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IFS Cloud ERP consulting partner for rollouts, supply chain, and data governance. Uses tested methods to cut risk and speed implementation
Discover the top 3 risks causing IFS Cloud implementation failures

Why IFS Cloud Implementations Fail and How to Ensure Success

Discover the top reasons IFS Cloud implementations fail and learn expert strategies to avoid costly mistakes. Get actionable advice on selecting the right consultant, planning for data migration, and ensuring post-launch success with tailored training and support.


The Three Biggest Risks in IFS Cloud Implementations

Many companies blame the software when their IFS Cloud implementation fails. However, the real issue is often poor advice and inadequate planning.

Dirty Data & No Rollback

Poor data quality can cost businesses $10,000+ per day. Without a pre-migration audit and a zero-downtime cutover plan, you risk operation disruptions.

Generic Training

Generic programs fail to address role-specific needs. Role-based workflows and tailored simulations can reduce training time by 40% and boost adoption.

Insufficient Support

50% of issues arise after go-live. Without 90-day hypercare support, costs increase and user frustration mounts. Long-term success requires immediate post-launch aid.

How to Choose the Right Consultant

Selecting the right partner is key to avoiding pitfalls. A qualified consultant delivers faster ROI, minimizes hand-off risks, and provides global expertise tailored to your business.

Discuss Your Project 
  • Industry-Specific Experience
    Ensure they know your sector (e.g., aerospace, field service). Requirements vary significantly.
  • Technical Knowledge
    Deep expertise in IFS Cloud integrations and agile project management is non-negotiable.
  • Transparent Contracts
    Avoid fixed-price contracts that hide scope gaps. Demand clear milestones and deliverables.

Guide to a Successful Implementation

Step 1

Pre-Migration Audit

Audit legacy systems and data. Create a zero-downtime cutover plan to prevent migration disruptions.

Step 2

Role-Based Training

Replace generic sessions with specific workflows. Reduce the learning curve and improve system adoption.

Step 3

90-Day Hypercare

Secure post-launch support for troubleshooting and optimization to address issues immediately.

Step 4

Expert Consultant

Verify track records with case studies. Ensure they have proven experience in IFS Cloud and integrations.

Watch Out for Red Flags

To further ensure success, be aware of the key warning signs when selecting a partner. Learn more in our guide on Red Flags in IFS Cloud Consulting.

Frequently Asked Questions

The three biggest risks are dirty data (lack of rollback plan), generic training that wastes time, and insufficient post-launch support. These issues can lead to significant downtime and cost.

A pre-migration audit identifies data quality issues and legacy system dependencies early. Addressing these beforehand allows for a zero-downtime cutover, potentially saving $10,000+ per day.

Role-based training focuses on specific workflows for each user type. This targeted approach reduces training time by roughly 40% and ensures users are prepared for their actual daily tasks.

Hypercare is intensive, post-launch assistance (usually 90 days) designed to address initial issues, troubleshoot performance, and provide user support to ensure a smooth transition.

Need a Roadmap for Your IFS Cloud Journey?

Contact us to discuss how we can help you avoid common pitfalls and achieve a seamless implementation.

Contact Us Today
IFS Cloud Implementation at Risk? 7 Critical Red Flags That Signal Project Failure

Red flags

Red Flags in IFS Cloud Implementations

A Comprehensive Guide to Identifying and Mitigating Project Risks Before They Derail Your Digital Transformation.

TL;DR: Summary of Critical Warnings

  • Customization Overload: High CRIM object counts are a death sentence for the Evergreen update model.
  • Generic Training: One-size-fits-all training leads to a 60% drop in user adoption.
  • Data Quality: Migrating "dirty" legacy data without a pre-audit guarantees post-launch failure.
  • Siloed Governance: Lack of cross-domain data ownership (Data Mesh) leads to integration bottlenecks.
  • Fixed-Price Traps: Partners offering fixed prices without detailed scope workshops are hiding future change orders.
What Problem Does This Article Solve?

This article provides a "Risk Radar" for CIOs, Project Managers, and Steering Committees. It enables stakeholders to identify subtle technical and organizational "Red Flags" that often go unnoticed during the sales and design phases, ultimately preventing budget overruns, timeline slippage, and operational disruptions during the transition to IFS Cloud.

I. Methodology Red Flags: The "Process vs. Tool" Trap

The most common reason IFS Cloud implementations fail is treating the project as a software installation rather than a business transformation. In the Initiate and Confirm phases of the IFS Implementation Methodology, specific red flags often emerge within the project team structure.

Red Flag: The "Lift and Shift" Mentality

When stakeholders demand that IFS Cloud "works exactly like our old legacy system," you have entered a dangerous territory. IFS Cloud is designed for modern, agile processes. Forcing it to replicate inefficient legacy workflows leads to excessive CRIM (Customization, Report, Integration, Modification) objects, which will break during the mandatory 6-month Evergreen update cycles.

Mitigation: Implement a "Standard-First" policy. Every customization must be justified by a clear ROI and signed off by a central governance board.
Red Flag: Absentee Executive Sponsorship

If the Steering Committee only meets once a month or if the executive sponsor is not actively involved in the Establish phase, the project loses its "political" weight. When difficult decisions regarding process changes arise, the lack of senior leadership results in "decision paralysis," stalling the timeline.

II. Technical & Architecture Warnings

The shift to IFS Cloud (OData, REST-API, Aurena) requires a different technical mindset than legacy IFS Applications 9 or 10.

The "Customization Debt" Red Flag

In IFS Cloud, the "Evergreen" model means you get updates every 6 months. If your partner is building heavy PL/SQL customizations without using Custom Events, Projection Configs, or Page Configurations, they are creating technical debt. Every major customization increases the risk that an update will fail, leading to significant maintenance costs.

The "Data Swamp" Migration

Is your migration plan simply "moving all historical data"? This is a major red flag. ERP systems thrive on lean, clean data. Migrating 20 years of inconsistent records without a Pre-Migration Audit will pollute your new IFS Cloud instance, causing errors in MRP, Financial Reporting, and Warehouse Management.

Legacy Integration Middleware

IFS Cloud is "API-First" via OData. If your implementation team insists on using outdated SQL-level integrations or old-school BizTalk patterns instead of the IFS Integration Platform or modern iPaaS (like Azure Integration Services), they are building a fragile architecture that will not scale.

Ignoring Data Mesh Governance

Modern implementations require Federated Data Ownership. If the project team assumes that "IT will own the data," the project will hit a wall during UAT (User Acceptance Testing) when business domains realize they have no control over the quality of their data products.

III. Consulting & Partner Selection Red Flags

Your implementation partner is the single most important factor in your success. However, many organizations fall for "Sales Cycle" promises that don't translate to "Delivery Phase" reality.

Red Flag Impact on Your Project The "Reality Check" Question
Fixed-Price with Vague Scope The partner will likely use "Change Orders" for every minor detail missed, leading to 20-40% budget inflation. "Can you show us a detailed CRIM list and a mapping of our business processes to standard IFS modules today?"
"B-Team" Swap The senior consultants who won the deal disappear after the contract is signed, replaced by junior staff learning on your dime. "Who exactly will be our lead functional consultant for SCM and Finance? Can we see their CVs and references?"
Lack of Industry Depth A generalist ERP consultant won't understand the nuances of Aerospace, Defense, or complex Manufacturing, leading to poorly mapped processes. "How many IFS Cloud implementations have you completed specifically in our sector?"
Generic Training Plans Standard manuals are provided instead of role-based training. Users won't know how to perform their specific daily tasks. "Will the training be conducted on our own prototype data using role-based workflows?"

IV. The "Dirty Data" Avalanche

Poor data management is the silent killer of ERP value. During the Establish and Implement phases, if you see the following signs, your project is in trouble:

  • No dedicated Data Migration Manager in the project org chart.
  • Postponing data cleansing until "just before Go-Live."
  • Lack of a Zero-Downtime Cutover Plan.
  • No validation of "In-Flight" data (open orders, inventory in transit).

Failure to address data quality early can lead to daily losses exceeding $10,000+ in operational efficiency once the system goes live, as staff scramble to fix master data issues while trying to fulfill customer orders.

Danger Zone

If your partner says "Don't worry about data quality yet, we'll fix it in the Cloud," you should immediately review your contract.

V. The Organizational & Cultural Red Flags

An ERP system is only as good as the people using it. Many companies overlook the psychological impact of moving to a modern, browser-based interface like Aurena in IFS Cloud.

Power User Resistance

If your "Subject Matter Experts" (SMEs) are too busy with their daily jobs to attend workshops, you will end up with a system that doesn't meet operational needs. This is a primary red flag for the Confirm Prototype phase.

Training as a "Checkbox"

Treating training as a one-time event at the end of the project is a recipe for disaster. Role-based simulations and continuous learning (Hypercare) are required for a successful transition.

Missing KPIs

If you cannot define how you will measure success (e.g., "Reduce invoice processing time by 30%"), you cannot verify if the implementation was actually successful. Moving to the cloud for "technology's sake" is a strategic red flag.

Frequently Asked Questions

A partner that claims they can do a "fixed-price implementation" without first conducting a detailed Scope Discovery Workshop. Without understanding your unique CRIM (Customization) requirements and data landscape, any fixed price is just a starting point for future change orders.

While there is no magic number, a project where more than 15-20% of requirements are met through core-code modifications (CRIMs) is at high risk. Modern IFS Cloud implementations should focus on Configurations (Custom Fields, Custom Pages, Events) rather than modifications to ensure Evergreen compatibility.

Research shows that 50% of ERP issues arise within the first 90 days after Go-Live. Without a dedicated "Hypercare" period where consultants are on-site or readily available for troubleshooting, user frustration can lead to shadow IT (users going back to Excel).

Yes. In manufacturing and SCM, poor data quality leads to incorrect inventory levels, failed MRP runs, and shipping delays. The cost of remediating these errors post-go-live is often 10x higher than fixing them during a pre-migration audit.

Pause and assess. Escalating to the Steering Committee is vital. It is far cheaper to delay a Go-Live by 2 months than to launch a system that fails to support the business. Consider hiring an independent auditor to conduct a Project Health Check.

Don't Ignore the Warning Signs

An IFS Cloud implementation is a marathon, not a sprint. The "Red Flags" listed above are not just technical hurdles—they are indicators of the long-term health of your business operations. By recognizing these signs early in the Initiate and Confirm phases, you can pivot your strategy, secure the right expertise, and ensure that your investment in IFS Cloud delivers the lasting value your organization expects.

Get a Project Health Check Today
An expert analysis of why IFS Cloud implementations fail, covering data migration, scope creep, and the critical need for a 'Book of Rules' and proper governance.

The Brutal Truth About IFS Implementations

  • IFS Cloud
  • UAT
  • Book of Rules

Executive Summary: The Strategy for Success

  • Data Integrity First - Establishing a «Clean Core» strategy where data governance prevents the migration of legacy errors.
  • Business-Led Validation —-Shifting UAT from a technical checkbox to a rigorous business process validation.
  • Standardization Over Customization — Leveraging native IFS Cloud Workflows to reduce technical debt.
  • The «Book of Rules» — Implementing a living governance document for configuration standards and security roles.
  • Role-Based Enablement — Delivering process-centric education, ensuring user adoption and minimizing friction.
  • Realistic Resource Allocation — Dedicating subject matter experts to the project rather than relying on part-time availability.
  • Post-Go-Live Sustainability — Planning for «Hypercare» to manage the productivity dip following the initial launch.

Embarking on an ERP transformation is one of the most significant undertakings for any enterprise. While the marketing brochures promise seamless integration and instant ROI, the reality on the ground is often starkly different. We have seen too many projects struggle, not because the software is incapable, but because the implementation strategy ignores the fundamental laws of ERP gravity. The brutal truth is that success in IFS Cloud requires a radical shift in mindset regarding data, governance, and process adoption.


The Silent Killer Is Dirty Data

The single most common reason for project delays and budget overruns is the state of your legacy data. Many organizations underestimate the complexity of untangling years of duplicate records, obsolete part numbers, and inconsistent supplier information. If you migrate this chaos into your new environment, you are simply moving a mess from one system to another.

A successful strategy demands a rigorous focus on IFS Master Data management. You must establish a Data Domain Map early in the project to identify the owners of every data set. This allows you to define what constitutes a «Golden Record» and ensures that only clean, validated data enters the production environment. Tools like the IFS Data Migration Manager are essential here, but they are only effective when paired with a strong data governance policy.

The «Book of Rules» Is Non-Negotiable

One concept we enforce strictly is the creation of an IFS Book of Rules. This is not just technical documentation. It is a strategic constitution for your ERP environment. Without it, your system will quickly degrade into a patchwork of ad-hoc configurations and inconsistent settings.

Your Book of Rules should explicitly define the following parameters:

  • Naming Conventions — For all custom objects, permission sets, and reports.
  • Modification Policies — Dictates when to use configuration versus customization.
  • Security Standards — Detailing how to grant reports to permission sets in IFS Cloud and manage Segregation of Duties (SoD).
  • Workflow Governance — To control the deployment of IFS Cloud Workflows and automation logic.

Maintaining this document requires a regular Governance Cadence where key stakeholders review system changes and ensure alignment with the original design principles.

Process Adoption vs. Legacy Replication

A frequent trap is the desire to make IFS Cloud look and behave exactly like the legacy system it replaces. This approach neutralizes the value of upgrading. The IFS SCM Pillar and other core modules are designed with modern best practices that streamline operations.

Instead of writing code to force the system into old habits, you should leverage IFS Business Process Automation. The IFS User Interaction Workflow capabilities allow you to guide users through complex tasks without breaking the core upgrade path. For example, rather than building a custom form for approvals, you can configure a workflow that triggers automatically based on specific data conditions. This keeps your system «evergreen» and easier to update.

The Role of the Expert Consultant

Selecting the right partner is critical. An IFS ERP Consultant should not just be a «yes man» who agrees to every customization request. You need a partner who will challenge your assumptions and push back when a request violates best practices.

True expertise means understanding the nuances of the platform. It involves knowing what is a multi-site planned part in IFS Cloud and how to configure IFS Cloud Permission Sets to protect sensitive data while enabling productivity. It also means having the foresight to plan for the «Valley of Death» that occurs post-go-live when user frustration peaks and productivity temporarily dips. A skilled consultant prepares you for this phase with targeted IFS UAT (User Acceptance Testing) scenarios that mimic real-world pressure, not just happy-path data entry.

Building Discoverability by Trust

User adoption hinges on trust. If users cannot find the reports they need or if the data looks wrong, they will revert to spreadsheets. You must ensure that IFS Crystal Reports and other analytics tools are correctly mapped and accessible.

We often see issues where users ask how do you grant reports to permission sets in IFS Cloud because the security model was designed by IT rather than the business. By involving process owners in the design of Permission Sets IFS Cloud, you ensure that access rights align with actual job functions. This transparency builds trust in the system and encourages users to rely on the «single source of truth» rather than their private data silos.

Conclusion

The path to a successful IFS Cloud implementation is paved with difficult decisions. It requires you to prioritize data hygiene, enforce strict governance through an IFS Book of Rules, and embrace standard IFS Workflows over custom code. By acknowledging these brutal truths upfront, you move from a high-risk project to a controlled, strategic transformation that delivers genuine business value.

Frequently Asked Questions

The IFS Book of Rules is a governance document that defines how your organization configures and uses IFS Cloud. It outlines naming conventions, modification policies, permission set structures, and workflow standards to ensure long-term system stability and prevent technical debt.

Implementations typically fail due to poor data quality (dirty data), lack of clear scope definition, and insufficient user engagement. Attempting to replicate legacy processes instead of adopting standard IFS Cloud workflows is another primary cause of failure.

Data migration must be treated as a business transformation project rather than a simple IT task. You should use the IFS Data Migration Manager to validate, cleanse, and map data domains before importing. Establishing a «Golden Record» strategy ensures that only high-quality master data enters the new system.

An expert IFS ERP consultant acts as a guide who challenges your existing processes and aligns them with IFS Cloud best practices. They facilitate the creation of the data domain map, assist in defining governance cadence, and ensure that technical configurations support actual business goals.

IFS Cloud workflows automate repetitive tasks and enforce business logic without requiring complex code customizations. By using the BPA (Business Process Automation) tool, you can streamline user interactions, such as approvals and data validation, ensuring consistency across the organization.
User Acceptance Testing in IFS Cloud Projects

Definition of UAT based of IFS implementation methodology

The «UAT base» in the context of the IFS implementation methodology refers to the formal foundation and criteria used for User Acceptance Testing (UAT) before the solution goes live. In IFS projects, UAT is structured within the broader implementation phases, particularly during the Establish Solution and Implement Solution phases. The UAT base involves the following key elements:

  • Definition: The UAT base is the set of solution scenarios, business processes, test scripts, data sets, and security profiles that have been confirmed and documented as meeting the customer’s requirements during earlier project stages. It acts as the agreed reference against which the customer validates that the delivered solution fulfills the intended business needs.

UAT Basics in IFS Implementation

  • The UAT base includes: 
    • Verified end-to-end business scenarios and processes.
    • Test scripts and acceptance criteria were established and approved in the Solution Acceptance Test (SAT).
    • Real or representative migrated data as used in the SAT environment.
    • Defined user roles and security settings as they will exist in production.
  • UAT is executed by expert users or core users, using SAT test scripts, in a dedicated environment that mimics the final production set-up.

IFS Methodology Context

  • The UAT base is established as part of the SAT at the end of the Establish Solution phase.
  • The results of UAT (Operational Readiness Test in IFS terminology) are used to validate business readiness and provide final approval before go-live.
  • Any deviations, test failures, or required fixes during UAT are fed back for resolution prior to system deployment.

Key Deliverables and Purpose

  • Confirm that the implemented solution aligns with the agreed-upon business requirements.
  • Validate that integrations, customizations, roles, data migration, and process workflows behave as expected.
  • Ensure end users are trained and ready to operate the solution confidently post go-live.

The UAT base represents the official starting point for customer validation activities, ensuring a controlled and traceable acceptance process as required by IFS implementation standards.

Rethinking Test Automation for IFS Cloud: Strategies for Resilient Implementation

Rethinking Test, Automation, and Technical Resilience

Rethinking Test Automation for IFS Cloud: Strategies for Resilient Implementation

Defining Complete Test Coverage

Complete test coverage in IFS Cloud means validating all paths — business processes, data flows, integrations, and modifications — from unit logic to end-user transaction flows. This includes:

  • Unit Testing: Testing each script, configuration, or code module in isolation.
  • Integration Testing: Verifying interactions between modules and across system boundaries, including external APIs.
  • System Testing: Exercising the entire solution with all functions and migrated data for both standard and exception workflows.
  • Regression Testing: Ensuring patches and updates do not break previously certified functions.
  • User Acceptance Testing (UAT): Validating the system against real scenarios, compliance rules, and security requirements.

Without clear boundaries, teams risk missing defects that only appear in complex, multi-step processes or during high-volume usage. Each phase in the IFS Implementation Methodology requires documented entry and exit criteria to declare the system go-live ready.

Automation Tooling and Frameworks

Automation is a cornerstone for regression coverage, especially in IFS Cloud where updates are frequent. Tools like IFS Test Tracker, HP Quality Center, and custom CI/CD frameworks automate test scheduling, execution, and reporting. The chosen toolset must support:

  • Automated functional/​UI scripts for standard IFS workflows.
  • API and integration testing with change detection.
  • Stable handling of customizations and new data fields to catch failures early.

Teams should review automation regularly to avoid brittleness, false positives, and resource-draining maintenance.

Version Control and Customization Management

IFS projects often include custom reports, interface modifications, and business rules. Managing these in source control systems (e.g., Git or Azure DevOps) is critical for:

  • Branching strategies to isolate live, development, and feature/​test environments.
  • Clear merging protocols, automated conflict detection, and rollback points.
  • Preventing version drift and ensuring clean synchronization after IFS Cloud updates.

Thorough documentation is required for all changes to maintain lineage and context.

Rollback and Data Integrity Strategies

A robust cutover plan includes:

  • Regular database exports using tools like IFS Data Migration Tool.
  • Transactional backups for critical modules.
  • Detailed scripts for restoring data, including job schedulers and integration points.
  • Referential integrity checks post-restore to avoid mismatches or broken workflows.

End-to-end testing, including dry-run cutovers, ensures rollback and recovery processes work as intended.

Performance Testing

Performance validation simulates peak and average transaction volumes. Key practices include:

  • Using load test tools like JMeter or LoadRunner to simulate multi-user activity.
  • Defining measurable thresholds for response times, server CPU, concurrency, and memory.
  • Running tests on production-like environments after major changes.

Metrics are logged, compared against historical runs, and reviewed for regressions or capacity planning.

Security and Authorization Tests

Security testing reviews general and role-based security, including:

  • Validating IFS roles and permissions for least privilege.
  • Attempting privilege escalation within the test system.
  • API-level security checks to prevent data exposure.
  • Verifying segregation of duties to prevent approval bypasses.

Penetration testing and code reviews can further strengthen security controls.

Integration with External Systems

IFS solutions often connect to ERPs, payment gateways, or IoT platforms. Integration test plans should:

  • Use stubs, mocks, and sandboxes to simulate third-party systems.
  • Validate expected and unexpected behaviors at interfaces.
  • Log all transactions for audit and troubleshooting.
  • Revalidate integrations after each update.

Failing to test integrations can lead to unexpected workflow breaks after changes.

Nonfunctional Testing

Comprehensive IFS projects embed nonfunctional validation for critical operations, including:

  • Simulating failover, node crashes, and recovery procedures.
  • Practicing disaster recovery scenarios with measured recovery times.
  • Testing high-availability clustering and load balancing.
  • Monitoring service response and log data for resilience benchmarking.

Failover and disaster recovery validations are as important as functional tests, especially for zero-downtime operations.

Conclusion

Test automation in IFS Cloud is not just about catching bugs — it’s about building resilience, ensuring reliability, and preparing for the unexpected. By adopting a systematic approach to testing, organizations can achieve successful implementations and maintain high-performance systems.

Frequently Asked Questions

What is complete test coverage in IFS Cloud?
Complete test coverage means validating all business processes, data flows, integrations, and modifications — from unit testing to end-user transaction flows. It includes unit, integration, system, regression, and user acceptance testing (UAT).
Why is automation important for IFS Cloud testing?
Automation ensures regression coverage, especially with frequent updates. It automates test scheduling, execution, and reporting, reducing false positives and catching issues early.
How should customizations be managed in IFS projects?
Customizations should be managed using source control systems like Git or Azure DevOps, with branching strategies, clear merging protocols, and thorough documentation.
What are the key steps for rollback and data integrity in IFS Cloud?
Key steps include regular database exports, transactional backups, detailed restore scripts, and referential integrity checks. Dry-run cutovers and end-to-end testing are critical.
What does performance testing involve in IFS Cloud?
Performance testing simulates transaction volumes using tools like JMeter or LoadRunner, defining acceptance thresholds and running tests on production-like environments.
How is security testing conducted in IFS Cloud?
Security testing includes validating roles and permissions, attempting privilege escalation, checking API security, and verifying segregation of duties.
What should integration test plans include for IFS Cloud?
Integration test plans should use stubs, mocks, and sandboxes, validate behaviors, log transactions, and revalidate integrations after updates.
Why is nonfunctional testing important for IFS Cloud?
Nonfunctional testing ensures system resilience, availability, and disaster recovery, including failover simulations and high-availability testing.
IFS Cloud Testing Strategy: Technical Frameworks for Continuous Implementation Success

IFS Testing: A Technical Perspective for Implementation Success

  • IFS Cloud
  • IFS implementation
  • Testing
  • Planning

TL;DR: The Executive Summary

Testing is the only insurance policy for your ERP investment.


  • What it is: A multi-layered technical validation of IFS Cloud configuration, CRIMs, and data.
  • Phase 0 to Go-Live: Testing starts during Discovery, not after Build.
  • The Evergreen Factor: Testing must be a continuous cycle due to bi-annual IFS updates.
  • Problem Solved: Eliminates post-go-live «surprises,» data corruption, and operational downtime caused by untested customizations.

What Problem Does This Article Solve?

Many organizations treat ERP testing as a «check-the-box» activity before Go-Live. This leads to the «Iceberg Effect»: hidden defects in customizations (CRIMs), broken integration logic, and security permission gaps that only surface under real-world load. This article provides a structured framework to shift testing «left,» identifying risks in the Prototype phase to save 40% of implementation costs and ensuring your IFS Cloud environment remains stable during its continuous update cycles.

1. Discovery & The Technical Baseline

In the IFS methodology, testing begins long before the first environment is provisioned. During the Discovery & Planning phase, the focus is on creating a Testable Requirement Baseline.

Process Scoping

Using the IFS Scope Tool to define every business sub-process. If it isn’t in the scope, it won’t be in the test plan.

Enterprise Rules

Defining the «Book of Rules» (EBR). These rules become the «Expected Results» in your future test scripts.

Technical Baseline

Analyzing legacy data sources. Testing early data quality prevents «Garbage In, Garbage Out» in later phases.

2. Prototyping: Validating the «Possible»

The Confirm Prototype phase is where technical consultants build a «working model» of your future state. This isn’t just a demo; it’s the first stage of System Integration Testing (SIT).

The Anatomy of a Prototype Test

Unlike standard vanilla testing, an IFS Prototype Test uses Company-Specific Data. We validate:

  • Cross-Departmental Handshakes: Does a Shop Order correctly trigger a Purchase Requisition based on the prototype MRP settings?
  • IFS Projections: For IFS Cloud, we test the OData endpoints (Projections) to ensure the UI and API layers are communicating correctly.
  • Key User Training: Key users act as «First Pass» testers, documenting system navigation hurdles.

3. Building & The «CRIM» Validation

In the Establish Solution phase, customizations (Configurations, Reports, Integrations, Modifications — CRIMs) are fully developed. This is the most technically intensive testing period.

Manual vs. Automated Test Cycles

IFS Cloud implementations now demand a hybrid approach. While process logic often requires manual walkthroughs by SMEs, Regression Testing should be automated using the IFS Automated Testing Tool (ATT).

The CRIM Checklist:
  • Validating Page Configurations via the IFS Page Designer.
  • Testing Business Process Automation (BPA) workflows.
  • Ensuring Custom Events trigger the correct background jobs.

IFS Test Tracker

Centralizing defect management is non-negotiable. Every bug found during CRIM validation must be linked to a requirement ID, a developer, and a re-test cycle.

4. Cutover & Operational Readiness (ORT)

As you approach the Implement Solution phase, testing shifts from «Does it work?» to «Can the business run on it?». This involves Operational Readiness Testing (ORT).

Load & Stress Testing

Will the system freeze on Monday morning when 500 users log in simultaneously to record time? We simulate peak transactional volumes to validate the cloud-pod scaling and database performance.

Data Migration Rehearsal

Not a test of logic, but a test of timing. We run mock cutovers to ensure the «Go-Live Weekend» window is sufficient for the final legacy-to-cloud data sync.

The Evergreen Reality: 23R1, 24R1, 24R2…

In IFS Cloud, testing is never «finished.» The Evergreen model introduces bi-annual updates that change the underlying codebase.

Impact Analysis

Using the Update Analyzer to find conflicts between the new IFS release and your customizations.

Regression Automation

Maintaining a library of automated scripts to ensure core processes (P2P, O2C) don’t break during an update.

Periodic UAT

Engaging business owners every 6 months to validate new feature functionality before it hits production.

Frequently Asked Questions

While IFS tests the «Core» product rigorously, they cannot test your unique Configurations, Custom Fields, and Integrations. An update may change a standard projection that your external BI tool relies on, or a new security logic might block your custom «Shop Floor» page. You own the validation of your specific delta.

Technical Testers focus on the «plumbing»: APIs, data integrity, and script execution. Key Users focus on the «Process»: Does this workflow actually match how we sell to our customers? Key users perform UAT (User Acceptance Testing) to ensure the system is fit for business purpose.

For a standard implementation, we recommend at least three full mock runs. Mock 1 is for technical mapping, Mock 2 is for functional UAT, and Mock 3 is the «Cutover Rehearsal» to time the final Go-Live sequence.

A load test failure usually points to either unoptimized SQL in a CRIM, or a need to adjust the «pod» scaling in the IFS Cloud architecture. Identifying this *before* Go-Live allows the technical team to refactor code or increase resource allocation without impacting live customers.

Don’t Gamble with Your Go-Live

Our experts provide managed testing services, from automated regression scripts to complex SIT orchestration.

Get a Testing Audit
  1. Five Underused IFS Cloud SCM Features That Can Save Your Team
  2. Site Cluster Functionality in IFS Cloud: Setup, Usage, and Business Impact
  3. Building Resilient Supply Chains in IFS Cloud SCM
  4. Multi-Site IFS Cloud Implementation – Key Lessons Learned

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