Foresight Definition and the the historical context
In his 1985 article on the Harvard Business Review, Prof. Michael Porter presented one of the most significant economic changes of the second half of last century: the evolution from industry-driven economy to knowledge-based economy. The latter challenges the status quo, in three parallel ways: first and foremost, it reshapes the industry structure, by ultimately altering the rules of competition of a sector.
Back in the day IT and Automation increased the power of buyers and raised the barriers to entry in many industries, while at the same time, making companies more agile, and reducing the time-to-market for innovation. In addition to that, the knowledge economy changes the nature of the competitive advantage, from efficiency in the value chain, to bundling and unbundling of activities in the value system. As a matter of facts, in those times we saw emerging new companies with innovative supply chain approaches, like Dell and Charles Schwab. And finally the knowledge-based economy fueled economic changes by promoting a focus on developing new businesses and new business models.
Foresight: a definition
This new economic paradigm required new approaches, new tools and new frameworks. And the implicit focus outside the boundaries of any company, the need to redefine the borders of a sector, and the emerging interest in future-driven innovation scenarios, together created a fertile ground for corporate foresight. In the business context, foresight is a process stemming from the analysis of future conditions, given current and emerging trends, and concluding with the development of creative and innovative future scenarios.
Since becoming a management tool, foresight has been transforming through four stages: Expert-based, Model-based, Trend-based Foresight and Open Foresight.
The table below summarizes the differences (adapted from Heiko, A., Vennemann, C.R. and Darkow, I.L., 2010. Corporate foresight and innovation management: A portfolio-approach in evaluating organizational development. Futures, 42(4), pp.380-393):
|Paradigm||The future is explored through experts||The future is modeled through algorithms||The future is a projection of current and emerging trends||The future can be shared by means of interaction|
|Objective||Future Exploration||Forecasting of the Future||Reacting to the Future||Shaping the Future|
|Process||Collect and compare the experts’ opinions||Statistical extrapolation, computer modeling||Analyze weak signals and early warnings; then project them in future trends and scenarios||Open and continuous dialogue|
|Models, matrices and spreadsheets||Trend-databases,
monitoring systems, Reports
|Scenarios, wild cards,
Foresight and innovation
The four stages, not only reflect the chronological development of the discipline, but also the types of corporate foresights currently in place in companies. Of course Future-Innovators, are more likely to use an Open Foresight approaches, whereas beginners and first-time users are more commonly associated to expert- and model-based foresight. Across the border, two commonalities emerge in companies using foresight processes: foresight has a strong bond with innovation and growth, so it is considered as a tool of the innovation and strategy functions.
In addition to that, firms using the foresight, do so because of four main reasons: 1) demand anticipation, to filter project initiatives based on future demand, e.g., demand for dashboard based navigational systems vs. handheld device navigational systems; 2) better knowledge generation in preparing for innovation rounds, e.g., future benefits, future occasions, future customer personas; 3) better context to their innovation efforts, e.g., assessing the role of smartphone maps as future competitor of dashboard based in-car satnav; 4) identifying better timings for launch, e.g., including a technology in a 5 year roadmap vs. a 10 year one.
Moreover, given that the nature of the innovation process changes from company to company, the role of the foresight discipline adapts to the types of innovation within each company: when innovation is pursued as technological push, foresight is used to identify the critical benefits for positioning the new products or features. So it helps to answer the question on the future usages of blockchain in a specific industry. When, instead, innovation is pursued as a consumer-pull, foresight sets the scene for future consumer insight platforms: by providing knowledge on how the passengers’ experience will evolve in the autonomous driving car in the future. In hybrid and open innovation settings, foresight can be used also for future-oriented evaluation of concepts and new technologies. In this sense, foresight adapts to a firm’s innovation effort, by becoming one of the following: 1) an inspiration for innovation; 2) a platform for future societal needs; 3) a technology roadmapping framework; or 4) an anticipatory intelligence system for future-related decision-making.
Besides the role of the discipline, the type of foresight tools and frameworks used, also limit the scope of the foresight’s impact on the overall innovation output: workshops and expert panels are best suited for incremental innovation, whereas disruptive and radical innovations require more scenarios and vision-oriented methodologies.
In conclusion, foresight is a discipline of many forms, and many tools, but it has a deep and strong bond with innovation.