Data Science

Data as the New Currency

Our hyper-networked society is producing data at an ever increasing rate. According to IBM research, more than 2.5 quintillion bytes of data are created each day; and more than 90 percent of the world’s stored data was created in the last two years alone. Analyst firm IDC estimates that the digital universe—all digital data created, replicated or consumed—is doubling every two years. By 2020, there will be over 44 trillion gigabytes (or 44 zettabytes) of digital data. This collection of big data translates to new business opportunities, but the beneficiaries are not exclusively enterprises. The use of big data also has the potential to transform the planning and delivery of a range of public services, including transportation and logistics, healthcare and disease control, for the benefit of citizens and societies around the world.

In previous blogs I’ve talked a lot about how the growth of Internet of Things (IoT) is going to be more about services than products. The IoT is yet another force leading us inexorably toward Everything-as-a-Service (XaaS), and XaaS will inevitably lead to more complex services, bundles, options and tailored services that address the needs of individual enterprises and citizens. The IoT will generate massive amounts of data from globally distributed sources and will impact every facet of technology, from devices to regulation, data storage and analysis, all the way to monetization. Never before have we had access to such comprehensive consumer patterns.

The inevitable global adoption of IoT will spawn the monetization of data-as-a-service (DaaS) operations. In an IoT ecosystem, we will track and bill for everything from a one-time feed of a small snippet of data with no analysis to a fully selected, aggregated, sorted and analyzed feed of “thing”-generated data from every part of the planet. We can envisage that most, if not all, data-feed services will be tailored exactly to the specifics of each individual customer. For a customized data feed, this service might have a one-person customer base that doubles as its target market. Service providers are faced with this problem: how do you quickly and economically charge for micro-instances of a service when that service has not been defined – or at least, not defined in the normal traditional sense?

A service might not exist until one customer specifies it, at which point it is immediately enabled by the system. As we all know, setting up a service in a traditional billing system sometimes takes longer and costs more than actually setting up the service in the infrastructure. On the opposite end of the spectrum, setting up tailored or bundled services with simplistic billing systems more suited to billing for stock keeping units associated with widgets also leads to disappointment in the form of an out-of-control product catalog. Neither option is acceptable in this new world of services.

In a data-driven IoT world, behavioral data can be used to design and fine tune public policies and services. Of course, threats to personal privacy (a la Big Brother) have to be addressed for big data to live up to its full potential. For example, traditional consent forms do not easily translate in an era where data sets are used for purposes that were not envisioned at the time that consent was given. Big data is different from other data forms as it depends on mixing information from different sources to derive insights from analysis that can help target new individuals. Clear regulation and policies about data anonymization will have a key role to play. A digital citizen’s confidence in how his information is used and protected in the data era is fundamental to the growth of the economy.

The IoT provides an opportunity to create a new type of transactional relationship between citizens and enterprises where both sides benefit from new services derived from data. For example, the advent of connected vehicles means data is shared in real time between the vehicle and road transport infrastructure, in order to feed intelligent transport systems that can lead to more efficient traffic movement, pollution reduction and an improved fuel economy.

We have to face the fact that if humans are in the process chain, it is not going to be possible to keep financial track of all the services created on the fly by systems in real time. One of the main points behind the IoT is that data will come mostly from devices and not humans, although humans set the policies for gathering the data in the first place. Similarly, we can predict that computers that receive data will be enabled to make decisions based on that information, albeit under guidance and constraints. In most cases, those decisions will be executed by computers who send requests for additional actions out to other IoT devices, again mediated by human-generated policies. Driving the implementation of a billing plan, rates, discounts and commitments could well be executed by policy-driven computers, too.

DaaS gives a service provider the opportunity to gather each nugget of data once and sell it multiple times. Or sell it just once, but only at a premium. The implications of the emergence of an IoT marketplace and where it might take us are impressive. Wherever it leads, the technology now exists to ensure these new business models are successful.


esmeralda-swartzEsmeralda Swartz is CMO of MetraTech, now part of Ericsson. She has spent 15 years as a marketing, product management, and business development technology executive bringing disruptive technologies and companies to market. Prior to MetraTech, Esmeralda was co-founder, Vice President of Marketing and Business Development at Lightwolf Technologies, a big data management startup. She was previously co-founder and Senior Vice President of Marketing and Business Development of Soapstone Networks, a developer of OSS software, now part of Extreme Networks (Nasdaq:EXTR). You can view her other blogs at www.metratech.com/blog.


Photo credit: John-Morgan / Foter / CC BY

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