Manufacturers continue to face significant challenges. Cost pressures, complex regulations, learning how to use disruptive technologies and the increasingly costly delivery of goods and raw resources combine with ongoing process and communications changes to muddy visibility across the supply chain.
We’re well into the fourth industrial revolution, described by the World Economic Forum as the “industry’s greatest change in 100 years,” yet years of over-reliance on paper forms and disparate technology systems has contributed to costly transport mistakes and delays for manufacturers. Spreadsheets and paper-based record-keeping are still prominent across many aspects of supply and logistics, making information difficult to trace, confirm and secure.
In a global survey, 84% of chief supply chain officers stated that “lack of visibility” across their supply chain was the “biggest challenge” they are currently facing.
Modern technology provides part of the solution.
Professor Klaus Schwab, founder and executive chairman of the World Economic Forum, describes the Fourth Industrial Revolution as “characterized by a range of new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human.”
Building from past success, today’s leading manufacturers are using these new technologies, like artificial intelligence (AI), analytics and blockchain, to help them improve visibility, avoid disruption, respond more rapidly and build better supply chains.
Improve Visibility to Avoid Disruption
Whether it is a parts shortage or goods stuck in transit, logistics disruptions can quickly cascade to negatively impact entire business ecosystems.
AI-based systems can alert manufacturers to shipment delays in advance, giving them time to initiate a resolution and get ahead of the disruption. This takes trust in new technology to build a better system that will not only avoid disruptions as much as possible, but mitigate those that do arise.
Providing advanced warning to a plant when a shipment is delayed can be predicted through AI tools that incorporate weather conditions, social trends, news, border crossing times based on time of day and day of the week, out-of-stock inventory and any number of other relevant factors. For example, predictive analytics can review more than 3,000 weather and transportation points across an entire delivery cycle, instead of relying on a weather forecast for one or two locations. The system can then mitigate delayed parts by automatically checking inventory, partner inventory and other suppliers, advising the employee and recommending a resolution. Bottlenecks are avoided as the manufacturing process gets reconfigured. Customers can be automatically notified of potential changes or delays.
One computer manufacturer used an AI-powered approach to risk management and shrunk its average response time to supply chain disruptions from days to minutes – up to 90% faster than before. By using AI-based insights to improve visibility across its entire supply chain, this manufacturer was able to complete several business case analyses using supply chain data from its production system within five weeks.
To reinvent its supply chain, first the manufacturer analyzed elements of its business by interviewing divisions, people and examining existing data. This was fed into the AI technology through a process that integrates these viewpoints, improves over time and enables quicker and easier use of the system for employees.
At this point, managers could inquire, ‘What is the impact to the customer delivery if the supply order is delayed?” and insights are gathered and analyzed all in one place to answer the question. Previously, managers would have had to manually query disparate departments including shipping, purchasing, customer orders and manufacturing.
Now, if the supply chain is disrupted, the company can quickly identify which of its orders are affected, determine the potential financial implications and initiate risk mitigation actions. The new process also automatically configures key performance indicators, or KPIs, to help make future planning, purchasing and financing decisions quicker and more accurate. Insights into processes running over budget are also provided before the situation gets out of control.
Maximizing Flexibility with Blockchain
Rapid response and supply chain visibility are hallmarks of today’s globally connected economy. More than ever before, supply chain professionals need complete visibility to any shipment issues, customs challenges or flight delays due to weather. At the same time, supply chain insights need to be completely trusted
Yet, platforms, systems and designations remain separated. Freight forwarders may use a different planning system than a port or end producer. Terminology and the level of detail stored in records may vastly differ. Cultural resistance to new technology may prevent adoption of more reliable methods.
Manufacturers are now turning to blockchain technology, which infuses multi-party visibility, trust, transparency and traceability into the supply chain.
For example, in the mining industry, one supplier we know is already using blockchain to trace an asset from the mine all the way through to the final end user. This transparent and auditable approach efficiently solves the problems of discordant platforms and communication.
In addition, trusted suppliers can be managed and pre-verified through data stored on a blockchain to provide immutable auditability of a supplier’s status and business. Manufacturers who make blockchain essential for managing their supply chain can gain more visibility and security, reduce risks and reduce and mitigate disruptions when they occur.
Better Supply Chains Equal Happier Customers
Using modern technology to build more responsive, resilient supply chains can also help manufacturers improve customer experience by better meeting critical KPI’s such as On-Time/In-Full. New technologies modernize the business network and unlock supply chain data to help businesses access and interpret data such as purchase orders, invoices and shipping notices as they move from supplier to customer across countless supply and logistics channels.
Advanced systems using AI and analytics are available to help give businesses direct access to the data they require in a format they can understand and use. Outputs are clear and actionable within the context of the broader supply chain. The business can understand the full breadth of business data including predictive insights and anomaly detection. This is an advantage over older systems that only allow viewing of individual documents one at a time.
For example, a high end U.S. shoe manufacturer implemented a cloud-based analytics solution to gain better insight into sales and regional preferences and better determine which items to place in which stores to help increase sales, customer satisfaction and loyalty, while at the same time reducing inventory levels. The manufacturer planned its inventory, assortments and pricing using spreadsheets, which became unwieldy as the business grew. They couldn’t glean detailed insights for timely business decisions from their sales, inventory and margin reports.
Today, the company has eliminated the inconsistencies that arise from passing spreadsheets around and has seen a 10% lift in forecasting accuracy and 50% faster reporting processes, and saves at least one day a week on strategic planning.
The shoe production team is rapidly able to adjust operations, whether it is ramping up construction of popular shoes or quickly halting fabrication of items that are not selling as well, giving the manufacturer greater agility during busier periods.
Advanced analytics, AI and blockchain are increasingly helping manufacturers reinvent their supply chains and stay abreast of the fourth industrial revolution’s “fusing [of] the physical, digital and biological worlds.”
Industry analyst Frost and Sullivan has estimated that 35% of global automotive manufacturing plants will be “smart factories” by 2025 as they use information from their processes and operations to help make production more efficient and protect against failures.
This transformation, in automotive and in manufacturing as a whole, is fueling a new era of efficiency, visibility and traceability for manufacturing leaders, contributing to increased customer satisfaction. As manufacturers continue to simplify and strengthen their supply chains through digitization, the path to better visibility across the entire supply chain only becomes clearer.
Jennifer Van Cise is vice president, global sales, IBM Sterling. She has executed change management and Lean Sigma initiatives in multi-facility environments across 6 continents. The scope of her career encompasses managing a $3.3B supply chain, supporting $20B in sales, directing a 2700-member team, and overseeing a $75M budget.
