In an interview with ERP Today, Thomas Failer, CEO of Data Migration International, argues that the time to migrate to SAP S/4HANA is not approaching—it is here.

The Tangled Web of Legacy Data

According to Failer, the pervasive problem of legacy data lies at the heart of the urgency. He explains: “Decades of operational history often reside within SAP ECC systems, much of it outdated, redundant, and unstructured. This digital baggage acts as a significant anchor, inflating costs, creating compliance nightmares, and severely hindering digital transformation initiatives.”

Moreover, maintaining these sprawling legacy environments consumes a lion’s share of IT budgets – often as high as 60-80% – leaving scant resources for strategic innovation. The sheer volume of this data slows down system performance, complicates upgrades, and makes extracting meaningful insights a herculean task.

Failer added, “Legacy data is often riddled with inconsistencies, duplicates, and quality issues. This “dirty data” undermines the accuracy of analytics, cripples the potential of AI and automation, and leads to flawed decision-making.”

Due to these factors, compliance becomes a precarious tightrope walk as outdated systems struggle to meet evolving regulatory demands like the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), exposing businesses to hefty fines and reputational damage. The lack of proper data governance and retention management within legacy ECC systems makes audits and legal discovery processes costly and time-consuming.

Clean Core and the Imperative of Clean Data

Failer points to a compelling alternative to solve this problem: SAP’s strategic direction, embodied in the “Clean Core” and “Composable Enterprise” vision. “This future-ready architecture emphasizes a modular, flexible, and agile approach to enterprise resource planning,” he notes. “The Clean Core advocates for a standardized, lean digital foundation in SAP S/4HANA, minimizing customizations and ensuring seamless upgrades, while the Composable Enterprise envisions a landscape of interoperable business capabilities that can be assembled and reassembled as needed.”

“Dirty data” undermines the accuracy of analytics.

However, the realization of this transformative vision is intrinsically linked to the quality of the underlying data. “You simply cannot build a Clean Core on a foundation of dirty, outdated data,” Failer says. “Migrating massive volumes of legacy baggage into SAP S/4HANA defeats the purpose, bloating the system and perpetuating existing inefficiencies.”

Similarly, a Composable Enterprise relies on consistent, high-quality data flowing seamlessly between its modular components. Thus, fragmented or unreliable data undermines the agility and flexibility this architecture promises.

The JiVS Solution

Data Migration International (DMI) offers a powerful solution to navigate this complex transition: the JiVS Information Management Platform (IMP). Failer states, “JiVS provides a strategic and intelligent approach to managing legacy data, enabling businesses to break free from the constraints of their SAP ECC systems and embrace SAP S/4HANA with confidence.”

The core principle of JiVS is the separation of historical data from active applications. Instead of a “lift and shift” approach that blindly migrates everything, JiVS extracts all legacy data (SAP and non-SAP) at the application layer, preserving its full business context. This data is then securely archived in a legally compliant and audit-proof manner. This means businesses retain 100% access to their historical data for audits, compliance, and operational needs, even after the legacy ECC system is decommissioned.

“With the historical data safely managed, JiVS enables businesses to selectively migrate only the necessary, high-quality data to SAP S/4HANA,” Failer says. “This targeted approach drastically reduces data volume – often by up to 90% – streamlining the migration process, accelerating timelines, and significantly lowering costs.”

DMI estimates that JiVS can reduce overall IT operating costs by up to 80% by enabling the retirement of expensive legacy systems and optimizing data storage. Furthermore, JiVS incorporates automated data quality analysis and cleansing, ensuring that only clean, relevant, and enriched data makes its way into the new SAP S/4HANA environment. “This supports SAP’s Clean Core principles and lays a solid foundation for leveraging advanced analytics, AI, and automation,” adds Failer.

Overall, the solution’s benefits include:

• Exceptional data transfer speed up to 30TB/day
• Zero business disruption and no downtime
• No need for costly or lengthy pre-projects
• More than 3,000 successful projects worldwide and a robust global partner network
• Over 3,000 supported business objects

The Fast Track to Freedom

The transformative power of DMI’s approach is evident in the success stories of companies that have embraced JiVS. Failer shares the compelling example of a leading automotive company that successfully retired its SAP ECC system in only four months.

JiVS provides a strategic and intelligent approach to managing legacy data.

He notes that faced with the looming 2030 deadline and the burden of a complex legacy landscape, the company partnered with DMI to implement JiVS. “By separating and archiving their vast historical data, we could significantly reduce the scope and complexity of their SAP S/4HANA migration, allowing them to transition to the modern platform at an unprecedented speed, freeing them from the constraints of their legacy system, reducing IT costs, and gaining the agility needed to thrive in a rapidly evolving industry,” Failer says.

The Time for Action is Now

SAP’s vision for a Clean Core and Composable Enterprise offers a path to agility and innovation, but it demands a commitment to clean, high-quality data, which can be provided by DMI’s JiVS solution, which addresses the challenges of legacy data, streamlines SAP S/4HANA adoption, and unlocks significant cost savings. “The ticking clock is a clear call to action: businesses still on SAP ECC must act now to secure their future and embrace the transformative power of SAP S/4HANA,” Failer concludes.

What This Means for ERP Insiders

Historization prevents vendor lock-in and supports business agility. Recognize the strategic advantage of historization – separating and archiving historical data in a vendor-neutral format. By utilizing solutions like JiVS IMP, users gain independence from the core operational system for accessing and managing historical records. This prevents vendor lock-in, as your valuable historical data remains accessible even if you choose to migrate to a different ERP system in the future. Furthermore, having a readily accessible, well-governed historical data archive enhances business agility by providing a comprehensive and compliant data foundation for analytics, reporting, and responding to evolving business needs without impacting the performance or complexity of your active ERP system.

Accelerate SAP S/4HANA migration while ensuring compliance. To expedite your move to SAP S/4HANA and maintain robust compliance, prioritize the separation and secure archiving of historical data. Retaining historical data in an audit-proof environment separate from your active SAP S/4HANA system allows you to meet regulatory requirements without bogging down your new environment with legacy baggage.

Clean Core is impossible without clean data. Avoid the temptation of a “lift and shift” approach. Instead, invest in data cleansing and harmonization before migration. By ensuring that only clean, standardized data populates your SAP S/4HANA system, you can minimize customizations, streamline processes, and fully leverage the benefits of the Clean Core architecture, including easier upgrades and faster adoption of new innovations.

The post Time’s Running Out on SAP ECC: Act Now to Avoid Soaring Risks and Costs appeared first on ERP Today.

Transforming Enterprise AI with Innovation and Business-Centric Solutions

IBM has long been a pioneer in AI, from Watson’s early innovations to today’s enterprise AI solutions. IBM’s AI strategy rests on two pillars: IBM Software, which provides security-focused and transparent enterprise AI, cloud, security, and automation solutions, and IBM Consulting, which drives large-scale business transformation, technology implementation, and managed services, leveraging IBM and ecosystem partner technologies. In fact, IBM is one of few major technology companies with a global consulting business at scale, which is a key differentiator when it comes to helping clients deploy AI. IBM’s AI book of business has grown to over $5 billion across software and consulting, with 80% of bookings coming from IBM Consulting.

Oracle’s AI strategy is built on over 40 years of enterprise technology and applications expertise, seamlessly integrating AI into both data platforms and business processes —Jody Clayton Group Vice President, Advanced Technology- SaaS Technology, Analytics, AI & Emerging Technology at Oracle

Oracle also has a long history with AI and innovative technologies, embedding AI directly into Oracle Fusion Cloud Applications Suite, offering a robust, scalable AI solution with tight control over data security and governance. With over 100 generative AI-driven capabilities already live and 50 ready-made AI agents across the suite, Oracle enables business users to change the way work gets done with AI through enhanced decision-making, workflow automation, and improved productivity. As Jody Clayton, group vice president, Advanced Technology – SaaS Technology, Analytics, AI & Emerging Technology at Oracle, emphasizes, “Oracle’s AI strategy is built on over 40 years of enterprise technology and applications expertise, seamlessly integrating AI into both data platforms and business processes. Our cloud infrastructure is engineered for performance and cost efficiency, making it the preferred choice for running AI workloads. By having a complete infrastructure, data, and application cloud platform, Oracle is able to drive AI services and embedded intelligence across the enterprise, helping improve the efficiency of all employees.”

Oracle’s AI strategy is anchored in three critical components. First is high-quality, context-rich data, which is essential for AI success, and Oracle’s data platforms provide a solid foundation for AI-driven automation. Second is a cost-efficient AI infrastructure, as Oracle’s cloud infrastructure is optimized for AI workloads, which can help reduce training and deployment costs while helping to enhance processing power. And third is deep connectivity across critical business processes, as Oracle integrates AI across key business functions, including finance, HR, supply chain, and customer experience. Rod Johnson, executive vice president, cloud applications, Oracle, says, “A prime example of Oracle’s AI-driven transformation is its own financial operations. With Oracle Fusion Cloud Enterprise Resource Planning (ERP) and Oracle Fusion Cloud Enterprise Performance Management (EPM), Oracle has achieved a record-fast financial close cycle, consistently reporting earnings in under ten days. In addition, Oracle has saved approximately 80,000 hours annually through AI-enhanced forecasting and budgeting. For businesses, these capabilities translate to tangible improvements, such as increased accuracy in demand planning, enhanced decision-making, and greater operational efficiency.”1

“The synergy between IBM and Oracle extends beyond automation into AI model integration. Oracle customers can leverage IBM’s watsonx AI models within Oracle Cloud applications, combining IBM’s granite models with Oracle’s AI stack and cohere models.” —Shobhit Varshney, VP & Sr. Partner, Americas AI Leader at IBM

Oracle’s AI solutions offer customers the opportunity for significant productivity gains and operational efficiencies. Whether optimizing finance, HR, or supply chain operations, AI in Oracle Fusion Applications is intentionally embedded into business processes to help deliver real-world impact, optimize workflows, and maximize revenue potential.

Co-owning Enterprise Transformations

Collaboration is at the heart of IBM Consulting’s strategy, with a strong focus on collaborating with industry leaders like Oracle to deliver AI-powered solutions that can help drive measurable business outcomes. With an open ecosystem approach, IBM Consulting meets clients where they are, leveraging AI models from IBM, Oracle, and other business partners to enhance business processes and bring together the strengths of both companies to help deliver optimized enterprise solutions.

With a legacy of AI leadership, IBM embeds generative AI capabilities into its implementation methodologies and platforms to help customers with Oracle deployments. A key enabler of this strategy is IBM Consulting Advantage, an AI-powered delivery platform that equips consultants with generative AI agents, assistants, and applications to augment their work supporting clients. IBM Consulting Advantage leverages IBM and business partner technologies and provides predefined frameworks, industry templates, business process flows, and intelligent workflows that streamline implementation and reduce manual effort through automation. Chacko Thomas, Americas Oracle Leader, IBM, highlights, “Oracle customers get out-of-the-box AI-powered SaaS, but as implementers, that is just our starting point. At IBM, we aim to enhance the entire implementation lifecycle by helping clients boost their productivity from design to testing. With IBM Consulting Advantage agents, assistants, and applications, our consultants are leveraging AI-powered tools to streamline processes and reduce manual effort, like generating test scripts. It is about delivering the best of Oracle Fusion Applications for clients while optimizing implementation with IBM’s productivity tools.”

IBM Consulting’s deep industry expertise helps organizations align AI adoption with their sector-specific challenges, helping clients navigate Oracle’s existing AI capabilities and identify where custom AI solutions are required. IBM’s acquisitions of Accelalpha and Applications Software Technology LLC have expanded its Oracle consulting expertise across industries such as supply chain and logistics, finance, and the public sector to support clients in their digital transformations with Oracle Fusion Applications. By enhancing Oracle Fusion Applications with industry-specific expertise, frameworks, and additional AI solutions, IBM Consulting enables Oracle customers to maximize efficiency and innovation while reducing time-to-value.

Additionally, with multi-cloud flexibility—including Red Hat OpenShift, certified on Oracle Cloud—IBM helps organizations deploy AI-driven automation across hybrid and multi-cloud environments, enabling scalability and adaptability. As Shobhit Varshney, VP & Sr. Partner, Americas AI Leader, IBM, emphasizes, “The synergy between IBM and Oracle extends beyond automation into AI model integration. Oracle customers can leverage IBM watsonx AI models within Oracle Fusion Applications, combining IBM Granite models with Oracle’s AI stack. IBM watsonx Orchestrate further enhances this ecosystem, enabling digital labor coordination across platforms so that organizations can tailor AI-powered automation to their unique business needs.”

Starting the Transformation Journey

For many organizations, the biggest challenge with AI-driven automation is knowing where to start. Oracle makes this easier with hundreds of built-in AI capabilities in Oracle Fusion Applications, many of which can be activated with minimal effort. IBM further simplifies the process by helping customers optimize these AI-driven capabilities, accelerating adoption and immediate value realization.

“Oracle customers get out-of-the-box AI-powered SaaS, but as implementers, that is just our starting point. At IBM, we enhance the entire implementation lifecycle—boosting productivity from design to testing.” —Chacko Thomas, IBM’s Americas Oracle Leader

Oracle has long been at the forefront of business process automation, with over 100 generative AI and machine learning capabilities embedded in its applications. Now, the company is advancing further with the release of new AI agents and its AI Agent Studio for Oracle Fusion Applications, which combines large language models (LLMs) with other technologies to accomplish complex tasks that previously could only be done by humans. This shift represents a major transformation in automation, moving beyond rigid, rule-based workflows to intelligent decision-making. By embedding AI-driven workflows within its enterprise applications, Oracle enables organizations to streamline operations while maintaining tight control over data governance and security. IBM provides consulting services and solutions to help clients implement and derive greater value from Oracle Fusion Applications, leveraging IBM Consulting Advantage to accelerate AI transformation.

Conclusion

As AI adoption accelerates, enterprises seek solutions that integrate intelligence while providing security, scalability, and efficiency. IBM and Oracle offer distinct yet complementary AI capabilities to help drive business transformation. IBM specializes in AI consulting and secure, enterprise-specific AI models designed for transparency and control. Meanwhile, Oracle embeds AI directly into all layers of the technology stack, helping enhance automation, decision-making, and operational performance.
Together, they create a robust AI-enabled enterprise ecosystem, combining Oracle’s built-in AI with IBM Consulting services to drive business transformation, technology implementation, and managed services . This synergy enables organizations to harness AI confidently, helping to drive efficiency, agility, and competitiveness in an increasingly intelligent business landscape.

References
1 https://www.oracle.com/playbook/financial-excellence/

The post Bridging AI Strategies: IBM and Oracle’s unified approach to Enterprise AI appeared first on ERP Today.

But 2025 marked a significant inflection point. With the backing of leading global private equity investor, Advent, SYSPRO embarked on an accelerated journey of growth, innovation, and transformation, poised to redefine its role as a critical partner in its customers’ digital evolution.

The investment by Advent isn’t just a financial transaction; it represents a paradigm shift for a company proud of its heritage. As Jaco Maritz, CEO, SYSPRO, explains, the move from a long-standing founder-led structure introduces new dynamics and opportunities. “This is our first transaction, to the extent that we brought in Advent,” Maritz notes. “So obviously, there’s quite a shift in the business, moving from the way that we did things, to a new paradigm.”

The Advent Catalyst: More Than Capital

Advent’s interest in SYSPRO stemmed from recognizing the company’s core strengths which, Martiz notes, include, “mission-critical embedded software within our customers,” its deep specialization in the resilient manufacturing sector, and its established global footprint.

The main theme around value extraction, is [the] move towards a cloud business – Jaco Maritz, CEO, SYSPRO

However, he candidly shares another key element of Advent’s calculus: “The other thing they really liked about us is everything we have not done yet.” This perceived untapped potential forms the foundation of Advent’s growth thesis. “One of the reasons why we were quite interested in [partnering with] them is the fact that they are growth orientated, and are really looking at the landscape, our position in it, and how we grow,” Maritz emphasizes.

Prioritizing Growth

With Advent’s support, SYSPRO’s strategic priorities for the near-to-mid-term center around three pillars:

Growth and Efficiency: This involves strengthening market position, particularly in the UK (bolstered by the recent acquisition of a key business partner there) and North America, while maintaining its stronghold in Africa. Efficiency gains are sought in go-to-market strategies, offering development, and customer support processes.

Extending the Offering: Led by Chief Solutions and Technology Officer Chris Lloyd, based in Manchester, England, this involves enhancing SYSPRO’s solutions through technology, innovation, and expertise. Crucially, the Advent partnership introduces new mechanisms like M&A, allowing SYSPRO to “come to the market a lot quicker with some of the changes to technology and functionality changes,” a departure from the previous “do it ourselves” approach, as Maritz describes it.

Extracting Value via the Cloud: The “main theme around value extraction,” according to Maritz, “is [the] move towards a cloud business.” This encompasses far more than just technology deployment. “We’re not only talking about a technology,” he clarifies. “We’re talking about the way that we manage, the way that we report, the way that we measure the commercial models the way that we do value-based pricing, as well as then, obviously, our technology and our solutions.”

While manufacturing has sometimes lagged in cloud adoption, Lloyd, who oversees SYSPRO’s product management, technology, and development, confirms a shift. “From our clients, we’ve seen a strong uptake in the cloud offering more recently,” he states.

Maritz concurs, observing a distinct change in customer conversations over the past year: “There’s a clear shift from our customers and new sales engagements that’s not just asking about cloud, but are interested in a cloud solution.” SYSPRO’s distinct positioning of SYSPRO ERP and SYSPRO Cloud ERP acknowledges this reality, meeting customers wherever they are on their cloud journey.

AI: The Manufacturer’s Co-Pilot

No technology discussion is complete without addressing Artificial Intelligence (AI). For SYSPRO, particularly given its manufacturing focus, AI presents significant opportunities beyond the hype. Lloyd envisions AI evolving into a “digital co-pilot that helps monitor the business… monitors key workflows, flags anomalies, and automates complex processes.”

However, he stresses the importance of maintaining human oversight, especially in critical manufacturing environments. “The ultimate vision here is continuous automation while still keeping the human in the loop,” Lloyd explains. “There’s going to be a big shift where people are happy for AI to flag certain things [but] there’s this trust barrier of letting AI take action. And that’s where this concept of keeping the human in the loop will be critical.”

The potential use cases for AI in manufacturing and distribution are compelling: intelligent production scheduling, optimized material requirements planning, predictive maintenance, enhanced quality control using cognitive AI, and sophisticated cost optimization.

“These are key value drivers in managing a complex manufacturing world,” Lloyd asserts. He believes that while AI demand might currently seem market-driven, its practical value in manufacturing will quickly equalize expectations. “For manufacturing, AI is going to be equalized quite quickly in terms of how much it can bring to that complex environment,” Lloyd says.

The ultimate vision here is continuous automation while keeping the human in the loop. – Chris Lloyd, CPO, SYSPRO

SYSPRO is already integrating AI capabilities, leveraging machine learning and document recognition for tasks like automating accounts payable processing. Current development focuses on streamlining customer purchase order-to-sales order workflows, automating stock replenishment triggers, and intelligent requisition approvals – tangible operational benefits delivered through AI.

Deep Roots, Sharpened Focus

SYSPRO’s enduring strength lies in its unwavering focus on manufacturing and distribution. While adjacent industry opportunities exist, the immediate strategy involves deepening penetration within current verticals rather than broad horizontal expansion. “A big opportunity for us [is] actually to go even deeper into some of those industries,” says Maritz, citing Food & Beverage as an example where SYSPRO can enhance its offering for specific sub-segments.

This industry specificity is a powerful differentiator. Maritz highlights the importance of speaking the customer’s language: “Customer executives, not only need to be confident that we are experts from a technology perspective, but they also want to know that we can solve their business problem. Having that conversation on the business level is critical, and that’s when a specialization matters.”

Maritz believes that for customers, choosing SYSPRO over competition often comes down to “the ability to solve [the problem] and actually provide the most cost-effective solution.” This isn’t merely about price but about value delivered efficiently. Relationships built on trust and demonstrated expertise are also key.

Lloyd adds crucial product-centric reasons: The sort of length and depth of the features within the manufacturing distribution space, SYSPRO’s ability to scale with customers as they expand, its strength in customizing and configuring SYSPRO to the exact customer needs, and the ability to integrate deeply into embedded processes.

SYSPRO seeks customers with clear technology and transformation plan, ready to leverage the platform’s depth, even if they start smaller and scale up. Maritz contrasts these ideal engagements with scenarios where the customer wants the latest but basic digitization like scheduling is still needed: “So with them, we say ‘Okay, let’s get your scheduling onto the system, then we can talk about AI.”

The Power of Partnership

SYSPRO’s growth and solution strategy heavily relies on a robust partner ecosystem, encompassing both Independent Software Vendors (ISVs) and Value-Added Resellers (VARs). “ISVs and partnerships are absolutely core to our strategy,” states Maritz.

These partnerships are cultivated both proactively, based on market trends, and opportunistically, driven by specific customer needs. The goal is transparency and collaboration. “We do foster and drive partner collaboration for that transparent relationship between us, the ISV and the customer,” Lloyd explains.

Maritz links this back to specialization. Just as SYSPRO focuses on its core strengths, partners like CRM specialists bring their expertise to the table. “We are specialists, and then, say, the customer requires a CRM system. It gives us opportunity to bring [the ISV or VAR] to the table as the CRM specialist,” he notes. The VAR channel also remains fundamental, as SYSPRO operates as a channel-driven company. These partners provide essential implementation, support, and localized industry expertise that SYSPRO couldn’t replicate centrally. “Within our partner base also, we build those skills and specialization within specific industries,” Maritz adds.

Forging Ahead

Internally, the shift from a founder-led entity to a private equity-backed organization inevitably impacts company culture. Maritz acknowledges the significance of this transition, emphasizing the need to retain skills and talent while embracing new ways of working, facilitated by a supportive Advent model.

The investment firm has brough expertise and hands-on mentorship model to SYSPRO, leveraging a network of specialists who act as mentors and advisors to SYSPRO’s senior leadership team (SLT). “Each of the SLT members has got somebody that almost shadows them as a mentor and an advisor,” Maritz reveals. “So, we suddenly went from trying to do this on our own to here’s somebody that’s actually done [it before].” This model has provided practical guidance, instilled confidence and accelerating strategic initiatives.

SYSPRO now stands at a compelling juncture. Armed with decades of industry expertise, fortified by strategic investment, and guided by experienced leadership, the company is doubling down on its manufacturing and distribution focus while embracing cloud, AI, and an ecosystem approach. As it forges ahead on these initiatives, for manufacturers and distributors navigating their own complex digital transformations, “SYSPRO aims to be more than just an ERP provider; it aims to be the indispensable platform and partner for future success,” Maritz concludes.

What This Means for ERP Insiders

Cloud is a core strategic priority, not just an option. SYSPRO, fueled by the investment from Advent views the shift to a cloud business as central to its future strategy and value extraction. This goes beyond just offering cloud deployment and involves changes in management, reporting, commercial models, and the overall technology stack. The company’s future development and focus are heavily weighted towards enhancing and expanding its cloud capabilities, responding to a clear increase in customer demand for cloud solutions observed in the last 12 months.

Expect accelerated innovation and offering expansion from SYSPRO. The partnership with Advent provides SYSPRO with new resources and mechanisms, including the potential for Mergers & Acquisitions (M&A). Given these factors, the industry can anticipate a potentially faster pace of innovation, and the introduction of new functionalities compared to SYSPRO’s historical “do it ourselves” approach. This acceleration applies to extending the overall offering, likely including more advanced cloud features and integrations.

SYSPRO’s plans include integrating AI and deepening platform capabilities. The company is actively incorporating AI into its solutions, envisioning it as a digital co-pilot for manufacturing processes while keeping the human touch. This, combined with a strong focus on building out its ISV partner ecosystem, signals a move towards becoming a more comprehensive platform player. Future SYSPRO versions will likely offer more integrated intelligence and broader capabilities through both native development and tighter partner integrations, often facilitated via its cloud platform.

The post SYSPRO’s Next Chapter: Fueled by Investment, Focused on Manufacturing’s Future appeared first on ERP Today.

With decades of experience in the local market, this company is part of a global healthcare network, which operates in multiple countries, including the Czech Republic, France, Germany, Norway, the Netherlands, Spain, Turkey, and the United Kingdom.

The company’s IT Director shared insights into the company’s transformation plans, emphasizing the critical role of SAP S/4HANA in streamlining finance, logistics, and ERP functions.

“Today, we process approximately 130,000 invoices daily and serve 22,000 pharmacies out of the 30,000 in this region,” he explained. “Our legacy ERP system, has functioned primarily as an accounting tool rather than a fully integrated enterprise system. The move to SAP S/4HANA will enable us to digitize manual processes, enhance financial planning, and integrate AI-driven analytics.”

The transformation roadmap at the company is structured into three key phases:
1. ERP Assessment & Business Case Development (2025)
• Conducting a feasibility study to define current system gaps.
• Engaging local SAP partners for process mapping.
• Securing executive approval for the transition.

2. Implementation Kickoff & Rollout (2026)
• Launching a global SAP S/4HANA implementation in collaboration with the company’s international teams.
• Standardizing procurement, financial forecasting, and supply chain management processes.
• Migrating warehouse management systems (WMS) and financial operations into a unified SAP framework.

3. Full System Deployment & Optimization (2027-2028)
• Expanding AI-driven insights for demand forecasting and inventory management.
• Integrating extended warehouse management (EWM) to optimize stock replenishment.
• Enhancing real-time financial reporting and risk management.

The IT Director highlighted the organization’s focus on leveraging AI within the SAP ecosystem.

“We manage millions of invoices per month, yet financial visibility remains a challenge. AI-powered tools in SAP S/4HANA, such as predictive analytics and automated risk assessments, will bring much-needed transparency,” he noted. “Our priority is to apply machine learning models for stock replenishment and pricing strategies, ensuring cost efficiency and adaptability in market fluctuations.”

The move to SAP S/4HANA also positions this region of the company as a potential SAP center of expertise for the broader network of regional teams.

“This region has a deep talent pool of SAP professionals, and our goal is to leverage this strength to become an SAP knowledge hub within our organization,” the IT Director stated. “We have already engaged with SAP’s regional General Manager to explore collaboration opportunities.”

This initial regional team at this company is also implementing Workday for HR. The IT Director noted that the existing HR system is essentially a custom developed solution based on a local HR application, but is not an enterprise-grade solution. The company will not leverage Workday’s full feature set to begin with, and will continue for a time to manage some HR processes like payroll outside of Workday. And deep integration with SAP S/4HANA is not currently planned.

Reflecting on the transformation process, the IT Director emphasized the importance of:
• Prioritizing Employee Training: “Training should not be an afterthought—it must be a priority from day one to ensure smooth adoption.”
• Long-Term Vision Over Short-Term ROI: “Companies should avoid focusing only on immediate financial returns and instead take a long-term strategic view when investing in digital transformation.”
• Managing Organizational Change: “Shifting company culture is just as important as implementing new technology. Employees need to understand the ‘why’ behind the transformation.”

With a two-year implementation timeline, the company is focused on laying the groundwork for a seamless SAP S/4HANA deployment. The company anticipates that Spain’s SAP rollout—currently underway—will provide valuable insights into best practices for a multi-market single-instance strategy.

As the transformation progresses, the company aims to redefine its IT landscape, embracing cutting-edge AI, automation, and cloud-first strategies to stay ahead in the evolving pharmaceutical distribution industry.

What This Means for ERP Insiders

Industry fit remains a key factor for ERP. It’s worth noting that a significant majority—95%—of the world’s life sciences companies utilize SAP solutions, which include SAP S/4HANA. This high adoption rate underscores SAP’s strong presence in the pharmaceutical industry, encompassing various segments such as research and development, manufacturing, and distribution. SAP S/4HANA offers specialized functionalities tailored to the pharmaceutical sector, including features like SAP Advanced Track and Trace for Pharmaceuticals. This application assists companies in complying with international and regional drug serialization mandates, effectively combating counterfeit medications and enhancing supply chain transparency. Such capabilities are particularly beneficial for pharmaceutical distributors like Alliance Healthcare aiming to ensure product authenticity and regulatory compliance.

Define a clear cloud strategy: public vs. private. Selecting the appropriate cloud deployment model is crucial for migrations like this pharmaceutical company is undergoing. SAP S/4HANA offers two primary options: Public Cloud (GROW with SAP): Ideal for small to medium-sized businesses seeking rapid deployment with standardized processes. This model
leverages preconfigured best practices, allowing for swift implementation, often within weeks. However, customization options are limited, making it suitable for organizations that can operate within SAP’s standard configurations. Private Cloud (RISE with SAP): Suited for larger enterprises with complex requirements necessitating extensive customization.
This model provides greater control over the environment, supporting tailored processes and integrations. The tradeoff includes longer implementation timelines and potentially higher costs due to the bespoke nature of the deployment.

Single ERP instance across multiple countries is achievable. Deploying a single-instance ERP across multiple countries like this global company is endeavoring to do is a complex but strategic approach that can deliver standardized processes, improved compliance, and enhanced visibility across global operations. A “Global Template with Localization” approach ensures consistency while allowing flexibility for regional needs. This starts with a Global Core Model, consisting of standardized business processes for finance, supply chain, procurement, HR, and reporting; centralized master data management (MDM) and governance; and consistent security and compliance policies. Then there are localized configurations, including adjustments for country-specific tax regulations, legal compliance, reporting standards (GAAP, IFRS), and HR policies; language support and multicurrency capabilities; and integration with local banking, tax, and payroll systems. A multi-national single instance strategy must also contemplate regulatory compliance and data residency. Each country has unique regulatory compliance, security, and data residency requirements.
Companies must ensure ERP is configured for VAT/GST, electronic invoicing, statutory reporting (e.g., SAF-T, Making Tax Digital in the UK), and compliance with Sarbanes-Oxley
(SOX), IFRS, and local GAAP standards. And CIOs must ensure ERP complies with data protection laws like GDPR (Europe), CCPA (California), PDPA (Singapore), and China’s PIPL, and choose regional cloud hosting where data sovereignty laws apply.

The post Enterprise Views: Global Pharmaceutical Distributor Advances Digital Transformation with SAP S/4HANA appeared first on ERP Today.

With new upgrades and implementations arriving more frequently than before, the enterprise software landscape is constantly in flux. This means businesses face new challenges in ensuring the quality and stability of their increasingly complex application ecosystems.

In an exclusive interview, Colin Armitage, CEO of Original Software, provided invaluable insights into the critical world of end-to-end testing, helping companies understand how they can mitigate risk and meet their quality goals. With a history stretching back to 1997, Original Software has been a consistent presence in a space often characterized by fleeting trends, offering a unique perspective shaped by decades of experience.

Making Testing Straightforward and Accessible

One of the key differentiators of Original Software is its roots in low-code and no code capabilities. Armitage explained that the decision to avoid a code-based testing solution was fundamental from the company’s inception, as it was fundamental to problem-solving.

“If you are trying to test a code base as it is, why on earth would you want to build another code base to test the first one? The testing code would be just as likely to have bugs in it as the code being tested. You would need specialized skills to build it, and you haven’t made the problem easier. You’ve made it harder,” said Armitage.

Beyond simply eliminating code, this approach tackles other inherent challenges in traditional test automation, such as managing timing dependencies. The common practice of embedding fixed-duration wait loops in test scripts highlights their inflexibility and potential for failure if application response times vary. Original Software’s solution intelligently handles timing, recognizing when the application is ready for the next action.

Adapting to the new Enterprise Software Landscape

Original Software’s core business revolves around helping organizations achieve their quality goals while man aging and reducing risk. This is particularly crucial during major upgrades and the implementation of new applications, ensuring a “risk informed state of play” when companies go live.

This is especially important in the modern technology landscape. ERP vendors are increasing the rate of updates, and companies cannot test the software the same way they have done in the past.

“Recently, a lot of ERP vendors have moved to monthly updates. What you could do to test something if it was only once a year was fine. If you have to test every month, you can’t go and rip 20 or 30 of the key business users out of the business every month for two weeks. It is just physically impossible. So, it tends to be at that more operational level there where they’ve reached a point where they just can’t continue testing the way they have been doing it,” said Armitage.

Armitage added that the ability to test business processes seamlessly across multiple applications becomes not just advantageous but “essential.” Original Software’s platform rises to this challenge by supporting a wide array of applications, from modern browser-based ones to desktop applications and even legacy IBM emulators, recognizing their continued importance in some business processes.

This is particularly important for companies that are now managing multiple ERP systems due to acquisitions. The ability to support these diverse environments is crucial for their companies navigating consolidation efforts.

“We may run into somebody who says, ‘we’re an SAP shop,’ but they’ll be using Salesforce as a CRM rather than SAP or they will be using something else for their e-commerce. For an end-to-end business process, you’ll typically be visiting multiple applications. So, it’s not a nice idea to support multiple applications. It’s essential,” said Armitage. “And it is that end-to-end testing, the ability to test the process across applications, that is essential. You don’t want to see application boundaries. You just want to be able to test the business process. It’s very much a strength of ours, going across applications.”

Understanding Challenges and Evolving to Meet Them

With nearly 30 years of experience in the testing space, Original Software understands where technologies like automation can be helpful and where business process overhauls are more likely to yield the desired results.

When looking to improve their testing workflows Armitage says companies should start off by taking a step back and evaluating their business pain points. For instance, companies often request test automation as their first order of business. Yet taking the time to review their current practices may reveal that the real issue isn’t a lack of automation but the disruptive impact of user acceptance testing (UAT), where key users are taken away from their regular duties.

“Companies can argue that maybe they could automate their testing, but that’s difficult if there’s new features. There’s always going to be an element of manual testing done on that. But more importantly, that familiarization with either changes or new features has to be done by the users, and that, again, has an impact on the business,” said Armitage.

While automating UAT might seem like a solution, it’s challenging with new features, and the crucial familiarization aspect for users will always require manual input, impacting business operations. Therefore, enhancing the efficiency of this process can be a significant win for companies.

Armitage cautioned against the expectation of automating everything, as it “doesn’t make any sense” for processes which run infrequently. Instead, he advocated prioritizing the automation of core processes that would cripple the business if they failed. He used the analogy of building a “survival pack” of automated tests for critical processes like order-to-cash or procure-to-pay, al lowing companies to quickly verify their core functionality after a new release.

Recognizing that some companies, especially in test automation, might need extra support, Original Software also offers a “fast start service” involving remote embedding of its personnel to help build initial test assets quickly. However, the bedrock of the company’s offering remains its comprehensive software platform.

Incorporating AI into Testing

Original Software has long been ahead of the curve on AI, incorporating it in a practical sense to solve fundamental testing challenges. Armitage illustrated this with the example of identifying UI elements, explaining how their AI can understand what a user would intuitively call an element (e.g., the “User” text box) rather than relying on technical HTML identifiers that are meaning less to a business user.

This focus on user-friendliness and readability is crucial for making test scripts accessible to a wider audience. While promising further developments in AI for its offerings, Armitage emphasized a realistic approach, learning from the initial over-promising often associated with new technologies. This allows Original Software clients like Costco to have an accurate expectation that it is refining what it already does well, rather than doing anything radically different.

“Costco uses part of our platform. It takes them three days to run the extraction because their live database is so big. They were delighted when we managed to shave around 20% off their time. That’s a big win, because they can get back to their day jobs earlier on and do more testing with the available time,” said Armitage.

Building a Business Case

While many IT experts will understand the importance of sophisticated testing capabilities, the reality is that they also need to build a business case that emphasizes the importance of testing to business leaders. However, this can be difficult, particularly when the primary benefit is avoiding potential catastrophes rather than generating direct revenue.

Armitage acknowledged that the “tipping point” for investment varies among customers. Companies that have experienced significant negative impacts from software failures often find the justification straightforward.

However, for others, the impetus might come from middle management facing increasing pressure due to inadequate testing coverage or the rising frequency of software updates.

The shift towards monthly updates by vendors like Infor, compared to the less frequent updates of on-premise systems like SAP ECC or Oracle EBS, makes traditional manual testing approaches increasingly unsustainable.

Armitage emphasized the need to present a compelling case to senior management, which Original Software assists customers in doing. Highlighting real-life examples of companies narrowly avoiding major issues can be a powerful tool.

Adapting to the New Normal

Companies often struggle to adapt to the rate of change in the new technological landscape. Armitage said that the move to the cloud has changed the rules in terms of vendor relationships and it also means that businesses are not in control of how often they need to run tests on their software.

Finding a partner like Original Software in this new environment is essential. It can help companies not only understand the technology landscape as it now exists but allow them to adapt to it. With new software deployments and upgrades constantly being rolled out, businesses need to have confidence that their investments are being protected from risk and can deliver the value they need to reach their business goals.

The post Protecting and Maximizing ERP Investment through Testing appeared first on ERP Today.

Unlocking the Autonomous Advantage in Supply Chains

The modern supply chain is a dynamic and often unpredictable entity. AI is providing the key to unlocking an ‘autonomous advantage,’ driving substantial business value. The numbers speak for themselves. According to the early findings of a study by the IBM Institute for Business Value (IBV), organizations with a higher investment in AI for supply chain operations witnessed an impressive 11.02% revenue growth in 2024, a substantial 61% premium compared to the 6.83% growth experienced by their less-invested peers.

This significant growth is fueled by AI’s ability to deliver real-time, personalized responses to transactional inquiries and drive improvements across critical areas like supply chain management, bottleneck identification, and design innovation. AI’s proactive capabilities are also crucial, allowing businesses to anticipate issues and generate mitigation plans.

By deploying AI across essential workflows such as global trade management and supplier selection, companies can achieve unprecedented levels of efficiency and resilience. The ability to explore and test hypothetical scenarios using data further empowers businesses to prepare for impactful events through autonomous orchestration.

Facing Manufacturing Headwinds with “Pragmatic AI”

The manufacturing sector is grappling with a trifecta of challenges today: escalating operational costs, the complexities of global supply chains, and a widening skills gap. Recognizing this, QAD is championing a practical approach to AI that focuses on enhancing manufacturing operations through “Pragmatic AI” and low-code/no-code extensibility.

This approach empowers manufacturers to integrate data-driven solutions that adapt to their unique needs and improve decision-making without compromising existing workflows. This philosophy emphasizes delivering tangible results rather than getting caught up in theoretical applications.

A prime example of this is the direct embedding of AI into QAD’s core solutions. The company uses AI to recommend commodity classification codes for optimal cross-border taxation and customs clearance, demonstrating how AI can be seamlessly integrated to address specific, pressing operational needs. This leads to measurable improvements without disrupting established processes.

These additions to QAD’s platform enable manufacturers to achieve systemic improvements through better data visibility and optimizing critical areas like supply chain, production quality, and workforce execution.

Simplifying Custom Gen AI

The power of generative AI (GenAI) is undeniable, but the process of creating custom models can often be intricate and resource-intensive. NTT DATA Business Solutions is simplifying this process with its innovative GenAI Connector. This tool is designed to streamline the creation of custom generative AI models, allowing businesses to leverage their own data and select the most suitable large language models to rapidly build and refine AI applications.

The GenAI Connector significantly reduces the complexities involved in GenAI development by offering a user-friendly process. Users can effortlessly load business data, configure models, and iterate on their performance. This streamlined approach profoundly impacts ERP systems as it automates routine tasks like data entry, document processing, and report generation.

Additionally, the ability to analyze vast datasets allows for generating insightful recommendations, identifying hidden patterns and anomalies, and forecasting potential outcomes. Together, these features provide businesses with a significant competitive edge.

High-Impact GenAI Deployment

Recognizing the transformative potential of Generative AI, Inetum launched its GenAI Factory initiative in April 2024. This initiative is designed to support clients through every stage of their GenAI projects, from the initial spark of an idea to full-scale deployment. These services are structured around four key pillars: Assimilation, Qualification, Prototyping, and Scaling.

Through Assimilation, Inetum assists teams in selecting suitable models and technologies. Qualification involves a thorough evaluation of business challenges to determine the feasibility of GenAI solutions. Prototyping focuses on developing initial models to validate concepts. Finally, Scaling ensures the successful deployment of GenAI solutions, complete with training programs for seamless integration.

Inetum strategically collaborates with industry giants like Microsoft and SAP to integrate cutting-edge technologies into their offerings. The company’s focus is on industries where GenAI can deliver the most significant impact, including banking, energy, the public sector, and customer experience.

The Future is Intelligent

The integration of AI into ERP systems represents a fundamental shift towards the intelligent enterprise. As AI continues to evolve, its role in ERP will only become more profound, empowering organizations to operate with greater agility, efficiency, and foresight.

What This Means for ERP Insiders

Navigate the hype and focus on what’s best for you. While AI offers significant potential for ERP, users must be discerning about its application. Focusing on practical AI solutions, like those offered by QAD, that address real operational problems with a human-in-the-loop approach is key to avoiding the pitfalls of overhyped or ineffective AI implementations. Prioritize AI tools that offer tangible benefits and integrate seamlessly into your organization’s existing workflows rather than going for something new that might not ease your processes or increase your ROI.

Explore the potential of custom GenAI models. The emergence of tools like NTT DATA Business Solutions’ GenAI Connector and Inetum’s GenAI Factory make it easier for ERP users to explore the development of custom generative AI models tailored to their specific business needs. This opens opportunities to automate complex tasks, gain unique insights from data, and enhance decision-making in ways that off-the-shelf solutions might not fully address. Consider how custom GenAI models could provide a competitive edge by leveraging their proprietary data.

Embrace the evolution towards autonomous supply chains. The trend towards AI-enabled supply chains, including the development of AI agents, signifies a shift from reactive to proactive supply chain management. This means the potential for systems that can anticipate disruptions, optimize inventory levels, and even make autonomous decisions within defined parameters. Understanding this evolution and exploring how AI can enhance visibility and resilience in their supply chains is crucial for future success.

The post The Rise of Intelligent Business appeared first on ERP Today.

To help the office of the CFO understand how to best leverage their ERP to drive value and innovation, ERPToday recently sat down with Michael Ross, Chief Strategy and Product Officer at Trintech.

Filling the Gaps

Ross highlighted how important it is to find the right partner to help guide the way in the financial close automation landscape. Though platforms like Oracle and Workday are powerful on their own, companies like Trintech help to “fill the gaps” by providing functionalities that these ERPs don’t inherently cover in detail, particularly in the complex area of Record to Report (R2R) activities.

“I’d say the office of the CFO and Financial Services was later to technology. We see that that is a market that is going through a transformation cycle, with new banking cores, new GLs, and new ERPs. We also see new compliance obligations really targeting financial services, with banks and capital markets. That really drives scale requirements. We’re seeing that as a space that we want to make more accessible to more customers because we see that scale for financial services just continuing to grow,” said Ross.

A key tool companies can rely on in this area is Artificial Intelligence (AI). Trintech is working to develop an in-house LLM with unique capabilities and the exploration of agentic AI models for tasks like matching, reconciliation, and journal entry automation. There are varying levels of AI readiness across industries, especially in heavily regulated sectors like financial services, so companies need flexible solutions that can adapt to different compliance environments.

Finding the Right Solutions

The most effective solutions are not one-size-fits-all. By offering platforms like Cadency for large enterprises and Adra for mid-sized organizations, Trintech caters to a wider range of organizational needs and complexities.

“We believe fundamentally that there are different segments and industries that need unique capabilities, right. Trintech is a great example; we run Adra. If we ran Cadency, it would be like driving a Mack truck when we need a Porsche. If you’re a Fortune 10 company, Cadency is a great choice. They’re both great cars, but every car has a great buyer,” said Ross.

Ross also highlighted Trintech’s vertical market focus, particularly in financial services and retail. The company is investing in solutions tailored to the unique needs and scale requirements of these industries, including leveraging technology gained through acquisitions to enhance banking-specific capabilities. This targeted approach emphasizes the importance of specialized solutions in addressing complex reconciliation and close challenges within specific sectors.

If you look three to five years out, everything will evolve around your view of data and AI. If you are AI centric, it all comes back to your data. You need to think about how to get the data clean and crisp.

While Trintech remains open to opportunistic inorganic growth, Ross emphasizes the strong focus on organic growth driven by the significant opportunities to improve financial close processes for existing and potential customers across their target ERP and vertical markets.

In his advice to a prospect navigating digital transformation in the office of the CFO, Ross stresses the critical importance of understanding their business readiness for AI and the need to ensure data quality. Though tools like those that Trintech provides can play a vital role in achieving financial reporting accuracy and controls, but companies must ensure that their data is AI-ready.

“If you look three to five years out, everything will evolve around your view of data and AI. If you are at a you are AI centric, it all comes back to your data. You need to think about how to get the data clean and crisp, whether it’s for tools like Cadency for financial access and controls or other tools. This is one of the areas where we’re starting to have customers come to us because they realize they need to get their data in order to use AI. And we’re a tool that helps with financial reporting accuracy and controls,” said Ross.

What This Means for ERP Insiders

Filling the Gaps in ERP Functionality
White ERP platforms like have powerful for financial management functionalities, they often lack detailed coverage for important activities like Record to Report (R2R). Companies must seek out partners like Trintech to fill these gaps with automation solutions for reconciliation, transaction matching, journal entry automation, and compliance reporting. The financial services sector, in particular, faces growing complexity with new compliance obligations and evolving banking structures. Trintech’s solutions help finance teams handle these challenges and scale effectively.

Leveraging AI is challenging, but likely will prove to be a worthwhile investment. The role of AI in financial close processes is slowly expanding. AI adoption varies across industries, but has been slower in highly regulated sectors like financial services, making flexible and adaptable AI-driven solutions essential. Ross advised companies to ensure their data quality is AI-ready to maximize the benefits of automation and improve financial reporting accuracy. Trintech is developing its own RN LLM and exploring agentic AI models to automate complex tasks like reconciliation and journal entry management.

Tailored Solutions for Different Business Needs. Trintech offers specialized solutions based on business size and complexity. Cadency is designed for large enterprises, while Adra caters to mid-sized organizations. Ross compared the two to a Mack truck and a Porsche—both effective, but suited for different needs. Trintech also focuses on specific verticals like financial services and retail, providing targeted solutions to meet industry-specific challenges. The company aims for organic growth while remaining open to strategic acquisitions to enhance capabilities.

The post Meeting the Financial Needs of the Modern CFO with Trintech’s Michael Ross appeared first on ERP Today.

At a glance, your ERP might be “working fine.” Orders process, invoices get paid, reports are run. But scratch the surface and you’ll find layer upon layer of outdated custom code, hard-coded integrations, bolt-on fixes, and decade-old workflows duct-taped to modern requirements. That’s not transformation—that’s survival. And it’s fragile.

Technical debt is the accumulated cost of quick fixes and shortcuts in software development that come back to haunt you. In ERP, it’s often rooted in legacy systems that were heavily customized during initial implementation— especially with platforms like SAP ECC, Oracle EBS, or Dynamics AX. Back then, it seemed smart to tailor everything to your business. But now, as vendors push cloud native platforms (SAP S/4HANA Cloud, Oracle Cloud ERP, Dynamics 365), those same customizations are massive roadblocks.

Consider this: it is estimated that by 2027, 70% of ERP transformation failures will be attributed to underestimating legacy complexity and technical debt. That’s a staggering figure, but one I see reflected every day in conversations with CIOs and operational executives. You can’t innovate if your core system is rigid and tangled in code no one wants to touch.

Let’s take a real-world example. One of our manufacturing clients wanted to shift to SAP S/4HANA to gain real-time analytics and automation. What should have been an 18-month journey turned into 30 because of legacy ABAP customizations no one fully understood. Each modification had to be rewritten, retested, and revalidated. The cost? Millions in delays—and lost competitive advantage.

So, what’s the answer?

First, get honest about your ERP baseline. Conduct a “technical debt audit.” Tools like SAP’s Custom Code Analyzer or Oracle’s Application Upgrade Advisor can show you just how deep the rabbit hole goes.

Second, embrace the clean core. This means standardizing processes where possible and using low-code/no-code extensions (like SAP BTP or Microsoft Power Platform) instead of heavy customization. You keep the system upgradeable and agile.

Third, treat ERP as a product, not a project. This mindset shift—from a one-time implementation to ongoing lifecycle management—forces you to consider not just cost and scope, but also sustainability. How will this decision age? Can it scale with AI and automation?

And finally, make your architects your best friends. Business leaders often see architecture as a tech-side issue. It’s not. The wrong architectural decision today is your business bottleneck tomorrow.

In a time when agility, compliance, and customer experience are all ERP-dependent, technical debt is not just an IT concern—it’s a strategic threat. The companies winning today are the ones who treat ERP transformation not as a migration, but as a modernization—one that starts by cutting the dead weight.

Let’s stop pretending ERP is a back-office tool. It’s your digital nervous system. And like any system, it can only operate at peak performance if it’s lean, clean, and built to adapt.

The post Technical Debt is the Silent Killer of ERP Transformation appeared first on ERP Today.

Yet for all the promise, the path to adoption is fraught with complexity. From integrating generative and agentic AI systems to navigating governance, compliance, and workforce trans formation, the execution challenge is real. This article provides a practical roadmap for executives seeking to align cutting-edge technologies with business priorities, regulatory requirements, and long-term ROI.

AI’s impact is inseparable from the data it draws on and the automated systems through which it operates. AI interprets data; automation acts on those insights. The interplay is crucial. “Think of AI as the brain, data as the senses, and automation as the body,” said the CIO of a global logistics firm. “Together, they create a learning, adaptive enterprise.”

Agentic AI—systems capable of autonomous decision-making within de fined constraints—represents the next frontier. Unlike traditional AI models, which require constant human supervision, agentic AI operates with goal orientation, continuously learning and optimizing.

AI, data, and automation are not silver bullets—they are force multipliers.

Large Language Models (LLMs) like GPT-4, Claude, and enterprise-specific variants are redefining knowledge work. From generating legal drafts to answering customer queries in natural language, LLMs promise not just automation but augmentation—an entirely new layer of digital capability.

Predictive analytics, meanwhile, provides foresight. It enables decision-makers to act preemptively, not reactively—forecasting everything from supply chain disruptions to customer churn.

AI adoption is not plug-and-play. A practical, four-stage framework ensures that deployment is grounded, scalable, and aligned with business strategy.

1. Strategic Alignment & Business Case Development

• Define Use Cases: Prioritize areas where AI can deliver measurable impact—fraud detection, personalized marketing, dynamic pricing.
• Quantify ROI: Estimate returns using metrics aligned with business KPIs, such as cost-to-serve, conversion rates, or asset uptime.
• Assess Readiness: Conduct an organizational maturity assessment across data infrastructure, talent, and governance.

2. Data and Infrastructure Readiness

• Data Quality and Accessibility: Ensure datasets are clean, integrated, and compliant with standards like GDPR and CCPA.
• Model Infrastructure: Choose between cloud, hybrid, or edge deployment. For high-performance workloads, consider vector databases and GPU acceleration.
• Vendor Strategy: Evaluate partnerships for model provisioning (OpenAI, Anthropic), orchestration platforms (Data Robot, H2O.ai), and infrastructure (AWS, Azure, GCP).

3. Governance, Risk, and Compliance

• Ethical Guardrails: Establish principles around fairness, explainability, and accountability. Appoint an AI Ethics Officer.
• Model Auditing and Validation: Adopt tools for drift detection, adversarial testing, and interpretability (e.g., SHAP, LIME).
• Regulatory Alignment: Stay ahead of AI-specific legislation such as the EU AI Act and U.S. AI Bill of Rights.

4. Deployment, Monitoring and Continuous Improvement

• Pilot Programs: Run limited-scope pilots to test efficacy and gather feedback. Use these to refine assumptions.
• MLOps and AIOps: Use DevOps-like practices for continuous deployment, versioning, and monitoring of AI systems.
• Human-in-the-loop Design: Integrate human oversight where necessary to maintain control and safety.

Governance isn’t a brake on innovation—it’s a necessary accelerant. Without it, AI initiatives risk collapse under scrutiny. A 2024 study showed that only 32% of executives feel “very confident” their AI is compliant and ethically sound. That’s a significant gap—and a call to action. Robust AI governance should include the following: Cross-Functional Councils in volving legal, compliance, IT, operations, and business units; Risk Heat Maps that map model and data risk across the enterprise; Third-Party Reviews, or regular audits to identify hidden biases, black-box models, or training data gaps; and Incident Management Plans, which are playbooks for managing AI related errors, from misclassification to hallucination.

“In highly regulated industries like healthcare or finance, governance can’t be an afterthought,” said a Chief Compliance Officer at a multinational bank. “It must be embedded from design to deployment.”

In these early days of the AI age, there are several myths that need to be debunked. The most significant myths are as follows:

MYTH 1: AI Delivers Immediate ROI

Reality: Strategic value often takes time to materialize. Short-term wins are possible, but transformative returns require integration, iteration, and cultural change. Recent reports suggest that only 8% of firms effectively scale AI. Why? Because they underestimate the time and investment needed for full adoption—including re-skilling, change management, and infrastructure. But beware of “death by proof-of-concept.” While ROI may not be immediate, have a plan to scale within a handful of use cases beyond the first few demonstrations of business impact.

MYTH 2: AI Will Eliminate More Jobs Than It Creates

Reality: AI changes jobs more than it erases them. It automates routine tasks but amplifies creative, strategic, and interpersonal functions. The World Economic Forum predicts that while 85 million jobs may be displaced by 2025, 97 million new roles will emerge—data scientists, AI trainers, compliance analysts, and more. Enterprises are investing in upskilling programs like IBM’s SkillsBuild and Google’s AI Career Certificate to bridge the gap.

MYTH 3: Ethics Slows Down Innovation

Reality: Ethics reduces friction, builds trust, and accelerates adoption. Take Microsoft’s Responsible AI framework—it didn’t slow its pace. It enabled them to move faster in regulated sectors like defense, education, and finance. Ethical AI builds a brand moat. Companies with clear, well-communicated AI values gain customer loyalty, employee engagement, and investor confidence.

Technology is only part of the equation when it comes to AI, data and automation. Success depends at least as much on human capital, organizational change management, skills development, talent acquisition and retention, and functional evolution. AI adoption must be sponsored from the top. CEOs and boards must signal its strategic importance and provide cover for experimentation. Transparent communication about AI’s purpose, potential, and limits can reduce fear and resistance. Empower employees as co-creators, not just end users. Cross-training employees in data literacy and AI fundamentals pays dividends. Encourage AI fluency across all departments—not just IT. Case in point: a major European telco launched an internal AI academy. Within a year, over 5,000 employees had completed courses, leading to 47 new AI-driven initiatives initiated from within business units.

You can’t manage what you can’t measure. C-level leaders must define success in AI not by experimentation, but by impact. Dashboards and OKRs should track AI initiatives alongside traditional performance metrics. Best practice is to review quarterly, iterate often.

Common KPIs associated with AI impact include:

• Operational Efficiency: Reduction in manual hours, error rates, or time-to-resolution.
• Customer Experience: Improvements in Net Promoter Score (NPS), retention, or personalization accuracy.
• Revenue Growth: Uplift from targeted marketing, dynamic pricing, or new AI-enabled services.
• Risk Mitigation: Fewer compliance breaches, faster anomaly detection, improved model explainability.

Agentic AI – referred to increasingly as the digital workforce – is gaining steam as potentially the most transformative AI application. By way of example, a global e-commerce platform recently deployed agentic bots to autonomously manage supply chain disruptions. These agents analyzed weather data, social media sentiment, and vendor performance to reroute shipments in real-time. The result? A 21% reduction in delayed orders, 14% savings in logistics costs, and a customer satisfaction boost of 11%. The initiative was so successful it’s now being replicated in other business functions. What made it work? Executive sponsorship, robust data infrastructure, and real-time monitoring. Plus, a fallback mechanism: human supervisors had override authority.

CxOs should be con templating the following questions now, in order to set their companies up to fully capitalize on the trans formative potential of AI, data and automation:

• Which parts of our business could benefit most from GenAI or agentic AI?
• Do we have a governance framework robust enough for emerging regulations?
• Are our data assets clean, connected, and compliant?
• What’s our talent strategy for AI? Are we hiring and upskilling at the right pace?
• How do we align AI projects with measurable business outcomes?

AI, data, and automation are not silver bullets—they are force multipliers. When guided by strategy, governed responsibly, and deployed with human-centered intent, they unlock transformative value. C-level leaders stand at a crossroads. The tools are ready. The frameworks are proven. What’s needed now is bold but disciplined execution. The winners in the AI era will be those who move not just fast, but wisely—aligning technological ambition with ethical stewardship and business impact. The time to lead is now.

What This Means for ERP Insiders

• Don’t get lost in the technical complexities of AI, data, and automation. C-level leaders must prioritize identifying specific business problems within the ERP system by focusing on defining clear use cases and quantifying the potential ROI using relevant business KPIs such as reduced order fulfillment time, increased customer retention and improved inventory accuracy. Moreover, whether those issues are supply chain inefficiencies, customer service bottlenecks, or financial reporting delays, organizations must ensure their AI and data plans align with the overall business strategy for those specific issues. This keeps initiatives grounded and focused on delivering real value rather than chasing the latest tech trends.
• AI is the “brain,” data the “senses,” and automation the “body.” Organizations that prioritize data quality and governance as foundational understand this concept, as the effectiveness of any AI or automation initiative hinges on the quality, accessibility, and compliance of the data within and connected to their ERP system. C-level leaders must ensure investments are made in data cleansing, integration, and establishing robust data governance frameworks. Furthermore, as AI adoption increases, so does the need for strong ethical guardrails, model auditing, and regulatory alignment. Ignoring these foundational elements will lead to flawed insights and potentially risky or non-compliant AI deployments within the ERP environment.
• Implementing AI and automation within an ERP context is not just a technology project. It is a significant organizational change that includes the human element. C-level leaders must actively address the human capital implications, including potential job role changes and the need for upskilling employees to work alongside AI-powered systems. Planning for change management, transparent communication about the purpose and impact of these technologies, empowering employees as co-creators, and investing in training programs are crucial to overcome resistance and foster a culture of adoption. The focus should be on augmenting human capabilities with AI and automation within the ERP workflow, rather than simply replacing human tasks.

The post AI, Data and Automation: Cutting through the Noise and Navigating the New Frontier of Enterprise Value appeared first on ERP Today.

Faced with a fragmented IT landscape, the challenge of retaining knowledge amid personnel turnover, and the increasing complexity of its projects, the company embarked on an ambitious transformation program aptly named Founding the Future. At the heart of this initiative lies the implementation of IFS Cloud, a strategic move designed to create a unified, future-proof backbone for the entire organization.

In conversation with ERP Today, Ralph Staal, Program Manager for the IFS implementation at Van Oord, shed light on the strategic imperatives that led the organization to embark on this journey.

“A couple of years ago, we knew we had to focus on leveraging the data we create daily,” Staal explained. “However, we struggled to translate that into proper initiatives that harmonize our application landscape and secure the foundational business processes in finance, procurement, and supply chain, especially on the project side.”

Addressing Complexity

A key driver was the evolving nature of Van Oord’s work and workforce as their projects became increasingly complex. Compounding this was the attrition of personnel as they take a lot of knowledge with them, making it imperative for Van Oord to set up a system that can institutionalize this valuable experience.

“By implementing a degree of standardization, we would have a way to retain knowledge and use that for our future projects to create better budgets, designs, and forecasts,” Staal said.

The desire to be more data-oriented was also paramount, with Staal emphasizing the practical need “to make sure we have the right data at the right time with the right person looking at it to take the right decision.”

A Strategic Fit

Given these goals, a simple cloud migration wouldn’t do for Van Oord; it was a ground-up implementation that also included replacing a legacy finance system. Van Oord is already a construction and engineering customer for IFS and after a thorough selection process, IFS Cloud, emerged as the clear choice for its maritime business too. “IFS really stood out,” Staal recounted. “We found that IFS had the best understanding of how contracting projects work; in terms of terminology and functionality, we just found that they were a good fit for our industry.”

IFS Success has really helped us make sure that we made the right decisions. – Ralph Staal, Program Manager for IFS implementation at Van Oord

The platform’s balance between standardization and flexibility was also appealing. “IFS is configurable, but it’s not extremely customized,” Staal observed, adding, “We’re trying to stick to standard as much as possible.”

According to Staal, the move toward the cloud was logical. “When we roll out the solution, we want to have one that is connected, reusable, and scalable,” he confirmed.

Navigating the Implementation Journey

Implementing a new ERP across a global, project-centric organization is inherently challenging. Van Oord faced hurdles like migrating from an extremely fragmented application landscape, establishing data and process ownership in an environment where these concepts were relatively new, and aligning numerous stakeholders across traditional organizational silos.

“Aligning with all the stakeholders so that we don’t face resistance later is the real challenge,” Staal admitted. Adding to the complexity, Van Oord is simultaneously implementing other major systems, like Workday and new planning solutions, requiring careful coordination and integration.

When Staal spoke with ERP Today in April, the project was nearing a major milestone. “We are at the final stages of the acceptance phase and will begin the user acceptance test phase for our first release in two weeks,” he shared. “Our first real entity will go live in June.”

Throughout this complex process, Van Oord has leveraged IFS Success—an engagement model delivering the knowledge and tools for customers to realize their true, long-term business potential. Staal noted that IFS Success “has really proven its worth, helping with explaining the best practices, doing design validations, and providing guidance on critical decisions.”

He added: “IFS Success has really proven its worth in the past year and half. [The] Customer Success Manager could look at some of the things we’re missing in our project and utilize IFS Success to provide that value to our project and our organization and that came in many different forms.”

“IFS Success has really helped us make sure that we made the right decisions,” Staal affirmed adding that he expected IFS Success to continue playing a large role in helping the company set up future support organization.

It’s about people working in a solution; not a solution dictating how people should work.

Future Focus

Van Oord expects significant benefits once the system is up and running in H2 this year. Technically, scalability and the ability to stay current with IFS updates by adhering to standards are key. For the business, Staal expected “better decision making through rolled-up data and insights, enhanced collaboration between the departments, and greater efficiency via reduced manual work, leading to faster financial closing and fewer errors.” Improved procurement cycle times and supplier performance management are also major targets.

Crucially, IFS Cloud also provides a foundation for future innovation. “As soon as we have this solid foundation in place, we can shift our focus [to] more innovative developments on top of our cloud solutions,” Staal said, hinting at future explorations like AI, enhanced sustainability tracking, and Quality, Health, Safety, Environment (QHSE) modules within IFS.

The Human Element

However, Staal emphasized that technology is only part of the equation. Effective change management, handled by a dedicated stream within the program using tools like a change network of ambassadors, remains critical. The biggest challenge is embedding ownership within the business itself. “The business is also taking ownership of what we deliver because the change will happen in the department. It will not happen in the project,” he explained.

Reflecting on the broader lessons learned, Staal concluded, “The real challenge is to really step away, and not so much look at a solution, but at how you work together and what you want to achieve together. In the end, it’s about people working in a solution, not a solution dictating how people should work.”

What This Means for ERP Insiders

Industry-specific cloud ERP is the norm for complex sectors. The market for cloud ERP is expected to hit around $74 billion by 2029, growing over 12% annually. However, the real momentum for companies in asset-intensive, project-driven sectors like Van Oord lies in industry-specific cloud solutions. While manufacturing leads overall ERP adoption, specialized providers gain traction because they embed deep domain knowledge, relevant KPIs, and pre-configured processes like complex project accounting or asset lifecycle management out-of-the-box. Van Oord’s selection explicitly hinged on finding a vendor that truly understood the contracting world and project core, which is why it chose IFS. Generic solutions often require heavy, risky customization to meet these unique demands, whereas industry-focused platforms like IFS Cloud offer a faster path to value and align better with specific operational needs.

Balance control, integration, and vendor alignment. Companies like Van Oord operate globally, often in remote locations, manage high-value assets, and handle complex projects, making their enterprise application strategy critical. When considering hybrid cloud ERP, key decision criteria include data governance & security, integration complexity, edge capabilities, and vendor industry focus. For the latter, for example, IFS focuses on asset-intensive, project-centric, and service-focused organizations in sectors like Construction, Energy, Utilities, Aerospace & Defense, Manufacturing, and Maritime. Aligning your needs with a vendor’s core competency reduces implementation risk and ensures the platform evolves with relevant industry capabilities.

Foster supply chain resilience amid volatility. Near-term factors like shifting tariffs highlight the need for supply chains built for resilience, not just static efficiency. Organizations should, therefore, expect their Cloud ERP provider to offer capabilities like unified visibility, scenario modeling, sourcing flexibility, and agile execution. For instance, Babcock International (Energy & Marine) leverages IFS as a full ERP across complex, multi-billion-dollar projects (like aircraft carrier construction and nuclear submarine maintenance). They have completed over 4,630 projects using IFS, relying on it as their “single point of truth” for managing materials, costs, labor, and asset maintenance across 12,000 users. Similarly, Royal IHC (Maritime) successfully consolidated 17 disparate legacy ERP systems into a single global IFS instance across 37 operating units in just 2.5 years, achieving significant standardization and efficiency gains.

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