Manufacturing is an incredibly diverse sector, and it would make sense if not all could expect to benefit equally from a given trend. Big Data – the availability of diverse amounts of information from internal and external processes – is set to drive innovation and profits within the manufacturing sector. But are all factories set up to gain from it?
Alessandro Chimera, Director of Digitalisation Strategy at data analytics and management software vendor Tibco, cautions that data-driven transformation requires planning, a statistical model and a methodology.
It all also takes time: “things need to fail” in order to acquire enough accurate data from which to draw useful conclusions. “Sometimes customers want to jump into predictive maintenance, expecting ‘the miracle of the black box’ that you just attach to the machinery,” Chimera says.
“Brembo (a customer in Northern Italy that manufactures braking systems for the likes of BMW and Porsche) had a lot of data already but didn’t initially know what to do about that.”
Brembo also only had one data scientist – dedicated to marketing. After bringing in another to look into production, data analysis showed that certain machine configurations were not optimal for testing mechanical stresses on braking systems in production. Once that was discovered, revenues lifted by about 25% over “a couple of years”.
Which segments are benefiting from Big Data today?
Customers in electronics, aerospace, automotive, chemicals, pharma, defence, energy, and food and drink are all benefiting from Big Data.
But those retaining highly labour-intensive manual processes may not have the ability to record and analyse data in this way. However, Internet of Things (IoT) kit such as attachable or embeddable sensors are getting cheaper and can connect and collect data from old equipment not originally designed to go online, Chimera says.
Tom Leeson, Senior Manufacturing Industry Marketing Strategist at information management software firm OpenText, confirms that it’s mainly ‘the big guys’ leveraging data to automate processes or accelerate digital transformation across the supply chain.
“Plants like automotive which have multi-tier long-tail, complex supply chains realised very quickly [in the pandemic] that communication was ‘broken’,” Leeson says. “With more digital, you have better visibility across the supply chain.”
Asset monitoring and performance, often performed across multiple geographically dispersed plants, is a key use case in which manufacturers are benefiting from data-driven insights. This goes beyond overall equipment effectiveness and minimised downtime to cover all aspects of business, he says.
Keeping up with change
Volkswagen consumes data from hundreds of manufacturing plants around the world to enable business decisions and agility across its entire supply chain. It has also saved on invoicing via implementing a common process on a single digital platform, says Leeson. “All those manufacturing sites were doing accounts payable differently: that’s another use case within finance,” says Leeson. “The big challenge today is that change is so fast, beyond the capacity of human support.
There are many aspects of manufacturing where humans need assistance simply because of the speed and competitiveness in the market.” Smaller manufacturers could benefit more, however, by teaming up with supply chain partners — on improving sales forecasts via Big Data, for example. “The big guys rely a lot on the smaller ones,” Leeson notes. Oliver Bridge, Director at Grant Thornton, says ‘heavy supply chain’ sectors have more to gain from Big Data.
However, finance teams are increasingly assigned to fix data issues, especially since the pandemic made us more aware of inadequate metrics and reporting. More data literacy is needed, as well as solutions to the challenge of integrating third-party supplier and customer data. “Many find it challenging to either process data supplied in incompatible formats or convince third parties to use their portals,” Bridge notes.
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