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Forging Ahead with Long-Termism, Deepening Supply Chain SaaS After Seven Years of Refinement – Exclusive Interview with Liu Bin, CEO of Deep Insights
Published
6 mois agoon
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Recently, ARC Advisory conducted an in-depth interview with Liu Bin, founder and CEO of Deep Insights. In this information-rich conversation, Liu not only reviewed the entire process of Deep Insights (formed by the merger of Quantum Asia and GILLION) from integration to restructuring, but also systematically elaborated on his unique understanding of the SaaS model, pragmatic views on the value of AI, and the overseas expansion blueprint shifting from “passive following” to “active advancement”. What he outlined is not a shortcut to chasing trends, but a difficult yet inevitable long-termism path in China’s complex enterprise services market.
I. Strategic Integration: Not “1+1=2”, but Genetic Recombination
The merger of Quantum Asia and GILLION was one of the most watched industry events in the supply chain software sector in 2023 in China. However, in Liu Bin’s narrative, this was never a simple story of scale expansion.
“We aim to achieve a strategic-level restructuring,” he made it clear from the start.
In his view, the core of the merger lies in complementary genes and capability recombination: Quantum Asia brought core SaaS genes, cloud-native architecture, and a reusable product ecosystem; while GILLION injected valuable industry-specific know-how, experience in serving large clients, and strong capabilities in handling complex deliveries.
“The integration of these two capability chains has laid a solid foundation for us to build an AI-driven end-to-end supply chain platform,” Liu revealed.
After the merger, Deep Insights made three crucial and coherent decisions:
Unified product roadmap: Built a complete product matrix covering WMS (Warehouse Management System), TMS (Transportation Management System), freight forwarding, shipping, and container management, committed to providing an “end-to-end supply chain collaboration platform” rather than scattered point tools.
Unified AI strategy: Clearly mapped out a phased development path from “AI-enhanced” (improving existing functions) to “AI-native” (restructuring product design), and ultimately to an “AI ecosystem”.
Unified delivery system: Innovatively proposed “AI-enhanced delivery”, aiming to use AI technology to improve the efficiency and standardization of project implementation, thereby achieving large-scale expansion.
“Our current goal is not only to make the system easy to use, but also to enable enterprises to have an intelligent supply chain platform that understands business and data and can independently optimize itself.”
II. The Way to Break Through in SaaS: Two Key Decisions – “Serving Large Clients” and “Supporting Customization”
“SaaS has encountered some difficulties in China, but its business model is sound.”
When asked why Deep Insights still adheres to the SaaS model amid a market flooded with customization demands, Liu Bin’s answer was unhesitant. Behind this seemingly plain statement is his deep belief in the industry’s underlying logic after more than a decade of deep cultivation in the supply chain software sector, experiencing model exploration and market tempering.
Currently, many peers in the SaaS industry shrink back in the face of complex customization needs from large enterprises and question whether SaaS can succeed in China. Why can Deep Insights stick to SaaS and make it a core competency? Liu shared two crucial “breakthrough” decisions during his entrepreneurial journey, and these details reveal the uniqueness of its model.
The first breakthrough was a strategic decision on “who to serve”.
“Initially, our understanding of SaaS was quite superficial. We thought SaaS was probably for small and medium-sized enterprises (SMEs), and large enterprises would never use it.”
Liu recalled the exploration period from 2016 to 2017, when they designed a SaaS product tailored for SMEs. But the market quickly gave feedback: “After about half a year, we realized it was not working. It’s extremely difficult to do SaaS for SMEs in China, unless you target C-end customers.”
Amid the predicament, Liu made a decision that turned the tide: “I proposed that the clients we originally served with software should be our future SaaS clients. Our SaaS must be able to serve large enterprises.”
This key strategic shift opened a clear path for Deep Insights’ SaaS journey, directly targeting medium and large client groups with stronger payment capabilities and digital transformation willingness, laying the foundation for the success of its business model.
The second breakthrough was product and architectural innovation regarding “how to do it”.
Serving large enterprises inevitably involves customization demands. Rejecting customization outright would mean losing clients, while fully embracing it would deviate from the essence of SaaS. Deep Insights’ solution is highly innovative – “SaaS should support customization”.
“Different from traditional views in the market, we provide each large client with a ‘customization package’ on the multi-tenant architecture of the public cloud,” Liu explained the sophisticated design in detail. “We maintain rapid iterations of the main version every two weeks, while clients’ personalized needs are encapsulated in independent customization packages. Clients can retain their customized functions and independently choose whether to upgrade with the main version.”
This design is like setting up a “private compartment” that can be independently arranged for each VIP on a standardized high-speed train, perfectly balancing the fundamental contradiction between rapid iteration of product standardization and core personalized needs of clients and becoming the cornerstone for Deep Insights to attract and retain large clients in the long term.
III. AI Positioning: Evolution, Not Subversion
Faced with the sweeping AI wave, Liu Bin demonstrated rare calmness and pragmatism. He believes that AI is not a subverter of SaaS, but a natural “evolution”.
“The core of SaaS is process standardization, which is essentially process-based. In contrast, the core of AI is data-driven intelligence,” he accurately analyzed the relationship between the two, pointing out that they have different underlying starting points but are not oppositional. Liu further elaborated that AI not only fully inherits the most excellent subscription-based business model of SaaS, but more importantly, “we have been doing SaaS for nearly 10 years, and in fact, we have accumulated a large amount of desensitized data, which has become the best ‘fuel’ for AI.”
He further pointed out that AI is profoundly transforming the very way software is developed. “Since the beginning of this year, we have been practicing how to drive our internal development processes with AI. Our vision is that by next year, over 60% of the work will be done by AI, with 30% to 40% handled by humans for confirmation and verification.”
Based on this, he gave a clear judgment on industry evolution: “Initially, we developed standalone software, then we moved to internet-based software, and later evolved into SaaS. In fact, the transition from SaaS to AI is another evolution, which I think is an inevitable process.”
IV. Strategic Upgrade of Overseas Expansion: From “Riding on Others’ Ships” to “Building Our Own Vessels”
Regarding Deep Insights’ future development direction, Liu Bin’s answer clearly and firmly points to globalization.
“In the past few years, our overseas expansion has been ‘following Chinese enterprises going global’,” Liu frankly reviewed the initial stage. “But starting from this year, we will take the initiative to expand overseas.” He revealed that he has recently led a team to visit Southeast Asian markets such as Thailand and Singapore intensively. “We will adopt a dual-track approach: on the one hand, continue to deepen services for Chinese enterprises expanding overseas; on the other hand, actively promote our supply chain cloud, AI, and localized products to the local market.”
Conclusion: The “Inevitable Path” for Long-Termists
Throughout the conversation, Liu Bin consistently showed the clarity and determination of a “long-termist”. He is well aware of the difficulties of SaaS in the Chinese market, has witnessed early twists and turns and industry fluctuations, but firmly believes in its inherent value and irreversible direction.
With the strategic triangle of “SaaS as the foundation, industrialization as the accelerator, and AI as the engine”, Deep Insights is striving to blaze a path to the future in the soil of China’s enterprise services that requires patience and wisdom.
The post Forging Ahead with Long-Termism, Deepening Supply Chain SaaS After Seven Years of Refinement – Exclusive Interview with Liu Bin, CEO of Deep Insights appeared first on Logistics Viewpoints.
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Supply Chain KPIs Are No Longer Keeping Up with the Job
Published
21 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
21 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
23 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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