Manufacturers to spend US$19.8 billion on analytics by 2026

Friday, 22 May, 2020

Manufacturers to spend US$19.8 billion on analytics by 2026

Manufacturing plants generate mountains of data throughout the day, every day. Traditionally, data has been noted on paper or analysed in spreadsheets. However, today it can be collected automatically via sensors and analysed with tools that far exceed the capabilities of spreadsheets.

ABI Research forecasts that in 2026, manufacturers and industrial firms will be spending US$19.8 billion on data management, data analytics and associated professional services.

“For many manufacturers, there is an appreciation that operational decisions need to be based on empirical evidence rather than guesswork. The challenges are not necessarily capturing and analysing data, rather what to analyse in the first place,” said Michael Larner, Principal Analyst at ABI Research. “The findings need to have a meaningful impact on operations and so manufacturers need to take a step back and devise precise objectives.”

Manufacturers need to engage suppliers to help them prioritise activities and shape projects. For example, is the priority to increase production, reduce waste, improve quality or to fully understand whether a piece of machinery needs to be serviced? Predictive maintenance is critical for avoiding downtime and improving safety on the factory floor. At the same time, video inspection software captures defects with a greater degree of accuracy than the human eye.

Advancements in AI and machine learning mean that suppliers cannot just report data but must also predict outcomes and suggest recommended actions. The orientation for action makes for compelling propositions, and when combined with data visualisation, platforms can embed data in many different roles. The advent of no-code/low-code platforms allows staff not have to be data scientists to utilise analytics in their roles.

“While manufacturers have spent decades refining their physical production lines, today they need to expend effort in optimising their processes for collecting and analysing data. But data should not be collected just for the sake of it,” Larner concluded.

These findings are from ABI Research’s ‘Data Management in Industrial Applications’ application analysis report.

Image: © Stiop

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