Big Data-based Foresight for a Proactive Strategy: a Must-have Tool for Business in the Era of Digitalisation
Alexander Chulok, Director of the HSE ISSEK Centre for S&T Foresight, wrote a column for the Association of European Businesses Quarterly Magazine.
Over the past decade, developed and emerging economies alike have faced a number of global challenges that can hardly be addressed with traditional strategic analytics instruments. Many current economic models and the management practices they are based on have ceased to be relevant because their underlying assumptions are now outdated. In reality, the rate of technological growth is higher than expected, and we can observe how technologically enhanced newcomers are pushing traditional companies out of business. Consumer behaviour (on b2c and b2b markets alike) is difficult not only to predict, but also foresee. Numerous 'semi-fixed' factors now play an important and independent role, such as ethical and environmental issues. Radically changing sources of company competitiveness can turn Big Data into the new oil. Intuitive decisions do not always turn out to be correct (should we go with the flow, or invest in wild cards?). As a result, even the most advanced quantitative techniques fail to guarantee results. We need a smart, agile and comprehensive methodology to ensure the sustainable competitiveness of a business.
Foresight is a science-based systematic method for the identification of potential windows of opportunities and coming threats. It is widely discussed as a new 'cure' for a proactive business strategy, and its roots go back to the 1960s when forecast methods just started to be a must-have for big corporations. Today, modern foresight toolkits include more than eighty instruments from various disciplines, including marketing, management, econometrics, statistics, and even psychology.
Employing different techniques and methods of foresight deeply penetrates into the decision-making process and becomes aneveryday routine for thousands corporations, industries and countries. For example, IBM and Hitachi use science and technological foresight to identify prospective market niches, Shell develops its own foresight for the energy sector through 2050 using scenario methods, and Google’s Chief Futurologist Raymond Kurzweil predicts key future trends through 2100. The European Commission distributed more than EUR 84 billion to priority areas selected during foresight investigations in agro, space, nano, health, urban, transport and other sectors. China developed its national roadmap through 2050 for eight priority 'systems', Japan produces 11th foresight made by the Delphi method (large expert survey), Brazil makes agro and industrial foresight exercise, and Russia has a national S&T Foresight through 2030 approved by the state and including more than one thousand R&D priority areas clustered by 50 topics, including new construction materials, quantum computing and biotechnologies.
A few years ago, a major revision of foresight methods was completed by a global society of experts. It was driven by rising demand from policy and decision-makers for a higher quality of strategic analytics that were evidence-based, proactive and provide the 'user' a full-fledged view: from eagle-eyed to a deep dive into all the details. Moreover, the most interesting and powerful issues for business are becoming increasingly 'multi': multidisciplinary, multiministerial and multicultural, whereas only a few experts could provide such a systemic view and not many models could operate with such complexity. New information technologies, AI algorithms and Big Data ensure the fundamental possibilities for a revolution in analytics.
One of the most powerful systems is intelligent Foresight Analytics (iFORA), which was created in National Research University Higher School of Economics and mentioned by OECD among the world’s top analytical software in 2018. It includes more than 300 million documents, including business and analytical reports, scientific publications, patents and grants, information from market aggregators and top conferences, HR descriptions and vacancies. Using AI technologies such as machine learning and neuronetworks, it constructs what are known as semantic maps for global trends and drivers, patent landscapes, and also reveals various market niches, benchmarks for technologies, perspective professions and even a digital portfolio and networks for individual employees. For example, iFORA shows how such a relevant topic today as IoT is linked with other areas and possible business implementations.
We are currently observing how a new industrial revolution is taking over more and more spheres and areas. It is disrupting traditional sources of business competitiveness and installing its 'code' in the core of economics. All companies are going digital, smart, agile, ethical and environmentally friendly. These changes could be a wild card for those who could not adjust to them, and a boost for new companies. Could we have predicted such changes in the past? Certainly yes, if we listened to the weak signal of future global trends and drivers. Foresight could not give us a 100% guarantee, but it does make the future more structured and investigated.
Generally speaking, there are several groups of foresight results that could be useful for companies. Firstly, this includes all information about global trends in social, science, technological, environmental, ethical and political areas. For some businesses, they could turn out to be a threat, and for others – windows of opportunities (like renewables or the uberisation of the economy). The second group deals with markets, products and services, where we can identify how traditional market niches are changing and what specific characteristics will be in high demand by a customer (for example, products with a high ethical focus). The third group reveals R&D and technologies that could be breakthrough, such as new energy sources or cell editing. By matching the current technological portfolio of a company with the global landscape, we can identify gaps and niches for improving the technological strategy. The last group shows what portfolio of competences and skills should be applied to create certain technologies and penetrate markets.
Nevertheless the 'last word' in the decision-making process is still reserved for humans, as Big Data-based foresight methods can make it more proactive, profound, evidence-based and truly strategically oriented for business needs and the prosperity of society.
Source: AEB Business Quarterly