Monetizing IoT Data with Blockchain

IoT Data

“Data is the most important asset class of current generation”. In Internet of Things (IoT) era, with increasing device proliferation in hyper-connected world, humongous collection of sensor data can facilitate the conversion of incredible ideas into value-adding services. In creating value with data explosion, Blockchain Technologies can play a critical role creating a peer-to-peer marketplace providing IoT sensor owners an opportunity to monetize data and simultaneously enable data consumers with a decentralized market to buy IoT sensor data.

According to Allied Market Research (AMR), the global market of sensors is poised to grow with a compound annual growth rate (CAGR) of 11.3 percent until 2022 when the market would reach $241 billion. The data resulting from such vast reach of IoT sensors is for the primary usage of the sensor owner or it is enhanced with value-added insights and reselling. In both the scenarios of either for primary usage or for enrichment and re-sale, the data remains unacceptably under-utilized and the utility if hindered away in organizational silos. Blockchain can provide a marketplace for IoT sensor data connecting data owners with 3rd party data consumers directly by externalizing the data outside primary silos.

The upside potential arrives from expected growth of todays 10+ billion sensors deployed globally to reach 40+ billion by 2020. Blockchain technology can help monetizing data by creating a marketplace offering a fully built financial ecosystem with a very minimal fees compared to a traditional fiat payment processors who typically charge between 1 and 3% for transactions. Also with creation of data utility tokens offers possibility to use small fractions of the token combined with very low fees making micro-transactions feasible. As well decentralization with blochchain backbone enables a very large numbers of participants in a trustless environment transacting with each other.

As shown in the picture above, a perfect ecosystems can be built for monetizing IoT data with Blockchain technology backbone. The players include sensor owners, data lakes gets created, network providers, blockchian data broker framework, data processers/enrichers, and data consumers / buyers. Sensor owners get an opportunity to monetize their data recovering some of their investments in IoT sensors. Network operators can win-back their enterprise accounts gaining scale and speed in the adoption of their network. This creates new types of buyers offering ease of access to data. Alongside data processors gain an eco-system to sell their services to the right people.

The use cases for such monetization of IoT data can be numerous covering multiple industries. A few examples of described below.

Use case

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Predictive Maintenance Value for Process Industries

PM

Process industries are undergoing digital transformation building and integrating Minimum Viable Products (MVPs) in their strategic path to enabling business models, services, customer experience, operations, and workplaces re-imagination. What I notice across process industry segment is application of industrial internet concepts in creating predictive maintenance models that are yielding advantages including – greater machine availability, superior process quality, easier to plan service intervals, longer machine service life, safer and more sustainable operation, lower service efforts and decreased costs. I am highlighting few aspects demonstrating thought leadership in this space.

  • Companies are sponsoring proof of concepts and pilots for creating models to monetize predictive maintenance. As Predictive Maintenance and Condition Based Monitoring directly impact equipment uptime, by offering Predictive Maintenance as a service, the manufacturer can guarantee equipment uptime to their customers for a fees, i.e. selling value-added services which promise recurring revenue.
  • Process manufacturing is leveraging integrated utilities to reducing electricity consumption with just-in-time energy management with a dynamic platform delivering energy performance improvement with ‘as-a-service’ through edge connectivity of various assets, data acquisition and gateway, cloud-based technology, and analytics. Also include tracking people movement and asset utilization.
  • SRP performance monitoring center using Industrial Internet is another classic example. Since starting the GE Digital’s SmartSignal program in 2012 and through to 2016, SRP identified more than 1,900 issues, of which 800 were “catches” – a problem that the plant was not previously aware of and, with the new alerts, was able to take corrective action. With time and improved training of the algorithms, the rate at which the company identifies true issues and catches has improved.
  • One use case of specific interest to Food and Pharma industry’s glass packaging quality control and improvement is Wi-NEXT IIoT that drives major changes in glass container quality improvement reducing non-conforming products by 7%, which equals 5% extra line productivity, better process control, and higher customer satisfaction
  • Lastly sustainable business models of predictive maintenance includes – bundling within basic service agreement framework, a freemium offering during warranty with downstream revenue potential, offer value added service with pay-per-use model, and gain-sharing with partner ecosystem.

Process manufacturing winners are those who identify best in class practices for developing business models for predictive maintenance of equipment. Win-win scenarios for manufacturers arise from enabling collaboration of experts in this space to exchange ideas, spot trends and drive innovations.