Three months to recover from supply chain disruption - there's a better way

Over the last three years, Blue Yonder has conducted surveys of global supply chain leaders regarding changes to their investments, assets, and challenges. Results reveal one perennial issue - Executives surveyed experienced disruptions every single year. In the 2025 Supply Chain Compass survey, nearly half of the leaders polled cited disruptions as their main concern.

In the U.S., tariffs and trade tensions are clearly a disruption. In July, American manufacturing shrunk for a fifth month thanks to trade uncertainty that has pushed up prices of imported raw materials, according to the latest data from the Institute for Supply Management. And this is despite recent pushes by companies to stock up on goods and supplies before they become more expensive. Tariff concerns have also pushed some Asian exporters to begin adjusting their focus away from the U.S. to regional markets. In June, Singapore’s exports (excluding oil) to the U.S. fell compared to June 2024. Meanwhile its exports to Hong Kong, Taiwan, and South Korea rose in June.

Rethinking supply chain management for volatility

A study from Accenture showed that the average time from discovering a disruption to organizing a full recovery is three months, although it can take up to five months. For 57% of companies, it takes a week or more just to be alerted to production or supply network disruptions. Even then, nearly 80% of executives in the research said it required an additional week or more to gauge the impact of the break.

One thing is clear - companies need a new way to think about supply chains. Those who succeed in the future will be the ones who build flexibility and adaptability now, preparing them for disruptions as they arise. Otherwise, they risk disruption-induced shortages that could headline earnings seasons and investor calls.

A new paradigm for supply chains — Interoperability

Many organizations require changes to their people, processes, and technology stacks to address the lack of visibility and coordination across all supply chain activities. Before tackling those changes, supply chain leaders need to challenge their basic assumptions and practices. Companies can’t keep adding people to solve the problem, and generative AI is already beginning to render some of the process work redundant.

To thrive amidst volatility and create strategic resilience, it is time to move beyond point solutions that merely hand off planning for execution. To dramatically improve decision-making and performance, organizations need to think holistically, end-to-end, in a way that includes their trading partners.

This means interoperable solutions running on a common data set, augmented by third-party data such as traffic, weather, risk, telematics, influencers, and aided by AI agents that can analyze it and surface critical insights. Such agents can identify critical issues that require attention, pinpoint the root causes of these issues, and provide feasible and cost-effective solutions.

These systems provide an in-depth and real-time understanding of customers, suppliers, carriers, and other key stakeholders, as well as insight into what is happening across all links and nodes. They help organizations anticipate future disruptions and threats, such as severe weather, power outages, or tariffs, and assist in mitigating or navigating their effects.

Multi-enterprise visibility with an AI-powered network

The best companies with multi-enterprise supply chains employ several best practices and principles to ensure efficiency, resilience, and scalability across their vast partner networks. Instead of relying on traditional supply chains that uncover and react slowly to problems, these businesses focus on being better prepared, more flexible, and faster at making decisions when something goes wrong.

Their best practices include embedding AI and generative AI across decision-making, planning, and logistics to increase agility and resilience. Their systems connect across ecosystems - to unify various enterprises - suppliers, logistics providers, carriers, and retailers. They invest heavily in supply chain visibility, creating a digital version of the supply chain that extends to carriers and suppliers, which provides a deep view into external resources. When operations change, they use data and findings from the adjustment to improve forecasts and future decisions. And they source from different regions to lower risk.

One example of an organization that has successfully adapted to handle volatility is Armada, a $4 billion supply chain solutions provider that moves nearly 100 million cases and 450,000 truckloads annually. Armada combined its digital demand, fulfillment, and warehouse management solutions with a central, next-generation control tower - a supply chain command center - to improve visibility and decrease response times, thereby increasing resilience.

Using operations processes and data to shape planning

Extreme volatility also demands a mindset shift. Instead of a long-term plan that is occasionally tweaked, supply chain leaders need to develop a process that is continually and deliberately shaped by operations and data. It represents amove from traditional planning-driven execution to a model where insights from operations continually inform and improve planning.

Companies adopting a continuous planning-synced-to-execution approach can generate new types of data, including process metrics, supplier performance details, customer feedback, and employee insights, which in turn help supply chain executives make smarter planning decisions.

A global automaker exemplifies this shift in approach. It utilizes analytics from operations to track the popularity of different vehicle models and colors across various regions. By collecting and analyzing this information, the automaker refines its marketing campaigns and production schedules to accommodate local consumer demand. This operations- and data-driven approach helps the company optimize inventory, reduce overproduction, and ensure that dealerships have the cars customers want, thus maximizing sales.

Role-based dashboards and flexibility

The mindset shift demands answers to important questions. Do the right teams have access to real-time details? Do they have operational feedback loops for better and more up-to-date decisions?

Role-based dashboards empower teams with actionable insights, enabling them to identify and quickly address potential chokepoints and mitigate risks. Now, generative AI accelerates this process by filtering out the noise and highlighting the most salient points for users.

For example, suppose a production line is in danger of being shut down due to a pending parts shortage. The sooner this issue surfaces, the more likely it is to be averted. Dashboards providing projected inventory views over a given time horizon, based on on-hand, in-transit, and on-order inventory, can alert users to future mismatches and projected shortages. These can be identified quickly and proactively addressed before they affect operations.

AI-driven demand forecasting and scenario planning

AI can help provide inputs based on the latest sales data and continually tune demand forecasts to make them more accurate. With a unified data model across planning and execution, AI agents can see and anticipate events and their implications across the supply chain. They can then use a knowledge graph to identify exceptions and determine root causes and do this approximately 20 times faster than traditional methods.

Running multiple scenarios simultaneously, they can decide on the most appropriate and cost-effective resolution. Finally, they can autonomously or collaboratively- working with agents, humans, and machines - resolve complex issues, even if they span multiple functions and trading partners.

The result? Smarter, faster, and more responsive organizations with happier, more loyal customers.

The future is about flexibility, interoperability, and speed

Volatility in the supply chain is here to stay. When disruption hits, it’s already too late to figure out how to adapt. The pandemic taught businesses how to act in times of turmoil, and some of those lessons are now proving beneficial.

Supply chain leaders will do well to unify data and systems, and strive to make solutions interoperable, and augment them with agents. They should seek to relace rigid, long-term planning processes in favor of agility enabled by machine precision and speed and apply this across the multi-enterprise network rather than just inside their four walls. This will enhance adaptability, efficiency, and resilience, and enable them to meet rapidly changing market conditions.