C-Suite manufacturers to prioritise data analytics Manufacturers to prioritise data analytics

Equipment breakdowns are the biggest hinderance to manufacturing revenues, but data analytics can act as a solution

Data analytics, combined with machine learning, can improve manufacturing operational efficiency, and the boardroom has begun to take note

Data analytics, combined with machine learning, can improve manufacturing operational efficiency, and the boardroom has begun to take note

Data analytics can take a number of forms to help reduce the breakdown of equipment.

Trend analysis uses data to monitor if a piece of equipment is moving towards failure, while pattern recognition uses the regularities in data to assess whether an asset will breakdown.

Data analytics, combined with machine learning, can improve manufacturing operational efficiency, and the boardroom has begun to take note.

A survey of 200 executives released today by Honeywell Process Solutions (HPS), a technology solutions company, and KRC Research, exemplifies this boardroom recognition.

67% of manufacturers plan to increase investments in data analytics over the next year, because they recognise its necessity in preventing the future breakdown of equipment.

>See also: The 3 pillars of big data analytics potential

The survey suggests these executives view data analytics – a key component of the Industrial Internet of Things (IIoT) – as a viable solution to a cycle of problems that lead to downtime and lost revenue.

Indeed, 70% of those respondents believe that data analytics can help reduce equipment breakdowns.

“Executives need to keep their businesses running smoothly and safely, and they’re banking on IIoT technologies to help navigate challenges, even during cash strapped times,” said Andrew Hird, vice president and general manager of HPS.

The majority of companies say they are already investing in data analytics technology because they believe it can reduce the main problems that hinder growth and restrict revenue.

Unscheduled downtime was suggested as the biggest threat to maximizing revenue, but 68% of those surveyed believe big data analytics can solve this problem.

Interestingly over a quarter don’t plan to invest in analytics, because they either don’t understand the benefits or don’t have the resources.

>See also: Top 8 trends for big data in 2016

“For some companies, hurdles remain before the IIoT can be fully adopted,” explained Hird.

“Some don’t believe they need it while others say they lack the resources to do it right. The good news is that IIoT is something that doesn’t require a wholesale change – it can be phased and scaled depending on an individual company’s circumstances.”

Data analytics is an extremely useful tool in the digital sphere, and it certainly can help with problems found in the physical world, like the manufacturing industry.

It will be a key component of a successful IIoT implementation for manufacturers moving forward.

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