Four Steps in the Evolution of the Machine Economy – IoT For All
With the fundamental technologies of theMachine Economy IoT, blockchain, and machine learning gathering, analyzing, and storing big data, businesses are turning critical information into actionable insights.
As these complex technologies continue to evolve and fields of innovation unfold, we are beginning to see the convergence of three major trends in the Machine Economy:
Machine-to-Machine (M2M) enables and supports communication between machines and devices through both wireless and wired systems. M2M relates to connecting, remote monitoring, sensing, and actuating devices at its most basic level. Overall, M2M communication, along with Machine Economys underpinning technologies, is projected to rise over thenext five to ten yearsby compound annual growth rates of 10% to 50%.
M2M connectivity will dramatically change the way we think about business assets and the future workforce, along with the skill sets required to succeed in a future automated economy. When machines serve and transact with other machines, the opportunity to create new value arises far beyond optimizing transactions for a single system user but rather for the aggregation of machines across a network.
The Machine Economy majorly impacts the way we design technological solutions. Still, to unleash its full potential, we need to understand where we are in terms of development with realistic expectations of when businesses can program machines to transact and participate autonomously, securely independently, and more reliably than today.
Smart machines are embedded with cognitive computing systems that use articial intelligence and machine learning algorithms to sense, learn, solve, and interact differently without the need for human intervention. Sensors, self-monitoring tools, and communication capabilities enable machines to produce unanticipated results by gathering and analyzing large data sets.
The machines that weve built to support us are now able to do more; improving operational efficiencies, decreasing costs, and mitigating business risks.
IoT, blockchain, and machine learning form the technology stack of the Machine Economy. With the use of sensors and intrinsic knowledge regarding its capabilities and features, self-monitoring machines can record and report on the status of its key components and environmental conditions. Embedded intelligence systems allow machines to automate decision-making and adapt parameters within defined business rules, ordering services like maintenance and repair.
Businesses are moving away from buying machines outright (CapEx to OpEx). Instead, they will see new business models emerge with self-managed assets (servitization) sharing their services in a distributed ecosystem. Business owners will no longer define value through ownership and machine subscription models; pay-per-outcome and real-time leasing will be prevalent. New marketplaces will be established based on the activity of acquiring, providing, or sharing access to goods and services, often facilitated by a community-based online platform to facilitate collaboration.
Spurred primarily by the growth in M2M connections, we are beginning to see a change in economic systems where machines communicate with each other independently, coordinate orders, execute transactions, and conclude contracts. Machines will become self-sovereign agents with their own identity and history. Machine needs and opportunities will primarily be identified by mining and analyzing data from M2M transactions and environmental information such as their condition, location, and performance level. As autonomous market participants, machines will become financial actors in their own right, with bank accounts and payment systems.
Technology is laying the foundation for a future of automated machines, trustless smart contracts, and interconnected sensors all with the end goal of improving human lives.
With the natural progression of technology, we are already well on our way toward the Machine Economy. The majority of businesses are firmly situated between the second and third steps, and we can expect the adoption and impact path to gain momentum steadily. Machines eventually become self-sufficient entities and autonomous market participants, executing end-to-end transactions safely, securely, and more efficiently than in historical systems affected by human error.
The Machine Economy promises to multiply our capacity to work smarter, more efficiently, and seamlessly through technology. The transition from companies selling products and services to selling measurable outcomes will redefine business strategies and the base of competitive advantage. We can simplify and execute precision operations through automation whilst laying the groundwork for more complex products to emerge.
As the Machine Economy becomes more ingrained in every industry, it will be defined by real-time demand sensing, high-levels of automation, and flexible production systems through the pervasive use of intelligent machines to complement human labor (machine augmentation).
Delivering outcomes will require companies to forge new ecosystem partnerships centered on customer needs rather than individual products or services. Although we still have a long way to go, we are already on a path where autonomous machines will have the power to make their own decisions, buy and sell services, and participate in the future economy as a new asset class of market participants.
With the rising importance of data collection, data analysis, and data security, businesses will need to innovate new offerings and expand their capabilities and ecosystems to compete in this emerging marketplace.
In the future, we willown much less(assets and machines) andshare much more(services and information) to create a new order of value where efficiency, productivity, and return on investment (ROI) reign supreme this is the Machine Economy.
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Four Steps in the Evolution of the Machine Economy - IoT For All