The year of 2017 has been full of disruptive ideas that challenged the decision-making environment of not only the policymakers, politicians and business leaders but also the general population. The dichotomy of perception and our inability to face our bigoted beliefs are pushing us to the extremes. The rise of new ideas, movements, and leaders has always given an impetus for innovative approach to address emerging challenges. Such crossroads of social, cultural and political movements historically brought in disruptive ideas - some of which did not survive the test of time and some eventually became the building blocks of our society.
After centuries of Dark Ages or the Middle Ages came the Renaissance. The Treaty of Westphalia that ended the Thirty Years' War was the foundation for modern nation-state. In political decision making the pluralistic ideas and possibilities of large democracies came with the emergence of the United States not only as a country but also as an idea after being ruled by the British Empire. The decision-making process has gone through several disruptive steps as well - the creation of international multilateral agencies and institutions like the League of Nations, the United Nations (UN), Association of South East Asian Nations (ASEAN), North Atlantic Treaty Organisation (NATO), European Union (EU), etc. Similarly, policy analysis for better decision making developed through the use of statistics and mathematical models pioneered by Robert McNamara, J.W. Forrester and Peter Drucker.
Many of the current analytical approaches that were adopted for political decision-making process came from trade, commerce, health and business sectors. The results have been mixed but in general through trial and error these analytical approaches did serve the purpose of improving peoples' lives in earlier decades. In recent decades, it seems even with democratisation of information people in general are not able to influence the political processes and policies. The modern world has created the opportunity for the policy makers and politicians to be disenfranchised from their electorates and has lowered the risk of being accountable.
So how do current political leaders capture the mindset of the commoners for their vote and business leaders continue to retain them as consumers? They do this through innovative use of statistics to comprehend the distinct links among different variables in our lives. In past, some of these distinct human traits and behavioural features were not identifiable easily but they were also not analysed then using computers and mathematical methods of permutations, stochasticity, etc. As this method proved useful, many business entities and countries started to rely on them heavily to make their short-term and long-term decisions.
Moreover, since early 2000 with the advent of social media, smart phone and e-commerce there have been a geometrical jump in data accumulation which is now known as Big Data or Big Data Analytics. Since 1950 until 2000, institutions and individuals working with quantitative analytics for decision making used small sets of data available to them through their specific agencies. Now data mining is a built-in process of e-commerce and social media and makes it possible for large business entities and government agencies to monitor and model a whole society. In some cases, like Google and Amazon, the data accumulated gives them the ability to monitor and forecast behaviours of not a single country but continents across the globe.
Barack Obama during his 2008 Presidential campaign used data analytics to plan micro-targeting strategies all over the United States. The same tactics and more advanced clustering methods were used by Trump campaign to target their probable voting demographics. The same strategy was also used by Narendra Modi in his truly novel election campaign in India. We are now in a world where algorithms can predict an individual's behaviour very accurately within some given set of environments. Hence, groups or individuals with deep pocket can not only buy the data available for sale but also buy service of practitioners who have mastered the art of influencing mass population's decision making process. Maybe we will see this in North Dhaka's mayoral election campaign - the use of data analytics for targeted social media promotion, text messages to local voters and robocalls. Should we not ask how did the candidates' campaigns receive our personal contact numbers? In what ways is our data privacy being violated? Moreover, can data truly provide absolute answers?
Even after using mathematical models that assures statistical certainty there are measurable examples of failures in such forecasting methods. At the end of the day we are building models based on data and the analysis can provide 100 per cent certainty on what the data tell, and you can correlate that to real world application. However, it cannot guarantee that because of data a person will behave like the data. Examples of the fallibility of data and models in most recent times are 2008 financial crisis and Donald Trump winning the US Presidential election.
Next evolutionary step in decision making process needs to integrate stochastic (randomness) process with System Dynamics approach. The data analytics and statistics will be the content while System Dynamics creates the boundary within which one models an issue or problem. This new approach has been used in small-scale demand focus impact evaluation in areas like controlling infectious disease, increasing specific fish population, etc.
Such integration will help us to model an analytical framework that is more attuned to reality rather than overfitting it based on our expectations. The infamous example on fallibility of data models by David Leinweber showed us that overfitting data can show that butter production in Bangladesh can explain 75 per cent of the variation in the S&P 500 movement. So, just having data is not the answer to use data for better decision making. We need to model appropriate environments as well. A model that can replicate dynamics and variables of our society and individuals using a System Dynamics approach and stochastic process needs to replicate one of the significant factors of decision making process - the errors, i.e., our irrationality. If we try to replicate the perfect decision-making model then it would be a grave mistake; in real world humans are irrational and full of errors. From aggregation of billions of peoples' unitary errors and irrational decisions we get our disruptive ideas. We have used stochastic process and System Dynamics for business, health and environmental decisions. It is now time for us to use the same approach for political decision making process as well.
The writer is Archer Fellow, Lee Kuan Yew Scholar
