How data builds supply chain resilience in manufacturing

Greg Sloyer Ph.D., Manufacturing Industry Principal at Snowflake explains how the manufacturing sector can build supply chain resilience with data

Strained global transportation networks and just-in-time manufacturing practices mean today’s supply chains are extremely vulnerable to disruption - and the past few years have offered a stark illustration of how fragile they really are. 

The disruption caused by COVID-19 had very real effects on the world economy, with the pandemic thought to have wiped US$4trn off revenues globally. This year, the war in Ukraine is causing further issues including increased freight costs and product shortages. So how can manufacturers build resilience into their supply chains - and grow their businesses even against a background of continuing economic turmoil? 

The key, quite simply, is data. For manufacturers, a data-driven approach can provide leaner, more sustainable operations and agile responses in the face of disruption and customer demand. To achieve this, there are three key strategies manufacturers can adopt which will enable them to build their businesses even in turbulent economic times: improving supply chain resiliency, powering industry 4.0 analytics, and enhancing the customer experience while generating new revenue streams.

Using data to bolster resiliency in the supply chain

Getting a product manufactured and into the hands of the consumer relies on all parties within the supply chain working with each other seamlessly - which has proven difficult in recent years. Data, such as identifying constraints in raw materials or providing customer and market characteristics can help manufacturers smooth out problems. However, this data often resides on numerous systems, belonging not only to the manufacturer itself, but the ecosystem of third parties it works with, including customers, suppliers, and logistics companies. Collaboration with partners across the ecosystem is a key step in gaining visibility and identifying opportunities for improvement. 

The challenge is to bring that data together to create a ‘big picture’ view of real-time situations. Data needs to be available in such a way that it can be analysed to identify risks and potential hiccups in the supply chain. Crucially, manufacturers also need to share data externally with partners, in a secure and compliant way. By doing so, data sets can be enriched, offering an end-to-end view of the whole supply chain that keeps everyone informed about what’s going on. 

Once this end-to-end view has been established, analytical technologies such as Artificial Intelligence (AI) and Machine Learning (ML) can offer insights in the form of alerts, forecasts and business intelligence recommendations. Insights such as these give businesses the luxury of agility - the ability to proactively spot a problem or predict an outcome, and act on these insights quickly, based on an understanding of the real-time situation. If manufacturers identify an issue, they can alter their plans. For example, switching suppliers or using another material and being able to inform partners of any changes that might affect them. 

Greg Sloyer Ph.D., Manufacturing Industry Principal at Snowflake

A data-driven approach to industry 4.0 and manufacturing

With regards to emerging technologies, manufacturers also have significant opportunities to use data to benefit from the possibilities provided by ‘Industry 4.0’, and become smarter and more sustainable. Key to this is the Industrial Internet of Things (IIoT), with intelligent sensors such as factory-floor machinery, robotics and handheld and wearable technologies offering a deluge of data that, once combined and analysed, can deliver a healthy boost in efficiency and quality to production processes.

However, for too many manufacturers, this data is still stuck in silos, such as supply chain management applications, ERP (enterprise resource planning) platforms and shop floor systems like Historians, MES, QM and control systems. Once combined, this data can be used to perform a huge number of tasks, such as predictive maintenance. This involves taking data from equipment used to predict how it might perform, for example, when machinery breakdown is imminent or a building’s energy use, to formulate plans that take advantage of the right type of energy, at the right cost, to help organisations hit their environmental goals. This will be a priority as we enter the new year, with almost half of British manufacturers (49%) planning to invest in green technologies for energy-efficiency measures over the next 12 months. 


Improving customer experience and harnessing new opportunities in manufacturing

As well as in production, smart, connected products offer manufacturers a huge opportunity to enhance the customer experience using IoT data. Once in use by the customer, these products continue to report back to the manufacturer, providing an opportunity to offer differentiating sales and services, or develop entirely new business models. 

Such benefits are only achievable if the data they generate is collected, analysed and acted upon promptly. To take one example, performance management, most commonly associated with costly industrial equipment, offers manufacturers the chance to launch ‘outcome-based services’, where customers are charged based on factors such as improved uptime or higher output quality. This data offers scope for manufacturers to launch equipment-as-a-service (EaaS) services, where customers acquire equipment flexibly, paying in ways linked to business outcomes. 

Likewise, smart field services which rely on data collected from faulty products, provide service technicians with an idea of what the issue is and which tools and parts they will need, long before they arrive at a customer site. The efficiency of the process results in reduced costs and significantly improved customer experience. 


Meeting the future of manufacturing

There’s no avoiding the fact that manufacturers are facing an unusually challenging economic environment, and in the future will still face a number of challenges. But this doesn’t mean that manufacturers can’t weather the storm and even grow their business. Central to doing so will be all of the data at their fingertips, from sensors on forklifts to point-of-sale terminals in shops - it all holds value. By using the data and sharing it with partners in their ecosystem, manufacturers will build resilience, improve customer experience, and find new revenue streams.


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