Leveraging Device Data Analytics for Business Growth

There is a virtual tsunami of data that businesses are creating. There is data from oil rigs, aircraft components, traffic signals, medical equipment, utility meters, network logs, GPS systems, mobile devices, check-out counters, video surveillance cameras, even elevators in buildings and the microwave in your home. This data from machines is unveiling nuggets of information that can drive business growth and lower operational costs. All it takes is analytics to unlock the chunks of insight that can give you a competitive edge.

Now, a 2013 Economist Intelligence Report called 'The Data Directive' commissioned by Wipro suggests that 40% of CXOs feel insights from machine generated data will be beneficial for their companies for taking strategic decisions. The findings of the study are exciting. It correlates high-growth firms with data usage. Not surprisingly, the study revealed that 51% of companies collect machine generated data (see figure below). All they now need to do is use sophisticated analytics to parse and transform this very large lump of ordinary numbers into business intelligence and usable insight. Suddenly, rows of numbers can become graphs and charts that tell elaborate stories about the way your business is doing, help define future strategy, and take accurate decisions with regard to products, supply chains and marketing spends.

Leveraging Device Data Analytics for Business Growth

Machine or device data is a relatively new phenomenon, although it must be noted that it is – and was – produced 24X7X365. The distinguishing feature of machine data is that it is a time-stamped record of events, lending itself to highly granular examination. But this data has been largely ignored. Its structured and unstructured nature as well as the fact that it is produced in several different formats makes it unwieldy. Translated, this really means that traditional systems of managing data are incapable of handling it.

But business change is forcing executives to look harder at device data and the tools to manage it. Does device data contain something I don't know? What if I explore the data and find something that can change my business?

A few examples of capturing and exploring data show that there is much to uncover by way of new product insights, new service discovery, increased customer spends and innovative business models:

Can telemetry data from a vehicle help predict when a component will fail? This spells a revolution in servicing as the automobile company needn't call in the vehicle for "routine maintenance" until there is sign of trouble. It can also afford to lower its inventory of spares and order only those that vehicles coming in for service need.

Can telemetry data from a vehicle help shorten insurance claims cycles? Insurance companies report that receiving the first notice of loss within 30 minutes of an accident reduces settlement time and loss adjustment costs, sometimes by as much as US$ 800.

There is much business value hidden in device data (to discover the immediate value of device data to your business, click here ). Primarily, device data can help build smarter systems and better outcomes. To do this requires investments in people, processes and technology. But more than the investment, organizations must have the willpower and energy to adopt new data management practices. How can you build organizational discipline to leverage data? We believe the first step is to ensure you have a business case for data management. What is the revenue it will generate? Which are the business processes that will benefit? How long will it take for the benefits to accrue? When you have the answers, everything else falls into place almost automatically.

About the Author

Jayant Prabhu is General Manager and Global Practice Head for the Big Data Analytics practice, a part of the Wipro Analytics service line. He is responsible for practice strategy and management, business & competency development and thought leadership on leading technologies like Big Data Analytics, Artificial Intelligence, Machine Learning, Internet of Things etc.

Jayant has over 17 years of IT experience around Information Management consultancy, Data Architecture and Implementation road map, Process Modelling, and Design and Implementation of BI & IM solutions around leading product suites. He has advised multiple Fortune 100 organizations on devising strategies to leverage Information as a strategic asset to drive innovation derive competitive advantage and manage costs utilizing leading edge concepts like Big Data, Cloud, and Analytics.

He has also been a regular speaker at leading industry & CXO forums organized by Gartner, IDC, MDM Institute on topics around Big Data Analytics, Master Data Management & Information Management strategies. He has also co-authored whitepapers on Big Data Analytics, Information Governance, Data Monetization etc. that have been published in leading publications. He is one of the founders of the 'Wipro MDM Leadership Council', a successful thought leadership platform that brings together practitioners from several organizations that are or are looking at implementing MDM to drive business transformation.

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