As enterprises continue to develop and explore opportunities and benefits from IoT through improved business performance and new products and services, additional opportunities in data monetisation are unlocked. These opportunities remain at an early stage as data exchange mechanisms, business models and regulatory frameworks continue to evolve but early trends are emerging.
Identified as a €50 billion worldwide revenue opportunity by the end of 2020, this level of data monetisation is based on enterprises intelligently analysing and managing their ‘new’ data assets in new ways, turning them into ‘data products.’ ‘Data products’ is a well-chosen term by DataStreamX, an innovative data service provider start-up in Singapore. The term reflects the need and requirement by enterprises to manage the process of converting and transforming business data including IoT data into defined data products, available for commercial arrangements.
Data monetisation is not a new concept. What has changed are the significant developments in IoT data, analytics and Big Data. In other articles and reports, Machina Research has addressed the developments of Big Data and Fast Data. These developments are now being consolidated with emerging data exchange mechanisms, business models and regulatory frameworks, and building a solid and growing market opportunity for data monetisation.
Emerging data exchange mechanisms
In June 2015, Machina Research published a report titled, “The Emergence of IoT Service Marketplace: Liquidity for IoT.” These IoT Service Marketplaces (ISM) are significantly more comprehensive entities, allowing niche providers to easily ‘plug-in’ to larger and less differentiated service providers (and vice versa), and one feature of such a ISM could be data brokerage. We are now beginning to see the first real players in this space emerging.
Data brokers are niche service providers enabling the commercial trading of data, and scanning the market, a few such notable service providers have begun to emerge. Whether strictly commercial businesses such as Emu Analytics in the UK, Wot.io in the US or DataStreamX in Singapore or substantially more open and public-oriented initiatives such as Leeds Data Mill or Open Data Bristol in the UK, or the City Data Exchange in Copenhagen, Denmark (enabled by the Hitachi Insight Group), what has become clear is that data exchange mechanisms are beginning to appear on the landscape and enable the managed share of data.
New business models
Data monetisation is set to generate a host of old and new business and commercial models, ranging from simple barter of data sets within Subnets of Things to models where the final value of the data is determined by the generated outcomes of the insight. As a note, Subnets of Things is defined as “an island of interconnected devices, driven either by a single point of control, single point of data aggregation, or potentially a common cause or technology standard,” and where a shared and agreed data community with recognised reciprocal arrangements prevails. Fundamentally, Subnets of Things are based on agreed data exchange mechanisms.
Machina Research has started to identify IoT solutions where these data exchange mechanisms become integral parts of new business models. Compared to earlier data transactions and exchanges, used for historical and descriptive analysis, data exchanges in real-time (Fast Data) have started to impact operational technologies. As these data exchange mechanisms become more and more robust and integrated, the real value of IoT data and analytics will become unlocked.
As an example, in Virtual Power Plant structures, use of data sets from third party suppliers such as weather forecasts systems for impact on wind power generation, or pricing models for energy trading, or ultimately, data about short-term online storage opportunities through electric vehicles are becoming important and crucial aspects of the overall Virtual Power Plant architecture, enabled by data exchange mechanisms.
Compliance with regulatory frameworks
As to the question of which data sets can and will be openly traded, regulatory bodies continue to observe developments in this market space. Where possible, for example within Subnets of Things, the data exchange mechanism established between stakeholders automatically addresses concerns and issues around data privacy and security. In more open, and commercially traded data products, service providers can assist enterprises in ensuring that sensitive data sets or products do not breach defined data privacy and security rights.
Data monetisation, either through architected APIs (Application Programming Interfaces) or data exchange mechanisms and brokers has emerged as a growing marketplace. Enterprise data is no longer confined to the few operational measurements or IT system outputs but has become a substantially growing and developing asset for many enterprises, especially those embarking on the IoT journey with more and more connected devices.
In a world where the physical world becomes increasingly digitised, the opportunity to monetise on generated key data sets as for example the event, location, weather, environment, or image becomes a potential opportunity, and as in any marketplace, what is now emerging is the supply and the demand for the data, potentially growing well beyond the €50 billion worldwide revenue opportunity by the end of 2020.