As intelligence becomes pervasive, data becomes the ultimate asset

Matt Aslett, Research Director, Data Platforms & Analytics
John Abbott, Founder & Distinguished Analyst

'Intelligence' is the ability to capture, analyze, understand and act on information, including the ability to recognize patterns, comprehend ideas, plan, predict, problem-solve, identify actions and make faster decisions. Traditionally, business intelligence has almost exclusively involved humans analyzing data generated by enterprise applications. But we are now in the midst of a revolution toward 'Pervasive Intelligence,' fueled by self-service analytics, the Internet of Things (IoT), artificial intelligence (AI), machine learning and deep learning, and business process automation tools and techniques – and enabled by the new economics of generating, storing and processing data.

Pervasive Intelligence has the potential to rapidly change the technology product and services landscape. Vendors that are able to translate data into value will survive and thrive. Those that do not will be left behind. We expect Pervasive Intelligence to be a significant catalyst for the rapid evolution of products and services. Those applications and services with the analytics and AI capabilities to translate data into intelligence will succeed, while those without will fall by the wayside. However, incumbent data platforms and analytics vendors hold the best cards due to their established installed customer bases and their substantial cash reserves, enabling them to acquire potential challengers and invest in research and development.

Pervasive Intelligence Data As The Ultimate Asset

Pervasive Intelligence promises to deliver significant change in how products are manufactured, supported, transported and monetized. Data is an asset – for example, Google is the primary owner of the world's search data, while Facebook is the primary owner of the world's social media engagements; both also have the advantage of infrastructure scale to deliver services and applications based on internal and external data.

This is a simplification, of course. Merely owning the data is not enough. In the long term, the sustainable value of the market will flow to those with the ability to enable or own the process of transforming data into profitable business action. Those that own the skillset to exploit the data and deliver it as a consumable service also have the potential to win.

We also believe that the time value of data is a significant driver for Pervasive Intelligence. Many types of data have a shelf life (for instance, weather data), and the utopian scenario is to compress the time between collecting data and taking the right action to zero. Implied, of course, are high degrees of business process automation and trust environments such that users can verify that data is uncorrupted and therefore actionable.

While there are multiple opportunities for generating value from data, a handful of large-scale platform providers will increasingly own significant volumes of data, the infrastructure to process it and the algorithms to exploit it. These platform providers are often well placed to offer data processing and machine-learning services based on their advantage of owning large data sets and the processing power to analyze them.

This raises the potential for disputes – between rival companies, as well as between consumers and companies – over data ownership and portability rights, as well as the prospect of governmental regulation (similar to the GDPR's regulation of the use of personal data). However – as we have previously noted – governmental regulation will be easier said than done, since the traditional tests for monopoly, such as price collusion and price gouging, don't necessarily apply.

Looking ahead: The next 10 years
In the short term, incumbent vendors can be expected to emphasize their ability to deliver machine learning and big-data analytics, and to serve IoT use cases with existing technologies, while making numerous tuck-in acquisitions to fill portfolio gaps. Among 45% of respondents, business intelligence was rated the top IT priority for 2018, according to 451 Research's Digital Pulse survey, followed by machine learning and artificial intelligence (29%) and big data (28%).

However, we expect early adopters will turn to startups, while transformational providers re-architect to serve emerging use cases that cannot be served using legacy technologies. In particular, existing assumptions about data processing locations will erode, driven by the need for data processing and analytics at the edge. Currently, 46% of IoT data is processed at the network edge/perimeter.

Bypassing the bureaucracy of IT departments will become standard procedure for operational technology brownfield enablers, while skill shortages will be an ongoing barrier to the progress of IoT adoption. Data scientists, AI/machine learning, IoT and big data will continue to be in demand and expensive, driving mainstream enterprises to explore managed services.

Further out, we expect incumbent vendors to explore strategic acquisitions and development to re-architect their portfolios, making Pervasive Intelligence a consistent top-three M&A category. We also expect industry consortia to push for greater interoperability across the stack.

Success will be measured through the automation of hundreds/thousands of legacy business processes via Pervasive Intelligence platforms and experience. Although 65% of enterprises expect to increase their spending on IoT projects over the next 12 months, early IoT successes will be narrow in focus, while large-scale projects risk failure as enterprises struggle to adjust business processes to enable business change.

Over time, the data haves and data have-nots will be identifiable. Those with the data will be the winners. Many of the early adopters of Pervasive Intelligence will adopt toward delivering IoT and intelligence expertise via managed services. The flagship mission-critical application portfolios of the past will be transformed, and while incumbent vendors that previously invested in R&D and strategic acquisitions will remain, their product portfolios will likely be, in large part, unrecognizable.
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