As a manufacturer, you want to drive efficiency improvements across your entire operation – innovation, design, sales, purchasing, production, distribution and service. The value contained within your data can help achieve all those objectives, and then some.
The term ‘big data’ may feel relatively new, but manufacturers have been aware of – and indeed, adopting – the concept for decades. However, being aware of something and actively taking advantage of it are two very different things.
By the very nature of their operations, most manufacturers capture a variety of different data and lots of it. Yet, too few have digitised that information and/or leveraged it to gain greater insight and a competitive edge.
In years gone by that may not have mattered so much. Human-focused improvement programmes, such as 5S, six sigma and kaizen, were still delivering healthy gains, and the ability to capture, store, move, manage and analyse large volumes of data was so complex and cost-prohibitive to be out of arms reach for all but the giants of industry.
That time, however, has now passed. Many lean initiatives have successfully been running for years and, although they are still largely beneficial, the gains being generated are more incremental than transformative.
Furthermore, the emergence of cloud and edge computing, advanced analytics, platform-as-a-service and plug-and-play software systems has democratised the power of big data and made it available to all.
To better understand how manufacturers can realise the true value of their data, The Manufacturer spoke with Tim Clark – Head of Manufacturing at one of the world’s foremost analytics and data management service providers, SAS.
How can manufacturers start making better use of the data they already gather?
Tim Clark: This is a great question because it highlights one of the very real challenges businesses struggling with – namely, truly understanding the different types of data being collected.
Once you define what is being captured, match that against the business problem you’re trying to solve, such as increased asset utilisation, greater yield from materials or improved product quality. Now, you will have the what, the when and the why.
Obviously if some or all the data you’re collecting and, in many cases, probably storing for long periods of time, doesn’t help to achieve that objective, then address that accordingly. Fundamentally, capturing, storing, moving and reviewing data all cost money. If you treat each of those activities as a cost-base, you must then ask yourself, ‘Is it worth it?’
Industry 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.
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Almost every company SAS engages with captures a lot of data, but it’s not always the right data, or there’s not enough of it, or it’s not in the right place or format or of the required quality. This isn’t necessarily a bad thing. Having these challenges – and recognising them – are the first steps towards formalising your long-term digital strategy.
Once you’re confident that you’re capturing the right data, how can you step up activities to increase the volume and gain insight quicker? This is where SAS applies an industry-leading capability of edge analytics. SAS can perform analytics where the data is generated, when the data is being moved and when it’s being stored. The benefit of that is twofold. Firstly, it keeps cost down; secondly, driving insight from where the data is being generated.
How can manufacturers effectively bridge the gaps between new digital capabilities and their legacy systems or equipment?
This really comes down to understanding what it is you want to achieve, how you’re trying to achieve it, what data is required, where is that data coming from, and how is that data going to be managed.
That can look daunting, but simplify it down; again, make sure you have the basics right. If it’s too complicated or large, reduce the scope and focus on something more palatable. Simplify it to a point where it’s easily understood and you can see/manage incremental change. Make sure you understand the data you have, how it is stored, that it can be enriched, and then leverage the platform to deliver business value, i.e. you are realising a return, and then apply scale.
Scale of any digital technology is a crucial factor and is so often overlooked; it can be a huge prohibitor of a business progressing along or even starting their digital journey. The key is to make sure you have a platform that can accommodate the type of data you collect, the tools and technology you’ve already invested in and deployed, has the flexibility to integrate seamlessly into your operations, but can also add value at the same time.
How does data enable the creation of new revenue streams?
Rolls-Royce Civil Aviation now generates more revenue from support and services (52%) than from selling aircraft engines (48%), according to Forrester. Here is a company which has successfully leveraged its ability to understand every aspect of a products lifecycle and place a monetary value against maintenance services as a result.
Data-driven insights allows your business to confidently predict how long a product will operate in the field and therefore when maintenance is required. Offering lucrative maintenance contacts provides you with a guaranteed, more predictable revenue stream, allowing you to protect margins because it’s all been forecast ahead of time.
This ‘servitization’ simply would not be possible without digital technology, data-driven insights and advanced analytics. You need the data to offer advanced services, but you can’t provide that service without having insight, and you can’t have insight without advanced analytics.
One of the biggest challenges manufacturers face is finding the time to step back and explore smarter, more efficient ways of working. What advice would you offer?
Many of the businesses I visit have full order books and are understandably focused on getting orders out of the factory door. Almost invariably, however, many of those who claim to not have time are wasting huge amounts of it fighting fires; fires which digital technology can help overcome, eliminate entirely, or identify much earlier before they become major issues.
If businesses could step back they would see that either the fire actually isn’t that big, they’ve been focusing on the wrong area, or they’ve identified the right area but are using unsuitable methods to address the problem.
It all comes back to understanding the ‘why’. If your organisation and everyone within it knows why they exist and what their role is, you’ll find that everything permeates from that.
This article is the second in a series of thought-leadership insights in to how manufacturers can better leverage the power of data.
You can read the first in the series, which sets out the importance of getting the basics in place first, here.
You can also read a case study detailing how one of the world’s largest hard disk drive manufacturers maintained its competitive edge by using big data analytics to augment its existing continual improvement programmes.
To learn more, please contact Tim Clark on:
+44 (0) 161 888 2065
+44 (0) 7979 366 142
