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 more about the Emerging Fellowship program and the inaugural class 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 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.


  • 06 Apr 2015 9:19 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?
  • 23 Feb 2015 5:07 PM | Anonymous member (Administrator)

    What Makes a Futurist “Good”?

    Jason Swanson, APF Emerging Fellow


    Photo by Sarah Reid / CC by 2.0

    A few weeks ago I had the pleasure of hosting my friend Jacob for a visit. Jacob is a quantum physicist and research group leader at the Quantum Network, making him one of the few people whose job might take more explaining than mine when asked what I do.

    Over the course of his visit, he asked me a question that has stuck with me. The question was a simple one; what makes a futurist “good”?  The question, while on the surface seemed straight forward, however the more I sought an answer, the more lost I became.

    We might judge a good futurist by credentials and training. Have they learned methods for looking at the future from an academic institution? Did they take a seminar or some manner of formal training? This training might have some manner of correlation with a “good” futurist, but the credentials themselves are third party verification of certain competencies in methods that a futurist might employ. Even more problematic is that many enter the field from other industries, with years of outside knowledge and expertise and little or no formal training or “futures” credentials, yet put out well-regarded work.

    With the idea of credentials and training no longer an option for figuring out who might be good, I started to think about output. Is it possible to objectively judge a forecast? Could one be a poor futurist but an excellent writer and create vivid images of the future? Sure. Could one be great at mastering the methods in a futurist’s tool box but not articulate the images of the future? Certainly. There is also the issue of bias; we may favor a particular writing style, or image, or method, thus gravitating towards a piece of work over others based more so on style than on content.

    Ultimately my line of thinking has led me to this; a good futurist is one that creates good forecasts, in whichever form they are presented. A good forecast is one in which action is taken. Thus, a good forecast could potentially be created by anyone, with any form of credentials. It could be articulated in any way. As long as a stakeholder takes action, it may be considered good. Admittedly this is a very simplistic view. As the field continues to work towards professionalizing, there may be a time when there will have to be some criteria for what makes a futurist “good”. There is no easy answer to this. That is the rub with trying to rate a futurist. At best we create a standard for what we view to be good work. At worst we risk narrowing the field and creating a status quo, creating groups that are “in” and “out”, good and bad. If we base being “good” on forecasts that produce action, how do we define action? Is it creating actionable strategies? What about simply asking better questions about the future?

    What makes a futurist “good” to you? Is it even possible to objectively call someone a good futurist?


  • 16 Feb 2015 1:25 PM | Julian Valkieser (Administrator)

    In my last articles, I have already mentioned the power of Big Data. My blog colleague Jason adopted it and expressed his own thoughts. In his last article, he has shown wonderfully how technology has already overturned business models and efficiency in other sectors and renewed them. In comparison to this, it could happen in the area of futurist and industry’s foresight as well.

    Now, there are foresight methods that work well or best with uncertainty. Indeed, Delphi-Interviews are planned preciously, e.g. interviewees are pre-selected. But this does not mean that the statements can be processed for hard facts of future reality. And, they should not. That's the exciting thing about scenarios. They give a way to stimulate the imagination and to derive recommendations for action.

    But again, you try to keep the "cone of plausibility" as narrow as possible. (See Jason's blog). You are looking for certain experts. You force certain issues. This is done in order to build the scenario reasonably.

    Now you can imagine how neutral subjective responses and subjective questions are. Anyone who read “Thinking Fast and Slow“ from Daniel Kahneman knows what I mean. And right here data comes into play. Information could passively express motives and interests of groups. I have already indicated this in my last article

    In this article, I already referred to the fact that you can only get the most out of Big Data, if one applies the prediction to a trigger event. One extracts motives and interests out of big data for one or more so-called, trigger events. These are events that can be relatively easily predicted in the near future based on data, because the circumstances are (should be) less complex. Based on these trigger events you can create a scenario. In principle, this is nothing new. Just the basic information is extracted out of big data instead of interviews and subjective insights.

    Let's take an example. A major mobile phone company has 50 million customers. Each customer has a phone and moves every day with this turned-on phone - in this case between different radio towers (See Triangulation). Let’s suppose further that the company receives 20-100 motion information’s by any customer. Provided the company may cache this information for a longer period of time, the result is a huge amount of data information, how people move, how long they stay in which locations, etc. Of course, each individual could now be afraid of privacy. But the individual is not of interest. It's about the mass.

    Imagine what you can do with this information now available. Road offices could optimize the logistics. Infrastructure projects could be optimized. Where should the new stadium be built? How is the highway to be calculated? How many trains must be set on this track?

    In a rising urban environment, where sheer masses of people are moving, all these data are exciting as the basis for trigger events and scenarios.

    And finally, I have another wonderful example for these ideas. Eric Fischer has evaluated geo-tagging data from photo cameras. He compared where locals and tourists take pictures in certain cities in the world and displayed this information on maps.

    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. Next, he starts as product manager "classifieds" at a german local based website.

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