In the current economic climate, supply chain leaders are grappling with an inevitable wave of uncertainty, fuelled by factors such as climate change, fluctuating demand, and global instability. The need of the hour is swift, informed decision-making that takes into account the ever-evolving landscape of opportunities and disruptions. While many businesses attempt to reduce risk by predicting changes in their operational environment, the frontrunners are those that focus on high-quality decision-making that embraces uncertainty and complexity.
Historically, companies have relied on supply chain planning technology to provide predictive insights and prescriptive scenarios to minimize risk. However, as technology advances, decision intelligence, powered by AI and machine learning, offers a fresh approach to decision-making in the face of complexity. This method moves away from traditional planning, which aims to avoid uncertainty, and instead leverages advanced capabilities like dynamic decision-making and probability-based planning to turn uncertainty into value.
In our unpredictable world, a quicker, more agile approach that embraces uncertainty is key to navigating the turbulent business landscape.
The Evolving Supply Chain Landscape
Over the past decade, supply chains have become increasingly complex. This complexity is driven by factors such as increased variability, expanded supplier bases, globalization, and a larger number of decision-makers, as pointed out by Matt Hoffman of John Galt Solutions. Simon Ellis from IDC underscores the need for quicker decision-making and meeting heightened customer expectations. While improved technology enables companies to offer greater speed and reliability to customers, it also changes the way supply chains operate.
In the past, supply chains were linear and compartmentalized, with limited visibility. Planning was static, providing snapshots of demand, supply, and market conditions at a specific point in time. However, today’s interconnected supply chains require real-time data collection and dynamic decision-making. End-to-end visibility and cross-functional decisions have become necessities, not luxuries.
Static planning results in fragile supply chains that resist change, which is incompatible with today’s interconnected world.
The Impact of AI and Decision Orchestration in Supply Chains
Ellis posits that decision intelligence is uniquely equipped to tackle modern challenges. AI-supported decision-making is quicker and more efficient, offering real-time analyses and dynamic decision-making. AI-driven decision intelligence automates decision orchestration, integrating processes and providing transparency across organizations and partners. For example, AI can evaluate the impact of nearshoring production on cost, customer service, and sustainability as interconnected elements, rather than isolated factors.
AI-enabled platforms monitor decision outcomes over time, allowing users to review and adjust strategies at the speed of business. With AI handling complex tasks, human planners can focus on higher-level work, shifting the role of supply chain planners from detailed planning to complex decision-making.
A Shift in Decision-Making Approach
Traditional planning processes aim to predict and avoid disruption, pursuing accuracy and certainty. However, this approach falls short in today’s dynamic landscape. As complexity increases, businesses must embrace it. Alex Pradhan of John Galt Solutions suggests that decision intelligence transforms complexity and uncertainty into competitive advantages. Companies can maximize value and outpace competition by viewing influential factors as opportunities.
Supply chain planning platforms infused with dynamic decision-making foster flexible, adaptable, and composable supply chains. These platforms acknowledge uncertainty and variability across supply and demand, generating scenarios for planners to choose the best course based on conditions and risk tolerance. This agile approach embraces volatility, plans for it, and remains flexible enough to manage and predict it.
Shifting Market Priorities
Companies prioritize cost control in supply chain strategies while maintaining efficiency and resiliency. Slow decision-making can severely impact a company’s bottom line, says Hoffman. The challenge is balancing investment, cost control, and agility. Pradhan suggests that upfront investments in
