Spending on IoT software to reach $53 billion by 2022

IoT software spending will reach $53 billion by 2022, according to consultancy IoT Analytics. The market has grown by an impressive 31% in the last year, driven by the proliferation of connected devices and the growing demand for data-driven insights. There has been strong growth in the number of connected IoT devices, reaching 14.4 billion worldwide. And projections are to reach close to 30 billion active connected IoT devices by 2027.

“We have seen some changes in the IoT software landscape over the last five to eight years,” explains Knud Lasse Lueth, CEO of IoT Analytics. “Some large companies have recently exited the space while most have put their foot down on the accelerator. I wouldn’t be surprised to see several new smaller players capturing a significant share of this market in the coming years,” he added.

Google and IBM  were some of the big players that announced the discontinuation of their services and products in the IoT software market in 2022. Another IT giant, SAP, has also started to retire its IoT services, including SAP IoT Edge.

In all three cases, according to IoT Analytics researchers, the companies have failed to gain significant traction and have begun to fall behind their competitors, such as AWS and Microsoft, which continue to lead in user preference.

This early in the year, the consultancy surveyed 100 senior executives from manufacturing, real estate, retail and other economic sectors in North America, Europe and Asia to better understand the IoT software market. All have purchased and used IoT software in the past year.

The suppliers mentioned by the interviewees are the basis for the map published this week, covering 100 of them, by solution segment.

Despite the withdrawal of large vendors and the strengthening of many others, the IoT Analytics team believes that ongoing technology changes, such as greater adoption of AI, Edge Computing, new protocols and the development of cloud-native software, offer great opportunities for any company to step in and offer a more modern, native software experience.

IoT, AI, cloud and Big Data/Analytics are considered the “big four technologies” that can provide the foundation to connect organizations, generate data and drive smarter operations. Using its sensors, network and analytics, the IoT provides the key tools to automate data collection and generate insights. It is the most important component of the digital stack for the industrial sector, for example.

Revenue opportunities in the IoT ecosystem

Technology adoption requires a healthy ecosystem of buyers, consultants, hardware vendors, technology implementers and talent organizations. Many of these are changing in their ways to support the growth of IoT deployment across all sectors.

Technology providers, for example, are moving away from the traditional model of providing a solution with a charge for the licence, towards a pay-per-use service model.

Monetisation opportunities are generally driven by various data monetisation models, including the following:

DATA AS A SERVICE: in this business model, organisations can collect and aggregate the data generated by IoT devices and sell it to end consumers or data aggregators. End consumers can create their own custom models or algorithms to generate insights from this data.

For example, telecom companies provide aggregated and anonymised customer geolocation data to local governments, enabling city planners to design better traffic management systems and for authorities to establish better “smart city” technology solutions.

The emerging trend of home automation is another example of the “data as a service” business model. For example, many IoT devices collect data from home automation end consumers. This can help consumer goods manufacturing organisations tailor the features of their products or target a specific customer segment to increase their revenue.

INSIGHTS AS A SERVICE: in this business model, organisations can combine internal data (e.g. sales and operations trends and machine performance pattern) with external data (such as company data from third-party platforms or other open source platforms).

Subsequently, these organisations can apply algorithms and or advanced analytics models to derive insights to be sold to end consumers. Insights as a service is a service that provides actionable information and a plan to use it. The service is delivered like any other software-as-a-service product. It is hosted in the cloud and end consumers can subscribe to these services. Some specialized SaaS IoT start-ups are following this path.

PLATFORM AS A SERVICE: organisations create custom and proprietary algorithms to generate enriched and personalised data in real-time, delivered to customers through cloud-based self-service platforms. Supported by built-in custom models, it provides a range of analytical capabilities that enable business analysts to diagnose and uncover key patterns and insights in their data and applications. This model also provides a set of visualization and dashboard capabilities that can enable operators and executives to make quick business decisions and maximize business value. Traditional IoT software vendors have followed this path.

BUSINESS AS A SERVICE: User organizations often invest heavily in capital assets and spend a huge amount on repair and maintenance activities. With the adoption of IoT, these organizations have realized the benefits of reducing these asset maintenance costs. They are also evaluating/starting to explore opportunities to create a formed package using insights from the internal IoT project exercise.

These companies have begun to provide this package of services in the form of business-as-a-service to other market participants facing similar challenges of reducing operational costs. For example, in the case of asset maintenance, organizations have begun to develop the capability to provide maintenance-related services to other market participants.

This is being referred to as ‘business as a service’. And it is becoming popular in large organizations with multiple business groups. These groups can typically spread the cost of building a platform across multiple units. And use the productivity gains to profitably bid to provide operation and maintenance services based on the IoT platform to other companies.

Along with changing mindsets and adopting the right monetization model, adopting new ways of working to leverage IoT as a revenue generator is critical. Many experienced business and technology executives are already working together to reimagine how IoT technology delivers business value and competitive advantage.