PiLog’s Value Engineering Webinar Series
Supply-Chain Management: MRO Inventory Optimization
Agenda – 3 Parts Webinar Series
 Introduction & Briefing on PiLog’s
Initiative
 Industry Trends & Challenges
 Earn Value Management roadmap
 Wave-1: Discovery Process
2nd Sep 2020
 Wave-2: Data Analytics / Diagnosis
 Wave-3: Process Analytics / Diagnosis
 Wave-4: Develop: Strategic Initiatives
 Wave-5: Implement: Strategic Initiatives
 Wave-6: Performance Metrics
 Wave-7: Roadmap: Automation &
Orchestration
 Question and Answers
PiLog
www.piloggroup.com
9th Sep 2020
16th Sep 2020
Takeaways
 Industry trends, current challenges &
opportunity in Inventory Optimization with
Master, Meta Data & Analytics
 Enabling Earn Value Management
SCM – Inventory Optimization
Webinar Series
 Structured Roadmap with operational visibility,
transparency and continual measurement
 Way Forward to successfully enable Digital &
Business Transformation
3
Supply Chain Management - Inventory Optimization
Session # 01
Industry 4.0
$ $ $ DATA leads the way in the
trends…
Industry 4.0
Industry 3.0
Industry 2.0
Industry 1.0
PiLog 08-02-2024
Mechanization,
Weaving loom, Water
& Steam power
Electrical Energy,
Mass production,
Assembly line,
Skills/Resource
division
~1784
~1870
www.piloggroup.com
Electronics, PLC,
Computers,
Industrial
Automation,
Hardware integration
~1969
Autonomous Systems,
Smart Enterprises,
BIG Data, IOT, AI,
ML, RPA, Process,
Data & Software
Integration
(Orchestration),
Data HUB
~2011
5
Industry 4.0 [Data & Analytics Trends]
Data and Analytics Investment Leads New Digital
Transformation for CIOs
“Data & Analytics investment
continues to increase”
Percentage of
Percentage of Respondents
Respondents Decreasing
Increasing Investment
Investment
Business intelligence or analytics solution
1%
Cyber/Information security
1%
Cloud services or solutions (SaaS, PaaS, etc.)
Core system improvements/transformation
Digital business initiatives (Including digital
marketing)
Customer/User experience
Artificial intelligence/Machine learning
PiLog 08-02-2024
Data and Analytics predictions through
2024
2%
10%
45%
40%
33%
31%
1%
31%
1%
29%
1%
27%
www.piloggroup.com
Source: Gartner Research
6
Anatomy of Enterprise Data
Enterprise Data
PiLog 08-02-2024
Master Data
(Business Entities)
Critical for any business operations
ERPs are fully dependent
Each Transaction is dependent
Material, Service, Vendor,
Customer, Equipment,
Finance, Employee,
Business Partner etc
Meta Data
(Business Definitions)
Data Dictionary: Definition of the data, it’s the data
defining data
Technical Dictionaries,
Taxonomies, Glossaries,
Ontologies
Transactional Data
(Business Events)
Generated out of the master data & business
processes (OLTP)
ERP, EAM, CMMS,
Operational Solutions
Analytical Data
(Business Performance)
Generated out of transactions over a period of time
(OLAP)
Analytics, Big Data,
InfoGraphics, Dashboards,
Business Intelligence
Solutions
Unstructured Data
Associated data for the business execution
E.g.: PDFs, drawings, audio, product specifications,
communication, portals
Big Data, Data Mining,
AI/ML Solutions
www.piloggroup.com
7
Key Challenges – Supply Chain Inventory Optimization
 Low adoption to latest industry technology trends and best practices
Inventory
Functions
 High impact of inventory hoarding costs on balance sheets
 Trail & Error model strategies deployment (Difficult to assess what
works & what doesn’t) enhancing great risk on business value
realization, ROI and in turn TCO
 Obsessed with modeling to determine precise inventory targets
without having right data (KRAs & KPIs Management)
 Optimized operational efficiency & effectiveness without looking at
the building blocks (Process modeling, Data – Availability,
Completeness, Accuracy, Timeliness)
PiLog 08-02-2024
www.piloggroup.com
WC
EOQ
Targets
Data
Quality
SCM Inventory
Optimization
Impact &
Risk
Strategies
Demand
Planning
8
Key Challenges – Supply Chain Inventory Optimization
•
•
•
•
•
Low adoption to latest industry technology trends and
best practices
High impact of inventory hoarding costs on balance
sheets
Trail & Error model strategies deployment (Difficult to
assess what works & what doesn’t) enhancing great risk
on business value realization, ROI and in turn TCO
Obsessed with modeling to determine precise inventory
targets without having right data (KRAs & KPIs
Management)
Optimized operational efficiency & effectiveness without
looking at the building blocks (Process modeling, Data –
Availability, Completeness, Accuracy, Timeliness)
PiLog 08-02-2024
www.piloggroup.com
Inventor
y
Function
s
WC
EOQ
Targets
Data
Quality
SCM
Inventory
Optimizatio
n
Impact
& Risk
Strategie
s
Demand
Planning
9
Value Engineering or Value Management
Value: The ratio of Function f(x) to Cost c(x)
Value Engineering: A systematic approach to improve the “value” of the product or service by analysis (or) examination of function
ROI & Strategic Goals
Analyze the Function f(x) to
 Improve the efficiency & effectiveness
 Reduce/Optimize the cost
Executive
Management
Operational
Executives
Tactical Efforts
Process /
Functional
Owners
Business Data
Stewards
Results
Top & Bottomline
Results
Strategic Performance
Metrics
Business Performance KPIs
Business Data &
Metrics
Strategy
Assessment
Operational Goals
Efficiency &
Effectiveness
Business Data
Quality
Early Warning
Stakeholders
PiLog 08-02-2024
www.piloggroup.com
Level
Focus
10
Recommended Roadmap to achieve strategic benefits
Perform Data Health,
Maturity and Criticality
Assessment
Design the strategic roadmap with impact,
risks, changes & targeted KPIs for the
implementation; focus on neutralizing the
forces that are contributing rapidly growing
working capital
Measure Business Performance &
Document the results of each
parallel strategy before rolling out
simultaneous advanced, automated
strategies
Wave-2
Wave-4
Wave-6
Wave-1
Wave-3
Wave-5
Wave-7
Initiate the Discovery
of As-Is processes,
data, systems &
technology
Analyze As-Is process model
[Descriptive, Prescriptive &
Explanatory]
Implement measurable low-risk
and high impact strategies with
proper change management &
targeted results
Orchestrate, Govern
Processes & Data;
Monitor the
performance
PiLog 08-02-2024
www.piloggroup.com
11
Wave-1: Discovery Process
 Do we have the right quality of master & meta data for effective
business insights (Analytics)
 Taxonomies, Dictionaries, Glossaries, Classifications,
Categorization, Hierarchies, Standards
 Do we have the spares criticality & it’s ranking ?
 Optimize the inventory parameters & Target EOQ
Master &
Meta Data
Analytics /
Classified
Info
Discovery
Process
 Do we have the right linkage between Equipment & it’s
associated spares?
 eBoMs, Equipment Master, Material Master
 Do we have the inventory qualified & quantified ?
 Obsolete, Incorrect, Surplus, Shortage, Redundant spares
PiLog 08-02-2024
www.piloggroup.com
Criticality
Redundant
Data
Inventory
Parameters
12
Wave-1: Discovery Process
 Do we have the historical transactional data to study the
trends, patterns of demand, sourcing & spend etc ?
 Machine Learning, AI, Descriptive Analytics, Process
modeling
 Do we have the right technology, systems & tools to manage
the processes ?
 ERP, Augmented tools, RPA, Orchestration,
Cloud/Premise, Landscape etc
 Do we have well established, result oriented matured
processes
 Descriptive, Prescriptive & Explanatory
Historical
Data
Patterns
Trends
AI/ML
Technology
Tools, ERPs
Discovery
Process
Process
Maturity
Cross
Functions
 Do we have effective & efficient processes to manage the
process dependencies ?
 Planning, Sourcing, Procurement, Maintenance,
Production & Operations
PiLog 08-02-2024
www.piloggroup.com
13
Inventory Control, Management and Optimization
• Inventory Management and Optimization are the components of inventory control.
• The overall category is ‘inventory control,’ beneath that lies inventory management and inventory optimization.
Inventory Control
Inventory Management:
Setting and achieving targets for all inventory operations.
Inventory Optimization:
Optimizing the stock of material
PiLog 08-02-2024
www.piloggroup.com
14
Inventory Control, Management and Optimization
• Inventory
Management and
Optimization are the
components of
inventory control.
• The overall category
is ‘inventory control,’
beneath that lies
inventory
management and
inventory
optimization.
PiLog 08-02-2024
www.piloggroup.com
15
Wave-1: Factors to consider for Discovery process
 Executive sponsorship & mentorship is key to success
 Stakeholder assessment with due engagement
 Mutually agreed RACI deployment & enablement
 Embark holistic model embracing success right from quick win enablement through long term
transformation journey
 Liaison & Gather accurate data from the source systems / tools with access to global teams
 Define and adopt KRAs, KPIs, Standards and other PM tools like Risk, Governance, Compliance etc. for
flawless execution
PiLog 08-02-2024
www.piloggroup.com
16
Wave-2 & 3: Data & Process Model Assessment
Data Health Assessment:
 Qualitative data management against standards & provisional reporting
 Assessment on data quality dimensions such as Completeness, Accuracy, Traceability,
Consistency, Timeliness, Availability and Validity
Process Maturity Model:
Supply Chain Maturity = f (Strategic Governance, Performance Enablement, Supply Network
Design, Supply Operations, Customer Fulfillment, Demand Management, Product Life Cycle
Management etc)
Materials & Assets Criticality:
Material Criticality = f (ABC - Spend YoY, FMSN - Pattern on consumption YoY, XYZ - Inventory
Hoarding, HML – High Medium Low, VED - Criticality & Impact, SDE – Lead time and Availability)
Equipment Criticality = f (Business, Maintenance, EHS, Statutory Requirements, MRO Inventory Data
Analysis)
PiLog’s low investment Value Analysis will enable Quick Wins to Business Transformations & Digitalization !!!
PiLog 08-02-2024
www.piloggroup.com
17
Wave-2: Data Quality Assessment
Completeness
Accuracy
Representation
Precision
Consistency
Data
Quality
Accessibility
Availability
Integrity
Timeliness
Traceability
2024/02/08
www.piloggroup.com
Validity
18
Wave-2: Data Quality Assessment
2024/02/08
www.piloggroup.com
19
Wave-2: Material Criticality Assessment
ABC Analysis
Material Criticality
VED Analysis
f (Business Criticality, Spend, Lead
time in S2P cycles, inventory
levels)
Based on Spend YoY
FMSN Analysis
Based on Criticality
& Impact
Right
Quality
Right
Place
Right
Quantity
HML Analysis
Criticality
Analysis
Based on consumption
pattern YoY
XYZ Analysis
Based on Inventory
Hoarding
Right
Time
Right
Source
Right
Price
Based on Unit cost of
Material
SDE Analysis
Based on Lead time and
Availability
Optimized Supply Chain
Wave-2: Master Data Criticality, Ranking by Equipment & Material Criticality Assessment
ECA = f(Business, Production, Maintenance, EHS, Human Capital)
Equipment Critical Assessment
OEE
OEE = Availability X Performance X
Quality
MRO Spend (% of total procurement
budget)
CoM (% of Replacement Asset Value)
20%
100%
0%
0%
0%
2
4
6
8
10
12
Workshop to
finalize
Parameters
50%
10%
0
Planning
0
2
4
6
Year
8
10
0
12
2
4
6
8
10
12
Year
Year
Categories
A (50%)
Critical
FLOC Based Maintenance
Generic
Generic
Specific
Conditional Monitoring Tools
Ex: Rotating Equipment - VMS
PiLog
B (30%)
Semi Critical Normal
C (20%)
Conditional Based Maintenance
Generic Task
List
Data collection
and Analysis
Specific Task
List
Preventive Maintenance
Generic Task
List
Hypothesis &
Recommendation
Specific Task
List
FMEA: RCM,RCA
(P&ID, PFD, Eqp maintenance History)
Review and
Approve
21
Wave-2: Effective Analytics driving efficiencies & decision making [Master & Transaction Data]
PiLog
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Wave-2: Effective Analytics driving efficiencies & decision making [Spend & Consumption Data]
PiLog
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Wave-3: Process Maturity Assessment
Sample of Supply Chain Maturity Assessment
Tailor-made Supply Chain Maturity Assessment
Supply Chain (P2I) Maturity = f (cost of procurement; cost of operations;
compliance & regulatory requirements; supplier performance
management; etc)
The weightages & factoring of parameters depends upon the
organization, its industry segment & P2I category
Unacceptable
Supply Chain
Maturity Assessment
Current Maturity
30%
Aspirations
Industry Benchmark
Compliance
25%
20%
15%
10%
EHS
5%
MRO
Spend
0%
Current State
Current Overall Maturity Score 2.0
(Current Capability)
Future State
Aspirational Maturity Score 3.0
(Strategic Initiatives)
OEE
PiLog 08-02-
Source: Gartner
www.piloggroup.com
24
Wave-3: Business Process Maturity Assessment
Acquire Documentation

SOPs / SOGs – Standard Operating Procedures /
Guidelines

Compare Prescriptive Vs Descriptive

Strategy Documents, Policies, Governance, Structures

Rationale / Explanatory Analysis

Functional & Technical documentation

System Driven Vs Manual Documented

Tools, Calculators, Formulae, Estimation Models

Analyze Workflows, Dataflows & Information Flows
wrt Business Processes
01
02
Acquire BPMN & Flow Diagrams
PiLog
Process Analysis

High-Level Process Flow at Organization Level

Detailed Individual Process Flows at Functional
Level

Detailed Process Flows with Interactions from
other functions

Detailed Information Flow Diagrams

Detailed Data Flow Diagrams
03
04
05
Facts Analysis




Diagnosis Reports
Documentation review: SOPs, Strategies for Stock
taking, Conditions, Picking & Packing etc.

Business Process Alignment Report

Stakeholders Capabilities Report
Review of exiting Inventory Parameters like Safety
Stock, Re-Order Point, Min. / Max. Levels, MRP
Parameters, Demand, Lead Times

Prescriptive Vs Descriptive Analysis Report

System Maturity Report

JIT, VMI, EOQ, KANBAN, Multi-enterprise Supply Chain

Business Network
Profile Assessment of the Stakeholders
www.piloggroup.com
Governance, Policy & Procedures Analysis Report
KPIs, KRAs, SLAs Alignment Report
Wave-4: Plan to Inventory (P2I) Strategy
Record to
Report
(R2R)
WH Planning
 Initial
Capacity
Planning
 Revalidation and
updating
of
Inventory
parameters (Safety
Stock,
Re-Order
Point, Min. / Max.
Levels,
MRP
Parameters, DLT
 SOPs,
Manuals,
Compliance
&
Regulations
PiLog 08-02-2024
Source to
Pay (S2P)
WH Setup
 Define / Refine Bin,
Rack, Open, Bulk
and
Yard
Management
Strategies
 Inventory
Forecasting
 Demand
Amalgamation
 Consumption
Patterns
 Replenishment
&
Fulfilment
Source to
Contract
(S2C)
Plan to
Produce
(Pl2P)
Storage
Conditions
Right
inventory
strategy like FIFO,
LIFO, LILO
Set conditions for DG
handling and abiding
to Statutory and EHS
requirements
Testing bulk storage
Audit schedule plan,
execution
Plan to
Inventory
(P2I)
Goods
Receipt
Define / Refine Put
away Strategies
 First in First Out
(FIFO)
 Last in First Out
(LIFO)
 Fixed Storage Bin
 Shelf
Life
Expiration
Date
(SLED)
 Batch
Management
 Partial Quantities
 Having right tools
and resources
Acquire to
Retire
(A2R)
Goods Issue
Define / Refine
Picking Strategies
 Fixed Bin
 Open Storage
 Fixed Storage
Bin
 Next Empty Bin
 Bulk Storage
 Near Picking
Bin
 Having
right
tool
and,
resources
Hire to
Retire
(H2R)
Order to
Cash (O2C)
Stock Taking
Physical
inventory
Strategy,
Plan
&
Schedule
 Continuous,
Perpetual Stock
Count
 Periodic
Stock
Count
 Annual
Stocktaking
 Pick Accuracy
 Stock
out
Validation
NextGen IM
& VM
 Just-in-Time
Inventory
Management (JIT)
 Economic
Order
Quantity (EOQ)
 MRP
 Quotations
 KANBAN
in
Inventory
Management
 Robotic
Process
Automation
 Multi
Enterprise
Supply
Chain
Business Network
26
Wave-4: Data & Process Strategy
Data is the Foundation for Digital Business
01
Corrective Measure: Embark on Data Harmonization Project
Preventive Measure: Establish Taxonomy & Classification
Establish Single Version of Truth
Data Analytics is essential for Smart & Quick decisions
02
04
05
Corrective Measure: Map Meta & Master data with Transactions
Preventive Measure: Align to capture the correct data
Establish Data Analytics Platform
03
Embrace the Data Science Vision
03
Corrective Measure: Refine formulae to optimize the Inventory
Preventive Measure: Automate the optimization models
Establish Trends, Patterns for AI / ML Models
Refine & Redefine the Process Models
04
01
Simplify & Automate core processes & workflows
Facilitate the Collaborative decision-making logic
Focus on User Experience
05
06
Process
Strategy
Data
Strategy
Simplification & Personalization of User Interfaces (UX)
Information stewards & Process Owners are real contributors
02
06
Information Quality is vital for Smart systems
Process & data maturity establishes the information quality
Process & data orchestration are core capabilities of Digital Business
PiLog 08-02-2024
27
Wave-5: Value Chain Strategic Implementation Framework
Engage with interdependent
Stakeholders
Establish Stakeholder
Engage into the activities
as the SOPs
Establish SOPs, Policies,
Governance
Collaborate the
efficiencies
ENGAGE
ESTABLISH
Establish Meta Data
Establish Data Quality
Metrics
Periodic Audit of Data &
Governance
Five – Es
FRAMEWORK
KRAs & KPIs are
measured regularly
Redefine the Vision
Statement
ENSURE
Determine Data &
Process Maturity
EMBARK
Innovations are
accommodated
EMPOWER
ROI is measured
Upskill & Cross Skill the
Stakeholder
Awareness & Change
Management
Implement each strategy
based on risk management
Systems, Technologies &
Platforms
PiLog
Refine Organizational
KRAs, KPIs & SLAs
www.piloggroup.com
Wave-6: Value Management – Plan to Inventory
Others*
Quantitative
Qualitative
Category
Strategic
Benefits, Premier
Processes
Risk Mitigation
Business Impact
Value Drivers
Expected Improvements
 Improve operational safety and end user satisfaction, Reduce risk of non-compliance
 Improved sourcing management
 Reduce human errors & free text spend
 Build the foundation for trustworthy, timely and accurate business insights through
dashboards on spend management, category management & vendor/contractor
engagement, sourcing management, data maturity etc
 Automated application of best practice templates during data build-out insures
consistent application of standard specifications for all the materials, reusable
taxonomy & classifications
 Ensure better integration with ERPs [SAP, Oracle, other ERPs] Apps
 Optimize Inventory parameters with RPA
 Comparative cost analysis using standard specifications during sourcing & procurement
 Reduce rework & improve the re-usability, quality & complaints resolution from end users
& vendors
 Reduce Un-Planned adhoc demand requests / changes
 Reduce Environment Health & Safety Management Cost by enforcing the compliance
Productivity,
Efficiency &
Effectiveness
 Smarter decision making with complete insights
 Quick turnaround during the procurement & vendor selection
 Simplify the interdependent activities across the organization
TCO Benefits
 Reduction of unnecessary inventory hoarding cost, duplicates & Non-moving stock
 Cost avoidance for regular/recurring procurement (Industry Bench markings)
 Seamless integration of systems with high quality data and refined processes
100%
Compliance
Automated
Inventory
Management
Improved % of
Automated
Procurement
20 - 30 %
40 - 50 %
40 - 50 %
20 - 30 %
100% Improved
Value chain
100% Value
realization
*Expected benefits based on industry experience
2024/02/08
www.piloggroup.com
29
Wave-6: Metrics driven Strategy for Inventory Optimization
Key Result Area
Effective
Control
Key Performance Indicator
Factors /
Dimensions
Industry Benchmark
Cost Reduction
~ 6-8% YoY
Wastage Reduction
<10 % Value of Overall
Stock
Reduction of Spares in Warehouse Damaged due to Storage
Conditions, Shelf Life
Cost Reduction
~5% YoY
Reduction of Warehouse Operation Cost
Cost Reduction
~ 4-7% YoY
Volume Utilization
~ 5-7% YoY
Reduction in Warehouse House Transfer Order Closure
Time Reduction
~ 7% YoY
Improvement in Warehouse Personnel Utilization Time
Utilization Time
~ 7% YoY
100%
% Commodities
0%
No. of Duplicate
Materials Count
Stock Reduction in inventory Holding Cost
Improved
Warehouse
Operations
Reduction of Non-Moving Stock w.r.t Overall Stock Value
Improved Warehouse Space
Master & Meta Data Assignment and standardization of correct classes as per
Quality
UNSPSC standards will improve spend visibility by more
than 25% from Current Level
Elimination of Duplicates
PiLog 08-02-2024
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30