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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

05/08
2013

The Big Data Business Potential for M2M Communications

Forward-thinking companies in a variety of industries are beginning to see tremendous business potential from using machine-to-machine (M2M) communication technologies through the proliferation of Internet-connected devices.

MarchingRobots The Big Data Business Potential for M2M CommunicationsIn fact, IT and business leaders are planning M2M implementations in areas ranging from smart grid energy networks to manufacturing and industrial plant monitoring to patient monitoring in healthcare, according to a recent study by TechRepublic and ZDNet.

Almost half of the survey respondents (48%) say they’re using or plan to use M2M technology for energy-related activities, such as smart metering, or communications between wirelessly-connected grid assets.

Forty-six percent of respondents are using or will use M2M communications for IT and network monitoring applications such as network traffic monitoring, while 43.9% are using or plan to use M2M technology for automotive, transportation, and logistics apps such as vehicle telematics and fleet tracking

Still, there are myriad opportunities for using M2M technologies – and big data analytics – in a wide swath of industries for different purposes.

For instance, a growing number of hospitals and other healthcare practitioners are using M2M data and analytics to track patients’ drug interactions and other aspects of patient monitoring.

Caregivers and insurers intend to use analytics to evaluate clinical outcomes (64%) and performance measurement and management (also 64%), according to a recent study by IDC.

For instance, hospitals, clinics, researchers, and insurers can analyze M2M data from patient drug interactions to help determine when patients are most likely to develop reactions to a particular type of drug (e.g., within the first six hours of initial intake) to train nurses and medical staff on monitoring and procedures for addressing dangerous interaction situations quickly.

Meanwhile, manufacturers also have numerous opportunities for applying analytics to operations.

For instance, sensory data gathered from a plant floor may determine that the bearings used for a manufacturing belt are running hotter than normal or are emitting vibrations that are outside of the normal range.

The use of analytics can help manufacturing leaders determine whether these indicators are symptoms of a pending breakdown.

The manufacturer can then use this information to order and install a part and shift production to another manufacturing line without have to disrupt operations. This is a much more cost-effective approach than incurring a breakdown and having to halt production until a replacement part can be ordered and installed.

Retailers are also finding ways to benefit from the use of M2M data and analytics.

British retailer Marks & Spencer has partnered with Avery Dennison to implement RFID technologies to make its inventory replenishment faster and more efficient. As merchandise is sold in a Marks & Spencer outlet, alerts are sent to the company’s distribution centers to automate the replenishment of merchandise to ensure that popular items are available to customers in store and online.

Additionally, retailers can use analytics against RFID data to glean other actionable insights.

For instance, RFID data that’s gathered and analyzed could inform retail executives whether an apparel combination that’s on sale (e.g., a specific brand of women’s blouses and skirts) is selling well or if certain color combinations are faring better than others.

Executives can then use this information to ensure the right mix of inventory is available for the stores where certain combinations are performing well. Executives can also use these insights to help determine the right mix of items and prices for future offers.

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