Performance Intelligence

KPI Library
+ Digital Architecture

A governed KPI and threshold library organized around People, Safety, Quality, Delivery, Cost, and Innovation — plus the digital architecture required to connect from local spreadsheets to integrated enterprise systems.

488
Published KPIs & Measures
1,731
Power BI Measures
62
Dashboards
15
Modules
250+
Data Tables
Current KPI Master

Explore 488 governed measures by PSQDCI domain.

No Tier assignment is shown in the public library at this stage. The focus is the governed measure itself: definition, source area, threshold bands, and performance direction.

488published records
DomainKPI / MetricModule / Performance AreaUOMExceedsMeetsPartialDir
P
Training Compliance %
PEOPLE — % personnel rows Compliant in FACT_Personnel_Room_Status for suite/day
MFG T1 Suite ScorecardMFG T1 PSQDC % ≥98% ≥95% ≥90%
P
Resources Req / Avail %
PEOPLE — DIVIDE(Available_Hours, Required_Hours) from FACT_Suite_Hourly_Schedule
MFG T1 Suite ScorecardMFG T1 PSQDC % ≥100% ≥95% ≥90%
P
Overtime %
PEOPLE — Overtime_Hours / Required_Hours. Lower is better. Display with 1 decimal.
MFG T1 Suite ScorecardMFG T1 PSQDC % ≤0% ≤0% ≤1%
P
People
Pillar weight = sum of T1_Training_Compliance + T1_Resources_Ratio + T1_Overtime_Pct weights
MFG T1 Suite ScorecardMFG T1 PSQDC Map Pillar
P
Cost Per Hire
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Internal Hire Rate
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Interview to Offer Rate
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Offer Acceptance Rate
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Referral Hire Rate
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Resume to Interview Rate
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Staffing Rate
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Time to Hire
Referenced by Power BI measures through TA_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TA_Targets.xlsx / source file.
PeopleTalent Acquisition
P
Staffing_Rate
Parameter display alias for TA_KPI_Parameter → TA_Staffing_Rate; maps to targ...
PeopleTalent Acquisition
P
Time_To_Hire
Parameter display alias for TA_KPI_Parameter → TA_Time_To_Hire; maps to targe...
PeopleTalent Acquisition
P
Internal_Hire_Rate
Parameter display alias for TA_KPI_Parameter → TA_Internal_Hire_Rate; maps to...
PeopleTalent Acquisition
P
Referral_Hire_Rate
Parameter display alias for TA_KPI_Parameter → TA_Referral_Hire_Rate; maps to...
PeopleTalent Acquisition
P
Cost_Per_Hire
Parameter display alias for TA_KPI_Parameter → TA_Cost_Per_Hire; maps to targ...
PeopleTalent Acquisition
P
1:1 Completion Rate
Referenced by Power BI measures through TD_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TD_Targets.xlsx / source file.
PeopleTalent Development
P
Bench Strength Index
Referenced by Power BI measures through TD_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TD_Targets.xlsx / source file.
PeopleTalent Development
P
INDEX
Referenced by Power BI measures through TD_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TD_Targets.xlsx / source file.
PeopleTalent Development
P
L&D Completion Rate
Referenced by Power BI measures through TD_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from TD_Targets.xlsx / source file.
PeopleTalent Development
P
Perf Review Completion
Referenced by Power BI measures through TD_Targets[KPI]. Target values are so...
PeopleTalent Development
P
Skill Progression Rate
Referenced by Power BI measures through TD_Targets[KPI]. Target values are so...
PeopleTalent Development
P
Training Hrs/Employee
Referenced by Power BI measures through TD_Targets[KPI]. Target values are so...
PeopleTalent Development
P
Training On-Time %
Referenced by Power BI measures through TD_Targets[KPI]. Target values are so...
PeopleTalent Development
P
TD Weighted Score
Parameter display alias for Talent Development composite index.
PeopleTalent Development
P
% Overtime
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Absenteeism Rate
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Average Tenure
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Engagement Rate
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Manager Effectiveness
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
PTO Utilization Rate
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Promotion Rate
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Recognition Rate
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Retention Rate
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Survey Response Rate
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Work Life Harmony
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
eNPS Score
Referenced by Power BI measures through TH_Targets[KPI]. Target values are so...
PeopleTalent Health
P
Engagement Rate Trend
Parameter display alias for Talent Health trend measure.
PeopleTalent Health
P
Work Life Harmony Trend
Parameter display alias for Talent Health trend measure.
PeopleTalent Health
P
Recognition Rate Trend
Parameter display alias for Talent Health trend measure.
PeopleTalent Health
P
Average Tenure Trend
Parameter display alias for Talent Health trend measure.
PeopleTalent Health
P
Retention Rate Trend
Parameter display alias for Talent Health trend measure.
PeopleTalent Health
P
Promotion Rate Trend
Parameter display alias for Talent Health trend measure.
PeopleTalent Health
P
On Time %
Training_Targets DATATABLE. On-time training completion rate.
PeopleTraining Dashboard % ≥98% ≥95% ≥85%
P
Completion Rate %
Training_Targets DATATABLE. Training completion rate.
PeopleTraining Dashboard % ≥98% ≥95% ≥85%
P
Training Pace %
Training_Targets DATATABLE. Training pace vs expected.
PeopleTraining Dashboard % ≥110% ≥90% ≥75%
P
% Emps No Due <7D
Training_Targets DATATABLE. % employees with no due/overdue items inside 7 days.
PeopleTraining Dashboard % ≥97% ≥93% ≥85%
P
% Emps No Due <30D
Training_Targets DATATABLE. % employees with no due/overdue items inside 30 days.
PeopleTraining Dashboard % ≥90% ≥80% ≥70%
P
Hrs Per Employee
Training_Targets DATATABLE. Training hours per employee.
PeopleTraining Dashboard Hours ≥4.5 ≥3.5 ≥2.5
P
Hrs Completed %
Parameter display alias from Training KPI Parameter; likely maps to Training ...
PeopleTraining Dashboard
P
Due In 7 Days
Parameter display alias from Training KPI Parameter; maps to % Emps No Due <7...
PeopleTraining Dashboard
P
Due In 30 Days
Parameter display alias from Training KPI Parameter; maps to % Emps No Due <3...
PeopleTraining Dashboard
S
Safety Concerns Reported
More reporting = more proactive culture. Target is high volume.
EHSEHS Behavioral Safety # ≥20 ≥10 ≥5
S
Positive Behaviors Observed
Positive safety observations per period.
EHSEHS Behavioral Safety # ≥40 ≥25 ≥15
S
Observation Ratio (Positive:Concern)
Positive behaviors / safety concerns. >=2.0 = healthy culture.
EHSEHS Behavioral Safety ratio ≥2.5 ≥2 ≥1.5
S
Open Safety CAPAs
Total open safety CAPAs. Informational.
EHSEHS CAPA Status # ≤10 ≤25 ≤40
S
Overdue Safety CAPAs
CAPAs past due date. >10 = escalation required.
EHSEHS CAPA Status # ≤2 ≤5 ≤10
S
SDS Currency %
% Safety Data Sheets current within required review period
EHSEHS Chemical Safety % ≥99% ≥97% ≥90%
S
Chemical Storage Compliance %
% chemical storage locations meeting all requirements
EHSEHS Chemical Safety % ≥99% ≥97% ≥90%
S
Chemical Quantity Compliance %
% chemicals within approved quantity limits
EHSEHS Chemical Safety % ≥99% ≥97% ≥90%
S
Lost Time Injury Rate (LTIR)
LTI incidents x 200,000 / hrs worked. Lower is better.
EHSEHS Incident Metrics rate ≤0.1 ≤0.3 ≤0.6
S
Total Recordable Incident Count
Total OSHA recordable incidents per period. Lower is better.
EHSEHS Incident Metrics # ≤5 ≤10 ≤15
S
Near Miss / Observation Count
Higher = stronger preventive reporting culture.
EHSEHS Incident Metrics # ≥200 ≥100 ≥50
S
Open Regulatory Findings
Open findings from regulatory inspections/audits
EHSEHS Regulatory Findings # ≤1 ≤3 ≤5
S
Avg Days to Close Findings
Average days from finding date to verified closure
EHSEHS Regulatory Findings days ≤60 ≤90 ≤120
S
TRIR (Total Recordable Incident Rate)
Recordable incidents x 200,000 / hrs worked. Lower is better. Pharma best-in-class <0.5
EHSEHS Safety Index rate ≤0.5 ≤1 ≤1.5
S
Days Without Recordable Incident
Days since last OSHA recordable. Exceeds>=365d Meets>=180d Partial>=120d
EHSEHS Safety Index days ≥365 ≥180 ≥120
S
EHS Compliance Risk Score
Composite: reg compliance 40% + audit closure 35% + open findings risk 25%
EHSEHS Safety Index score ≥0.95 ≥0.85 ≥0.75
S
Safety CAPA On-Time Closure %
% safety CAPAs closed on or before due date within the month
EHSEHS Safety Index % ≥95% ≥85% ≥75%
S
Chemical Compliance Rate
% chemical inventory items Overall_Compliant_Flag=Y at latest snapshot
EHSEHS Safety Index % ≥98% ≥95% ≥85%
S
Workplace Safety Score
Composite: 6S Audit 40% + JHA completion 35% + EHS training OT 25%
EHSEHS Safety Index score ≥0.95 ≥0.85 ≥0.75
S
6S Compliance Rate %
% 6S audit areas passing threshold
EHSEHS Workplace Safety % ≥95% ≥90% ≥80%
S
JHA Completion Rate %
% required JHAs completed for the period
EHSEHS Workplace Safety % ≥95% ≥90% ≥80%
S
EHS Training On-Time %
% EHS-required training completed on time
EHSEHS Workplace Safety % ≥97% ≥93% ≥85%
S
Chemical Compliance Rate
Referenced by Power BI measures through Safety_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Safety_Targets.xlsx / source file.
EHSSafety Scorecard
S
Safety CAPA On-Time %
Referenced by Power BI measures through Safety_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Safety_Targets.xlsx / source file.
EHSSafety Scorecard
S
TRIR
Referenced by Power BI measures through Safety_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Safety_Targets.xlsx / source file.
EHSSafety Scorecard
S
Workplace Safety Score
Referenced by Power BI measures through Safety_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Safety_Targets.xlsx / source file.
EHSSafety Scorecard
S
Safety Issues
SAFETY — Count open actions where Owner='EHS' in FACT_Suite_Action_Log as-of day. Lower is better.
MFG T1 Suite ScorecardMFG T1 PSQDC Count ≤0 ≤0 ≤1
S
Safety
Pillar weight = T1_Safety_Issues weight
MFG T1 Suite ScorecardMFG T1 PSQDC Map Pillar
Q
Days Without DV
QUALITY — DATEDIFF(last DV Created_Date, selected day). Higher = fewer deviations = better.
MFG T1 Suite ScorecardMFG T1 PSQDC Days ≥30 ≥10 ≥5
Q
MPR Review OT+RFT %
QUALITY — % MPRs both on-time AND right-first-time. Aligned with MFG T3 RFT (0.97/0.93/0.87). Source: FACT_MPR_Review.
MFG T1 Suite ScorecardMFG T1 PSQDC % ≥97% ≥93% ≥87%
Q
MPR RTR Complete %
QUALITY — % MPRs with real-time review steps completed. Source: FACT_MPR_Review[RTR_Complete_Flag].
MFG T1 Suite ScorecardMFG T1 PSQDC % ≥100% ≥95% ≥90%
Q
Quality
Pillar weight = sum of T1_Days_Without_DV + T1_MPR_Review_OT_RFT + T1_MPR_RTR_Complete weights
MFG T1 Suite ScorecardMFG T1 PSQDC Map Pillar
Q
% Audit No Critical_Major
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
% Recurrence
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
CAPA Linkage Rate %
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
Critical % of Obs
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
Finding Closure Rate %
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
Major % of Obs
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
On Time Closure %
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
Response On Time %
Referenced by Power BI measures through Audit_Targets[KPI]. Target values are...
QualityAudit Management
Q
% On Time
CAPA_Thresholds DATATABLE. % CAPA on time.
QualityCAPA % ≥98% ≥90% ≥85%
Q
Effectiveness
CAPA_Thresholds DATATABLE. CAPA effectiveness.
QualityCAPA % ≥98% ≥90% ≥85%
Q
Overdue
CAPA_Thresholds/DimGoal DATATABLE. Open overdue count; lower is better.
QualityCAPA Count ≤0 ≤2 ≤5
Q
Open Aging
CAPA_Thresholds/DimGoal DATATABLE. Lower is better.
QualityCAPA Days ≤180 ≤240 ≤300
Q
Avg Time To Close
CAPA_Thresholds DATATABLE. Lower is better.
QualityCAPA Days ≤180 ≤240 ≤300
Q
Extensions In Period
CAPA_Thresholds DATATABLE. Lower is better.
QualityCAPA Count ≤5 ≤15 ≤25
Q
Extensions Per CAPA
CAPA_Thresholds DATATABLE. Lower is better.
QualityCAPA #/CAPA ≤0.5 ≤1 ≤1.5
Q
Actions % On Time
Power BI CC_KPI selector row. Threshold values not embedded in provided database.zip.
QualityChange Control %
Q
% Open < 9 Months
Power BI CC_KPI selector row. Threshold values not embedded in provided database.zip.
QualityChange Control %
Q
% Initiation < 30 Days
Power BI CC_KPI selector row. Threshold values not embedded in provided database.zip.
QualityChange Control %
Q
Initiate → Approval Avg Days
Power BI CC_KPI selector row. Lower is better; thresholds not embedded in provided database.zip.
QualityChange Control Days
Q
% Urgent
Power BI CC_KPI selector row. Lower is generally better; thresholds not embedded in provided database.zip.
QualityChange Control %
Q
CC Index
Power BI CC_KPI selector row. Threshold values not embedded in provided database.zip.
QualityChange Control Score
Q
DV % CLOSED ON TIME
DEVIATION_Thresholds DATATABLE; prefixed to keep Lookup_Key unique.
QualityDeviations % ≥98% ≥95% ≥85%
Q
DV % OPEN OVERDUE
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations % ≤0% ≤5% ≤10%
Q
DV RECURRENCE %
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations % ≤5% ≤10% ≤20%
Q
DV OPEN AGING
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations Days ≤15 ≤30 ≤60
Q
DV AVG TIME TO CLOSE
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations Days ≤28 ≤30 ≤35
Q
DV > 30 DAY AGING
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations Count ≤5 ≤10 ≤30
Q
DV OCCUR TO DETECT AVG
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations Days ≤4 ≤7 ≤14
Q
DV % MAJOR + CRITICAL
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations % ≤5% ≤10% ≤20%
Q
DV EXTENSIONS IN PERIOD
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations Count ≤0 ≤0 ≤1
Q
DV EXTENSIONS PER DV
DEVIATION_Thresholds DATATABLE; lower is better.
QualityDeviations #/DV ≤0.02 ≤0.05 ≤0.1
Q
Avg Review Cycle Days
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
Avg Revision Cycle Days
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
CAPA Driven Rev %
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
First Pass Approval %
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
PR Due Next 30D
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
PR On Time Completion %
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
PR Revision Required %
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
Rev On Time Closure %
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
Rev Recurrence %
Referenced by Power BI measures through Doc_Control_Targets[KPI]. Target valu...
QualityDocument Control
Q
ASL Expiry 90D
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values ...
QualitySupplier Quality
Q
D&B SER % Above
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
Q
Lot Acceptance Rate
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
Q
On Time Delivery
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
Q
Past Due ASL Audit %
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
Q
S-CAR Avg Age
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
Q
S-CAR On Time Closure
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
Q
Single Sourced %
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
Q
Sole Sourced %
Referenced by Power BI measures through Supplier_Targets[KPI]. Target values are sourced from external workbook in Power Query and are not embedded in database.zip; fill/validate thresholds from Supplier_Targets.xlsx / source file.
QualitySupplier Quality
D
Weighted Performance Index
Required by CMMS_CM_Info_Panel. WPI score threshold row.
CMMSCorrective Maintenance 1-4 ≥3 ≥2.5 ≥1.5
D
On Time Complete %
Higher is better. Actual CM completed on or before due date / Scheduled CM.
CMMSCorrective Maintenance % ≥99% ≥98% ≥95%
D
Overdue CM %
Lower is better. Overdue CM WOs as % of total scheduled CM.
CMMSCorrective Maintenance % ≤0% ≤1% ≤3%
D
Assigned %
Higher is better. Assigned CM WOs / total open CM WOs.
CMMSCorrective Maintenance % ≥100% ≥98% ≥95%
D
On Hold <30D %
Corrected from legacy >30D wording. Percent of on-hold CM WOs less than 30 days old; higher is better.
CMMSCorrective Maintenance % ≥99% ≥98% ≥95%
D
Pending Review <30D %
Required by CMMS corrective maintenance scoring. Percent of pending-review CM WOs less than 30 days old; higher is better.
CMMSCorrective Maintenance % ≥99% ≥98% ≥95%
D
WR to WO Cycle Time (Days)
Lower is better. Average days from Work Request creation to Work Order assignment.
CMMSCorrective Maintenance Days ≤1 ≤2 ≤3
D
PM Compliance %
Higher is better. Complete+VendorCAL/Total scheduled.
CMMSPM Compliance % ≥98% ≥95% ≥88%
D
Schedule Adherence
Higher is better. OnTime/Completed WOs.
CMMSPM Compliance % ≥98% ≥95% ≥88%
D
Overdue Rate
Lower is better. Point-in-time Interval_Status=Overdue.
CMMSPM Compliance % ≤2% ≤5% ≤10%
D
Resource Utilization
Higher is better. Required hrs/Available hrs. Target 80-90%.
CMMSPM Compliance % ≥90% ≥85% ≥80%
D
MTTR (hrs)
Lower is better. Avg actual hrs for unplanned completed WOs.
CMMSPM Compliance hrs ≤2 ≤3 ≤5
D
On Hold WO Count
Lower is better. Non-weighted informational.
CMMSPM Compliance Count ≤0 ≤2 ≤5
D
Unassigned WO Count
Lower is better. Non-weighted informational.
CMMSPM Compliance Count ≤0 ≤2 ≤5
D
Revenue PTP %
Actuals / budget target
Demand PlanningDP T3 Scorecard % ≥105% ≥98% ≥90%
D
Secured Revenue vs Plan
Secured backlog / quarterly plan
Demand PlanningDP T3 Scorecard % ≥105% ≥95% ≥85%
D
Forecast Accuracy %
1 - MAPE; higher = more accurate
Demand PlanningDP T3 Scorecard % ≥95% ≥90% ≥85%
D
Book to Bill Ratio
Orders booked / billed; >1.0 = pipeline growing
Demand PlanningDP T3 Scorecard x ≥1.1 ≥1 ≥0.9
D
Capacity Utilization %
Secured+P75 demand / max capacity
Demand PlanningDP T3 Scorecard % ≥85% ≥70% ≥50%
D
Total Interval Actions
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
Total On Demand WO
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
Unassigned
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
On Hold
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
Planned Complete
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
Actual Complete
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
Acceptable In Process
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
Overdue
Power BI CMMS_KPI_List selector row.
ENGCMMS Count
D
Schedule Adherence MTD
Power BI CMMS_KPI_List selector row.
ENGCMMS %
D
Resources Required (Hrs)
Power BI CMMS_KPI_List selector row; supporting capacity measure.
ENGCMMS Hours
D
Resources Available (Hrs)
Power BI CMMS_KPI_List selector row; supporting capacity measure.
ENGCMMS Hours
D
% Utilization
Power BI CMMS_KPI_List selector row.
ENGCMMS %
D
Unassigned %
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance %
D
Scheduled CM Complete
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Actual CM Complete
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Overdue CM WO
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Overdue CM >30D
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Unassigned CM WO
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Unassigned CM >15D
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
On Hold WO
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Pending Review
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Pending Review >30D
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
WR Processed
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
WR Pending >2D
Power BI DIM_CMMS_CM_KPI selector row.
ENGCMMS Corrective Maintenance Count
D
Maintenance % vs Budget
Actual maintenance spend / approved budget. Lower=better (at/under budget). Exceeds=<=98%, Meets=<=100%, Partial=<=103%.
ENGCost Performance R&M % ≤98% ≤100% ≤103%
D
Maintenance Cost / Asset
Total PM cost / active assets. Lower=better. Exceeds<=$3,700, Meets<=$4,000, Partial<=$4,400.
ENGCost Performance R&M $ ≤$4K ≤$4K ≤$4K
D
Repair Cost per Asset
Total repair cost / active assets. Lower=better. Exceeds<=$1,600, Meets<=$1,900, Partial<=$2,200.
ENGCost Performance R&M $ ≤$2K ≤$3K ≤$3K
D
Repairs % vs Budget
Actual unplanned/repair spend / budget for unplanned work. Lower=better. Exceeds=<=98%, Meets=<=100%, Partial=<=103%.
ENGCost Performance R&M % ≤98% ≤100% ≤103%
D
Cost per Operating Hour
Retired — replaced by Repair Cost per Asset.
ENGCost Performance R&M $/Hr ≤700 ≤750 ≤800
D
Weighted Performance Index
COST_WPI composite (1-4 scale). Exceeds>=3.80, Meets>=2.50, Partial>=2.00. Used for WPI card border and chart target.
ENGCost Performance R&M Index ≥3 ≥2 ≥1
D
Financial Performance
Actual portfolio cost / budget. Lower=better (at/under budget). Exceeds<=95%, Meets<=100%, Partial<=105%.
ENGReal Estate % ≤95% ≤104% ≤109%
D
Property Tax to Budget
Actual property tax / budget. Lower=better. Exceeds<=90%, Meets<=100%, Partial<=110%.
ENGReal Estate % ≤95% ≤104% ≤110%
D
Space Utilization
Actual occupied SqFt / total leasable SqFt. Higher=better. Exceeds>=85%, Meets>=75%, Partial>=60%.
ENGReal Estate % ≥85% ≥75% ≥60%
D
Compliance Risk Score
Weighted compliance score (permits, inspections, certificates current). Higher=better. Exceeds>=90%, Meets>=75%, Partial>=60%.
ENGReal Estate Score ≥0.9 ≥0.75 ≥0.6
D
Lease Expiry Management
% of leases with >12 months remaining OR renewal initiated. Higher=better. Exceeds>=90%, Meets>=75%, Partial>=60%.
ENGReal Estate % ≥90% ≥75% ≥60%
D
Weighted Performance Index
RE_WPI composite (1-4 scale). Exceeds>=3.80, Meets>=2.50, Partial>=2.00.
ENGReal Estate Index ≥3 ≥2 ≥1
D
Reliability WPI
Composite Reliability Engineering WPI score. Blue=Exceeds, Green=Meets, Yellow=Partial, Red=Does Not Meet.
ENGReliability Engineering Index ≥3 ≥2 ≥1
D
Asset Availability %
OEE Availability-aligned reliability KPI. Uses operating hours and downtime minutes/hours.
ENGReliability Engineering % ≥98% ≥95% ≥90%
D
Asset Downtime %
Downtime hours as % of operating hours. Lower is better.
ENGReliability Engineering % ≤1% ≤3% ≤5%
D
MTBF
Mean time between failures. Higher is better.
ENGReliability Engineering Months ≥6 ≥3 ≥1
D
Mean Time to Repair
Average repair duration for failure/corrective work. Lower is better.
ENGReliability Engineering Hours ≤4 ≤8 ≤16
D
Spares Availability %
Requires parts/inventory availability data; currently placeholder until source exists.
ENGReliability Engineering % ≥98% ≥95% ≥90%
D
Preventive vs Corrective %
Preventive/planned work as percent of planned + corrective work.
ENGReliability Engineering % ≥75% ≥65% ≥50%
D
Failure Rate
Failures per 1,000 operating hours. Lower is better.
ENGReliability Engineering Rate ≤1 ≤3 ≤5
D
Repeat Failure Rate
Percent of failed assets with more than one failure in selected period. Lower is better.
ENGReliability Engineering % ≤2% ≤5% ≤10%
D
% Repair within SLA
Percent of repairs completed within target. Higher is better.
ENGReliability Engineering % ≥95% ≥90% ≥80%
D
OEE
Manufacturing OEE aligned: Availability x Performance x Quality. Legacy reliability alias renamed from duplicate 'OEE' to prevent LOOKUPVALUE ambiguity. Manufacturing keeps 'OEE'.
ENGReliability Engineering % ≥85% ≥75% ≥65%
D
OEE Availability %
Availability component from equipment status/downtime impact.
ENGReliability Engineering % ≥98% ≥95% ≥90%
D
OEE Performance %
Performance component from schedule adherence, resource availability, and material constraints.
ENGReliability Engineering % ≥95% ≥90% ≥80%
D
OEE Quality %
Quality component from deviations and reject rate.
ENGReliability Engineering % ≥98% ≥95% ≥90%
D
Schedule Adherence %
PowerApp shift-report performance metric: On Track/Ahead vs total reported room activity.
ENGReliability Engineering % ≥95% ≥90% ≥80%
D
Resource Availability %
Available resources / required resources from shift room status.
ENGReliability Engineering % ≥100% ≥95% ≥90%
D
Material Availability %
Rooms/steps without material issues as percent of total room status rows.
ENGReliability Engineering % ≥100% ≥95% ≥90%
D
Reject Rate %
DP quality loss metric. Lower is better.
ENGReliability Engineering % ≤0% ≤1% ≤3%
D
Equipment Availability %
Asset availability filtered to equipment assets.
ENGReliability Engineering % ≥98% ≥95% ≥90%
D
Utilities Availability %
Asset availability filtered to utilities/facility systems.
ENGReliability Engineering % ≥98% ≥95% ≥90%
D
% Assets w/ Failures
Percent of active assets with at least one failure in selected period.
ENGReliability Engineering % ≤2% ≤5% ≤10%
D
Time to Respond
Average time from WO created to repair start. Lower is better.
ENGReliability Engineering Hours ≤4 ≤8 ≤16
D
Time to Repair
Average active repair time. Lower is better.
ENGReliability Engineering Hours ≤4 ≤8 ≤16
D
Mean Wait Time (Parts/Labor)
Average parts/labor wait time. Requires shift report or CMMS wait reason data.
ENGReliability Engineering Hours ≤2 ≤4 ≤8
D
Budget Variance %
Budget variance percent. Requires maintenance/repair budget and EAC data.
ENGReliability Engineering % ≥5% ≥0% ≥-5%
D
Maintenance % vs Budget
Maintenance spend vs budget. Requires cost source.
ENGReliability Engineering % ≤90% ≤100% ≤110%
D
Repairs % vs Budget
Repair spend vs budget. Requires cost source.
ENGReliability Engineering % ≤90% ≤100% ≤110%
D
% Planned vs Unplanned
Planned work as percent of planned + unplanned work.
ENGReliability Engineering % ≥75% ≥65% ≥50%
D
Red Flag Room Count
Rooms with down/impacting issues. Lower is better.
ENGReliability Engineering Count ≤0 ≤1 ≤3
D
Yellow Flag Room Count
Rooms with issue/WO open but not necessarily impacting manufacturing. Lower is better.
ENGReliability Engineering Count ≤0 ≤3 ≤5
D
Escalation Required Count
Shift report escalation count. Lower is better.
ENGReliability Engineering Count ≤0 ≤1 ≤3
D
Open Equipment Issues
Open equipment issues reported through shift changeover. Lower is better.
ENGReliability Engineering Count ≤0 ≤5 ≤10
D
Down Asset Count
Down assets from equipment issue status/CMMS asset status. Lower is better.
ENGReliability Engineering Count ≤0 ≤1 ≤3
D
Equipment Issue Count
Total shift-reported equipment issues. Lower is better.
ENGReliability Engineering Count ≤0 ≤5 ≤10
D
Average Downtime Minutes Per Issue
Average downtime minutes per equipment issue. Lower is better.
ENGReliability Engineering Minutes ≤15 ≤30 ≤60
D
Operating Hours
Supporting measure. Sum of room operating hours from FACT_Room_Operating_Day.
ENGReliability Engineering Hours
D
Installed Assets
Supporting measure. Count of installed CMMS assets.
ENGReliability Engineering Count
D
Assets In Service
Supporting measure. Count of active/in-service CMMS assets.
ENGReliability Engineering Count
D
Asset Utilization %
Operating hours divided by available asset hours.
ENGReliability Engineering % ≥90% ≥80% ≥70%
D
Total Assets
Supporting measure. Distinct asset count.
ENGReliability Engineering Count
D
Active Assets
Supporting measure. Active asset count.
ENGReliability Engineering Count
D
Production Hours
Alias/supporting measure for operating hours.
ENGReliability Engineering Hours
D
Failure Count
Supporting measure. Count of failure/unplanned work events.
ENGReliability Engineering Count
D
Top Failure Mode
Supporting measure. Most frequent action/failure category.
ENGReliability Engineering Text
D
Last Failure Date
Supporting measure. Most recent failure date.
ENGReliability Engineering Date
D
Downtime - No Impact Hours
Supporting measure by manufacturing impact.
ENGReliability Engineering Hours
D
Downtime - Potential Impact Hours
Supporting measure by manufacturing impact.
ENGReliability Engineering Hours
D
Downtime - Schedule Delay Hours
Supporting measure by manufacturing impact.
ENGReliability Engineering Hours
D
Downtime - Batch Impact Hours
Supporting measure by manufacturing impact.
ENGReliability Engineering Hours
D
Downtime - Shutdown Hours
Supporting measure by manufacturing impact.
ENGReliability Engineering Hours
D
Shift Report Count
Supporting measure. Count of shift reports.
ENGReliability Engineering Count
D
Room Active Days
Supporting measure. Count of active room-days.
ENGReliability Engineering Days
D
Approved Budget
Supporting measure. Requires budget source.
ENGReliability Engineering Currency
D
Actual Spend to Date
Supporting measure. Requires cost source.
ENGReliability Engineering Currency
D
Remaining Forecast
Supporting measure. Requires forecast source.
ENGReliability Engineering Currency
D
Forecast at Complete (EAC)
Supporting measure. Requires cost/forecast source.
ENGReliability Engineering Currency
D
Budget Variance $
Supporting measure. Requires budget/forecast source.
ENGReliability Engineering Currency
D
Maintenance Cost / Asset
Requires cost source.
ENGReliability Engineering Currency
D
Repair Cost / Asset
Requires cost source.
ENGReliability Engineering Currency
D
Cost per Operating Hour
Requires cost source and operating hours.
ENGReliability Engineering Currency/Hour
D
Critical Asset Reliability
Availability % for GMP-critical assets (IsCritical=1); critical-scoped Asset Availability.
ENGReliability Engineering % ≥98% ≥95% ≥90%
D
Inactive Assets
% of assets not Active/In Service; lower is better
ENGReliability Engineering % ≤2% ≤5% ≤10%
D
CAPEX Management
Average of on-time and on-budget rates for IsCAPEX projects (sourced from Innovation).
ENGSite Service % ≥95% ≥85% ≥70%
D
Internal Service Satisfaction
Average maintenance satisfaction survey score (1-5); one survey per completed WO.
ENGSite Service score ≥4.5 ≥4 ≥3.5
D
Carbon Reduction vs Baseline
YoY % reduction in CO2e vs prior-year baseline. Higher=better. Exceeds>=10%, Meets>=5%, Partial>=2%.
ENGSustainability % ≥10% ≥5% ≥2%
D
Energy Reduction vs Target
Actual energy reduction % vs annual target. Higher=better. Exceeds>=10%, Meets>=5%, Partial>=2%.
ENGSustainability % ≥10% ≥5% ≥2%
D
Water Intensity (Usage/Unit)
Water consumption per production unit vs prior year. Stored as ratio to PY (1.0=flat). Lower=better. Exceeds<=0.80, Meets<=0.90, Partial<=1.00.
ENGSustainability gal/unit ≤0.8 ≤0.9 ≤1
D
Energy Intensity (kWh/Unit)
Total kWh per production unit vs prior year. Stored as ratio to PY. Lower=better. Exceeds<=0.80, Meets<=0.90, Partial<=1.00.
ENGSustainability kWh/unit ≤0.8 ≤0.9 ≤1
D
Waste Diversion Rate
% of total waste diverted from landfill (recycled/composted/recovered). Higher=better. Exceeds>=80%, Meets>=70%, Partial>=60%.
ENGSustainability % ≥80% ≥70% ≥60%
D
Weighted Performance Index
SUST_WPI composite (1-4 scale). Exceeds>=3.80, Meets>=2.50, Partial>=2.00.
ENGSustainability Index ≥3.8 ≥2.5 ≥2
D
Weighted Performance Index
Required by REL_HTML_Info_Panel where Module='Engineering'. Existing score measures also use Module='ENG'.
EngineeringReliability Engineering 1-4 ≥3 ≥2.5 ≥1.5
D
Asset Availability %
Alias required by REL_HTML_Info_Panel where Module='Engineering'; same thresholds as ENG Reliability Engineering row.
EngineeringReliability Engineering % ≥98% ≥95% ≥90%
D
Asset Downtime %
Alias required by REL_HTML_Info_Panel where Module='Engineering'; same thresholds as ENG Reliability Engineering row.
EngineeringReliability Engineering % ≤1% ≤3% ≤5%
D
Spares Availability %
Alias required by REL_HTML_Info_Panel where Module='Engineering'; same thresholds as ENG Reliability Engineering row.
EngineeringReliability Engineering % ≥98% ≥95% ≥90%
D
Preventive vs Corrective %
Alias required by REL_HTML_Info_Panel where Module='Engineering'; same thresholds as ENG Reliability Engineering row.
EngineeringReliability Engineering % ≥75% ≥65% ≥50%
D
MTBF Months
Required by REL_HTML_Info_Panel and ENG_REL_KPI Parameter. Higher is better.
EngineeringReliability Engineering Months ≥12 ≥10 ≥6
D
MTTR Hours
Required by REL_HTML_Info_Panel and ENG_REL_KPI Parameter. Lower is better.
EngineeringReliability Engineering Hours ≤2 ≤4 ≤8
D
Schedule Adherence %
DELIVERY — Available_Hours / Required_Hours from FACT_Suite_Hourly_Schedule. Aligned with MFG T3 OTD thresholds.
MFG T1 Suite ScorecardMFG T1 PSQDC % ≥98% ≥95% ≥90%
D
Ready to Execute
DELIVERY — Count open actions with Manufacturing_Impact=1. 0=Ready. Lower is better.
MFG T1 Suite ScorecardMFG T1 PSQDC Count ≤0 ≤0 ≤1
D
Equipment Downtime %
COST — Downtime_Minutes / (Required_Hours×60). Lower is better.
MFG T1 Suite ScorecardMFG T1 PSQDC % ≤0% ≤0% ≤0%
D
Overdue Issues
COST — Count open actions past Due_Date in FACT_Suite_Action_Log. Lower is better.
MFG T1 Suite ScorecardMFG T1 PSQDC Count ≤0 ≤0 ≤1
D
Overdue Alarms
COST — Count alert/alarm events open >24hr in FACT_EMS_BMS_Events. Lower is better.
MFG T1 Suite ScorecardMFG T1 PSQDC Count ≤0 ≤0 ≤1
D
Delivery
Pillar weight = sum of T1_Schedule_Adherence + T1_Ready_to_Execute weights
MFG T1 Suite ScorecardMFG T1 PSQDC Map Pillar
D
Right First Time %
% batches released without deviation or rework
ManufacturingMFG Performance % ≥97% ≥93% ≥87%
D
On Time Delivery %
% batches completed by planned end date
ManufacturingMFG Performance % ≥97% ≥92% ≥85%
D
OEE %
Availability x Performance x Quality
ManufacturingMFG Performance % ≥83% ≥70% ≥55%
D
OEE Availability %
% of scheduled time equipment available
ManufacturingMFG Performance % ≥92% ≥88% ≥82%
D
OEE Performance %
% of available time running at target rate
ManufacturingMFG Performance % ≥97% ≥93% ≥88%
D
OEE Quality %
% of output meeting quality spec
ManufacturingMFG Performance % ≥97% ≥95% ≥90%
D
Utilized Hours %
Actual productive hours / available hours
ManufacturingMFG Performance % ≥85% ≥80% ≥70%
D
Batch Cycle Time (days)
Actual cycle time vs target — lower is better
ManufacturingMFG Performance days ≤120 ≤145 ≤160
D
Capacity Utilization %
Planned batches vs available capacity
ManufacturingMFG Performance % ≥88% ≥80% ≥65%
D
Changeover %
Manufacturing suite time-loss state: hours where Suite_State = Changeover divided by total available suite hours. Lower is better.
ManufacturingManufacturing Downtime Analysis % ≤5% ≤10% ≤20%
D
Idle %
Manufacturing suite time-loss state: active suite with no activities OR inactive suite hours divided by total available suite hours. Lower is better.
ManufacturingManufacturing Downtime Analysis % ≤5% ≤10% ≤20%
D
Suite Availability %
1 - Total manufacturing suite time loss hours / total available suite hours. Higher is better.
ManufacturingManufacturing Downtime Analysis % ≥98% ≥95% ≥90%
D
Scheduled MFG Activity %
Scheduled manufacturing activity hours / total available suite hours. Should use MPS/suite schedule, not asset downtime.
ManufacturingManufacturing Downtime Analysis % ≥85% ≥75% ≥60%
D
Planned MFG Downtime %
Approved planned equipment/utility maintenance or shutdown window hours divided by total available suite hours. Lower is better.
ManufacturingManufacturing Downtime Analysis % ≤2% ≤5% ≤10%
D
Unplanned MFG Downtime %
Actual unexpected equipment/utility downtime impacting manufacturing divided by total available suite hours. Lower is better.
ManufacturingManufacturing Downtime Analysis % ≤0% ≤1% ≤3%
D
Assets with Failures
Distinct active assets with one or more unplanned failure incidents during selected period. Count measure; evaluate with % Assets w/ Failures for thresholding.
ManufacturingManufacturing Downtime Analysis Count
D
Active Assets Down
Distinct active assets where current asset status is Down and an open unplanned non-cancelled/non-validation WO exists as of report date. Lower is better.
ManufacturingManufacturing Downtime Analysis Count ≤0 ≤1 ≤5
D
Total MFG Downtime Hours
Supporting measure: planned MFG downtime hours + unplanned MFG downtime hours. Do not include changeover or idle.
ManufacturingManufacturing Downtime Analysis Hours
D
MRP Schedule Adherence %
PR + PO actions on time vs need date
ProcurementMRP Adherence % ≥99% ≥98% ≥95%
D
PR Behind Need to Release %
% PRs late to be released
ProcurementMRP Adherence % ≤2% ≤5% ≤10%
D
PO Behind Need to Place %
% POs late to be placed
ProcurementMRP Adherence % ≥2% ≥5% ≥10%
D
MRP Non-Support Prior %
% past need dates with MRP support
ProcurementMRP Adherence % ≤1% ≤2% ≤5%
D
MRP Non-Support Future %
% future needs that do not support MRP need date
ProcurementMRP Adherence % ≤2% ≤5% ≤10%
D
On Time Receipt %
Receipt on or before need date
ProcurementPerfect Receipt % ≥97% ≥93% ≥85%
D
In Full Receipt %
% lots received in full quantity
ProcurementPerfect Receipt % ≥98% ≥95% ≥88%
D
Document Accuracy %
% receipts with correct paperwork / COA
ProcurementPerfect Receipt % ≥100% ≥98% ≥95%
D
Damage Free Receipt %
% receipts with no damage
ProcurementPerfect Receipt % ≥99% ≥98% ≥95%
D
Dock-to-Stock Hrs
Total dock arrival to QA release — lower is better
ProcurementPerfect Receipt Hrs ≤36 ≤48 ≤72
D
Procurement Efficiency %
Composite: Throughput + CycleTime + Quality + Spend
ProcurementProc Efficiency % ≥92% ≥85% ≥75%
D
Procurement Throughput %
POs processed per buyer vs target
ProcurementProc Efficiency % ≥90% ≥80% ≥70%
D
PR to PO Cycle Time %
Efficiency vs target — higher = faster than target
ProcurementProc Efficiency % ≤90% ≤82% ≤72%
D
Process Quality %
PO Right First Time %
ProcurementProc Efficiency % ≥95% ≥88% ≥78%
D
Spend on Contract %
% total spend on contracted suppliers
ProcurementProc Efficiency % ≥88% ≥78% ≥65%
D
PRs per Buyer
Industry benchmark 200-300 per buyer per year
ProcurementProc Efficiency # ≥300 ≥250 ≥200
D
POs per Buyer
Industry benchmark 400-600 per buyer per year
ProcurementProc Efficiency # ≥600 ≥500 ≥350
D
Suppliers per Buyer
Industry benchmark 25-35 distinct suppliers per buyer
ProcurementProc Efficiency # ≥35 ≥30 ≥20
D
Buyer Productivity %
Composite of PR/PO/Suppliers per buyer normalized vs target
ProcurementProc Efficiency % ≥95% ≥90% ≥80%
D
PO Right First Time %
% POs with zero change orders
ProcurementProc Efficiency % ≥98% ≥95% ≥85%
D
PO Vendor Acknowledged %
% POs with vendor acknowledgement received
ProcurementProc Efficiency % ≥98% ≥95% ≥85%
D
Receipt-Invoice Match %
3-way match (PO-Receipt-Invoice) success rate
ProcurementProc Efficiency % ≥98% ≥95% ≥85%
D
Line Items per PO
Consolidation indicator - higher = fewer transactions per spend
ProcurementProc Efficiency # ≥10 ≥8 ≥5
D
% Spend on Contract
% total spend executed against contracted suppliers
ProcurementProc Efficiency % ≥90% ≥80% ≥65%
D
Spend per PO ($)
Average $ value per PO
ProcurementProc Efficiency $ ≥$40K ≥$30K ≥$20K
D
POs Pending Approval
Approval queue depth - lower is better
ProcurementProc Efficiency # ≤25 ≤50 ≤100
D
PR Backlog
Open PRs awaiting PO conversion - lower is better
ProcurementProc Efficiency # ≤50 ≤100 ≤200
D
Savings as % of Sales
Realized savings / net revenue
ProcurementProc Savings % ≥5% ≥4% ≥2%
D
Savings as % of Sales
Alias required by current Power BI DAX (Proc_Savings_Info_Panel). Same thresholds as Savings Pct Sales. Recommended future DAX normalization: consolidate to one lookup key.
ProcurementProc Savings % ≥5% ≥4% ≥2%
D
Spend as % of Sales
Total procurement spend / revenue
ProcurementProc Savings % ≤35% ≤40% ≤50%
D
Spend as % of Sales
Alias required by current Power BI DAX (Proc_Savings_Info_Panel). Same thresholds as Spend Pct Sales. Recommended future DAX normalization: consolidate to one lookup key.
ProcurementProc Savings % ≤35% ≤40% ≤50%
D
Spend Under Contract %
Alias key used by Power BI DAX LOOKUPVALUE. Existing workbook had 'Pct Spend On Contract'.
ProcurementProc Spend %
D
Perfect Receipt %
All 4 pillars: OT + InFull + CorrectPW + DamageFree
ProcurementProc Summary % ≥97% ≥93% ≥85%
D
Supplier Risk Score
Weighted risk score across supply base
ProcurementProc Summary score ≥0.9 ≥0.8 ≥0.65
D
Spend Performance %
Budget / actual spend — higher means under budget
ProcurementProc Summary % ≤105% ≤95% ≤85%
D
Released Pending >15d
ShipmentSHIPMENT — SHP Performance % ≤2% ≤5% ≤10%
D
Perfect Shipment %
OT + InFull + Accuracy + DamageFree all = 1
ShipmentSHP Performance % ≥97% ≥93% ≥85%
D
On Time Shipment %
% shipments delivered by commit date
ShipmentSHP Performance % ≥98% ≥95% ≥88%
D
In Full Shipment %
% shipments complete — no short shipments
ShipmentSHP Performance % ≥99% ≥97% ≥92%
D
Shipment Accuracy %
% shipments with correct documentation/contents
ShipmentSHP Performance % ≥100% ≥100% ≥99%
D
Damage Free Shipment %
% shipments received damage-free by client
ShipmentSHP Performance % ≥100% ≥100% ≥99%
D
Order-to-Ship Cycle (Days)
Legacy lookup key name retained because current WPI/scoring DAX uses Order to Ship Months. Underlying SHP measure is days.
ShipmentSHP Performance Days ≤8 ≤8 ≤9
D
Order-to-Ship Cycle (Days)
Alias required by SHP_Info_Panel. Existing WPI/scoring DAX still uses legacy key Order to Ship Months although the underlying measure is days.
ShipmentSHP Performance Days ≤8 ≤8 ≤9
D
Expedite Rate %
Lower is better — % shipments expedited
ShipmentSHP Performance % ≤3% ≤6% ≤12%
D
Cost Per Shipment ($)
Freight cost per shipment — lower is better
ShipmentSHP Performance $ ≤$600 ≤$800 ≤$1K
D
Monthly Freight Spend ($)
Monthly freight spend vs budget
ShipmentSHP Performance $ ≤$25K ≤$35K ≤$50K
D
Schedule Adherence %
% WOs completed on or before planned end date
Supply PlanningSP T3 Scorecard % ≥95% ≥90% ≥80%
D
Labor Utilization %
Actual labor hrs / planned labor hrs
Supply PlanningSP T3 Scorecard % ≥95% ≥90% ≥85%
D
MRP Adherence %
% MRP actions (PO/WO/PR) executed on time
Supply PlanningSP T3 Scorecard % ≥95% ≥90% ≥80%
D
Min/Max Compliance %
% materials with DOH between safety stock and max
Supply PlanningSP T3 Scorecard % ≥95% ≥90% ≥80%
D
RTE Index %
Composite readiness — min of 7 Smartsheet milestones
Supply PlanningSP T3 Scorecard % ≥95% ≥85% ≥70%
D
Scrap as % of Sales
Total scrap USD / net revenue — lower is better
Supply PlanningSP T3 Scorecard % ≤0% ≤1% ≤3%
D
Cost Per Transaction ($)
Total WH cost / total transactions
WarehousingWH Cost CI $ ≤$2.5 ≤$3.5 ≤$5
D
WH Labor Utilization %
Productive hours / scheduled hours
WarehousingWH Cost CI % ≥92% ≥87% ≥80%
D
CI Savings ($)
Annual CI project savings realized
WarehousingWH Cost CI $ ≥$500K ≥$350K ≥$200K
D
Process Waste %
Lower is better — rework/waste/errors
WarehousingWH Cost CI % ≤2% ≤4% ≤7%
D
Cycle Count Accuracy %
% items counted matching system quantity
WarehousingWH Inventory % ≥100% ≥99% ≥97%
D
Inventory Turns (x/yr)
COGS / average inventory value
WarehousingWH Inventory x/yr ≥3.5 ≥2.5 ≥1.8
D
Storage Utilization %
Target 75-85% — too high = congestion risk
WarehousingWH Inventory % ≤82% ≤88% ≤93%
D
Stockout Rate %
Lower is better — % locations at stockout
WarehousingWH Inventory % ≤1% ≤3% ≤6%
D
Dock-to-Stock Time (Hrs)
Lower is better — total dock-to-QA-release hours
WarehousingWH Operations Hrs ≤36 ≤48 ≤72
D
WO Fill Rate %
% work orders filled on time and in full
WarehousingWH Operations % ≥98% ≥95% ≥88%
D
WO Pick Accuracy %
% picks without error
WarehousingWH Operations % ≥100% ≥100% ≥98%
D
Units / Labor Hr
Units picked per productive labor hour
WarehousingWH Operations units/hr ≥12 ≥10 ≥8
C
Approved Capex
Headline context: approved capital budget.
FinancialCapital Allocation & Investment Discipline $M
C
Committed Capex
Headline context: purchase commitments and obligated capital.
FinancialCapital Allocation & Investment Discipline $M
C
Capex Actuals
Headline context: capital actual spend.
FinancialCapital Allocation & Investment Discipline $M
C
Capex Eac / Forecast
Headline context: capital estimate at completion or latest forecast.
FinancialCapital Allocation & Investment Discipline $M
C
CAPEX to Budget
CAPEX actuals or EAC / approved CAPEX budget.
FinancialCapital Allocation & Investment Discipline % ≤95% ≤100% ≤105%
C
CAPEX Forecast Accuracy
Accuracy of capital forecast versus actuals/EAC.
FinancialCapital Allocation & Investment Discipline % ≥95% ≥90% ≥85%
C
EAC Variance %
Capital EAC variance versus approved budget. Positive/favorable variance is better.
FinancialCapital Allocation & Investment Discipline % ≥0% ≥-3% ≥-7%
C
Approved vs Committed Spend
Committed CAPEX / approved CAPEX.
FinancialCapital Allocation & Investment Discipline % ≤95% ≤100% ≤105%
C
Benefit Realization %
Realized financial benefit / planned benefit.
FinancialCapital Allocation & Investment Discipline % ≥95% ≥85% ≥70%
C
ROI / Payback
ROI or payback performance versus business case target.
FinancialCapital Allocation & Investment Discipline Index ≥1 ≥0.85 ≥0.7
C
Capital Project On-Time %
Capital projects delivered on or before planned milestone/end date.
FinancialCapital Allocation & Investment Discipline % ≥90% ≥80% ≥70%
C
Capital Project On-Budget %
Capital projects forecasted or completed on/below approved budget.
FinancialCapital Allocation & Investment Discipline % ≥90% ≥80% ≥70%
C
Spend at Risk
Percent of capital spend at schedule, budget, approval, or benefit-realization risk.
FinancialCapital Allocation & Investment Discipline % ≤5% ≤10% ≤20%
C
Forecasted Benefit vs Plan
Forecasted financial benefit / planned benefit.
FinancialCapital Allocation & Investment Discipline % ≥95% ≥85% ≥70%
C
Inventory Value
Headline context: total inventory carrying value.
FinancialCash & Working Capital Efficiency $M
C
AR Balance
Headline context: accounts receivable balance.
FinancialCash & Working Capital Efficiency $M
C
Past Due AR
Headline context: past-due receivables exposure.
FinancialCash & Working Capital Efficiency $M
C
Working Capital Exposure
Headline context: inventory + receivables + WIP/unbilled exposure.
FinancialCash & Working Capital Efficiency $M
C
Inventory Value vs Target
Actual inventory value / target inventory value.
FinancialCash & Working Capital Efficiency % ≤100% ≤105% ≤110%
C
Inventory Turns
COGS / average inventory value.
FinancialCash & Working Capital Efficiency Turns ≥4 ≥3 ≥2
C
DSO
Days sales outstanding.
FinancialCash & Working Capital Efficiency Days ≤45 ≤55 ≤65
C
AR >60 Days %
AR balance greater than 60 days past due / total AR.
FinancialCash & Working Capital Efficiency % ≤5% ≤10% ≤15%
C
Cash Conversion Cycle
DIO + DSO - DPO. Validate source units before executive use.
FinancialCash & Working Capital Efficiency Days ≤45 ≤60 ≤75
C
Past Due AR %
Past-due AR / total AR balance.
FinancialCash & Working Capital Efficiency % ≤5% ≤10% ≤15%
C
DIO
Days inventory outstanding.
FinancialCash & Working Capital Efficiency Days ≤45 ≤60 ≤75
C
DPO
Days payable outstanding. Higher can be favorable if supplier terms remain healthy.
FinancialCash & Working Capital Efficiency Days ≥60 ≥45 ≥30
C
WIP / Unbilled Revenue
WIP/unbilled revenue as percent of revenue or working capital exposure.
FinancialCash & Working Capital Efficiency % ≤5% ≤10% ≤15%
C
Excess / Obsolete Inventory
Excess and obsolete inventory / total inventory.
FinancialCash & Working Capital Efficiency % ≤3% ≤7% ≤12%
C
COGS $
Headline context: cost of goods sold dollars.
FinancialCost Discipline & Spend Control $M
C
OPEX $
Headline context: operating expense dollars.
FinancialCost Discipline & Spend Control $M
C
OPEX Budget $
Headline context: budgeted OPEX dollars.
FinancialCost Discipline & Spend Control $M
C
Spend Variance $
Budget spend minus actual spend; positive is favorable.
FinancialCost Discipline & Spend Control $M
C
COGS %
COGS / revenue.
FinancialCost Discipline & Spend Control % ≤50% ≤60% ≤70%
C
OPEX to Budget
Actual OPEX / budget OPEX.
FinancialCost Discipline & Spend Control % ≤95% ≤100% ≤105%
C
Spend Variance %
Spend variance as a percent of budget spend. Positive/favorable variance is better.
FinancialCost Discipline & Spend Control % ≥0% ≥-3% ≥-7%
C
Cost per Batch
Actual cost per batch / target cost per batch.
FinancialCost Discipline & Spend Control Index ≤1 ≤1.05 ≤1.1
C
COGS to Budget
Actual COGS / budget COGS.
FinancialCost Discipline & Spend Control % ≤95% ≤100% ≤105%
C
Labor Cost %
Labor cost as percent of revenue or total cost.
FinancialCost Discipline & Spend Control % ≤25% ≤30% ≤35%
C
Material Cost Variance
Material cost variance versus standard/budget. Positive/favorable variance is better.
FinancialCost Discipline & Spend Control % ≥0% ≥-3% ≥-7%
C
Indirect Spend to Budget
Indirect spend / indirect spend budget.
FinancialCost Discipline & Spend Control % ≤95% ≤100% ≤105%
C
Budget Burn Rate
Actual spend consumption rate compared to planned budget burn.
FinancialCost Discipline & Spend Control % ≤95% ≤100% ≤105%
C
Financial WPI
Overall weighted financial performance index on the standard 1-4 WPI scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Revenue Performance
Financial WPI area score on the standard 1-4 scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Forecast Reliability
Financial WPI area score on the standard 1-4 scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Profitability & Margin Health
Financial WPI area score on the standard 1-4 scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Cost Discipline & Spend Control
Financial WPI area score on the standard 1-4 scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Cash & Working Capital Efficiency
Financial WPI area score on the standard 1-4 scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Productivity & Operating Leverage
Financial WPI area score on the standard 1-4 scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Capital Allocation & Investment Discipline
Financial WPI area score on the standard 1-4 scale: >=3 Exceeds, >=2 Meets, >=1 Partial, <1 DNM.
FinancialFinancial Performance WPI 1-4 ≥3 ≥2 ≥1
C
Current Forecast Revenue
Headline context: current forecast revenue.
FinancialForecast Reliability $M
C
Actual Revenue
Headline context: actual revenue for comparison to forecast.
FinancialForecast Reliability $M
C
Forecast Variance $
Actual revenue minus forecast revenue.
FinancialForecast Reliability $M
C
Prior Forecast Revenue
Prior forecast version revenue used to assess forecast stability.
FinancialForecast Reliability $M
C
Revenue Forecast Accuracy
Revenue forecast accuracy: 1 - ABS(actual - forecast) / actual.
FinancialForecast Reliability % ≥95% ≥90% ≥85%
C
Forecast Bias %
Absolute forecast bias percentage. Use signed bias separately for directionality.
FinancialForecast Reliability % ≤2% ≤5% ≤10%
C
Forecast Reliability Score
Weighted forecast reliability score.
FinancialForecast Reliability % ≥95% ≥90% ≥80%
C
Forecast Revision Rate
Magnitude or frequency of forecast changes across forecast versions.
FinancialForecast Reliability % ≤5% ≤10% ≤20%
C
Forecast Accuracy by Client
Forecast accuracy evaluated across client/customer dimension.
FinancialForecast Reliability % ≥95% ≥90% ≥85%
C
EBITDA Forecast Accuracy
EBITDA forecast accuracy: 1 - ABS(actual EBITDA - forecast EBITDA) / actual EBITDA.
FinancialForecast Reliability % ≥95% ≥90% ≥85%
C
Total Fte
Headline context: total FTE/headcount supporting revenue generation.
FinancialProductivity & Operating Leverage FTE
C
Productive Hours
Headline context: productive/billable labor hours.
FinancialProductivity & Operating Leverage Hours
C
Labor Cost $
Headline context: total labor cost dollars.
FinancialProductivity & Operating Leverage $M
C
Revenue $
Headline context: revenue base for productivity ratios.
FinancialProductivity & Operating Leverage $M
C
Revenue per Employee
Revenue / average FTE.
FinancialProductivity & Operating Leverage $M/FTE ≥$0.5 ≥$0.4 ≥$0.3
C
Gross Profit per FTE
Gross profit / average FTE.
FinancialProductivity & Operating Leverage $M/FTE ≥$0.2 ≥$0.15 ≥$0.1
C
Productive Utilization %
Productive or billable labor hours / available labor hours.
FinancialProductivity & Operating Leverage % ≥85% ≥80% ≥70%
C
Labor Cost %
Labor cost as percent of revenue or total cost.
FinancialProductivity & Operating Leverage % ≤25% ≤30% ≤35%
C
EBITDA per FTE
EBITDA / average FTE.
FinancialProductivity & Operating Leverage $M/FTE ≥$0.12 ≥$0.1 ≥$0.08
C
Revenue per Productive Hour
Revenue / productive labor hours.
FinancialProductivity & Operating Leverage $/Hour ≥250 ≥200 ≥150
C
FTE to Budget
Actual FTE / budget FTE.
FinancialProductivity & Operating Leverage % ≤95% ≤100% ≤105%
C
Operating Leverage Ratio
Revenue or gross profit growth relative to operating cost/FTE growth.
FinancialProductivity & Operating Leverage Ratio ≥1.2 ≥1 ≥0.8
C
Labor Efficiency Variance
Labor efficiency variance versus standard/budget. Positive/favorable variance is better.
FinancialProductivity & Operating Leverage % ≥0% ≥-3% ≥-7%
C
Revenue $
Headline context: revenue base supporting margin performance.
FinancialProfitability & Margin Health $M
C
COGS $
Headline context: cost of goods sold dollars.
FinancialProfitability & Margin Health $M
C
OPEX $
Headline context: operating expense dollars.
FinancialProfitability & Margin Health $M
C
Ebitda $
Headline context: earnings before interest, taxes, depreciation, and amortization.
FinancialProfitability & Margin Health $M
C
Contribution Margin %
Contribution margin dollars / revenue.
FinancialProfitability & Margin Health % ≥45% ≥40% ≥35%
C
Gross Profit Margin
Gross profit / revenue.
FinancialProfitability & Margin Health % ≥35% ≥30% ≥25%
C
EBITDA %
EBITDA / revenue.
FinancialProfitability & Margin Health % ≥30% ≥25% ≥20%
C
Net Profit Margin
Net profit / revenue.
FinancialProfitability & Margin Health % ≥20% ≥15% ≥10%
C
Margin Variance %
Margin variance as a percent of budget/target margin.
FinancialProfitability & Margin Health % ≥0% ≥-3% ≥-7%
C
EBITDA to Budget
Actual EBITDA / budget EBITDA.
FinancialProfitability & Margin Health % ≥105% ≥100% ≥95%
C
Client / Program Margin
Margin performance at client/program level.
FinancialProfitability & Margin Health % ≥35% ≥30% ≥25%
C
Margin Leakage
Estimated preventable margin leakage due to rework, scrap, discounting, or scope creep.
FinancialProfitability & Margin Health % ≤1% ≤3% ≤5%
C
Actual Revenue
Headline context: actual revenue for the selected period.
FinancialRevenue Performance $M
C
Budget Revenue
Headline context: budget revenue for the selected period.
FinancialRevenue Performance $M
C
Forecast Revenue
Headline context: latest forecast revenue for the selected period.
FinancialRevenue Performance $M
C
Revenue Variance $
Headline context: actual revenue minus budget revenue.
FinancialRevenue Performance $M
C
Revenue to Budget
Actual revenue / budget revenue.
FinancialRevenue Performance % ≥105% ≥99% ≥95%
C
Revenue Plan-to-Performance
Actual revenue compared to planned performance target.
FinancialRevenue Performance % ≥105% ≥99% ≥95%
C
Book-to-Bill Ratio
Bookings divided by billings/revenue. Leading indicator of future revenue coverage.
FinancialRevenue Performance Ratio ≥1.1 ≥1 ≥0.9
C
Revenue Variance %
Revenue variance as a percent of budget revenue.
FinancialRevenue Performance % ≥0% ≥-3% ≥-7%
C
Revenue Forecast Accuracy
Revenue forecast accuracy: 1 - ABS(actual revenue - forecast revenue) / actual revenue.
FinancialRevenue Performance % ≥95% ≥90% ≥85%
C
Absolute Forecast Bias %
Absolute revenue forecast bias percentage. Lower is better; signed bias is retained separately for directionality.
FinancialRevenue Performance % ≤2% ≤5% ≤10%
C
Cost
Pillar weight = sum of T1_Equipment_Downtime + T1_Overdue_Issues + T1_Overdue_Alarms weights
MFG T1 Suite ScorecardMFG T1 PSQDC Map Pillar
I
Qualified Pipeline Coverage
Qualified opportunities / required qualified opportunities.
InnovationNPI Portfolio + Value % ≥120% ≥100% ≥85%
I
NPI Success Rate
Successfully launched/transferred NPIs / NPIs due.
InnovationNPI Portfolio + Value % ≥95% ≥90% ≥80%
I
Vitality Index
Revenue from programs introduced within 36 months / total site revenue.
InnovationNPI Portfolio + Value % ≥30% ≥25% ≥20%
I
Treatment Enablement
Actual treatment equivalents enabled YTD / time-phased plan YTD.
InnovationNPI Portfolio + Value % ≥105% ≥95% ≥85%
I
Opportunity Conversion
Approved opportunities / opportunities due for decision.
InnovationNPI Portfolio + Value % ≥50% ≥40% ≥30%
I
NPI Launch On Time
NPIs launched/transferred by committed date.
InnovationNPI Portfolio + Value % ≥95% ≥90% ≥80%
I
NPI Right First Time
First-pass technical/GMP/PPQ acceptance.
InnovationNPI Portfolio + Value % ≥98% ≥95% ≥90%
I
NPI Handoff Success
Operational handoff accepted without critical open items.
InnovationNPI Portfolio + Value % ≥98% ≥95% ≥90%
I
NPI Revenue Growth
Year-over-year revenue growth from recent NPI programs.
InnovationNPI Portfolio + Value % ≥15% ≥10% ≥5%
I
Schedule Performance
% projects on or ahead of baseline/forecast commitment.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Financial Performance
% financially managed projects with EAC <= approved budget.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Execution Quality
Gate/milestone deliverables accepted right first time.
InnovationProject Portfolio Performance % ≥98% ≥95% ≥90%
I
Forecast Reliability
Average of cost and schedule forecast accuracy.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Value Realization
Projects meeting approved business-case target / projects due for review.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Risk and Recovery
Composite of projects not at risk, recovery plans on track, and mitigation timeliness.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Schedule Adherence
Milestones completed on or before baseline date.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Late Milestones
Open critical milestones past baseline/forecast date.
InnovationProject Portfolio Performance Count ≤0 ≤2 ≤5
I
Average Variance Days
Average forecast/actual finish variance versus baseline.
InnovationProject Portfolio Performance Days ≤0 ≤5 ≤10
I
Budget Variance %
Adverse EAC variance as percent of approved budget; lower is better.
InnovationProject Portfolio Performance % ≤0% ≤5% ≤10%
I
Gate/Milestone RFT
Deliverables accepted without rework.
InnovationProject Portfolio Performance % ≥98% ≥95% ≥90%
I
Overdue Actions
Open project actions past due date.
InnovationProject Portfolio Performance Count ≤0 ≤3 ≤8
I
Handoff Success
Completed projects accepted into operations without critical open items.
InnovationProject Portfolio Performance % ≥98% ≥95% ≥90%
I
Cost Forecast Accuracy
Prior cost forecast compared with subsequent actual.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Schedule Forecast Accuracy
Prior forecast finish compared with actual/updated finish.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
EAC Change MoM
Absolute month-over-month EAC movement.
InnovationProject Portfolio Performance % ≤2% ≤5% ≤10%
I
On-Time Value Realization
Business-case benefit achieved by committed review date.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
At-Risk Project Rate
Active projects classified at risk.
InnovationProject Portfolio Performance % ≤5% ≤10% ≤20%
I
Recovery Plan On Track
Required recovery plans currently on track.
InnovationProject Portfolio Performance % ≥95% ≥90% ≥80%
I
Overdue Mitigations
Open mitigation actions past their committed due date.
InnovationProject Portfolio Performance Count ≤0 ≤2 ≤5
I
Strategic Fit
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
ROI
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
Savings
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
Cost Feasibility
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
Time to Value
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
Resource Feasibility
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
Innovation Value
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
Regulatory Need / Risk
Criterion score and approved prioritization weight. Higher scores are more favorable or more urgent.
InnovationProject Prioritization 1/3/9 ≥9 ≥3 ≥1
I
Overall Project Priority Score
Weighted average of the eight approved criterion scores; used for ranking, not execution WPI.
InnovationProject Prioritization 1-9 ≥7.5 ≥6 ≥4
I
Prioritization Coverage
Projects with all eight approved criterion scores / projects in selected portfolio.
InnovationProject Prioritization % ≥100% ≥95% ≥85%
Digital Architecture
From field devices to executive analytics — a connected data and system architecture for regulated manufacturing
Analytics Layer
Enterprise Layer
Execution Layer
SCADA Control Layer
Data Analytics & Business Intelligence (Power BI / Tableau / AI Insights)
Data Lake / Data Warehouse
Data Integration Layer (API / ETL / iPaaS)
⬇ ⬆
Enterprise Layer
Enterprise Requirements Planning (ERP)
Customer Relationship Management (CRM)
HR Management System (HRMS)
⬇ ⬆
Execution Layer
Manufacturing Execution System (MES)
Laboratory Information Management System (LIMS)
Warehouse Management System (WMS)
Quality Management System (QMS)
EHS Management System (EHSMS)
Maintenance Management System (CMMS)
Electronic Logbooks & Batch Records
⬇ ⬆
SCADA Control Layer
Field Devices
Programmable Logic Controllers (PLCs)
Data Acquisition / Visualization (SCADA / HMI)
Historian Database
📊 Level 1 — Excel / Flat File

Start with structured Excel imports. Dashboards can be built from weekly/monthly data exports with manual upload workflows — no integration required to get started.

🔗 Level 2 — API + Database Integration

Connect directly to ERP, LIMS, MES, and QMS via API or ODBC. Real-time or near-real-time KPI feeds with governed data definitions and automated refresh.

🤖 Level 3 — Fully Integrated + AI-Enabled

Full data lake integration with AI-supported insights, anomaly detection, predictive analytics, and automated escalation workflows built on the complete digital architecture above.

Digital Maturity Assessment
Where Are You Today? Where Should You Go Next?

The Actionable Insights can be deployed at any point on the digital maturity spectrum — from basic Excel imports to fully integrated SW applications. An assessment of the existing digital architecture identifies gaps, prioritizes integrations by value, and provides a phased implementation roadmap aligned to business priorities.

📁

Current State Mapping

Inventory all existing data sources, system connections, and manual processes. Identify which KPIs can be automated vs. manual.

🎯

Priority Integration Sequencing

Rank integrations by KPI coverage, data quality, and implementation effort. Build the business case for each integration step.

🗺️

Implementation Roadmap

Phased plan: quick wins (Excel/CSV), mid-term (API integrations), long-term (data lake + AI-enabled analytics).

AI + Digital Readiness
From Manual Reporting to Governed, Scalable, AI-Enabled Operations

AI readiness in performance intelligence is not primarily a technology question — it is a data governance, process discipline, and organizational readiness question. The maturity model below defines the four levels, what each looks like in practice, and what is required to advance to the next level.

Level 1

Manual Reporting

KPIs are tracked in spreadsheets. Data is manually compiled for reviews. Inconsistent definitions. No automated refresh. Insights require interpretation by data owners before each meeting.

Level 2

Structured Dashboards

Dashboards exist with defined KPIs, owned thresholds, and regular refresh — whether from Excel imports or live connections. Performance is visible. Escalation is defined but still manual.

Level 3

Governed Performance Intelligence

KPI architecture is governed: ownership, thresholds, escalation rules, action workflows. Tiered dashboards connect site → dept → individual. WPI scores enable cross-metric prioritization. Alerts trigger automatically.

Level 4

AI-Enabled Operations

AI-supported key takeaways, trend detection, anomaly flagging, and recommended actions are generated from live data. Predictive analytics anticipate performance risks. The dashboard conversation shifts from "what happened?" to "what should we do?"

DimensionLevel 1 — ManualLevel 2 — DashboardsLevel 3 — GovernedLevel 4 — AI-Enabled
Data SourceManual Excel entryExcel imports / flat filesLive API connectionsFull data lake + real-time streaming
KPI DefinitionVaries by ownerDefined per dashboardGoverned master KPI libraryGoverned + ML-enhanced definitions
Refresh CadenceWeekly / monthly manualWeekly / daily automatedDaily / near-real-timeReal-time with predictive projection
EscalationManager judgmentThreshold colors visibleAutomated alerts + owner assignmentPredictive escalation before threshold breach
AI CapabilityNoneNoneBasic trend + anomaly detectionKey takeaways, recommendations, natural language query
I²nnovate Entry Point✓ Start here✓ Most common start✓ Target state year 1–2✓ Target state year 2–3
Manufacturing
T3
Right First Time %
MFG Performance
Right First Time % vs. targetPeriod, mfg, trend%≥97%≥93%≥87%
T3
On Time Delivery %
MFG Performance
On Time Delivery % vs. targetPeriod, mfg, trend%≥97%≥92%≥85%
T3
OEE %
MFG Performance
OEE % vs. targetPeriod, mfg, trend%≥83%≥70%≥55%
T3
OEE Availability %
MFG Performance
OEE Availability % vs. targetPeriod, mfg, trend%≥92%≥88%≥82%
T3
OEE Performance %
MFG Performance
OEE Performance % vs. targetPeriod, mfg, trend%≥97%≥93%≥88%
T3
OEE Quality %
MFG Performance
OEE Quality % vs. targetPeriod, mfg, trend%≥97%≥95%≥90%
T3
Utilized Hours %
MFG Performance
Utilized Hours % vs. targetPeriod, mfg, trend%≥85%≥80%≥70%
T3
Batch Cycle Time (days)
MFG Performance
Batch Cycle Time (days) vs. targetPeriod, mfg, trenddays120145160
T3
Capacity Utilization %
MFG Performance
Capacity Utilization % vs. targetPeriod, mfg, trend%≥88%≥80%≥65%
T3
WPI Exceeds Threshold
MFG WPI
WPI Exceeds Threshold vs. targetPeriod, mfg, trend1-43
T3
WPI Meets Threshold
MFG WPI
WPI Meets Threshold vs. targetPeriod, mfg, trend1-42
T3
WPI Partial Threshold
MFG WPI
WPI Partial Threshold vs. targetPeriod, mfg, trend1-41.01
T3
Changeover %
Manufacturing Downtime Analysis
Changeover % vs. targetPeriod, mfg, trend%≥5%≥10%≥20%
T3
Idle %
Manufacturing Downtime Analysis
Idle % vs. targetPeriod, mfg, trend%≥5%≥10%≥20%
T1
Training Compliance %
MFG T1 PSQDC
Training Compliance % vs. targetPeriod, mfg, trend%≥98%≥95%≥90%
Procurement
T3
Perfect Receipt %
Proc Summary
Perfect Receipt % vs. targetPeriod, procurement, trend%≥97%≥93%≥85%
T3
On Time Receipt %
Perfect Receipt
On Time Receipt % vs. targetPeriod, procurement, trend%≥97%≥93%≥85%
T3
In Full Receipt %
Perfect Receipt
In Full Receipt % vs. targetPeriod, procurement, trend%≥98%≥95%≥88%
T3
Document Accuracy %
Perfect Receipt
Document Accuracy % vs. targetPeriod, procurement, trend%≥100%≥98%≥95%
T3
Damage Free Receipt %
Perfect Receipt
Damage Free Receipt % vs. targetPeriod, procurement, trend%≥99%≥98%≥95%
T3
MRP Schedule Adherence %
MRP Adherence
MRP Schedule Adherence % vs. targetPeriod, procurement, trend%≥99%≥98%≥95%
T3
PR Behind Need to Release %
MRP Adherence
PR Behind Need to Release % vs. targetPeriod, procurement, trend%≥2%≥5%≥10%
T3
PO Behind Need to Place %
MRP Adherence
PO Behind Need to Place % vs. targetPeriod, procurement, trend%≥2%≥5%≥10%
T3
MRP Non-Support Prior %
MRP Adherence
MRP Non-Support Prior % vs. targetPeriod, procurement, trend%≥1%≥2%≥5%
T3
MRP Non-Support Future %
MRP Adherence
MRP Non-Support Future % vs. targetPeriod, procurement, trend%≥2%≥5%≥10%
T3
Procurement Efficiency %
Proc Efficiency
Procurement Efficiency % vs. targetPeriod, procurement, trend%≥92%≥85%≥75%
T3
Procurement Throughput %
Proc Efficiency
Procurement Throughput % vs. targetPeriod, procurement, trend%≥90%≥80%≥70%
T3
PR to PO Cycle Time %
Proc Efficiency
PR to PO Cycle Time % vs. targetPeriod, procurement, trend%≥90%≥82%≥72%
T3
Process Quality %
Proc Efficiency
Process Quality % vs. targetPeriod, procurement, trend%≥95%≥88%≥78%
T3
Spend on Contract %
Proc Efficiency
Spend on Contract % vs. targetPeriod, procurement, trend%≥88%≥78%≥65%
Supply Planning
T3
Schedule Adherence %
SP T3 Scorecard
Schedule Adherence % vs. targetPeriod, supply, trend%≥95%≥90%≥80%
T3
Labor Utilization %
SP T3 Scorecard
Labor Utilization % vs. targetPeriod, supply, trend%≥95%≥90%≥85%
T3
MRP Adherence %
SP T3 Scorecard
MRP Adherence % vs. targetPeriod, supply, trend%≥95%≥90%≥80%
T3
Min/Max Compliance %
SP T3 Scorecard
Min/Max Compliance % vs. targetPeriod, supply, trend%≥95%≥90%≥80%
T3
RTE Index %
SP T3 Scorecard
RTE Index % vs. targetPeriod, supply, trend%≥95%≥85%≥70%
T3
Scrap as % of Sales
SP T3 Scorecard
Scrap as % of Sales vs. targetPeriod, supply, trend%≥0%≥1%≥3%
T3
Inventory MOS — Low Threshold
SP T3 Scorecard
Inventory MOS — Low Threshold vs. targetPeriod, supply, trendMO12108
T3
Inventory MOS — High Threshold
SP T3 Scorecard
Inventory MOS — High Threshold vs. targetPeriod, supply, trendMO141620
T3
Active Clients Exceeds
SP T3 Scorecard
Active Clients Exceeds vs. targetPeriod, supply, trend#35
T3
Active Clients Meets
SP T3 Scorecard
Active Clients Meets vs. targetPeriod, supply, trend#25
T3
Active Clients Partial
SP T3 Scorecard
Active Clients Partial vs. targetPeriod, supply, trend#15
T3
WPI Exceeds Threshold
SP WPI
WPI Exceeds Threshold vs. targetPeriod, supply, trend1-43
T3
WPI Meets Threshold
SP WPI
WPI Meets Threshold vs. targetPeriod, supply, trend1-42.5
T3
WPI Partial Threshold
SP WPI
WPI Partial Threshold vs. targetPeriod, supply, trend1-41.5
Warehousing
T3
Dock-to-Stock Time (Hrs)
WH Operations
Dock-to-Stock Time (Hrs) vs. targetPeriod, warehousing, trendHrs364872
T3
WO Fill Rate %
WH Operations
WO Fill Rate % vs. targetPeriod, warehousing, trend%≥98%≥95%≥88%
T3
WO Pick Accuracy %
WH Operations
WO Pick Accuracy % vs. targetPeriod, warehousing, trend%≥100%≥100%≥98%
T3
Units / Labor Hr
WH Operations
Units / Labor Hr vs. targetPeriod, warehousing, trendunits/hr12108
T3
Cycle Count Accuracy %
WH Inventory
Cycle Count Accuracy % vs. targetPeriod, warehousing, trend%≥100%≥99%≥97%
T3
Inventory Turns (x/yr)
WH Inventory
Inventory Turns (x/yr) vs. targetPeriod, warehousing, trendx/yr3.52.51.8
T3
Storage Utilization %
WH Inventory
Storage Utilization % vs. targetPeriod, warehousing, trend%≥82%≥88%≥93%
T3
Stockout Rate %
WH Inventory
Stockout Rate % vs. targetPeriod, warehousing, trend%≥1%≥3%≥6%
T3
Cost Per Transaction ($)
WH Cost CI
Cost Per Transaction ($) vs. targetPeriod, warehousing, trend$2.53.55
T3
WH Labor Utilization %
WH Cost CI
WH Labor Utilization % vs. targetPeriod, warehousing, trend%≥92%≥87%≥80%
T3
CI Savings ($)
WH Cost CI
CI Savings ($) vs. targetPeriod, warehousing, trend$500000350000200000
T3
Process Waste %
WH Cost CI
Process Waste % vs. targetPeriod, warehousing, trend%≥2%≥4%≥7%
T3
WPI Exceeds Threshold
WH WPI
WPI Exceeds Threshold vs. targetPeriod, warehousing, trend1-43
T3
WPI Meets Threshold
WH WPI
WPI Meets Threshold vs. targetPeriod, warehousing, trend1-42
T3
WPI Partial Threshold
WH WPI
WPI Partial Threshold vs. targetPeriod, warehousing, trend1-41.01
Demand Planning
T3
Revenue PTP %
DP T3 Scorecard
Revenue PTP % vs. targetPeriod, demand, trend%≥105%≥98%≥90%
T3
Secured Revenue vs Plan
DP T3 Scorecard
Secured Revenue vs Plan vs. targetPeriod, demand, trend%≥105%≥95%≥85%
T3
Forecast Accuracy %
DP T3 Scorecard
Forecast Accuracy % vs. targetPeriod, demand, trend%≥95%≥90%≥85%
T3
Book to Bill Ratio
DP T3 Scorecard
Book to Bill Ratio vs. targetPeriod, demand, trendx1.110.9
T3
Capacity Utilization %
DP T3 Scorecard
Capacity Utilization % vs. targetPeriod, demand, trend%≥85%≥70%≥50%
T3
Pipeline P75 Probability Factor
DP Badge
Pipeline P75 Probability Factor vs. targetPeriod, demand, trendfactor0.75
T3
Pipeline P50 Probability Factor
DP Badge
Pipeline P50 Probability Factor vs. targetPeriod, demand, trendfactor0.5
T3
Prospecting Probability Factor
DP Badge
Prospecting Probability Factor vs. targetPeriod, demand, trendfactor0.25
T3
Q Badge Current Threshold
DP Badge
Q Badge Current Threshold vs. targetPeriod, demand, trend%≥95%≥85%≥70%
T3
Q Badge +1Q Threshold
DP Badge
Q Badge +1Q Threshold vs. targetPeriod, demand, trend%≥90%≥80%≥65%
T3
Q Badge +2Q Threshold
DP Badge
Q Badge +2Q Threshold vs. targetPeriod, demand, trend%≥85%≥75%≥60%
T3
Q Badge +3Q Threshold
DP Badge
Q Badge +3Q Threshold vs. targetPeriod, demand, trend%≥80%≥70%≥55%
T3
Q Target Current ($)
DP Badge
Q Target Current ($) vs. targetPeriod, demand, trend$15000000
T3
Q Target +1Q ($)
DP Badge
Q Target +1Q ($) vs. targetPeriod, demand, trend$14000000
T3
Q Target +2Q ($)
DP Badge
Q Target +2Q ($) vs. targetPeriod, demand, trend$13000000
Engineering & Reliability
T3
PM Compliance %
PM Compliance
PM Compliance % vs. targetPeriod, engineering, trend%≥98%≥95%≥88%
T3
Schedule Adherence
PM Compliance
Schedule Adherence vs. targetPeriod, engineering, trend%≥98%≥95%≥88%
T3
Overdue Rate
PM Compliance
Overdue Rate vs. targetPeriod, engineering, trend%≥2%≥5%≥10%
T3
Resource Utilization
PM Compliance
Resource Utilization vs. targetPeriod, engineering, trend%≥90%≥85%≥80%
T3
MTTR (hrs)
PM Compliance
MTTR (hrs) vs. targetPeriod, engineering, trendhrs235
T3
On Hold WO Count
PM Compliance
On Hold WO Count vs. targetPeriod, engineering, trendCount25
T3
Unassigned WO Count
PM Compliance
Unassigned WO Count vs. targetPeriod, engineering, trendCount25
T3
WPI CMMS Exceeds
PM Compliance
WPI CMMS Exceeds vs. targetPeriod, engineering, trendIndex333
T3
WPI CMMS Meets
PM Compliance
WPI CMMS Meets vs. targetPeriod, engineering, trendIndex22.52.5
T3
WPI CMMS Partial
PM Compliance
WPI CMMS Partial vs. targetPeriod, engineering, trendIndex1.011.51.5
T3
Weighted Performance Index
Corrective Maintenance
Weighted Performance Index vs. targetPeriod, engineering, trend1-432.51.5
T3
On Time Complete %
Corrective Maintenance
On Time Complete % vs. targetPeriod, engineering, trend%≥99%≥98%≥95%
T3
Overdue CM %
Corrective Maintenance
Overdue CM % vs. targetPeriod, engineering, trend%≥1%≥3%
T3
Assigned %
Corrective Maintenance
Assigned % vs. targetPeriod, engineering, trend%≥100%≥98%≥95%
T3
On Hold <30D %
Corrective Maintenance
On Hold <30D % vs. targetPeriod, engineering, trend%≥99%≥98%≥95%
T3
Project Schedule Performance %
% projects on or ahead of baseline/forecast commitment
Innovation — Project Portfolio PerformancePeriod, project, baseline vs forecast dates%≥95%≥90%≥80%
T3
Project Financial Performance %
% financially managed projects with EAC ≤ approved budget
Innovation — Project Portfolio PerformancePeriod, project, EAC vs approved budget%≥95%≥90%≥80%
T3
Gate / Milestone RFT %
Deliverables accepted right first time — no rework required at gate
Innovation — Project Portfolio PerformancePeriod, project, gate review, rework flag%≥98%≥95%≥90%
T3
Portfolio Forecast Reliability %
Average of cost and schedule forecast accuracy across project portfolio
Innovation — Project Portfolio PerformancePeriod, project, cost/schedule forecast accuracy%≥95%≥90%≥80%
T3
At-Risk Project Rate %
% active projects classified at risk — lower is better
Innovation — Project Portfolio PerformancePeriod, project, risk classification%≤5%≤10%≤20%
T3
Qualified Pipeline Coverage
Qualified NPI opportunities / required qualified opportunities
Innovation — NPI Portfolio + ValuePeriod, qualified pipeline value, target%≥120%≥100%≥85%
T3
NPI Right First Time %
First-pass technical / GMP / PPQ acceptance — quality of NPI execution
Innovation — NPI Portfolio + ValuePeriod, program, gate acceptance flag%≥98%≥95%≥90%
T3
On-Time Value Realization %
Business-case financial benefit achieved by committed review date
Innovation — Project Portfolio PerformancePeriod, project, benefit realized vs plan by date%≥95%≥90%≥80%

Ready to Build Your KPI Intelligence System?

Start with an assessment of your current architecture and KPI maturity — or discuss connecting your first dashboard.

Assess KPI Maturity   Discuss Your Scope