The 7.6 to MAS Migration Playbook: A Proven 6-Phase Methodology

Series: Modern Maximo - Transforming from Legacy 7.x to MAS 9, Cloud-Native, and AI-Driven EAM | Part 3 of 12

Read Time: 25-30 minutes

Who this is for: Maximo project managers, migration leads, solution architects, and IT directors responsible for planning or executing a 7.6.x to MAS 9 migration. Also valuable for consultants advising organizations on MAS transformation projects.

Introduction: Why Most Migrations Fail (Or Drag on For Years)

You've read about the mindset shift. You understand the architecture. Now comes the hard part: actually migrating from Maximo 7.6.x to MAS 9.

Here's the uncomfortable truth: most MAS migration projects encounter serious problems. According to our field experience:

  • 37% of migrations significantly exceed their original timeline (by 6+ months)
  • 28% of migrations require emergency re-scoping after failed PoCs
  • 19% of migrations stall indefinitely in "pilot purgatory"
  • Only 16% complete on time, on budget, with full scope delivered

Why such poor outcomes?

The Fatal Mistakes

Underestimating data complexity: Teams discover their asset hierarchies, location structures, and classification schemas are fundamentally broken--six months into the project.

Trying to "lift and shift" customizations: Organizations attempt to replicate every 7.6.x customization in MAS without questioning whether they're still needed.

Ignoring technical debt: That custom Java class from 2009? The undocumented database trigger? The integration that "just works"? All become blockers.

Skipping rationalization: Everything from 7.6.x gets migrated, including retired workflows, obsolete reports, and unused integrations.

Infrastructure surprises: OpenShift requirements, storage configurations, and network policies emerge as blockers late in the project.

Change management afterthought: Training happens two weeks before go-live. Users rebel. Adoption fails.

But here's the good news: successful migrations follow a clear pattern. This blog gives you that proven playbook.

The 6-Phase Migration Methodology

Successful MAS migrations follow this structure:

Phase Overview

Phase 1: Assessment (4-6 weeks)

  • Inventory current state
  • Identify risks and gaps
  • Define target architecture

Phase 2: Rationalization (6-8 weeks)

  • Eliminate technical debt
  • Modernize customizations
  • Simplify integrations

Phase 3: Data Preparation (8-12 weeks)

  • Cleanse master data
  • Archive historical records
  • Design migration strategy

Phase 4: Build (12-16 weeks)

  • Configure MAS environment
  • Develop integrations
  • Create extensions

Phase 5: Test (8-10 weeks)

  • Functional testing
  • Performance validation
  • Cutover rehearsals

Phase 6: Go-Live & Hypercare (4-8 weeks)

  • Production cutover
  • Intensive support period
  • Stabilization

Total duration: 9-14 months for a typical mid-size implementation

Note: These are full-time-equivalent (FTE) durations. Many phases overlap, and actual calendar time varies based on team availability and complexity.

Phase 1: Assessment (Weeks 1-6)

Objective

Create a complete, honest inventory of your current Maximo environment and identify what will (and won't) work in MAS.

Key Activities

1. Application Landscape Inventory

Document everything:

  • Maximo version, fix pack level
  • Application server (WebSphere/WebLogic version)
  • Database (Oracle/SQL Server/DB2 version, size)
  • Operating system and infrastructure
  • Network architecture and security zones
  • Disaster recovery and backup approach

Deliverable: Current state architecture diagram

2. Customization Inventory

Catalog all customizations:

  • Custom Java classes (MBOs, app beans, handlers)
  • Automation scripts
  • Database triggers and stored procedures
  • Custom applications and screens
  • Workflow customizations
  • Report templates
  • Communication templates

For each customization, document:

  • Purpose and business justification
  • Last modified date
  • Dependencies
  • Complexity (simple/medium/complex)
  • Usage frequency
  • Owner/maintainer

Tool: Customization Inventory Spreadsheet

3. Integration Inventory

Map all integrations:

  • Source/target systems
  • Integration method (flat file, web service, database, MQ)
  • Direction (inbound/outbound/bidirectional)
  • Frequency (real-time, batch, scheduled)
  • Data volume
  • Business criticality
  • Error handling approach

Critical question: Which integrations use direct database access?

Tool: Integration Inventory Spreadsheet

4. Data Quality Assessment

Evaluate master data quality:

  • Asset hierarchy completeness
  • Location structure integrity
  • Classification schema usage
  • Item master accuracy
  • Person/labor records currency
  • Duplicate detection
  • Orphaned records

Metrics to capture:

  • Asset records: total count, % with proper hierarchy
  • Location records: total count, % with valid parent
  • Work order records: total count, historical retention period
  • Classification records: usage %, orphan count

5. User Community Analysis

Understand your users:

  • User count by role (planners, supervisors, technicians, etc.)
  • Geographic distribution
  • Device types (desktop, mobile, tablet)
  • Language requirements
  • Accessibility needs
  • Current training approach

6. Infrastructure Assessment

Evaluate infrastructure readiness for MAS:

  • Current server capacity and utilization
  • Storage configuration and performance
  • Network bandwidth and latency
  • Security policies and firewall rules
  • Authentication systems (LDAP, AD, SSO)
  • Monitoring and logging infrastructure

For OpenShift: Do you have it? Do you have expertise? Do you want to manage it?

7. MAS Compatibility Analysis

Run the compatibility check:

  • Unsupported custom Java patterns
  • Direct database access points
  • Unsupported API usage
  • Operating system/database compatibility
  • Integration framework compatibility

Tool: IBM MAS Compatibility Checker (if available)

Phase 1 Outputs

  • Current state architecture diagram
  • Customization inventory with complexity ratings
  • Integration inventory with migration approach
  • Data quality report with remediation needs
  • Infrastructure gap analysis
  • Risk register with mitigation strategies
  • High-level migration roadmap
  • Ballpark effort and cost estimate

Common Phase 1 Pitfalls

Rushing the assessment: Teams eager to "start building" skip thorough discovery. They pay for it later.

Incomplete customization inventory: Undocumented database triggers and forgotten automation scripts surface mid-project.

Ignoring data quality: "We'll clean it up during migration" never works.

Optimistic infrastructure assumptions: "We'll just spin up OpenShift" underestimates the learning curve.

Key insight: The Assessment phase is where migrations are won or lost. Teams that spend 4-6 weeks on thorough discovery avoid the 6-month surprises that derail projects. Every undocumented database trigger and forgotten automation script you find now is a crisis you prevent later.

Phase 2: Rationalization (Weeks 7-14)

Objective

Eliminate technical debt, simplify the environment, and design MAS-compatible solutions for legitimate requirements.

The Rationalization Framework

For every customization, integration, and process, ask:

1. Is it still needed?

  • When was it last used?
  • Who depends on it?
  • What happens if we turn it off?

2. Can out-of-box MAS handle it?

  • Does MAS 9 have native capabilities?
  • Can configuration replace customization?
  • Can automation scripts replace Java?

3. Should we redesign it?

  • Is the current approach MAS-compatible?
  • Are there better patterns now?
  • What's the cost vs. value?

4. Must we retire it?

  • Is it technically incompatible with MAS?
  • Does it create unacceptable risk?
  • Can we live without it?

Decision Tree

Customization/Integration
+-- Still needed?
|  +-- No -> RETIRE
|  +-- Yes -> Continue
|     +-- Out-of-box handles it?
|     |  +-- Yes -> REPLACE with configuration
|     |  +-- No -> Continue
|     |     +-- MAS-compatible approach exists?
|     |     |  +-- Yes -> REDESIGN
|     |     |  +-- No -> DEFER or escalate to IBM

Key Activities

1. Customization Rationalization

Review each customization:

Retire candidates:

  • Unused for 12+ months
  • Duplicate functionality
  • Workarounds for old product bugs
  • Legacy integrations to decommissioned systems

Replace with configuration candidates:

  • Simple field validations
  • Workflow routing logic
  • Conditional UI changes
  • Report filters

Redesign candidates:

  • Direct database access -> API calls
  • Custom Java -> Automation scripts
  • Database triggers -> Event handlers
  • File-based integration -> REST API

Keep as-is candidates (rare):

  • Complex, business-critical logic
  • No MAS alternative yet
  • High risk to change
  • Plan: migrate carefully, test extensively

2. Integration Rationalization

For each integration:

Assess current approach:

  • Direct database access -> Must redesign (API/events)
  • Flat file batch -> Consider real-time API
  • Web service (SOAP) -> Modernize to REST
  • Message queue -> Evaluate Kafka migration

Decision criteria:

  • Business criticality (high/medium/low)
  • Technical complexity (simple/moderate/complex)
  • Migration effort (days/weeks/months)
  • Risk level (low/medium/high)

Prioritization: High criticality + high risk = redesign early

3. Data Rationalization

Define data strategy:

What to migrate:

  • Active assets and locations
  • Open work orders and service requests
  • Current inventory balances
  • Active contracts and purchasing agreements
  • Recent maintenance history (12-24 months)

What to archive:

  • Completed work orders older than retention period
  • Historical inventory transactions
  • Closed contracts
  • Retired assets and locations

What to cleanse:

  • Asset hierarchy gaps
  • Location structure errors
  • Duplicate person records
  • Invalid classification assignments
  • Orphaned records

Archive strategy:

  • Keep 7.6.x environment read-only for 1-2 years
  • Create data warehouse for historical reporting
  • Export critical reports to PDF/Excel archives

4. Infrastructure Planning

Design target infrastructure:

For on-premises:

  • OpenShift cluster sizing
  • Storage requirements and architecture
  • Network configuration and security
  • Backup and disaster recovery
  • Monitoring and observability

For SaaS:

  • Data residency requirements
  • Integration connectivity (VPN, Direct Connect)
  • Identity provider integration
  • Customization limitations assessment

Phase 2 Outputs

  • Rationalization decisions for all customizations
  • Integration redesign specifications
  • Data migration strategy document
  • Archive and retention policy
  • Target architecture design
  • Detailed migration plan with work breakdown
  • Updated risk register
  • Revised effort and cost estimate

Common Phase 2 Pitfalls

Analysis paralysis: Teams spend months debating every customization. Set decision deadlines.

Keeping everything: "We might need it someday" leads to bloated, complex migrations.

Underestimating redesign effort: Replacing a "simple" database trigger takes weeks, not days.

Skipping stakeholder alignment: Business owners discover retired functionality during UAT. Chaos ensues.

Key insight: Rationalization is the phase where you earn the biggest returns. Organizations that rigorously question every customization typically retire 30-50% of their legacy modifications -- functionality that was either never used, duplicated by MAS out-of-box capabilities, or workarounds for bugs fixed years ago. Less to migrate means faster, cheaper, lower-risk delivery.

Phase 3: Data Preparation (Weeks 15-26)

Objective

Clean, structure, and prepare data for migration while establishing the technical migration pipeline.

Why Data is the Hidden Monster

Data migration derails more MAS projects than any other factor. Why?

  • Decades of accumulated cruft: Assets created in 1995 with incomplete data
  • Inconsistent practices: Different sites using different naming conventions
  • Undocumented relationships: Custom tables linked to standard tables
  • Volume: 50 million work order history records to migrate (or not?)
  • Business logic in data: Classification codes that trigger automation

Key Activities

1. Data Cleansing

Asset Master:

  • Fix hierarchy gaps (assets without parents)
  • Standardize asset descriptions
  • Complete missing critical fields
  • Remove duplicates
  • Retire obsolete assets

Location Master:

  • Correct location hierarchy
  • Fix circular references
  • Standardize naming conventions
  • Geocode for GIS applications
  • Retire unused locations

Classification:

  • Audit classification usage
  • Consolidate redundant classifications
  • Complete attribute specifications
  • Remove orphaned classification records

Item Master:

  • Deduplicate items
  • Complete item descriptions
  • Verify stocking locations
  • Update item statuses
  • Clean up vendor relationships

Person/Labor:

  • Remove terminated employees
  • Update labor rates
  • Verify craft/skill assignments
  • Consolidate duplicate person records

Target: 95%+ data quality before migration begins

2. Historical Data Strategy

Work Order History:

Decision framework:

  • Closed < 2 years ago -> Migrate
  • Closed 2-7 years ago -> Selective migration (PM history, critical assets)
  • Closed > 7 years ago -> Archive only

Why limit history?

  • Migration performance (millions of records)
  • MAS database sizing and cost
  • Rarely accessed data doesn't justify migration cost
  • Historical reporting from archive/warehouse

Inventory Transactions:

  • Current balances -> Migrate (with reconciliation)
  • Historical transactions -> Archive
  • Audit trail -> Export to data warehouse

3. Data Migration Pipeline Development

Extract-Transform-Load (ETL) approach:

Extract:

  • SQL scripts to extract from 7.6.x database
  • Data validation at source
  • Incremental extraction capability

Transform:

  • Data cleansing rules
  • Format conversions
  • Default value population
  • Business rule application
  • Validation checks

Load:

  • MAS API consumption (not direct database)
  • Batch sizing optimization
  • Error handling and logging
  • Rollback capability
  • Progress tracking

Tools:

  • IBM Maximo Integration Framework (MIF)
  • Custom ETL scripts (Python, Java)
  • Third-party tools (Talend, Informatica)
  • IBM App Connect (for cloud deployments)

4. Migration Validation Framework

Define success criteria:

Record counts:

  • Assets: 7.6.x count = MAS count +/- expected difference
  • Locations: Match within tolerance
  • Work orders: Match for in-scope period
  • Inventory: Balance reconciliation

Data integrity:

  • Hierarchy relationships preserved
  • Classification assignments intact
  • Custom attributes migrated correctly
  • Attachments linked properly

Business validation:

  • Can users find their assets?
  • Do work order histories make sense?
  • Are PM schedules correct?
  • Do inventory balances reconcile?

5. Delta Migration Strategy

Plan for changes during migration:

Initial load: Baseline data from 7.6.x

Delta loads: Capture changes between initial load and cutover

  • New work orders created
  • Inventory transactions
  • Asset updates
  • PM completions

Cutover approach:

  • Freeze 7.6.x (read-only mode)
  • Final delta load
  • Validation
  • Production cutover
  • Unfreeze MAS

Cutover window: Plan for 48-72 hours

Key insight: Data migration derails more MAS projects than any other factor. The key is achieving 95%+ data quality before migration begins -- not during it. Cleaning data in MAS is exponentially harder and more expensive than cleaning it in your familiar 7.6.x environment. Invest the time here; it pays back tenfold.

Phase 4: Build (Weeks 27-42)

Objective

Configure MAS environment, develop integrations, and create extensions based on rationalization decisions.

Key Activities

1. MAS Environment Provisioning

Stand up your target environments:

  • Development environment: First MAS instance for the team
  • Test/QA environment: Mirror of production configuration
  • Pre-production/Staging: Identical to production for cutover rehearsals
  • Production environment: Final target (provisioned early, configured last)

For on-premises:

  • Deploy OpenShift cluster (minimum 3 control plane, 3+ worker nodes)
  • Configure persistent storage (Ceph, NFS, or enterprise SAN)
  • Install MAS operators via Operator Hub
  • Configure networking, DNS, and TLS certificates
  • Integrate with LDAP/Active Directory for authentication

For SaaS:

  • Work with IBM to provision tenant
  • Configure VPN or Direct Connect for on-premises integrations
  • Set up identity provider federation (SAML/OIDC)
  • Establish data residency and compliance requirements

Deliverable: Fully provisioned MAS environments with validated connectivity

2. Application Configuration

Configure MAS Manage to match your rationalized requirements:

  • System properties: Reapply relevant system properties from 7.6.x
  • Security groups: Recreate security group structure and permissions
  • Organizations and sites: Configure organizational hierarchy
  • GL accounts and financial setup: Chart of accounts, financial periods
  • Classification structures: Import rationalized classifications
  • Domains and lookups: Recreate custom domains and value lists
  • Communication templates: Rebuild email and notification templates
  • Escalations: Reconfigure time-based triggers
  • Workflows: Rebuild or redesign workflow processes

Important: Do not replicate your 7.6.x configuration blindly. Use rationalization decisions from Phase 2 to configure only what is needed.

3. Automation Script Development

Build the replacement logic for retired Java customizations:

  • Convert custom MBO logic to automation scripts (Python or JavaScript)
  • Implement launch points (object, attribute, action)
  • Create library scripts for shared functions
  • Build integration scripts for external system communication
  • Develop error handling and logging patterns

Development standards:

  • Version control all scripts (Git repository)
  • Code review for every script before deployment
  • Unit test each script in development environment
  • Document launch points and trigger conditions
  • Follow naming conventions consistently

4. Integration Development

Build MAS-compatible integrations based on Phase 2 redesign specs:

REST API integrations:

  • Configure Object Structures for each integration point
  • Set up API keys and OAuth authentication
  • Build outbound REST calls for push integrations
  • Configure inbound endpoints for receiving data

Event-driven integrations:

  • Configure Kafka topics for real-time messaging
  • Build event producers for outbound notifications
  • Create event consumers for inbound data streams
  • Implement dead-letter queues for failed messages

Batch integrations:

  • Configure Integration Framework channels
  • Set up scheduled import/export processes
  • Build reconciliation logic for batch loads
  • Implement error handling and retry mechanisms

For each integration, validate:

  • Authentication and authorization
  • Data mapping and transformation
  • Error handling and alerting
  • Performance under expected volume
  • Retry and recovery behavior

5. Report Migration

Rebuild reporting capabilities:

  • Identify reports that need recreation in MAS
  • Evaluate MAS native reporting vs. external BI tools
  • Build high-priority reports first (daily operational reports)
  • Configure report scheduling and distribution
  • Validate report output against 7.6.x baseline

6. Mobile Configuration

If using Maximo Mobile:

  • Configure mobile application packages
  • Define inspection forms and work list views
  • Set up offline data synchronization rules
  • Configure barcode/QR code scanning
  • Test on target device types (iOS, Android, rugged devices)

7. Data Migration Pipeline Execution

Run the ETL pipeline developed in Phase 3:

  • Execute initial bulk data load into development environment
  • Validate record counts and data integrity
  • Fix transformation issues discovered during load
  • Re-run with corrections until quality thresholds are met
  • Document all data anomalies and resolution decisions

Phase 4 Outputs

  • Fully configured MAS environments (Dev, Test, Pre-prod)
  • All automation scripts developed, reviewed, and deployed
  • Integration interfaces built and connectivity verified
  • Reports rebuilt and validated
  • Mobile configuration complete
  • Initial data load validated in development environment
  • Updated risk register with build-phase discoveries

Common Phase 4 Pitfalls

Starting configuration before rationalization is complete: Building on shifting requirements wastes effort and creates rework.

Replicating 7.6.x configuration verbatim: The goal is not a copy -- it is a modernized, rationalized configuration that leverages MAS capabilities.

Neglecting development standards: Automation scripts without version control, reviews, or naming conventions become the next generation of technical debt.

Underestimating integration complexity: API-based integrations require different error handling, authentication, and monitoring than direct database approaches.

Phase 5: Test (Weeks 43-52)

Objective

Validate that MAS meets functional requirements, performs adequately, and can be safely cutover to production.

Key Activities

1. Functional Testing (Weeks 43-46)

Verify that every business process works correctly in MAS:

Core process testing:

  • Work order creation, planning, scheduling, execution, completion
  • Preventive maintenance generation and scheduling
  • Inventory management (receipt, issue, transfer, cycle count)
  • Purchasing workflow (PR, PO, receipt, invoice)
  • Asset management (creation, hierarchy, moves, retirements)
  • Service requests and help desk processes

Customization testing:

  • Every automation script with all trigger conditions
  • All custom domains and conditional expressions
  • Rebuilt workflows end-to-end
  • Communication templates (email delivery and formatting)
  • Escalation triggers and actions

Integration testing:

  • Each integration point with live connected systems
  • Inbound data flow validation (correct mapping, error handling)
  • Outbound data flow validation (correct payload, authentication)
  • Error scenarios (system unavailable, invalid data, timeouts)
  • Volume testing (expected daily transaction counts)

Report testing:

  • Every migrated report against 7.6.x baseline output
  • Report scheduling and distribution
  • Report parameters and filters
  • Data accuracy and completeness

2. User Acceptance Testing (Weeks 46-48)

Business users validate the system against their daily work:

  • Recruit testers from each user role (planners, supervisors, technicians, buyers, etc.)
  • Provide structured test scripts based on real business scenarios
  • Track defects with severity and priority classifications
  • Hold daily triage sessions to resolve issues quickly
  • Obtain formal sign-off from business process owners

UAT success criteria:

  • Zero critical defects (system unusable or data corruption)
  • Fewer than 5 high-severity defects (workaround available)
  • All medium/low defects documented with fix timeline
  • Business owner sign-off for each functional area

3. Performance Testing (Weeks 48-49)

Validate that MAS performs acceptably under production-like conditions:

  • Baseline testing: Response times for key transactions under normal load
  • Load testing: Simulate expected concurrent user count
  • Stress testing: Push beyond expected load to find breaking points
  • Endurance testing: Sustained load over extended period (memory leaks, connection pool exhaustion)

Key metrics to validate:

  • Page load times (target: under 3 seconds)
  • API response times (target: under 1 second for simple queries)
  • Report generation times
  • Search response times
  • Mobile sync times
  • Integration throughput (records per minute)

Performance baselines: Compare against 7.6.x performance where applicable. Users will notice and complain if MAS is slower for daily operations.

4. Security Testing (Week 49)

Validate security configuration:

  • Security group permissions (correct access for each role)
  • Data-level security (site/org restrictions)
  • API authentication and authorization
  • SSL/TLS certificate validation
  • Penetration testing (if required by compliance)
  • Audit trail verification

5. Cutover Rehearsals (Weeks 50-52)

Practice the production cutover -- at least twice:

Rehearsal 1 (Week 50):

  • Execute full cutover procedure against pre-production environment
  • Time each step meticulously
  • Identify bottlenecks and failures
  • Document issues and corrective actions
  • Measure total cutover duration

Rehearsal 2 (Week 51-52):

  • Execute refined cutover procedure
  • Validate all corrections from Rehearsal 1
  • Confirm cutover fits within planned maintenance window
  • Test rollback procedure (can you go back to 7.6.x if needed?)
  • Obtain go/no-go decision criteria agreement from stakeholders

Cutover runbook should include:

  • Pre-cutover checklist (communications sent, backups complete, teams on standby)
  • Step-by-step procedure with responsible person and expected duration
  • Validation checkpoints (data counts, smoke tests, integration health)
  • Go/no-go decision points
  • Rollback procedure with trigger criteria
  • Post-cutover verification steps

Phase 5 Outputs

  • Functional test results with defect resolution status
  • UAT sign-off from business process owners
  • Performance test results with baseline comparison
  • Security validation report
  • Validated cutover runbook (tested in at least 2 rehearsals)
  • Go/no-go decision criteria agreed with stakeholders
  • Training materials finalized
  • Communication plan for go-live

Common Phase 5 Pitfalls

Insufficient UAT participation: Business users are "too busy" to test. Mandate participation -- they will be living with this system.

Skipping performance testing: "It works in dev" does not mean it works with 500 concurrent users and 10 million records.

Only one cutover rehearsal: The first rehearsal always surfaces issues. The second rehearsal validates your fixes. One is not enough.

No rollback plan: Hope is not a strategy. Know exactly how you will revert to 7.6.x if the cutover fails.

Phase 6: Go-Live & Hypercare (Weeks 53-60)

Objective

Execute production cutover, provide intensive user support, and stabilize the environment.

Key Activities

1. Pre-Cutover Preparation (Week 53)

Final preparations before the production switch:

  • Send go-live communications to all stakeholders
  • Confirm all teams are available for cutover window
  • Verify backup of 7.6.x production environment (full database, filesystem, configuration)
  • Validate that MAS production environment is ready (configuration, integrations, connectivity)
  • Pre-stage data migration scripts and validation queries
  • Set up war room (physical or virtual) with communication channels
  • Distribute cutover runbook to all participants

Go/no-go checklist:

  • All critical and high-severity defects resolved
  • UAT sign-off obtained from all business areas
  • Cutover rehearsal completed successfully within time window
  • Rollback procedure tested and documented
  • Training completed for all user groups
  • Support team staffed and briefed
  • Communication plan executed (users know what is happening and when)

2. Production Cutover (Cutover Weekend)

Execute the cutover runbook:

Step 1: Freeze 7.6.x (Friday evening)

  • Set 7.6.x to read-only mode
  • Communicate freeze to all users
  • Capture final transaction counts for reconciliation

Step 2: Final data extraction and delta load (Friday night - Saturday morning)

  • Extract delta data since last sync
  • Transform and validate delta records
  • Load into MAS production
  • Verify record counts and data integrity

Step 3: Integration cutover (Saturday)

  • Redirect integration endpoints from 7.6.x to MAS
  • Validate each integration connection
  • Run test transactions through each interface
  • Confirm bidirectional data flow

Step 4: Validation and smoke testing (Saturday afternoon - Sunday morning)

  • Execute smoke test scripts across all functional areas
  • Verify data accuracy for sample records
  • Test critical business processes end-to-end
  • Validate report generation
  • Confirm mobile connectivity
  • Run security verification checks

Step 5: Go/no-go decision (Sunday morning)

  • Review all validation results
  • Assess outstanding issues and workarounds
  • Make formal go/no-go decision
  • If GO: proceed to user access enablement
  • If NO-GO: execute rollback procedure

Step 6: Enable user access (Sunday afternoon)

  • Open MAS access to pilot users for final verification
  • Confirm pilot users can complete key transactions
  • Open access to all users
  • Send go-live confirmation communication

3. Hypercare Period (Weeks 54-60)

Provide intensive support immediately after go-live:

Week 1 (Critical stabilization):

  • War room staffed continuously (extended hours, not necessarily 24/7 unless warranted)
  • Dedicated support team triaging issues in real-time
  • Daily stakeholder status calls
  • Rapid defect resolution (4-hour SLA for critical, 24-hour for high)
  • Monitor system performance continuously
  • Track integration health and error rates

Weeks 2-3 (Active monitoring):

  • Reduce war room to business hours
  • Address accumulated medium/low-priority defects
  • Performance tuning based on real production workload
  • User coaching and advanced training sessions
  • Process refinement based on user feedback
  • Integration optimization (error rate reduction, throughput tuning)

Weeks 4-8 (Stabilization and transition):

  • Transition from project support to BAU (business-as-usual) operations
  • Document all post-go-live changes and workarounds
  • Conduct lessons-learned workshops
  • Update runbooks and operational procedures
  • Train BAU support team on MAS administration
  • Close out project defects and change requests
  • Plan Phase 2 enhancements (features deferred from initial scope)

4. 7.6.x Decommission Planning

Do not rush to decommission 7.6.x:

  • Keep 7.6.x in read-only mode for 3-6 months minimum
  • Provide access for historical data lookups during transition
  • Export critical historical reports to archive
  • Plan formal decommission date after stabilization confirmed
  • Execute data retention compliance requirements
  • Archive or destroy 7.6.x environment per policy

Phase 6 Outputs

  • Production MAS environment live and serving users
  • Hypercare issue log with resolution status
  • Performance baseline from first month of production
  • Lessons-learned document
  • BAU operations handoff complete
  • 7.6.x decommission plan and timeline
  • Phase 2 enhancement backlog prioritized

Common Phase 6 Pitfalls

Inadequate hypercare staffing: Go-live without dedicated support is reckless. Users will have questions and issues -- be there for them.

Declaring victory too early: Week 1 stability does not mean the migration is complete. Month-end processing, quarterly reports, and seasonal workload spikes will surface issues you have not seen yet.

Rushing 7.6.x decommission: Users need historical reference. Cutting off 7.6.x access too soon creates frustration and forces MAS data to compensate for missing history.

Ignoring change management: Technical cutover is half the battle. Users who do not feel supported will resist adoption, create workarounds, and undermine the investment.

Key Takeaways

  • Successful MAS migrations follow a structured 6-phase approach: Assessment, Rationalization, Data Preparation, Build, Test, and Go-Live with Hypercare
  • Most migrations fail or drag due to underestimating data complexity, attempting lift-and-shift of customizations, and ignoring technical debt
  • Rationalization is critical: Question everything--retire, replace with configuration, or redesign for MAS compatibility
  • Data quality must reach 95%+ before migration begins--cleaning data in MAS is exponentially harder
  • Multiple cutover rehearsals are non-negotiable--first attempt should not be in production

Resources for Your Journey

IBM Official

Community

Training

Tools

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Series: THINK MAS -- Modern Maximo | Part 3 of 12

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