ProFutures Blog

The APF Profutures blog features posts by the Emerging Fellows and other APF futurists. We will be sharing intriguing futures ideas and information about professional futurists and the practice of strategic foresight.

You can learn more about the Emerging Fellowship and the selected Fellows on the Emerging Fellows page. Please direct your questions to Terry Collins

Your comments are welcome, so long as they are courteous, brief, and on topic. 
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  • 20 May 2015 1:26 PM | Anonymous member (Administrator)

    Future Shock for Futurists

    By Jason Swanson, APF Emerging Fellow

    Roughly this time last year, Ben Wittes of the Brookings Institute wrote about what he called the “Intelligence Legitimacy Paradox. ” Wittes argued, “…the threat environment America faces is growing ever more complicated and multifaceted, and the ability to meet it is growing ever-more-deeply dependent on first-rate intelligence. Yet at precisely the same time, the public has grown deeply anxious about our intelligence authorities and our intelligence community is facing a profound crisis of legitimacy over its basic authorities to collect.”

    Witte’s explanation for this paradox is technology. Technology has allowed for weak nations and non-state actors to play “in the big leagues of if international power politics”.  As technology is helping to contribute to the USA’s threat matrix, “…technological change is also the fundamental reason for the intelligence legitimacy crisis. The more ubiquitously communications technology spreads and the more integrated it all becomes globally, after all, the more that surveillance of the bad guys—in all their complexity—requires the intelligence community to surveil systems that we all use every day too. In other words, the same technologies that are making the threat picture more complicated, more diverse, and more bewildering are also bringing the intelligence process into closer day-to-day contact with people living their daily lives. These technologies also require intelligence agencies, to be effective, to touch giant volumes of material, most of which is utterly anodyne. The more the community does these things, as it must, the more people it offends and the more legitimacy problems it creates for itself.”

    As a Futurist, I find the “Intelligence Legitimacy Paradox” fascinating.  Technological advances have made for an increasingly complicated threat matrix, yet at the same time gives our security agencies the tools to mine for first-rate intelligence. Leaving aside the issues surrounding the authority to collect data and information, I wonder if technological acceleration might one day create a paradox or dilemma for the futures field?

    As mentioned above, Witte’s explanation for the paradox was technology, but to be more accurate the core of Wittes’ idea might be better defined as technological acceleration. With more and more data being generated and shared, agencies must sift through vast piles of information to find first-rate intelligence, scanning more broadly, probing more deeply, and coming closer in contact with those creating and sharing the data than ever before. As technological change continues to accelerate, the amount of data we generate will continue to grow. In 2015, we are expected to create and share eight zettabytes of information. How much is a zettabyte? 1 zettabyte = 1 trillion gigabytes. And that amount will rise, along with the ease of sharing the data that we create. As technology accelerates, Witte’s “Intelligence Legitimacy Paradox” might be even more pressing in the future, with more and more data being generated, an ever more complicated and evolving threat window,  closer touch points with data creators, and a greater need for quality data in the ever-expanding sea of information.



    So where might this leave the futures field? To be clear, the majority of us are not dealing with a security risks or impending violence, rather we see more complex and rapid changes to the present, a more complicated and multifaceted threat matrix to present or current reality by way of rapidly approaching futures. Much like the intelligence community, our field must also contend with technology acceleration. As researchers, we put a premium on quality information, or what Witte calls “first-rate intelligence.”  If the information we use for our work is less that quality, we can assume the output also to be less than quality, or to borrow a phrase,” garbage in, garbage out”.

    As more and more data is created and shared there is an issue of quantity versus quality that any researcher must contend with. For Futurists, in particular, this has the potential to be a blessing and a curse. With the acceleration of data generation, we are able to use increasingly rich streams of information to gain insights and generate images of the future. Beyond trends and drivers of change, these data streams also put us in touch with novel ideas and other signals. With more data being generated and shared over time, we might expect to come in contact with greater numbers of novel ideas and signals. This is where I see a potential issue. While not quite a paradox such as the “Intelligence Legitimacy Paradox”, the issue I see arising might be called something to the effect of “Future Shock for Futurists”. This is where the accelerating change of technology, specifically the increase in the amount of data being generated and shared exponentially increases over time, combined with accelerating social change, create an issue in which novel ideas and signals are no longer novel but commonplace, or in instances where they are novel, the shelf life of these ideas are extremely short, creating the potential for an echo chamber of sorts within the field.  What happens to our signals and signposts if they move from novel to accepted idea in a matter of weeks rather than years? Would that affect your practice?


    Longer term the issue of increased data creation may be solved as data analytics such as R become easier to use so that we might make sense of  this growing sea of information. It stands to reason that web analytics will also provide increased brokering and curation services for information delivery in the form of a stronger filter bubble. Nearer term we might continue to use primary research, social networks (being mindful of our own filter bubbles there!) and other tools to ride the growing wave of data, being mindful of the rate at which ideas move from the seemingly crazy person rambling to accepted social fact.

    How has increased data generation affected your practice? Do you see a downside to the increased creation and sharing of data? How might the hyper acceleration of ideas, where an idea might move from novel conception to mainstream inception affect the filed?

    --------------------------------------------------------------------------------

    http://www.lawfareblog.com/2014/05/the-intelligence-legitimacy-paradox/

    http://www.informationlifecyclemanagement.net/collateral/analyst-reports/idc-extracting-value-from-chaos-ar.pdf

    http://www.bloomberg.com/graphics/2015-pace-of-social-change/

    http://www.r-project.org/



  • 11 May 2015 12:11 PM | Julian Valkieser (Administrator)

    My past articles were more and more related to Big Data and Foresight. In this article I want to demonstrate the concept of High Reliability Organizations (HRO).


    The world is a very complex system. That’s no question. You can’t understand it as a whole. It is impossible. But on macro level, some organizations and companies try to make complexity highly reliable by preparing for the unexpected as much as possible. I was fascinated by this idea and the underlying approach. I believe that you can submit projects with better risk management. Conversely, the procedure of HROs would be exciting for Foresight.


    Let me introduce the definition of an HRO, which states that those organizations have a particular behavior regulation and organizational structure. It is characterized to operate at a high percentage of reliability, despite the fact that these organizations act continuously under changing or difficult conditions. Statistically, one would expect a much higher error rate compared to traditional organizations.


    HROs are usually structured very complex. When you think of a hospital or an aircraft carrier, there are diverse professional groups in many hierarchies and groupings. If a patient comes to a hospital, he meets doctors, nurses, medical technicians, traditional technicians, employees of the service or management, and certainly more people who contribute in any manner to the smooth workflow in the hospital.


    Accompanied by complex team constellations, clear structures and hierarchies are needed. We know it, especially from the military, and here in accordance with aircraft carriers in the extremes. Where responsibilities prevail and decisions must be made ​​in short periods of time, it requires a clear and transparent decision-making process.


    One of the essential characteristics of a HRO


    Sensitivity for operational processes:  The personal sensitivity to the patient and the colleagues is more important than the pure control of data, such as patient records, prescribed medications or recorded data to physical circumstances. Environmental information must also be made ​​available. So you can see new developments that need to be noticed also. But how to get information that have an impact on a particular situation. Environmental factors can be seen, among other things under the description of a "Vuja De".


    A Vuja De would be a realization of a previously known routine, you didn’t have before. You were sensitive to this factor in the routine situation and discovered an anomaly, which is previously not noticed. (Sutton, 2001) This observation and a possible recommendation should be added to a manual or guideline to improve knowledge management and the common experience. Additionally, it is also an element of an HRO to adapt policies, practices and specifications constantly.


    I'm very interested in the concept of Vuja De and I do not want to see it only as a buzzword, even though it describes what we already applies to many Foresight methods. In my mind, have a look inside HROs and their circumstances, you will certainly derive new insights for Foresight methods from short-term methods like them used in HROs.


    Sources:


    Sutton, R. I. (2001): Weird Ideas That Work: 11 ½ Practices for Promoting, Managing, and Sustaining Innovation.


    About the author:


    Julian Valkieser finalized his study with the thesis on "evaluation criteria for innovation projects in the early stages". Parallel to this, his last engagement was in the Corporate Foresight Department of Evonik Industries AG. Now, he is a product manager at a german local based website.

  • 07 May 2015 9:44 AM | Sandra Geitz (Administrator)


    The Past, the Future, the Pasture, Michael Leunig

    This penultimate APF post ponders our habits of thinking and doing, and whether we can open ourselves to see and act on potential futures. 


    What enables and what inhibits us to think of possible futures?

    What if thinking seems freely imagined by the young. So what happens to our early abilities as we mature? Is it that we develop habits and rules of thumb to contain the complexity of our lives? Habits help us deal with overwhelming choices and pathways. Is that we notice that particular strategies work more often? More successes, and less embarassments or failures are the result of sticking within certain rules and habits? Does training and schooling further embed our proven methods and shortcuts? We keep within these deep grooves of thinking and doing, often unable to imagine other or better ways of thinking and doing.


    How to think and do with time and experience?

    The diagram attempts to distil my own experiences and learnings, using abduction for problem-solving, designs and intuitive insights, using science of induction or probabilistic inferences, as well as deduction and intuitive judgement via experience. It also is based on Ackoff’s (1989) knowledge hierarchy from specific data, information, knowledge, to the wisdom of the universal. And, it includes and visualises concepts of design thinking versus science by Roger Martin (2007) and Doerfler and Ackermann’s (2012) intuition studies. Abductive, Inductive and Deductive thinking, adapted from Ackoff (1989), Martin (2007) and Doerfler and Ackermann (2012). 



    Abductive, Inductive and Deductive thinking, adapted from Ackoff (1989), Martin (2007) and Doerfler and Ackermann (2012)


    When I’m open and curious, fearless and playful, I recognise I’m more likely to use abductive thinking. This involves deeply noticing and observing phenomena, pondering what if and what might be, to generate potential or preferred futures. It is seeing new patterns and connections through those vast reams of data. This mode of thinking and doing aligns with problem solving within uncertainty and design thinking. It envisions a potential known outcome, and explores various pathways of what and how we may arrive at this future state.

    Very rarely, in situations where I know many inputs what and their outcomes, I may use induction to infer how they relate together. At first this thinking appears similar to abduction, but it needs large samples and probabilistic conditions to infer the how. From my experience, it is easy to develop the wrong theory, as data is rarely valid for probability,.

    Most often, in known environments, I’ll choose deduction to reach the desired outcome using known inputs what and methods how. This thinking generates predictable outcomes from known approaches. It just works (most of the time). I use this thinking so often, it becomes automatic habit or intuitive. In areas of considerable experience, I’m so confident I just know the outcome looks right or not. Intuitive judgement of experience.


    So what, if we judge with time and experience?

    The visual provides the clue.  Deduction works when environmental conditions are stable and known, if connections between inputs and their outcomes are known and predictable. Deduction is established and validated in practise over the years from theories of induction if there is a stable environment/

    And if the environment becomes turbulent or uncertain? Then, what if thinking becomes the best approach. Trouble is, it is directly opposite to intuitive judgement by experience. It requires us to put aside our wisdom and experience that worked in our pasts. We need to delve into data and emerging details, to become curious and child-like, exploring unknowns and novelty. Deeply uncomfortable, yet essential practise.


    References: 

    Ackoff, Russell. (1989). From data to wisdom, Journal of Applied Systems Analysis,16(1), 3-9.

    Doerfler, Viktor & Ackermann, Fran. (2012). Understanding intuition: The case for two forms of intuition, Management Learning, 43(5) 545-564. Retrieved December 20, 2014 from http://mlq.sagepub.com/content/43/5/545

    Martin, Roger. (2007). The nature of the schism between the design view of business & the business view of design, SMMRSD. Retrieved March 21, 2015 from  http://summarised.co.za/


  • 20 Apr 2015 3:34 AM | Anonymous member (Administrator)

    Written by: Alireza Hejazi, APF Emerging Fellow

    Reviewing a number of published works, I concluded that the futurists’ roles can be generally defined based on a continuum that stretches from a point of leadership to a point of innovation. Many functions, competencies and responsibilities might be considered on this continuum, but there are six key roles that can be attributed to futurists. First, three roles are described from the point of leadership and then three other roles are reviewed from the point of innovation in this post.

    In my view, the futurists are primarily leaders. This is why I changed the direction of my studies down the road of strategic foresight at MA level in 2012 and took up the leadership road at PhD level in 2013. I look at foresight from a leadership perspective, and this convinces me to consider Mumford, Campion and Morgeson’s (2007) strataplex of leadership skills as a good basis for classifying futurists’ roles. Therefore, I can regard a futurist as an analyst, a manager, or a consultant in the first place. 

    Second, I think that foresight is aimed at serving the objective of facilitating or improving innovation at the corporate level. Consequently, Rohrbeck’s (2011) taxonomy of initiator, strategist, and opponent can be considered as one of the best classifications that have been proposed to this date. I will make an attempt to describe each role briefly in this post based on two of the above mentioned resources.

        

    Futurist as analyst

    An analyst is the person who applies foresight tools and methodologies in his or her activities, someone who is competent in scanning, trend analysis, and basic forecasting. An analyst is not laboring under the influence of others’ ideas. Instead, he or she studies those ideas and proposed the best way of applying them in favor of individual, national and international benefits. The analyst produces information for the second role, the manager.

    Futurist as manager

    A futurist manager is usually a foresight project manager who supervises the foresight processes at the corporate level. He or she facilitates projects and generates intelligence from foresight methods and outputs. A futurist manager is a self-disciplined individual capable of creating change, managing uncertainty, coordinating a range of foresight activities, applying alternative futures and transforming to better futures.

    Futurist as consultant

    A futurist consultant is a strategic leader who works with executives to facilitate change based initiatives on the base of insights resulted from foresight processes. He or she may be known as a senior executive, a director, or creator of foresight initiatives. A futurist consultant possesses good teaming and collaboration competencies, practices problem-solving foresight and welcomes transformational challenges.

    Futurist as initiator

    Foresight activates innovation by identifying new customer needs, technologies, and product concepts of competitors at the corporate level. A futurist initiator analyzes cultural shifts and collects the needs of lead customers. He or she scans the science and technology environment to identify new emerging technologies. At a higher level, a futurist initiator identifies new competitors’ concepts by monitoring the activities of the competitors.

    Futurist as strategist 

    Foresight directs innovation activities by creating a vision, providing strategic guidance, consolidating opinions, assessing and repositioning innovation portfolios, and identifying the new business models of competitors. A futurist strategist develops well-informed future-oriented strategies that lead innovation on desirable effective paths.

    Futurists as opponent 

    Foresight challenges the innovators to create better and more successful innovations by challenging basic assumptions, challenging the state-of-the-art of current R & D projects, and scanning for disruptions that could endanger current and future innovations. A futurist opponent not only challenges innovative ideas and assumptions, but proposes tweaks and re-adjustments that can improve innovation in various ways. 

    It should be noted that foresight is a cross-functional profession, and a futurist may play two or some of these roles simultaneously based on the nature of enterprise he or she serves. Another consideration is that new future-oriented jobs have been created or conceived in recent years such as: future-guide, global system architect, global sourcing manager, grassroots researcher, organizational quartermaster, monitor/analyst, and talent aggregator (Wagner, 2010). It is possible to include all these jobs and professions into the proposed taxonomy or perhaps something better.


    References

    Mumford, T. V., Campion, M. A., & Morgeson, F. P. (2007). The leadership skills strataplex: Leadership skill requirements across organizational levels. Leadership Quarterly, 18(2), 154-166.

    Rohrbeck, R. (2011). Corporate foresight: Towards a maturity model for the future orientation of a firm. Berlin: Springer-Verlag.

    Wagner, C. G. (2010). 70 jobs for 2030. The Futurist, 45(1), 30-33.


    About the author

    Alireza Hejazi is a PhD candidate in Organizational Leadership at Regent University and a member of APF Emerging Fellows. His works are available at: http://regent.academia.edu/AlirezaHejazi 

  • 13 Apr 2015 3:04 PM | Daniel Bonin (Administrator)

    Within this blog post, I want to point out three problems with crowd-scouring and big data analytics that are relevant to open foresight practices. Big data tools offer ever more sophisticated ways to gather and analyze huge amounts of data. But one has to ask what conditions must be met by a crowd to generate helpful insights. Some examples indicate that big data predictions are not flawless (see e.g. the most recent faulty forecasts of Google Flu Trends (Lazer et al. 2014). For instance, analyzing data gathered in social networks or from digital platforms does not guarantee the effect of wisdom of the crowd, per se. The idea of wisdom of the crowd is based on the idea that estimates of a large group of people are on average more accurate than of single experts, as long as the interviewed group consists of highly diverse individuals. Wisdom of the crowd rests on four assumptions (Surowiecki 2005), which might serve as criteria to identify unbiased data sets:

    1. Decentralization (knowledge is distributed among many individuals, there is no such thing as an omniscient person)
    2. Diversity of opinion (individuals contribute private information)
    3. Aggregation (there are tools or algorithms that can aggregate and filter individual contributions in order to create a more accurate insight)
    4. Independence (the contribution of individuals in the crowd is not influenced by their peers)

    I want to focus on three problems that might arise when applying open foresight methods (a) self-selection, (b) crowding out motivation to participate and (c) anchoring on to peer’s behavior.

    Self-selection

    Threats to the quality of a data set are statistical biases like self-selection. Self-selection might occur due to limited access to technology that enables information sharing or personal rejection of social networks. Thus, decentralization is violated and the diversity of opinions is reduced as private information is neglected. With such problems occurring even in modern urban regions like New York, one should question the validity of big data predictions that use data sets from rural regions of the world (e.g. Crawford 2013). If we falsely believe that big data will always enable us to hear the voice of all people, we might unintentionally put more weigh on the opinions of people that are already heard anyways. Thus, futurists applying open foresight tools should familiarize themselves with the basics of experimental design and statistical biases.

    Crowding out of motivation

    It is argued that there are three dimensions of why people might volunteer: (a) extrinsic motivation (e.g. money), (b) intrinsic motivation (e.g. one’s own values like altruism) and (c) image motivation (desire to signal certain behavior) (Ariely et al. 2009). It is well known, that incentive schemes can backfire. For instance monetary incentives can potentially crowd out the motivation to volunteer. Another problem might be that incentives could reduce the quality of contributions. If we install incentives for contribution to an open foresight platform, some people might start to “mass produce” content at cost of the quality to earn rewards. This might moreover crowd out the participation of individuals that have high standards to their own work or are intrinsically motivated and are then discouraged to contribute. So we need to get the incentives right to maintain both a high participation rate and quality on open foresight platforms.

    Anchoring on the behavior of peers’ and wisdom of the confident

    Various experiments have shown that individuals tend to adjust their behavior and the magnitude of their behavior towards that of others, for better or worse (e.g. Schultz 2007). Under the assumption that individuals are influenced by their peers, it might be wise to identify individuals that are less likely to adjust their behavior so that independence within the data set is preserved. Research of De Polavieja and Madirolas (2014) shows a way to do this. They postulate that individuals within the crowd differ with regard to their confidence in their own opinion. The weight individuals put on their own private information and the opinions of their peers differ. The hypothesis is that with increasing confidence in one’s own opinion, the accuracy of estimations increases. With an intelligent line of questioning, they were able to prove their hypothesis.

    While open foresight processes seldom aim to identify the most accurate estimation but rather open up new views (see e.g. The Future of Facebook), the research of De Polavieja and Madirolas (2014) might still contribute to the improvement of (open) foresight practices. If we are able to identify individuals that are more confident in their own opinion and can get information on how the different individuals are related to each other in the network, we might be able to identify thought leaders, mavericks and influencers within the community. These individuals might then be questioned in more detail and come up with unique ideas about possible futures. Of course, such rankings might also help us to prioritize ideas and help to skim through inputs. Possibilities are abundant here; we could, for instance, integrate short creativity tests into questionnaires to make the selection process even more rigorous.


    References

    Ariely, D., Bracha, A., & Meier, S. (2009). Doing good or doing well? Image motivation and monetary incentives in behaving prosocially. The American Economic Review, 544-555.

    Crawford, K. (2013). The Hidden Biases in Big Data. https://hbr.org/2013/04/the-hidden-biases-in-big-data

    The Future of Facebook. http://futureoffacebook.com

    Lazer, D., Kennedy, R., King, G., & Vespignani, A. (2014). The Parable of Google Flu: Traps in Big Data Analysis. Science, 343(6176), 1203-1205.

    Miemis, V., Smart, J., & Brigis, A. (2012). Open foresight. Journal of Futures Studies, 17(1), 91-98.

    De Polavieja, G., & Madirolas, G. (2014). Wisdom of the Confident: Using Social Interactions to Eliminate the Bias in Wisdom of the Crowds.

    Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological science, 18(5), 429-434.

    Surowiecki, J. (2005). The wisdom of crowds

  • 06 Apr 2015 9:28 PM | Anonymous member (Administrator)

    Fear is the mind-killer.

    Jason Swanson, APF Emerging Fellow

    In my last post, I pondered about what might make a futurist a good futurist. With the help of some great input from Maree Conway, rather than asking what might make a futurist good, perhaps we ought to ask what makes a futurist effective.

    In the month that has passed since writing that blog post, the thoughts about what makes for an effective futurist have still been top of mind. During those four weeks, I have had a number of conversations where I was asked what attributes might be needed to be a good (or effective) futurist?

    To be sure, there is an endless list of attributes that one might associate with a good or effective futurist. In fact, if you were to administer a Myers-Briggs type test to the futures community you may even generate some sort of archetype, but for me, as a professional early in his career there are two attributes I feel are particularly relevant; fearlessness and obsession.

    Anyone involved in futures must be fearless. Foresight is about change, and change makes many people uncomfortable. You will constantly be walking an edge, talking about images that might be, sometimes playing the role of provocateur, pushing your audience to think differently, to question their current reality, and to hopefully change their mental models. You will be challenged, occasionally be called crazy, and deal with territory where there are no data points. There is also a very public learning curve to this field. You will blog, you will write, and you will speak about the future, all the while honing your craft as you go. It is not for the faint of heart, and as a beginner this may feel incredibly daunting. It did for me. It still does.

    The fearlessness one develops is joined by a second attribute I feel is just as important; obsession. I am not condoning a horrible life balance, but rather a passion about the future, and a drive to perfect a craft that cannot be perfected. Foresight is something I refer to as “the gift and the curse”. It frames my view of reality, and for better or worse I cannot turn it off. I recall an email exchange between two gentlemen I consider mentors. During the exchange, one of them remarked that choosing this line of work was more a lifestyle choice than a choice of profession. I couldn’t agree more. It is that obsession about the future; the endless drive to see what might be next, the bottomless curiosity that makes us question our current reality that separates this field from so many.

    For those that may be considering entering the field, or have just begun their careers and are wondering what attributes make for a good or effective futurist, develop your fearlessness and turn your passion and curiosity to obsession. On the days where you feel fear creeping in, let your obsession and passion guide you. For those who have spent time in the field, may your fearlessness never runs out nor you obsession wane.


  • 30 Mar 2015 2:46 PM | Julian Valkieser (Administrator)

    In my previous articles, I have already mentioned some examples where large amounts of data are used to create future predictions. Mostly, these are very specific and limited to a certain range. After all, worldly influences are very complex. If there is too much variety of influences, the predictions using big data are less accurate.

    Next I want to mention other examples, in which big data is used for creation of short- and medium-term forecasts. Of course, at first this has little to do with Futurists and Foresight and long-term forecasts. But in my opinion, it represents a baseline for future practice for Futurists and Foresights. I will explain at the end of the article. Now I want to mention two examples of big data forecasting.

    The Berlin-based start-up SO1 claims to be able to predict your behavior very accurately based on customer data in supermarkets. With certain offers and discounts they can move you to change your favorite brand. This works on the principle that we already know from Amazon: “Customers Who Bought This Item Also Bought”. Of course, the concern of SO1 is a frightening scenario. After all, each customer may be offered different prices for a specific product. I think no one wants this. Presumed that SO1 maintain its algorithm, this is a good indication of how well you can predict human behavior already.

    Another example from German Technology Review: Thomas Chadefaux from Trinity College in Dublin, analyzed social media channels and the Google News Archive from 1900 to 2011 by specific signal words, to find out if weak signals in the media advance to crises and violent confrontations. With a probability of 85% he could predict crises, like those in Armenia, Iran or Iraq up to one year in advance. The problem here is currently: He is looking back. How his algorithm will be developed in the future, must be observed. Nevertheless, one should be alert of his name.

    In summary, I would like to explain why I see these examples of predictions using big data so important for the area of Futurists and foresight. Of course, classical foresight methods are used for a company to be prepared for future influences and circumstances. For example, this is also the theme of the so-called HRO (High Reliability Organizations).

    Many companies base their strategic decisions in the short and medium term now on Big Data. For long-term and accompanied much more complex decisions Big Data itself is not complex enough. Here the classical Futurist jumps in. On the basis of Big Data evaluated scenarios and trigger events (see previous article) it can record creative eventualities that have not been enumerated by Big Data Analytics. The future of Futurists is essentially asking to set its basis for discussion with big data and finally, base eventualities on classical methods to which a company besides the main focus should also prepare. An HRO works similarly. There are eventualities outlined and for each one with a given weighting a process is defined, e.g. how to react. HRO examples are hospitals, fire stations or on an aircraft carrier.

    About the author:

    Julian Valkieser finalized his study with the thesis on "evaluation criteria for innovation projects in the early stages". Parallel to this, his last engagement was in the Corporate Foresight Department of Evonik Industries AG. Now, he is a product manager "classifieds" at a german local based website.

  • 16 Mar 2015 11:37 AM | Sandra Geitz (Administrator)

     

    Psychological distances are social, temporal, spatial and experiential



    Along a similar theme to the last post, I’m exploring enhancing and enabling futures thinking. This post is concerned with Bridging Psychological Distance, from Rebecca Hamilton’s HBR article this week, and how this may impact facilitating foresight.


    What is psychological distance?

    People directly experience only the here and now. It is egocentric. In order to think about the future, another person’s perspective, remote locations and/or understand hypothetical options, people need to transcend their self, or their individual present experiences. This is termed by psychologists, Nira Liberman and Yaacoc Trope as overcoming psychological distance. People are able to do this, to varying degrees of ability, by creating distant abstractions, or mental constructs.

    Psychological distance can occur as one or in several dimensions. Social distance is the gap between yourself and other people. Temporal distance is the gap between the present experience and the future. Spatial distance occurs between your present location and some far away distance. Experiential distance is the gap between one’s direct experience and an hypothetical or imaginery situation.


    Why may psychological distance be important to foresight?

    Liberman and Trope’s research shows that the farther removed an object is from direct experience, the more abstract one represents the distant object. Also, their research shows that each of the four psychological distances are cognitively related to each other, that they similarly influence and are influenced by the level of abstraction, and that they similarly affect they way we preference, predict, perceive and take action.

    If the psychological distance is large, we tend to think in more abstract ways; we focus on the big picture, the why or purpose of our choices, and the desirability of our options. Large distances and abstract language are associated with power and visionary thinking.


    When the psychological distance is small, we think in more concrete terms,; we are focussed on the details, the how and what of our choices, and the feasibility of each option. Small distances are synonymous with familiar, concrete tasks.From this research, Hamilton advises that the optimal strategy is adjusting the psychological distance to suit the needs of the particular task at hand.

    Social distance can be reduced by taking into account the perspectives of others, employing the ability to step into another’s shoes. Similarly, social distance can also be reduced by reducing temporal distance, through immediate task deadlines, or by meeting others onsite, reducing spatial gaps.

    Temporal distance can be reduced by adopting milestones or internal deadlines, to reduce overwhelm of the distant project completion, or visualising the future state.Temporal distance can be reduced through less social and/or spatial distance, such as meeting with stakeholders of the large project task.

    Spatial gaps are reduced by face-to face meetings and travelling onsite. And experiential distances can be minimised via role plays, prototyping experiences to enable more concrete thinking or action to occur. Similarly, experiential distance can be reduced via social distance, by peer group word of mouth recommendations to encourage us to take similar actions.

    However, if big-picture thinking, creativity or authority is the desired goal, increasing social distance by using abstract language helps. Deploying greater spatial distance by moving meetings offsite or to open, lofty and spacious surroundings can assist expansive thinking. Increasing temporal distance for long-term planning horizons can encourage more ambitious goal-setting. And, increasing experiential distance with hypothetical questions and imagery may encourage a broader range of scenarios to be considered.


    How can we use greater psychological distance to expand our futures options?



    How might we minimise distances to enable concrete actions towards our preferred futures?

  • 09 Mar 2015 1:32 AM | Anonymous member (Administrator)

    Written by: Alireza Hejazi, APF Emerging Fellow

    Attending a summit on the investment in R&D, I found the majority of R&D outputs discussed in the summit were professionally polished secondary research. A panel of experts was tasked to evaluate a strategic framework documenting a baseline, as well as alternative futures for a number of stakeholders active in the construction industry. An interesting debate was ignited in the panel when I suggested three points to be considered in their appraisal: originality, quality and timeliness. Coming back home from the summit, I asked myself how much the stakeholders should really budget for the unknown—the future. To answer that question I wrote this post and I assume those three points may make general criteria in budgeting foresight projects.

    Primary or Secondary?

    How much should the stakeholders pay for insights offered by futurists? In my view, a criterion can be made based on the primary or secondary nature of research. Secondary research means using other researchers’ data rather than generating one’s own statistics. Using data produced by well-known institutes such as ILO, WTO, UNESCO, Gallup, and etc. a futurist can conduct secondary research. Futurists do more secondary research than primary explorations and most of scanning jobs are based on secondary sources of information.

    While secondary research can be precious in the right place, like many other researchers, futurists are expected to create their own data. Normally, primary research offers a better taste of trustworthiness to stakeholders. Governments and NGOs collect and publish statistics, researchers and authors write books and articles based on their observations, speakers write speeches according to their ideas and information, but what do futurists produce? Generally speaking, futurists find, interpret and represent the results of all that data for their clients, books and articles and also their speeches.

    The missing point in judging research outputs produced by futurists is that primary data does not interpret itself. A dexterous interpreter is needed to make sense of that data. The collection of the data from various sources can be done by every researcher, but futurists enliven the collected data by suggesting alternative futures. Collecting and interpreting are both necessary, but what is the best data in foresight profession?

    According to Gordon (2009), “The best data is primary data—data researched and presented by the original researcher—and the best use is primary use” (p. 14). Results from scientific research which are based on primary data are usually published in top research journals and are sometimes delayed for publishing due to the sensitivity of issues for investors who sponsored the research project and perhaps never published.

    The value of primary data can be also revealed in the light of inherent limitations of using secondary data. Those limitations are identified by Burnett (2008) in this manner: “First, the information is frequently dated. Second, seldom are secondary data collected for precisely the same reasons that the information is sought to solve the current marketing problem” (p. 61). The stakeholders want fidelity and they prefer the primary source. The futurists can lead that sense of preference skillfully towards original authentic foresight outputs produced by their own reliable and valid research.

    Quantitative or Qualitative?

    Potent futurists are expected to organize and conduct both quantitative and qualitative researches. A noteworthy foresight output is expected to open up a window through which readers may peer into the world of foresight to learn more from the findings. Strong foresight works engage the audience by displaying and discussing correlations, values, and other details both quantitatively and qualitatively.

    The choice of using a qualitative or quantitative design (or both), for a given research problem is mainly related to the nature of problem. Basically, quantitative methods are appropriate when: “(1) measurement can offer a useful description of whatever you are studying, (2) when you may wish to make certain descriptive generalizations about the measures, and (3) when you wish to calculate probabilities that certain generalizations are beyond simple, chance occurrences” (Williams & Monge, 2001, p. 5).

    While most quantitative researches create generalizations that transcend the immediate situation or particular setting, qualitative researches often do not try to generalize beyond the particular situation, but may leave it to the reader to assess applicability (Fraenkel, 2009, p. 15). The history of futures research shows that the majority of studies have been conducted through qualitative approaches. The main reason is that the future is unknown and less quantitative data are normally available compared to other fields of study.

    The research perspective, approach, and method should be determined as a consequence of deciding upon the objectives of the investigation. Thus, one particular perspective, approach, or method is neither better nor worse than another, just simply more or less appropriate within the specific circumstances and objectives of a foresight project. What matters for a fair payment are time, fund, knowledge, skill and energy that are devoted by a futurist or a team of futurists to a foresight project through both quantitative and qualitative approaches.

    On time or Late?

    The importance of each foresight output at any given time depends on aspects of the situation, such as the type of industry and the amount of volatility in the external environment. The consequent is the timeliness of a foresight report that is set up for submission to related stakeholders. The futurists are not the only ones who need time to accomplish research; the stakeholders also need enough time to devise their companies with foresight insights or new strategies proposed by the futurists.

    The amount of budget that investors offer to know the unknown is tightly related to available time for decision making or change management. Firms that consistently establish a management reserve for foresight projects can tell us how much time is needed and how valuable a foresight output will be over time. Certainly a specific percentage of the performance budget should emerge as the right amount, but it is directly related to timeliness, potential risks, and the degree of predictability of the industry. As observed by Verzuh (2005, p. 106), “high-risk industries such as software development may add as much as 30 percent to the budget. More predictable projects will use an amount closer to 5 percent of the performance budget.”

    The factor of time determines how much should be paid for a foresight output. Over multiple foresight projects, a normal range will appear for both futurist and client. Imagine an alternative scenario like this: A construction company is interested in a particular topic and the CEO decides to hire a futurist to research the topic for them, but time is a determining factor in the success of company. The futurist spends six months researching the issue, and six months doing and writing up the research. How much do you think the futurist could charge for this report? If the CEO needs the final report six months earlier, then how quickly should the job get done? How about the quality of research and how about the payment? Many clients pay considerable outlays for private research reports. They pay not just because of the worthiness of information, but because of its timeliness. Quick and qualified futurists are brilliant gems in every company.

    In my view, the budgetary value of a foresight output depends on its originality, quality and timeliness, but its intellectual value and the contribution that it will make to building better corporate futures may not be determined by such means of assessment easily.

    References

    Burnett, J. (2008). Core concepts of marketing. Zurich: Jacobs Foundation.

    Fraenkel, J. R. (2009). How to design and evaluate research in education. New York, NY: McGraw-Hill.

    Gordon, A. (2009). Future savvy: Identifying trends to make better decisions, manage uncertainty, and profit from change. New York: American Management Association.

    Verzuh, E. (2005). The fast forward MBA in project management. Hoboken, New Jersey: John Wiley & Sons.

    Williams, F., & Monge, P. (2001). Reasoning with statistics: How to read quantitative research (5th ed.). Fort Worth: Harcourt College.

    About the author

    Alireza Hejazi is a PhD candidate in Organizational Leadership at Regent University and a member of APF Emerging Fellows. His works are available at: http://regent.academia.edu/AlirezaHejazi

  • 02 Mar 2015 1:03 PM | Daniel Bonin (Administrator)

    With this blog post I would like to think about: What if futurists were ubiquitously employed in companies? This simple mind game might sound trivial, but I think it can provide interesting food for thought. The question this scenario raises is: What are possible chances and threats as well as implications for the futurist profession? At first glance, it might sound like a preferable future for our profession, but what is the catch for self-employed futurists and consultancies specializing in this field? How can this group of futurists still create value and “compete” with in-house futurists that can draw upon the sophisticated infrastructure of companies?

    What would this mean concerning our methods and the content we provide, if our former clients would have installed in-house futurists? In this scenario the share of clients with existing knowledge in future studies would increase and so would the expectations to provide more novel insights. As a result futurists might need to specialize their business in order to be able to create value for clients with in-house futurists.

    As a consequence, we would less often provide rudimentary training programs on foresight, but instead be tasked to refine existing foresight processes within companies and develop implementation strategies. The analysis of organizational structures and processes as well as change management would become an integral element of our day-to-day work. Today it is often the case that we build up and consult about processes that are completely new ground to our clients. But in the future we would need to learn how to make a diagnosis and fix a running system. Like a doctor or psychologist we would make a diagnosis on the basis of the patient’s conditions and their specific requirements. But are we, as futurists, capable of carrying out change management. And what would our instruments be? We haven’t successfully mastered the challenge to provide our generated insights to different stakeholders and to cast off the image as soothsayers, yet. How can we then change whole processes credibly?

    Related to the need to provide services tailored to the specific characteristics of our clients, another issue arises. If more and more futurists find their way to companies, both futurists and in-house futurists might need to think about what interferences other players make about the future. If you read the latest state of the art report on the Future of Communication, chances are that your competitor’s futurist read this piece as well. Today we apply our foresight tools but neglect that our clients‘ competitors or other futurists think about the future as well, and adapt their future behavior accordingly. How valuable is the detection of e.g. weak signals to create some kind of value or even a competitive advantage, if weak signals are on the verge of becoming common knowledge? Thus, we need to consider our client’s market position, strengths and weaknesses to create value through foresight activities. Especially, when we identify future markets or assist new product development. We might need to integrate strategic management tools like BCG-Matrix, SWOT-analysis, Porter’s five forces, GE-McKinsey Matrix or the Business Model Canvas in the foresight process.

    Next, firsthand insights gained from discussions with shakers and movers could create more value than scanning freely available resources and surveys. In-house futurists are likely to be able to access a huge IT-infrastructure with all the Big Data tools that comb through the internet. So what can futurists with a lack of IT-infrastructure do? It may be wise to create an extensive network of decision makers that can be referenced similarly to how journalists cite their sources. In contrast to historians that write about important historical figures in hindsight, we need to identify possible important figures of the future through foresight to tell today about the future they work towards.

    But there is also good news. Generally speaking, I do believe that futurists create positive externalities through their services for the society as a whole as we promote long-term thinking and reveal future problems, and help identify and then realize preferred futures. This is especially true if more and more futurists are hired in companies that do not have a particularly good record of sustainable actions.

    So I believe it is important for self-employed futurists and consultancies to develop some kind of unique selling proposition to remain a sought-after service provider if the foresight capabilities of companies increase. With an increasing specialization of futurists, we might need to get accustomed to a new form of collaboration, namely co-opetition between futurists. Furthermore, I fear that ruinous price competition and the free provision of services to get a foot in the door during tender and pitches might be a future problem given fierce competition between external futurists and the market power of companies. However, if not us as futurists than who else can think about such threats and is then able to prevent such negative consequences?

    Some questions remain:

    • What could unique selling propositions be given such competitive market conditions?
    • What are the implications for the questions Jason raised in his latest blog post “What Makes a Futurist ‘Good’?”
    • Are today’s futurists ready to join companies? What are the skills needed to succeed as an in-house futurist?
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