Big Data, Open Data, and the Asymmetry of Information
Anytime you own an asset, be it a building, stock, bond, or even a race horse, you want to measure it and determine how its value has changed in the market. Often this process is consider Asset Surveillance. We might think about it as how firms look at their own assets, but what happens when someone else, uninvited, without permission, monitors your asset? What if they then make that asset information available to other parties, like your competitor or prospective buyer? It can create great economic clashes.
Today, with the development of Big Data via sensors, cameras, and mobile phones, many assets such as real estate, cars, brands, our relationships, and even bodies are being measured without our permission. LinkedIn does this, too, by measuring the value of careers, jobs, and even universities. Such asset surveillance creates new and valuable opportunities for Big Data monetization. It also suggests that some firms and parties are in a position to do the asset surveillance and some are not. There is an asymmetry of information. That asymmetry of information causes various economic problems and opportunities.
The economic concept of asymmetric information is fascinating to me and many … so valuable is this economic concept that research on the topic earned the 2001 Nobel Prize in economics. The idea is that there is an imbalance of power in a transaction when one party has access to more information than the other. It results in buyers not being able to bid as much or sellers not knowing what to ask for an asset. Markets freeze up or at least huge price premia are placed on the uncertainty. Bringing more information to all sides allows for more efficient markets. Buyers and sellers converge. The needed data is available and open. We might even think of the world of Open Data as being built on breaking down asymmetry of information in various markets.
Changes are afoot in the world of data sharing with the creation of Open Data – data that can be used by anyone and for which there are no restrictions on its use. As more people have access to more information at less (or no) cost, asymmetry of information has started to break down. Today’s digital platforms, like apps, mobile phones, Internet pages, and even social networks, enable information to be communicated very quickly in a format that is relevant to whatever decision a party needs to make. Often the data is freely available, which is good to the users of the data.
In the case of Uber, for instance, drivers and passengers alike have access to the same information about the location and availability of – as well as demand for – drivers. That information can affect the outcome of the economic relationship between driver and passenger, both of whom choose to work together (or not) based on the same set of data. Airbnb does something similar with housing.
When asymmetry of information breaks down, markets operate more efficiently. It does not even mean that prices have to fall. In fact, in the case of Uber, it is now possible for drivers to earn premium fares during peak periods, something that was not possible in the past.
I think it will be interesting to see how digital platforms continue to remove the asymmetry of information in our daily decisions. Already Yelp helps us pick better restaurants. Similar models based on digital platforms are on the way in how we select housing, insurance, doctors, and even who to date (as in on-line dating services). In this age of big data analytics, data-driven decision making and information accessibility, symmetry of information will become more demanded and help us match supply and demand.
These important implications of Big Data use in overcoming asymmetry of information and its related economic challenges in the digital economy, and more, are developed in greater detail in my recent book, From Big Data to Big Profits: Success with Data and Analytics. The book examines the evolving nature of Big Data and how businesses can leverage it to create new monetization opportunities. Using case studies on Apple, Netflix, Google, LinkedIn, Zillow, Amazon, and other leading-edge users of Big Data, the book also explores how digital platforms, including mobile apps and social networks, are changing customer interactions and expectations, as well as the way Big Data is created and managed by companies. Companies looking to develop a Big Data strategy will find great value in the SIGMA framework, which assesses companies for Big Data readiness and provides direction on the steps necessary to get the most from Big Data.
Analytics, Asset Surveillance, Asymmetric Information, Automation, Big Data, Big Data Analytics, Big Data to Big Profits, Data Analytics, Data Monetization, Data Products, Digital Platforms, Economic Sciences