Making the most of the manufacturing analytics revolution

Posted on 27 Jun 2018 by The Manufacturer

Tim Clark discusses how analytics is improving manufacturing and describes the steps you can take to unlock its full potential.

Digitalisation Analytics Data Digital Big Data - Stock
Analytics gives manufacturers the power to convert their data into actionable insight.

Analytics – the use of mathematics, statistics, predictive modelling and machine learning to find patterns in data – gives manufacturers the power to convert their data into actionable insight.

It is powering connected factories, eliminating supply chain problems and using customer feedback to improve products in real time. Analytics delivers unprecedented understanding of challenges and opportunities, enabling you to not just survive, but also to thrive.

By 2020, 60% of manufacturers will use digital platforms to enhance investments and support up to 30% of revenue [IDC Futurescape: Worldwide Manufacturing 2018 predictions (Oct 2017)].

Therefore, investing now in clean, consolidated data for analysis is vital in the modern hyper-competitive manufacturing environment.

Why has analytics become so crucial?

Manufacturers are often data-rich but insight poor. Complex machinery, systems and their employees generate huge quantities of data, but it is often locked away in departmental silos, where it’s hard to use, let alone usefully process and share.

Analytics helps make sense of your data, see what’s important and informs decision making. It highlights problems, drives efficiencies and reveals new opportunities.

This article first appeared in the June issue of The Manufacturer magazine. To subscribe, please click here.

SAS e-book screenshotIndustry 4.0 is commonly understood as the trend toward automation and data exchange in manufacturing technologies, including cyber-physical systems, the Internet of things and cloud computing.

However, this is often misinterpreted to just mean the automation of basic physical and digital processes. Many manufacturers have already achieved this level of automation. So, they stop innovating, believing they’ve already achieved Industry 4.0.

In reality, Industry 4.0 encompasses so much more. We define it as using data across the entire value chain, and using that data to generate actionable insights and release monetary value.

Download our exclusive free eBook to learn how your business can realise the future of manufacturing today.

Analytics is at the heart of many of today’s exciting technologies. Artificial intelligence’s (AI) value comes from accurately and efficiently analysing large volumes of complex data without fatigue.

It is increasingly essential for forecasting demand, optimising supply chains and automating processes. Yet, AI needs a strong analytical foundation to do its job, and analytics allows AI to process and interpret data and operate without human intervention.

Manufacturers can also benefit from the Internet of Things (IoT), especially connected sensors that generate data from the manufacturing process. Through ‘edge analytics’, analytics is delivered to where data is being streamed from, meaning insights are generated in real time. This makes predictive maintenance possible, leading to cheaper, more efficient production.

Why is analytics important?

Industrial Data Summit: Why does UK manufacturing waste so much of its data? - image courtesy of Depositphotos.
Complex machinery, systems and their employees generate huge quantities of data, but it is often locked away in departmental silos.

Analytics matters because it helps turn a disparate collection of employees, departments and technologies into a dynamic, integrated organisation.

When analytics permeates across operations, it creates a unified ecosystem where knowledge is collected and made available to all business areas. This helps deliver evidence-based decisions, innovation and the best customer service.

Conversely, manufacturers unable to gain valuable insight from data cannot hope to improve or succeed in today’s digital economy.

How do you deploy advanced analytics successfully?

It’s important to understand the challenge before deploying analytics. New insights reveal aspects of a business problem you did not initially appreciate, but first you need an objective, whether it’s to improve performance or product quality, before investing time and resource to integrate solutions.

For example, commercial vehicle manufacturer Navistar wanted to develop trucks that suffered fewer breakdowns than the competition. It started with its employees, applying SAS Office Analytics to help HR teams retain the best talent.

Analytics let them determine which star employees were likely to leave, allowing Navistar to intervene and encourage them to stay.

However, to make analytics work you need support from key decision makers and the employees who will be using it. This requires a strong business case demonstrating the positive impact analytics can have on profits.

Tim Clark, Head of Manufacturing, SASTo get widespread buy-in from staff it’s vital to articulate clearly and simply how analytics can make their work both easier and better.

For more information, please click here to download an exclusive free whitepaper, co-created with The Manufacturer.

Tim Clark, Head of Manufacturing at SAS UK & Ireland –

About SAS

Founded in 1976, SAS is a leading developer of analytics, data management and business intelligence software. It provides the insight needed to make faster, better decisions that benefit businesses. All Fortune 500 companies across 10 different industries rely on SAS.