How Data Monetization Is Creating a New Data Economy for IoT
How Data Monetization Is Creating a New Data Economy for IoT
The rapid expansion of IoT has paved the way for a new data economy.
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The capabilities of connected technology are expanding rapidly with the trajectory of the Internet of Things moving at a rapid pace, bringing monumental benefits to industries. The ability of connected devices to collect, collate, and analyze data has gone to the next level through the ability of devices to sell and trade everything from storage and computation/analytics to electricity and sensor data. Data analytics can save companies millions in terms of running costs through predictive maintenance insights, waste reduction, and reduced downtime. We've also seen a layer of monetization where connected devices will be layered with various Software-as-a-Service options, from energy cost insights(e.g. knowing a refrigerator is not cold enough or that a home device is using more energy than normal and costing more) to subscription models (e.g. a coffee machine that orders extra coffee beans when running low or a refrigerator connected to a food delivery service).
But we're moving even further — and what's emerging is the evolutionary creation of a "machine economy." This has brought forth a slew of platforms, marketplaces, and trading spaces designed to enable companies to sell or exchange data. Let's look at some noteworthy examples.
Farmobile creates a means to buy and sell farm data. Farmers pay a yearly subscription that includes a passive uplink connection(PUC) — a small, in-cab device that collects machine and agronomic data every second. As farmers work in the fields, Farmobile automatically builds an electronic field record (EFR) of data, including planting dates, commodity, variety, population, harvest dates, total production, average yield, average moisture, and more. Twice yearly, at the end of the planting and harvest seasons, data is certified and placed in a data store for purchase by equipment manufacturers, agronomists, insurers, and other interested parties. Data can be sold multiple times to different buyers each season. Its value compounds year-over-year, providing ongoing monetization opportunities. To date, the PUCs have gleaned data from more than one million acres of farmland.
Last year, the company rolled out its data marketplace, DataStore, the first private digital exchange for machine and agronomic information. DataStore leverages blockchain technology and allows farmers with certified data to receive offers for data and accept or reject them. They also can choose to license their data multiple times, creating a recurring revenue source.
Notably, many emerging marketplaces are using blockchain and related technologies to facilitate a means to buy and sell data. The key benefits posited are the ability to make micro-payments at an extremely low cost via efficient payment methods and immutable records of data transactions. One example is Streamr, which is creating a decentralized means for just about anyone to buy and sell data. Their open-source platform allows data owners to easily connect to the peer-to-peer network to stream their data and also uses blockchain smart contracts and tokens to facilitate transactions and incentivize data exchange respectively. They note:
"Your automobile will soon be producing data about congestion, road quality, and mechanical feedback. If you choose, this can all be sold to highways agencies, fellow drivers, parts manufacturers, and smart city operators who can use it to make automated road repairs, schedule maintenance, and redirect traffic in real-time."
A similar offering is in operation through DataBroker by DataDao. One of their first use cases involved data from shipping containers from the Port of Antwerp. If insurers were able to buy data around temperature and discover, for instance, when the temperature control failed on a ship, they would know when things went wrong and appropriately manage a claim.
They cite another group of potential buyers: academics, scholars, scientists, and researchers who are always in need of accurate, reliable data to back up their scientific research. While data sharing is cited as a means to accelerate science by facilitating collaboration, transparency, and reproducibility, Data Dao notes that data sharing is still relatively limited. Apart from the privacy issues, proprietary aspects, and ethics, there is a lack of training in data sharing, and sharing data is not associated with credit or reward. Data marketplaces mean that researchers who require weather data or data from pollution, power grids, or vehicle telematics can now buy access to a feed from a weather sensor that is already being used instead of having to invest in sensors themselves.
Then, of course, there's the envy of many who wished they got there first: IOTA, with their data marketplace, launched in Nov. 2017. They contend that their public distributed ledger architecture, Tangle, in opposition to blockchain, ensures data authenticity and an audit trail of data as their ledger enables tamper-proof data. Late last year, industrial behemoths Bosch announced that their Cross-Domain Development Kit (XDK) — a "universal programmable sensor device equipped with sensors to measure various ambient data including humidity, noise and light levels, and acceleration" — would now be able to simultaneously collect, upload, and sell data on IOTA's decentralized data marketplace in fully open-source code.
Rest assured, it's not all blockchain — offerings such as Samsung Artik, Dawex, and Terbine do not rely on blockchain technology for real-time data retail. For example, Terbine utilizes IBM cloud, Watson IoT, and AI to facilitate a means to monetize the massive volumes of IoT data available.
The Evolutionary Journey Is Slow and Cautious With More Questions Than Real Answers
In reality, monetized market trading has been rather slow with most companies in pilot mode, building alliances and partnerships for an extended period of time. This makes it easy to generate plenty of questions about data monetization and the role of data market places, specifically:
How will the data marketplaces compare with each other?
How will they leverage their competitive advantage?
What happens to a company's data if an exchange is closed or sold to another competitor?
Can data be sold after the original purchase to a nefarious third party (presumably something the blockchain-embedded marketplaces are claiming to prevent)?
What if a data marketplace is hacked?
How many data marketplaces will proliferate? (Hopefully, it won't be as onerous and the proliferation of competing IoT platforms.)
But what is clear is that we're at the very cusp of IoT providing a new stream of revenue and setting a new data economy — making connected devices more valuable than ever.
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