Data has already acquired the status of an asset, an integral part of the operations of all businesses and, in many ways, as important to them as financial and human capital.
The insights into the data have given companies like Amazon and Flipkart the tools to break the rules of the game, so even established retail chains have been forced to change their age-old business practices to stay competitive. . It’s the secret sauce that powers Uber’s emergency and rideshare pricing algorithms, and the reason app-based rideshare companies have overtaken the traditional taxi industry. Data-driven decision making will distinguish successful businesses from those that won’t survive the decade.
As an increasing number of companies begin to recognize data as an asset, they have started to make a concerted effort to capture as much data as possible. Large industrial companies like GE are building the Industrial Internet by introducing sensors into every part of the huge machines they build so that they can capture as wide a range of data indicators as possible. This will allow them to use data analytics to optimize performance, reduce equipment downtime and deliver unprecedented quality of service.
Online advertising engines (and the retail businesses they serve) have started deploying advanced browser fingerprinting tools to track user behaviors online so they can more precisely target their products to users. potential consumers. The wellness industry has started to take advantage of the proliferation of wearable devices to collect large amounts of health data from sensors close to the body all the time and run analytics that provide solutions in assisted living spaces. and fitness. Almost daily, we hear about new data collection companies that are using technology in unique ways to collect data sets that until now were beyond our reach. This includes companies like Saildrone, a fleet of driverless sailboats with sensors that patrol the oceans and collect data that can be useful to the fishing industry, marine science, and even global warming research.
It’s not always obvious how we can use these datasets, but if there’s one thing we’ve learned it’s that when you have the opportunity to intersect large volumes of data with hundreds of other previously unrelated data points, the patterns that are beginning to emerge will, more likely than not, offer game-changing information.
Governments have been relatively slow to appreciate the value of data as an asset class. But as more and more of our modern cities are modernized to become ‘smart’, local governments are beginning to discover the benefits of data-driven decision making in municipal governance. They realized that once the sensors are activated and vast volumes of data inevitably begin to accumulate, tools can be built to identify trends and infer patterns in municipal data in the same way we have seen. with consumer technology.
At this point in its development, the benefits of this data-centric approach are not immediately evident, but over time, government decision-making may well evolve from simply using data to make the decision to some form of policing. Predictive that uses the vast data sets are collected to power complex statistical models to preemptively address and solve municipal problems.
The first example of this type of change will likely be the use of data to predict where a crime is most likely to occur and who is most likely to commit it. While this is almost exactly the plot of Philip K. Dick’s sci-fi dystopian Minority Report, it has already come true in various cities across the United States. The Fresno Police Department uses a program called Beware to analyze billions of relevant data points to generate “threat scores” on individuals. It then uses these scores to reach individuals at high risk of committing an offense and warns them, long before they have done anything, that they are under surveillance, hoping to anticipate the occurrence of the crime.
While this Big Brother approach to governance is puzzling, there is something else about these developments that excites me. If data-driven decisions can improve the application of criminal law, could the same principles not be applied to other areas of governance as well? Could we not, for example, use automatic data collection technologies to replace the myriad of legal obligations with which large industrial companies must comply? Instead of forcing companies to report themselves, it should be possible to deploy smart sensors and other data collection tools to allow companies to automatically report compliance. This would remove the tyranny of inspections and license renewals and do more to improve India’s ease of doing business ranking than any legislative amendment.
Rahul Matthan is a partner at Trilegal. Ex Machina is a column on the intersection of technology and law.
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