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How Avantor and Aera Technology Are Operationalizing Decision Intelligence, Insights from ARC Advisory Group’s 30th Leadership Forum
Published
3 mois agoon
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During the 30th Annual ARC Advisory Forum on February 10th, the session “The New Frontier of Operations and Supply Chain” offered 1.5 hours of valuable learning. It provided a platform for professionals to share their experiences and insights about the future of supply chains. The session delved into real-world end-user case stories, high-level discussions on implementing innovative solutions, and integrating AI into operational processes.
How Avantor Got Started on Its Decision Intelligence Journey
Jared Guckenberger was the end-user presenter during the session, showcasing the results of implementing Aera Technology’s Decision Intelligence solution. Jared is the VP of Global Supply Chains at Avantor. Avantor provides mission-critical materials and tools to life science companies, biopharmaceutical producers, and medical R&D organizations. Avantor has a global reach of 175 countries, 40 distribution centers, plus various college closet storage sites.
Scale:
10,000 supplier/ source combinations
250,000 SKUs sold per year
1.5 SKU-location combinations
10M+ purchase + customer orders per year
Jared shared Avantor’s supply chain challenges, including very high transaction and data volumes. Inventory challenges: too much, too old, and too little at the same time (excess, write-offs, and stockouts). Jared expressed the need to sense, decide, and act faster: integrate better with suppliers (many are low-tech, non-EDI). Many solutions must be “change-ready”, scalable, and usable by many roles, not fully autonomous AI.
Jared played a pivotal role in establishing a working relationship with Aera Technology to address the company’s supply chain challenges by utilizing Aera’s Decision Intelligence solution. It’s not only “Agentic Ai but also classic machine learning, decision logic, which are all orchestrated into repeatable decision processes. The core idea of Decision Intelligence is that it lets the system make thousands of routine decisions humans don’t have time for, rather than “smarter than humans” decisions.
At the start, Avantor focused on three reasonable target skill areas, focusing on decisions and processes that were traditionally inefficient. Avantor focused on stock rebalancing, purchase order cancellation, and purchase order prioritization to address inventory issues and improve customer service.
Stock Rebalancing: In the past, it was largely a manual, monthly exercise with lots of churn, and distribution centers were reluctant to spend days loading trucks; only top items were prioritized. Now: System scans twice a week to find dead or slow-moving stock and target locations with demand. DI produces move recommendations: planners approve or reject. On approval, stock transport orders are created in SAP automatically. The overall impact includes moving from infrequent “chunks to continuous, every other day rebalancing. Captures many “small” opportunities humans previously ignored: reduces write-offs and dead stock.
Purchase Order Cancellation: Traditionally, dynamic demand (orders canceled or changed) had a slow response time of 2-3 weeks. Now, systems scan weekly and propose PO cancellations. They send recommendations to suppliers via email (no EDI required). Suppliers reply by email; the system parses the response and summarizes it. The buyer then decides whether to accept or deny the cancellation. This process has reduced the cycle time from weeks to about a week or less. In the early phase, this approach has already saved $300K in inbound POs within 1-2 weeks using a small group.
Purchase Order Prioritization: Avantor has transitioned from a reactive to a proactive approach to managing stockouts. Now: The new system predicts potential stock shortages based on current demand and supply data. It then automatically emails vendors with requests like, “Can you move this delivery up by C days?” The vendor’s response (yes, no, or partial) is processed by the system and presented to the buyer, who then confirms the changes after considering associated costs. This proactive service enhancement improves the customer experience without relying on Advanced Planning and Scheduling (APS) tools like SAP.
Key Takeaways:
“Don’t wait for perfection; go live, then iterate.” Avantor currently has 62 enhancements still in the backlog. Pick skills with clear, immediate business impact and strong business sponsorship. Simplify processes where possible before or alongside automation. Lastly, have a roadmap ready: successful pilots quickly create demand for more AI/decision-intelligence use cases, which must then be prioritized and funded.
Executive Leadership Q&A Discussion:
After the presentation portion of the session, we moved into a Q&A style format with various industry professionals, including:
Peter Quimby of Aera Technology
Jeremy Hudson of Open Sky Group
Bryan Batchelder of Datex
Jared Guckenberger of Avantor
With over an hour of discussion, here are some of the top-line questions and answers from our panelists.
Question 1: As a system integrator, what best practices should customers follow when integrating new solutions, especially around data and AI?
Jeremy Hudson responded that many prospects want to attack the “gnarliest” use cases or copy flash keynotes (digital twins, robots, etc). Jeremy suggests you start with the simple, high-impact problems (where not everyone sends ASNs/EDI) rather than trying to boil the ocean. Focus on supporting decision makers, accept that data won’t be perfect, and choose tools that can work with and around bad data.
Question 2: How do you handle a go-live when the system isn’t perfect yet? Did you run a parallel (head-to-head) system, and how did you manage the risks?
Jared responded that there was no parallel legacy system because they had zero systems to begin with, so they could not do a clean head-to-head comparison. He also added that there was a “steering team” which was set up to communicate extensively with their distribution network. Citing an example of having to explain that spending $15 on UPS to avoid losing $1,000 in inventory.
Peter Quimby added that this is about Decision Intelligence, explicitly designing, evaluating, and learning from decisions. You “bring some eggs to make the omelet”: accept early friction to start capturing learning signals.
Question 3: Bryan, your role at Datex is part back-end developer and front-end product manager. What capabilities have you been recently working on, and how have your customers responded?
Bryan spoke in great detail about how the Datex platform is built on a low-code app platform that enables professional services teams to implement customizations faster and more cost-effectively. Additionally, some capabilities that Bryan is working on include embedding AI and agentic coding tools to help users define data sources (essentially queries over the data), which enables those data sources to be wrapped into reports. Lastly, they are striving towards building their own multi-agent orchestration and execution environment. Which would essentially mean that their customers would have their own agent that is loaded with all available context from sales prospectability to post-implementation debriefs.
Final Thoughts:
The session highlighted the current thinking and actions of leading companies in the supply chain market. A paradoxical trend is emerging: a significant rise in disruptions is occurring alongside the achievement of new levels of operational efficiency. Both end-users and providers are navigating distinct challenges, yet they share the common goals of increasing resilience and efficiency, and maintaining a competitive edge through digital transformation.
The post How Avantor and Aera Technology Are Operationalizing Decision Intelligence, Insights from ARC Advisory Group’s 30th Leadership Forum appeared first on Logistics Viewpoints.
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Supply Chain KPIs Are No Longer Keeping Up with the Job
Published
19 heures agoon
29 mai 2026By
Supply chain leaders are being asked to deliver far more than cost savings. They are expected to improve resilience, accelerate decisions, manage supplier risk, strengthen continuity, and support broader business strategy. Yet in many organizations, the performance metrics used to evaluate supply chain teams still reflect an older operating model built primarily around savings and transactional efficiency.
That gap matters. If the work has expanded but the scorecard has not, teams may be incentivized to optimize for short-term cost reductions while underweighting resilience, responsiveness, and risk readiness. Supplier diversification, recovery planning, sourcing cycle time, decision latency, and exposure visibility are increasingly central to supply chain performance, but they are not always captured in traditional KPI frameworks.
The Institute for Supply Management recently published a useful article on this issue, arguing that supply chain value now needs to be measured across a broader set of dimensions, including resilience, speed, risk reduction, and organizational readiness. The piece makes the case that savings remain important, but they are no longer sufficient as the primary indicator of supply chain contribution.
For supply chain executives, the larger takeaway is clear: measurement systems need to catch up with the strategic role supply chain now plays. Organizations that modernize their KPI frameworks will be better positioned to demonstrate value not only through cost control, but through continuity, agility, and better enterprise decision-making.
Read the full article from the Institute for Supply Management here: Supply Chain work has evolved faster than the KPI’s used to measure it.
The post Supply Chain KPIs Are No Longer Keeping Up with the Job appeared first on Logistics Viewpoints.
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Why Regulated Supply Chains Are Prioritizing Traceability Over Pure Efficiency
Published
19 heures agoon
29 mai 2026By
For decades, supply chain strategy was dominated by efficiency. Companies reduced inventory, consolidated suppliers, optimized transportation networks, minimized operational slack, and extended global sourcing structures in pursuit of lower costs and better asset utilization.
Those priorities still matter. But in regulated industries, they are no longer enough.
Healthcare, pharmaceuticals, aerospace, food, and medical-device supply chains now operate under a broader definition of performance. Product accountability, traceability, compliance continuity, and operational control are becoming as important as traditional efficiency metrics. In these sectors, the supply chain is not simply a cost structure. It is part of the organization’s control system.
That is why traceability is moving from an administrative requirement to a strategic operating capability. It allows companies to understand where materials originated, how products moved, which lots were affected, where inventory was distributed, and which customers or facilities received product. In stable conditions, that information may appear routine. Under disruption, it becomes essential.
Efficiency Alone Can Create Fragility
Highly optimized supply chains can perform very well when conditions are stable. The problem emerges when something goes wrong.
A supplier issue, quality deviation, transportation disruption, documentation failure, or traceability gap can quickly create consequences that extend far beyond delayed delivery. In regulated environments, these failures may trigger investigations, product holds, recalls, compliance exposure, customer disruption, and reputational damage.
That changes the operating calculus. A supply chain optimized purely for cost may not provide enough visibility or control when conditions deteriorate. The result is a shift toward a more balanced view of operational performance.
The objective is no longer simply maximum efficiency. It is controlled resilience.
Traceability Is More Than Compliance
Traceability is often treated narrowly as a compliance requirement. Its strategic value is broader.
Strong traceability improves root-cause analysis. It strengthens recall precision. It supports supplier accountability. It reduces ambiguity during disruptions. It helps organizations isolate operational risk more quickly and respond with greater confidence.
In practice, traceability becomes part of the enterprise’s ability to operate under uncertainty. A supply chain that clearly understands its dependencies can respond more intelligently than one relying on fragmented records, manual investigation, and disconnected documentation.
This is especially important in industries where the cost of ambiguity is high. In food, a traceability gap can widen the scope of a recall. In pharmaceuticals, incomplete lot visibility can delay containment. In aerospace or medical devices, documentation failures can affect audit readiness, quality assurance, and customer trust.
The strategic point is straightforward: traceability is not just about knowing what happened. It is about being able to act when it matters.
Complexity Is Raising the Bar
Several forces are increasing traceability requirements across regulated industries. Global sourcing networks are longer and more complex. Product portfolios are becoming more specialized. Regulatory scrutiny continues to increase. ESG expectations are adding new accountability pressures. Serialization, product authentication, and chain-of-custody requirements are expanding.
At the same time, supply chains are becoming more digital. Sensor data, IoT monitoring, electronic batch records, serialization systems, digital quality environments, supplier platforms, and logistics visibility tools now generate far more operational information than before.
The challenge is no longer simply collecting data. The challenge is coordinating and interpreting it across the enterprise.
That requires stronger data governance, better integration, and more contextual intelligence. Traceability systems create limited value if the data remains trapped in separate systems or disconnected from operational decision-making.
Traceability Depends on Coordination
A quality alert matters only if the organization can quickly identify affected inventory. A supplier issue matters only if downstream dependencies are visible. A transportation disruption matters only if customer, inventory, and compliance implications can be understood quickly.
This is where the broader shift toward continuous intelligence becomes important. As discussed in The Next Supply Chain Operating Model Will Be Built Around Continuous Intelligence, supply chains increasingly require systems capable of sensing, interpreting, and coordinating operational response continuously.
Traceability becomes significantly more valuable when it supports faster and more coordinated decisions. It is not enough to document product movement after the fact. Companies need traceability data to inform decisions in near real time.
This also explains why graph-oriented architectures and contextual AI systems are attracting attention. Regulated supply chain risk rarely exists in isolation. It moves through relationships among suppliers, products, lots, facilities, customers, logistics flows, and regulatory obligations.
Understanding those relationships operationally is becoming increasingly important.
The Efficiency Tradeoff Is Becoming More Nuanced
Prioritizing traceability does not mean abandoning efficiency. It means recognizing that efficiency must be balanced against resilience, accountability, and operational control.
The most efficient network on paper may not be the most resilient network under stress. A lower-cost supplier strategy may create greater exposure if visibility is weak. A highly optimized transportation network may become vulnerable if traceability and exception response are insufficient.
This does not eliminate the importance of lean operations. It changes the definition of operational maturity.
The organizations that perform best increasingly understand where visibility, traceability, and control create disproportionate strategic value. They are not simply asking how to reduce cost. They are asking where lack of control could create unacceptable operational, regulatory, or reputational exposure.
The Strategic Implication
Regulated supply chains are moving toward a broader definition of operational excellence.
Cost and efficiency still matter. But so do traceability, governed response, compliance continuity, visibility, accountability, and operational resilience.
The organizations that lead over the next decade may not simply be those with the lowest cost structures. They may be the ones capable of maintaining control, preserving trust, and coordinating response effectively under increasingly complex operating conditions.
In regulated industries, traceability is no longer merely administrative infrastructure. It is becoming part of the competitive operating model itself.
The post Why Regulated Supply Chains Are Prioritizing Traceability Over Pure Efficiency appeared first on Logistics Viewpoints.
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Medtronic: Strengthening Regulated Medical Device Supply Chains
Published
21 heures agoon
29 mai 2026By
Medical device supply chains operate under a different standard than many commercial supply chains.
Efficiency still matters. So do inventory discipline, transportation performance, and cost control. But regulated healthcare environments must also preserve traceability, quality assurance, compliance continuity, documentation integrity, product accountability, and controlled response processes.
That changes the operating model.
Medtronic offers a useful example. As one of the world’s largest medical technology companies, it operates across a complex global network of manufacturing sites, suppliers, logistics providers, hospitals, clinicians, distributors, regulators, and field-service organizations.
The objective is not simply to move products efficiently. It is to maintain product availability, quality, traceability, and regulatory compliance at the same time.
Regulation Changes the Supply Chain Equation
In many industries, supply chain performance is measured primarily through cost, service, and working-capital efficiency.
In regulated healthcare, the equation is broader. A shipment delay matters, but so does a documentation error, labeling issue, quality deviation, traceability gap, supplier compliance problem, or uncontrolled product movement.
The consequences can extend well beyond logistics disruption. They may affect regulatory exposure, product release, recall management, or clinical continuity.
That changes how resilience is defined. In regulated supply chains, resilience is not simply the ability to move inventory around disruption. It is the ability to preserve continuity while maintaining quality, traceability, and compliance discipline throughout the process.
That is a more demanding operating requirement.
Visibility Must Extend Beyond Transportation
For medical device companies, visibility cannot stop at shipment tracking.
The enterprise also needs visibility into supplier quality, serialized inventory, manufacturing conditions, product genealogy, service inventory, documentation status, field inventory positioning, and regulatory workflows.
The supply chain is not merely transporting products. It is managing accountable product movement across a controlled operating environment.
This is why regulated industries are investing more heavily in integrated visibility and traceability systems. Companies need to know not only where products are, but whether they remain compliant, whether documentation is complete, whether quality conditions have been maintained, and whether downstream commitments remain protected.
That requires tighter coordination across supply chain, quality, manufacturing, logistics, and regulatory functions.
Exception Management Becomes More Sensitive
Exceptions carry greater operational consequence in regulated healthcare environments.
A delayed shipment may affect hospital inventory. A supplier issue may trigger quality review. A labeling problem may delay product release. A traceability gap may complicate recall management.
The organization therefore needs more than awareness. It needs governed response.
This connects directly to the broader rise of autonomous exception management in logistics operations. In regulated supply chains, earlier detection is valuable not only because it accelerates response, but because it gives the enterprise more time to coordinate a compliant response before risk escalates.
AI-assisted systems may help prioritize exceptions, assemble context, identify affected inventory, and route decisions more efficiently. But the operating environment still requires governance, escalation controls, auditability, and human oversight.
This is not uncontrolled automation. It is governed operational intelligence.
Coordination Across the Enterprise
Medical device supply chains are deeply interconnected.
Supply chain teams must coordinate continuously with manufacturing, procurement, quality, regulatory, logistics, commercial teams, field-service operations, and healthcare providers. A disruption in one part of the network can quickly propagate into others.
That is why fragmented systems create particular risk in regulated industries. Disconnected operational environments do not merely reduce efficiency. They can increase operational and compliance exposure at the same time.
For medical device companies, enterprise coordination is not a process improvement exercise. It is part of the control system that protects product integrity, customer commitments, and regulatory standing.
The Broader Lesson
Medtronic’s operating environment reflects a broader shift across regulated industries.
The future supply chain is not simply leaner or faster. It must also be more traceable, more coordinated, more governed, more resilient, and more transparent.
That requires stronger integration between supply chain execution, quality management, regulatory processes, and enterprise intelligence systems.
In regulated healthcare, the supply chain is becoming part of the trust architecture surrounding the product itself. Over the next decade, that may become one of the most important strategic operating requirements in the industry.
The post Medtronic: Strengthening Regulated Medical Device Supply Chains appeared first on Logistics Viewpoints.
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