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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  • 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.

  • 10 Feb 2015 7:43 AM | Bridgette Engeler Newbury (Administrator)

    The empires of the future are the empires of the mind. Winston Churchill

    Design and its outputs may reflect our individual and collective imaginations, but design is first and foremost a philosophy, based on a system of values, which seeks to solve problems. What are we creating? Why and for whom? These are questions, in no particular order, to which answers are manifested tangibly and most often in the form of a new product or service or organisational or business model.

    Designers are practical agents of visual imagination, both anticipating futures and creating the sensory blueprints for the objects and experiences to come. The images, objects and technologies that surround us are rich with desirable images and symbolism; they’re powerful and persuasive, well-crafted and covetable, and often very well made. Designers can turn abstract futures-oriented concepts and ideals into visible or tangible form. Designers and design thinkers are agents in articulating futures, and therefore have individual and collective agency for humanity more broadly to sense, see and negotiate (or refuse) the transition.    

    Not all design is good (by any definition). So I’m contemplating what something like long-range design - ‘design with foresight’ – could be. AKA prospective design, it’s what I suggest is design that emerges when futures thinking and design thinking are used together, in a structured manner, to develop an idea that may not exist until sometime in a long-range future, or which will not be to the detriment of preferred futures.

    • Prospective design relies not on technology but on human interaction, deep thought and reflection
    • Prospective design embraces design’s potential to shape conversations, to (re-)frame problems, and to drive participation by understanding the needs and resources of all the differing functions in a consuming world
    • Prospective design is inherently good and not just because it’s always intentional and sociological
    • Prospective design does not produce novelty for the sake of novelty
    • Prospective design makes a product, service or organisation truly useful. Things are purchased, used, adopted and recommended because they serve a purpose and deliver value: value that improves people’s lives and makes them happier. This is the real measurable value people desire. Prospective design optimises the feelings and experiences of customers, while being responsible to community, planet and what is yet to come
    • Prospective design satisfies form and aesthetics, without compromising usage or need. Designed artefacts do not simply fulfil desire or need; they can actualise and reflect wants. The look and feel of something, its materiality and substance, ethereality and intangibility, ephemera and sensation are all part of the feelings it arouses – which are in turn a strategic and integral part of the user’s realisation of value
    • Prospective design helps us to make sense of things. ‘Value’ (as perceived by the user) creates engagement. Good design creates curiosity and engages its audience in meaningful, valuable ways. It also conveys the intentions and trustworthiness of the organisation behind the design and helps people make informed choices
    • Prospective design can be a catalyst or guide, a means for people to create their unique and evolving stories, and their own individual meaning
    • Prospective design is durable and enduring. It increases the value of something over time. It remains relevant as its users, community or culture develops and matures. It may not exert influence or manipulate buyers, but it often takes risks to provoke worthwhile change.

    Prospective design is concerned with context and environment. It’s unobtrusive and meaningful, enhancing people’s experience; it’s not about dominating strategic decisions. Prospective design draws together futures thinking with the principles and practices of design to frame a strategic conversation without an elitist position. Design may be part of a complex, living ecosystem, but prospective design can strive to be a positive agent of transformation that contributes to better-being.


  • 02 Feb 2015 8:34 AM | Sandra Geitz (Administrator)

    "We cannot solve our problems with the same thinking we used when we created them."

      - Albert Einstein

    Ideas_Silent.jpg

    How to facilitate teams for generating and enacting?


    There seems to be a growing acceptance that diverse experiences and perspectives correlate with better outcomes: greater financial performance results, improved risk management, greater innovation and employee satisfaction and engagement, see the recent McKinsey article, Why diversity matters.


    And yet, neither diversity of experience, gender, ethnicity, gender, nor age guarantees that the best ideas will be shared, genuinely heard nor be accepted and implemented on their merits. In many recent experiences, I have seen culturally diverse teams conforming to expectations of the loudest, most senior team-member just like the best homogenous teams. Is this your experience, too?


    What is really happening to the diverse potential of rich ideas?


    For a long time, I’ve been interested in processes and methods that generate ideas and solve complex problems. I’m particularly interested in understanding ways to facilitate and encourage teams to examine issues or problems with an open mind, and help them reach beyond their own cognitive biases.


    So, a recent Stowe Boyd blog grabbed my attention, Phil Gilbert on sidestepping cognitive biases in group design activities: When you give voice to more people, the best ideas win, not the loudest ones. Interesting. Boyd explained two key ways that information processing is disrupted by a team’s culture and psychology. Firstly, effective ideation can be impaired by sharedness bias:


    Groups communicate predominantly about information, which all or most group members share before entering the discussion, and neglect unshared information, which only one or few members have initially. …  group members individually judge shared information as more important, relevant, accurate, and influential than unshared information. This bias seems to have two reasons: First, shared information can be confirmed by more than one group member. Second, individuals evaluate their own information as more valid than information from other members. Thus, unshared information, even if mentioned in the discussion, is not seriously considered by other group members and therefore has less impact on the final decision than shared information.


    Hence, with established sources of team knowledge and shared experience, groups tend to discuss, share and privileged information that is held in common. Novelty is rarely introduced within team meetings themselves. New ideas tend to be socialised with team members prior to any decision-making in meetings.

    The second is preference bias:

    Even when all information necessary to identify the correct solution is exchanged during discussion, individual group members often stick to their initially preferred wrong solution. People bias their information processing to favor an initially preferred alternative. Other studies show the same phenomenon at the group level: Group decisions can often be predicted by the initial preferences of its members. If a majority favors a certain alternative before the discussion, the group seldom decides to chose another alternative. Thus, frequently, group discussions are superfluous, and groups would be better off using a decision shortcut like an immediate vote or averaging procedure.

    We preference our own preconceived views and information over others. In spite of new valid information, we tend to conform to initial opinions we have of an issue. We tend to be closed to other possibilities, rarely are we convinced of others’ arguments, and we privilege our own ‘objectivity’. This sounds familiar…

    Boyd interviewed Phil Gilbert, IBM general manager of design, on how he applies design thinking, diversity and inclusion to team product ideation. Gilbert believes that the major issue to generating future possibilities, is exposing everybody’s ideas to the whole team: both encouraging all to contribute and hearing each idea.

    At IBM, team workshops are designed to include a wide diversity of experience and backgrounds. Gilbert’s method is sticky notes and silence, as depicted in the diagram above. Everyone present is encouraged to write down all their ideas on separate sticky notes and post them on a wall, without judgement, comment or self-censure. Team leader(s) sort, group and arrange like ideas on the wall, while everyone observes and reflects in silence. Then, individuals may leave the room to discuss ideas, in person, by phone or by a team social media tool. The group returns after an agreed time brainstorming and socialising their ideas (minutes, hours, or days). Gilbert explains that the process usually generates a few dozen new ideas.


    Phil Gilbert’s approach also aligns with Alex Pentland’s research, Social Physics, that I discussed in earlier post. Peak idea flow occurs in teams that iteratively work as individual’s generating novelty and team collaborators discussing, building and socialising these new ideas into practice, summarised in this diagram:

    PeakIdeaFlow.jpg


    “Any useful idea about the futures should appear to be ridiculous.”  - Jim Dator


    Profound words. Futures requires a healthy amount of personal resilience in ourselves. What of the teams that are thinking about their future? Have we designed our methods so that participants, as individuals and teams, are able to bypass cultural and psychological biases to see and accept issues and information anew.


    How can we promote genuine exploration, engagement and reflection with new ideas?


    How can we design experiences that suspend judgement, cynicism and criticism?


    How can we facilitate better futures?
  • 26 Jan 2015 1:17 AM | Anonymous member (Administrator)

    Written by: Alireza Hejazi, APF Emerging Fellow

    Attending an international exhibition on a marketing mission recently, I was asked to score service and product providers there and nominate my preferred candidate of that expo. After reviewing many pavilions, I made up my top ten list and scored them according to my check list. I voted for a European company that met most of my desired factors of presenting their services in a client-friendly manner. On the final day, my nominee won the cup not just because of my vote, but due to many other votes that other evaluators had given in favor of them. What looked nice in my eyes was also fine in the eyes of others. I asked myself whether such scorings and rankings could be also made for professional futurists. The idea made me write this blog post.

    I think that ranking the futurists can be a challenging task due to a number of reasons. First of all, there is no universally agreed system of scoring for futurists. Secondly, futurists normally come from different fields of expertise and they cannot be ranked similarly. And thirdly, ranking the futurists may be done validly by institutions that might be authorized for such rankings. I would like to share some of my assumptions and questions about the feasibility of such a scoring system in this post. I should remind that the goal of ranking is not to drive low scores away, but to claim them as candidates of high rank through professional development.

    The first question that comes into mind is this: “What is the benefit of ranking?” or “Why should the futurists be ranked?” In my view, futurists can benefit easily from their own personal branding without ranking; but if they are going to be entitled to the merits of professional recognition, they should be identified by the degree of excellence they provide with their services. In other words, ranking is a means of qualification in terms of knowledge, skill and the quality of service that professional futurists provide for their clients. In my view, professional recognition and related merits are logically belonged to those who provide high quality foresight outputs. Fortunately, the APF’s Most Significant Futures Works program has been serving this idea since 2013.

    Another question that will arise concerning a ranking system is this: “Can the futurists be ranked according to their academic degrees, the number of their published or referenced works, the number of their students, the efficiency of methods and techniques they have developed or the number of their daily Tweets?” or “Should they be judged according to the values they bring to their own nations and the entire humanity?” Conventional methods of ranking may sound useful for scoring the futurists who live in societies where thinking and acting about the future is respectful, but how about futurists who live in regions where futurism is nonsense in the eyes of local decision makers who are positioned based on aristocracy, not meritocracy?

    Any conceivable scoring system for futurists should recognize the fact that futurists are various in their talents and capabilities. While many of them are competent in applying qualitative methods of research, there are some who are brilliant in using quantitative methods of inquiry. Many futurists are good communicators and some of them are skillful in communicating what is ahead in innovative ways. Most of them are open-minded and lifelong learners, but what makes them valuable for themselves and the societies they serve? What are the social impacts of futurists and how can a ranking system measure them in national and international scales?

    The first step that should be taken in this line is to provide a clear and detailed description of the knowledge, skills and attributes expected of a competent futurist or foresight practitioner. A competency framework like what is developed by the International Manipulative Physical Therapy Federation (Rushton, 2013) can be also made for professional futurists based on these components:

    (1) Dimensions: The dimensions are the major functions for foresight performance at post graduate level. The functioning of strategic foresight and futures studies graduates should be evaluated after their graduation in practice.

    (2) Competencies: The competencies are the components of each dimension stated as a performance outcome. The competencies linked to a dimension indicate the standardized requirements to enable a professional futurist to demonstrate each major function for performance at post graduate level.

    Competencies can be divided into competencies related to knowledge, skills and attributes.

    (a) Knowledge: Encompasses the theoretical and practical understanding, use of evidence, principles, and procedures.

    (b) Skills: Encompasses the cognitive, psychomotor and social skills needed to carry out pre-determined actions.

    (c) Attributes: Encompasses the personal qualities, characteristics and behavior in relation to the environment.  

    There are other concerns in the workplace that should be addressed. Research shows that ranking systems are often viewed negatively by people. However, many major corporations such as General Electric (GE), Intel, and Yahoo! use relative rankings and believe in their advantages. For example, Jack Welch, the former CEO of General Electric, instituted a forced ranking system at GE in which 20% of employees would be in the top category, 70% would be in the middle, and 10% would be at the bottom rank. Employees who were repeatedly ranked at the lowest rank would be terminated (Ryan, 2007). Corporate futurists or foresight practitioners might be ranked internally within the corporations they work, but how should they be ranked externally in a larger scale within the global community of futurists?

    Relative rankings may create a culture of performance at corporation level by making it clear that low performance is not tolerated, but how about rankings that might be made by scoring futurists at a professional level? Should a low scorer be expelled out of international futurist communities? Or should he/she be prohibited from practicing the foresight profession without receiving required certifications? More importantly, what are the potential downsides to such rankings? Should a ranking encourage the futurists to upgrade their academic education in foresight and develop their professional skills, or conversely discourage them and deprive them from professional recognition?

    There are many other questions and assumptions like what are mentioned above that make a long list. They highlight a special attention that should be paid to all the details of any effort that would be likely made towards ranking the futurists. Until the completion of a standardized ranking system, conducting self-other rating agreement surveys can be the easiest way to capture a better understanding of futurists’ standing in companies and organizations they serve.  

    References

    Rushton, A. (2013). Educational Standards in Orthopaedic Manipulative Therapy, Part A: Educational Standards. International Manipulative Physical Therapy Federation.

    Ryan, L. (2007, January 17). Coping with performance-review anxiety. Business Week Online, 6.

    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

  • 19 Jan 2015 12:17 PM | Daniel Bonin (Administrator)

    Business wants to increase the repurchase rate, achieve positive word of mouth recommendations and promote cross buying behavior. But how can futurists get there? There are various hurdles to take if one assumes that futurists are part of the service industry.


    Client satisfaction is based on the comparison between expected and actual/ perceived performance. However the client might not have an idea of what they can expect and/or might hold an unfavorable mental model about foresight. The service provider has the opportunity to leave good impressions and build trust at points of contact with clients (“moments of truth”). During these moments, emotional intelligence is sometimes even more important than purely factual knowledge. Gaps in communication are the sources of many unnecessary misunderstandings. But in particular the distinct characteristics of services can be challenging for futurists:

    5. Characteristics of services

    1. Production and consumption might take place at the same time (e.g. Workshops).

    2. Once the service is provided the client cannot have the product exchanged for another product (like you can do with physical products), but may ask you to revise your work. This characteristic constitutes a source of conflict as futurists often challenge the client’s opinions and views. Thus building trust is essential.

    3. Foresight services cannot be stored as they are normally individualized to fit the client’s needs and objectives.

    Two characteristics are particularly important:

    4. It is hard to measure or assess the quality of foresight services. Intangibility constitutes a source for misunderstandings and also makes the comparison between futurists very hard.

    5. The client plays an integral part in the production process of foresight related services. The outcome depends on both parties. But the client might not realize this. Here, again, it is essential to establish mutual trust.

    So one can say that the client or anyone who is thinking about hiring a futurist faces a high degree of uncertainty caused by the characteristics of services. Clearly, futurists need to build trust and increase the service quality to increase customer satisfaction. But in order to increase the service quality one needs to identify areas where improvements are necessary. In marketing some of the following options are used to build trust and assess the service quality.

    Build Trust

    • Make sure that you respond to client’s needs in a flexible and fast way, but be honest and clear about what is attainable and what not.
    • Create reference points: Clarify what is expected and what can be expected (e.g. provide a sample of one’s work).
    • Hand out physical objects as a gift (e.g. artifact from the future) like some service providers (e.g. t-shirts from restaurants) do to increase psychological proximity.
    • Create trust by social proof: name clients, provide testimonials and use smart wording (e.g. “Over X business executives already joined our newsletter”).
    • Show expertise: Provide detailed descriptions about the knowledge and abilities of you / your team.

    Assess Service Quality

    While, simple questionnaires could also be used to assess the service quality, more sophisticated tools may provide additional insights. The following tools and methods might be used to assess the service quality and to gain a better understanding of the service flows. By doing so one has not only the ability to improve the service quality and reduce misunderstandings but also standardize client communication and processes.

    Communication gaps: Researchers identified communication gaps that often occur and decrease the service quality. Figure 2 shows where special attention needs to be paid (Patusuraman, Zeithaml and Barry, 1985).

    Blueprinting: Blueprinting is used to structure and sketch service flows. A blueprint consists of different types of “lines” and types of “activities” as shown in figure 3. This technique can be used to identify “moments of truth” and to standardize service processes.

    SERVQUAL: Using a Likert scale, client’s expectations and perceptions are measured and compared along five dimensions: (1) Tangibles (physical facilities, equipment and employees), (2) Reliability, (3) Responsiveness, (4) Assurance (e.g. credibility and competence), (5) Empathy/ Customer Understanding. I tried to create a questionare based on the book by Zeithaml, Parasuraman and Berry (1990), which can be found here.

    Critical Incident Method: Client’s are asked to memorize and describe “critical moments” (could be either positive and negative) in order to gain insights into the causes, outcome, feelings, actions involved and resulting changes in behavior. Afterwards all occurring problems are clustered, the frequency of certain problems is assessed and the relevance/ degree of annoyance is analyzed (“Frequenz-Relevanz-Analyse für Probleme”).



    References

    Bitner, M. J., Ostrom, A. L., & Morgan, F. N. (2008). Service blueprinting: a practical technique for service innovation. California management review, 50(3), 66.

    Borth, B. O. (2004). Beschwerdezufriedenheit und Kundenloyalität im Dienstleistungsbereich: Kausalanalysen unter Berücksichtigung moderierender Effekte. Springer.

    Edvardsson, B., & Roos, I. (2001). Critical incident techniques: Towards a framework for analysing the criticality of critical incidents. International Journal of Service Industry Management, 12(3), 251-268.

    Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. the Journal of Marketing, 41-50.

    van Doorn, J. (2004). Zufriedenheitsdynamik: eine Panelanalyse bei industriellen Dienstleistungen. Duv.

    Zeithaml, V. A., Parasuraman, A., & Berry, L. L. (1990). Delivering quality service: Balancing customer perceptions and expectations. Simon and Schuster.

  • 12 Jan 2015 9:02 PM | Anonymous member (Administrator)

    Towards Disintermediation.

    Jason Swanson, APF Emerging Fellow.

    In my post last month I explored a few ideas of how big data might affect the futures field in terms of both practice and business.  This post will continue that exploration, this time focusing more on the potential implications for the business side of things as big data tools such as R and Python come to fore, as well as academic programs such Udacity’s nanodegree in Data Analysis come to market. For an excellent primer on these tools, please take a moment and read my colleague Julian Valieser’s posts found here and here.

    I would like to explore the implications of big data on the futures field using a lens of scarcity, abundance, and disintermediation.  There are quite a few examples of industries that have experienced line of development. The retail industry comes to mind with consumers once relegated to seemingly few retail outlets, then an abundance of options, and now retail is becoming increasingly disintermediated as the internet has allowed for increased opportunities for peer to peer transactions. The music industry is has followed this path, and even public education here in the United States is dealing the changes that a system and its stakeholders have to contend with as it moves from the abundance period in terms of information access into disintermediation.

    Apply this lens to the futures field, one might make the argument that thinking about the future is indeed disintermediated. Everyone person alive thinks about the future in some capacity. It is part and parcel of living. When we define the futures field as the professional practice of studying the future using a defined methodology, an argument can be made that the field is still at the scarcity stage. The number of professional futurists is tiny in comparison to other professions.  I can’t help but reflect on how many times I have given my futurist elevator speech during my brief time in this profession whenever I am asked what it is I do.

    What might it take to move the futures field from scarcity to abundance or even all the way to disintermediation? If we are to consider the examples of retail, music, and education, the key additive was technology, particularly when moving from the abundance stage to the disintermediation phase. Concerning the futures field, there are signs that the field may be beginning to move from the scarcity stage to the abundance stage. Among those signals are the small but growing numbers of academic programs offering courses and degrees on the topic of foresight, growing interest in existing foresight courses and programs, and even growing interest in the application of foresight methodology in disciplines such as design.

     If these signals might signify a slow move to the abundance stage for the foresight field, what might that look like? Let’s use the retail industry at the abundance stage as an example once more. At the stage of abundance, the consumer had a high degree of choices in retail outlets, with a high degree of choice in terms of items, and many price points for those items. The foresight field at the abundance stage may look similar to the retail industry; a high degree of choice in terms of foresight services, many practitioners, an increase in organizational or internal futurists, more choices in training programs, in short, more. Of course a critical uncertainty here is will there be demand to account for all this “more” beyond simply an interest in methods.

    As I mentioned in my last post, big data has the potential to change our practice and our industry. As big data tools continue to simplify and improve, there will be an effect on the futures field. One of those effects might be speeding futures through the abundance stage into disintermediation. As these tools develop, become easier to use and more accurate, the by product may be a growing interest in what’s next. Using predictive analytics and modeling to give a client, company, or organization accurate peaks into the future could push the field into adopting these tools (Again, please check out Julian’s blog post for an excellent use case). The move towards incorporating this type of data into our work may have the effect of “legitimizing” the work in the eyes of clients who in the past may have been standoffish, or who may shy away from more qualitative pursuits.

    As big data tools continue to develop over time, these tools have the potential to be a factor in moving the futures field into the disintermediation phase.  We can expect over time that big data tools, like nearly all forms of technology, will become cheaper and easier to use. As the ease of use increases and price points fall there is the potential for new users.  Given enough time, a user might be able to utilize these tools through apps on a phone or other personal devices. A person might be able to one day run predictive models with the same ease of sending a text message. This sort of breakthrough could be compared to having a futurist in your pocket, crunching massive sets of data and giving highly plausible scenarios back to the end user. At this point the futures field may be considered disintermediated, with users being able to directly use methods and tools in developing images of what the future may be like.

    Could big data and big data tools be a catalyst to push the futures field towards disintermediation?

  • 05 Jan 2015 7:33 AM | Julian Valkieser (Administrator)

    In my last article, I referred to the importance of Big Data as it has become more and more important for decisions in medium-term periods. Big Data is an often used buzzword – especially by large corporations and middle management levels.

    I have mentioned R programming, claiming that everyone in the area of Foresight should learn it in the near future. Now we have to add the programming language Python. For people with a lot of self-discipline I would like to recommend a Google search and a good book. For myself, I have gone the way of Coursera, a Massive Open Online Course (MOOC), which I can highly recommend.

    It is not so much about being a programmer. After all, it is not our field of interest. Rather, it's about using these programming languages to play with a large amount of data so that you can develop an understanding of the benefits. Of course, there are also tools that require no programming skills. Maybe you have heard of NeuroBayes or RapidMiner? But someone who wants to sell a car should also know how a car works.

    Especially the tool RapidMiner shows very clearly what makes this kind of tools and what Big Data is all about: The visual presentation or summary of large amounts of data. Only a good representation and summary can be a benefit from Big Data.

    Beautiful examples of where data analysis for short-term forecasts are used are as follows:

    http://edition.cnn.com/2012/07/09/tech/innovation/police-tech/

    http://www.popsci.com/science/article/2011-10/santa-cruz-experiment

    http://www.skyhookwireless.com

    http://firstmonday.org/article/view/3663/3040

    http://www.slate.com/...big_data_...guessing_that_you_re_pregnant.html

    Of course, these examples are not transferable or all reality based. But – to get back to the metaphor of the car – in terms of data analysis, we find ourselves status quo in the early days of the Ford Model T.

    There are certainly countless more of such examples. All more or less well understood and scientifically correct. Another example: Nate Silver Predicting an election.

    One thing you can say now: Forecasts based in the past are less reliable, or partially obsolete, for example, if you are emanating from seasonal recurring events, such as the flu or the purchase of heaters in winter time. If you can analyze data in terms of motives and interests (See also Computing and Intuiting futures from Sandra Geitz), then it gains a different picture. Motives and interests provide information representing "we are going to…,", situations such as "I'll buy a car if I get a raise."

    This could be transmitted at the macro level, e.g. if the Democrats are elected in 2020, they will finally put through a specific law, because we all know that they are still working on this. It is very likely that they will do it if external circumstances allow it. This is when Big Data comes into play. The Democrats re-election depends in turn on the people's interests which can be reflected, e.g. on Google queries.

    All of this relates only to medium-term time horizons and Foresight is less about making a prediction, rather likedepicting a scenario. However, a scenario could be represented more closely or exactly, as already hinted by Jason with his, “A Shrinking Cone of Plausibility” blog. Big Data could serve to draw the “so called trigger events” in this case to create scenarios based on these trigger events. For example: The next US president election, Jason used a Cone of Plausibility in a familiar example. I like this approach. But for me, Big Data is used for the representation of starting points or trigger events with which you can create scenarios in the distant future.

    Existing Scenarios are mostly based on the current day or status quo. At this point, let’s go back to the Big Data analysis where Democrats will be re-elected. Based on this forecast with a certain probability we can build a scenario that is not mirrored from today's point of view, but from the status of the so-called trigger event that a particular party is elected. Of course, this should not be the only factor for our scenario. Other trigger events could be used such as other interests and motives. What are the media interests? In what way have the most protests been expressed? Which governments were overthrown and which companies enjoy continuously high investments in the market? How have prices developed for this and that? This information be more precisely reflected in the near future with Big Data analytics. Of course, not 100% accurately – but more accurately than if not used, or only subjectively evaluated.

    The recommendation


    Try to engage in R and Python. Look at tools above with which you can analyze data and represent it visually, even without programming skills. The former and the latter tend to be the same.

    A pretty manageable article on R and Python in terms of big data is from the DC data community.

    But finally – why R and Python? R is primarily used for visual analysis of structured data sets, such as you already know from an Excel spreadsheet. Corresponding programming packages could complement R. Python is a little more powerful, albeit with the appropriate packages the functionality of both languages overlap. The scene will still argue which tool is more appropriate. Using Python for the analysis of texts are getting really exciting. Essentially, it is mostly a matter of counting words. How often is a corresponding keyword mentioned in a particular text or even more interesting, how often is it mentioned in a specific timetable in the whole web? Since most of the texts can be classified according to one author, and date etc., it is exciting here to see who mentioned what, when, where and why. And that's what makes the data analysis so exciting: text analysis. As mentioned above, interests and motives are the valuable insights as they represent a target of individuals and groups. I might tend to buy more bio in the future or try to travel without a car? Of course, most of us won’t write it down digitally. But who else is active in clubs, google-searching, mailing and shopping online? It's all about your interests!

    Have a nice easy entry case in R and Python offered by Beautiful Data Blog.

    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.


  • 29 Dec 2014 4:39 PM | Bridgette Engeler Newbury (Administrator)

    It’s that time of year. Celebrations and traditions. Endings and beginnings.  Promises and provocations. Reflections and resolutions.  And now that the tinsel, incandescent holly and Santa-shaped shortbread are on sale, the flurry of ‘top ten’ lists will appear as quickly as the hot cross buns do (across supermarkets in the UK and Australia at least).  

    As Jim Carroll says here it’s relatively easy to extrapolate current trends into a ‘Top Ten for 2015’; it’s quite a different matter to look further ahead, as he does to 2025.

    Some of those lists will posit that we’re in an era of innovation, entrepreneurship and technology to transform cities, economies and lives. Spurred on by wearables, rapid urbanisation, smart cities and rising popular demand for access to high-quality (and sometimes sustainable) infrastructure, it all leads to seemingly ‘good’ growth that is assumed to follow globally.

    So I want to highlight Mashable's list of notable innovations in 2014.

    Few of the innovations that improved the world in 2014 will make onto the top tens for greatness in 2015 or beyond, and only a couple might be considered trend-setters. Why, I wonder? Compare it to a list of tech predictions like this one - just who are the incredible innovations on this list intended for? What worldview or model of subjectivity is inscribed in the scenarios and technologies offered by the developers of such marvellous wearables and other remarkable tech wizardry? And who stands to benefit? When you compare this with the Mashable list, it’s pretty obvious that most espouse a pronounced way of thinking about the world and civil society, with rather limited implications for people, planet and participation. 

    It is one thing to reinforce the beliefs, value systems and infrastructures that underpin particular ways of life; quite another to expound the importance of technologies that privilege a few when reliable access to electricity, clean drinking water, somewhere safe to sleep or sanitary facilities are not part of everyday life for too many. I’m not denying the need for or value of innovation, invention or experimentation (that Mashable list embraces all of those) but I am questioning the way value and need are prioritised, and by whom, based on what, and the kinds of futures that are being shaped by the infrastructure, innovation and technology these choices deliver.

    As Andy Hines notes in his latest blog, maybe we could take some time to explore the ‘why’ of values, not just the ‘what’. Because there’s more to life in 2015 than networked information technology. Lasting change has to come from within, whether it’s individual, community or organisation. It won’t come from an app alone or something we plug in.

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