IoT data will account for 10 percent of all the data registered globally in 2020, according to IDC market intelligence firm. Yet, adopters of IoT – companies and governments around the world – have just started taking the first steps to maximizing the benefits and capturing potential value of streaming big data.
Naturally, this way is paved with great challenges related to data security and ownership, creating the infrastructure for data sharing and monetization and solutions for data analysis and understanding. 2018 will see how companies, industries, and governments address these challenges and bring up innovative, transformative strategies for the successful application of IoT data.
Reuse IoT Data to Increase Efficiency and Cut Costs
According to McKinsey report, most IoT adopters fail to use their data or derive just a small part of its value. For example, only one percent of data coming from 30k sensors on one oil grid turns into actionable insights.
Moreover, this data is used for tracking online operational issues – monitoring and failure detection, rather than prediction and optimization. Whilst prediction and optimization are believed to unlock the true potential of IoT data and make serious economic impact on the operations across various fields.
Predictive analytics and maintenance powered by big data intelligence take center stage among the key trends of IoT in 2018. It means that companies realize the massive increase in data brings multiple opportunities and are ready to take action and assign investment.
This trend is expected to develop at different levels across various verticals. For example, IoT-enabled manufacturing and clean energy sector start applying big data to transform control and maintenance from “replace and repair” to “predict and prevent.” It helps optimize maintenance resources, decrease breakdowns, and eventually introduce more cost-efficient risk-free operations.
McKinsey estimates predictive models to reduce maintenance cost by up to 40% and decrease equipment downtime by 50% in some industries.
In healthcare, predictive models based on AI analytics of legacy and real-time IoT data are expected to manage increased patient traffic and improve operational efficiency in hospitals in general.
In retail, predictive consumer data analytics unpack limitless opportunities from improved on-demand inventory to data-driven marketing based on customer behavioral patterns and purchase choice.
Obviously, emerging prediction capabilities require tools and services for advanced IoT data representation, visualization and analysis. Today, IoT leaders including IBM and GE already provide platforms for predictive maintenance and automation. In 2018 we will likely see more custom and SaaS solutions in this field.
Access and Share IoT Data
To maximize the value of IoT data and extract as much as 60% of its potential (McKinsey), we need to learn how to integrate and analyze data from many heterogeneous IoT systems simultaneously. In other words, the market needs an open, low-cost data infrastructure where cleansed streaming data is accessible and affordable for mutual benefits. In this case, IoT adopters will be able to see the full picture and make more objective data-driven decisions.
This need hasn’t emerged yesterday. Microsoft, Bosch, Samsung, Cisco, Fujitsu, and Orange are collaborating with IOTA blockchain to launch an open data marketplace that allows any player to get the bits of valuable IoT data for a microfee. This solution represents a novel micropayment business model where IoT-enabled devices are able to initiate financial transactions to get the data they miss from other IoT entities and thus maximize their operation.
In general, an open data market is seen as one of the building blocks of emerging IoT ecosystem. In 2018 we’ll witness the development of this infrastructure. Today, it requires further adoption of blockchain and Tangle technology that secures micropayments and much needed elaboration of data standards.
Most importantly, mutual access and legit and secure sharing of IoT data requires the IoT entities to development new business practices, data ownership policies, and attitude based on collaborating with other IoT entities.
The key challenges, however, remain valid. Companies and authorities are still figuring out the potential of interoperability and shared IoT data, deciding on the investment to deploy an IoT data marketplace, and performing organizational and technical changes to keep up with this pace.
Monetize IoT Data
Despite the proven benefits of applying IoT data, many entities don’t intend to derive value from their data assets simply because they don’t recognize the opportunities. Instead, many IoT-enabled companies and even industries get data as a “byproduct.”
Meanwhile, this “exhaust” data could become a much needed asset for other sectors. For example, the data on the quality of wastewater from production may have little value for the enterprise, but make serious impact on the operation of the nearby hydropower plant.
Monetization of IoT data, including exhaust data, is a brand new model that will make it to the agenda of many decision makers in 2018. Apart from participating in emerging open data markets, companies are expected to rethink their data usage and focus on extracting additional value from their IoT infrastructure. It means turning IoT data to the profit center.
However, many challenges stand in the way of creating these monetization models. First of all, data ownership policies and standards are still unclear. Even today, many IoT development projects don’t clearly define the subject of data ownership and transfer of rights. Policy makers are yet to create standards on data collection, sharing, and use, while consumers are not confident with sharing and donating data. Not to mention the lack of practices for permission-based and public data sharing.
Redesign Products and Services Using IoT Data
Application of IoT data brings up the array of opportunities for redesigning, adjusting, and customizing operations, processes, products, and services across various industries, from vehicle manufacturing to retail sales and digital services. Therefore, usage-based design is expected to expand vastly in 2018.
Recently, Abu Dhabi has enabled adaptive traffic control that applies real-time IoT data from trackers and sensors on the roads and at intersections to ensure smooth traffic flow, prioritize passages for ambulances and emergency vehicles and keep public transport schedule precise. This is the example of how IoT data allows businesses to transform regular operations and increase efficiency.
Usage-based design is relevant for any business process. Application of IoT data can help retailers provide truly custom and timely offers, improve store layouts and redesign products based on usage patterns.
Banks can adjust financial products based on a real-time capital exploitation view. Insurers can provide more agile policies based on real-time conditions of a client’s health or a business’s standing.
Product manufacturers can use performance data to prioritize functionality correction and eliminate underused features, streamline urgent modifications, redesign tasks and jobs, and build a more conscious strategic approach for future development.
Connected IoT systems and emerging interoperability will be able to excel usage-based design. Access to IoT data from other entities will build a more complete picture of how products and services are used. Therefore, we will see more subtle, refined design, workflows and strategies.
According to McKinsey research, IoT will have a potential total economic impact of as much as $11.1trillion per year by 2025. It’s still a long way to go. However, smart application of IoT data today will enable the first adopters to get a share of this volume in the nearest future.