Let’s start with the elephant in the room: predictive analytics has been overhyped and underutilized in IoT. Most organizations claim to be “data-driven,” yet struggle to operationalize even basic foresight. 

The problem isn’t a lack of models. It’s that predictive intelligence is being treated like a dashboard feature instead of a business enabler. 

When predictive analytics is siloed from your operational workflows, it becomes retrospective—ironic, isn’t it? To truly unlock its value, you must embed predictive intelligence in the orchestration layer, where decisions are made, not just visualized. 

Let’s explore 7 uncommon ways high-maturity organizations are using predictive analytics to fundamentally transform their IoT operations—not just report on them. 

Why it’s time to add a new brain to your IoT stack 

The next evolution of predictive analytics isn’t just mathematical — it’s conversational. OpenText Aviator IoT is now integrating a Large Language Model (LLM) into its orchestration layer, adding natural language understanding to your operational intelligence. 

This means operators, engineers, and supply chain leaders can ask complex questions in plain English — like “What’s the predicted failure risk for our pumps next week?” or “Show me anomalies in energy usage across our top 5 facilities” — and get real-time, contextual responses from the system. No queries to write, no dashboards to configure. 

By embedding LLM capabilities into Aviator IoT, OpenText is laying the groundwork for more intuitive human-AI interaction. Rather than simply visualizing predictive outcomes, users may soon be able to engage with them conversationally—potentially transforming how insights are accessed and applied across frontline operations. This paves the way for AI to become more explainable, usable, and operationally relevant at scale reducing the reliance on complex query languages.  

And in high-stakes industries like energy, manufacturing, and transportation, that means faster decisions, fewer errors, and smarter orchestration — without deep technical training. 

What are predictive analytics?  

Predictive analytics aren’t crystal balls. They provide clarity. Predictive analytics leverage historical data, statistical techniques, machine learning, and real-time inputs to anticipate what is expected to happen next. In today’s hyperconnected industrial ecosystems, where thousands of signals stream in from products, sensors, and machines, predictive analytics distills chaos into foresight. 

At its core, predictive analytics transform fragmented IoT data into forecastable outcomes—whether identifying a failing conveyor belt before it halts production or forecasting a demand spike for a critical pharma SKU. To operationalize predictive intelligence effectively, organizations must go beyond models and vendors. They must adopt platforms that connect insight with orchestration, enabling frontline execution at machine speed. That’s exactly where OpenText Aviator IoT delivers. 

7 Ways to leverage predictive intelligence for your IoT strategy 

The promise of predictive analytics in IoT is clear: fewer breakdowns, optimized operations, and smarter decisions. But while many organizations collect data and run models, few are turning those insights into real-world ROI.  

The difference? Execution. The following seven principles reveal what it takes to embed predictive intelligence into your operations, and unlock its full strategic value. 

1. Predictive maintenance isn’t about maintenance—It’s about asset strategy 

Yes, predictive analytics can help prevent downtime, but that’s just the starting point. The real unlock is using predictive insights to rethink your entire asset lifecycle strategy, and reshape how and when you deploy assets. 

Instead of reacting to failure, organizations are leveraging IoT-enabled models to simulate wear, stress, and fatigue long before equipment is deployed. This forward-looking approach allows teams to determine not just when to maintain, but where, how, and even if an asset should be deployed at all. 

By proactively identifying underperforming components or high-risk usage scenarios, enterprises can optimize asset placement, extend equipment life, and prioritize capital investment where it delivers the most value. The result isn’t just fewer breakdowns—it’s smarter capital planning, reduced total cost of ownership, and greater confidence in long-term infrastructure decisions. 

Key stat: Manufacturers using predictive analytics report up to 30% savings in maintenance costs (McKinsey). 

2. Anomaly detection should trigger autonomous action 

Most anomaly detection stops at alerts. But alerts without orchestration are just noise. The leaders are taking it further by tying anomalies directly into automated workflows. That means triggering repairs, routing alerts to service bots, or initiating self-healing routines.  

This approach transforms detection into resolution, reducing response times and minimizing downtime without requiring manual intervention. By embedding autonomous actions into everyday operations, organizations can move from reactive problem-solving to proactive system performance, so that issues are handled before users even notice. 

Think about it this way: If your system knows it’s breaking, why can’t it start fixing itself? 

3. Demand forecasting is obsolete without edge intelligence 

Using yesterday’s demand to plan tomorrow’s operations doesn’t cut it anymore. Forecasting needs to happen at the edge, where demand is shaped in real time by weather, market signals, or human behavior. Static models sitting in the cloud can’t keep up with dynamic environments.  

Edge intelligence allows organizations to process and act on data locally, without the latency of round trips to centralized systems. This means faster adjustments to inventory, pricing, and resource allocation based on what is happening right now. Not what happened last week. It’s how modern businesses stay agile in constantly shifting conditions. 

Use case: Smart retailers adjust supply chain inventory based on in-store footfall and ambient temperature, streamed via IoT. 

4. Asset optimization is the new sustainability strategy 

Everyone’s talking net zero. Few are connecting it to predictive analytics. Yet IoT can predict energy surges, idle time, and asset strain, allowing you to reduce emissions while optimizing performance. ESG meets ROI.  

Predictive insights help identify inefficiencies that traditional monitoring might miss, enabling smarter scheduling, right-sizing of energy loads, and timely asset adjustments. The result is a more sustainable operation that not only meets regulatory expectations but also drives measurable cost savings and long-term resilience. 

OpenText Insight: Unified intelligence and digital twins can model energy outcomes and adapt asset schedules in real time. 

5. Operational efficiency must be preemptive 

Don’t wait for a KPI to drop. Use predictive models to simulate bottlenecks before they cascade. Logistics, production, and facility management teams are now using digital twins powered by live IoT data to test "what-if" scenarios daily—not quarterly.  

This shift enables proactive adjustments to scheduling, routing, and resource allocation, reducing the likelihood of costly delays or disruptions. By modeling stress points before they occur, teams can make faster, smarter decisions that keep operations running smoothly. It means no surprises, and no scrambling. 

Why it matters: Operational resilience isn’t a nice-to-have. It’s now a board-level mandate. 

6. Predictive personalization is the frontline of retention 

You’re not just predicting churn. You’re predicting what makes people stay. Use interaction data from connected systems to forecast when to upsell, when to support, and when to innovate. If your product isn’t adapting to user behavior in real time, someone else’s will. 

Predictive personalization turns passive usage data into proactive customer engagement, creating moments of value before users even ask for them. It’s how connected brands move from one-time purchases to lasting loyalty, anticipating needs and delivering relevance at every touchpoint. 

Modern example: Smart appliances offering feature updates based on user behavior patterns. 

7. Energy forecasting is infrastructure resilience 

Power grids, manufacturing floors, and HVAC systems now face extreme volatility from climate disruptions and unpredictable consumption patterns. Predictive energy analytics allows organizations to simulate peak loads, optimize distribution, and preempt outages.  

It enables better planning for energy-intensive operations, supports sustainability targets, and reduces the risk of equipment failure due to overload. By anticipating demand and dynamically adjusting supply, businesses can maintain uptime, control costs, and build resilience into every layer of their infrastructure. 

Urgency: According to the IMF, technological fragmentation alone could shave 5% off GDP.  

Predictive analytics is not just a feature, it’s a foundation

Predictive analytics isn’t just a capability; it’s a strategic mindset shift. When integrated natively into your IoT orchestration layer, it transforms your entire operation into a self-correcting, insight-driven system. 

And that’s exactly what OpenText Aviator IoT delivers. Aviator IoT enables predictive maintenance to reduce downtime and optimize asset utilization 

️It’s not just about predicting failure. It’s about embedding foresight into every process. From asset orchestration and supply chain traceability to compliance and customer connection, Aviator IoT brings predictive insight to the edge, in real time. 

Ready to stop reporting and start orchestrating? 
Explore OpenText Aviator IoT 
Dive into our Track & Trace Solutions 

The post 7 Ways to operationalize predictive intelligence in IoT  appeared first on OpenText Blogs.

Choosing the right Internet of Things (IoT) platform provider is a critical step in any successful IoT implementation. As enterprises scale up their digital transformation initiatives, the complexity of managing diverse devices, ensuring security, and extracting actionable insights grows rapidly. The right IoT platform doesn’t just connect your devices—it connects your business to real-time intelligence, actionable insights, and future-ready innovation.  

But not all providers are created equal. Here are 7 expert tips to guide your evaluation process. Use these 7 enterprise-grade tips to evaluate and select a platform built for performance, security, and future innovation 

7 Must-know tips for IoT platform success 

1. Assess their track record and experience 

Start by evaluating the provider’s experience with similar use cases and industries. A strong track record shows the provider understands real-world implementation challenges and can offer proven methodologies, best practices, and frameworks. Ask for case studies, references, and measurable results. Ensure they can support both your current needs and future growth—scalability is key as your IoT network expands. 

2. Prioritize identity-driven security 

Security should be non-negotiable. The best IoT platforms take an identity-centric approach, authenticating and authorizing every device, user, and system interaction. This is critical in reducing attack surfaces and ensuring compliance with regulations like GDPR and HIPAA. Look for features like dynamic security contexts, autonomous authentication, and role-based access controls to protect both your devices and data from evolving threats. 

3. Evaluate integration flexibility 

An effective IoT platform must integrate seamlessly with your existing systems—ERP, CRM, WMS, cloud applications, and legacy technologies. Look for platforms that offer “any-to-any” communication protocol support (e.g., MQTT, FTP, APIs), making it easy to exchange data across disparate systems. This enables holistic insights and drives more value from your IoT data. 

4. Look for managed services and support options 

Managing an IoT ecosystem is complex, and not every organization has the in-house expertise to handle it. Check if the provider offers managed services, including 24/7 monitoring, maintenance, and technical support. This can significantly reduce your internal burden and ensure the platform performs optimally—especially important for mission-critical or regulated industries. 

5. Confirm end-to-end data protection and compliance 

Data generated by IoT devices often includes sensitive operational or personal information. Your platform should offer comprehensive data encryption—both in transit and at rest—as well as robust compliance management. Identity management, audit trails, and geographic data privacy controls are must-haves to meet evolving regulatory demands across regions. 

6. Demand extensibility and ecosystem compatibility 

Your IoT journey doesn’t end with device connectivity. You’ll want a platform that supports analytics engines, digital twins, reporting services, and other advanced capabilities. Make sure the provider supports an open architecture and has a portfolio of complementary solutions (e.g., AI, machine learning, or edge computing) that you can plug into as your needs evolve. 

7. Test their vision for innovation and longevity 

IoT is a long-term investment. Choose a provider that’s continuously innovating—one that can evolve with the pace of technology. Ask how often their platform is updated, what features are on their roadmap, and how they plan to incorporate advancements like AI, 5G, or blockchain. A provider with a strong vision for the future will help ensure your IoT strategy remains competitive for years to come. 

Don’t choose just a platform: Choose a partner 

Selecting an IoT platform provider goes beyond comparing feature lists—it’s about choosing a trusted partner who understands your goals, mitigates your risks, and grows with your business. From secure device onboarding to advanced analytics and ecosystem integration, the right provider will empower your organization to unlock the full potential of IoT. 

If you're just getting started or looking to scale an existing IoT implementation, use these tips as a foundation to guide your evaluation and selection process. The success of your digital transformation depends on it. 

Track every product. Protect your brand. Explore end-to-end supply chain traceability from OpenText.

The post How to build an enterprise-ready IoT platform: 7 essential tips  appeared first on OpenText Blogs.

As businesses across industries embrace the Internet of Things (IoT) to drive real-time insights, predictive maintenance, and operational efficiencies, the complexity of managing connected devices, data, and security continues to grow. That’s why an identity-driven IoT orchestration platform has become essential—not just for enabling IoT, but for scaling it securely and successfully. 

6 Key benefits of using an identity-first IoT orchestration platform 

Let's unpack six compelling reasons your organization needs an identity-driven IoT orchestration platform.  

1. Secure your IoT ecosystem from the ground up 

IoT ecosystems are prime targets for cyber threats due to the massive number of connected endpoints. On average, every week 54% of organizations suffer from attempted cyber-attacks that target IoT devices.  

An identity-driven orchestration platform ensures that every device, user, and system is authenticated and authorized before being granted access.  

This framework helps enforce zero-trust principles, reduces vulnerabilities, and provides auditability to meet data protection regulations. With the rise of edge computing, identity-first security also enables adaptive responses to emerging threats in real time, ensuring robust and scalable defense. 

2. Orchestrate diverse devices and protocols seamlessly 

IoT environments often include a mix of devices using different standards and protocols. An identity-driven IoT orchestration platform enables seamless orchestration by acting as a unified layer that abstracts these complexities.

It standardizes device communication and ensures consistent roles, permissions, and interactions. This allows for smooth onboarding, integration, and real-time coordination of devices, reducing operational overhead and enhancing responsiveness, especially in dynamic settings like logistics or smart manufacturing. 

3. Enable scalable and flexible integration 

Integrating IoT with enterprise systems can be difficult without the right foundation. An identity-centric IoT orchestration platform enables secure, any-to-any communication across legacy systems, cloud services, and modern applications.

It ensures that IoT data flows are governed, traceable, and secure. The platform's modular architecture allows businesses to expand capabilities quickly and efficiently while maintaining control, making IoT a strategic enabler of digital transformation rather than a standalone initiative. 

4. Ensure data integrity and compliance 

In an IoT environment, massive volumes of data are constantly generated, transmitted, and analyzed. An identity-driven orchestration platform ensures that each data transaction is tied to a verified identity, maintaining integrity and traceability.

This level of accountability supports compliance with regulations like GDPR and HIPAA, while also preventing data misuse. By enforcing secure data flows and encryption protocols, an IoT orchestration platform provides confidence that sensitive information is protected at every stage. 

5. Automate decisions with trustworthy data 

Automation is only as effective as the data that powers it. Identity-driven orchestration ensures data is collected from verified sources and validated before entering analytics pipelines or triggering automated workflows.

This improves the accuracy of predictive maintenance, real-time alerts, and supply chain decisions. With trusted data, organizations can confidently implement AI-driven strategies that enhance efficiency and responsiveness across operations. 

6. Manage the lifecycle of every ‘thing’ 

Every connected device has a lifecycle that must be managed—from onboarding and configuration to updates and retirement. An identity-centric IoT platform assigns and tracks unique identities for each device, enabling precise control throughout its lifecycle. This streamlines provisioning, enhances monitoring, and simplifies the process of revoking access when a device is decommissioned. It ensures your IoT environment remains secure, efficient, and scalable as it evolves. 

Get started with an identity-driven IoT orchestration platform 

By adopting an identity-driven IoT orchestration platform, your organization lays a secure, scalable foundation for innovation. Whether you’re managing a global fleet or optimizing a smart factory, putting identity at the center of your IoT strategy ensures you stay agile, compliant, and in control. 

Track every product. Protect your brand. Explore end-to-end supply chain traceability from OpenText.

The post 6 Reasons why businesses need an identity-driven IoT orchestration platform  appeared first on OpenText Blogs.

In today’s fast-moving, interconnected world, businesses are turning to digital supply chains to stay competitive, resilient, and customer-focused.  

By leveraging advanced technologies like AI, IoT, and blockchain, digital supply chains offer a smarter, faster, and more efficient way to manage operations—from procurement to delivery.  

In this blog, we explore eight powerful benefits of supply chain digitization and how it can transform your business for long-term success. 

What is the digital supply chain? 

Today’s most successful companies have achieved advanced levels of digital sophistication and maturity within their supply chains. Research from IDC shows a strong correlation between digital maturity and superior business performance, including higher revenue growth and profitability. 

Unlike traditional supply chains—which are often linear, fragmented, and reliant on outdated systems—digital supply chains operate in real time, adapt dynamically to changing conditions, and foster stronger collaboration. They are built around ecosystems of interconnected partners and suppliers, linking internal systems with external data sources to enable seamless information sharing, responsiveness, and end-to-end visibility. 

At the heart of a digital supply chain is a digital backbone—a foundational infrastructure that allows all transactions to occur digitally. This enables efficient, transparent collaboration across stakeholders, including suppliers, customers, logistics providers, and financial institutions. The digital backbone serves as a platform on which companies can deploy advanced technologies to pursue strategic goals and seize new opportunities. 

The real power of the digital supply chain lies in its ability to collect accurate, comprehensive, and timely data—and transform that data into actionable insights. These insights lead to better decisions, improved operational efficiency, reduced costs, and more resilient supply networks. 

Supply chain digitization vs. supply chain digitalization 

While often used interchangeably, supply chain digitization and supply chain digitalization represent two distinct stages in the evolution of modern supply chains. 

• Supply chain digitization is the process of converting physical documents, such as paper-based records, into digital formats. This foundational step improves data accessibility and enables more efficient handling of information. 

• Once data is digitized, companies can move to supply chain digitalization, which involves using digital tools and technologies to automate workflows, enhance visibility, and improve process efficiency. Digitalization is about transforming operations—not just making them digital, but also smarter, faster, and more integrated. 

Together, these steps lay the groundwork for building a fully connected and intelligent digital supply chain. 

Key benefits of the digital supply chain 

Digitalization of the supply chain enables better use of resources, optimized production, stronger supplier relationships, increased visibility, and a healthier bottom line. Let's dive into the key benefits of the digital supply chain.  

1. Reduced cost and improved revenue 

By virtually eliminating manual tasks, the digital supply chain dramatically reduces human error and input time while freeing staff for higher value activities. According to one study, the average annual cost for organizations to manually enter data into ERP and back-end systems alone was more than $1 million. 

At a strategic level, improving the speed, quality and accuracy of tasks, such as demand forecasting, inventory management and order fulfilment, directly drives revenue and profitability. 

2. Increased supply chain visibility 

In a recent survey (Reuters Events, The state of European Supply Chains 2024) addressing supply chain visibility gaps was prioritized as a top area for investment, reported by 68 percent of the respondents.  

The problem is the vast number of disconnected legacy systems used to address each stage in the traditional supply chain process. This includes a lack of integration between information technology (IT) and operational technology (OT) systems. 

Digitizing the supply chain creates opportunities for breaking down these barriers and connecting disparate systems both internally and externally. As a result, data can pass quickly and securely across the entire supply chain, enabling near real-time visibility. Supply chain visibility makes it possible for staff to instantly see the current status of any activity, enabling them to make informed decisions. 

3. Improved decision-making  

For most businesses, decisions need to be made quickly, and agility is vital. Basing decisions on historical reports and spreadsheets is far from optimal. Research has shown that more than two thirds of supply chain managers still use Microsoft® Excel® as an inventory management tool. In the world of big data, this isn’t ideal.  

A digitized supply chain allows organizations to gather and analyze massive amounts of data with far less effort and in far less time. The ability to gain insight from real-time data generated anywhere in the supply chain offers significant benefits in every aspect of the business, from product development to sales and marketing to customer experience. 

4. Building supply chain resilience  

The COVID-19 pandemic revealed serious and systematic weaknesses in supply chains. Global supply chains have become extended and complex to take advantage of low-cost sourcing, lean inventories, and Just-in-Time manufacturing practices.  

When supply chains became disrupted, organizations found it difficult to maintain logistics routes or switch to alterative suppliers. IDC found that diversifying their sourcing strategies, along with improving supply chain visibility, were the most important focus areas for organizations to mitigate the impacts of disruption. 

Digital supply chains allow for deeper connections and improved collaboration between trading partners, as well as an ecosystem of suppliers, which makes alternative sourcing arrangements faster and more effective.  

Overall, digitalization helps build supply chain resilience and more sustainable supply chains. This enables increased mobility and accountability while driving proactive responses to emerging problems.  

5. Supply chain automation  

Automation improves overall supply chain performance by eliminating friction and choke points between functions. In addition, it creates new business opportunities and a better customer experience through enabling innovative self-service options.  

However, most organizations have yet to realize the full benefits of supply chain automation. As the use of AI expands and more complex processes are targeted for automation, the effectiveness of these efforts increasingly depends on robust process transformation, high-quality data, and strong digitization and digitalization capabilities to deliver desired outcomes. 

6. Driving collaboration and innovation  

The digital supply chain enables multi-enterprise collaboration by breaking down data silos within an organization and between external partners. It allows seamless and secure integration between the systems of the organization and its suppliers, customers, logistics, and financial institutions.  

Through digital enablement, data becomes actionable; workflows are streamlined; and critical information such as order milestones, inventory statuses, and payments can be shared securely and instantly.  

Organizations and their partners can quickly establish shared responsibilities and accountability and track them in real time. As organizations look towards their partners to improve their competitiveness in the market and drive increased collaboration in product design and development, a digital supply chain is the foundation of success. 

7. Enhancing sustainability  

With consumers increasingly favoring companies and products they perceive as sustainable, brands are seeking external partners with good sustainability records and may require their existing partners to address identified gaps. The digital supply chain has a major role to play in helping businesses reduce their impact on the environment through efficient management of stock and avoidance of waste.  

Digitalization enables improved inventory and materials management, ensures accurate tracking of goods in transit, and helps avoid materials shortages, all of which leads to more efficient use of resources. It also improves visibility into the supply chain, which helps organizations to better identify, and address risks related to sustainability and ethical business practices. 

8. Enabling technologies 

Organizations can increase revenue, save expenses, reduce risk, and boost customer experience by developing digital supply chain capabilities to improve operations and make smarter decisions faster. 

 There are several complementary digital technologies that enable this, including: 

• Multi-Enterprise Collaboration Networks 
  These cloud-based platforms connect all supply chain partners on a single network, enabling seamless collaboration, real-time data sharing, and greater agility across the ecosystem. 

• Internet of Things (IoT) 
  IoT devices provide real-time visibility into assets and shipments, linking the physical and digital worlds to improve tracking, operations, and decision-making. 

• AI and Machine Learning 
  AI/ML analyze large volumes of supply chain data to enhance forecasting, optimize operations, and automate decision-making for improved efficiency and cost savings. 

• Digital Twins 
  Digital twins create virtual models of physical products or processes using real-time data, allowing predictive simulations and better insights into operations and supply chain scenarios. 

• Supply Chain Command Centers 
  Supply chain command centers centralize and analyze supply chain data to enable proactive monitoring, issue resolution, and faster responses to disruptions and changing conditions. 

• Blockchain 
  Blockchain secures and tracks supply chain transactions in an immutable ledger, enhancing transparency, reducing fraud, and eliminating intermediaries. 

• Identity and Access Management (IAM) 
  IAM systems control and secure access to supply chain platforms and data, ensuring only authorized users and devices can interact with sensitive systems in real time. 

Digital supply chain transformation: How to get started 

Today, digitally transforming supply chains is crucial for most organizations. It is an increasingly important step to ensure long-term business success, drive efficiency, deliver sustainability, and, most importantly, create better customer experiences.  

However, this is no simple undertaking. It is unlikely that any business can implement a “rip and replace” strategy when digitizing their supply chain. Instead, an incremental, planned approach designed to produce tangible benefits is the best way to get started. 

 To take the first step toward a smarter, more connected supply chain, organizations need the right partner and platform. OpenText Digital Supply Chain Collaboration provides tools to digitize operations, enhance visibility, and drive seamless, secure collaboration across your entire ecosystem. Learn how OpenText can help you accelerate transformation and unlock the full value of your supply chain.  

The post 8 Benefits of leveraging the digital supply chain  appeared first on OpenText Blogs.

Supply chain collaboration is more critical than ever as global networks grow in complexity and customer expectations continue to rise. However, achieving seamless collaboration across suppliers, partners, and internal teams is no easy feat.  

In this blog, we explore the key benefits of effective supply chain collaboration and share four practical strategies to help you overcome common obstacles and build a more connected, agile supply chain. 

The benefits of supply chain collaboration 

At its core, supply chain collaboration is the process of connecting and aligning all stakeholders—suppliers, partners, logistics providers, and internal departments—to work together more effectively. When done well, it creates a transparent, responsive network that delivers better outcomes for everyone involved. 

The benefits are substantial: improved visibility and communication, faster time to market, lower operational costs, greater agility in responding to disruptions, and a better customer experience. With increasing global uncertainty, supply chain collaboration has evolved from a competitive advantage to a business necessity. 

While many challenges stem from technical limitations like fragmented systems and manual processes, others are organizational in nature—such as data inconsistency, lack of transparency, or misaligned objectives between partners.  

Read on to learn four technology-driven strategies that address both technical limitations as well as organizational barriers to collaboration. The right supply chain collaboration software, combined with professional expertise tailored to your business needs, plays a pivotal role in enabling and optimizing these improvements. in enabling and optimizing these improvements. 

4 solutions for common supply chain collaboration challenges 

Modern supply chains face a range of collaboration challenges, from fragmented processes to security risks. These four solutions help businesses overcome common pain points and build stronger, more efficient partnerships.  

1. Consolidate supplier onboarding into a unified workflow 

Many organizations struggle with complex, resource-intensive supplier onboarding processes that span multiple systems and departments. To address this, businesses can simplify onboarding by centralizing it on a single platform that integrates with their ERP system.  

By streamlining workflows and enabling self-service capabilities, companies can automate data collection, accelerate approvals, and ensure consistent supplier interactions. The result is faster onboarding, lower administrative costs, easier community management, and a more seamless, professional experience for trading partners. 

2. Eliminate manual processes with system-to-system integration 

Manual processes continue to bog down supply chains—especially in critical functions like order-to-cash and procure-to-pay. These tasks often involve re-keying data between disconnected systems, which not only slows things down, but also introduces errors and inefficiencies.  

By replacing manual steps with automated data exchanges using EDI, APIs, and other integration technologies, companies can create seamless, system-to-system connectivity across their internal operations and external trading partners. This shift doesn’t just save time. It improves data quality, reduces costly errors, and gives teams real-time visibility into transactions, helping them respond faster and work smarter. 

3. Strengthen access and security through centralized identity management 

When users need multiple logins to access different systems, it creates more than just frustration—it introduces serious security risks and administrative complexity. A centralized identity and access management (IAM) solution can solve this by enabling federated access control across your entire supply chain ecosystem.  

With a single, secure framework for authenticating both internal and external users, IAM simplifies access while strengthening your security posture. This approach not only improves compliance and reduces IT overhead but also supports customer self-service and smoother collaboration. Ultimately, this helps your teams work more securely and efficiently. 

4. Leverage AI to enhance collaboration and predictive insights  

Supply chains thrive on speed and agility, but delays, inefficiencies, and slow responses remain all too common. That’s where AI comes in. By automating key collaboration tasks—like supplier onboarding, performance tracking, and risk detection—AI removes friction from the process and frees teams to focus on higher-value work.  

Tools like intelligent assistants and predictive analytics help teams anticipate issues before they escalate and make faster, data-driven decisions. Beyond improving responsiveness, AI also lightens the load on customer support and IT, unlocking scalable gains in efficiency across the entire ecosystem. 

Streamline your supply chain collaboration 

Building an efficient, secure, and connected supply chain requires more than just good intentions—it requires the right tools and strategies. By consolidating onboarding, integrating systems, securing access, and leveraging AI, organizations can overcome the most common collaboration challenges and unlock significant operational value. 

OpenText Digital Supply Chain Collaboration solutions offer the capabilities needed to make this transformation possible. From cloud-based integration to identity management and AI-powered automation, OpenText helps businesses modernize their supply chain operations and foster stronger, more collaborative relationships with partners.  

With the right supply chain collaboration software and decades of professional B2B integration experience, OpenText enables faster partner onboarding, stronger compliance, and improved operational resilience.

Learn more about OpenText Digital Supply Chain Collaboration. 

The post 4 Strategies to overcome supply chain collaboration challenges  appeared first on OpenText Blogs.

Supply chains report that 3% to 20% is lost to chargebacks each year (Source: Gartner Top 5 Practices to Reduce Retailer Chargebacks and Lower Costs). And in today’s fast-paced, data-driven supply chains, chargebacks are a costly and often avoidable problem.  

These penalties, typically issued when a trading partner fails to meet specific requirements, can erode profit margins, damage relationships, and disrupt operations.  

Fortunately, digital supply chain collaboration offers ways to reduce and even prevent retailer chargebacks. By improving visibility, communication, and data accuracy, businesses can align more closely and avoid the pitfalls that lead to chargebacks. 

What is supply chain chargeback management?  

A supply chain chargeback is a financial penalty that a retailer or distributor imposes on a supplier for failing to meet agreed-upon requirements, such as late shipments, incorrect labeling, or incomplete orders. Supply chain chargeback management aims to reduce these penalties by identifying root causes, improving compliance, and streamlining operations across the supply chain. 

5 tactics to prevent supply chain chargebacks  

Supply chain management software streamlines fulfillment by improving order accuracy, automating workflows, and providing real-time visibility, helping businesses avoid chargebacks due to delays or errors. 

Here are five tangible ways to tackle chargebacks using digital tools and smarter collaboration: 

1. Identify and group chargeback root causes 

The first step in solving any problem is understanding it. Supply chain chargebacks often stem from recurring issues like late shipments, incorrect labeling, or mismatched purchase orders. However, without a clear view of the data, these issues can seem random or isolated. 

What to do: 

• Use digital dashboards to track chargeback trends over time. 

• Group chargebacks by root cause categories—such as shipping errors, documentation issues, or compliance failures. 

• Visualize this data to spot patterns and prioritize the most frequent or costly issues.  

By categorizing chargebacks, you can move from reactive firefighting to proactive problem-solving. 

2. Assign owner for compliance improvements 

Once you know what’s going wrong, the next step is to make sure someone is responsible for fixing it. Too often, chargeback management falls through the cracks because no one owns the process. 

What to do: 

• Assign clear ownership of chargeback categories to specific teams or individuals—such as logistics, warehouse operations, or customer service. 

• Set KPIs and accountability metrics for reducing chargebacks in each area. 

• Use workflow tools to track progress and ensure follow-through. 

When everyone knows their role in compliance, it becomes easier to make consistent improvements. 

3. Boost collaboration with suppliers, retailers 

Chargebacks are often a symptom of poor communication between trading partners. Misaligned expectations, unclear requirements, or last-minute changes can all lead to costly mistakes. 

What to do: 

• Use cloud-based platforms to share real-time data with suppliers and retailers. 

• Set up automated alerts for order changes, shipment delays, or compliance risks. 

• Hold regular collaboration meetings to review performance and align with expectations. 

Digital collaboration tools help ensure that everyone is working from the same playbook—reducing misunderstandings and improving execution. 

4. Use data tools to improve performance 

Modern supply chains generate massive amounts of data. The key is turning that data into actionable insights that help prevent supply chain chargebacks before they happen. 

What to do: 

• Implement predictive analytics to flag potential issues—like shipments at risk of delay or orders with missing documentation. 

• Use machine learning models to identify which suppliers or SKUs are most likely to trigger chargebacks. 

• Integrate data from multiple systems (ERP, WMS, TMS) to get a 360-degree view of supply chain performance. 

With the right tools, you can shift from reacting to chargebacks to preventing them altogether. 

5. Strengthen quality checks and dispute handling 

Even with the best systems in place, mistakes can still happen. That’s why it’s important to have strong quality control and a clear process for disputing chargebacks when they’re issued in error. 

What to do: 

• Introduce automated quality checks at key points in the supply chain—such as before shipping or receiving. 

• Use digital documentation (photos, timestamps, scan logs) to verify compliance and support dispute claims. 

• Create a centralized chargeback portal where teams can track, investigate, and respond to chargebacks efficiently. 

A strong dispute process not only helps recover lost revenue but also builds trust with trading partners. 

Prevent chargebacks: Collaboration is the cure for chargebacks 

Supply chain chargebacks are often a symptom of deeper issues, such as miscommunication, poor data quality, or lack of visibility within a supply chain. OpenText Business Network Cloud helps businesses reduce chargebacks by providing end-to-end visibility and automation across trading partner interactions. Our Trading Grid and Command Center solutions enable businesses to identify and group chargeback root causes through advanced analytics and real-time monitoring of transaction data.  

It supports assigning ownership for compliance improvements, such as e-invoicing, by integrating workflows and role-based dashboards that track and trace accountability throughout your entire supply chain.  

OpenText enhances collaboration with suppliers and retailers via a centralized, cloud-based environment that facilitates seamless data exchange and communication. No matter your industry or geographic location, the path to fewer chargebacks and better performance starts with a smarter, more collaborative connected community. 

The post How to prevent retailer chargebacks in your supply chain: 5 proven tactics  appeared first on OpenText Blogs.

Every June 27th, we celebrate Micro, Small, and Medium Enterprises (MSMEs). These businesses are the backbone of our economy, driving innovation, creating jobs, and fostering vibrant communities. This year, MSME Day 2025 carries a powerful theme: 
“Enhancing the Role of MSMEs as Drivers of Sustainable Growth and Innovation.” 

 At OpenText, we recognize the unique challenges faced by MSMEs. Often, MSMEs lack the resources of larger corporations, yet they need enterprise level integration to compete in the global marketplace. That’s why we are proud to support MSMEs with easy EDI integration solutions that help them grow, compete, and innovate while building long-term sustainability.  

What is MSME Day? 

Recognized by the United Nations since 2017, MSME Day raises awareness about the critical role MSMEs play in building strong, inclusive, and sustainable economies. These businesses: 

• Represent 90 percent of all companies worldwide 

• Provide over 70 percent of global employment 

• Contribute approximately 50 percent of global GDP 

This year’s theme highlights the importance of MSMEs in leading innovation and driving responsible growth. 

OpenText is aligned with this mission by offering integration and automation solutions that help MSMEs operate more efficiently, reduce waste, and adapt to changing global standards for sustainable business. 

Why supporting MSMEs matters more than ever  

MSMEs often face significant hurdles, including: 

• Limited access to financing and technology 

• Disruption from global economic shifts or supply chain issues 

• Difficulty scaling digital operations 

Yet these businesses are uniquely positioned to lead innovation at the local level and shape resilient, sustainable economies. 

OpenText bridges the gap by delivering digital infrastructure that enables MSMEs to overcome resource limitations. Our EDI solutions are designed to simplify supply chain integration and support long-term business continuity regardless of size or budget. 

How OpenText supports MSMEs with flexible, scalable digital solutions  

With decades of experience in EDI integration, OpenText offers solutions that go far beyond basic document exchange. Our technology is built for the evolving needs of MSMEs, supporting a wide range of communication protocols, data standards, and deployment models. We help businesses stay compliant with global mandates, adapt quickly to changing partner requirements, and harness the power of AI and analytics to unlock new opportunities. 

Key benefits of OpenText EDI for MSMEs: 

• Quick and scalable deployment 
  Get started quickly with expert onboarding and personalized support. 

• Custom supply chain integration 
  Integrate with internal ERP systems and external trading partners for operational efficiency. 

• Real-time transaction visibility 
  Gain full oversight of your data to make more informed, timely decisions. 

• Flexible support models 
  Choose between self-service tools or managed services based on your business needs and budget. 

• Growth-ready technology 
  Scale confidently with a solution built to support long-term sustainability and innovation. 

By reducing manual effort and enabling smarter, data-driven logistics, OpenText solutions also help MSMEs lower their environmental footprint, further supporting the theme of sustainable growth. 

Join the celebration and embrace growth  

MSME Day is a time to celebrate the incredible achievements of small businesses. But it’s also a call to action. Learn more about OpenText and discover how to overcome EDI integration hurdles to unlock new levels of efficiency and growth.  

Happy MSME Day!  

The post MSME Day 2025 – Celebrating the engine of our economy  appeared first on OpenText Blogs.

As summer arrives in the Northern Hemisphere, there's a familiar shift in pace—schools slow down, out-of-offices go up, and calendars open just enough to take a breath. For many, this season invites a moment to reset, reflect, and prepare for what’s next. And at OpenText Business Network, that’s exactly what our latest releases do for your digital supply chain: they deliver fresh innovations to reduce complexity, respond to evolving customer needs, and help businesses thrive in a world that's always on.

OpenText™ Business Network is a leading cloud platform for B2B integration and supply chain collaboration, enabling organizations to connect systems, partners, and data across complex ecosystems. With AI-driven insights, built-in compliance, and a highly secure infrastructure, the platform helps global businesses digitize operations, boost agility, and scale with confidence.

Since our last update in December, we’ve delivered two major releases—25.1 in January and 25.2 in April—packed with enhancements that simplify operations, strengthen resilience, and accelerate decision-making. Here’s what’s new:

Smarter Insights with Command Center and Trading Grid with Aviator

AI continues to take center stage in Business Network, making it easier for users to analyze integration health and act faster:

• Error message analysis: When B2B transaction errors occur, identifying the root cause can be time-consuming. This feature uses AI to surface patterns, diagnose recurring issues, and suggest resolutions in real time—reducing delays and improving recoverability.

Trading Grid Insights Error Analysis 

• Ask Aviator for Command Center—Integration Monitor: Business users can now get instant answers about document flows, partner activity, and platform performance—without needing technical expertise. This helps teams monitor operations proactively and resolve issues before they impact customers.

Ask Aviator in Integration Monitor 

• Payload Analysis: Business users no longer need to interpret raw EDI data on their own. With Aviator, anyone can simply ask a question in natural language—like “What is this invoice for?”—and instantly receive a plain-English explanation. It’s a game changer for making complex supply chain data understandable and usable across teams.

Trading Grid with Aviator Payload Viewer 

• Transaction Finder: Give your team the power to explore transaction data their way. Using intuitive, conversational search, users can uncover specific insights—such as delayed shipments or missing acknowledgments—without digging through multiple screens. It’s flexible, fast, and built for real-time answers.

Trading Grid with Aviator Transaction Finder 

• Enhanced Historical Analytics: REST APIs and deeper insights into partner and document metrics make it easier to track long-term integration trends and power custom reporting.

Elevating Trading Grid Insights

Formerly known as Trading Grid Lens, Trading Grid Insights is now tightly integrated with Aviator for real-time, AI-driven queries:

• Service Traffic Prioritization: New visibility tools allow IT to manage low- vs. high-priority traffic during peaks, ensuring consistent uptime and service levels.
• Partial Processing Status: Improved tracking for partially processed documents helps teams stay on top of exception handling and reduces bottlenecks.

Global Compliance at Your Fingertips

Keeping up with eInvoicing mandates worldwide is no easy task—but we’ve made it easier with expanded compliance capabilities:

• 25.1 introduced support for the latest Franco-German Factur-X and ZUGFeRD standards, including German X-Rechnung validation.
• 25.2 added support for Romania (via in-house development), Singapore, and E-Reporting on our TG E-Invoicing Navigator platform.

Integration Enhancements: Secure, Scalable, and Self-Service

• Advanced SFTP & Containerization: Enhanced security and streamlined deployment are delivered through advanced SFTP support and containerized services for Messaging and Data Integrator.
• ERP Adapter Expansion: New integrations include SAP S/4HANA P2P, Oracle Fusion SCM, MS Dynamics 365 (Finance & Operations, Business Central), and NetSuite—simplifying ERP-to-B2B integration across more environments.
• Self-Service Capabilities: From onboarding partners to deleting records and setting up translation maps, our TG Quick Connect workflows reduce onboarding time and empower business users to act independently.

Enhancing Supplier Collaboration

• Purchase Order Negotiation: Businesses can now collaborate on POs with trading partners before syncing into back-end systems, improving accuracy and reducing order rework.
• Package Codes and PO Notes: Shipment and order data are now more precise with added support for dimensional package data and embedded notes.

Expanding Platform Access and Security

• SCIM and SSO Enhancements: Streamlined provisioning of users and partners across systems improves identity governance and speeds up community onboarding.
• Vault & Key Management: Credential management now aligns with enterprise security standards, reducing risk and meeting compliance mandates.

Performance and Productivity Boosts

• Faster Processing: Onboarding and deduction tasks are now processed more efficiently, with split batch processing minimizing delays.
• Improved Portal Search and Custom URLs: Enhancements to Core Collaboration Access include more comprehensive search and support for customer-branded URLs in shared communities.

A Season of Growth with OpenText Business Network

Just like summer offers time to pause and plan, OpenText Business Network’s latest innovations help you step back, realign, and move forward with purpose. Whether it's gaining real-time insights, streamlining compliance, or giving your teams more control, our 25.1 and 25.2 releases are designed to help you build smarter, more connected supply chain ecosystems.

We’re excited about what’s ahead—and we’ll be back later this year with even more updates to keep you moving forward.

The post What’s New in OpenText Business Network Cloud appeared first on OpenText Blogs.

In 2025, Agentic AI has entered the vocabulary of nearly every CIO around the world. Many companies are still in the exploratory stages of Agentic AI, which means there’s no better time than now to embrace this next evolution of AI.

CIOs have been inundated with a mix of different technologies over the past decade. For example, in 2018, blockchain looked promising for the industry—but struggled to get off the ground as originally intended due to its complexity. Agentic AI and Gen AI are different propositions, but promise to add true value to a business operations.

The main reason for the success of Gen AI to date is that anyone can use the technology, both at work and at home. We’re all welcome to use it on our own PCs or mobile devices, enabling us to discover new insights. 

This ‘consumerization’ of Gen AI has been key to why it has spread so quickly around the world, inside companies of every size. But what happens when you combine process automation with AI capabilities? For supply chain and integration leaders, it means gaining intelligent EDI agents that proactively resolve issues, adapt to shifting demands, and free up their teams to focus on higher-value work—not manual troubleshooting.

Let’s dive into what agentic EDI is, and how it will transform supply chain orchestration.

What are EDI agents?

Electronic Data Interchange (EDI) transactions have been exchanged across global supply chains for decades, but only now can we start to explore opportunities to really ignite the potential of using the data within an EDI transaction to drive insights and optimize supply chain processes like never before.

Many new technologies have been introduced over the past 50 years since the very first EDI transaction was exchanged, and the technology has evolved with each new piece of technology that entered the market. Agentic EDI represents the next evolution of technology that will fundamentally change the EDI landscape.

In the ever-evolving world of supply chain and procurement, the pressure to move faster, smarter, and more efficiently has never been greater. Traditional EDI systems—while foundational—are increasingly seen as rigid, rule-based, and reactive.

Enter agentic EDI: a transformative fusion of Agentic AI and EDI that promises to revolutionize how organizations manage data, decisions, and disruptions.

Agentic EDI refers to the integration of autonomous AI agents into EDI systems, enabling them to not only exchange structured data but also interpret, act on, and optimize that data in real time. Unlike traditional EDI, which simply transmits purchase orders, invoices, and shipping notices between systems, agentic EDI systems will:

• Make decisions based on contextual data
• Adapt workflows dynamically
• Collaborate with other agents or humans
• Learn from outcomes to improve over time

This shift mirrors the broader trend of Agentic AI—AI systems that operate with a degree of autonomy, capable of initiating actions, making decisions, and collaborating across complex enterprise environments.

With EDI agents we have an opportunity to unlock the potential of the data that resides inside an EDI transaction. Here at OpenText we help companies exchange more than 31 billion transactions per year, if you consider that each transaction has 80 data fields, on average, that represents 2.5 trillion pieces of data.

Why agentic EDI matters to supply chain and procurement leaders

For executives, agentic EDI represents a leap from automation to autonomy. It’s not just about reducing manual effort—it’s about enabling resilient, intelligent, and proactive operations. In a world where supply chain disruptions, compliance risks, and cost pressures are constant, EDI agents offer a strategic edge.

This technology aligns with broader digital transformation goals, helping organizations move from siloed, reactive systems to connected, intelligent ecosystems. This evolution is critical for staying competitive in a global market where agility and foresight are paramount.

Five high-impact use cases of agentic EDI

1. Autonomous supplier onboarding and compliance

Traditional supplier onboarding is slow, manual, and error prone. Agentic EDI systems will autonomously:

• Validate supplier credentials against third-party databases
• Check compliance with ESG, regulatory, and contractual standards
• Initiate onboarding workflows and flag anomalies

This potentially reduces onboarding time from weeks to hours and ensures compliance from day one. It also improves supplier experience and accelerates time-to-value.

2. Dynamic purchase order optimization

In conventional EDI, purchase orders are static documents. With agentic EDI, AI agents will:

• Analyse real-time inventory, demand forecasts, and supplier performance
• Adjust quantities, delivery windows, or even suppliers dynamically
• Negotiate terms autonomously within predefined guardrails

This ensures optimal procurement decisions even in volatile markets. It also reduces stockouts, excess inventory, and procurement costs.

3. Proactive risk detection and mitigation

Agentic EDI systems will continuously monitor:

• Supplier delivery patterns
• External risk signals (e.g., geopolitical events, weather, financial health)
• Internal KPIs (e.g., late deliveries, quality issues)

When a risk is detected, the system can autonomously reroute orders, notify stakeholders, or trigger contingency plans—minimizing disruption without human intervention. This capability is vital for building resilient supply chains.

4. Intelligent invoice reconciliation and fraud detection

Invoice matching is a classic EDI function, but agentic EDI will take it further:

• AI agents can detect anomalies in pricing, quantities, or payment terms
• Cross-reference invoices with contracts, POs, and delivery receipts
• Flag or resolve discrepancies autonomously

This not only reduces fraud and errors but also accelerates payment cycles and improves supplier relationships. It also supports touchless invoicing, freeing up finance teams for strategic work.

5. Collaborative demand planning and forecasting

Agentic EDI systems will integrate with demand planning tools and external data sources (e.g., market trends, social signals) to:

• Predict demand shifts
• Collaborate with suppliers to adjust production schedules
• Automatically update procurement plans and inventory targets

This creates a more agile, responsive supply chain that can pivot in real time. It also supports just-in-time and just-in-case inventory strategies.

Additional use cases for EDI agents

As agentic EDI matures, new applications will emerge:

• Sustainability Tracking: Agents will monitor carbon emissions, ethical sourcing, and ESG compliance across the supply chain.
• Contract Lifecycle Management: AI will track contract terms, trigger renewals, and ensure compliance.
• Returns and Reverse Logistics: Agents will automate return authorizations, restocking, and credit issuance.
• Supplier Collaboration Portals: AI agents will act as digital assistants for suppliers, answering queries and guiding processes.
• Multi-Tier Visibility: Agentic EDI will extend beyond Tier 1 suppliers to monitor Tier 2 and Tier 3 risks and performance.

Implementation considerations for agentic EDI

While the potential is vast, implementing agentic EDI requires careful planning:

• Data Quality: AI agents are only as good as the data they consume. Clean, structured, and real-time data is essential.
• Change Management: Teams should be trained to work alongside autonomous systems and trust their outputs.
• Governance: Guardrails must be in place to ensure AI agents operate within ethical, legal, and strategic boundaries.
• Integration: Agentic EDI must seamlessly connect with ERP, TMS, WMS, and supplier systems.
• Security and Compliance: As agents access sensitive data, robust cybersecurity and compliance frameworks are critical.

The strategic payoff of agentic EDI

For supply chain and procurement executives, agentic EDI is more than a technology upgrade—it is a strategic enabler. It allows organizations to:

• Improve decision accuracy through real-time insights
• Enhance resilience by proactively managing risks
• Free up talent to focus on strategic initiatives
• Improve supplier collaboration and satisfaction

Those who embrace this shift early will not only streamline operations but also gain a competitive edge in an increasingly complex global landscape.

EDI agents are the natural evolution of supply chain automation—moving from static data exchange to intelligent, autonomous orchestration. For procurement and supply chain leaders, it offers a powerful way to drive efficiency, agility, and strategic value in a world where speed and intelligence are the new currency.

The journey to agentic EDI is not without challenges, but the rewards are substantial. Organizations that explore the potential of these technologies now will be better positioned to navigate uncertainty, capitalize on opportunities, and lead in the next era of digital supply chains.

Looking to reimagine your supply chain operations? Learn how OpenText Business Network can help.

The post Agentic EDI: The next evolution in intelligent supply chain orchestration appeared first on OpenText Blogs.

Migrating from older generation ERP systems to SAP S/4HANA offers great potential to improve operational performance and transform business processes. However, this major program doesn’t happen in isolation. A smooth transition requires careful attention to SAP S/4HANA integration, especially SAP EDI Integration with external trading partner systems.

5 questions to answer before migrating to SAP S/4HANA

As companies plan for their S/4HANA migration, addressing key SAP HANA integration challenges early on will help mitigate risks, prevent delays, and ensure long-term success. Read on to learn five key questions every enterprise should answer before embarking on their SAP S/4HANA journey.

1. How are we minimizing risk and disruption? 

The average cost for a company to migrate to SAP S/4HANA varies widely depending on organizational size, complexity, and specific requirements. Generally, SAP S/4HANA migration costs range from $250,000 for smaller implementations to hundreds of millions of dollars for large enterprises.

The high costs raise the stakes around managing risks related to the budget, but this is only a part of the story. Since ERP systems play a central role in supporting day-to-day business operations, ensuring minimal disruption during the transition is a key priority for organizations.

In fact, despite the looming 2027 support deadline for SAP ECC, nearly half of SAP ECC customers are still considering staying with legacy ERP beyond that date, citing concerns about complexity, cost, and risk. SAP itself emphasizes that a carefully planned migration approach is essential to ensure business continuity and minimize operational risk.

Integrations with other systems play a central role in managing the migration risks. Unfortunately, in the broad realm that is SAP S/4HANA integration, there is one area that tends to get overlooked. Too many organizations treat SAP EDI integration as an afterthought and set themselves up for encountering delays, unplanned costs, and other issues during implementation. 

2. Do we know all our integration requirements?

SAP S/4HANA integration projects demand precise understanding of how data flows between systems. With internal systems this is usually a lesser issue since they are managed by the organization itself. However, external partner systems tend to cause a lot more headaches since partners can have very diverse requirements.

Making matters worse, existing SAP EDI integrations that hold the key to figuring out these requirements have usually been built over years—or even decades—project by project and without comprehensive documentation.

Because of this, mapping out the specific requirements can be challenging, and many companies resort to a “brute force” approach with their systems integrator manually reviewing individual EDI documents. Alternatively, vendors specializing in EDI can help capture the partner data requirements faster and more efficiently.   

Without clear visibility into current-state integrations and the specific trading partner data requirements, organizations risk missing key details that will create complications in the later stages of the migration. A comprehensive review early on ensures accurate data modeling and avoids costly rework.  

3. How much can we trust the data coming from external partners? 

A survey by IDG found that 44% of the data feeding corporate ERP systems comes from external sources. Business operations, therefore, are highly reliant on the quality of the data exchanged with trading partners. According to another IDG survey, only about two thirds of respondents considered external partner data to be accurate.

With such a high expectation of errors within partner data, it’s important to address this at a very early stage. What’s best is to incorporate SAP HANA data integration and B2B data quality management considerations into your business process design when defining your SAP S/4 migration project.

4. Do we have the tools and skills we need for SAP EDI integration? 

Thanks to the diversity of trading partner data requirements, managing SAP EDI integration can be notoriously complex. The challenges compound when the business has an extensive network of trading partners to manage or the partners span multiple geographies.
 
Problems are often related to using legacy integration tools. In the case of B2B data exchange, generic integration platforms are not designed for managing the complexities and diversity of connecting with external systems and managing partner engagement. However, even with modern, fit-for-purpose tooling, lack of specialist EDI expertise can lead to poor design choices and slow integration support and change management.

To tackle these issues, organizations need a modern integration solution that supports both traditional B2B/EDI integration and API integration use cases and ideally streamlines SAP HANA cloud integration with system-specific tooling. Beyond technology, having skilled integration specialists involved is equally important to execute a successful migration strategy.

5. Are we truly ready for SAP S/4HANA integration? 

Today, most organizations begin their SAP S/4HANA integration journey without clearly defined B2B or SAP HANA data integration requirements. Identifying the requirements in the beginning of the S/4HANA migration project minimizes the risk of encountering surprises and delays during implementation and can even accelerate system blueprinting by speeding up data model definition.
Modern integration technology, in turn, allows for optimal solution design by leveraging the most suitable integration patterns for each use case from real-time API integrations to efficient message-based transaction flows.

Having both a clear understanding of the current integration needs and the solution design options enabled by modern integration technology is an essential component of readiness to embark on the journey to S/4HANA.

Get Started: Ensure a Seamless Transition to SAP S/4HANA

Migrating to SAP S/4HANA is a complex undertaking, but with the right integration strategy, it’s also a powerful opportunity to modernize and future-proof your operations. Asking the right questions before you begin will allow you to identify integration challenges early. This means you'll reduce risk, streamline trading partner connectivity, and accelerate time to value.
OpenText provides the modern integration tools, expertise, and data readiness insights needed to make SAP EDI integration seamless and scalable.  

Explore how OpenText can simplify your S/4HANA migration here.

The post 5 key questions to ask before your SAP S/4HANA migration  appeared first on OpenText Blogs.