managing future expectations globally

In this paper, some of the most important results of the recent work of our Futures Observatory, the culmination of a decade of global research involving several thousand managers and professionals from large organisations, are explored in the context of the long-range planning undertaken by larger organisations, especially governments, which can positively influence their environments. A range of research techniques have been developed to allow them to identify possible futures and - where possible - to manipulate them.

The paper also includes a summary of the fundamental concepts underpinning the work and of the evidence which validates this.

The author is a senior lecturer in the Centre for Strategy and Policy, at the Open University Business School, of which he was the first Head. In addition to being the author of a number of books, including the MBA text-book 'Marketing' (in its second editions in both Europe and the US), he is Director of the Open University’s ‘Futures Observatory’. Sponsored by a number of multinationals, it is run jointly with The Strategic Planning Society of which he is chairman of the related special interest group. He has been advisor on long-range planning to a number of organisations and governments.

Particular thanks are due to Averil Horton, who worked as Research Fellow on the later stages, and to our co-sponsors - Barclays Bank, BT Laboratories, ICI and ICL - along with the Cellule Prospective in Jacques Santer's cabinet within the European Commission and the Scenario Processes Group at Shell Oil.

Much of our work to date (Mercer,1995a, 1995b, 1996b, 1997c, 1998d, 1999c) has focused on how smaller organisations can react to possible future developments in their environment. This paper, though, looks at the other end of the scale. It suggests how some of the larger and more powerful actors, especially multinationals and those in government, can proactively influence the environment itself. A prime objective of any such strategy is, having predicted the future outcomes which are likely to occur without any intervention, to positively influence these outcomes by adopting the optimal pattern of intervention.

As shown in our previous work, managers of smaller organisations may be able to achieve a degree of success in terms of the typically limited outcomes they are looking for. On the other hand, in recent years, managers of organisations actively participating in the wider macro-environment - larger organisations, most notably national governments, which are the subject of this paper - have been largely unsuccessful in their own parallel endeavours. One major reason for this lack of success has been the increasing uncertainty which has pervaded the macro-environment, resulting in their inability to predict the likely outcomes; with the consequence that intervention has been poorly executed. Indeed, as a matter of principle, they have increasingly avoided such intervention.

Accordingly, we look here at the more sophisticated level of forecasting which might be undertaken by such larger organisations, and in particular by governments, working on global scenarios. Even so, the origin of this more sophisticated package of techniques for larger organisations (including governments) lies in our work in developing simpler techniques for smaller organisations (Mercer, 1995a, 1995b). As part of this overall development work, we found an increasing need to develop more specific research techniques for identifying the key forces for change emerging in the external environment in general; techniques which are - accordingly - of equal interest to the larger organisations. As one result, we have been forced to develop new, formal research techniques which may be used for this purpose (Mercer, 1996a, 1998a Mercer et al, 1998). In this context, the process starts with a much larger number of scenario focus groups than would normally be used - typically more than ten and preferably up to twenty. The starting point for each of these is, though, much the same 'Wall-Post-It' group work. We have found, however, that the time limitations here prevent such ad-hoc global scenario groups from fully completing the later stages of the process in the one session for which they are typically available; since this usually cannot last longer than two hours. Thus, we specifically ask such groups only to derive 'scenario titles' separate from the drivers - though they are still influenced by the work they have done on them.

Even so, the great advantage of any scenario based approach is that it widens the view of the future - as we wished to do in this global research. Our experience has shown that other techniques (even including Delphi - Twiss, 1980) tend to narrow it, as part of their focusing on 'key issues'. As is hinted above, however, in our ‘global’ research - due to time pressures - the first two steps - detecting the 'drivers' - were undertaken exclusively by our participants and the last two - producing the scenarios - exclusively by our central staff. In the case of the step which links the two there was an overlap.

In 'global' research, therefore, the transformation into the final scenarios (and even the production of the overall 'mini-scenarios') is now undertaken by our central staff rather than the participants (Mercer, 1997d). The prime input to this process is all the drivers identified, from all the groups involved, and these are progressively clustered - by our central staff - into aggregated 'mini-scenarios'; regardless of how they have originally been clustered by the groups. In this respect, we still closely follow the stages of the 'traditional' process. This overall clustering is, however, then compared (cross-checked) with the separate work of the groups - to ensure that it is still meaningful in broad terms. This has generally proved to be the case. It is our experience that there is, in any event, some considerable convergence between the results of most of the groups.

These combined mini-scenarios are then transformed, again following the traditional approach, into the final scenarios. In view of the very broad scope of the investigation, covering the whole of society, it has though proved necessary to utilise four scenarios - rather than the two we would normally recommend for our more conventional work with smaller organisations. These are again compared with those suggested by the groups, and once more we have found no major disagreements between them in our research.

So far, the qualitative (focus group) technique(s) described have been assumed to be the same as those applying to just one group of eight participants. However, in this more sophisticated approach, the database now includes the results of a number of such groups and we can proceed further by aggregating these. This is needed to provide significant numbers of participants. Even at this qualitative stage of the overall research, we need them to ensure that all the important drivers - the dimensions to be quantified in subsequent stages - have been identified. As there may be more than a hundred such drivers to be identified, if the research is to be genuinely to be ‘global’, it may be necessary to run ten or more groups, so that multiple occurrences of each of these significant drivers may be observed. Otherwise, one cannot be confident that the single occurrences (emerging from a smaller number of groups) may not just represent one individual’s idiosyncrasies.

On the other hand, one group of factors which has traditionally caused problems for researchers (Rockfellow, 1994) are those ‘wild cards’ which surprise everyone. According to strict theory, these ‘wild cards’ must be completely unpredictable (or at least of low predictability) as well as of high impact; and, hence, these might cause problems of detection even for those using the techniques described here. There is, though, one important sub-category of such wild cards: those involving slow hidden processes, which are present over long periods but suddenly emerge (as ‘creeping catastrophes’ - Steinmuller, 1996). One outcome of our new approach is that this category - which in practice accounts for a large proportion of 'wild cards' overall - may be detected by the technique(s) described here; as long as sufficient numbers of participants are involved. Essentially, in this context, researchers should look for two or more occurrences which surprise them; the opposite extreme to the more normal focus group process of reduction to the key factors. They need to find two such occurrences because our observation is that it is otherwise almost certain that they will reject the factor as unbelievable!

In our global work even these internal tests for consistency are supplemented by a comparison with the published work of a wide range of other futurists. Here too, though, we have found a surprising degree of convergence; indeed of agreement. Though the nature of future developments is often seen to be a controversial issue, one result from our research was that, at least amongst those studying the long-term future, there is a significant degree of unanimity; a workable consensus. Indeed, one major aspect of our results turned out to be a surprising degree of convergence between the outcomes reported by almost all the various groups - ranging from uninformed generalists to informed futurists - in contradiction to the supposed uncertainty reported by the media. It is this convergence, at all stages indeed, which we believe goes a long way to underwriting the viability of our qualitative techniques.

The techniques progressively 'emerged' from different stages of the previous Millennium Project. In particular, the simplified methods of scenario forecasting, initially developed for use with our students (Mercer, 1995a), were worked up into the specific ‘focus group’ approach during workshop sessions with these students. The key theoretical underlying assumptions behind all the stages of the research, however, are derived from our hypothesis of ‘Aggregated Expectations’ (Mercer, 1997a, 1998a). This clearly has its indirect origins in the, macro-economic, ‘rational expectations hypothesis’ (Lucas, 1973). In its present form, however, it directly results from extended observations of the workings of the scenario focus groups which provide the basis for the qualitative research overall. Whilst the individual members of these groups freely discussed their own wishes for future developments, and the philosophies behind them, they readily accepted that the actual outcomes would be decided by the wider world. Accordingly, they - as members of the groups - universally based their ‘predictions’ upon their expectations as to what the population as a whole would decide; as the hypothesis states. Even so, their expectations were arrived at subjectively; and did not result from rational economic calculations - as the ‘rational expectations hypothesis’ would suggest (Svensson,1996).

Accordingly, the core concept behind all our approaches, towards corporate strategy as well as those relating to global scenarios which we are about to examine, is that spelled out by our Hypothesis of Aggregated Expectations. Taking the concept further (Mercer, 1997a), and applying it in a more general sense, our evidence is that much of society now looks to such 'expectations' - to set the context for what will actually happen in the future. These expectations are the outcomes which they are persuaded will inevitably happen given certain inputs. Our basic assumption, therefore, is that if enough people put their weight behind the same 'expectations', and the inputs are observed to happen, they will adjust their behaviour to take account of what is expected; and, accordingly, the expected outcomes will occur! This process might even be described as 'self-fulfilling expectations'.

Overall, then, all our research has set out to describe the future which will come about as a result of current expectations (Mercer, 1997a, 1997d). It is based, in the first instance, upon three broad assumptions which have only become viable in recent years:

1 - The future of humanity, in the developed nations at least, is no longer generally constrained by significant shortages of resource.

This is still a controversial assumption, where much of the developing world suffers from severe shortages and even in the developed world bottlenecks can result in local shortages, but - as may be seen from the detailed findings of our research reported elsewhere (Mercer, 1996d, 1996e, 1996f, 1996g, 1997b, 1998f, 1999a) - it has now become a justified one for much of the activity taking place in the economically more advanced countries.

Thus, the physical resources available to mankind are still growing faster than the demands being made on them - with oil reserves, for instance, now reaching the historically high level of half a century - even though uneven distribution of these resources may yet cause problems (Mercer, 1998b). More important, the new requirements arising from the coming ‘knowledge society’ make very limited demands upon physical resources. Indeed, the basic economic ‘law of diminishing returns’ is now being reversed; knowledge becomes more valuable the more it is used!

2 - Accordingly, that future is now being progressively determined by social decisions, taken not just by a few leaders but by millions of their citizens, taking billions of small decisions as part of their daily lives.

Thus, to a large extent our lives are no longer necessarily ruled only by the inflexible logic of the economics of scarcity or the dictates of political ideology, but are more typically decided by our own actions and those of millions of our fellows.

3 - The general, longer-term, framework within which these specific, individual decisions is taken is largely provided by the individuals' expectations of what the future holds for them.

Every man, and woman, has free will, and now has the power to express this; he or she will ultimately make their own decision. But a major influence on that decision - and often the most important influence - is what they expect the future to be, and hence how it will generally determine the ultimate outcome of their own small decision.

In the specific context of this research, this naturally leads to the most important assumption:

4 - If you can measure these 'expectations' as to future developments, to a large extent you can establish the most likely form of that future.

Even if you can just determine the expectations of the opinion-leaders, as our own research does, you can still gauge, with some degree of accuracy, the major elements currently shaping the future.

The hypothesis is best introduced in terms of a simple example, detailed in the appendix, which parallels some of the earliest work on rational expectations but comes to a rather different conclusion.

The output from our qualitative focus group research is typically used to determine the questions for subsequent quantitative research (Wells, 1974). As the requirement for quantifying our futures research was very similar, we chose this approach - in preference to Repertory (Kelly) Grids (Sampson, 1986) - because of the large number of dimensions involved. Thus, the results of this qualitative research were used to identify the 162 dimensions, the most likely factors (drivers) for change, to be explored in the subsequent quantitative research.

For the quantification stage we use rather more traditional marketing research techniques, albeit once more on a larger scale;

We have used senior managers, and professionals, in our work primarily because we - unusually - have relatively easy access to them. On the other hand, we also assume that, in terms of the macro-environment, they have significantly greater leverage than ordinary members of the wider population. For example, even in our initial mail-survey the sample comprised 300 students studying the OUBS course (‘The Challenge of the External Environment’); which examined the long-term developments in the organisational environment. Though the sample should be formally described as a ‘convenience’ sample, we have found (Mercer, 1996c, 1996b) that - due to the large numbers of students and the generally representative nature of the organisations from which they came - their responses typically give a sound guide to those of the overall population of such managers.

Each of the factors (questions) was presented in terms of three semantic differentials (Osgood, 1957). Thus, apart from a limited number of general ‘demographic’ questions, the questionnaire comprised only the 162 questions - one for each of the factors, key events, identified in the qualitative stages of the research. For each of these factors three pieces of information were requested:

The participants were asked whether the event was likely (defined as greater than 50%), between 10% and 50% likely, and less than 10% likely.

For those events which were likely the respondents are asked to choose from a range of likely dates (2000, 2010, 2020, 2030, 2050+) the one they thought most likely.

For each factor they are asked to rate its importance, to their organisation, in terms of a seven point (1 to 7, very important) semantic differential.

Although the result may look like an early stage of a conventional Delphi study (Twiss, 1980), and might even be used as such, the dimensions in this case are already derived from the wider population rather than being in the process of being sought from expert opinion.

Despite the complexity of the questionnaire it proved viable; so 160 responses (53%) were received from our initial survey - in line with our normal response rate - even though the questionnaire was relatively long and complex for a mail survey. Less than ten percent of these were completed incorrectly.

In order to test the validity of these initial results, identical samples of students were surveyed, using identical questionnaires, for each of the next two years. In terms of the overall results of these follow-up surveys there was a remarkable degree of stability; with those for both 'importance' and 'probability' diverging by less than 2%; as can be seen from Table I below. Indeed, the only individual issues which diverged by more than 10% on either of these scales were those which were extensively discussed in the media over the period; 'moon colonies', 'chips in the brain' and 'the rapid growth of the EU'. Only in terms of dates was there any systematic divergence, with the overall average growing from 2024 to 2033 (at three times the actual rate); though even here the individual issues did not typically show any greater divergence than this.

In addition, to test the responses of a different audience, a sub-set of 48 dimensions/issues was tested on a wider sample of (500) respondents to a survey amongst MBA alumni; the questionnaire for which also covered a number of more detailed questions, including those on the use of long-range planning quoted at the beginning of this paper. In this case, as can be seen from Table 1 above, the importance and date results were again remarkably stable; lying within 3% of the overall figure in the case of 'importance' and within the longitudinal range of results for 'dates'. Comparison of 'probability' was not possible as the basis for measurement had changed - to allow use of a more conservative semantic differential scale.

Although all these - longitudinal and horizontal - results are still based upon relatively specialised samples, albeit mainly senior managers and planners typically operating in the field of strategy, the degree of stability seen to exist across them suggests that the overall process may well be stable, and reflect a meaningful convergence of results.

The quantified results from the initial survey suggested that further development required that, paradoxically, we revert to the previous stage! Thus, as already stated, the earlier - ‘qualitative’ - stage of the work involved a much larger number of participants than conventional equivalents. Accordingly, although it must still be strictly judged as qualitative research, it proved possible to indirectly compare the results of this with the later quantified work; at least in broad outline. In this context, the key differences between the two can be summarised in terms of :

- the (quantified) individuals are asked to reply, more conservatively, in terms of the future of their own organisation, where the (qualitative) groups are asked to consider the future of the world as a whole.

- the individuals are asked to report their own views, while the groups are asked to agree possible futures.

In addition, it is likely that the dynamics of group work - following the reported patterns experienced in more conventional focus groups - open out the overall horizons, so that the individual ideas are debated in a generally supportive climate - where this group support allows the participants to consider ideas which are rejected (presumably as unrealistic) by the individuals.

For the purposes of comparison, the ‘qualitative’ results were therefore ‘quantified’ by two measures. The first was the number of groups reporting a specific reference to the topic in their list of drivers. This was derived from a total of 16 groups completing all stages of their work, in the initial phases of the project. The second was the total number of such mentions, where a topic might be considered sufficiently important for different aspects to be reported separately.

In many areas the two sets of results were comparable (Mercer, 1998f). For instance, employment was included by 12 groups (with 38 mentions) compared with an importance rating of 5.3 (and a probability of 76%), and global warming was included by 11 groups (with 20 mentions) against an importance rating of 6.0 (and a probability of 80%). There were, though, areas where the two diverged markedly. Thus, in terms of apparent differences in perceived levels of importance, 11 groups included space travel, with 26 mentions, but this was given only a 3.4 importance rating by the individuals; though it did have a probability of 70%. These divergences seemed to result from systematic underestimates by the individuals in certain areas. They seem to be less inclined to see the importance of (and likelihood of) events which involve changes in the structures of society, or those that are remote from them (or their organisation).

The comparison of the quantified results with the earlier quantitative ones is important, in that it adds an extra dimension to the results. Thus, the quantified results measure, with greater statistical accuracy, the current position of the individual expectations. On the other hand, we believe that the qualitative (focus group) results better indicate what future changes in these positions might be likely.

Accordingly, to ‘map the future’ - which is the overall aim of the process - both aspects need to be taken into consideration; the quantitative results to plot the current position and the qualitative ones to indicate the direction in which changes may occur; or may be made to occur - remembering that one key function of such a map is to allow governments to decide where they can make such changes.

One specific, remaining limitation of all the techniques described is a failure of the ordinary participants to highlight structural changes occurring in the macro-environment. This is partly because the techniques typically tend to be most effective in aggregating large numbers of ‘small’ expectations. But it is mainly because most Western managers are ‘culturally blind’ to many of the structural changes which occur across society as a whole. One group of Third World participants who had a Marxist background, for instance, did detect such structural factors.

The result is that the central staff, aggregating the drivers into the final scenarios, must themselves detect where the issues reported are symptoms of underlying structures. In practice this proves less problematic, than might be expected; where the academic researchers, involved in our work to date, are motivated to find such structural trends.

Once more, it is difficult to quantify these, but in general these structural changes (once detected) typically fall into the ' certain ' category.

The full results, have been described elsewhere (Mercer, 1998f) but, in the context of this discussion, the main point to be noted was the stability of the outcomes:

For example, in examining the sub-set of the most critical 48 issues, as judged in the horizontal survey, we found that there was still quite a wide spread of levels of importance, down from 6.3 (on a scale from 1 to 7), understandably recorded by a ‘global water shortage’, to 3.2, for a 'moon colony'. Not unexpectedly, the events judged to be the most important are those which would have the most direct impact on the whole of humanity; including ‘global warming' (6.0), 'severe environmental laws' (5.7) and a 'global financial crash' (5.6) and accordingly must be considered as the greatest threats. On the other hand, the order of these remained unchanged over the three years surveyed. When compared with the results from the horizontal extension, there were differences in detail but the overall pattern was still much the same. For instance, seven of the top eight issues were the same between the two surveys. The results, therefore, showed considerable stability, on all fronts, for the processes overall.

A similar level of stability was also observed in terms of probabilities and dates.

The overall project involved the development of two new sets of qualitative research techniques. ‘Simpler scenarios’, allows this approach to be used as a framework for more general research and ‘self-documenting focus groups’, enables a large number of dimensions to be generated; as input to the subsequent quantitative research which uses well-tried techniques (based on semantic differentials). These results may then be compared with those obtained from the qualitative stages; to map both the current position and the likely direction of change. As initially evidenced by the observed convergence of results, the combination allows the expectations of a large population to be investigated - and, thus, future outcomes to be more accurately predicted.

How, then, may the hypothesis of aggregated expectations be put into practical use, at the more sophisticated level demanded by larger organisations? In essence, this process involves three stages:

1. observation/measurement of existing expectations - the starting point must be an understanding of what the population's existing expectations are; and, hence, what will happen if no intervention occurs. Without knowing where you are, and in what direction you are currently going, it is impossible to steer a course to the destination you want. The new techniques, reported earlier, allow this information to be obtained. The emphasis upon observing (measuring) the population’s expectations - by various forms of marketing research - rather than predicting them from mathematical models - is central to the practical use of the hypothesis in this context.

2. decision on the possibility of intervention - the next, key, step is to decide whether any intervention - to change the outcomes - might be feasible. This formalises the recent recognition that governments are not all powerful, but may only be successful in certain classes of action. This basic decision, whether or not to act, leads naturally to two types of subsequent activity. At one extreme, therefore, the expectations may be so firmly held, or the tools for changing them so weak, that it would be unrealistic to expect the outcomes to change. In this case the third step, where intervention simply is not possible, becomes:

3a actions to ameliorate the outcomes - actions are then taken not to change the outcomes, but to alleviate - or intensify (if positive) - the symptoms arising from the inevitable outcomes. Damage limitation may then offer the most practical route.

On the other hand, if it appears possible to modify the expectations, such that more beneficial outcomes will be achieved:

3b modification of expectations - the various tools, including those of marketing but also those of persuasive modelling, can then be deployed to steer expectations in the desired direction. Conviction marketing techniques (MERCER, 1999b) are then likely to become the methods of choice.

The result of our recent work for those larger organisations which can positively influence their environments, covers a range from research into basic theory to development of new leading-edge strategic approaches. Thus, a range of research techniques have been developed to allow them to identify possible futures and - where possible - to manipulate them.

The validity of these new approaches is supported by the stability of the results using different samples, longitudinal as well as horizontal, and different measures. It is also underwritten by the successful exposure of the detailed results over the past three years, to a wide range of different audiences, as indicated in the references which follow.

1. How confident are you about the accuracy of long term predictions? How might the techniques described in this paper help improve their accuracy?

To help explain the theoretical underpinnings of this, let us take the example of one individual who is asked to contract for the supply of a repeat purchase good at some time in the future. This example is chosen since it offers a more realistic example of price-setting than market-clearing by some form of auction (to an informed public) which is the starting point for much of neo-classical economics. Here, there need be no direct balance of supply against demand, and bounded rationality is implicit in the process. Hence, one key reason for the divergence from classic rational expectations, even if wage or price stickiness is allowed for..

There have been many practical mechanisms suggested by marketing academics to describe how this is achieved in practice; ranging from historical, through cost-plus, to competitive pricing. Even so, it is arguable that the analogue of the economic 'market price' still enters into the equation in the shape of the expectations of the supplier, and of the purchaser, as to what will be - on the date of future supply - the generally prevailing price which they will be required to meet. As this is a repeat-purchased good, as indeed are most consumer goods, the price can be assumed to be based upon the currently applying price modified by an allowance for the expected inflation over the period in question.

Where Pf = Future Price, Pc = Current Price, Ie = Average Expected Inflation, and

Isymbol 100 \f "Symbol" \s 10 = Individual Deviation from the Average (Expected) Inflation.

This compares, for instance, with the rather more complex form of even the ‘simple’ representation of the rational expectations hypothesis given by Bill Gerrard [Beyond Rational Expectations: A Constructive Interpretation of Keynes’s Analysis of Behaviour Under Uncertainty, The Economic Journal, 4 (March), 327-337 (1994)];

_t-1 X^e_t=E(X_t|Ω_t-1)

where _t-1 X^e_tis the rational expectation formed in period t-1 of the variable, X, in period t and E(X_t|Ω_t-1) is the mathematical expectation of X_t conditional on the information set Ω_t-1 available in period t-1 (where the whole is characterised by unbiasedness and orthogonality)

The last term in our own equation allows for the fact that the individual’s information is bounded, and their interpretation of it may not be as rational as many economists’ would wish. If, however, we aggregate a sufficient number of such individual decisions the resulting new aggregate price is:

As suggested earlier, it may then be reasonably assumed that the individual deviations are effectively random and will sum to zero - indeed that is, by definition, the case for the average price. This is a key feature of the generalised hypothesis, as it is for the rational expectations hypothesis, hence the emphasis on aggregation. The resulting new ‘market price’ average (Pa) therefore will be:

It is, thus, possible to focus on the overall, average, expectations (of the total population) as to what inflation will be - and this becomes a self-fulfilling (prophetic) expectation.

Lucas, R.E, (1973) Some International Evidence on Output-Inflation Trade-Off, American Economic Review, Vol. 63, pp 326-334

Mercer, D, (1995a) Scenarios Made Easy, Long Range Planning, Vol. 28 No. 4, pp 81-86

Mercer, D, (1995b) Simpler Scenarios, Management Decision, Vol. 33 No 4, pp 32-40

Mercer, D, (1996a) A New Qualitative Technique for Exploring the Future, Marketing Education Group (MEG), August

Mercer, D, (1996b) Industry Scenarios - Short Termism Revealed, Industrial Management and Data Systems, Vol. 96 No. 8, pp 23-27

Mercer, D, (1996c) Marketing Practices in the 1990s, Journal of Targeting, Measurement and Analysis for Marketing, Vol. 5 No. 2, pp 175-181

Mercer, D, (1996d) Predictable Futures - The Drivers for Change, Beyond 2000, Challenges for Futures Research - Report of the International Sommerkademie des Secretariats für Zukunftsforschung, pp 149-158

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Mercer, D, (1997c) Robust Strategies in a Day, Management Decision, Vol. 35 No. 3, pp 219-223

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Mercer, D, (1999b) Marketing; the Encyclopaedic Dictionary, Basil Blackwell, Oxford

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Rockfellow, John D, (1994) Wild Cards: Preparing for the Big One, The Futurist, Jan-Feb

Sampson, P, (1986) Qualitative Research and Motivation Research, Consumer Market Research Handbook (3rd. ed.), ed R. Worcester and J. Downham, McGraw-Hill, New York

Steinmuller, K, (1996) The Future as a Wild Card - Towards a Methodology of the Unpredictable, Beyond 2000, Challenges for Futures Research - Report of the International Sommerkademie des Secretariats für Zukunftsforschung, pp 98-104

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Wells, W. D, (1974) Group Interviewing, Handbook of Marketing Research (ed. Robert Ferber), McGraw-Hill, New York

Table I: Average (48 issue sub-set)	1996	1997	1998	% change 1998/1996	1998 (alumni)	% difference 1998 alumni vs. students
IMPORTANCE (scale 1-7)	4.9	4.9	4.9	1.8%	4.8	-3.0%
PROBABILITY	57.0%	56.8%	57.6%	1.3%	n.a.	n.a.
LIKELY DATE	2024	2026	2033	0.5%	2025	-0.4%