Supply Chain Visibility: Building Resilience Beyond COVID-19

Supply chains have always been vulnerable to disruptions, from natural disasters to geopolitical issues. But supply chains of the modern era have never faced the level of upheaval as the one brought by the COVID-19 pandemic.

“Events like coronavirus are rare,” commented Samuel Mathew, Global Head of Documentary Trade at Standard Chartered, “but the impact of them are so much greater because the world is so interconnected.”

In these past months, the outbreak exposed the vulnerabilities of the decades-old globalization strategy of interdependent and multiple-tier sourcing, driving organizations to take a long hard look at their supply chain strategy for business continuity and growth.

RETHINKING SUPPLY CHAIN VISIBILITY

An often cited example of supply chain disruption is the shortages faced by automotive factories due to the devastating earthquake and tsunami that hit Japan in 2011.

The impact of the natural disasters was not only felt by local manufacturers. International assembly facilities and automotive brands were also forced to stop or slow production due to parts shortages by lower-tier suppliers located in the affected area.

The multi-tiering supply network combined with lack of data and information created a domino effect that spanned across the world. And 9 years later, organizations are facing the same issues brought by a new threat, COVID-19, prompting business leaders to emphasize further on end-to-end supply chain visibility.

• Big Data and Analytics

Management Events’ recent Executive Trend Survey found that 64% of supply chain executives named data science and analytics as their top investment priority for 2021.

The finding corroborates with Oxford Economics’ research study, where 86% of executives believe that supply chain visibility and flexibility can be increased by the use of big data, which some organizations have been investing heavily in.

For example, Georgia-Pacific, a manufacturer of tissue, packaging, paper and other products, is working on a data consolidation project to merge all their data while using a data analytics logistics service to estimate delivery times.

Milind Balaji, Senior Supply Chain Manager at Georgia-Pacific, disclosed that the biggest problem is knowing where the products are, and that real-time insights could help with decision-making on rerouting or storing the shipments differently in the case of unexpected events.

“Supply chains are increasingly becoming data-driven, and businesses that lack visibility into core supply chain functions fall behind when it comes to making informed business decisions.”

– Why End to End Supply Chain Visibility Matters in the New Normal

Quantzig

Data analytics also play a key part in mapping and monitoring global suppliers, allowing firms to keep track of the locations and abilities of tier suppliers and preventing single-sourcing.

General Motors has spent years mapping their supply chains, investing in analytic tools that geocode their suppliers and analyze risks associated with their multi-tier supply chain and impending crises.

This analytics approach enables General Motors to determine, within hours, the impact of a disruption to their supply chain for the days and weeks to come, giving them “lead time to execute avoidance and mitigation strategies.”

McKinsey Global Institute seconded the strategy of mapping suppliers in their recent global supply chain report, mentioning that, “Creating a comprehensive view of the supply chain through detailed subtier mapping is a critical step to identifying hidden relationships that invite vulnerability.”

According to Fred Baumann, the Group Vice President of Global Industry Strategy at Blue Yonder, “[Big data and analytics within the supply chain] give the ability to navigate disruptions months in advance, rather than responding once they have happened. By identifying patterns in what can initially seem unrelated factors, businesses are in a better position to make immediate and effective decisions than ever before.”

• Internet of Things (IoT)

The Internet of Things (IoT) is a game-changer in improving the visibility of every aspect of the supply chain, from shipment tracking to inventory management.

Although the primary use of IoT is still mainly on asset supervision, the emergence of the coronavirus has led business leaders to see the crucial role of IoT in real-time tracking and emergency planning.

• Delivery optimization – While tracking of goods helps companies to determine the arrival and location of the products, the data collected by IoT sensors also enables businesses to identify delays and weak links in their supply chain and optimize their transportation routes for faster delivery.

• Alternative routes – Additionally, IoT allows companies to make fast and data-driven route changes in case of unexpected circumstances, allowing flexible contingency planning and preventing lengthy delays.

• Product monitoring – When faced with logistics disruptions, companies of old had no way to monitor the state of their products. But with IoT devices providing real-time data, companies are able to constantly monitor the conditions of their goods, especially perishable items, in their warehouses and transportation storages.

A prime example of IoT supply chain usage is DHL, which implemented IoT to predict market demand for cost saving and to track their trucks for increased visibility. Back in 2018, DHL launched DHL SmarTrucking in India, which leverages IoT technology for route optimization, predictive analyses, consignment tracking, and container temperature monitoring.

“Using a range of IoT sensor-equipped machinery throughout the supply chain means that potential problems or stumbling blocks can be flagged in real-time. Previously this would cause severe disruptive downtime. Instead, we’re seeing a systemic change in supply chain transparency and functionality.”

– Shio Muriyama, supply chain expert,

 The New Age Of IoT And The Supply Chain

Although global IoT spending has dropped due to the pandemic, IDC predicts that the technology will “achieve a compound annual growth rate (CAGR) of 11.3% over the 2020-2024 forecast period.”

The transportation industry is also expected to achieve double-digit CAGR in IoT spending over the period while the warehouse management market is anticipated to spend more than $19 billion on IoT by 2025.

• Machine Learning

Based on the 2020 MHI Annual Industry Report, only 12% of supply chain executives currently employ AI in their organizations, with 60% expecting to implement the technology in the next five years.

Among the AI subsets, machine learning is often mentioned as a high-benefit technology for efficient supply chain management (SCM), and is also a top focus area for CIOs.

“Machine learning techniques, including a combination of deep analytics, IoT, and real-time monitoring, can be used to improve supply chain visibility substantially, thus helping businesses transform customer experience and achieve faster delivery commitments.”

– Maruti Techlabs

Amazon, for instance, has been using machine learning for automated warehousing and drone delivery while giving its supply chain direct control over areas such as packaging, order processing, support and logistics.

Another giant with a massive product portfolio, Microsoft, employs machine learning techniques to develop a fully integrated supply chain system that captures and analyzes real-time data, and assists in risk mitigation and quick query resolutions.

During the pandemic, customers and businesses alike were faced with uncertainties on order shipments. But companies that modeled their operations with AI handled the disruption better than their counterparts.

“When you’re dealing with a situation like this, where information is changing constantly, machine learning models are very useful,” Bill Waid, the General Manager of Decision Management with FICO, explained in an interview on AI and supply chain. “It can very quickly crunch those numbers and make very informed estimates of what the forecast patterns are looking like.”

In fact, management consulting company, West Monroe, believes that machine learning tools “may eventually make better decisions than even the best supply chain managers.”

• Control Tower Technology

Another rising AI solution for end-to-end supply chain visibility is the control tower – a centralized hub that Gartner describes as comprising data, processes, people, organization and technology for transparency and smart decision-making.

According to IBM, the concept has been around for more than a decade, but is getting increased attention from business leaders looking to effectively manage complex and siloed supply chain systems.

“In these volatile times, supply chain visibility and control have never been more important. Control tower concepts and data analytics capabilities must be upgraded to meet new demand patterns, support growth opportunities, and manage greater external risks.”

– Alexander Gunde, President of Global Technology Sector at DHL,

Post-Coronavirus Supply Chain Recovery

While control towers help to achieve greater efficiency and agility, there are many control tower options with distinctive capabilities and key differentiators, such as uncovering hidden costs, order optimization, and logistics management.

Hence, businesses seeking to implement control tower solutions need to have a clear purpose and defined function for the technology, whether it’s supply-chain visibility, scenario planning or alerting.

Supply chain management information resource, SupplyChainBrain, stated that, “Too often organizations aren’t clear on the scope of the control tower solution, the key functions that are included, and the span of control for the particular solution. That’s why control towers often fall short of expectations and benefits realization.”

The IBM Sterling Inventory Control Tower, for example, focuses on inventory management and provides a single almost real-time view of an organization’s inventory, including product availability, shortages, supply-demand imbalances, and supplier orders. The solution enables inventory visibility across the supply chain while identifying external impacts for faster response and better customer experience.

As control towers vary in definition and capability, supply chain leaders need to ascertain the right time for them to invest in the technology.

Christian Titze, the Research Vice President at Gartner, advises that, “A control tower only makes sense when the supply chain organization already has a certain degree of cross-functional integration in place — internally and with business partners. Otherwise, the tower won’t be able to observe enough signals to support accurate decision-making.”

ACHIEVING SUPPLY CHAIN GOALS

The development of data, IoT, machine learning and control tower in supply chain management substantially enhances an organization’s visibility into each stage of their product journey, enabling them to make adjustments to routes and inventories when necessary.

However, advanced technologies can only do so much. To achieve an effective and responsive supply chain, companies need to start with the problem statement.

“Ask yourself,” Anne Johnston Weaver, Global Supply Chain Intelligence Platform Leader at EY, said in an article on real-time supply chain visibility, “What problems are you trying to solve, and how does solving this problem help achieve your business goals?”

At the moment, there’s a significant gap between the need for visibility and the actual visibility of supply chains. But companies that take the effort to address and gain transparency will not just see cost savings, risk reductions and overall efficiency in their supply chain management – they will also be in an advantageous position to thrive in the markets of today and tomorrow.