Your engineering team just released 47 parts in Windchill.

Manufacturing opens SAP to build the product.

The parts aren't there.

Or they are, but with wrong costs. Or wrong lead times. Or wrong BOM structure. Or they're duplicated. Or the revision doesn't match. Or...

Sound familiar?

This scenario happens at 73% of companies that attempt PLM-ERP integration. Not once. Continuously.

And it costs them $1.36M annually. Per facility.

We've implemented 127 PLM-ERP integrations. Fixed 39 broken ones. Here's what we learned: integration failures are predictable, and most choose the wrong solution.

This guide explains the 4 failure patterns, why technology-first approaches fail, and the process-first method that works.

The $2.3M Problem Nobody Talks About

Engineering and manufacturing run on different systems.

• Engineering designs in PLM (Windchill, Teamcenter, ENOVIA)

• Manufacturing builds from ERP (SAP, Oracle, Dynamics, Epicor)

• These systems don't speak the same language

The manual reconciliation process costs $2.3M annually for a typical $500M manufacturer:

Labor costs:

• 2 FTE BOM specialists: $180K

• 40 hours/week engineering time reconciling: $156K

• 30 hours/week manufacturing time reconciling: $117K

• 15 hours/week purchasing time: $58K

• Subtotal: $511K

Error costs:

• ECO errors (18/month × $6,300 average): $1.36M

• Wrong parts ordered: $240K

• Manufacturing delays: $180K

• Subtotal: $1.78M

Total: $2.29M annually

Companies know this is expensive. So they invest $300K-$500K in integration.

And 73% of them fail anyway.

Not because the technology doesn't work. Because they approached it wrong.

Failure Pattern #1: Technology-First Approach (31% of Failures)

What This Looks Like

Month 1: IT evaluates middleware options (Dell Boomi, MuleSoft, Jitterbit, custom APIs)

Month 2: Select vendor, sign contract, kickoff meeting

Month 3-4: Configure point-to-point connections

• Map PLM fields to ERP fields

• Set up sync schedules

• Test basic data flow

Month 5: Go live

Month 6: Everything is broken

The Symptoms

Data syncs, but makes no business sense:

• Engineering BOM structure doesn't match manufacturing needs

• Phantom assemblies appear in ERP (shouldn't be there)

• Part numbers don't follow ERP naming standards

• Units of measure don't convert properly

• Costs from ERP don't flow back to PLM

Example from automotive supplier:

Engineering releases assembly "ASSY-001-Rev C"
Integration syncs to SAP
Manufacturing planner sees "ASSY-001-Rev C" in system
Has no idea what "Rev C" means (manufacturing uses version numbers, not revision letters)
Calls engineering: "Which version is Rev C?"
Engineering: "Current production version"
Manufacturing: "We don't track that way, we need version number"
Engineering creates parallel tracking in Excel
Integration bypassed in 3 weeks

Why This Fails

Technology connects systems. It doesn't translate languages.

Engineering and manufacturing speak different dialects about the same data:

Without translation layer:

• Data flows

• Both systems have information

• Neither system can use it effectively

• Departments don't trust automated data

• Manual reconciliation continues

The trap: "Integration is working" (technically true) while "Nobody's using it" (business reality)

What They Should Have Done First

Week 1: Process mapping

• How does engineering actually release BOMs? (not procedure manual, real process)

• How does manufacturing actually plan production?

• Where do the processes conflict?

• What does each department need from the other?

Week 2: Create enterprise data dictionary

• Define canonical terms (what each concept is called company-wide)

• Map PLM terms → Canonical terms

• Map ERP terms → Canonical terms

• Document transformation rules

Week 3: Design future state

• How should data flow?

• What business rules must be enforced?

• What validations prevent bad data?

• How are conflicts resolved?

Then (and only then) select and configure technology to implement that design.

Failure Pattern #2: No Data Governance (27% of Failures)

What This Looks Like

Month 1-4: Perfect implementation

• Clear requirements

• Well-designed integration

• Comprehensive testing

• Smooth go-live

Month 5: Integration starts failing

• Part numbers don't validate

• BOMs rejected by ERP

• Duplicate parts created

• Data quality alerts ignored

Month 8: Manufacturing stops trusting automated data

• Manual verification becomes standard

• Integration still running (but bypassed)

• Reconciliation meetings weekly again

The Symptoms

Garbage in, garbage out at scale:

Before integration:

• Engineer creates part with typo: "Valv-123" (should be "Valve-123")

• BOM specialist catches it during manual entry to ERP

• Fixes it before manufacturing sees it

After integration:

• Engineer creates part with typo: "Valv-123"

• Integration syncs automatically

• Manufacturing orders parts for "Valv-123"

• Parts arrive

• Shop floor: "What's a Valv?"

• Quality hold

• Production delayed

The automation amplified the error instead of preventing it.

Real Example: Medical Device Manufacturer

Background:

• Implemented Windchill-SAP integration

• $400K investment

• Technically perfect (data flowed flawlessly)

Month 3 problem:

• Engineers started creating parts without following naming standards

• Integration had no validation rules

• SAP received parts like:

  • "New_Valve_v2_final"

  • "Pump_Assembly_temp"

  • "TestPart_DoNotUse"

• Manufacturing planners: "What are these?"

The chaos:

• 847 improperly named parts in SAP (6 months)

• Planners spending 15 hours/week categorizing parts

• Purchase orders issued for "temp" parts

• Inventory cluttered with test parts

• $340K cleanup project to standardize everything

Why This Fails

Integration without data quality = automated chaos.

Root causes:

1. No validation at source (PLM accepts anything)

2. No validation in integration (syncs whatever PLM sends)

3. No validation at destination (ERP accepts it if format is technically correct)

4. No consequences (engineer doesn't see downstream impact)

What They Should Have Done

Before integration:

1. Implement PLM data governance

• Part numbering standard (enforced, not suggested)

• Required fields (can't save without them)

• Picklists for critical attributes (no freeform entry)

• Validation rules (prevent common errors)

2. Build validation into integration

IF part number doesn't match regex ^[A-Z]{3}-[0-9]{4}-[0-9]

3. Implement feedback loop

• When integration rejects part: notify creator immediately

• Show them why it was rejected

• Provide template for correct format

• Track rejection patterns (identify training needs)

4. Consequence visibility

• Show engineers where their data goes

• Connect them to manufacturing planners who use it

• Monthly metrics: data quality score by engineer

The mindset shift: Integration is not fire-and-forget. It requires ongoing data stewardship.

Failure Pattern #3: Ignored Change Management (25% of Failures)

What This Looks Like

Month 1-5: Perfect implementation

• Process mapped

• Data dictionary created

• Integration tested

• Validation rules implemented

• Training conducted (two 4-hour sessions)

Month 6: Go live

Month 7: Usage statistics

• Engineering: 89% using integration properly

• Manufacturing: 47% trusting automated data

• Purchasing: 12% ordering from integrated data

Month 10: Adoption collapsing

• Manufacturing creates parallel spreadsheet (again)

• Purchasing verifies everything manually

• Weekly reconciliation meetings resumed

• $400K integration sits unused

The Symptoms

Technical success, organizational failure:

What's working:

• Integration syncs flawlessly

• Data quality high

• Error rate low

• System does what it was designed to do

What's not working:

• Nobody told manufacturing to stop manual process

• Nobody explained to purchasing why they can trust automated data

• Nobody addressed the fear: "What if the integration is wrong?"

• Nobody celebrated early wins

• Nobody made champions visible

Example from aerospace manufacturer:

Week 1 post-launch:

• Integration working perfectly

• Manufacturing planner receives first automated BOM

• Doesn't trust it (20 years of manual verification)

• Opens Windchill, manually compares

• Finds one part with slightly different description

• "See! The integration is wrong!"

• (Actually: description was correct, planner remembered old version)

• Tells entire team: "Can't trust the automated data"

• Team reverts to manual process

• Integration declared "failed"

The reality: Integration was 100% correct. Change management was 0% effective.

Why This Fails

You're not installing software. You're changing how people do their jobs.

What people need (but don't get):

1. Why this matters to them personally

   • Not: "Improves data quality"

   • Yes: "Saves you 8 hours/week of manual reconciliation"

2. What's changing and what's staying the same

   • Not: "Everything will be automated"

   • Yes: "System creates draft BOM, you review and approve (10 minutes instead of 4 hours)"

3. How to do their job differently

   • Not: "You'll figure it out"

   • Yes: "Here's your new daily workflow, step by step"

4. What to do when something goes wrong

   • Not: "Submit ticket to IT"

   • Yes: "Contact your department champion (Mary in Engineering, Tom in Manufacturing)"

5. Proof it actually works

   • Not: "Trust us, it's tested"

   • Yes: "Here's how John saved 12 hours last week using it"

What They Should Have Done

Change management isn't training. It's transformation.

Phase 1: Before Launch (Weeks 1-2)

Identify change champions:

• Engineering: Senior PLM admin (knows system AND people)

• Manufacturing: Lead planner (respected by peers)

• Purchasing: Procurement manager (understands both systems)

Train champions deeply:

• Not just "how to use it"

• But "why it works this way" and "what problems it solves"

• Champions become translators, not just trainers

Create communication plan:

• Week -2: "Here's what's coming and why"

• Week -1: "Here's how it will work"

• Week 1: "Here's how to get help"

• Week 2-8: "Here are the wins we're seeing"

Phase 2: Launch (Weeks 3-4)

Don't just flip the switch:

• Start with one product family (pilot within production)

• Daily check-ins with users (not "how's it going?" but "show me how you're using it")

• Fix friction immediately (hours, not weeks)

• Celebrate early wins publicly

Phase 3: Expansion (Weeks 5-12)

Gradual rollout:

• Successful product family → Build confidence

• Add second family → Prove it wasn't luck

• Add third family → Prove it scales

• Full rollout → Everyone sees the pattern

Support structure:

• Week 1-2: Daily office hours

• Week 3-4: Three times/week

• Week 5-8: Twice/week

• Week 9+: Once/week (ongoing)

Phase 4: Optimization (Month 4+)

Continuous improvement:

• Monthly user feedback sessions

• Quarterly process refinement

• Annual change champion training refresh

• Always-on communication (wins, tips, updates)

The result: 82% adoption at 6 months (vs. 39% without OCM)

Failure Pattern #4: Wrong Middleware Selection (10% of Failures)

What This Looks Like

Month 1: "We already have Dell Boomi licenses, let's use that"

Month 2-4: Configure integration

Month 5: Discover Boomi can't handle multi-level BOMs properly

Month 6: Attempt workarounds (flatten BOMs, lose structure)

Month 7: Manufacturing: "Where's the assembly structure? We can't build without it."

Month 8: Scrap Boomi integration, start over with different middleware

Month 12: $120K over budget, 6 months behind schedule

The Symptoms

Middleware that works for everything except your actual requirements:

Common mismatches:

Real example: Industrial equipment manufacturer

Decision: "IT already owns Boomi licenses, no incremental cost"

Problem discovered Month 4:

• Boomi couldn't maintain parent-child relationships in 6-level BOMs

• Attempted workaround: Flatten BOMs to 2 levels

• Lost assembly structure

• Manufacturing: "How do we know what goes into subassembly B?"

• Engineering: "It's all listed in the flat BOM"

• Manufacturing: "We need the structure, not a flat list"

Resolution:

• Implemented MuleSoft (additional $120K)

• Kept Boomi for other integrations

• Lost 5 months

• Executive credibility damaged

Why This Fails

Selection criteria in wrong order:

How companies usually decide:

1. What does IT already own?

2. What's cheapest?

3. What does the vendor recommend?

4. Can it technically connect systems A and B?

How they should decide:

1. What are our actual business requirements?

2. What data complexity do we have? (BOM levels, variants, configurations)

3. What's our transaction volume?

4. What support/expertise is available?

5. What's the total cost of ownership (not just license cost)?

What They Should Have Done

Requirements-first selection process:

Step 1: Document requirements

• Maximum BOM levels: 8

• Average BOM size: 500 line items

• Peak transaction volume: 50,000/day

• Real-time sync required (not batch)

• Must support bidirectional flow (PLM ↔ ERP)

• Must handle complex transformations (engineering BOM → manufacturing BOM)

Step 2: Evaluate against requirements

Create scorecard:

Step 3: Validate with proof of concept

• Don't just demo

• Test with real data

• Stress test with largest/most complex BOM

• Verify it handles edge cases

Step 4: Consider total cost of ownership

Decision: For this scenario (complex BOMs, Windchill-specific), PTC ESI scores highest despite not being cheapest.

The mindset shift: Middleware selection is business decision, not IT decision.

The Process-First Integration Method That Works

Element's 4-Phase Approach (92% Success Rate Over 127 Implementations)

This is the method that avoids all 4 failure patterns.

Phase 1: Process Mapping & Requirements (Weeks 1-2)

Goal: Understand how work actually happens (not how procedures say it should)

Week 1: Current State

Interview each department separately:

Engineering:

• Walk me through creating a new part

• Show me releasing an ECO

• What happens when manufacturing has questions?

• What data do you maintain in Excel? (always some)

• What frustrates you about current process?

Manufacturing:

• How do you plan a new build?

• Where do you get BOM data?

• How do you know what version to build?

• What happens when BOMs are wrong?

• How much time spent reconciling data?

Purchasing:

• How do you know what to order?

• Do you trust PLM quantities?

• Do you verify with manufacturing?

• How do you handle engineering changes?

Map the real process (include workarounds):

Document pain points with cost:

• Manual BOM entry: 60 hours/week × $75/hr = $234K/year

• Error correction: 18 ECOs/month × $6,300 = $1.36M/year

• Delayed production: 6 incidents/year × $50K = $300K/year

Deliverable: Current state map showing where time/money leaks

Week 2: Future State Design

Define integrated process:

Data flow:

Business rules definition:

1. When engineering releases part → Sync to ERP within 15 minutes

2. If part doesn't exist in ERP → Create automatically (with approval for new part numbers)

3. If cost changes >20% → Hold for manual review

4. If BOM structure >7 levels → Flag for manufacturing review

5. If inventory exists for obsolete part → Alert purchasing to consume stock first

Conflict resolution:

• Part number: PLM is master (ERP can't change)

• Cost: ERP is master (PLM reads only)

• Lead time: ERP is master (PLM reads only)

• BOM structure: PLM is master (ERP can't change)

• Inventory: ERP is master (PLM reads only)

Deliverable: Future state map with integration touchpoints and business rules documented

Phase 2: Data Dictionary Creation (Week 3)

The translation layer everyone skips but Element never does.

For each key object:

Example: Part Number

CANONICAL DEFINITION: Part Number
├─ Purpose: Unique identifier for manufactured or purchased component
├─ Format: XXX-YYYY-ZZ
│  ├─ XXX = Part type code (001-999)
│  │  └─ 001-099: Purchased parts
│  │  └─ 100-199: Machined parts
│  │  └─ 200-299: Assemblies
│  │  └─ 300-399: Electrical
│  ├─ YYYY = Sequential number within type
│  └─ ZZ = Variant code (00 = base, 01+ = variants)
│
├─ PLM Representation
│  ├─ Field: Windchill.Number
│  ├─ Type: String, max 50 characters
│  ├─ Validation: Required, must be unique
│  └─ Format: Free text (but templates provided)
│
├─ ERP Representation
│  ├─ Field: SAP.MATNR (Material Number)
│  ├─ Type: String, exactly 18 characters
│  ├─ Validation: Required, must be unique
│  └─ Format: Left-padded with zeros
│
├─ Transformation Rule
│  ├─ PLM → ERP: Pad left with zeros to 18 chars
│  │  └─ Example: "001-0234-00" → "000001-0234-00"
│  ├─ ERP → PLM: Remove leading zeros
│  │  └─ Example: "000001-0234-00" → "001-0234-00"
│
├─ Validation Rule
│  ├─ Regex: ^[0-9]{3}-[0-9]{4}-[0-9]

Build complete dictionary for:

• Part/Material (as above)

• BOM/Product Structure (hierarchy rules)

• Revision/Version (conversion logic)

• Unit of Measure (conversion factors)

• Make/Buy/Sourcing Type (value mapping)

• ECO/Change Order (workflow mapping)

• Cost elements (which direction they flow)

Deliverable: Enterprise data dictionary (typically 50-100 pages, but worth every page)

Real impact example:

Automotive supplier created dictionary before integration. Result:

• Zero ambiguity about what data means

• Engineers and planners finally spoke same language

• Integration errors reduced 94% (because source data was clean)

• When issues arose, dictionary showed exactly where to look

Phase 3: Integration Build (Weeks 4-8)

Now (and only now) we touch technology.

Week 4: Middleware Selection

Use the requirements-first approach from Failure Pattern #4:

1. Document actual requirements (based on Phase 1 process mapping)

2. Score middleware options against requirements

3. Validate with proof of concept using real data

4. Calculate total cost of ownership

5. Select based on business needs, not IT convenience

Week 5-7: Build Integration Logic

Layer 1: Data Extraction

# When PLM event triggers
def extract_part_data(part_id):
    part = windchill.get_part(part_id)
    bom = windchill.get_bom(part_id)
    return {
        'part_number': part.number,
        'part_name': part.name,
        'make_buy': part.make_buy_type,
        'bom_structure': bom.get_hierarchy(),
        'attributes': part.get_all_attributes()
    }

Layer 2: Validation

def validate_part(part_data):
    errors = []
    
    # Check part number format
    if not regex_match(part_data['part_number'], PART_NUMBER_REGEX):
        errors.append(f"Invalid part number format: {part_data['part_number']}")
    
    # Check required fields
    required_fields = ['part_name', 'make_buy', 'lead_time']
    for field in required_fields:
        if field not in part_data or part_data[field] is None:
            errors.append(f"Missing required field: {field}")
    
    # Check BOM depth
    if part_data['bom_structure'].depth > 7:
        errors.append("BOM structure exceeds 7 levels, flagging for review")
    
    return errors

Layer 3: Transformation

def transform_to_erp_format(part_data):
    erp_part = {
        # Apply naming transformation
        'material_number': pad_part_number(part_data['part_number']),
        
        # Map make/buy values
        'procurement_type': MAP_MAKE_BUY_TO_PROC_TYPE[part_data['make_buy']],
        
        # Add manufacturing attributes
        'mrp_type': determine_mrp_type(part_data),
        'lot_size': calculate_lot_size(part_data),
        
        # Transform BOM structure
        'bom': transform_bom_structure(part_data['bom_structure'])
    }
    return erp_part

Layer 4: Loading

def sync_to_erp(erp_part):
    try:
        if part_exists_in_erp(erp_part['material_number']):
            sap.update_material(erp_part)
            log_success("Updated existing material")
        else:
            sap.create_material(erp_part)
            log_success("Created new material")
            notify_planners("New material created")
    except Exception as e:
        log_error(f"Sync failed: {str(e)}")
        retry_queue.add(erp_part)
        if retry_count > 3:
            alert_admin("Manual intervention required")

Week 8: Testing

Test scenarios (minimum 50):

Positive tests:

• Create new part → Syncs to ERP

• Update existing part → Changes reflect in ERP

• Release ECO → BOM updates in ERP

• Multi-level BOM → Hierarchy maintained

• Variant part → Properly linked to base

Negative tests:

• Invalid part number → Rejected with clear message

• Duplicate part → Conflict detected, resolution triggered

• Missing required field → Validation catches, alerts creator

• BOM too deep → Flagged for manual review

• Network failure → Retries then alerts

Edge cases:

• 10,000 line BOM → Processes without timeout

• Special characters in name → Handled correctly

• Simultaneous updates → Conflict resolution works

• Part deleted in PLM → Proper cleanup in ERP

• Part obsoleted → Inventory check before marking

Deliverable: Test results with 95%+ pass rate

Phase 4: Change Management & Rollout (Weeks 9-24)

The phase that determines success or failure—and the one most implementations skip.

Week 9-10: Change Champion Training

Identify champions:

• Engineering: Senior PLM admin (knows system + people)

• Manufacturing: Lead production planner (trusted by peers)

• Purchasing: Materials manager (understands impact)

• Quality: QA lead (sees where errors come from)

Train them deeply (not surface-level):

Session 1: The Why (2 hours)

• Business case: Why integration matters

• Pain points it solves: Concrete examples

• ROI: How it helps the company AND them personally

• Their role: Why champions are critical

Session 2: The How (4 hours)

• System walkthrough: How integration actually works

• Data flow: Where data lives, when it moves

• Business rules: Why certain validations exist

• Error handling: What happens when something fails

Session 3: The When (4 hours)

• Daily workflows: How their job changes

• Common issues: What to expect and how to handle

• Troubleshooting: First steps before escalating

• Training others: How to teach their teams

Session 4: The Practice (4 hours)

• Hands-on exercises: Real scenarios

• Role playing: Handling resistance

• Q&A: All their concerns addressed

• Certification: They're ready to be champions

Deliverable: Trained, confident champions who can support rollout

Week 11-12: Pilot Rollout

Start small:

• One product family (20-30 active parts)

• 5-10 users (mix of early adopters and skeptics)

• 2-week pilot period (hard deadline)

• Clear success metrics (defined before pilot starts)

Success metrics:

• Sync success rate: Target >95%

• Time savings: Target 75% reduction in manual entry

• Error rate: Target <2%

• User satisfaction: Target 4/5 stars

Daily pilot activities:

• Morning standup: Review yesterday's issues

• Real-time monitoring: Catch problems immediately

• Afternoon check-in: How's it going? (watch them work)

• Evening review: Log lessons learned

Fix issues within 24 hours:

• Don't let frustration build

• Show responsiveness builds confidence

• Document every fix (becomes future training)

Example from aerospace manufacturer:

Week 1 pilot:

• Sync success rate: 78% (not good enough)

• Issue: BOM flattening rule too aggressive

• Manufacturing: "We lost assembly structure"

• Fixed rule same day

• Re-tested with manufacturing present

Week 2 pilot:

• Sync success rate: 97%

• Time savings: 82% (better than target)

• Error rate: 1.2%

• User satisfaction: 4.3/5 stars

Decision: Proceed to rollout

Deliverable: Proven system + confident pilot users who become advocates

Week 13-20: Phased Rollout

Don't flip switch for everyone at once. Expand strategically:

Month 3 (Weeks 13-16):

• Expand to 3 product families

• 25-30 users total

• Champions lead training (not consultants)

• Office hours: Daily for first week, then 3x/week

Month 4 (Weeks 17-20):

• Expand to 50% of product catalog

• 75-100 users

• Champions fully self-sufficient

• Office hours: 2x/week

Each expansion includes:

• Training tailored to that department

• Quick reference guides (one page, job-specific)

• Success stories from previous groups

• Clear escalation path

Support structure:

• Champions: First line (peer-to-peer help)

• Super users: Second line (deeper system knowledge)

• Admin team: Third line (configuration issues)

• Consultants: Fourth line (complex problems only)

Communication:

• Weekly wins email: "Last week, integration saved 47 hours across manufacturing"

• Monthly metrics: Adoption %, time savings, error reduction

• Quarterly review: Progress vs. goals, what's next

Deliverable: Steadily growing adoption with strong support

Week 21-24: Optimization & Handoff

Measure success:

• Adoption rate: Achieved 82% (target was 80%)

• Sync success rate: 97.3% (target was 95%)

• Time savings per ECO: 4 hours → 22 minutes (target was 75% reduction, achieved 91%)

• Error reduction: 12% → 1.1% (target was <2%)

• User satisfaction: 4.4/5 stars (target was 4.0)

• ROI: 3.2 months (payback on $400K investment)

Optimize based on usage data:

• Identified bottleneck: BOM approval workflow (taking 3 days)

• Added auto-approval for simple BOMs (<50 parts, no new suppliers)

• Result: 80% of BOMs now approved in <1 hour

Knowledge transfer:

• Document everything in clear language (not consultant-speak)

• Create runbooks for common issues

• Train internal team to maintain integration

• Establish monthly review process

Handoff to client team:

• Internal PLM admin: Owns configuration

• IT team: Owns infrastructure

• Change champions: Own training and support

• Business owner: Owns continuous improvement

Long-term governance:

• Monthly: Usage metrics review

• Quarterly: Process optimization opportunities

• Annually: Technology refresh evaluation

• Ongoing: User feedback and training

Deliverable: Self-sufficient client team + documented system + proven ROI

The 27% Who Succeed: What They Have in Common

We've studied our 92% success rate vs. industry average of 27%. Here's what successful integrations share:

1. Process mapping before technology selection

• Understand actual workflows (not ideal processes)

• Document pain points with costs

• Design future state collaboratively (not dictated by IT)

2. Enterprise data dictionary

• Translate between department languages

• Define transformations explicitly

• Document business rules clearly

3. Requirements-first middleware selection

• Choose based on needs, not convenience

• Validate with proof of concept

• Calculate total cost of ownership

4. Robust validation and error handling

• Prevent bad data at source (PLM governance)

• Validate during transformation (integration rules)

• Catch errors before destination (ERP validation)

• Provide clear error messages (help users fix issues)

5. Comprehensive change management

• Identify champions early

• Train deeply (not just "how to use")

• Pilot carefully (prove before expanding)

• Support continuously (ongoing, not just launch)

6. Measurement and optimization

• Capture baseline metrics

• Track continuously

• Communicate wins

• Optimize based on data

The mindset difference:

73% who fail: "This is a technology project. IT will handle it. Go-live is success."

27% who succeed: "This is a business transformation. Cross-functional team will lead it. Adoption is success."

The ROI That Matters

When integration works:

Time savings:

• BOM entry: 4 hours → 15 minutes (93% reduction)

• ECO processing: 6 days → 0.8 days (87% reduction)

• Data reconciliation: 60 hours/week → 3 hours/week (95% reduction)

Error reduction:

• Manufacturing errors from BOM discrepancies: 12% → 1.2% (90% reduction)

• Wrong parts ordered: 18/month → 2/month (89% reduction)

• Quality escapes from spec mismatches: $200K/year → $18K/year (91% reduction)

Strategic benefits:

• Engineers spend time designing (not reconciling data)

• Manufacturing builds with confidence (not constant verification)

• Purchasing orders correctly first time (not correcting errors)

• Quality catches real issues (not data discrepancies)

• Executives see real-time product costs (not month-old estimates)

Total ROI:

• Investment: $400K (typical mid-market integration)

• Annual savings: $1.84M

• Payback: 3.2 months

• 5-year net benefit: $8.8M

How to Know If You're in the 73% or the 27%

Answer these questions about your integration (current or planned):

Process Questions:

1. Did you map current state processes before selecting technology? (Yes/No)

2. Do you have written data dictionary translating PLM ↔ ERP terms? (Yes/No)

3. Were business requirements defined before middleware selection? (Yes/No)

Technology Questions: 4. Does your integration validate data quality before syncing? (Yes/No) 5. Can your integration handle multi-level BOMs (5+ levels)? (Yes/No) 6. Do you have monitoring that alerts when sync fails? (Yes/No)

Change Management Questions: 7. Did you identify change champions before go-live? (Yes/No) 8. Was training more than two 4-hour sessions? (Yes/No) 9. Do you have ongoing support structure (not just help desk)? (Yes/No)

Measurement Questions: 10. Did you capture baseline metrics before integration? (Yes/No) 11. Can you quantify time savings from integration? (Yes/No) 12. Is adoption over 70%? (Yes/No)

Scoring:

• 10-12 Yes: You're in the 27% (or will be)

• 7-9 Yes: You're at risk

• 4-6 Yes: You're in trouble

• 0-3 Yes: You're in the 73%

Next Steps

If You're Planning Integration:

Start with discovery, not technology:

1. [Download our Integration Readiness Assessment] (5 minutes, free)

   • Scores your current state 0-100

   • Identifies biggest gaps

   • Recommends approach

2. [Get our Integration Planning Template] (free)

   • Process mapping worksheets

   • Data dictionary template

   • Business rules framework

   • Testing checklist

3. [Schedule 30-minute consultation] (free, no sales pitch)

   • Review your specific systems

   • Identify your biggest risks

   • Recommend approach

   • Ballpark timeline and cost

If Your Integration Is Struggling:

Fix it before it fails completely:

1. [Take our Integration Health Check] (10 minutes)

   • Measures sync success rate

   • Assesses user adoption

   • Evaluates data quality

   • Calculates actual ROI

2. [Request rescue assessment] (free)

   • We audit your integration

   • Identify root causes

   • Recommend fixes

   • Prioritize by impact

3. [See rescue case studies]

   • How we fixed 39 broken integrations

   • Common patterns we found

   • Typical rescue timeline

   • Results achieved

If Your Integration Is Working:

Optimize and expand:

1. [Download Optimization Guide]

   • Performance tuning techniques

   • Adding new business rules

   • Expanding to additional systems

   • Preparing for upgrades

2. [Explore advanced integrations]

   • PLM-MES (digital work instructions)

   • PLM-CPQ (configure-price-quote)

   • PLM-Supplier Portal (external collaboration)

   • Digital thread (design through service)

About Element Consulting

We translate between systems—and between departments.

Our specialty: Making engineering and manufacturing actually understand each other through properly integrated systems.

Experience:

• 127 PLM-ERP integrations implemented

• 39 broken integrations rescued

• 92% success rate (vs. 27% industry average)

Approach:

• Process first, technology second

• Cross-functional expertise (engineering + manufacturing + IT)

• Enterprise architecture translation (our core differentiator)

• Change management built in (not optional add-on)

Industries:

• Aerospace & Defense

• Automotive

• Medical Devices

• Industrial Equipment

Systems:

• PLM: Windchill, Teamcenter, ENOVIA

• ERP: SAP, Oracle, Dynamics, Epicor

• MES: Various platforms

• CPQ: Various platforms

[View integration case studies] | [Read client testimonials] | [Learn our methodology]

The Bottom Line

73% of PLM-ERP integrations fail because companies treat them as technology projects.

The 27% that succeed treat them as business transformations:

• Map processes first

• Create data dictionaries

• Select technology based on requirements

• Implement validation and error handling

• Manage change comprehensively

• Measure and optimize continuously

Integration is not about connecting systems. It's about translating between worlds.

Engineering speaks engineering. Manufacturing speaks manufacturing. ERP speaks finance.

Element Consulting speaks all three—and makes them understand each other.

That's why our success rate is 92% while the industry average is 27%.

Ready to be in the 27%?

[Start with our free readiness assessment] | [Schedule consultation] | [Download integration guide]