Future-Proofing the Supply Chain: How Manufacturers Use Real-Time Data to Influence Business Decisions
In the current landscape, maintaining productivity and product quality is no longer a reliable competitive differentiator. Large firms are finding new ways to increase the efficiency of core business operations, strengthen their supply chains and reduce costs through real-time monitoring and analytics. This push towards digital transformation raises an important question: How does real-time data influence manufacturers’ business decisions and long-term stability?
Industry 4.0: The role of real-time analytics
Industry 4.0 has become a catch-all term for the integration of advanced manufacturing systems with the industrial internet of things (IIoT). This union provides greater interconnectivity between operational technologies (OT) and information technologies (IT), more oversight of supply chain activities and a means of turning raw data into evidence-based business decisions.
As far back as 2018, researchers and thought leaders were already championing the benefits of Industry 4.0. However, at the time only 14% of CXOs were highly confident in their organisation’s ability to harness the full potential of these technologies, according to a Deloitte survey. In the years since, digital transformation has become a top priority for manufacturers, with the ongoing health crisis driving new use cases for IIoT, automation and cloud-based management services.
Real-time data offers the insight manufacturers need to optimise their production processes and maintain visibility over key supply chain activities.
Instead of treating real-time monitoring and data analytics as provisional solutions, manufacturers should harness these applications to position themselves for long-term success. The idea of “future proofing” is rooted in a belief that, armed with the right tools and insights, companies can quickly adapt to material changes in their industries, market uncertainties and other sources of disruption. This could be a new pandemic, global economic instability or some other unforeseen crisis.
Here’s a quick breakdown of how real-time data is enabling these predictive capabilities and giving manufacturers a competitive advantage:
Streamlines quotes, pricing and proposals
Manufacturers’ ability to provide quick and accurate pricing quotes is inextricably linked to their selling potential. Companies that rely on manual, paper-based processes often lag behind those that have automated configuration, pricing and quoting (CPQ) systems. The more time it takes to respond to a customer inquiry, the higher the chance another business will step in with a better offer. Using real-time analytics and automation, manufacturers can streamline customer relationships and close more deals.
Improves cost controls and product quality
Per unit pricing, delivery costs and quality control metrics are essential to winning bids from tier-1 original equipment manufacturers (OEMs) and other leading brands. Manufacturers that use real-time monitoring are able to identify supply chain problems and production site inefficiencies that drive up the per unit costs of their products. The same monitoring systems can also help troubleshoot the root causes of process and batch-based quality issues, notes Louis Columbus, senior contributor to Forbes. When paired with statistical process control (SPC) techniques, real-time data can build a stronger foundation for industrial manufacturing and product delivery.
Reduces maintenance costs and unplanned downtime
One of the most common uses of IIoT in the manufacturing sector is for equipment monitoring and predictive maintenance. Every piece of machinery has an average lifespan, but harsh worksite conditions and the stress of fast-paced manufacturing processes can put undue strain on key internal components. In the past, manufacturers operated from a reactive posture and waited for equipment to break down before taking any action. This often led to unplanned downtime, scheduling conflicts and reputational damages.
By outfitting production machinery with IIoT sensors, manufacturers are able to predict when equipment will malfunction before a downtime event occurs. This not only helps protect the continuity of supply chain operations, it also reduces the cost of ongoing maintenance and repair activities. According to one study by the U.S. Department of Energy, predictive maintenance programs provide savings between 30% to 40% over reactive measures. Incorporating these insights into the decision-making process allows manufacturers to stay one step ahead of productivity issues and build trust with suppliers, channel partners and customers.
Stepping into the future of manufacturing
Despite the clear benefits offered by Industry 4.0 and real-time data, stepping into the future of manufacturing requires careful planning and alignment between IT and OT assets. At Unisys, you can build a strong foundation for IT excellence that will remain adaptable in years to come. You will be able to maintain your operational continuity and develop an effective digital transformation strategy that maximises your ROI and minimises risk.
Explore our manufacturing industry resources to learn more.