Data Fuels IoT, But is the Hardest Part to Get Right

Data Fuels IoT, But is the Hardest Part to Get Right

To get ahead in the Internet of Things (IoT), a strong data analytics effort makes the difference. A new survey conducted by MIT finds companies with strong analytics capabilities are three times more likely to get value from IoT than are those with weaker analytics capabilities.

Those are some key takeaways from a recent MIT Sloan Management Review research project, “Data Sharing and Analytics Drive Success with IoT,” which finds there’s plenty of optimism about IoT. A majority, 52%, of respondents strongly believe their organization will get value from IoT within three years. However, IoT is still new in town — fewer than 13% of respondents have been actively using IoT for two or more years.

Data is the fuel of IoT, and it is also the hardest part to get right. To get value from the IoT, organizations need to be able rising volumes of data from a large variety of sources. The biggest challenge for deriving value from IoT were data analytics, specifically “handling and analyzing the resulting data from IoT devices,” the report’s authors — Stephanie Jernigan (Boston College), Sam Ransbotham (Boston College) and David Kiron (MIT Sloan Management Review) — state. There is also a need for more analytics talent in organizations; at least 49% of organizations are “analytically challenged.”

IoT dwarfs any data management challenges that have come before it. “IoT devices often provide significantly more data to be managed and analyzed than companies traditionally handle,” the authors state, noting that GE currently collects at least 50 million data variables from 10 million sensors embedded within its machines — “far greater than the data generated by retail and social websites.”

Still, once data analytics is mastered, IoT becomes a significant source of value for the business. Being able to measure return is also a hallmark of well-managed data organizations. Forty-five percent of enterprises with good or excellent analytical capabilities can measure the return on their IoT investments, compared to only 19% of those without good analytical capabilities can do so.

Part of this strong analytical capability is a strong data-sharing culture, the authors add. Ultimately, “creating business value from the Internet of Things is strongly associated with sharing data with other organizations.” The data-sharing requirements of IoT means rethinking the way data is managed across enterprises, they explain. For starters, someone in the enterprise needs to be responsible “for developing, monitoring, and adjusting” data-sharing practices. Plus, there will need to be guidelines on when it’s appropriate to share data, what data should be shared, and who should have access to it.

Data-sharing is already a common practice in the IoT space. Two-thirds of respondents to the MIT survey – all of whom are actively working on IoT projects – collect data from or send data to their customers, suppliers, or competitors. “Sharing IoT data tends to be a two-way street,” the authors observe. “Organizations are as likely to send data to customers, suppliers, and competitors as they are to receive data from them. This exchange of device data across organizational borders deepens existing relationships between organizations and forges new relationships.”

Jernigan, Ransbotham and Kiron urge managers to develop a strong analytics capability; an ability to share data; and prepare customers for an ongoing business relationship with their IoT devices. It all goes well beyond simply managing IoT devices or their data. “As companies gain experience with the IoT, they become enmeshed in a network of organizational relationships that require dedicated resources and management attention. Creating business value from the IoT depends as much on the maintenance of these relationships as on the development and maintenance of IoT devices.”