance of a specific technology per se, and more interested in the impact that a given technology or trend will have on its business in the future’ [8]. In such cases, it is essential to have a broad strategic direction to aim towards. This should provide the flexibility to incorporate emerging opportunities and/or adapt to changes in the operating environment. This can, however, create a problem, as trend extrapolation can become more problematic over time. Since forecasting is based on incrementalism, it is difficult to establish new strategic directions, if required. It is important, then, to provide a target of some form, and this, then provides a basis for appreciating the value of particular trends beyond the immediate timeframe. Hence, techniques such as backcasting, can be used to provide a normative vision against which we can extend, expand and (re-)focus future forecasts.
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They noted that from their experience, the focus of technology forecasting should be in the realm of 10–30 years as assessments in the less than 10 year timeframe are often overly optimistic while predictions beyond 30 years tend to be pessimistic, in their view.
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4. Backcasting Many of the decisions we have to make today have very long-term consequences. Therefore, it is essential to have some idea of what the future may hold when making major decisions. It is not enough to define a visionary state without first identifying the possible future contexts. While forecasting, can in part, provide a basis for this, there is a growing realisation that “long accepted scientific paradigm procedures such as validation and replication could not be applied to confirm the forecasting tools beyond the near future” [2]. This led, in part to the development of the process called ‘backcasting’ [18]. Here, potential future paradigms that are relevant to the case in question are identified, leading to the selection of normative, desired (or aspirational) future state (or states) [7]. These, then provide a target for strategic planning and for organizational change. Like forecasting, backcasting is “a methodology for planning under uncertain circumstances” [11]. However, backcasting is built around a fundamentally different premise, namely that it is “a method in which the future desired conditions are envisioned and steps are then defined to attain those conditions, rather than taking steps that are merely a continuation of present methods extrapolated into the future” [11]. So while forecasting is about trends analysis, backcasting uses normative future visions to provide a basis to develop the strategies necessary for its realisation. Distinctions between forecasting and backcasting can be made along three axes [7]: † Backcasting is set in a context of discovery whereas forecasting is set in one of justification; † Backcasting is shaped by purpose whereas forecasting is shaped by causality; and † The fundamentals of backcasting are uncertainty and indeterminacy whereas for forecasting they are determinism and predictability. As such, backcasting allows one to move away from the incrementalism prevalent in forecasting, as it can create a desirable future that is fundamentally different than the current conditions. Indeed, it allows an organization to look to make revolutionary changes in the way it operates. The Australian Army has made backcasting a central plank to its continuous modernization program [14,22], whereby an aspirational, notional ‘Army-after-Next’ (AAN), set 30 years into the future, is backcast to identify the capabilities necessary for the Objective Force (OF), set in the 15–20 year timeframe [1]. In this case, the mechanism is the development and evaluation of a series of future warfighting concepts that are tested through a formal experimentation process [22]. This indicates that for organizations that have very long-term planning requirements in a complex and ever-changing environment, the backcasting philosophy can be usefully employed to provide a rigorous and traceable strategic planning process. We believe there are a few minor weaknesses with the backcasting approach, as described within the literature. Certainly, from our experience within the Defence context, divergence from unwanted futures is as critical as convergence to desirable ones. Trending towards a desired future might, under certain circumstances, quickly
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degenerate into an undesired one. One could point, for example, to the nuclear arms race of the latter half of the last century. Here the aspirational future of national and international security was achieved through overwhelming military firepower providing a level of stability between two superpower-blocks. However, changing circumstances have led to a current context where rogue states or terrorism are able to access nuclear devices and may have fewer inhibitions in using them. So while internal analysis may suggest some ‘optimal’ future, limitations in current knowledge or unexpected perturbations of the system may have major ramifications. So from a risk management perspective, the aim is not to seek the optimal future, but one that best delivers the desired outcomes at acceptable levels of risk. Therefore, backcasting requires the capacity to identify a future that is desirable within a number of possible contexts and be able to mediate between wanted and unwanted futures if necessary. Dreborg [7] states that “Backcasting studies typically aim at providing policy makers and an interested general public with images of the future as a background for opinion forming and decisions” with the intent being that “new knowledge and new ideas may lead to the identification of some entirely new options” [7]. This implies that it should be posited within a scenario-based setting. As described later, given the nature of these futures and the need to incorporate forecasting, it is important to be able to establish a chain of interrelated scenarios which transition to the timeframe being considered [19]. Techniques for developing a series of projected future contexts, such as Field Anomaly Relaxation2 (FAR), have great utility [4,17,24]. In particular using FAR, we can develop a range of scenarios from ones extrapolated from the current situation out to those on the periphery of possibility. Importantly, relationships and linkage between these can be proposed. Thus we can achieve Dreborg’s requirement that “the result of a backcasting study is alternative images of the future thoroughly analysed as to their feasibility and consequences.” [7] However, this leaves a set of problems: whether and how these can be realised. Therefore we need to develop a construct that will incorporate this.
5. Migration landscapes One of the major aims on any futures thinking (or foresight) activity is to develop knowledge and understanding of the complex ensemble of possible futures, and so, to provide the opportunity to develop strategies to be best placed to meet the challenges that emerge. Therefore, it would be ideal for any organisation in this circumstance to make decisions proactively and confidently. This requires some appreciation of their level of knowledge and the significance of it; an aspect that futures work is designed to 2 FAR is a systematic technique for describing potential futures where the environment is dynamic and evolved out of attempts to capture the essential factors that describe future scenarios. FAR can be usefully employed to facilitate discrepancy analysis where desirable (strategic) and probable (normative) futures are compared and difference highlighted.
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deliver. If we consider, for a moment, the three classes of knowledge suggested by Schoemaker3 [20]: 1. Things we know we know 2. Things we know we don’t know 3. Things we don’t know we don’t know While the first is trivial, the second is significant, as it sets a basis for expanding our knowledge. In fact, it is the transition from the second to the first class that is at the heart of futures work, and establishes the relationship between forecasting and backcasting. That is, by developing a migration landscape between what we confidently know or project (forecast) and what we desire (backcast), we can identify strategies to either discover what we do not currently know, or at least we can make an assessment cognizant of that. In either case, we are in a position to make better-informed decisions when required. Migration landscapes indicate options for transition in order to provide a road map for development (if we have the freedom to do this) or at least, they indicate potential pathways along which transition can occur, indicating the possible preconditions for change and so allowing for contingency planning to combat these. This means that a migration landscape is not merely an extrapolation of trends. Rather it is a web where possible alternate paths are signified by the interconnected strands of the web. The distinct pathways evolve from changes in the environment or in technology futures terms, to the realisation (or not) of projected discoveries. Therefore, connections between these strands provide the opportunity for making decisions. Identifying the significant points then provides a strategy for planning, in that most major decisions are projected in advance. However, there are risks with developing such migration landscapes. First, our knowledge and confidence of understanding the future decreases as a function of both time and fidelity. The further we think into the future, the more generic our models of it become. Second, there is always the likelihood that there is a discontinuity between that which is forecast and that which is backcast. Indeed, it would be surprising if this were not the case. Therefore, we need to create migration landscapes that focus towards some intermediate (realizable) point (or points) that can mediate between the aspired to and the projected. This point should be sufficiently far into the future to accommodate change but sufficiently well defined so as to allow for the commitment of resources. This philosophy is summarised in Fig. 1. Here, the desired and projected futures (developed through backcasting and forecasting, respectively) are mediated through an intermediate state or states. The basis for developing this intermediate state is the ability to describe a physical capability which can deliver the desired effects necessary to remain competitive at that interim stage and which places the organisation in an advantageous position to realise its future goals. Importantly, however, this does not entail a prescriptive 3
Donald Rumsfeld has received considerable attention recently for discussing knowledge in these terms.
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Fig. 1. Strategic planning map philosophy.
or particular physical solution. For instance, if a consequence of a desired future was to perform a new function, it could suggest significant changes the organisational structure. While we may not know exactly what that future structure should be, we can set an intermediate structure that remains functional and allows for the transition to the desired end-state. This structure, however, would be at a very high level, possibly only including functional groups, estimation of the personnel levels, and key roles. Indeed, the Australian Army’s OF is structured in this way [1]. Within any such intermediate state, there are multiple projected options. Indeed, one should expect that multiple options for a future organisation, product or system should coexist here. These options act as a safety mechanism, providing the flexibility to overcome unforeseen problems or opportunities. They also provide the basis for analysis of which option is the appropriate one to transition towards as time passes by and more information is known. For each, however, it is essential to know what are the success and failure criteria for their realisation along with the intermediate decision points. The importance of this last point cannot be underrated. Knowing in advance which decisions need to be made and when, allows the organisation to collect information and perform analysis pre-emptively, thus encouraging better informed decision making. In short, as Fig. 1 shows, the determination of migration landscapes indicates transition strategies and the associated decisions necessary over time. This identifies choice, and leads to a final, pivotal consequence; that the strategic planning activity is dependent on the context and the opportunity this provides. If we commence with one well developed system (such as an existing organisation) that is determining its long-term strategic vision, circumstances may exist where it is not feasible to develop multiple future contexts. At the other end of the spectrum, the concurrent development of multiple component entities (such as the integration of discoveries from distinct technology domains) where the endsate is unknown, we have multiple start points and potential end-states. In both cases the mapping to migration landscapes and intermediate states provides a basis for developing
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strategies for change that will be continually modified as new knowledge arises. The differentiating factor, then, becomes the determination of the appropriate levels of abstraction and fidelity to optimise the cost-benefit nexus.
6. Strategic planning maps Combining the elements of forecasting, backcasting and migration landscapes leads to the development of what can be defined as strategic planning maps for particular circumstances. As noted, they are dependent on the problem being considered. Indeed, it is possible that a number of layered concurrent maps would be necessary for a particular problem. For instance, within an organisation, there would be an overall strategic map in which the future visions and intermediate constructs are defined in very broad terms. In addition, it may be necessary to map out more focussed and detailed strategic maps whose significant outcomes would appear as decision points on a higher level map. This would allow particular users to design maps of the appropriate detail for particular users. These maps may be configured quite differently, some having single start and end points, other having multiple ones. Therefore, it is important to identify classes of these strategic maps. 6.1. One-to-one mapping The first class of strategic planning maps is one-to-one, that is, from a current singular state evolving into a future singular state. So while we project alternate futures, only one will be realised. Opportunity here, then, is related to influencing which future will evolve by using mechanisms to encourage the trajectory (or trajectories) that best align with the organisational goals. In many cases, the reality is that there is little opportunity to fundamentally change the direction. For instance, one cannot create an environment where there is an abundance of fossil fuels (although one might suggest one where there are bioalternatives). So, in such cases the goal is to preposition oneself to best realise opportunities while minimising threats. One example of this would be the development of future strategic contexts. For understanding future context and the evolution to them, techniques such as FAR have great utility in that they can provide insights into how situations might evolve, and the drivers for such evolution [3,4,5,16]. Significantly, analysis of what drives these transitions can provide operators with warning signals of likely changes in the environment and allow for proactive planning or at least the development of risk mitigation strategies. From this, plans can be developed to close the gap or at least manage the risk associated with it (operational). As such, it can provide a basis for determining the migration landscapes from the current state to the future one along with the key indicators as to the realisation of the desired future(s). 6.2. One-to-many mapping Another possibility is one-to-many mapping. In this case we have a singular entity with a desired end-state, but the opportunity to transform it in a number of ways. In this case,
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the strategic planning maps provide options from which an organisation can choose those that are preferable. Central to this choice would be the selection of those that are sufficiently close so that unforeseen variations pose only a limited problem. In addition, it means that the intermediate state or states are more flexible and responsive to change. An example of this might be for a broadly functional organisation that wishes to transform itself into a more focussed entity. In this case, they have many options to choose from and can select the path that meets their requirements. Of course, there are constraints. Indeed, the basis for identifying the requirements for any options is likely to be the possible contexts. Hence, one might employ a one-to-one strategic map to create an array of contexts from which those scenarios seen to be appropriate are derived. In this case, the options can be identified, developed and evaluated against such a backdrop. One useful application of the one-to-many strategic planning maps is organisational change within an evolving context. For instance, for an organisation that wishes to explore the development of new products, technology-based strategic maps have some utility. Certainly, to adapt to technology innovation, identifying and aggregating enabling technologies to produce a range of technological concepts is not enough. Determination of the viability of such concepts is essential. Therefore an understanding of the likelihood of the enabling technologies being realised, the timeframe within which this should occur and the critical elements on the pathway from our current knowledge to the fielding of a system articulated through the identified concepts all must be considered. One approach is to embed this technology migration landscape within the strategic planning map (other considerations such as the strength of the market place, the marketability of such technologies and competitive pressure are also necessary). This allows one to determine the direction of technological change in parallel to the development of future strategies and long-term visions. It also allows the opportunity to identify multiple trajectories for technological change and the associated indicators as time progresses. In addition, it provides an opportunity to consider revolutionary concepts (such as Quantum Computing) that might fundamentally change the operating environment, but are currently uncertain (both in terms of their realisation and associated timeframe). In such cases, the key indicators provide the mechanism for incorporating such technologies into strategic thinking by identifying the key milestones that must be achieved if these high-risk, high-payoff technologies are to be realised. 6.3. Many-to-many mapping Futures planning involving technology innovation would often take a many-to-many approach. That is to say, there may be many versions of what the current context is. For instance, some projected future technology concepts might be realised in different ways based on different beliefs on what particular technologies can do. In addition, there is often concurrent (although not necessarily competitive) research focussed on the development of products that would deliver the same functionality. For instance, the development of future computing power is concurrently following different streams; further enhancement of current chips (through further miniaturisation and energy efficiency), alternate chip designs (such as asynchronous chips), and alternate chip material properties (through lasing of Silicon), alternate chip types (using other materials such as boron-doped carbon),
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Fig. 2. Notional (simplified) strategic planning map for the army continuous modernisation process (taken from Ref. [6]).
alternate computing philosophies (chemical or quantum computers). One might also include developments in fields such as nanotechnology and biotechnology if the scope of the problem extended to possibilities for bio-computing. While each of these might deliver some unique capability (or not deliver at all), the options for the future computer are many and varied. As with the one-to-many mapping, there remains a need to identify the basic context, although this is likely to be less important as the concurrent developments would, in general, largely ameliorate shifts in context. However, in order to provide a basis for analysis, it is important to understand the context within which these technology concepts would be employed. As such, the determination of specific requirements for an array of options would serve the purpose. 6.4. Notional mapping—Army Continuous Modernisation It is instructive to give a pictorial representation of how a strategic map might look. Fig. 2 represents a way of viewing the progression to possible future force constructs based on contextual (e.g. technological) developments [6]. In this particular case, the army continuous modernisation process is considered. This, of course, is likely to be more simplified that a truly representative map, however, it does indicate the key points. Firstly, there are likely to be many possible future environments, within which particular scenarios are possible. These environments might range from dual competitive superpowers operating conventionally (e.g. Cold War), to a single superpower acting as the lead-global policeman to maintain stability (e.g. immediate post-cold war era), to conventional nation states being challenged by issue-based unconventional non-state actors (e.g. ‘War on Terrorism’). For each of these futures and associated scenarios, there is likely to be an optimal notional future Army (e.g. AAN). At the present time, we have the ‘Army in Being’4 and the challenge is to 4 In reality, we have the current Army plus those capabilities that are currently being procured and integrated into the Land Force. Therefore, the choice of starting point is probably the Army of 5 years hence.
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identify those strategies that will allow a transition to the future conceptual force that minimises risk, maximises functionality continually through the timeframe and is flexible enough to transition as new information occurs. As such we can both identify possible intermediate organisations (or in Australian Army parlance, OF’s), and the migration paths to achieve these. Importantly, there are a number of success indicators or events that will provide further information and assist in determining which path to pursue. Of course, we are not suggesting that all possible contingencies can be identified. However, we can use some analytical tools and techniques that can assist in recognising the trends, opportunities, threats and risks and integrate these. This, then, gives decision makers a level of insight beyond their current boundaries. Importantly, it forces them to think beyond the most likely projected future (which is often just an optimistic or pessimistic re-badging of the present to a future time). It requires them to plan against contingencies that are both possible and uncomfortable.
7. Conclusion Decision making is always an exercise in risk management. It is essentially about managing uncertainty in a structured, transparent and auditable way. Strategic planning provides decision makers with a basis for managing these issues by providing a mechanism to identify future goals and ways to achieve these. But there are always two competing agendas, namely where we desire to be in the future and what we can achieve with the resources we have. So the choice of approach is important. Backcasting and forecasting provide means for extrapolating from the present and towards an optimal future. However, much can be lost if these are not connected in some meaningful way. Therefore migration landscapes between these need to be articulated and analysed to identify those activities necessary for the realisation of a desired end-state. Such analysis might suggest that aiming towards a desired future may be high risk as slight changes in the environment in the interim may lead to the realisation of an undesirable future. In addition, if one is able to foresee important decision or events in advance, preparatory activities could be undertaken to better inform the decision maker as to the optimal path to pursue. Here we describe such a philosophy which links forecasting and backcasting through the development of strategic planning maps. We suggest these maps can be usefully employed to look at strategic contexts, organisational changes and technological innovation opportunities. These maps can have single or multiple starting points, depending on the circumstance of use, and can be embedded within one another to provide the appropriate level of fidelity to the problem. They also provide a basis for the identification of achievable intermediate states. These can provide a basis for determining the continued viability of an organisation during such a transition. We believe they provide the foresight, flexibility and transparency necessary for the realisation of opportunities within a futures strategic planning environment.
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