In his keynote at this year’s Industrial Data Summit, Tim Clark – head of manufacturing at SAS – discussed how to unlock the value of data produced by machines.
Following a morning of roundtable conversations and an expert panel discussion, Tim Clark took to the stage to deliver his Industrial Data Summit 2018 keynote .
According to the Annual Manufacturing Report 2018, more than 90% of UK manufacturers believe ‘smart factory’ technologies will enable them to increase productivity, and a further 85% said they are using digital technology to transform their business.
Furthermore, Gartner has predicted that by 2020, 40% of data science tasks will be automated – resulting in increased productivity and broader usage by ‘citizen’ data scientists.
These findings and many more like them are a strong indicator that data can help businesses improve productivity, process speed and efficiency, Clark noted.
“If we look back in history, we can see notable examples of how a competitive edge became standard,” he continued. “At the 1896 Olympics, Thomas Burke crouched at the start line of the 100-metre dash in the now-standard four-point stance.
“Twelve seconds later, Burke took the gold. The time saved by his starting stance helped him to achieve it and today, sprinters start in this way as a matter of course. This an apt analogy for the business world – you are all looking for that competitive edge.”
Tim Clark spoke at Industrial Data Summit 2018, where almost 100 executive decision-makers gathered to discuss how best to take advantage of and leverage the power of digital technology.
You can read an overview of the day’s discussions, insights, advice and takeaways here.
The Manufacturer has a number of upcoming ‘summits’ which follow the same interactive format:
Your competitive advantage is your data
Every business is searching for an edge over their competition; too few have realised they already have it – their data. They just need to learn – and have the right tools in place – to get more from it.
“Today’s machines don’t just make a lot of noise, they also make lots of sense,” Clark explained. “The machines of today speak to you in real-time, they let you know when they need maintenance, they let you have more capacity, they offer advice, and they could tell you how to make more money.”
Machines have never been so vocal. So, why don’t we talk to them more?
Speaking to machines means understanding what they are saying to you. Furthermore, it means they understand what you are telling them. It means both of you understand what the business wants to achieve.
This sounds complicated, but it can already be done by using the data you already have, but using it differently to drive more value in your operations. As Clark noted, “Speaking to the machines is not simply about descriptive reporting; it’s about getting greater insight and value from your data.”
Putting machines at the heart of the conversation
To bridge the gap between data and value, businesses need to leverage analytics. It’s only through analytics that specific goals and objectives can be achieved, alongside uncovering new relationships, identifying unseen patterns, automating tasks and gaining new understanding of the world around you.
“Analytics is a commonly used term, but what does it actually mean?” Clark asked. “At SAS, analytics allows our customers to focus on the specific business problem through a scalable, trusted analytical platform.
“Big Data isn’t new and we are all aware of the complexities of collecting, integrating and moving data, and this leads to the need to be able to use the right analytics for the right data to achieve the best business outcome.”
The example Clark gave was the Microsoft Office suite. You can make notes and draw tables in Word, Excel and PowerPoint, so why have all three applications? Because they are all very good at specific capabilities and combining them creates a very powerful productivity platform.
Analytics life cycle
“The challenge businesses face is gaining greater efficiency, true control of cost of goods sold (COGS) and driving new revenue streams,” Clark continued. “This can be achieved by leveraging an analytical platform that embraces the analytical life cycle needed to address the verity, velocity and volume of today’s data-driven challenges.”
SAS defines the ‘analytics life cycle’ around the integration of data – structured, unstructured and streaming. The life cycle encompasses every aspect of data discovery and deployment, from data governance and data streaming (IoT), to artificial intelligence and scalability.
“As data is now so pervasive in many operations, the analytical model is only as good as the data being fed into it at the time you feed it in,” Clark said. “Therefore, monitoring a model’s performance or scoring is essential.
“A common mistake is building something once and assuming it’s right thereafter. Modern data-driven businesses have robust but agile analytical frameworks that support the stream nature of data, constantly evaluating and challenging the processes and information being presented. This feeds the strategies around cognitive machine learning and artificial intelligence that will truly differentiate successful businesses.”
Supporting your growth ambitions
The application of advanced analytics around your production, maintenance and supply chain could deliver annual business growth of between 4% – 10%; but achieving that means getting the basics right first.
Ahead of the Industrial Data Summit, The Manufacturer spoke with Tim Clark about how manufacturers could do exactly that. You can read his advice here.
To learn more, please contact Tim on:
+44 (0) 161 888 2065
+44 (0) 7979 366 142