In today’s fast-paced business world, supply chains are the backbone of seamless operations. The ability to efficiently manage the flow of goods and services from manufacturing to the end consumer is paramount.
In recent years, artificial intelligence (AI) has emerged as a transformative force, revolutionizing the way supply chains operate. The most prevalent use case today is the application of AI and machine learning (ML) models to boost the accuracy of demand forecasting. But, as the adoption of AI and ML becomes more widespread, new applications continue to emerge — revealing significant untapped potential.
At Blue Yonder, we’ve seen firsthand how applying AI and ML to demand planning can increase supply chain resilience, boost planner productivity and bring agility to critical decision-making. AI is a critical enabler of demand and supply planning (DSP), which allows planners to easily collaborate, model and optimize a 360-planning view in seconds versus days. As lag times are minimized via AI, companies can capitalize on new opportunities and resolve disruptions before cost and service outcomes are affected.
This blog post will explore the myriad ways AI is reshaping the future of supply chains via DSP and other next-gen demand planning practices.
Intelligent scenario planning: Manage disruptions, build resilience
In the most recent Blue Yonder Supply Chain Executives Survey, 84% of respondents said their organization has experienced supply chain disruptions over the previous year. The top impacts of these disruptions included customer delays (named by 42% of executives), stalled production (42%), regulatory compliance issues (39%), reputational and monetary damage (38%), and an inability to meet demand (38%)
Scenario planning is a critical tool for understanding the impact of disruptions — in advance of taking action — to drive more confident, predictable outcomes. However, the scenario-planning tools and processes used by most companies today are suboptimal.
Why? Because they rely on human intuition and manual intervention to create and evaluate multiple complex scenarios. Not only is manual scenario planning a tedious and time-consuming job, but it also results in suboptimal decisions because too many granular scenarios, or too few wide scenarios, were created — missing critical levers and decision points. Given the complexity of modern marketplaces, as well as modern supply chains, it’s hard for human planners and human cognition to create and test meaningful demand planning scenarios.
Enabled by ML, Blue Yonder’s next-gen demand planning solutions rely on advanced algorithms that intelligently and autonomously reduce the problem scope to a logical set of scenarios that are realistic and most applicable. Embedded predictive AI evaluates this feasible set of scenarios and recommends the top scenarios that will achieve the company’s predefined objectives. This allows human planners to map out various levers in a scenario, set boundary values, then fire-and-forget.
AI- and ML-powered scenario planning reduces the average time taken from days or hours to mere minutes. Planners can focus on higher-value strategic decision-making and actions, rather than just collating data.
