AP520 Error Job Already Exists

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If your AP520 job goes into recovery with invalid parameters, and the examine log contains the error message “AP520 conflict, job already exists”, that means either an AP520 is already in recovery, or you will need to delete the conflicting record from APMONITOR.  First, check to see if any user has an AP520 job in recovery.  If they do, then resolve the issue and recover the job.  If there is no AP520 in recovery, you will need to delete the conflict from APMONITOR.  Either create a paint screen for the APMONITOR file, or connect to your database directly using a database utility.  Look for a duplicate AP520 job to the one that you are trying to run.  Remove that record from APMONITOR and recover your job.

 

Data Transparency In The AI Age

As artificial intelligence (AI) becomes more embedded in product development and operations, it’s reshaping not just factories, but the relationships between brands and the companies that build their products. In a recent Forbes article, senior contributor and CEO of AI-powered analysis platform Instrumental Anna-Katrina Shedletsky explores how data transparency is becoming a defining force in electronics manufacturing in the AI age. Historically, electronics manufacturing has operated on thin margins and “cost-plus” contracts, giving factories little incentive to share detailed production data. Full transparency can expose efficiencies or issues that brands might use to renegotiate pricing, making manufacturers understandably cautious. As Arch Systems CEO Andrew Scheuermann points out, when margins can be as low as two percent, unrestricted data sharing can feel existential. AI is beginning to shift that dynamic. Brands are investing in large data sets that combine design, manufacturing, and returns information to improve product quality and customer experience. To unlock that value, manufacturers must move beyond one-off reports toward more open, continuous data sharing—forcing both sides to rethink trust, accountability, and partnership models.

The article highlights Logitech as an example of this evolution. Led by global quality and manufacturing head Martin Hess Pedersen, Logitech treats manufacturers as partners rather than suppliers. Contracts share risk, while transparency flows both ways: factories gain insight into consumer sentiment, return rates, and product performance, creating a powerful feedback loop between the factory floor and the customer. AI accelerates this shift by enabling collaborative problem-solving, from temporary, task-specific data use to “closed-loop quality” systems that connect factory data with real-world usage. The payoff is faster innovation, higher quality, and stronger partnerships—driven as much by trust as by technology.

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Enterprises Turn to Cloud Security, Management Solutions for Agility, Protection, Cost Control

As cloud environments grow more complex and interconnected, enterprises are re-evaluating how they manage security, governance, and costs at scale. In a recent article for ERP Today, content director Tarsilla Moura explores how U.S. organizations are reshaping their cloud strategies to prioritize stronger security, tighter management, and greater operational efficiency. Organizations are increasingly turning to managed cloud security services to improve resilience, protect against expanding cyber threats, and stabilize operations. With workloads spread across platforms like AWS, Azure, Google Cloud, and private clouds, many enterprises are finding that internal teams alone can’t keep pace with growing attack surfaces, compliance demands, and skills shortages. External partners are filling that gap with 24/7 monitoring, cloud-native security controls, and ongoing operational support.

At the same time, cloud management solutions are gaining traction. These tools provide unified visibility, automated governance, and data-driven insights that help enterprises rein in costs and maintain performance across fragmented environments. Together, cloud security and cloud management are becoming inseparable parts of a more structured, partner-led operating model. The article points to examples of providers helping enterprises reduce misconfigurations, improve reliability, and significantly lower monthly cloud spend through automation, policy-based controls, and architectural optimization. Looking ahead, AI-driven automation and predictive analytics are expected to further transform cloud operations, with managed cloud services projected to grow rapidly over the next decade. For ERP leaders, the message is clear: system performance and reliability increasingly depend on disciplined cloud governance and security, not just application optimization. Enterprises that unify security, management, and automation will be best positioned to scale efficiently and sustain long-term value.

 

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How to Fix users not seeing bookmarks even though they have access Lawson v10

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Follow the quick guide below to learn how to fix users not seeing bookmarks even though they have access Lawson v10.

 

Problem:

When logged in to the Lawson v10 dashboard, you notice that the user is missing a Manager Self-Service bookmark (see screenshot):

 

Resolution:

As an admin, navigate to “Manage Roles” on your Lawson Homepage:

 

Select the portal role assigned to user (if default.xml, then create a new one):

 

Next, enable “Allow use of menus and user defined bookmarks”:

 

This should now show the additional bookmarks the user has access to:

They may have to log out then log back in to see the changes made. That’s it!

Data Benefits AI; AI Benefits Data

AI (artificial intelligence) and data are inseparable: without one, the other can’t reach its full potential. As Forbes enterprise tech contributor Joe McKendrick explains in a recent article, the latest AWS blueprint shows that in the era of large language models, what really sets companies apart is not the AI itself, but the quality, structure, and accessibility of their data. Generative AI needs more than just structured data—it thrives on unstructured and multimodal data like video, audio, and code. Yet many organizations struggle to make their data AI-ready, facing barriers in accessibility, accuracy, and completeness. The good news? AI can help fix these gaps. Tools like agentic AI and LLMs automate data profiling, quality checks, and integration, transforming passive storage into intelligent, business-aware ecosystems. This not only unlocks trapped insights but also makes data accessible to a wider audience, empowering smarter decisions across the organization. To succeed, AWS recommends an AI-first data strategy: audit and unify data, modernize architecture, build internal skills, keep humans in the loop, and measure outcomes. McKendrick summarizes when data and AI work together, businesses don’t just get smarter technology—they get a smarter, more agile organization.

 

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How to debug Lawson Business Intelligence (LBI) Report prompting Database Login

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Learn how to debug Lawson Business Intelligence (LBI) Report prompting Database Login.

 

Here is an example issue when opening a report via LBI dashboard:

It prompts to a login screen and no credentials work:

To solve this, first validate the datasource of the report and validate its correct (it may resolve after you click save and test the report again)

If not, see if you can view the report with Data Refresh

If it generates data, you can grab this URL:

Edit your report from the dashboard, in this example we edit the “LP Exception Report”:

You can copy this URL:

You can either replace it complete with the top URL shown below with the HTTPS://yourorg.domain.com…. Etc.

OR

You can modify the link with just the tail end of it as shown below:

Then copy and paste this URL back in and save:

That’s it! Test it and the database login prompt should no longer show if you followed everything correctly.

If this is too complex for you and you need Lawson specialists to help manage your Lawson ERP system, Nogalis offers a team of consultants to help manage this for you under one MSP contract. Feel free to reach out to us to get a free consultation today.

The 8 Data Trends That Will Define 2026

Data is evolving just as fast as AI—and according to strategic business & technology advisor Bernard Marr in an article he shares on Forbes, the organizations that win in 2026 will be those that rethink how they collect, govern, and activate information.

Marr highlights eight major data trends shaping 2026:

  • Agent-Ready Data: Ensuring data is accessible, structured, and secure for AI agents.

  • GenAI for Data Engineering: Automating cleaning, formatting, ETL, and audits with natural-language-driven pipelines.

  • Data Provenance: Strengthening traceability and authenticity across all data sources.

  • Compliance & Regulation: Navigating new rules like the EU AI Act and evolving U.S. state-level laws.

  • The Agentic Edge: Moving AI agents onto devices and sensors for real-time, on-site decision-making.

  • Generative Data Democracy: Enabling everyone to access insights using natural language—supported by strong data literacy.

  • Synthetic Data: Accelerating adoption of realistic, privacy-safe AI-generated data.

  • Data Sovereignty: Managing cross-border rules, ownership, rights, and IP-safe usage.

These trends reflect a broader shift: AI agents are becoming the primary consumers and processors of enterprise data. To prepare, organizations must modernize their data infrastructure, remove silos, and adopt stronger governance frameworks. GenAI will drastically reduce the friction in data engineering, but only trustworthy, well-governed data will deliver reliable insights.

Marr’s message is clear: the data landscape of 2026 is faster, smarter, and more autonomous. Those who invest early in agent-ready systems, generative tooling, and compliance-aligned architecture will gain a sharp competitive edge—while those who wait risk being left behind in the agentic era.

 

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The New Speed Of Business: Preparing ERP For The AI Era

Business is moving faster than ever—and according to supply chain management and manufacturing expert Richard Howells and his recent article on Forbes, organizations won’t keep up unless their enterprise resource planning (ERP) foundations are ready for the artificial intelligence (AI) era. AI doesn’t magically create speed; it amplifies the quality of the data and systems it sits on. Without clean, connected, and timely data, AI risks exposing gaps rather than delivering value.

Howells reflects on lessons from the predictive analytics wave: dashboards alone couldn’t predict the future without solid data foundations. Today, ERP is evolving from a back-office ledger to a real-time decision platform, connecting operations, finance, and customer data in one intelligent system. Employees can now interact with cloud ERP that surfaces anomalies, recommends actions, and enables instant decision-making. Utilities are leading this shift. Once reactive and siloed, they now leverage AI and sensor data to predict equipment failures, optimize crew deployment, and resolve issues before customers notice. In manufacturing, machine learning adjusts chemical processes mid-run, while IoT-enabled ERP synchronizes maintenance, production, and logistics in real time. Even customer operations are benefiting: AI accelerates case management, reduces errors, and embeds intelligence directly into workflows.

Howells stresses that the challenge isn’t deploying AI—it’s preparing for it. Companies must modernize legacy systems, clean and connect data, and scale high-value use cases quickly. Those that do can turn ERP into a true engine of speed and insight, responding to market changes instantly. Those who delay risk falling behind more agile, data-ready competitors. The future of ERP isn’t just about transactions—it’s about transformation, where real-time decisions and readiness define competitive advantage.

 

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IPA Process Notifications

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There may be some cases where you want to notify your IT or other staff that an Infor Process Automation (IPA) flow has run successfully, or has run with errors overall, in addition to internal notifications for specific events.  Follow these steps to set up notifications on an IPA process.

  1. First, log into Process Administrator.
  2. Next, navigate to Configuration > Process Definitions > User Defined Process
  3. Open your Process.
  4. On the “Notify by Email” option, select your preferred option.
  5. Once you select an email notification type, the email notification tab will open up.
  6. You can use global parameters in the email details.

You are now set up to receive notifications!

Data Compliance: Can AI Help Users Navigate New Technologies and Regulations?

In today’s fast-evolving digital landscape, data compliance has become a growing challenge for businesses looking to leverage new technologies. In an insightful article for Technology Networks, freelance science writer RJ Mackenzie explores how artificial intelligence (AI) could be the solution to helping companies navigate the complex world of data regulations. As technologies like AI, machine learning, and big data continue to change the way businesses operate, so too do the regulations that govern data protection, such as GDPR and CCPA. Mackenzie highlights how AI could significantly ease the burden of compliance by automating tasks like monitoring sensitive data and flagging potential violations in real-time. This automation can reduce human error, improve efficiency, and provide companies with a clearer understanding of how to stay compliant with evolving laws.

However, the article also stresses the limitations of AI in the compliance realm. While AI is capable of processing large amounts of data quickly, it still requires human oversight, particularly when interpreting complex legal frameworks or making ethical decisions. Mackenzie emphasizes that a balanced approach is essential: AI can assist, but human judgment must remain central to compliance strategies. Ultimately, AI holds great potential in simplifying data compliance, but businesses must use it wisely to ensure they’re meeting regulatory requirements without sacrificing the human elements that ensure ethical and responsible decision-making.

 

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