Chair Professor of Economics, Plaksha University
January 3, 2024
The #datascience revolution is underway, because semiconductor capacity has increased by 33.5 million times over the last fifty years. Fitting more transistors on a chip has accelerated processing speed. According to Moore's Law, the number of transistors on a microchip doubles every two years. While you can stream #YouTube shorts or order #Uber on your phone, Tech companies continue to hoard your data to disentangle the signal from the noise. This allows them to enhance offerings to customers in terms of product quality and selection.
Companies personalize each product’s online presence to match consumer needs, providing customers with attractive and addictive opportunities to choose from, while spending time and money.
Simultaneously, companies are figuring out how many employees to hire, what to pay them, how to automate processes such as marketing and sales support, how much to invest in fixed versus variable capital, and how to spend in the presence of competitors. The revenue earned by a customer’s trust is important , but so are the costs associated for the firm. What ties together this part of data science to the actions that a business takes?
Consumer theory in economics attempts to answer this question for firms about how to spend scarce time and money and maximize utility.
While Economics for the Producer talks about how to maximize profits with the given technology. These topics come under neoclassical microeconomics theory.
But economics is as much about how firms can act strategically as a response to the actions of other firms. This comes under the purview of #GameTheory. Firms and consumers make decisions in a specific macroeconomic environment, and economics enriches our understanding of that environment (financial markets, inflation, unemployment, growth). Courses on #Financialmarkets, #Macroeconomics and #EconomicGrowth enable in-depth understanding of forces acting on demand and supply-sides.
Economics is also about setting up the best models to allow firms to price their products and services. Should a firm offer its product as a PAYG like Uber? Offer advertising for its search service like #Google to maximize profits? Or should it offer subscription like #Spotify? Or should it offer both, like #Amazon? This is in the realm of #IndustrialOrganization in economics.
Furthermore, policy makers, communities and individuals also care about social welfare markers, such as health, education, and equality. Indeed, #Development economics is about how incremental social welfare can be achieved with the right set of interventions. This is in the realm of understanding causal impacts through statistical models.
Finally, economic theory has made deeper strides in understanding how markets (e.g., kidney, marriage, retail) should be organized (e.g., through auction and market mechanisms) for maximizing social welfare. These courses dovetail with designing of algorithms, data mining, pattern detection, machine learning and natural language processing and can help businesses make the best decisions in the interests of customers. Finally, #behavioural economics offers clues to companies about how to make a product more addictive, while also sharing best strategies with consumers to exercise greater self-control and fulfil personal goals.
This complementary approach of economics, when combined with data science, creates the strategic foundations to answer relevant questions for businesses. It also helps build a scalable framework for optimization and causal inference, which can provide a north star to the company’s management while making customer-centric decisions.
#DataScience on its own is a valuable resource and will continue to be in demand. However, combined with #economics, it becomes an irresistible lever for making measurably impactful decisions for businesses, customers and society.
