27th July, 2020
Megan Doyle

How to Monetize IoT: Data Trading in the Machine Economy

Tags: M2M Communication

The Internet of Things (IoT) is driving digital transformation in business, and many established B2B markets are already realizing the scale of opportunities presented by the technology. 

With rapid developments in data-driven devices, IoT has skyrocketed. By 2025, the global IoT market is predicted to reach $1.6 trillion; an opportunity that companies can’t afford to ignore. 

The early stages of IoT have since evolved from connecting devices to the Internet. The way that individuals and organizations are producing and consuming data has changed with the advent of new technologies. Artificial intelligence and machine learning have led to an era of continuous data gathering, information enrichment, and trend analysis. The next trajectory is to move toward the Machine Economy where devices will enable businesses to trade and sell sensor data and analytics. 

The Machine Economy will establish a new framework for innovative business models to boost profitability with new growth opportunities through machine-to-machine communication (M2M), and the application of blockchain technology, machine learning, and robotics. Characterized by their intelligence, autonomy, and economic independence, future machines will act as market participants in a networked system, executing operational activities with little-to-no human involvement. 

Among the many business benefits of IoT solutions, data is the key resource paving the way for new business models. Organizations must go beyond being market leaders to become functional market makers.

New Monetization Opportunities with IoT

Many companies are investing in IoT, but don’t always have a clear plan for monetization and determining which datasets to monetize or acquire is often complex. 

When planning and developing IoT solutions, monetization should be a clear goal from the start. Companies should consider their strategic objectives, data access and control, ability to consistently collect data, and the data’s exclusivity. Functionally, this means mapping out organizational goals and developing a system to convert collected data into a value-generating business resource:

Data is aggregated and analyzed through an IoT data ecosystem — a collection of infrastructure, analytics, and applications — that turns raw data into actionable insights. Data ecosystems often involve strategic partnerships between businesses that provide related services. In these cases, the largest share of profits goes to the business that builds and controls the ecosystem platform. 

There are two primary ways to monetize IoT data ecosystems:

  1. Using data-driven insights to improve internal processes
  2. Selling data-driven products and services

Organizations already exploring IoT are using data to inform the development of new products and services that enhance customer experience, streamline business processes, and increase market share. For example, industrial equipment can be connected to a digital platform where suppliers create an additional revenue stream by charging customers a subscription in exchange for valuable business insights. This type of monetization system stems from implementing a flexible software-as-a-service (SaaS) model that generates additional revenue on top of the original business offering. 

SaaS solutions are agile, scalable, and configurable, which means that these solutions are easily deployed across various industries. SaaS solutions offer value-added services that form the final layer that enables genuine business value in a data ecosystem.

Designing Data Commercialization Strategies for the Future

In reality, monetized market trading of data has significantly lagged on the uptake with many companies remaining in the proof of concept (PoC) phase.

As we advance toward more complex digital marketplaces, the act of data trading will move beyond human-to-human and human-to-machine transactions to include commercialization mechanisms designed to serve autonomous machine participants. 

Machine participants will evolve in three significant phases of over the next 10 to 20 years

  • Phase 1: Basic
    Machines will purchase specific items defined by a set of programmed rules

  • Phase 2: Adaptable
    Machines make optimized selections among competing offers based on learnings and rules

  • Phase 3: Autonomous
    Machines deduce human needs based on rules, context, and preferences

The real benefits will come from exploiting and creating new business models around the needs and capabilities of increasingly intelligent machines while aligning these models with the needs of society. In the case of machines serving other machines, the opportunity to create and charge for value arises from an aggregation of machines across the network, where billions of devices can trade and sell information.

Many emerging marketplaces are using blockchain technology to facilitate the process of buying and selling data. This enables companies to make micro-payments at an extremely low cost via smart contracts. As a peer-to-peer networked system, blockchain reduces transaction costs to nearly zero, which is good for buyers and sellers because there is no longer a need to pay large service fees to banks, agents, and middlemen.

IoT, and complementary technologies, are making connected devices and intelligent machinery more valuable than ever. We're at the very cusp of data commercialization, and if done right, it will set a precedent for entirely new information economies.

About the author

Megan Doyle

Business Content Specialist at Next Big Thing AG.