Foresight Process as a Key Success Factor

Foresight Process as a Key Success Factor

Key Success Factors of a Foresight Program

November 27, 2018, Bruno Jacobsen, Irmeli Hirvensalo

Collecting information that eventually comes to be called "foresight" is a process. Whether we're talking about within a systematic foresight program or in a single project. So what exactly is the "foresight process?"


This article is based on our ebook Key Success Factors of a Foresight Program. Get it for free: Key Success Factors of a Foresight Program (ebook)

Foresight Process as a Key Success Factor

The foresight process refers to the process of collecting, analyzing, and reporting information about specific foresight topics to decision-makers. Ideally, this process is not developed in isolation. It is anchored in the existing information and decision-making processes of the organization.


Indeed, the deliverables (key success factor number 3) that the process yields should feed into the strategic planning process, investment decisions, and innovation activities taking place within an organization. This ensures that decision-making is educated and future-oriented. It also makes sure there is a greater level of awareness within the organization about developments that are relevant to it.


But while there should always be a foresight process, it doesn't necessarily always look the same. Its nature will be slightly different, depending whether the focus is a longer-term foresight program or a single project.


In this article, we cover both. Depending on your situation, you should adopt one process or the other.


Process for a Foresight Program

The main objective of a foresight program is to collect signals and impulses from the world around and processing them into meaningful conclusions about the future.


This means that, for an organization, it's important to have a radar out for any signals that suggest future changes to the status quo. The status quo isn't just defined by what the reality is. It also includes signals and impulses that suggest changes to the organization's expectations of the future (or future scenarios) they have envisioned. These changes have an impact, whether direct or indirect, on a company's strategy built on those expectations. And so this process becomes essential for the company to successfully carry out its vision and strategy.


In the early stages of foresight development, it is usually an individual project that kickstarts the collection of signals and impulses from the company's operating environment. This usually takes the form of a scenario exercise or a trend report. At this stage, this is done on a ad-hoc basis. In other words, it is not yet done with the objective of building a long-term foresight program.


But as this activity is done on a more continuous basis, a program starts to emerge. As the program matures, and horizon scanning becomes more continuous, a "radar" is developed.


The organization begins to may more attention to these signals. These can come from several sources, and can generally be placed into a simple PESTLE analysis: taking into account the political, economic, social, technological, legal, and environmental developments affecting the company.


When the program becomes more robust, information sources begin to matter more. What are the most knowledgeable, accurate, and cost-efficient sources for information on certain topics? Who should keep an eye on them and how? How much will it cost?


Another thing that grows in importance is the organization's ability to analyze the information. Depending on the size of the organization, it will need one or several people fully dedicated to regularly filtering and analyzing incoming signals.


Finally, we are left with the actual deliverables of foresight, which we will cover more in depth in another post. A foresight program has one objective - to turn information about future developments and turn it into something useful and actionable. But the actual form of that "something useful and actionable" can vary.


For some, it may consist of weak signals alerts or trend analyses. For others, it may be early warning systems or the development of alternative scenarios. (We have covered these foresight methodologies and others in a previous article. You can find it here.) Some of these cover the long-term, and therefore are constantly being refined. Others, are actionable immediately - making timely analysis extremely important.


A foresight program therefore has a straightforward process: information input, analysis, and output. Or, in foresight terms, collection of signals and impulses from the environment, analysing the information within the context of future changes, and delivering relevant and actionable output to key decision-makers. As both the signals and the deliverables can be useful immediately, in the short term, or in the long term, this process needs to be done on a continuous basis.


Process for a Foresight Project

A foresight project is in many ways similar to a foresight program. But as it is done within a shorter period and attempts to address a specific question, it is typically divided into 4 phases. In reality, any research project involves going back and forth between these phases. But, for the sake of simplicity, we'll describe them as a cyclical continuum.



1. Scoping the research

A foresight assignment is kicked off by defining the research question(s) related to the situation at hand. An example of a topic could be the following. "What is the future of traffic like, and how can we position our organization to take advantage of the future landscape?"


The scope of the research can vary. From industry to organization, to department. But it generally deals with strategic choices, risk identification, or investment decisions. For that reason, getting the research question right is crucial.


2. Retrieving information from different sources

Most research processes start off with going through readily available published information. This can be either free information online or paid (access to research journals or market intelligence databases). However, not all relevant information is published. So the next step is to complement this knowledge with experts' opinions. In the above example, this could be a series of experts on traffic (planning, technology, vehicles, etc.). In this case, Delphi interviews have shown to be extremely useful. 


3. Analysis and foresight co-creation

Once information has been collected from different sources, it's time to make sense of them in the context of the original research scope.


In foresight, this is best done in groups. Co-creation generally yields much better results.


The information should be brought by those who collected it into a working group consisting of experts, stakeholders, and decision-makers. Often, analysis and its delivery happen in parallel. This is in contrast to a foresight program, where analysis is first "packaged" and then delivered to decision-makers.


4. Documentation and feedback

In foresight assignments, the analysis typically takes place in groups of people workshopping and drawing conclusions together. It is especially important to bring different kinds of expertise and several viewpoints to the table. However, it is equally important to make sure the results don't "disappear" at the end of the workshop.


During and after a workshop, the discussions should be documented into a structured format. It is important that the format makes it easier to later return to the conclusions and be able to make use of them.


In the end...

Whether with the purpose of establishing a foresight program or doing a single foresight project, what matters is that the activity serves organizational decision-making.


What are "good" foresight results? It's wholly determined by how well the foresight output matches the needs of the organization.


And, once we have those results, being able to use them requires that the organizational processes that foresight feeds into are also in good shape. If, on the other hand, they are barely defined or don't even exist, it won't work.


A company can have a crystal ball and not know what to do it with. But more on this on a later post.


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