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.
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