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How to Optimize Fulfillment with Unified Data
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1 an agoon
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Order fulfillment is the complete process from when an order is placed until the shipment is delivered. Accurately fulfilling thousands of orders for millions of items is extremely challenging. Many large organizations have multiple systems for order, warehouse, or transportation management that are barely integrated – frequently not at all. However, large organizations are often equipped to handle fulfillment in-house, leveraging their extensive resources and capabilities. An organization with tens of thousands of different products may have to move them across many modes of transportation, IT systems, and third-party logistics partners, all adding to complexity, as well as loss of visibility and control.
Sudden and significant changes in demand, especially in consumer markets, stack up more challenges, requiring order revision and reallocation. If your systems are disjointed and you lack the ability to analyze masses of data in real time, you will struggle to deliver on-time, in-full and your reputation and revenue will be negatively impacted.
Optimizing fulfillment requires a series of steps to get a shipment from its source to the end customer. These steps include sourcing and receiving inventory, storing inventory, order processing, picking and packing an order, shipping the order, and returns management. Standard sizes and categorizations play a crucial role in determining the costs associated with shipping products that meet standard criteria in fulfillment centers. The fulfillment process is further complicated by ongoing shifts in customer expectations and demands and geo-political and weather disruptions.
Introduction to OTIF Fulfillment
The key measurement of fulfillment is on-time in-full (OTIF) fulfillment, which is calculated as a percentage of orders that are delivered on the requested delivery date and in the quantity requested by the customer. The formula for OTIF is:
Measuring a supply chain against OTIF metrics is a key strategy that helps decision makers attach a tangible value to the success of their fulfillment and allows them to determine key strategies. Factors like planning tools, inventory management, demand patterns, and innovations in technology contribute to the success or failure of fulfillment optimization. Establishing standard benchmarks for services and innovations in fulfillment centers is crucial in this context. Fulfillment costs can significantly impact profit margins, making it crucial for businesses to understand these financial implications and how they influence consumer spend.
The question then becomes “what is a good OTIF score to shoot for?” Fulfillment success, and the associated OTIF score, will vary by industry, region, and other assorted factors, but generally speaking, an OTIF score is considered good if it falls between 80% and 90%. Many companies aim for 95% or higher, which can be a daunting task. For suppliers, the penalties associated with missing OTIF goals can be significant. For example, Walmart’s OTIF program mandates that suppliers should meet the 90% on-time and 95% in-full goals to avoid penalties. Walmart fines suppliers 3% of the cost of goods sold (COGS) for orders that fail to meet on-time and in-full delivery requirements.
A good fulfillment strategy can help businesses boost customer satisfaction (CSAT), reduce inefficiencies, and increase sales. By setting clear expectations and standards for fulfillment operations, including OTIF rates, shipping times, and inventory levels, businesses can ensure that they meet customer demands and maintain high levels of satisfaction. Regularly monitoring and analyzing fulfillment operations can help identify areas for improvement and implement strategies to optimize these processes.
Effective fulfillment requires a well-designed system, efficient logistics, and a reliable supplier network to ensure timely and accurate delivery of products. Companies have two options to consider for fulfillment operations: in-house fulfillment or outsourcing fulfillment to a third-party logistics (3PL) provider. While outsourcing to a 3PL is a common strategy, new technologies and approaches now exist to achieve higher OTIF rates in house.
Warehouse Fulfillment Complexities and Inefficiencies
InterSystems surveyed 450 senior supply chain practitioners to examine key supply chain technology challenges, trends, and decision-making strategies across five key use cases: fulfillment optimization; demand sensing and forecasting; supply chain orchestration; production planning optimization; and environmental, social, and governance (ESG). These respondents came from 13 countries and 12 industries, representing decision-makers across project management, fleet management, sales & marketing, HR, and finance.
This blog is Part 1 in our Optimizing Supply Chain Performance with Unified Data series, with a focus on optimizing fulfillment. Effective inventory management strategies are crucial for businesses looking to expand their operations and improve delivery efficiency, particularly when scaling to multiple warehouse locations. Looking to the future, businesses should prepare for trends such as the growth of micro fulfillment centers and the need for adaptive strategies to stay competitive in the evolving landscape.
Ability to Meet Fulfillment Goals
According to the survey, only a mere 1% of respondents achieve 80% or higher for their OTIF metrics, with the average percentage of OTIF being a mediocre 62.21%. The ability to meet fulfillment goals is impeded by several issues. When asked to name their top three challenges for fulfillment optimization, respondents cited the high volumes and complexities of SKUs (59%), inadequacies of existing planning tools (51%), and volatile demand (42%). Considering that the majority of respondents are using manual processes, legacy systems, or multiple solutions from different vendors to integrate and prepare disparate data, this makes sense.
SKU complexity generally refers to the challenges and inefficiencies associated with keeping a large number of SKUs within a store, warehouse, or factory. This includes picking the correct items from inventory, packing them appropriately, and ensuring their timely delivery to customers. Managing too many SKUs leads to higher inventory carrying costs and general inefficiencies. On top of that, the lifecycle of a SKU is getting shorter, especially as more businesses turn to e-commerce for direct-to-consumer selling. A SKU is designed, received, and pushed to the market, but often it is not available six months later, making replenishment nearly non-existent. Without re-stocks, optimizing fulfillment from the right location is more important than ever. Strategies for managing excess inventory and preventing overstocking are crucial to maintaining efficient operations.
Inadequacy of Planning Tools
The second challenge identified by respondents was the inadequacy of planning tools. This can lead to fulfillment failure from the standpoint of missed deadlines, increased costs, or poor customer satisfaction. Timely information is critical, as data older than a few days can lead to costly supply chain disruptions. Perhaps not surprisingly, the industries that reported they would see the biggest improvement in fulfillment rates if able to ingest real-time data and provide actionable insights to business users were automotive and aeronautics (55%), FMCG (44%), and manufacturing/CPG (43%).
Demand Volatility
The final challenge associated with optimized fulfillment is demand volatility. Demand volatility is the sudden and unpredictable variation in customer demand for products or services over a specific time. The root causes are not always easy to identify, but they can be attributed to changing customer expectations and demands, changing promotions, or a shift in market dynamics such as external weather events, geo-political instability, and shipping disruptions like the Francis Scott Key Bridge collapse or the blockage of the Suez Canal. These changes make it harder for companies to forecast demand in both the near and long term and can lead to further supply chain disruptions. Effective returns management is also crucial in handling the unpredictable nature of demand, ensuring that returned products are inspected, restocked, or disposed of efficiently. Tracking how much inventory is held and assessing inventory age are essential to making informed decisions about restocking and mitigating risks such as stockouts and overstocking.
Fulfillment Strategies
Respondents were asked to identify the data technology innovations they would most want to implement to achieve fulfillment optimization. The top response was the use of artificial intelligence (AI) and machine learning (ML) (46%), which outpaced predictive and prescriptive analytics (37%), the use of a decision intelligence platform within supply chain (37%), real-time harmonized and normalized data from multiple sources internal and external (37%), and streamlined integration of different solutions (37%).
These technologies can be directly integrated with existing systems, allowing businesses to automate workflows and reduce errors in managing inventory and order fulfillment.
AI and ML impact every stage of the order fulfillment process, with a specific emphasis on forecasting, inventory management, order processing and picking, and last mile deliveries. For improved OTIF, AI and ML help companies make smarter decisions faster, improve turnaround times, and simplify manual processes in the warehouse. The real desire for survey respondents is to improve upon current systems and processes to make better sense of their data, enabling optimized fulfillment processes. Inventory management systems can ensure businesses are notified when stock levels are low, allowing timely replenishment and minimizing the risk of stockouts.
Actionable insights drive significant efficiencies in every area, increasing automation and significantly boosting productivity. Supply Chain Orchestrator provides the infrastructure needed to optimize raw materials handling from point-of-supply to end consumption. Organizations can integrate transportation, warehouse management systems, and advanced robotics. Packaging plays a crucial role in the fulfillment process, ensuring items are carefully packaged for safe transport.
By increasing automation through Supply Chain Orchestrator, organizations accelerate decision-making, offer self-service access to analytics, and remove human errors. Organizations are ready to implement AI and ML-driven prediction and productivity gains. They achieve rapid adaptation to any changes in demand, logistics disruptions, or business priorities, leading to increased CSAT and higher revenue. An efficient fulfillment system is essential in managing order delivery and inventory, contributing to better operational efficiency.
Order Accuracy and Efficiency
Order accuracy and efficiency are critical aspects of fulfillment operations, as they directly impact a business’s ability to fulfill orders on time and in full. Effective order picking and shipping processes are essential for improving order accuracy and efficiency, reducing fulfillment costs, and enhancing the overall customer experience.
By implementing efficient logistics and shipping strategies to ship orders, businesses can reduce shipping times, improve their OTIF rates, and increase CSAT. Regular monitoring and analysis of picking and shipping processes are vital for identifying areas for improvement and implementing strategies to optimize fulfillment operations.
Technology plays a significant role in improving order accuracy and efficiency. Automated packaging and shipping systems can help businesses streamline their operations, reduce errors, and lower fulfillment costs. By leveraging these technologies, businesses can ensure that their customers receive their orders accurately and on time, leading to higher levels of satisfaction and loyalty. But technology plays an even bigger role in data unification and management, especially when it comes to integrating new technology with existing applications.
Final Thought on Fulfillment and Repeat Purchases
These survey findings confirm that most organizations lack the necessary capabilities to optimize highly complex supply chains with interwoven dependencies. To be truly agile and competitive, organizations must be capable of extracting critical insights in near real-time. But as things stand, this remains a significant challenge when so many businesses lack end-to-end visibility, or rely on manual data analysis and ad hoc assemblages of different solutions.
In the face of constant change, disruption, and opportunity, organizations need a streamlined source of standardized, clean, meaningful, and reliable data that is available to business users. Maintaining proper stock levels is crucial to ensure product availability and prevent issues like stockouts or overstocking. An intelligent data platform eliminates the significant data challenges that organizations encounter on their path to optimized fulfillment and repeat purchases.
Read the full report here.
Chris Cunnane is the Supply Chain Product Marketing Manager at InterSystems. In this role, he is responsible for developing and executing marketing strategy and content for the InterSystems supply chain technology suite. Chris has 20+ years of supply chain expertise, leading the supply chain practice at ARC Advisory Group, as well as holding various sales, marketing, and operations roles in the wholesale, retail, and automotive parts markets. He holds a BA in Communications from Stonehill College and an MA in Global Marketing Communications from Emerson College.
The post How to Optimize Fulfillment with Unified Data appeared first on Logistics Viewpoints.
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Last Chance: Join the Webinar on AI, Component Sourcing, and the Future of Procurement
Published
1 jour agoon
22 juin 2026By
Electronic component sourcing is becoming one of the most important cost and risk challenges facing manufacturers.
Pricing remains opaque. Supplier quotes do not always reflect true market pricing. Internal purchase history may show what a company paid, but not whether that price was competitive.
At the same time, chips and components are increasingly tied to geopolitics, tariffs, AI infrastructure, defense demand, electrification, industrial automation, and supply chain resilience.
The webinar is tomorrow at 11 AM ET. Register now to join ARC Advisory Group’s discussion, The Hidden Cost of Component Sourcing — and How AI Is Fixing It, featuring Jim Frazer in conversation with Lytica CEO Martin Sendyk.
This is a practical conversation for procurement, supply chain, engineering, operations, and executive leaders who are trying to understand how component sourcing is changing.
Manufacturers need to control cost, protect supply, support product launches, and manage risk in a market where visibility is often limited. Overpayment can remain hidden. Component risk can appear too late. Engineering and procurement decisions can become locked in before teams have enough market intelligence to make the best sourcing choices.
Tomorrow’s webinar will examine why traditional approaches to component sourcing are under pressure and how manufacturers can use better intelligence to identify hidden cost, improve benchmarking, and manage sourcing risk more effectively.
Attendees will learn:
Why electronic component pricing remains difficult to benchmark
How hidden overpayment can persist inside normal procurement activity
Why supplier quotes, list prices, and internal history are not enough
How real transactional data can improve pricing visibility
Why geopolitics, AI demand, tariffs, electrification, and defense demand are changing the sourcing risk equation
How AI and sourcing intelligence can help procurement teams make better cost and risk decisions
The issue is no longer only whether a company can secure supply.
The issue is whether it can secure the right components, at the right price, with the right risk profile, early enough to influence the business outcome.
For many manufacturers, that requires a more transparent, data-driven, and intelligence-led sourcing model.
Register now for the ARC Advisory Group webinar with Jim Frazer and Lytica CEO Martin Sendyk before the session begins tomorrow at 11 AM ET.
Register for the Webinar
The Hidden Cost of Component Sourcing — and How AI Is Fixing It
Date: June 23, 2026
Time: 11:00 AM ET
Location: Online
Speakers: Jim Frazer, Vice President, ARC Advisory Group, and Martin Sendyk, CEO, Lytica
If your organization manages a significant electronic component spend, this webinar will help you understand how AI and transactional market data can expose hidden sourcing costs and turn procurement into a more proactive system of intelligence.
Register now to reserve your spot.
The post Last Chance: Join the Webinar on AI, Component Sourcing, and the Future of Procurement appeared first on Logistics Viewpoints.
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Weekly Supply Chain and Logsitics News Round Up (June 15th-18th 2026)
Published
5 jours agoon
19 juin 2026By
This week in logistics, the industry faces a pivotal shift as Transportation Management Systems evolve into ‘decision intelligence’ hubs, moving beyond basic routing to become the core operating brain of the supply chain. Meanwhile, operational complexity reaches new heights with the massive logistical undertaking of the 2026 FIFA World Cup, even as trade tensions show signs of cooling following the European Parliament’s approval of a landmark EU-US tariff relief deal. From record-breaking automation at Nestlé’s new California hub to the fluctuating volatility of global air freight rates, these developments underscore a sector increasingly defined by high-tech integration and rapid adaptation to global market forces.
The Leading Supply Chain and Logistics Stories of the Week:
TMS Is Becoming Less of a Routing Tool and More of a Decision Intelligence Layer Beyond Execution
The role of the Transportation Management System (TMS) is undergoing a major paradigm shift. While traditional evaluations still focus heavily on execution-level metrics—like route optimization, automated tendering, and freight audit capabilities—these features have essentially become table stakes. Moving forward, the true strategic value of a TMS lies in its evolution from execution software to “transportation decision infrastructure.” Rather than just completing transactions, next-generation platforms serve as the continuous decision-making layer of the supply chain. By drawing data from across the entire network, integrating external market signals, and resolving multi-functional bottlenecks, modern TMS solutions are transitioning into the core operating brain that synchronizes movement, cost, and service levels in real time.
The Logistics Issue: The Supply Chains Behind the World Cup
While most fans focus entirely on the action on the pitch, supply chain professionals are watching what might be the most complex logistical undertaking in sporting history: the 2026 FIFA World Cup. Spanning three host nations—the United States, Canada, and Mexico—the sheer scale of the tournament requires moving more than twenty million pounds of equipment, coordinated across 5,000 vehicles and millions of square feet of warehouse space. The challenge isn’t just massive volume; it’s the absolute lack of tolerance for delay or error across highly regulated international borders. Industry experts point out that success hinges on establishing a unified ecosystem in which freight forwarders, customs officials, and vendors collaborate in real time. Crucial to this effort are standardized product identification and cloud-based labeling networks, which ensure that every critical piece of equipment, food shipment, and medical supply is fully traceable and compliant with differing regional mandates—proving that at this scale, elite collaboration is the only way to avoid catastrophic bottlenecks.
Transatlantic Trade Relief: European Parliament Greenlights EU-US Tariff
In a major relief to transatlantic supply chain operators, the European Parliament has officially voted to implement the long-awaited trade agreement with the United States. Under the newly approved legislation, the EU will eliminate tariffs on all American industrial goods and grant preferential market access to key U.S. agricultural and seafood shipments. In return, the U.S. has agreed to cap import tariffs on European products at 15%—effectively averting threatened 25% tariff hikes on European-built vehicles. Importantly for logistics planners, the deal incorporates a “defensive toolbox” to mitigate long-term trade volatility, including a sunset clause set for late 2029, a safeguard mechanism to protect EU markets from disruptive import surges, and strict conditions that allow the EU to suspend tariff preferences by the end of 2026 if the U.S. fails to lower existing duties on European steel and aluminum derivatives.
Nestlé Opens Its Largest and Most Technologically Advanced Distribution Center in the U.S.
Nestlé USA has officially unveiled its new 700,000-square-foot distribution hub in Arvin, California. Equipped with a $330 million price tag, the state-of-the-art facility represents a critical step in the company’s broader $25 billion U.S. infrastructure upgrade, emphasizing a pivot toward leaner, automation-first supply chain workflows. The Arvin facility houses the largest Automated Storage and Retrieval System (ASRS) in Nestlé’s global network, operating alongside laser-guided vehicles, automated crane systems, and layer-picking robotics. This build marks a major shift from retrofitting existing spaces to intentionally designing high-tech capabilities directly into greenfield logistics layouts from day one. Designed to mitigate peak-season labor bottlenecks, upskill the frontline workforce, and run on 100% renewable electricity as a zero-waste site, the facility showcases how global leaders are leveraging heavy automation to establish flexible, resilient distribution networks that protect margins against ongoing labor and capacity constraints.
Air Freight Spot Rates Spike 41% YoY in May, but Relief Is Expected Soon
Global air cargo spot rates surged by 41% year-over-year in May, averaging $3.40 per kilogram, driven by persistent geopolitical disruptions, carrier fuel surcharges, and localized demand booms like semiconductor and data center equipment shipments. According to Xeneta data, spot rates from Northeast and Southeast Asia to North America jumped nearly 40% compared to earlier this year. However, the pricing pressure isn’t uniform; transatlantic lanes from Europe to North America actually saw a 26% decline over the same period. For procurement teams battling these elevated costs, there is a glimmer of light on the horizon. Long-term contract rates appear to have peaked in April, and as carriers restore capacity and the market enters its traditional summer lull, analysts predict that year-over-year spot rate comparisons will finally begin to cool down, offering much-needed breathing room for shippers who have been relying on short-term contract extensions.
Song of the week:
The post Weekly Supply Chain and Logsitics News Round Up (June 15th-18th 2026) appeared first on Logistics Viewpoints.
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Why Octave’s Austin Event Matters: From Asset Lifecycle Software to Intelligence at Scale
Published
6 jours agoon
17 juin 2026By
Octave Live OnTour Austin takes place at a consequential point in the evolution of the industrial software market. Asset-intensive organizations are under sustained pressure to improve capital project execution, asset reliability, operational resilience, safety, quality, cybersecurity, and workforce productivity. At the same time, they are being asked to make better use of data and apply AI in ways that are practical, governed, and operationally relevant.
This is the context in which Octave’s Austin event should be evaluated.
Octave, the software spin-off from Hexagon AB, brings together software assets across engineering, construction, geospatial intelligence, asset operations, quality, public safety, physical security, and industrial cybersecurity. Its Design, Build, Operate, and Protect framework provides a clear structure for organizing those capabilities around the industrial asset lifecycle.
However, the strategic significance of the event is not limited to Octave’s portfolio structure. The more important issue is what Octave’s positioning indicates about the broader direction of industrial software.
The market is shifting from digitized workflows toward intelligence at scale.
Industrial Software Is Moving Beyond Functional Digitization
For much of the past two decades, industrial software investment has centered on functional digitization. Engineering teams adopted design, modeling, analysis, and engineering information management tools. Construction teams deployed project controls and field execution systems. Operations teams invested in EAM, APM, optimization, and reliability applications. Quality, safety, physical security, and cybersecurity functions developed their own specialized technology environments.
These investments created meaningful value within individual domains. But they also reinforced a long-standing structural problem: industrial work is highly interconnected, while the supporting software environment often remains fragmented.
A design change can alter construction cost and schedule. Construction execution quality can affect commissioning performance. Poor handoff from construction to operations can increase maintenance burden. Maintenance backlog can elevate safety and compliance risk. A cybersecurity incident can become an operational disruption. A public safety event may require geospatial, security, asset, and operational context at the same time.
This is the gap that lifecycle intelligence seeks to address.
Lifecycle Intelligence Requires Context Across the Asset Lifecycle
Octave’s Design, Build, Operate, and Protect framework is meaningful because it reflects how industrial assets are planned, built, used, maintained, protected, and improved over time.
In the Design domain, Octave can address engineering, modeling, analysis, information management, and geospatial intelligence. In Build, the portfolio extends into construction, supply chain management, and project performance. In Operate, the focus expands to operations optimization, asset performance, enterprise asset management, quality, compliance, and risk. In Protect, Octave’s positioning includes public safety, physical security, and industrial cybersecurity.
Individually, these are established industrial software categories. Collectively, they suggest a broader strategic direction: the use of software to preserve, connect, and operationalize context across the asset lifecycle.
That is where the Austin event becomes important. Customers and partners should look for evidence that Octave is moving beyond portfolio aggregation toward a more integrated model of lifecycle intelligence.
Intelligence at Scale Depends on Integration, Data, and Workflow Relevance
The phrase “intelligence at scale” should be interpreted operationally, not rhetorically. In industrial environments, intelligence at scale means that software can connect relevant data, apply domain context, and support better decisions across complex workflows.
This requires more than analytics dashboards. It requires software that can help users understand the implications of decisions across functions. It also requires a data foundation that connects engineering data, project execution status, asset histories, maintenance records, geospatial information, quality events, safety incidents, and cybersecurity signals.
AI increases the importance of this foundation. AI capabilities will have limited enterprise value if they are disconnected from operational systems and industrial context. The more material opportunity is AI that is embedded in real workflows and supported by trusted domain data.
For Octave, the strategic question is whether its portfolio can support AI-enabled decision-making across the asset lifecycle, rather than isolated AI features within individual applications.
The Event Should Be Assessed as a Roadmap Signal
Buyers should treat Octave Live OnTour Austin as a roadmap signal.
The first area to assess is integration. Octave’s portfolio breadth creates potential value, but customers will need clarity on how the company intends to connect products and workflows over time. Important indicators include shared data models, workflow orchestration, user experience consistency, API strategy, and cross-domain analytics.
The second area is AI. Customers should listen for specific use cases, not general AI messaging. Relevant examples could include project risk identification, asset performance optimization, maintenance prioritization, quality exception management, safety response, cyber risk monitoring, or engineering decision support. The key issue is whether AI is being tied to operational outcomes.
The third area is ecosystem fit. Industrial organizations rarely standardize on a single vendor across the full technology landscape. Octave will need to clarify how its offerings interact with ERP, EAM, APM, MES, PLM, project controls, cybersecurity, and analytics environments. The value proposition must be additive without increasing architectural complexity.
The fourth area is sequencing. Broad portfolios require disciplined execution. A credible roadmap should identify where Octave will focus first, what integration steps matter most, and how customers should think about value realization over time.
Broader Market Implications
Octave’s Austin event matters because it reflects a larger shift in industrial software.
The next stage of the market will not be defined solely by applications that digitize individual workflows. It will be defined by platforms and architectures that connect operational context across functions. This does not mean every customer will consolidate around a single software suite. Industrial technology environments will remain heterogeneous. But the strategic requirement for connected data, workflow continuity, and decision support will continue to intensify.
AI will accelerate this trend. Effective AI depends on relevant context. If industrial data remains trapped in disconnected systems, AI will be limited to narrow productivity assistance. If data and workflows are connected, AI can support higher-value decisions involving risk, reliability, performance, safety, and resilience.
That is why lifecycle intelligence is becoming an important industrial software concept. It reflects the need to move from systems that record activity to systems that help organizations understand and act on operational complexity.
ARC Advisory Group Perspective
Octave has a credible opportunity to participate in this market transition. The company has meaningful software assets across multiple industrial domains, and its Design, Build, Operate, and Protect framework provides a practical way to organize the portfolio.
The central question is execution. Octave will need to demonstrate that its portfolio can become more than a set of adjacent capabilities. Customers will expect integration clarity, practical AI use cases, ecosystem openness, and a roadmap that connects near-term value to a longer-term lifecycle intelligence strategy.
For buyers, the Austin event should be used to evaluate roadmap direction and strategic fit. For partners, it should clarify Octave’s intended role in the industrial software ecosystem. For the broader market, it is another indication that industrial software is moving toward connected intelligence at scale.
The companies that define this next phase will not simply digitize industrial work. They will connect context across the asset lifecycle and convert that context into better decisions.
The post Why Octave’s Austin Event Matters: From Asset Lifecycle Software to Intelligence at Scale appeared first on Logistics Viewpoints.
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