IoT Maturity, AI & New Value In the Digital Age
Almost a decade ago when those in the industry were explaining what IoT means (it was M2M at that time) and how it would transform many industries and processes, the market reacted with doubts mixed with confusion.
It was challenging for the market to connect the dots between the technological side and the expected long-term benefits of how IoT will eventually scale up and drive the digital transformation, leading to a better outcome for humanity.
Since then, the market perception of IoT has changed to promising, with the dots getting more connected, not only because IoT technologies have significantly progressed, but also because the surrounding digital infrastructures have been developed. Along with enabling evolved technologies, such as AI and ML, innovation and market-driven new business models have moved in the same direction.
Most importantly, industry global awareness and business trust are reaching unprecedented levels.
Throughout the IoT maturity journey, we’ve seen phenomenal growth and successful IoT deployment in the global market where it has accelerated the development process of many economies, and has shown increased profitability, efficiency, and enhanced outcomes.
Global Efforts Are Paying Off
Globally, structured efforts have also successfully taken place to ensure IoT deployments are currently addressing, or have the potential to address key global challenges for humanity. The UN’s Sustainable Development Goals (SDGs) are a perfect example of such an effort.
We’ve witnessed a broad range of proven success stories, from simple IoT farming solutions that enhance the quality and productivity of crops to more advanced sophisticated solutions in sectors such as manufacturing, energy, health, transportation and smart cities.
Although the different IoT maturity stages are region- and market-specific, the characteristics are common across the board. Obviously, the lowest maturity stage is recognized by simple data collection for standalone process improvement. Then, it moves up to the second level of maturity with data aggregation, analysis and integration to achieve measurable and sustainable business value.
The highest stage of maturity is reached when engagement with industries and sectors outside the regular value chain are developed to open up data and drive cross-industry solutions, bundle projects, and create value-sharing mechanisms among partners.
Technologies like AI and ML will play a key role in this highest stage, where the core of the value proposition is best realized in cross-industry and previously unconnected industry solutions.
In this highest stage of maturity, a technology-neutral and comprehensive digital ecosystem is the ultimate goal. Data is contributed, moved, integrated and shared by ecosystem partners, resulting in a sustainable model
This starts in the early design phase of IoT projects, while business models are still maturing.
IoT in Practice
With smart water or electric meters, for example, the data from meters is integrated with data produced by many different sources such as consumer devices, health, mobility, weather, home monitoring, and third-party data sources.
This improves water or energy use and also gives an awareness of consumption and supply at a basic level, and leads to the extraction of other key knowledge-based scenarios. For example, in-home health services for the elderly or hospital patients, a change in usage patterns could indicate a problem requiring health intervention, and inspire new types of citizen-assistance services. Data can also indicate any hazardous, safety, or security conditions for alerts that serve the smart buildings, where early detection of malfunctions can be prevented. Service personnel and resources can be allocated, dispatched, and linked to other new services.
New value can be extracted and expanded to commercial suppliers to create consumer service-based opportunities such as appliances that are charged based on energy consumption.
The same concept applies to industry verticals and domains, including supply management, manufacturing, farming, energy, transportation, smart cities, health, and so on.
Multi-purpose value creation
In a well-integrated connected world, the increasing availability of reliable, secure, high-quality integrated and shared data is certainly shifting the value proposition. This shift will lead to technical, societal, scientific, and commercial innovation that will accelerate digital transformation.
A multi-purpose data-oriented model will become the cornerstone of a value exchange system transforming the way value is created, exchanged, and perceived.
Obviously, issues like data-ownership, privacy, security, anonymization, legacy systems integration, sharing business rules and digital policies, still need to be addressed within their specific industry frameworks, alliances and regulations.
Openness and the cultivation of a collaborative culture are most needed to make the difference,and willbecome indispensable for value creation in the future.
Global, regional and local bridges between business’s own boundaries, industries, partners, institutions, communities are likely become a necessity to shape a sustainable, inclusive, and trustworthy digital future for all.
At this highest level of maturity, we can be certain that the long-term economic benefits coupled with a better outcomes for human well-being will be achieved.
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