University of Texas at Austin


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Data Economy

Rajiv Garg & Maytal Saar-Tsechansky

Over the past two decades Internet and communication technologies have changed the way businesses are gaining competitive advantage. More recently with the increased generation and accumulation of data, organizations and individuals have been trying to utilize data in their everyday decisions and actions. Data is enabling individuals to better understand their life, actions, health, schedule, behavior, and more. Data is enabling organizations to learn about their efficiencies, deficiencies, supply chain, employees, customers, and competitive environments, among other things.

data economy article graphicThis quest to exploit data to do better has increased the need for data science and analytics. Data science helps to make sense out of data, understand the hidden patterns, uncover the dynamics, and structure the unstructured world. Data analytics helps take advantage of historical data to develop descriptive and predictive insights by applying machine learning, economic, mathematical, and statistical methods. Enticed by the opportunities provided by structured and unstructured data, corporations have been increasingly investing in both data generation and data analysis.

For example, Google provides all of their products for free, not because they can function at zero cost but because they can utilize consumer behavior in increasing the returns from targeted advertising. Facebook provides us an online platform to stay connected with our friends and family (including those that are distant or were lost), not because they are funded by people interested in achieving happiness from social networking, but because they can help advertisers connect to individuals by presenting products that their social network cares about. Credit card companies enhance their rewards to attract and retain customers despite shrinking margins, not because they want every customer to pay interest when payments are spread over time, but because they can utilize the spending behavior and target individual customers with carefully customized offers from advertisers. Nevertheless, exceptions like Wikipedia provide ever-growing digital encyclopedia for free because they care about social good; but it has been tough such enterprises to survive without monetizing user’s click data.

In this data driven economy, where Internet technologies have reduced loyalties (to some extent), survival strategies for companies depend on their efficiency and effectiveness in monetizing all activities in their value chain. It is not hard to perceive that all information goods will be available to us for free in the near future and companies will monetize their customers’ data. The assumption we are making is that there is still some profit margin to be extracted from goods that need to be advertised to consumers. An opposite stream of thought suggests all products and services being monopolized, resulting in no investment in advertising. In this extreme case, the Googles and Facebooks of the world will start charging a fee for their offerings. More practically (at least in the foreseeable future) we should expect to be somewhere between a perfect competition (especially for information goods) and all monopolies, which will present opportunities for monetizing data.

It is no longer fictitious to imagine homes being controlled by a system that can detect our trajectory towards home and the refrigerator ordering missing ingredients necessary to prepare dinner. The smart refrigerator would possibly select a brand that has provided an offer based on past purchases suggesting repeated selection of competing brand. In this setup, car manufacturer will be profiting from sharing the destination information with the home automation system, the home automation system profits from the refrigerator manufacturer by providing information on arriving home owner, refrigerator manufacturer making money by sharing past purchase information with advertisers, and advertisers expect to profit from having lower customer acquisition cost.

Companies are realizing the need to build strategies around clever use of data and capitalize the interplay between complementing products and services. This emerging data driven economy will change the way companies compete and require differentiations on data science and analytic capabilities. A word of caution - “if you don’t know where you are going you will go nowhere” – build strategies with the right minds before investing too much in big data, so that every piece of data will then mint coins for you.

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