One goal of this article is to give an overview of the risk management issues with company supply chains and how AI technologies are impacting it. Another goal is to begin the discussion about mitigations for the unique set of risk management issues associated with today’s supply chains, including emerging risks.
ERM and TPRM
Enterprise Risk Management (ERM) is a comprehensive, organization-wide approach to identifying, assessing, and managing risks that could affect an organization’s ability to achieve its objectives. ERM encompasses all aspects of a company’s business, including risks associated with third parties such as contractors or supply chain companies. TPRM is often used to describe Third Party Risk Management, the subset of ERM that refers to identifying, assessing, and mitigating risks associated with third parties. These third parties are entities who your company has a direct relationship with. Your company’s data’s confidentiality, integrity, or availability can rely upon these third parties but they are not your employees or customers.
TPRM and Supply Chain Risk Management
A supplier is a business entity that provides goods or services to another organization. Nearly all businesses rely on some form of supply chain (a group of company suppliers) for sourcing, production, or distribution. Supply Chain Management (SCM) is the coordination and optimization of a business’s entire production flow, from sourcing raw materials to delivering finished products to customers. It encompasses the planning, execution, control, and monitoring of supply chain company activities with the aim of creating net value.
It is very common for companies to have supply chains composed of multiple levels, reflecting the complexity and fragmentation of modern supply networks. Modern global supply chains are deeply complex, making it difficult to track details closely at every step from start to finish. Furthermore, if a company does not have access to reliable data on its suppliers, it won’t be able to fully and accurately assess risks. The risk issues involved with supply chains are often as complicated as the risk management issues within the company using the supply chains, if not more so.
Overview and Summary of Risk Issues
Mastering the intricacies of supply chain risk management can positively impact business outcomes in many ways and can be a game-changer for business. Effectively managing the risks associated with supply chain management can be as important as properly mastering the risks inside a company, or even more important. Poor supplier performance, financial instability, political disruption, or exposure to natural disasters can significantly impact supply chains.
With the growth of international businesses, the increased linkages of global economies, the Covid-19 pandemic, and recent wars supply chain disruptions have increased. More massive, cascading effects across organizations’ supply chains are now occurring and are predicted. Statistics show that businesses with high visibility into the risks associated with their supply chains are reaping the benefits of lower costs, higher efficiency, and better customer experiences.
Companies often do a poor job of managing risks associated with their supply chains, or having visibility into the risks associated with supply chains on an ongoing basis. Here are some background statistics:
- Only 6% of companies report complete supply chain visibility.
- 69% of companies do not have any supply chain visibility at all.
- Companies with advanced SCM capabilities were 23% more profitable than their peers. (Per a 2024 study by Accenture).
Characteristics of Supply Chain Risk Management
One of the foundational tenants of ERM is that risks should be managed in a coordinated manner rather than in isolated silos, and the companies in supply chains can be considered silos as they are separate corporate entities. The risk issues with supply chains are as wide and varied as the companies in the supply chains used. The increasing reliance on cloud-connected supply chains and IoT networks exposes companies to cybersecurity risks. But supply chain risk management is about more than any specific type of risk, such as cybersecurity. Primary risk management issues with supply chains include:
- Financial Risks
- Operational Risks
- Supplier Performance
- Geopolitical Risks
- Cyber Threats
- Environmental, Social, and Governance (ESG) Compliance
- Natural Disasters and Climate Risks
(extreme weather events, climate-related issues) - Demand Planning Complexity
- Global Labor Shortages
- Product Quality Risks
Supply Chains Risk Management Ownership and Challenges
Most enterprise risks have a single risk owner, but because supply chains are vast and varied third parties, different groups and roles are responsible for different parts of the risk. This means supply chain risk has no single overarching owner with whom ERM can act as a thought partner. This poses a big coordination challenge. Supply chain risk management has unique characteristics because supply chain risk management:
- Is naturally distributed among many different people and functions in the companies involved in supply chains
- Has many heterogeneous risks that vary greatly in importance
- Issues are numerous, diverse and can be unique to the supply chains involved
- Data is almost always point-in-time and lagged. It therefore requires different management tactics to be effective.
Strategies for Mitigating Supply Chain Risks To mitigate supply chain risks companies should:
- Implement strategies such as diversifying suppliers
- Conduct thorough assessments of partners
- Use advanced analytics and forecasting tools
- Invest in cybersecurity measures
- Develop comprehensive contingency plans.
In addition integrating data governance into the organizational supply chain risk management strategy and company culture fosters a risk-aware environment where employees and supply chain entities understand the importance of managing supply chain data responsibly. This cultural shift encourages accountability and promotes best practices in data handling, further supporting risk management efforts.
How AI Is Reshaping Supply Chain Risk Management
AI tools can provide real-time visibility into the supply chain by integrating data from various sources, including IoT devices, ERP systems, and third-party logistics providers. This helps companies monitor performance and respond quickly to disruptions.
- AI algorithms analyze historical data, market trends, and external factors to provide more accurate demand predictions, enabling businesses to optimize inventory levels and reduce overstock or stockouts.
- AI tools process vast amounts of real-time data to improve supply chain decision-making.
- AI-powered solutions can provide real-time insights into every aspect of the supply chain, including tracking shipments, monitoring inventory levels, and identifying potential disruptions.
AI tools are increasingly being utilized to enhance supply chain management in various ways. AI optimizes supply chain operations through advanced data processing and pattern recognition. Ways that AI tools are improving and optimizing supply chain risk management include:
- Demand Forecasting
- Inventory Management
- Supplier Selection and Risk Management
- Route Optimization
- Predictive Maintenance
- Process Automation
- Enhanced Visibility
- Customer Service Improvement
- Sustainability Initiatives
- Scenario Planning
Supply Chain Control Towers
A supply chain control tower is a cloud-based solution that provides end-to-end visibility and management of the entire supply chain network. It leverages advanced technologies such as artificial intelligence (AI), machine learning, and the Internet of Things (IoT) to collect, integrate, and analyze real-time data from various sources across the supply chain. Supply chain control tower applications can be very beneficial for supply chain risk management but they can also be expensive. Key features of supply chain control tower applications include:
- Real-time visibility
- Data integration
- Analytics and decision support
- Collaboration
- Exception management
- Customizable dashboards
The benefits of implementing a supply chain control tower include more accurate forecasting, greater supply chain agility, optimized inventory levels, and improved decision-making. By providing real-time visibility and actionable insights, supply chain control towers enable organizations to proactively manage their supply chains, reduce risks and costs, and respond quickly to disruptions.
Digital Twins
A digital twin is a virtual representation of a real-world object, system, or process that accurately mirrors its physical counterpart which in this case is a company’s supply chain. This virtual model is designed to simulate behavior, characteristics, and performance using real-time data from sensors and other sources. Like supply chain control towers, using digital twins can be very beneficial for supply chain risk management, but they can also be expensive.
- Digital twins are a combination of multiple enabling technologies, such as sensors, cloud computing, AI and advanced analytics, simulation, visualization, and augmented and virtual reality.
- Companies can use a customized mix of technologies, depending on their needs and expectations.
- What distinguishes digital twins and makes them so powerful is their ability to emulate human capabilities, support critical decision-making, and even make decisions on behalf of humans.
- Digital twins observe their physical environment through a network of sensors that dynamically gather real-time data; they evolve by learning from this information and its contexts and by interacting with humans, devices, and other networked digital twins.
Key features of digital twins include:
- Real-time data synchronization
- Lifecycle representation from design to decommissioning.
- Simulation and analysis
- Decision-making support
- Integration of technologies like Internet of Things (IoT), machine learning, and advanced analytics
Digital twins support end-to-end visibility and traceability, enabling supply chain practitioners to spot patterns of highly complex and dynamic behavior. With their ability to compute thousands of what-if scenarios, the technology learns from these decisions and gains in maturity over time. This helps managers make faster, more accurate, and better-informed decisions with long-term impact at a considerably lower cost.
Conclusion
The risks supply chain entities pose to a business can include operational, financial, reputational, and compliance risks. Every business with a supply chain should define and enforce a supply chain risk management strategy. This strategy should involve continuously finding, assessing, and controlling the risks associated with supply chains to ensure they don’t cause more harm than good. An iterative approach that gathers information throughout the relationships with supply chain entities is highly recommended. Core strategies recommended include:
- Leveraging internal risk management expertise for supply chain risk management
- Creating a standard supply chain risk management framework
- Highlighting areas of low supply chain visibility
- Educating supply chain entities on risk mediation
By leveraging AI tools, companies can achieve greater efficiency, reduce costs, and enhance their overall supply chain resilience. By leveraging AI-powered Supply Chain Control Tower and Digital Twin applications companies can achieve greater efficiency, reduce costs, and enhance their overall supply chain resilience with cutting-edge AI technology.
References
- 37 Supply Chain Statistics, Trends, and Predictions for 2024
- How supply chain visibility impacts a business’ operations and lucrativenessThe Role of AI in Developing Resilient Supply Chains
- Supply chain control towers: Providing end-to-end visibility
- Unlocking the Potential of Digital Twins in Supply Chains
- What is supply chain management?
- What is supply chain risk management (SCRM)?
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