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How AI Agents Are Reshaping ERP in the “SaaSpocalypse” Era

The term “SaaSpocalypse” – referenced by Rick Rider, SVP of product management for Infor, refers to the predicted upheaval in enterprise software caused by artificial intelligence (AI) agents, which are expected to replace many point SaaS applications. In an interview with Jordan Berger, SVP, TMT Market Intelligence for AlixPartners, ERP Today’s Chris Vavra explains that while this scenario sounds dramatic, the real impact is more nuanced: lightweight, UI-heavy SaaS tools are vulnerable, but core enterprise resource planning (ERP) systems—handling critical data, compliance, and audit trails—remain essential. Berger notes that AI agents are already automating low-judgment workflows like HR intake, procurement approvals, and routine reporting. ERP platforms that thrive will act as stable, governed transaction cores with clean APIs, identity integration, and fine-grained permissioning, while vendors relying mainly on configurable UIs and generic workflows face the greatest risk.

This environment is accelerating demand for modular, API-first ERP architectures rather than full-suite replacements. Enterprises are focusing on making ERP programmable and AI-ready, building narrow, differentiating capabilities in-house while relying on ERP for compliance and integration. Industries with structured, routine work—professional services, retail HQs, and tech—are experiencing the fastest ERP workflow shifts, whereas highly regulated sectors like healthcare, energy, and finance will change more gradually due to compliance and operational constraints. In the post-“SaaSpocalypse” world, ERP and critical industry systems that control data, enforce governance, and enable agent orchestration will dominate, while standalone SaaS point solutions lose relevance. Organizations investing in AI-ready ERP foundations, flexible integrations, and automated governance will capture the most value and maintain a competitive edge.

 

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Creating Favorites

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To view and manage favorites in the Infor Lawson Portal, follow these steps below.

From the home page, select the hamburger icon beside Menu > User Options and select the Favorites tab to view the Favorites configuration.

 

URL / Token

 

The URL is a direct link to an external site, and the token is what’s available to your user, within a specified data area and system code

Click Save to add the new favorite item to your Favorites list. You can also click “Edit Favorites” directly on the home page, then click the Add icon to create new favorites, such as URLs, tokens, or custom forms.

How AI Is Forcing ERP Vendors to Rethink the Human Side of Transformation

Artificial Intelligence (AI) is rapidly reshaping enterprise resource planning (ERP) systems, but it’s also pushing vendors to rethink how they approach the human side of digital transformation. In senior editor Chris Vavra’s recent ERP Today article, the author explores how AI is accelerating employee readiness and what that means for ERP vendors, particularly when it comes to onboarding and governance. Research from SAP and Wakefield Research reveals that 88% of Chief Human Resource Officers (CHROs) believe AI is helping early-career employees become role-ready faster, creating new pressures for ERP systems to deliver intuitive, governed AI tools. With 79% of HR leaders saying early-career employees get AI tools within their first month, vendors must ensure these tools are easy to use from day one—especially for employees who don’t have months of training. This shift towards AI-driven productivity is already showing tangible results, with 56% of CHROs reporting increased confidence and productivity in early-career talent using AI. However, the study also highlights significant governance gaps: 56% of HR leaders say employees turn to unsanctioned AI tools when formal guidance is lacking, leading to compliance and quality risks. To meet these challenges, ERP vendors must prioritize four key practices: designing entry-level roles for higher-value work, embedding critical thinking in onboarding, establishing AI governance from the start, and ensuring equitable AI access. As AI becomes embedded in ERP systems, success will depend on a blend of technology, data readiness, and thoughtful change management.

 

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How the GEN job tables connect

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The GEN job tables provide detailed information about job execution, allowing for tracking and troubleshooting. Each table serves a specific function in recording various aspects of the job lifecycle, from submission through execution to completion. This structure ensures clear mapping of relationships and dependencies among the tables, which is essential for monitoring and managing batch processes efficiently allowing admins to be able to trace job progress and diagnose issues at both macro and micro levels.

🔹 Job Table Relationships

JOBQUEUE (one row per submitted job)

|

|–< JOBSTEP (one or more steps per job)

|       |

|       |–< JOBSTEPLOG (messages for each step)

|

|–< JOBLOG (high-level messages/logs for the job)

|

|–< JOBPARM (parameters used when submitting job)

🔹 GEN tables related to jobs:

JOBQUEUE.JobQueue = primary key (ties everything together).

JOBSTEP.JobQueue → foreign key to JOBQUEUE.

JOBLOG.JobQueue → foreign key to JOBQUEUE.

JOBPARM.JobQueue → foreign key to JOBQUEUE.

Each job in the system is uniquely identified by the JobQueue value, which acts as the primary key and links related records across all main tables. By using foreign keys, the JOBSTEP, JOBLOG, and JOBPARM tables maintain referential integrity, allowing for efficient tracking and management of job execution details and associated parameters.

To retrieve comprehensive job execution data, a query can be constructed that joins the JOBQUEUE table with JOBSTEP, JOBLOG, and JOBPARM using the JobQueue field. This ensures all relevant information, such as job parameters, execution steps, and log messages, can be efficiently accessed and analyzed for each job instance.

Here is an example of a query to find who ran the GL199 with any messages found in the joblog. The results will show

  • Who ran it → UserName.
  • When it ran → StartDate + StartTime.
  • Job status → Status (Success, Error, etc.).
  • Parameters used → from JOBPARM.
  • Messages → from JOBLOG.

 

SELECT     JQ.JobName,    JQ.Program,    JQ.UserName,    JQ.StartDate,    JQ.StartTime,    JQ.EndDate,    JQ.EndTime,    JQ.Status,    JP.ParameterName,    JP.ParameterValue,    JL.Message

FROM GEN.dbo.JOBQUEUE JQ

LEFT JOIN GEN.dbo.JOBPARM JP ON JQ.JobQueue = JP.JobQueue

LEFT JOIN GEN.dbo.JOBLOG JL ON JQ.JobQueue = JL.JobQueue

WHERE JQ.Program = ‘GL199’

ORDER BY JQ.StartDate DESC, JQ.StartTime DESC;

 

Steering Cloud ERP Migrations with Data Governance

Migrating to a cloud ERP (enterprise resource planning) system offers numerous benefits, but without strong data governance, the process can quickly turn chaotic. In a recent article on ERP Today, tech contributor Mageshwaran Subramanian emphasizes how data governance is the key to successful ERP migrations, ensuring data quality, security, and efficiency. Subramanian highlights several critical strategies for a smooth migration, starting with early-stage data validation. Instead of treating data quality as a post-migration task, businesses should begin validation at the extraction phase, preventing costly issues later on. Archiving also plays a major role—clearly separating active data from historical data ensures the new cloud ERP system remains clean and efficient, saving on subscription costs and improving performance. Another essential step is defining the “golden record” for the cloud era. Data silos in legacy systems often lead to duplicate records, which can skew insights and disrupt operations. By using automated de-duplication and creating a unified master record, organizations can avoid these pitfalls and unlock the full potential of their cloud ERP system. Finally, Subramanian explains the link between data governance and AI-readiness. AI technologies depend on accurate, clean data to function effectively. Poor data leads to inaccurate forecasts and unreliable analytics, making a strong governance framework crucial for ensuring the success of AI-driven tools in a new ERP environment. For companies looking to migrate, a disciplined, data-driven approach is essential for long-term success and sustainable growth.

 

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Hybrid ERP Deployments Becoming Standard as Industry Grows

As the ERP (enterprise resource planning) market continues to evolve, hybrid deployments are becoming the go-to solution for businesses seeking flexibility, scalability, and control. In senior editor Chris Vavra’s recent ERP Today article, he explores the growing shift toward hybrid ERP systems and their strategic value for modern enterprises. The global ERP market, valued at $16.3 billion in 2023, is projected to more than double by 2033, with hybrid deployments leading the charge. While on-premise ERP remains crucial for organizations with strict compliance needs, hybrid models allow businesses to mix core workloads with cloud services for analytics, automation, and edge connectivity. For CIOs and enterprise architects, this means moving beyond the “cloud versus on-prem” debate and focusing on managing data governance, security, and process migration across both environments. As cloud ERP solutions gain traction, driven by real-time data access and scalable infrastructure, companies are also seeing increased investment in industry-specific ERP modules. These tailored solutions, combined with AI and predictive analytics, are transforming ERP systems into decision intelligence platforms, offering deeper insights across sectors like manufacturing, healthcare, and retail. With the rise of digital transformation strategies, hybrid ERP models are not just about system upgrades—they’re key to compressing cycle times, stabilizing supply chains, and supporting new digital services. As the market grows, the demand for ERP solutions that drive measurable operational impact will only intensify.

 

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MySQL Formula to Convert Days to Years & Months

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When working with date and time values in MySQL, it’s common to store durations in days. However, sometimes you need to present those days as a more human-readable format—like years and months. For example, showing “2 years, 3 months” instead of “825 days.”

Here’s a simple way to achieve this using a MySQL formula.

Converting Days to Years and Months

Since MySQL doesn’t have a built-in function to directly convert days into years and months, we can use arithmetic with division (/) and modulo (%) operators.

SELECT

FLOOR(days / 365) AS years,

FLOOR((days % 365) / 30) AS months

FROM

your_table;

How It Works

  • FLOOR(days / 365)
    Divides the total days by 365 to get whole years.
  • (days % 365)
    Gets the leftover days after subtracting the full years.
  • FLOOR((days % 365) / 30)
    Divides the leftover days by 30 to approximate months.

Example

Suppose your table looks like this:

CREATE TABLE durations (days INT);

INSERT INTO durations (days) VALUES (400), (825), (1200);

Running the query:

SELECT

days,

FLOOR(days / 365) AS years,

FLOOR((days % 365) / 30) AS months

FROM durations;

Would produce:

days years months
400 1 1
825 2 3
1200 3 3

Notes and Limitations

  • This method assumes 365 days per year and 30 days per month. It’s an approximation, not a precise calendar conversion.
  • If you need exact calendar-aware calculations (e.g., accounting for leap years or exact month lengths), you’ll need to work with MySQL date functions and actual date values instead of raw day counts.

Final Thoughts

Converting days to years and months in MySQL can be done easily with simple math functions. While the above approach works well for approximations, consider whether you need exact date-based calculations before choosing the method.

If you often store durations in days, this formula provides a quick way to present data in a more user-friendly format.

Inside the Global Data Center Investment Surge and Why It Matters for ERP Leaders

The global surge in data center investments is reshaping the way enterprise technology, especially AI and cloud services, will be delivered in the coming years. In a recent ERP Today Article by chief editor Tarsilla Moura, the author explores how massive investments by tech giants like Microsoft, Amazon, Meta, and Alphabet, projected to exceed $630 billion by 2026, are driving this transformation. This investment boom reveals three key trends: the race to support enterprise AI, the growing importance of regional infrastructure, and the limitations of energy resources. For ERP (enterprise resource planning) leaders, this is more than a tech trend—it’s a fundamental shift in the infrastructure that powers business applications. Data centers are becoming larger, more power-demanding, and strategically placed to meet AI needs, with investments spread across the U.S., Europe, and Asia. However, challenges like power grid access, equipment shortages, and regulatory delays are slowing down construction. As a result, companies are focusing on regions with more reliable energy sources. Additionally, financing these projects has shifted from cash reserves to debt markets. For ERP leaders, these shifts will affect service pricing, regional expansion, and the pace of technological advancements, making it essential to understand the evolving infrastructure behind enterprise systems.

 

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Lawson Security – Cannot get Productline List error

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Most Lawson v10 systems has moved to Infor Security Service web portal to manage user provisioning etc.

 

However, Lawson Security Administration is still necessary for security reports, identity information, among other tasks.

 

When logging into Lawson Security Admin, you may receive this error and wonder why all of a sudden?

In order to resolve this, stop and start IBM and Lawson services in the proper order (your server names will differ from below but be similar under Windows Services.

STOP – Lawson and Websphere Services

  1. IBM WebSphere Application Server V8.5 – Infor10Prod-Appserver
  2. IBM WebSphere Application Server V8.5 – lsfappCellManager01
  3. IBM WebSphere Application Server V8.5 – Node Agent-Infor10Prod
  4. insight Environment “Prod”

 

Verify JAVA processes are down.

START – Lawson and Websphere Services

  1. insight Environment “Prod”
  2. IBM WebSphere Application Server V8.5 – Node Agent-Infor10Prod
  3. IBM WebSphere Application Server V8.5 – lsfappCellManager01
  4. IBM WebSphere Application Server V8.5 – Infor10Prod-Appserver

 

How to Modernize Cloud ERP Without Breaking What Already Works

Modernizing cloud ERP without disrupting proven operations is becoming a top priority for manufacturers. In an article by Chris Vavra for ERP Today, the focus is on how companies can evolve their ERP systems strategically—without risking costly downtime or losing valuable process knowledge. Rather than forcing a full cloud replacement, Syspro offers a dual deployment model: manufacturers can choose between on-premises ERP, cloud-based ERP on Microsoft Azure, or a hybrid of both. This approach allows organizations to modernize at their own pace, tailoring deployments plant by plant based on readiness, connectivity, and regulatory requirements. The key advantage is continuity. Businesses can retain existing workflows, data, and customizations while adding cloud benefits like scalability, AI-driven insights, and real-time analytics. This helps avoid the hidden costs of ERP overhauls—such as productivity loss and workflow rebuilding—which often push projects over budget. Operationally, the impact is immediate: planners gain better visibility into demand shifts, finance teams reduce manual workarounds, and IT shifts focus from infrastructure maintenance to integration and security. Vavra emphasizes that successful modernization isn’t just about technology—it’s about managing operational risk. Recommended best practices include upgrading current systems first, piloting cloud deployments in targeted areas, and scaling gradually. Ultimately, hybrid cloud strategies are emerging as the future of ERP, prioritizing flexibility, continuity, and low-risk transformation over disruptive, one-size-fits-all migrations.

 

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