IoT: Data Analytics Means Everything
Data generated by IoT devices can provide the backbone for digital business transformation, but only if companies are adept at analyzing that data.
“Much of the benefit from IoT is the data,” says Sam Ransbotham, associate professor of information systems at Boston College’s Carroll School of Management and co-author of the research report “Data Sharing and Analytics Drive Success with IoT.” However, 58 percent of respondents to that study believe they need to improve their overall analytics capabilities to optimize IoT benefits and 52 percent want to boost their analytics talent.
“Notably, companies with strong analytics capabilities are three times more likely to get value from IoT than are those with weaker analytics capabilities,” Ransbotham says. He has pointed out that developing the capacity to take advantage of the flood of data from IoT devices to react to opportunities quickly is among the largest and perhaps most difficult issues organizations face.
It’s little wonder, then, that gaining specific expertise in IoT analytics is a concern. As Gartner reports, multiple analytics techniques will become necessary to handle all the incoming sensor data. Currently, “many BI and analytics practitioners lack expertise in the streaming analytics, time series data management, and other technologies used in IoT analytics,” writes the analyst firm’s Christy Pettey.
Comrades in IoT Analytics
Can integrators and VARs help support a business’s need to mine, clean, and assess IoT data; identify high-quality data; and pull out relevant information to derive actionable insights? The answer is yes, though often in partnership with other entities.
For instance, Tata Consultancy Services, a global systems integration, business consulting, and technology transformation and services firm, frequently collaborates with platform providers, co-innovation partners, and data analytics outsourcers to drive data analysis efficiency and accelerate speed to market, according to TCS’ Dinanath (Dina) Kholkar, vice president and global head of analytics and insights. TCS, he says, has built IoT ecosystems by bringing multiple partners together. One example is a partnership between TCS and Mesosphere that will enable TCS to leverage Mesosphere’s data services to offer big data, real-time analytics, IoT, and hybrid cloud solutions to customers on their digital transformation journeys.
When thinking about enhancing the IoT services they can provide to customers, integrators should pay attention to how they can build their own partner ecosystems. It takes a complete team to help companies navigate the journey to Business 4.0, according to Kholkar. A strategic technology adviser, high-quality data scientists, and big data architects and developers can work in partnership with an experienced systems integration team to deliver the analytics value customers want. As Kholkar notes, “There’s really no one-stop shop for these services yet.”
One way integrators can prepare themselves to better support customers’ IoT analytics requirements is to connect with big data vendors such as Cloudera, Hortonworks, and IBM that offer consulting and system integrator partnerships or reseller programs that revolve around their big data platforms. For instance, TCS’ partnerships include one with Cloudera to provide big data analytics to customers. It combines TCS’ deep domain knowledge and engineering strength with Cloudera’s Hadoop distribution, innovation, and expertise to enable customers to leverage data “to make impactful enterprise-wide improvements,” says Kholkar.
Analytics in Action
When it comes to IoT-based analytics, TCS sees repeat demand from industries for use cases including:
- Telematics-based pricing in insurance
- Patient monitoring and home elder care in healthcare and life sciences
- Asset management and equipment monitoring in manufacturing
- Energy management and remote asset maintenance in energy, resources, and telecom
- Shopper assistance in retail
Systems integrators will present their findings to end customers based on the IoT application in question and how the data is being used to inform the business. This comes after working with other parties to enhance data analytics capabilities for these and other scenarios. Ideally, all parties involved, including the customer, technology consultant, integrator, and data analytics partner, understand why the data is needed and how it will be used. They should collectively agree on the best way to review reports based on the IoT data too, says Kholkar.
In the majority of IoT applications, the customer owns and stores (usually in the cloud) all the raw data coming from its IoT-enabled devices, securing it and providing access to authorized partners, he notes. The analytics output based on that data is typically integrated into a larger decision support system that provides alerts or other feedback around issues and opportunities from partners like systems integrators, VARs, and data analytics providers.
In telematics, for example, an insurance company may receive an updated customer driving score from an IoT-equipped vehicle at the end of each trip and use those transactions to revise the premium amount at renewal time. In a manufacturing plant, a manager could be notified in real time if a sensor triggers an alert for a potential failure or overload, Kholkar says. In other instances, findings may not be presented back to the end customer at all. This may be the case when a third-party data analytics provider works with a systems integrator to provide a value-added service or automated action to the end customer.
In order to remain relevant to a growing number of businesses, now is a good time to start putting an end-to-end IoT ecosystem in place, with particular consideration to data analytics. While only about 30 percent of enterprises have yet adopted IoT products, Gartner says, that will rise to more than 65 percent by 2020.
Jennifer Zaino is a freelance writer with extensive experience covering business and technology.