Why Most SAP PM Implementations Fail — And How High-Reliability Plants Fix It

Why Most SAP PM
Implementations Fail
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sustainable reliability.

Why Most SAP PM Implementations Fail
2
Digitized ≠ Optimized
 SAP PM adoption is widespread, impact is limited
 Plants digitize tasks but not decisions
 Reliability outcomes remain flat despite system usage
 Maintenance becomes administrative, not strategic
 Execution improves, failures persist
 The problem is structural, not technical
And Why Technology Alone Never Fixes Maintenance

3
Big Systems. Small Outcomes.
The SAP PM Promise vs Reality
 Promised: control, discipline, standardization
 Reality: work orders without prioritization
 Data captured but rarely acted upon
 PM compliance mistaken for performance
 Planners overloaded with administrative tasks
 Reliability still depends on heroics
Where Expectations Break Down

4
Software Is Not Strategy
The Core Misdiagnosis
 SAP PM is an execution system, not a decision engine
 Plants expect intelligence from configuration
 Strategy is assumed to emerge from workflows
 Maintenance logic remains manual and tribal
 Technology automates inefficiency
 Systems follow thinking — not the other way around
Treating Software as Strategy

5
Activity Is Not Reliability
Activity Obsession
 PM compliance becomes the primary KPI
 Work order volume replaces risk reduction
 Teams rewarded for busyness, not outcomes
 Failures occur despite “green dashboards”
 Activity metrics hide systemic risk
 Reliability requires impact, not effort
When More Work Delivers Less Reliability

6
Time ≠ Risk
Calendar-Based Maintenance Trap
 PM schedules fixed by calendar, not condition
 Asset criticality ignored
 Over-maintenance on low-risk assets
 Under-maintenance on high-risk assets
 Failures occur between PMs
 Risk-driven maintenance is missing
Time Is Not Risk

7
Data Doesn’t Decide
Data Without Decisions
 SAP PM captures massive data volumes
 Data lacks prioritization logic
 Reports explain yesterday, not tomorrow
 Planners manually interpret risk
 Insights arrive too late
 Decisions remain reactive
When Information Becomes Noise

8
Humans Can’t Scale Chaos
Planner Burnout
 Planners manage hundreds of assets manually
 Conflicting priorities every day
 Spreadsheets outside SAP PM
 Stress-driven decision making
 Knowledge trapped in individuals
 Systems fail to support thinking
Human Cognition Cannot Scale Chaos

9
Customization ≠ Capability
The Customization Trap
 Heavy SAP PM customization
 Business logic hard-coded into workflows
 Every exception adds fragility
 Upgrades become risky and slow
 Knowledge locked in consultants
 Systems become brittle over time
Complexity Masquerading as Capability

10
Execution Needs Intelligence
The Missing Intelligence Layer
 SAP PM executes what it’s told
 No continuous asset behavior analysis
 No automated risk ranking
 No failure prediction logic
 Decisions remain manual
 Intelligence must sit above execution
Execution Without Thinking

11
Systems Beat Effort
High-Performing Plants
 Decisions driven by risk, not routine
 Predictive insights guide execution
 Maintenance aligned to business impact
 Leaders see risk, not just KPIs
 Continuous learning loops
 Systems support thinking
Reliability Is Designed, Not Enforced

12
Record, Don’t Decide
SAP PM’s Proper Role
 Excellent transaction backbone
 Reliable work order execution
 Strong compliance tracking
 Stable master data
 Not designed for decision logic
 Must be guided, not overloaded
Strong Execution, Not Intelligence

13
Design the System
Architecture That Works
 Asset data feeds intelligence layer
 AI evaluates risk continuously
 Decisions prioritized automatically
 SAP PM executes approved actions
 Feedback improves future decisions
 Closed-loop reliability system
Intelligence Above Execution

14
Maintenance That Thinks
Enter MaintWiz AI CMMS
 Continuous asset behavior analysis
 Risk-based work prioritization
 Predictive failure detection
 Intelligent scheduling recommendations
 Planner cognitive load reduction
 Business-aligned maintenance
Decision-Centric Maintenance

15
Better Together
MaintWiz + SAP PM
 MaintWiz drives intelligence
 SAP PM executes reliably
 No SAP customization required
 Faster value realization
 Scalable across plants
 Future-proof architecture
Best of Both Worlds

16
From Chaos to Control
What Changes With MaintWiz
 Fewer emergency work orders
 Higher wrench time
 Reduced downtime risk
 Predictable maintenance plans
 Leadership visibility improves
 Reliability becomes repeatable
From Reaction to Control

17
Scale Reliability
Reliability at Scale
 Multi-plant benchmarking
 Standardized decision logic
 Local execution flexibility
 Central risk visibility
 Consistent reliability outcomes
 Leadership confidence
Governance Without Micromanagement

18
Choose the System
The Leadership Question
 More configuration or better decisions?
 More reports or less risk?
 More activity or higher reliability?
 Tools or systems?
 Compliance or performance?
 Execution or intelligence?
What Are You Really Investing In?

19
Design for Reliability
Final Takeaway
 SAP PM is necessary but insufficient
 Intelligence must guide execution
 Systems outperform heroics
 Maintenance is a business system
 Reliability is engineered
 MaintWiz makes it repeatable
Reliability Is a Design Choice

20
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Why Most SAP PM Implementations Fail — And How High-Reliability Plants Fix It

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