Essay by Massimo Russo and Tian Feng: “With COVID-19, the press has been leaning on IoT data as leading indicators in a time of rapid change. The Wall Street Journal and New York Times have leveraged location data from companies like TomTom, INRIX, and Cuebiq to predict economic slowdown and lockdown effectiveness.¹ Increasingly we’re seeing use cases like these, of existing data being used for new purposes and to drive new insights.² Even before the crisis, IoT data was revealing surprising insights when used in novel ways. In 2018, fitness app Strava’s exercise “heatmap” shockingly revealed locations, internal maps, and patrol routes of US military bases abroad.³
The idea of alternative data is also trending in the financial sector. Defined in finance as data from non-traditional data sources such as satellites and sensors, financial alternative data has grown from a niche tool used by select hedge funds to an investment input for large institutional investors.⁴ The sector is forecasted to grow seven-fold from 2016 to 2020, with spending nearing $2 billion.⁵ And it’s easy to see why: alternative data linked to IoT sources are able to give investors a real time, scalable view into how businesses and markets are performing.
This phenomenon of repurposing IoT data collected for one purpose for use for another purpose will extend beyond crisis or financial applications and will be focus of this article. For the purpose of our discussion, we’ll define intended data use as ones that deliver the value directly associated with the IoT application. On the other hand, alternative data use as ones linked to insights and application using the data outside of the intent of the initial IoT application.⁶ Alternative data use is important because it is incremental value outside of the original application.
Why should we think about this today? Increasingly CTOs are pursuing IoT projects with a fixed application in mind. Whereas early in IoT maturity, companies were eager to pilot the technology, now the focus has rightly shifted to IoT use cases with tangible ROI. In this environment, how should companies think about external data sharing when potential use cases are distant, unknown, or not yet existent? How can companies balance the abstract value of future use cases with the tangible risk of data misuse?…(More)”.