The vast amounts of data streaming into corporate networks come from numerous sources including so-called smart machines that use sensors to automatically monitor a wide variety of conditions and generate reams of performance data.
For manufacturers, these Machine2Machine (M2M) interactions hold the potential to reduce cost and boost revenue.
For example, more than 70% of manufacturers are evaluating, planning or putting into place smart technologies for maintenance and optimization of their assets and their customers’ assets, notes IDC Manufacturing Insights.
Moreover, of the companies that have already invested in smart technologies, a quarter are investing from 25% to 49% of their IT budgets, while two-thirds are spending less than 25%, according to IDC.
Over the next three years, manufacturers increasingly plan to use service as a competitive diffentiater and they’ll use smart technologies – such as sensors and data acquisition systems – along with ubiquitous connectivity and big data analytics for long-term profitable revenue and to reduce costs, IDC notes.
Likewise, Aberdeen Research recommends that companies optimize the entire data path “from the device to the data repository,” according to a research report on M2M communications.
Companies that have big data repositories larger than 25 terabytes increasingly view M2M-generated big data as important, according to information Aberdeen has gathered from 348 companies.
In 2011, 41% of these companies ranked M2M-generated big data as important; in 2012, that number grew to be 50%. In 2011, 16% of companies that have data repositories less than 25 terabytes noted that M2M-generated big data was very important; that increased to 28% of companies in 2012.
“M2M adoption is more mature in certain industry verticals such as supply chain, field service and other related areas where granular insight and monitoring is desired,” according to the Aberdeen report. “Other industries have not seen the need or imperative to research and invest in M2M initiatives as the applications for M2M are still being discovered relative to their particular needs.”
In addition, the top-performing and industry-average organizations in the survey indicate higher adoption rates for mobile apps accessing both internal and external M2M data sources, according to the report. However, planned adoptions for mobile M2M data among the lowest-performing companies in the study signifies they’re intent on catching up.
“Taking the vast mountain of data generated by M2M devices and analyzing the data, whether it is past data previously collected, or real-time data, can provide insight into patterns, trends, areas of inefficiency or potential risk,” the report notes.
Aberdeen suggests that analytics and M2M can work together to glean intelligence that can be used to improve operational performance.
It recommends that organizations:
- Evaluate M2M to see if it would benefit the company when integrated into existing business processes
- Consider the cost of an M2M initiative, noting that M2M devices will generate a lot of data that needs to be stored and accessed
- Use analytics on current and historical M2M data to identify trends and issues
- Use insights gathered from M2M analytics to improve workflow and business processes
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