Amid the toughest ever market competition, it is essential to have an accurate vision of the future for a country or corporation have a chance to prosper. A reliable and proven instrument in this field is traditional foresight, an increasingly important element of Marketing 3.0.
Identifying market niches with high potential has undoubtedly been a top item on strategic agendas of developed and developing countries, huge corporations, and rapidly growing companies. Technooptimists believe that the so-called platform, or cross-cutting technologies such as ICT systems, biotechnology, new materials, or advanced manufacturing techniques, will soon transform almost all known markets. And marketing specialists agree that new analytical tools are needed to address the rapidly increasing external turbulence, changes in many traditional behavioral patterns of market participants, and booming neurotechnology, which can be used to get a much deeper insight into household needs.
Only time will tell how drastic the upcoming changes will be. However, no country can afford to forgo attempts at identifying or predicting where the market landscape will experience breakthroughs and what evolution scenarios are possible for conventional industries. Although the BRICS nations – and Russia is not an exception here – joined that race long ago, each has been moving at a different pace, and our country is far from leading the pack.
As it is almost impossible to guess the future from the present, exhaustive knowledge of the future markets and accurate forecasts are not as important for success as the willingness of the key actors in a national innovation system to perceive and absorb disruptive technologies and embrace the new production paradigm (which is often associated with digitalization and Industry 4.0). The public and the attitudes decision makers at every level – who have been largely setting the tone and pace for upcoming changes – take toward innovation have been playing a significant role in such transformations. Those wide-ranging activities can be integrated into a single course with traditional foresight – a tool for shaping the future that has been long and actively used in many countries to handle their governance tasks. The examples include a roadmap for up to 2045 in China, regular industry foresights in Brazil, and a national foresight to be completed in 2018 in South Korea. In addition to national foresights, EU countries have been developing more specific industry and regional foresights. Since the 1970s, 10 national Delphi-based foresights have been carried out in Japan, the latest one focusing on Society 5.0. While Russia has only begun integrating those processes into its set of ‘day-to-day’ strategic measures, some of its innovations and achievements in that field can be justifiably claimed as the world’s best. This shows just how efficient traditional foresight instruments can be in identifying markets with high potential.
What do we need to know about markets? First of all, we obviously need to know who is who: which markets possess high potential, which ones are developing, which ones are dying, and which ones are stagnating. But that is clearly not enough. It is important to understand what global trends are behind the transformation of existing business models and what has triggered that transformation – whether it is technology or social trends, statutory changes, or ethical standards that can play a decisive role.
In recent years, the so-called wild cards, or black swans, i.e. unlikely events of enormous impact, have been increasingly important. Apart from political events – actively discussed by experts for some time already – they include environmental, value, and demographic transformations, which have been rarely viewed in Russia with reference to future markets.
The key to creating a market niche or entering an attractive market is the consumer properties of one’s product or service – the medium between the producer and the demand. But how does one find out what properties will be in the highest demand and pave the way to the highest added value, given that those value chains and the consumer itself are constantly evolving as more and more breakthrough technologies enter the market, disrupting established business models that were clearly dominating just a decade ago? For example, it took only a few years for Airbnb to surpass Hilton in market capitalization, while General Motors, which had spent decades becoming a dominant force in the market, was replaced among the world’s 10 largest companies by the much younger Tesla.
In such circumstances, only very rough estimates, or ranges, can be produced by conventional forecasting approaches, such as econometric modeling, consensus forecasts, or extrapolation. Even scenario analysis, which better structures market uncertainties, cannot be fully relied on – especially when embedded multi-scenario approaches are substituted for a simplified set of two or three options that is used more to justify the basic scenario than to analyze a diversified portfolio of possible events.
Big data analysis, including the methodologies based on artificial intelligence, became an integral part of the strategic consulting discourse in the 21st century and now can open a new era in marketing analytics. However, its key issues also remain unsolved. Those include reliable sources, interpretation of results (not possible without top level experts as yet), and using them to make effective decisions (which largely depends on the governance culture and willingness to rely on a machine rather than own sense).
As a result, the market pull and technology pressure approaches, which have been used separately since the 1970s, are transforming amid the foresight proliferation. Its underlying principles – argumentativeness (supported by big data) and coordination and involvement of key stakeholders – helped create a long-term pool of analytical instruments that can be successfully used to identify or build markets with high potential at every level, from national to corporate. Borrowed from a plethora of adjacent disciplines (sociology, marketing, management, econometrics, modeling) and adapted to the goals and objectives of foresight, they are adding a new twist to the discourse on markets with high potential.
Take Delphi expert surveys. Over their nearly seven decades in existence, they have moved from mass mailing campaigns and manual processing of questionnaires to advanced interactive forms, making it possible to assess a respondent’s expertise using such objective metrics as a citation index or patent activity and not relying on his or her words. Usually, Delphi questionnaires are quite extensive, have many questions, and can be used along with various analytical econometric tools to identify clusters for innovative products or services, taking into account changes in demand and the level of technological preparedness.
Used initially for technology domain structuring, technology roadmaps have become a foresight tool to build complex routes for moving from scientific research to specific market niches and vice versa, showing various technology portfolios necessary to create products and provide services with chosen properties.
A focus on actively engaging the key stakeholders, which certainly include the public, makes foresight an instrument that can be used not only to analyze current and potential demand but also to shape it, regularly pointing out markets with high potential and innovative products and services.
Nearly all leading corporations have integrated foresight tools into their governance routines, using them to create or revise development strategies, define priorities for technology and research support, identify competency centers, and help their employees develop competencies required to remain competitive in future markets. Moreover, some global multinationals have a number of foresight centers specializing in different forecasting functions such as futurology or traditional econometric modeling.
Over the past decade, Russian companies have been actively using foresight to address both mid- and long-term (10-15 years) strategic development and tactical goals, including technology benchmarking and management competency ramp-ups. The practice was pioneered by large state-owned enterprises, primarily in industries whose products tend to have a long life cycle, such as energy, aerospace, and shipbuilding. A few years ago, many private companies, including mid-sized firms, also started looking for different foresight tools to evaluate future scenarios for their priority markets in such fields as health, agriculture, fertilizers, metallurgy, finance, and many others. Both corporate foresight and industry-specific research and technology forecasting centers were established, with the latter under the auspices of certain ministries.
The ‘rating’ approach, which is prevailing in the consulting industry and implies reducing the number of priority areas to something between 10 and 15, has largely created a ‘mental’ trap for decision makers. Why study the 11th trend or market if we have the top 10?
The problem with that approach is the fact that it largely relies on basic prerequisites of the past – low or at least predictable market volatility, a virtually stable cost structure, and gradual, non-disruptive impact of technology. However, the modern environment has set a new standard of strategic forecasting and planning requirements. It goes not from generals to particulars but vice versa. Supported by big data analysis, that inductive maneuver allows for capturing the most important trends and identifying necessary markets and products in a network or cluster view as opposed to hierarchic one.
In Russia, that logic has been implemented within its national research and technology development outlook for up to 2030.
Below are some examples of markets and products with high potential expected to deliver outperformance over the next 10–15 years in a range of industries.
Agriculture: genetically modified and brand new plant types and varieties; precision agriculture, telematic, and human-free technology systems in farming; robotized urban and industrial farming and food manufacturing facilities;
Metals: metal powders, aluminum alloys, and products manufactured using powder metallurgy processes; nanostructured composite metal materials; complex high precision metal products; smart composite metal materials (shape-memory, self-healing, and self-repairing);
Textiles: composite natural fiber materials; smart and electronic textiles; nanofibers; eco-textiles; 3D textile printing;
Chemicals: intermediate products of basic organic synthesis with reduced energy, heat, and resource consumption (green processes); materials and products with reduced toxic and pollutive impact on ocean, sea, and water (light-blue processes); production and use of materials and technologies impacting climate change (deep-blue processes).
The outlook lists more than 170 markets with high potential and 400 traditional markets across 16 key industries. The so-called platform, or cross-cutting technologies, which have been drastically changing the production paradigm and hence consumer properties of products and services, will be one of the most important drivers behind industry transformations.
Among the notable domains are new materials and nanotechnologies. Like ICT systems, they have been penetrating nearly all industries to change cost structures and adapt or create properties on a pro rata basis.
While there is no shortage of traditional or innovative market analysis methods, many questions that are important for decision makers remain Rhetorical.
First, the very essence of market or market niche can hardly be addressed with conventional statistical classifiers – they just fail to catch up with changes in real economic processes. For a number of years, global professional communities have been discussing alternative statistical frameworks, including those utilizing big data analysis.
Second, the obvious need to combine the market and technology approaches in future market analysis proves difficult to address, with the barriers ranging from ‘techies’ and ‘economists’ speaking different languages to complex nonlinear effects of disruptive technology that are unevenly distributed in time but still require estimating.
Third, prioritization and choosing the right focus are of paramount importance. One or two criteria are clearly just not enough. What we need is an intelligent and flexible system that can adapt to evolving value chains, as well as national research and technology, infrastructure, and talent reserves to further implement our expansion strategy by swiftly entering ‘base camp’ markets, and so on.
Finally, predicting what ‘does not yet exist’ – markets with high potential – is a complicated task that requires a complex system to detect weak signals of their emergence – that is, user signals associated with the transformation of existing needs and the appearance of new, business ones reflected in changing business and institutional models that have been effective, with the absence of strict, established industry standards among the possible manifestations.
While helping analyze and predict future markets, traditional foresight can also bring the key stakeholders together to shape them – and be an effective solution.
