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Digital Literacy Will Help Manufacturers Unlock Power of Data

Digital literacy and data engineers will be key to manufacturers unlocking the potential of data for their businesses, says the director for industrial digitalisation at the University of Sheffield Advanced Manufacturing Research Centre (AMRC).

Professor Rab Scott delivered the message at ‘Power of data and digital in industry’, at a recent event held to explore initial outcomes and learnings from NextGen, a project to embed low-cost digital technologies in manufacturing companies to drive productivity into manufacturers through digital technology adoption and skills development.

FourJaw’s Chris Iveson and Connexin’s Rikki Coles also spoke at the event, and together with Prof Scott they made a powerful case for how adopting a digitally-focused culture – and unlocking the power of data – can help productivity, save energy and reduce waste.

Prof Scott said ‘digital literacy’ is a crucial first step for manufacturers who want to start their digital transformation journey – and that step is one NextGen can help them take with confidence.

“An awful lot of companies are still confused about whether they need a data scientist or a business analyst – it’s about digital literacy as the first step,”  he told delegates. “Digital literacy is more about understanding what digital skills you need to go and get rather than having those skills yourself. There is a desire and demand for this sort of training and introduction, which we’re offering through NextGen. We’re not going to give you a finished data scientist in six or ten weeks, but at least manufacturers will understand what they need to go and invest in.”

Prof Scott, who is also chief engineer for digital manufacturing for the High Value Manufacturing Catapult network which covers the whole of the UK, warned that as analytics tools continue to become more commoditised – data engineers with domain knowledge will be absolutely critical in looking at, and understanding, a company’s data.

“When we started to talk to the ten companies that signed up to NextGen and asked them what they really wanted – they weren’t quite sure and thought it was a data scientist,” said Prof Scott. “But they need to start not with data science but with data engineers.

“There is a subtle difference. With data science, you take a prepared data set and try and analyse that. But the challenge there is what if you have captured the wrong data, what if it is structured in the wrong way, what if the data has got holes in it, what if it hasn’t been cleaned, what if it is biased?”

“You can analyse all you like but if you haven’t got the right data, in the right format, you still won’t get any answers of value. The true skills are about data engineering –  knowing what data to capture, knowing how to capture, knowing how to structure and knowing how to begin to cleanse it and then to actually analyse it.”

The idea behind NextGen, which is funded by Innovate UK and run by the AMRC, is to enable businesses to leverage a competitive advantage by extracting meaningful insights from data, moving them from a reactive to a predictive business model and helping them to use digital innovation to boost productivity and push towards net-zero. It also seeks to lower the barrier to data science and develop ‘digital champions ‘ in those businesses.

Ten companies took part in the first cohort, including: Stanley Black & Decker, Sterling Machining, ELE Advanced Technologies, ARMEG, CW Fletcher, Cooper & Turner, Sylatech, Magellan Aerospace and Henllan Bakery. They each received a package of support centred around four key areas: FourJaw’s IoT hardware and analytics software to monitor machine utilisation and productivity; skills support through a six-week data science course provided by EyUp Skills Academy; tailored business support with digital tech company Razor; and networking support through a ‘hackathon’ event.

FourJaw co-founder and CEO Chris Iveson said eight of the ten companies who signed up to NextGen were new to the company. One of those taking part is precision machining company, Sterling Machining, which specialises in the extrusion tooling and subcontract machining industries and proudly cites the shaft which closes Wembley Stadium’s roof as one of the products it manufactured.

Sterling Machining was already using FourJaw’s machine monitoring platform on six of its CNC machines, supporting and informing its continuous improvement strategy by driving efficiencies across its factory floor. Through NextGen, it added the FourJaw kit onto another four machines and has since applied it to two more.

In a case study video shown by Chris, Sterling Machining explained how it had seen a number of commercial, process, cultural and efficiency improvements since deploying FourJaw across its factory floor, including improved machine utilisation, going from 70 to 100 per cent in some instances. Other benefits included having more confidence in quoting and understanding what work is most profitable; making informed commercial decisions about hiring resources and buying new machines; understanding the actual time spent on jobs; encouraging friendly competition between machine operators; and improving processes.

In a report by Sheffield tech company Razor, early findings from NextGen show that every company interviewed was experiencing difficulties around utilising different data sets, with 80 per cent having direct challenges in how to actually begin utilising data. Almost two-thirds also said they were struggling to collect the ‘right’ data, or identifying what the right data is.

From the first cohort, 80 per cent said they saw significant opportunity in developing or acquiring new software and systems for their businesses that could solve pains around specific areas of manufacturing such as scheduling, process monitoring, and tooling and breakdown.

The report also shows that 60 per cent of the companies interviewed saw a significant benefit in having specialised dashboards to provide KPIs; while another 60 per cent saw a significant opportunity and benefit in having a central data warehouse that receives and stores a plethora of different accurate data sets.

Early learnings for the NextGen delivery team included being realistic with timescales and not doing too much too quickly; understanding that companies do not always value support which is ‘free’; and that there is still nervousness about Industry 4.0 technologies especially with respect to cyber and data security. These learnings will be used to change and flex the delivery style of the support for future cohorts.

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