Demand-Driven Supply Chain Planning
Lecture 6: Introduction and Recap
Dr. Josef Packowski
CAMELOT Consulting Group
Karlsruhe, 2021
1
Welcome back!
2
What have we learned so far?
2.1 Fundamentals and evolution of SC planning
2.2 The importance of Flow
2.3 Unlocking a solution: Decoupling and the Demand-Driven Operating Model
SUPPLY CHAIN MANAGEMENT AS A PART OF THE ORGANIZATION
Supply Chain Management in literature: Selected Definitions
“... is a set of approaches utilized to efficiently integrate suppliers,
manufacturers, warehouses, and stores, so that merchandise is produced and
distributed at the right quantity, to the right location, and at the right time, in
order to minimize system wide costs while satisfying service level
requirements.”
(Simchi-Levi, 2003)
= Koordination und Synchronisation aller SC Partner über alle
Wertschöpfungsstufen über Zeit, Menge zum erwarteten Servicelevel
Supply Chain Management
“… encompasses the planning and management of all activities involved in
sourcing and procurement, conversion, and all logistics management
activities. Importantly, it also includes coordination and collaboration with
channel partners, which can be suppliers, intermediaries, third party service
providers, and customers. In essence, supply chain management integrates
supply and demand management within and across companies.”
(CSCMP, 2008)
Demand-Driven Supply Chain Planning Lecture 1: Operating a SC in a VUCA world
© CAMELOT 2021
Slide 31
Klausur
SUPPLY CHAIN MANAGEMENT AS A PART OF THE ORGANIZATION
Operations and SCM objectives – what we want to achieve …
= How to cope with VUCA world?
RELIABLE & robust
Providing planned and reliable supply to build up on robust and integrated Demand to Supply
processes = use advanced demand planning & become demand driven
AGILE & adaptable
Strengthen organizational ability to anticipate and adapt to rapidly changing market
environment = create a demand-driven adaptive enterprise
LEAN & efficient
INNOVATIVE &
competitive
Design and optimize the supply chain to meet product life cycle, financial, and market
requirements = design and configure a demand-driven supply chain
Apply innovative concepts and solutions to drive step changes in performance for supply chain
design, processes, systems, and organization to meet future requirements
= shape innovations and trends in supply chain planning
CAPABLE & committed
Engage and develop people who are keen to continuously enhance understanding and
expertise = design and transform the organization
aktuelle Prioritäten herausfinden
bei Pharma Unternehmen mit lebenswichtigen Medikamenten ist reliable oberste Prio, bei hohem Kostendruck eher lean
Demand-Driven Supply Chain Planning Lecture 1: Operating a SC in a VUCA world
© CAMELOT 2021
Slide 34
FUNDAMENTALS AND EVOLUTION OF SC PLANNING
The VUCA world describes today’s supply chain challenges which need to be managed to ensure
competitiveness
VUCA
Volatility
Demand and supply
volatility due to rapid
and dynamic
changes
aufgrund der gestiegenen
Produktvielfalt, Personalisierung
der Produkte u. Reduktion
Auftragslosgrößen, globale
Vernetzungen
Rom
Uncertainty
High variability goes
along with less
predictability
Unsicherheit in Bezug auf
supply, diese erhöhen die
Unsicherheit in der
Planung der NBetze
Complexity
Ambiguity
Globalization, M&A
and increased
number of product
variants lead to
complexity
Fragmentation of
planning processes
and isolated planners
result in lack of clarity
nimmt durch die zunehmende
Vernetzung zu, erhöht die
Komplexität der Korrdination
unterschiedliche Sichtweisen
der beteiligten Akteure z.B.
hinsichtlich Sicherheitspuffer
Traditional supply chain optimization approaches cannot handle the new challenges of the VUCA
world as they were tailored to operate in a stable and predictive business environment
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
© CAMELOT 2021
Slide 11
FUNDAMENTALS AND EVOLUTION OF SC PLANNING
Supply Chain Planning is typically divided in different planning processes covering specific parts of the
end-to-end supply chain
Kaskadierung des Supply Prozesses
upstream
Supply Planning
Supplier
Scheduling
Production Planning
Production Site
Distribution Center
Distribution Planning
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
Replenishment Planning
© CAMELOT 2021
Demand Planning
Customer
(downstream)
Slide 12
FUNDAMENTALS AND EVOLUTION OF SC PLANNING
Planning problems in supply chain management can be separated into 3 planning levels
Health Care Industry
Betrachtung relevanter Informationen
in der kurzfristigen Planung sind Fixkosten keine relevanten Informationen,
in der strategischen Planung sind diese relevant (Engpassressource)
zeitlicher Aspekt der Segmentierung der Planungsaufgabe
1
Long-term level
Time buckets: (semi-) annual
2
Mid-term level
Time buckets: weeks or months
Product range, sales markets
Product types, sales segments
Locations/capacities, product
allocations, manufacturing
technologies
Sales orders, customers
Sales and operations volumes,
overtime, segment capacities,
seasonal inventories
Strategic partners/suppliers and key
materials
Resources, tasks
Key components/modules
3
Short-term level
Time buckets: shifts, days, weeks
Focus / Objects:
Detailed components
Main objectives:
Order acceptance and detailed
operations scheduling
Time
Focus / Objects:
Focus / Objects:
Company-wide strategic planning
Main objectives:
Coordination of mid-term material
flows
< 3m
Operational
Main objectives:
3-24 m
Tactical
Design and structure of the supply
chain
2-10 yrs
Strategical
Horizon
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
© CAMELOT 2021
Slide 13
Klausur
DIMENSIONS OF SUPPLY CHAIN PLANNING
1
Planning tasks at the long-term level
Building blocks
PLANNING PROBLEMS / DECISIONS
Sales
Product Program and
Strategic Sales
Planning
Determination of product-market portfolio based demand forecasts and strategic market cultivation strategies
Planning of product life cycles (new product introductions, ramp-ups etc.)
Considerations regarding the decoupling point of demand (MTO / MTS)
Distribution
Physical Distribution
Structure
Decisions regarding out-/insourcing of transports
Determination of number and size of warehouses, definition of transport routes and transport modes
Production
Plant Location and
Production System
Selection of production sites and production systems (manufacturing technology)
(Dis-)Investment of production capacities
Design of plant layout and material flows between machines
Procurement
Materials, Program,
Supplier Selection,
Co-operations
Selection of suppliers and design of disposition processes
Strategic cooperation with key suppliers, establishment of concepts such as VMI, JIT, …
SOURCE: Fleischmann et al. (2008); Meyr et al. (2008)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Slide 7
Klausur
DIMENSIONS OF SUPPLY CHAIN PLANNING
2
Planning tasks at the mid-term level
Building blocks
PLANNING PROBLEMS / DECISIONS
Sales
Mid-term Sales
Planning
Aggregated forecast and sales planning for product groups and sales regions, consideration of marketing activities and
advertising campaigns
Implications for requirements of stock sizing
Distribution
Distribution Planning
Mid-term planning of transport capacities on resource group level
Determination of necessary stock levels on product group level
Determination of distribution capacities bought from third-party carriers
Production
MPS / Capacity
Planning
Classic mid-term smoothing of employment and coordination of operations activities in the supply chain
Management of seasonal demand fluctuations
Procurement
Personal Planning
Planning of personnel capacities according to the production program (definition of shift schedules)
Procurement of additional capacities via subcontracted labor
Procurement
MRP, Contracts
Overall planning of demand- or consumption-oriented material requirements planning
Basic agreements especially with A-class suppliers
SOURCE: Fleischmann et al. (2008); Meyr et al. (2008)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Slide 8
Klausur
DIMENSIONS OF SUPPLY CHAIN PLANNING
3
Planning tasks at the short-term level
Kundenauftrag / Beschaffungsauftrag abarbeiten
Building blocks
PLANNING PROBLEMS / DECISIONS
Sales
Short-term Sales
Planning
Fulfillment of customer orders from stock (stock reservation, “available-to-promise")
Creation of new production contracts based on customer orders ("capable-to-promise")
Distribution
Warehouse
Replenishment,
Transport Planning
Short-term transport planning („routing") based on daily required quantities
Required daily warehouse replenishments for single products
Production
Lot-Sizing and
Machine Scheduling
Determination of production quantities and sequences
Detailed scheduling of operations tasks
Procurement
Short-term Personnel
Planning, Ordering
Materials
Filling of material commitments
Skill-based personnel planning (short-term shift scheduling)
SOURCE: Fleischmann et al. (2008); Meyr et al. (2008)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Slide 9
Notiz im Block
FROM MRP TO ERP
Klausur
Material Requirements Planning (MRP) II is the core concept for production planning and control in
current ERP systems
past: functional departments e.g sales (sold all products)
Master Production Scheduling
problems: data, organizational and system interfaces
solution: integrated database with access to all systems
(e.g. logistics or production system) to reduce interfaces
Component …
Component k-1
Material Requirements Planning
Component k
Demand calculation
Lot-sizing
Integrated
Database
Order scheduling
bedient alle
Funktionsblöcke
14 0
12 0
Capacity Requirements Planning
10 0
80
60
40
20
Capacity balancing
0
Sequencing
SOURCE: Günther/Tempelmeier (2012)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
follows a strictly
MRPMRPII
II follows
sequential
approach
a strictly sequential
approach
Slide 19
FROM MRP TO ERP
To create a document, master data is read from the database. Documents are “transaction data”
written to the database
Customer master data
Beleg / Dokument
Pricing
Sales order
General data
Sales organization specific data
…
Price
Taxes
…
Customer – Material Info
Transmission master data
Material master data
Basic data
Sales data
Purchasing
Transmission medium
Transmission time
…
…
Bei Transaktionsbasierten Systemen war
die Technologie limitierend, da die
Prozesse sehr lange gebraucht haben
Customer orders data database tables
(transaction data)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Transaction-based Systems
System pulls master data from databases into sales
document, data can be added there (read & write) and
saved back into database
Slide 20
Klausur !
FROM MRP TO ERP
ERP’s structure is strictly hierarchical: one plant has to be assigned to a specific company code
Software organization is hard coded: certain inputs are required e.g. country, plant, etc.
Fatal: With ERP, cross-plant planning is not possible
Organisationsstrucktur der Software
Organizational structure in ERP
ERP functionalities
Consolidation
BASF
Client
Holding
Company code
BASF Schweiz
Switzerland
General ledger
FI/CO transactions
…
MRP kann man nur ausführen wenn man sagt wo
CRP
Sequencing
Plant
1000
1100
1200
BASF Ludwigshafen: 300 Werke
Warehousing
MM/WM transactions
…
Storage
location
0001
0001
0002
Übergreifende Planung war nur durch goße Exceltabellen möglich
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Slide 22
FROM MRP TO ERP
The traditional ERP-based production planning cycle starts with Material Requirements Planning (MRP)
Input
Planung auf Werksebene:
Demands for finished products from Demand Planning or MPS
Bills of material for produced materials
Available inventory, safety stocks, existing production execution orders, etc.
Sequential planning
steps in ERP:
Demand Planning
Master Production
Scheduling
MRP: Calculating required material quantities taking into consideration demands, inventory and bills of material. Creation of
corresponding planned production orders and purchase requisitions
Material Requirements
Planning
Demands for finished products
Capacity Requirements
Planning
Planned orders
Product A
A
A
A
Purchase requisitions for
purchased materials
Sequencing
F
E
F
F
F
F
time
No consideration of
available capacity!
Order Execution
E
A
E: produced /
F: purchased material
Netting to zero
Demand
Supply
Output
beide Seiten müssen gleich groß
sein, sonst Beschaffungsauftrag
bei Ungleichgewicht versucht System
sofort auszugleichen: problematisch
bei hoher Volatilität
Feasible material plan that covers all demands
Planned production end dates aligned with demand dates
But: No consideration of available capacity!
Durchschnittswerte
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Slide 23
FROM MRP TO ERP
Principle of MRP: MRP creates dependent demand for components
Netting to zero principle
1. Location heuristic
1. Location heuristic
+
Receive demand
Generate purchase
requisitions
Generate
DC
Demand
(Forecast,
Sales order)
Purchase
Requisition
Receive
Distribution Center
2. Location heuristic
2. Location heuristic
Receive stock transport
requisitions
Generate planned
orders
Production Plant
+
stock transfer
DC
Stock transport
requisitions
Planned orders
BOM explosion
BOM explosion
+
Receive stock transport
requisitions
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Plant
Dependent
Demand
Slide 24
FUNDAMENTALS AND EVOLUTION OF SC PLANNING
The second step of the traditional ERP-based production planning cycle is
Capacity Requirements Planning (CRP)
Input
Sequential planning
steps in ERP:
Routings
Material plan for produced materials from MRP
Available capacity (capacity profile / shift model)
Demand Planning
Master Production
Scheduling
CRP: Evaluate impact of material plan on available capacity, usually on a weekly or monthly bucket level. Derive measures to solve
identified capacity shortages (e.g. adjust shift model).
Material Requirements
Planning
Planned orders for all products on the resource
Capacity Requirements
Planning
Purchase requisition for input components
A
B
Sequencing
A
A
A
C
A
C
B
Available capacity
Period 4
302
Period 5
286
Period 6
294
Capacity requirements1
288
308
290
Capacity utilization
95%
108%
98%
2h/100 PC
time
Capacity
profile
X
Order Execution
Output
1. For all products on that resource
Capacity – checked material plan
Identified measures to deal with capacity shortages
But: No feasible production plan (planned orders not sequenced yet)
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
© CAMELOT 2021
Slide 15
FUNDAMENTALS AND EVOLUTION OF SC PLANNING
The traditional ERP-based production planning cycle continues with Manual Sequencing
as its third step
Input
Planned production orders from MRP
Available capacity (capacity profile / shift model)
Sequential planning
steps in ERP:
Demand Planning
Master Production
Scheduling
Manual Sequencing: Creating a feasible, finite production schedule by bringing planned production orders into a sequence. Based on
defined sequencing criteria, e.g. in order to reduce set up times.
Material Requirements
Planning
Planned orders for all products on the resource
Capacity Requirements
Planning
Purchase requisition for input components
A
B
Sequenced planned orders
A
A
A
C
C
B
A
A
A
Wasserfallmodel
wenn Aufträge vorgezogen werden sollen,
muss material planning auch neu gemacht
werden (Material muss verfügbar sein)
A
Sequencing
No consideration of
material availability!
Order Execution
wenn Aufgaben isoliert ausgeführt werden,
werden Abhängigkeiten zwischen den
Schritten nicht berücksichtigt
APS führt alle Aufgaben simultan durch
time
Output
Sequenced production schedule per resource
But: Material availability has not been considered, input components (purchased or manufactured in-house) might not be available
-> Still no feasible production plan
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
© CAMELOT 2021
Slide 16
FUNDAMENTALS AND EVOLUTION OF SC PLANNING
APS in Production Planning and Scheduling provides simultaneous material and capacity planning
APS: Simultaneous consideration of material and capacity
availability
ERP: Sequential planning steps
Demand Planning
Master Production Scheduling
MRP
Material Requirements Planning
!
Capacity Requirements Planning
Sequencing
CRP
Order Execution
Advanced Planning Systems allow simultaneous planning of
material requirements, capacity requirements planning and
sequencing
MRP, Capacity Requirements Planning (CRP) and sequencing
are performed serially in disjointed steps
Nearly good planning results can only be achieved by
executing several planning runs → ineffective, trial and error
approach
Single, integrated process step
Essential in capacity-constrained production environments
Only suitable when capacity is not an issue
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
© CAMELOT 2021
Slide 17
ADVANCED PLANNING SYSTEMS
Capabilities of SAP PP/DS comprise of dynamic order networks, set up times and simultaneous
planning
1
Dynamic order
networks
Enabler for simultaneous material and capacity planning
Creates a link between orders to ensure consistency
Logical connection between supply and demand (order network)
Dynamic readjustments of order network in case of changes in demand or supply
Sequence dependent
setup times (in min)
Product A
B
C
0
60
20
A
B
120 0
120
C
180 180
0
2
Dynamic setup times
Model setup times in planning as close as possible to the real setup times
Depends on product portfolio that have to be produced
ERP: Standard setup times per product
APS: Sequence dependent setup times
MRP
3
Simultaneous planning
CRP
Simultaneous planning of material requirements, capacity requirements
planning and sequencing
Single, integrated process step
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Slide 41
ADVANCED PLANNING SYSTEMS
Although solving many of the shortcomings from MRP/ERP, also Advanced Planning Systems still don’t
solve all today’s planning challenges
SHORTCOMINGS
IMPLICATIONS
Application of optimization algorithms is limited to linear
optimization problems
Feasible plans across multiple supply chain stages can be created,
but a true, holistic optimization is not possible due to the nonlinear nature of supply chain planning problems
Plans are created based on (inaccurate) forecast
Lack of feedback loops, i.e. capabilities for monitoring and
analysis of actual supply chain performance to facilitate a
continuous improvement process
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 2: Fundamentals and evolution of supply chain planning
Plans are frequently changing, which creates nervousness in the
planning process and leads to short-term “firefighting”
Planning quality is impaired when planning is based on
inaccurate or false assumption, especially in volatile
environments
Slide 51
1
Welcome back!
2
What have we learned so far?
2.1 Fundamentals and evolution of SC planning
2.2 The importance of Flow
2.3 Unlocking a solution: Decoupling and the Demand-Driven Operating Model
PURPOSE OF THE SUPPLY CHAIN: FLOW
Relevanz: unterschiedliche Entscheidungsebenen
The First Law of Supply Chain Management
man muss immer die Entscheidungsebene betrachten, um die richtigen Ziele zu setzen
bspw. macht es keinen Sinn eine Anlage anzuschhaffen mit 600 Einheiten pro Minute
wenn bisher nur eine Prototyp produziert wird. Folglich ist das OEE schlecht, wofür der
Production Planner nichts kann. Es handelt sich um eine strategische Fehlentscheidung
All benefits will be directly related to the speed of FLOW of materials and information
(George W. Plossl)
Information
Materials
Caveat:
Both Materials and Information must be RELEVANT
All benefits will be directly related to the speed of FLOW of
RELEVANT materials and information
© copyright 2017 Demand Driven Institute
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 12
PURPOSE OF THE SUPPLY CHAIN: FLOW
Flow is the primary objective in a Demand-Driven Adaptive Enterprise
“All benefits will be directly related to the speed of FLOW of materials
and information.”
George W. Plossl
Information
Materials
Protection and Promotion Flow =
ROI Maximization
When flow is occurring:
Service is consistent and reliable
when a system flows well
Revenue is maximized and
protected.
Inventories are minimized.
Expenses ancillary and/or
unnecessary are minimized.
Cash flow follows the rate of
product flow to market demand.
Source: Demand Driven Institute
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 5
Klausur
PURPOSE OF THE SUPPLY CHAIN: FLOW
How does Flow influence the ROI?
Net Profit → ∆ROI
∆Flow → ∆Cash Velocity → ∆
Investment
(
Flow
)
Flow is the rate at which a system converts material to product required by a customer.
echter Bedarf
Cash velocity is the rate of net cash generation; sales dollars minus truly variable costs (aka contribution margin) minus
period operating expense.
Cash velocity
wenn Bestände lange liegen ist cash velocity nicht gegeben
ROI
Net profit/investment is the equation for ROI
Queuing Theory
The less time it takes products to move through the system, the less the total inventory investment
The simple equation is:
WIP = Throughput * Lead Time
Source: Demand Driven Institute
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 8
Klausur
PURPOSE OF THE SUPPLY CHAIN: FLOW
Having seen the traffic example –
What does hinder Flow? What is the missing element for Flow?
∆Visibility → ∆Variability → ∆Flow → ∆Cash Velocity → ∆ Net Profit → ∆ROI
Investment
(
Variability
Visibility
Variability is defined as the summation of the
differences between our plan and what happens
Visibility is defined as relevant information
for decision making
)
Variability
= Flow
Variability
= Flow
Visibility
= Variability
Visibility
= Variability
Source: Demand Driven Institute
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 10
VARIABILITY AND ITS IMPACT ON FLOW
Various kinds of variability are endangering the Flow within a supply chain and are therefore the main
challenge for modern supply chains – it is the #1 objective to manage variability adequately
Demand variability is an external variability caused by
customer and market behavior through fluctuations in
demand plan
Management variability
Operational variability is an internal variability caused by
normal variations in a system and by random events
Management variability is an internal, self-imposed variability
caused by human behavior within an organization.
Variability can be managed and minimized, but not eliminated
Verspätungen in Produktion
Supply variability
Vertical variability
Supply variability is an external variability caused by bad
supplier performance through disruptions in the supply
network and delayed delivery dates
Demand variability durch Kunde
Operational
variability
z.B.
Maschinen
ausfall
Only management variability as a self-imposed variability is
under our direct control and thus, the first target for
improvement
Organizational Output
Horizontal variability
© copyright 2017 Demand Driven Institute
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 15
VARIABILITY AND ITS IMPACT ON FLOW
The common supply chain safety nets managed in our planning systems do not reduce variability but
rather promote it further increasing the bullwhip effect
Illustrative
HOW IS IT HAPPENING ACROSS THE SUPPLY CHAIN?
PHYSICAL MATERIAL FLOW
Supplier Tier 2
Supplier Tier 1
Production Tier 2
Production Tier 1
Central DC
Local DC
Customers
stocks are stored between
stages - physical decoupling
points
Stock buffer
Lead Time
SYSTEM INFORMATION FLOW
S
“Netting to zero“ concept
MRP
-100
D
+100
S
MRP
-100
D
+100
System Lead Time
S
MRP
-100
D
+100
Inflated Lead Time
S : Supply element, D : Demand element, DRP : Distribution Requirements Planning, MRP : Material Requirements Planning
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
S
DRP
-100
D
+100
S
DRP
-100
für jeden Bestand im System
ein Modell, durch Rundung
steigt der Effekt
D
+100
Variability
System Lead Time ist dann die Summe aller lead times
The buffers are actually supposed to decouple, but are passed on in the system
= strongly dependent on customer demand
Slide 19
THE IMPORTANCE OF FLOW
The trouble with netting to zero and demand variability in a VUCA world
Forecast-based replenishment,
firefighting and overreaction results
in the oscillation between too much
and too little
Most companies experience a
“bi-modal” inventory distribution
# of parts or SKU
MRP nimmt Sicherheit weg, durch
Netting to zero triggert ein neuer
Bedarf die Aufrüstung aller Schritte
davor, die lead time wird zusätzlich
erhöht da alles verkettet ist
Volatilität wird durch
Rundungseffekte weiter erhöht
(man bestellt nicht 0,5 sondern
direkt 1 kg)
Warning
Too Little
Optimal Range
Warning
Too Much
0
Too much of the wrong stuff, too little of the right stuff
© copyright 2018 Demand Driven Institute, all rights reserved
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
Slide 22
VARIABILITY AND ITS IMPACT ON FLOW
Traditional planning approaches allow usage of safety stock only in the fulfillment horizon but not in
the planning horizon
echte Kundenaufträge dürfen safety stock nutzen
forecast dürfen safety stocks nicht nutzen
soll in Planung aber auch genutzt werden
safety stock wird in Planung nicht
berücksichtigt, er wird nicht genutzt
(ERP rührt Bestände nicht an)
Volatilität
Schwankungen in order visibility
horizon (man hat Kundenaufträge)
Variabilität
es liegen keine Kundenaufträge
vor sondern nur forecasts
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 21
Purpose of the supply chain: FLOW
Relevant information are the basis for visibility – and with that also for Flow – in a supply chain;
four prerequisites are necessary
Understanding Relevant Ranges:
Which assumptions are valid in which time range?
Most companies fail to recognize that the information to
be used in the strategic, tactical and operational planning
range is vastly different
E. g. usage of full cost (incl. fixed cost)
in short term decisions
Flow-Based Operating Model:
Flow as the common basis for day-to-day decision
making
Does the decision increase the speed of flow?
Does the decision reduce the variability of flow?
Does the decision increase the relevance of flow?
Soll-Ist-Abgleich zwischen Vorgaben und Realität
Tactical Reconciliation between Relevant Ranges:
Bidirectional adaption between planning ranges
Strategy as guideline for operational capabilities
Projection of model performance under (assumed)
conditions
Feedback to strategy by operational capability
and performance
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Flow-Based Metrics
Derived from the strategy
Fixkosten auf dieser Ebene irrelevant
Covering speed, variability, relevance of material,
information and cash flow
Linking the relevant planning ranges
Slide 11
The wrong focus on unit cost
The conventional approach of S&OP / MPS / MRP cannot foster flow, because it fails to satisfy the four
prerequisites
fehlende Rückkopplung
Understanding relevant ranges
Flow-based operating model
Dominance of fully-absorbed cost for short term
decisions
Proposed models (MRP, LEAN, Theory of Constraints,
…) rest on assumptions which never hold in practice
Reliance on heavily detailed forecasts
Thus limited application or “work arounds”
Tactical reconciliation between relevant ranges
Reconciliation basically one way (right to left)
Furthermore, slight changes on the right frequently
translate into massive changes on the left
Flow-based metrics
Flow-based metrics like on-time delivery and fill rates
exist
But conflicting with non-flow metrics (e. g. full cost)
At the complex enterprise level: No effective organizational model, metrics and
communication system enabling implementation, sustaining and evolving flow!
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 31
wichtig
THE WRONG FOCUS ON UNIT COST
Conflicting views: Cost-Centric and Flow-Centric Metrics
Cost-Centric Metric Objectives
Flow-Centric Metric Objectives
Gross profit product margins
Part and product standard cost
Working capital dollar targets
Cost-reduction initiatives
Product cost variance analysis
Reliability/Stability
Speed/velocity
System improvement/waste
Strategic contribution
Local operating expense
Cost-Centric View
Flow-Centric View
∆Cost → ∆Cash Velocity → ∆
∆Flow → ∆Cash Velocity → ∆
© copyright 2017 Demand Driven Institute
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Net Profit
( Investment )
Net Profit
( Investment )
→ ∆ROI
→ ∆ROI
Slide 26
wichtig
THE WRONG FOCUS ON UNIT COST
Conflicting Actions
Cost-Centric Action
Tactical Objective
Flow-Centric Action
Efficiency
Run larger batches; extend the forecast; run only on optimal resource
Protect critical resources; run smaller batches to pull; run on any
process capable resource
Margin Maximization
Focus on lowering unit product cost
Focus on increasing service level, premium pricing, leveraging
constrained resources and incremental revenue opportunities
Inventory Turns
Impose an inventory dollar value; postpone inventory receipt;
mandate across the board reductions
Commit to strategic stock positions that meet the lead time strategy
Budget Performance
Focus on actions to achieve standard unit cost
Focus on the incremental costs of leveraging flow to the market
Volume Maximization
Lower price and raise order minimums
Focus on service, lead times and lower order minimums
Continuous Improvement
Identify unit cost reduction opportunities through increasing resource
efficiency or labor reduction
Identify the largest sources of variation and remove them to lower
lead times and reduce investment in all strategic buffers
© copyright 2017 Demand Driven Institute
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 27
1
Welcome back!
2
What have we learned so far?
2.1 Fundamentals and evolution of SC planning
2.2 The importance of Flow
2.3 Unlocking a solution: Decoupling and the Demand-Driven Operating Model
UNLOCKING A SOLUTION: DECOUPLING
The only way to reduce the effect of variability in the supply chain is to stop variability amplification –
the bullwhip effect – in both directions; the supply chain needs to be “decoupled”
What does “decoupling” exactly mean?
Creating independence between supply and use of material. Commonly denotes providing inventory between
operations so that fluctuations in the production rate of the supplying operation do not constrain production
or use rates of the next operation.
(APICS Dictionary, 14ed., page 43)
Effekt eines Stoßdämpfers
Production
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Distribution
Slide 34
STRATEGIC INVENTORY POSITIONING
Strategic placed decoupling points compress lead times, reduce variability, and consequently ensure
flow keeping the overall supply chain in a stable state
Strategically place decoupling points of inventory within the product
structure and supply chain.
Demand Signal Distortion
Precursor
Bulk
Production
Filling
This stops the transfer and
amplification of variability in both
direction where it matters most.
Packaging
Planning horizons shorten and lead
times compressed.
Supply Continuity Variability
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 11
Überschrift wichtig, Bilder nicht malen
UNLOCKING A SOLUTION: DECOUPLING AND THE DEMAND-DRIVEN OPERATING MODEL
Decoupling as described within Demand Driven combines aspects of MRP (“everything dependent”)
and LEAN (“everything independent”) creating a “dependent independence” within the supply chain
Forecast
Quantity
MRP
Demand Driven
Takt Time or
Consumption
Time
MPS
Lean
Finished
product
Safety
Stock
Finished
product
Buffer
Sales Orders
Finished
product
The explosion stops at each
stock position – No Matter
What!!
Kanban
Kanban
loop
Production
Order
MRP
Orders are created based on MRP
The explosion starts when a
buffer triggers the order
signal
Intermediate
product
Intermediate
product
Decoupled Explosion literally
means “independent
dependence”
Intermediate
product
supermarket
Purchased
product
Purchased
product
Intermediate
product
Safety
Stock
Purchased
product
Intermediate
product
Intermediate
product
Purchased
product
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
Purchased
product
Purchased
product
© CAMELOT 2021
an bestimmten Stellen
decoupling points bewusst
gesetzt
In between the decoupling
points Demand Driven MRP
explodes in the EXACT same
manner as MRP
Demand Driven MRP still
seeks to net to zero between
the decoupling points
Slide 29
THE DEMAND DRIVEN OPERATING MODEL
Three types of buffer are used to cover supply chain variability: Inventory, Capacity and Time
Stock
Use of inventory to
cover demand spikes
or supply disruptions
These are interchangeable
and interdependent
regarding sizing and flow
Buffering
Variability
Time
Use of time buffers to
anticipate delays in
supply
Capacity
Use of spare capacity
to increase throughput
when needed
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 3: The importance of FLOW & How to become Demand-Driven?
Slide 43
1
Recap
2
Demand planning
2.1 Basics
2.2 Challenges
2.3 Trending topics
3
Lessons learned
Warum so abhängig von forecast Modellen und wieso ist der forecast
in den drei Modellen unterschiedlich behandelt?
Wie erzeugt man den forecast?
Outlook auf camelot System reflektieren
wichtig
BASICS
Tactical demand planning – the classic 6-step demand planning process
Advanced planning system (APS)
Demand Analyst + APS
Data
load
Release
Demand Planner
6
Validate
1
2
5
Data
preparation
Statistics
4
Enrich
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 5: Advanced & AI-enabled Demand Planning
3
Forecast
Slide 14
wichtig
BASICS
Datenverfügbarkeit ist immer noch kritisch
Overview of the different clusters of forecasting methods
ON THE RISE
STILL MAINLY USED
Complexity /
data availability
Very High
High
Average
Low
Judgmental
Univariate
Causal
Machine learning
Incorporate intuition,
opinions and subjective
estimates in the forecast.
Used in cases where there
is a lack of historical data.
(e.g. S-curves, scenario
planning)
Forecast generation based on
order or shipment history.
Typically it contains trend and
seasonality analysis.
(e.g. Exponential smoothing,
simple linear regression,
ARIMA)
Regression examines causal relations
between known and unknown
variables. Regression reaches a
higher forecasting accuracy
compared to univariate models.
(e.g. price sensitivity, incorporating
google search behavior)
This forecasting procedure uses the
overwhelming data quantities and
complexity within the datasets
which are available nowadays.
Manually fitting clusters and
regression models often fail based
on that complexity.
Change Mangement:
Entscheider sollen © CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 5: Advanced &Daten
AI-enabled
Demand Planning
vertrauen
Slide 15
BASICS
Univariate statistical models allocated to demand time series patterns
CONSTANT
- Moving average
- 1st order exponential smoothing
INTERMITTENT
- Croston’s exponential smoothing
SPORADIC
vertauscht
TREND
- There is no good model (alternatively
use naïve models like copy history or
moving average with a long horizon)
- Regression against trend
- 2nd order exponential smoothing
Lifecycle Planung
Vorgängermodell für Planung
neues Modell nutzen
SEASONAL
- Linear regression against seasonality
- 3rd order exp. smoothing without trend
TREND & SEASONAL
- Linear regression against trend and
seasonality
- 3rd order exponential smoothing
PHASE-OUT
- 1st order exponential smoothing
- (2nd order exponential smoothing)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 5: Advanced & AI-enabled Demand Planning
Produkte die im Markt anlaufen
PHASE-IN
- No forecast
- (2nd order exponential smoothing)
keine Historie vorhanden
Slide 16
BASICS
Key Performance Indicators (KPIs) to measure the quality of the Demand Planning Process
Forecast Accuracy (FA)
Measures the average
accuracy of the forecast
versus the sales.
The most commonly used measure is
the weighted mean absolute
percentage error (WMAPE) based on
Sales Orders.
Forecast Accuracy = 1 – WMAPE
𝑊𝑀𝐴𝑃𝐸 =
σ |𝐴𝑐𝑡𝑢𝑎𝑙 − 𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡|
σ 𝐴𝑐𝑡𝑢𝑎𝑙
Weighting by sales volume, turnover or
margin across time periods and
portfolio.
(FVA)
Forecast Value Add
Measures the forecast accuracy or
bias improvement for specific process
steps, e.g. forecast enrichment.
Calculated by comparing KPIs from
different process steps, e.g. how much
the Forecast Accuracy and bias have
improved during manual enrichment
versus baseline statistical forecast, e.g.
FVA = FA FC after enrichment – FA Statistical FC
Forecast is
balanced, no
systematic
error
-1
Actual Demand is
lower than Forecast
(overforecasted
/undersold)
𝐵𝑖𝑎𝑠 =
0
1
Actual Demand is
higher than Forecast
(underforecasted /
oversold)
σ(𝐴𝑐𝑡𝑢𝑎𝑙 −𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡)
σ 𝐴𝑐𝑡𝑢𝑎𝑙
Measures the systematic error
(over- or underforecasting).
welchen Mehrwert hat der Planner durch
manuelle Anpassungen hinzugefügt
Forecast Bias
Forecast lag depending on main lead
time requirements.
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 5: Advanced & AI-enabled Demand Planning
Slide 21
wichtig
CHALLENGES
We have more data then every before but experience a shift to the VUCA* world (BUT Big Data won’t
solve all challenges…)
CHAOS THEORY
CLOCKWORK UNIVERSE
As system, with its states governed by deterministic laws that are
highly sensitive to initial conditions, making them unpredictable
A perfect machine, with its gears governed by the laws of physics,
making every aspect of the machine predictable
Weather
Holidays
Social media
Traffic jams during rush hour
Crisis
Events (e.g. soccer, Christmas, promotions)
*) volatility, uncertainty, complexity and ambiguity
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 5: Advanced & AI-enabled Demand Planning
Slide 23
DDMRP
1
Introduction to Demand Driven MRP
2
Strategic Inventory Positioning
3
Stock Buffer Sizing
4
Dynamic Buffer Adjustments
UNLOCKING A SOLUTION: DECOUPLING AND THE DEMAND-DRIVEN OPERATING MODEL
The different elements of the Demand Driven Operating Model will be covered by the lectures of the
second part of the course
Variance Analysis Return Loop (supply order generation and stock management)
Lecture
Actual
Demand
Lecture
6.1
Demand Driven
Model Configuration
Demand Driven MRP
(Supply Order Generation)
Available inventory &
buffer status
Lecture
Supply
Orders
6.2
Demand Driven Execution
(Buffer Management)
Manufacturing
Orders
Released Manuf. Orders
Manuf. Order Status
7.1
Scheduled
Manuf. Orders
6.3
Lecture
Demand Driven Scheduling
(Finite Control Point
Scheduling)
© copyright 2018 Demand Driven Institute, all rights reserved
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
S&OP
T
M
Variance Analysis
Return Loop
(scheduling,
resources and
execution)
Slide 34
INTRODUCTION TO DEMAND DRIVEN MRP
What Is Demand Driven MRP?
model: wo kommt buffer hin?
plan: welcher buffer muss benachschubt werden?
manage: Bestellungen müssen produziert und geliefert werden
upstream (vom Kunden zum
supplier) u. Materialien downstream
mehrstufig
} A multi-echelon approach to model, plan and manage supply chains to protect and promote the flow of relevant
information and materials, based on the principles of Position, Protect and Pull
} DDMRP is the supply order generation and management engine of a demand driven operating model
DDMRP
} DDMRP is build on the foundation
of various well known and widely
applied concepts, including MRP,
DRP, Lean Manufacturing (Toyota
Production System), Theory of
constraints and Six Sigma
MRP
DRP*
Lean
Theory of
Constraints
Six Sigma
Innovation
*Distribution Requirement Planning
Position, Protect and Pull
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 5
UNLOCKING A SOLUTION: DECOUPLING AND THE DEMAND-DRIVEN OPERATING MODEL
Key principle of the Demand Driven Operating Model is the split between supply chain configuration
(e.g. based on forecasts) and short-term supply chain planning & execution based on actual demand
Planning
Tactical Horizon
Forecast
Wofür braucht man forecast wenn alles nach
pull Prinzip gesteuert?
Forecast ist notwendig um SC im taktischen Bereich zu
parametrisieren (Ausrechnung der Größe der buffer)
Parameter Adjustment
Execution
Supply chain parameterization
Frozen Horizon
Operational Horizon
Actual Demand / Consumption
Order
abweichend von Planung
Inventory Buffer
Trennung von Forecast und actual demand
Bi-directional reconciliation
Operational Planning
Demand-Driven Supply Chain Planning Lecture 6: Introduction and Recap
Tactical Planning
© CAMELOT 2021
Slide 32
INTRODUCTION TO DEMAND DRIVEN MRP
The DDMRP methodology provides a framework for a multi-echelon IM and replenishment planning
approach that consists of five major building blocks
Konfiguration
Modeling/Re-modeling the Environment
Position
1
an der richtigen Stelle platzieren
Protect
2
Strategic Decoupling
Plan
Buffer Profiles and
Levels
buffer richtig dimensionieren:
wie viel buffer brauchen wir?
Execute
Pull
3
Dynamic Adjustments
dynamische Anpassung des buffers
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
4
Demand Driven
Planning
5
Visible and
Collaborative
Execution
echten Kundenbedarf verwenden
Slide 7
Klausur
Strategic Inventory Positioning
Six factors determine the final strategy for inventory positioning
Customer Tolerance Time
Market Potential Lead Time
} The time a typical customer is willing to
wait before seeking an alternative source
} This lead time will allow an increase of price
or the capture of additional business
through new customer channels
bei Zigaretten: Toleranz ist 0, man will es sofort
Auto: bereit halbes Jahr zu warten
External Variability
} Demand and Supply variability can lead
to disruptions in sources of supply and
overwhelm resources Schutz vor langer Lieferzeit o. schlechter
zukünftiges Potential: wenn wir schneller am Markt wären
könnten wir weiteren Marktpotential abgreifen?
Positioning
Strategy
Sales Order Visibility Horizon
} The time frame in which sales orders or
dependent demand typically become aware
Qualität (buffer sind notwendig)
Inventory Leverage and
Flexibility
} The places in the supply network
structure that enables the most lead
time compression
Critical Operation Protection
} Types of operations that have limited capacity
or where quality can be compromised by
disruptions z.B. buffer vor bottle neck resource
wenn mehrere Zwischenprodukte in
verschiedene Endprodukte eingehen
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 13
STRATEGIC INVENTORY POSITIONING
wichtig
A New Form of Lead Time Emerges: Decoupled Lead Time (DLT)
} Use of decoupling points also reveals the need for a new type of lead time
} Must be understood and calculated in order to:
ê
ê
ê
ê
Compress lead times to market required ranges
Determine realistic due dates when needed
Set decoupling points buffer levels properly
Find high value inventory leverage points for decoupling
Decoupled Lead Time (DLT): längste Zeit zwischen 2 buffern
A qualified cumulative lead time defined as the longest unprotected/un-buffered
sequence in a supply network (bill of material / distribution network)
1
3
4+5 = 9
5
SF4
12
SF1
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
10
SF5
SF2
4
} DLT is calculated as the summation of the lead times on that longest unprotected
sequence.
} Anytime a manufactured item has a non-buffered (coupled component) its DLT will be
greater than its MLT.
} In the product structure on the right, there are two decoupled manufactured parts with
decoupled lead times that are larger than their manufactured lead times
(FG1 and SF2).
} What are the DLTs for each of them?
2+3+3+1 = 9
FG1
RM2
SF3
3
2
30
RM1
RM3
RM4
30
Slide 23
STRATEGIC INVENTORY POSITIONING
typische Klausuraufgabe
Exercise: Determination of decoupled lead times
Unterschied parts und buffered parts
3
1
2
11
RM1
2
SF5
1
SF2
4
3
SF1
3
SF3
} How many parts have Decoupled Lead Times greater than
their manufacturing lead times?
SF7, SF2, SF6)
A:4 (FG1,
4 (FG1;
SF6; SF7; SF2)
FG1
5
SF6
2
SF7
3
RM4
SF4
8
RM3
} What is the decoupled lead time of part FG1?
5+3+3
A:
11= 11
RM5
} What is the decoupled lead time of part SF6?
A:2+24 = 4
RM2
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 24
STOCK BUFFER SIZING
For each decoupling point, color-coded buffer zones are used to serve three different purposes
Shock absorption
} Dampen both supply and demand variability
} Significantly reduce or eliminate the transfer of
variability (nervousness, bullwhip effect)
Green Zone
Yellow Zone
Red Zone
Lead time compression
} Decouple supplier lead times from the consumption side
of the buffer
} Compress lead times instantly
Supply order generation
} Combine all relevant demand, supply and on-hand
information to produce a “net flow” equation for supply
order generation
} Buffers are heart of the actual planning system in
DDMRP
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 29
STOCK BUFFER SIZING
Each Zone Has a Specific Purpose and Calculation
Green Zone
Order frequency and size
Yellow Zone
Primary coverage
pipeline stock (nicht physisch auf Lager)
deckt die lead time ab
kein safety stock!
Safety dieser
hier ist wirklich existent
Red Zone
Group Settings
(Buffer Profiles)
Nachschubaufträge für buffer werden wirklich
generiert
= determiniert wie oft und wie viel ich bestelle
Individual Part Properties
Item Type
Lead Time
Lead Time Category
Minimum Order Quantity (MOQ)
Variability Category
Location (Distributed parts only)
Average Daily Usage (ADU)
Zone and Buffer Levels
for Each Part
Bedarf
hierfür benötigt man forecast
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 30
STOCK BUFFER SIZING
Each zone is sized appropriately and calculated according to its particular purpose
Calculation of DDMRP Buffer Zones
MOQ = Mindestbestellmenge
Top of Green (ToG)
1.
2.
3.
Green buffer zone = max(MOQ; desired or given replenishment interval x ADU; LTF x ADU x DLT)
ê Determines typical order size
ê Determines average order frequency
Green Zone
Top of Yellow (ToY)
Yellow Zone
wenn man nur mittwochs bestellen kann
muss Bestellung auch mindestens bis zum
nächsten Mittwoch halten
= ToR + Summe Yellow Zone
Yellow buffer zone = DLT x ADU
ê Demand coverage in the buffer
Top of Red (ToR)
Red Zone
Red buffer zone is calculated in three steps:
1.
2.
3.
Red Zone Base (LTF x ADU x DLT)
Red Zone Safety (Red Zone Base x Variability Factor)
Total Red Zone (Red Zone Base + Red Zone Safety)
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 44
STOCK BUFFER SIZING
Example Part
Part RM1
Average Daily Usage
40
Buffer Profile
Purchased (P), 30% LT Factor (L), 60% Variability (M)
MOQ
1000
Imposed or Desired Order Cycle (DOC)
14 days
Decoupled Lead Time (DLT)
28 days
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 45
STOCK BUFFER SIZING
The Entire Calculated Buffer for Part RM1
Top of Green (TOG) = Red + Yellow + Green = 2658
1000
Top of Yellow (TOY) = Red + Yellow = 1658
1120
202
336
Top of Red (TOR) = 538
Red Safety
Red Base
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 50
STOCK BUFFER SIZING
Additional Calculations
} Green Zone / ADU = average order frequency. What is the average order frequency for the
example?
} Yellow Zone / Green Zone = average number of open supply orders. How many supply orders on
average should we expect to see in our example?
} Red Zone / ADU = days of safety in the buffer. How many days of safety are in the buffer?
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 51
DYNAMIC BUFFER ADJUSTMENTS
In order to react to dynamic market effects, stock buffers need to be dynamically adjusted
Trend
Seasonality
Ramp-Up
Qty
Qty
Time
Qty
Time
Time
Recalculated adjustments
Planned adjustments
} Buffer levels flex as Average Daily Usage (ADU) is updated
} Buffers are intentionally flexed up or down in anticipation of
planned events or seasons
1200
70
1000
60
800
600
400
200
0
1000
100
800
80
40
600
60
30
400
40
200
20
50
20
10
0
0
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
0
Slide 56
DYNAMIC BUFFER ADJUSTMENTS
What Is a Planned Adjustment?
} Planned adjustments are based on certain strategic, historical, and business intelligence factors.
} These planned adjustments are manipulations to the buffer equation that affect inventory positions by raising or lowering
buffer levels and their corresponding zones at certain points in time.
} There are three primary types of planned adjustments:
} Demand Adjustment Factor (DAF)
} A manipulation of the ADU input at a
specific time period to a historically
proven or planned position based on
an approved business case or as a
reaction to rapid changes in demand
within short periods of time.
} Zone Adjustment Factor
} Zone adjustments can be applied to
any of the three zones
} Adjustments can be made in terms of
a factor (1.5 would increase zone size
by 150%) or days of demand
} Lead Time Adjustment Factor
} The use of a lead time adjustment
factor relates to a planned or known
expansion to the lead time of a part
} A factor of 1.5 would increase the lead
time by 150%
} As the demand adjustment factor
alters the ADU, all buffer zones are
affected
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.1: Demand Driven MRP – Part I (Steps 1 – 3)
Slide 60
1
Demand Driven Replenishment Planning - Qualified Demand
2
Demand Driven Replenishment Planning - Prioritization by Buffer Status
3
Visible and Collaborative Execution
DEMAND DRIVEN REPLENISHMENT PLANNING - QUALIFIED DEMAND
wichtig
In Demand Driven MRP the replenishment decision is only based on actual consumption and qualified
sales orders in order to avoid issues associated with forecast based planning
Plant
Logistics
?
Forecast
Plant
Planning
Logistics
Suppliers
} Planned orders create supply order in anticipation of need
} Forecast error associated with planned orders results in
inventory misalignments and expedite expenses
Sales
Order
Planning
Suppliers
} Only qualified sales orders within a short range horizon qualify as
demand allocations
} Sales orders give a near perfect demand signal in terms of what
will be sold and when it will be sold
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.2: Demand Driven MRP – Part III (Steps 4 – 5)
Slide 6
wichtig
DEMAND DRIVEN REPLENISHMENT PLANNING - QUALIFIED DEMAND
The Net Flow Equation: Stocked items are resupplied as actual demand forces the net flow equation
of parts into their respective rebuild zones
Sales orders
On-Order
On Hand
Qualified
order spike
Today
Net Flow Equation
=
Open Supply
ON-ORDER STOCK
} The total of all outstanding replenishment
orders
} Increases when a new order is released
} Decreases when material is received
against an order or when an order is
canceled
ON-HAND STOCK
+
} The quantity shown in the inventory
records as being physically in stock
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.2: Demand Driven MRP – Part III (Steps 4 – 5)
QUALIFIED SALES ORDER DEMAND
} Today’s customer orders
-
} Any backlog
} Significant order spikes within the decoupled lead-time forward horizon
wo ist Bedarf der höher als erwartet ist
(könnte unseren buffer gefährden)
Slide 7
DEMAND DRIVEN REPLENISHMENT PLANNING - QUALIFIED DEMAND
wichtig
When & how much to order – The DDMRP net flow position
} The result of the net flow equation is called “net flow position”
} When the net flow position is <= Top of Yellow, a new replenishment
order is generated
◄ 1658
351
378
qualified demand
50
geht wieder auf Top of Green hoch
in dem Moment in dem
man etwas bestellt
Example:
◄1280
Open Supply
} The quantity of the replenishment order is calculated as:
Top of Green - Net flow position
780
} On Hand = 550
} On-Order = 780
heute, zukunkt und spikes
} Order Recommendation = 378
On Hand
} Qualified Demand = 50
} Net Flow = 1280
527
net flow position = wesentlicher Punkt
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.2: Demand Driven MRP – Part III (Steps 4 – 5)
Slide 11
DEMAND DRIVEN REPLENISHMENT PLANNING - QUALIFIED DEMAND
wichtig
Calculating Average On Hand Position and Range
} Average On Hand position will be the total red zone plus one half of the green zone
(example: 100 + 30 = 130)
60
} Average On Hand range is from the top of red to the top of red + green zone
} Let’s understand why…
180
100
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.2: Demand Driven MRP – Part III (Steps 4 – 5)
Slide 13
wichtig
DEMAND DRIVEN REPLENISHMENT PLANNING - QUALIFIED DEMAND
Planning and Prioritization – DDMRP Stock Buffer Status
Buffer liefert Information
Priorisierung zwischen Buffern rot/ grün/ gelb?
} In a DDMRP process, the status of a stock buffer is a key input for planning decisions
} The Stock Buffer Status is described by
ê
ê
ê
Regel: color first percentage second
(erst rot dann gelb dann Rest,
innerhalb buffer geht es nach Prozent)
Net flow position
Color status
es kann sein dass manchmal gelb aber weniger Prozent:
erst Farbe innerhalb Farbe geht es nach Prozent
Planning priority (relative buffer status)
} Planning priority = Net flow position as a percentage of top of green
2290
2658
1000
1120
590
538
Buffer Status
Yellow
(22.2%)
1055
300
426
1084
Red
(58.3%)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.2: Demand Driven MRP – Part III (Steps 4 – 5)
1810
2187
750
712
725
OTOG
(104.7%)
Slide 17
VISIBLE AND COLLABORATIVE EXECUTION
The purpose of the DDMRP analytics view is to identify any out-of-range inventory development
Planning view
Execution view
Analytics view
} Each zone is sized to fulfill a specific purpose
} Zones are directly derived from planning zones
} Used for monitoring the planning status
} On-hand zones are directly derived from planning
zones
} Available stock + expected demand & supply
quantities within lead time horizon
} Focus only on available stock on hand
OTOG
Top of Green (ToG)
(Over top of
green)
Green
Zone
Top of Yellow (ToY)
} Used for monitoring the execution status
Red Zone
} Actual development of available stock on hand vs.
defined buffer zones
Upper Dark
Red Zone
OTOG
Upper Red
Zone
Green OnHand Zone
Upper Yellow
Zone
Average On-hand target level
(ToR + Green Zone)
Yellow
Zone
Top of Red (ToR)
} Used for ex-post analysis of the stock buffer
integrity
Average On-hand position
Green OnHand Zone
Green
Zone
Overstock
alert level
(Red Zone +
Green Zone +
% of Yellow
Zone)
(ToR + ½ * Green Zone)
Yellow OnHand Zone
Red OnHand Zone
Stock-out
Zone
Lower Yellow
Zone
On-hand stock alert level
© copyright 2018 Demand Driven Institute, all rights reserved.
Demand-Driven Supply Chain Planning Lecture 6.2: Demand Driven MRP – Part III (Steps 4 – 5)
(% of ToR)
Lower Red
Zone
Lower Dark
Red Zone
Slide 38
1
Introduction to production planning in a VUCA world
2
Demand driven cyclic production planning
3
Typical Benefits of Demand Driven Rhythm Wheel Planning
wichtig
INTRODUCTION TO PRODUCTION PLANNING IN A VUCA WORLD
Rhythm Wheel Planning addresses the pain points in today‘s supply chains efficiently
Rhythm
Wheel
Forecast
Production
Pull signal
Customer
Production
Customer
Pull consumption with
decoupling of demand and
production
Bullwhip effect causes instability
and increases inventory buffers
Order signal
Demand
Order signal
Capacity usage
Demand
Capacity usage
Leveled capacity utilization
through active usage of
inventories
Instable capacity utilization
Inventory
Inventory
Cycle Time
Cycle Time
= Lead time
Long and volatile Cycle Times
A
C
B
C
B
A
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
A
B
C
A
B
C
Tactical parameter driven
planning with end-to-end
synchronization
Slide 9
wichtig
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
The main pillars of the demand driven SCM philosophy are the DDMRP* and the DDRWP* concepts
leveling variability through a constant alignment of capacity, lead time and buffer stocks
Two-sided management of customer demand
Demand Driven
Rhythm Wheel
Planning
volatility
Manufacturing assets
Rhythm Wheel-managed
Demand Driven
Material Requirements
Planning
Buffering in planning through dynamic buffer
stock adjustments
36h
CT (+)
E
D
CT
C
12h
B
CT (-)
Customer demand volatility
Inventory stock keeping units (SKU)
*DDMRP: Demand driven material requirements planning | DDRWP: Demand driven cyclical rhythm wheel planning
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Slide 11
wichtig
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
Complexity is reduced by separating tactical configuration with the RW Designer from operational
planning and execution with the RW Planning
Forecasted demand
Minimum order quantity
Tactical planning
parameterization in
DDRWP
Campaign building
Configuration
run
Pre-configuration of
Rhythm Wheel
Design
da nutzt man
den forecast,
man betrachtet
einen Horizont
mit Vorlauf man
hat noch keine
konkreten
Kundenaufträge
Sequence calculation
Was ist die optimale
Reihenfolge auf wheel?
Pre-configuration
Customer demand
Pull Element, veranlasst Produktion
Operational
planning execution
in DDRWP
Generating
supply orders based on
pre-configuration and
consumption demand
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Planning
run on
Rhythm
Wheels
Inventory
Supply orders
Ausfürhrung
hier werden
tatsächliche
Kundenaufträge
genutzt
Slide 13
wichtig
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
The five components of the Demand Driven Rhythm Wheel concept achieve a stabilized and leveled
production plan
Capacity
Position
1
Protect
2
Product to Line Allocation Leveled Flow with Rhythm
(Leveled Mix)
Wheel Design
Pull
3
4
5
Dynamic Adjustments
of Config & Parameters
Demand Driven
Rhythm Wheel Planning
Takted Execution
and Range Monitoring
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Slide 16
wichtig
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
A Rhythm Wheel is scheduling all products on a production resource in a predefined sequence
Position
Wechselwirkungen zwischen Produkten betrachten
Was ordne ich zu mit welcher Präferenz?
1
Text
PRODUCT-TO-LINE ALLOCATION
SEQUENCING
The product portfolio is assigned to a primary production
The designated product portfolio is optimized in a fixed cycle
resource based on runtime and setup dependencies
defining the repetitive order of production campaigns
This results in a reduction of the overall load from production
The optimized sequence leverages OEE and improves customer
and changeover times over all production resources
service level as it controls variability in the supply chain
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Slide 17
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
Rhythm Wheel planning is characterized by a repetitive and changeover optimized planning
approach with pre-defined Rhythm Wheel cycle times
1st cycle
Repetitive planning
2nd cycle
Cycle
time
3rd cycle
Cycle
time
Product A
Setup optimized production
sequence
Cycle
time
Product B
Product C
Was ist die Rüstoptimale Reihenfolge?
Setup matrix
Cycle time boundaries
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Slide 19
wichtig
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
The Rhythm Wheel Designer addresses the parameterization for Rhythm Wheel Planning
Objective
Supports the production planner in creating Rhythm Wheels
for relevant production assets
Output of the process is an optimized production Wheel
Design with ideal product sequence and make-quantities for
a leveled production
Supports existing product portfolios by different Wheel
Designs
How it works
Based on setup matrices the designer creates for all relevant
products an optimum production Cycle with minimized
changeover times
By analyzing all relevant demand and master data (e.g.
demand volumes, production rates, resource capacities) the
optimum Cycle Time is defined
In the medium and long-term horizon a renewal of parameter
settings and configuration is necessary to incorporate
changes of demand patterns (volatility, trends, etc.)
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Slide 21
wichtig
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
Rhythm Wheel types can be chosen based on the selected strategy with regard to demand pattern,
product sequences and production assets where Rhythm Wheel Planning cannot be applied
Rhythm Wheel Design strategy
A
Classic Rhythm Wheel
Variability
B
Breathing Rhythm Wheel
Variability
C
Non Rhythm Wheel
High-Mix Rhythm Wheel
S
Variability
SOFOS Heuristic
Variability
Z
Z
Z
Z
Y
Y
Y
Y
X
X
C
B
A
Volume
keine
boundaries
Cycle
time
X
C
B
A
Volume
X
C
B
A
Volume
C
B
A
Volume
CT (+)
Cycle
time
Cycle
time
Cycle
time
Cycle
time
CT (+)
1st Cycle
For a homogeneous product mix with rather constant
demand every product is scheduled every Cycle
The Classic Rhythm
Wheel produces fixed
quantities according to a
fixed schedule
jedes Produkt in jedem Zyklus mit fester Losgröße
The Breathing Rhythm
Wheel produces
consumption-based
quantities and is more
flexible
2nd Cycle
3rd Cycle
For a high-mix portfolio it is
favorable to define different
production rhythms
Low volume products are not
scheduled every Cycle to avoid
high setup times
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Setup-oriented forward
scheduling
No repetitive Cycle
Order size derived by
standard product
heuristic
Slide 22
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
DDRWP prioritizes production if capacity constraints emerge and cycle times are violated to achieve
automated leveling periods
Rhythm wheel
design
Actual plan without
factoring
Cycle
Time
Cycle Time
violation
Cycle
Time
Application of
factoring
Leveled plan
Reduction of
Cycle Time
Cycle
Time
Cycle
Time
max
max
max
max
min
min
min
min
Time
Cycle Time
violation
Time
Extension of
Cycle Time
Time
Cycle Time
attainment
Cycle Time
attainment
Time
The Rhythm Wheel Design
defines the Cycle Time
boundaries
The Rhythm Wheel Heuristic
determines the Cycle length
using latest demand figures
The Rhythm Wheel Heuristic
automatically levels the
Cycles through factoring
Factoring methods align the
current Cycles with the
Rhythm Wheel Design
The durations are defined
based on the necessary
business requirements
Cycle Time violations are
identified and handled
individually
Product or market priorities
are considered for each
product individually
Cycle Time violations are
eliminated leading to a
leveled production and
consistent lead times
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Slide 26
DEMAND DRIVEN CYCLIC PRODUCTION PLANNING
Factoring according to buffer status ensures that in capacity overloads urgent supply orders are
prioritized
Buffer status according to DDMRP log are considered
The higher the factoring prio the more urgent the product has to be replenished
Factoring prio defines which product will be factored first (prio 1 is factored first)
If the maximum cycle time is exceeded the DDRWP factors the products according to the buffer priority – products with a
high buffer status (color first, percentage second) are pushed out first
Example: Cut off factoring based on buffer status
Product A
Cut off to next cycle
Source Loc.
Source Product
Buffer Status
Factoring Prio
Plant 1
Product B
70%
1
Plant 1
Product A
20%
2
Plant 1
Product C
10%
3
Product B
Product C
Time
© CAMELOT 2021
Demand-Driven Supply Chain Planning Lecture 6.3: Demand Driven Rhythm Wheel Planning
Higher Prio
CTmax
Slide 1
1
Introduction of DDS&OP
2
DDS&OP and the link to the DDOM
3
DDS&OP and the link to the AS&OP
4
Summary and Q&A
Demand-Driven S&OP
As part of the overarching Demand Driven Adaptive Enterprise Model, Demand Driven Sales &
Operations Planning connects the operationally focused DDOM with the strategic planning range
Model
configuration
DEMAND DRIVEN
OPERATING MODEL
Actual
Demand
Demand Driven
Operating Model
TM
Variance
analysis
All contents © copyright 2018 Demand Driven Institute, all rights reserved.
Slide 50
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
Business plan
parameters
DEMAND DRIVEN
S&OP
ADAPTIVE
S&OP
Demand Driven
Adaptive
Adaptive
S&OP
S&OP
TM
Model projections, innovation
& strategic recommendations
Market
Driven
Innovation
TM
Demand-Driven S&OP
The three model components of the Demand Driven Adaptive Enterprise Model
Demand Driven
Operating Model
Demand Driven
S&OP
TM
The DDOM is a predictable and agile system that
promotes and protects the flow of relevant
information and materials within the operational
relevant range (hourly, daily and weekly)
Supply order generation based on actual
demand
Operational scheduling and execution model
based on DDMRP buffer status
DDMRPs key parameters are set through
DDS&OP to meet business and market objectives
while minimizing working capital and expediterelated expenses.
TM
The DDS&OP is a tactical bi-directional
integration point between the strategic and
operational relevant ranges of decision making.
DDS&OP maintains and updates the parameters
of the DDOM based on current and emerging
business strategy supplied by Adaptive S&OP and
the systematic review of past and projected
DDOM performance.
DDS&OP evaluates scenarios proposed in the
Adaptive S&OP process in order to provide
relevant DDOM projections.
DDS&OP recommends strategic alterations
and/or internal innovations to leadership
involving DDOM future capability and
performance.
Operational horizon
Slide 51
Adaptive
Adaptive
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
Tactical horizon
S&OP
TM
The Adaptive S&OP is the integrated business
process that provides management the ability to
strategically define, direct and manage relevant
information in the strategic relevant range and
across the enterprise.
Market Driven Innovation is combined with
Operations Strategy, Go-to-Market Strategy and
Financial Strategy to create strategic information
and requirements for tactical reconciliation and
strategic projection to effectively create and
drive adaptation
Decision making process based on provided
scenarios from DDS&OP that leads to an
aggregated plan
Strategic horizon
Demand-Driven S&OP
DDS&OP sets key parameters of a Demand Driven Operating Model (DDOM) based on the output of
the Adaptive S&OP process and projects the DDOM performance as basis for strategic decisions
DDS&OP is a bi-directional tactical reconciliation hub in a Demand Driven Adaptive Enterprise (DDAE) Model
between the strategic and operational relevant ranges of decision making. DDS&OP sets key parameters of a
Demand Driven Operating Model (DDOM) based on the output of the Adaptive S&OP process.
DEMAND DRIVEN
S&OP
Demand Driven
S&OP
TM
DDS&OP also projects the DDOM performance based on the strategic information and requirements and various
DDOM parameter settings. Additionally, DDS&OP uses variance analysis based on past DDOM performance
against critical metrics (reliability, stability and velocity) to adapt the key parameters of the DDOM and/or
recommend strategic changes to the business.
Tactical Exploitation Opportunities
BUSINESS PLAN
PROMOS & LINE
EXTENSIONS
Master Settings
DEMAND PLAN
DEMAND DRIVEN
OPERATING MODEL
DEMAND
MODEL
CONFIGURATION
Demand Driven
ADAPTIVE
S&OP
Adaptive
Adaptive
CAPABILITIES
Operating Model
S&OP
TM
PERFORMANCE
TARGETS
Variance Analysis
© 2017 DDI & Richard C. Ling Inc – all rights reserved
Slide 52
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
Model Projections & Strategic Recommendations
TM
Demand-Driven S&OP
Five elements of Demand Driven Sales & Operations Planning within tactical and strategic horizons
DEMAND DRIVEN
OPERATING MODEL
Demand Driven
Operating Model
TM
DEMAND DRIVEN
S&OP
ADAPTIVE
S&OP
Demand Driven
Adaptive
Adaptive
S&OP
S&OP
TM
TM
Tactical
1
Review
Variance Analysis:
How did the DDOM
perform in the past?
Slide 53
2
Tactical
Projection
Performance projection:
How will the DDOM
perform?
Strategic
Configuration /
Reconciliation
3
Shaping the DDOM to
improve performance
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
4
Exploitation
Exploitation of
opportunities
5
Recommendation &
Strategic Projection
Derive recommendations for the
Adaptive S&OP & evaluate
developments of the strategic range
Tactical
Demand-Driven S&OP
1
Review
2
Tactical
Projection
3
Strategic
Configuration /
Reconciliation
4
Exploitation
5
Recommendation &
Strategic Projection
The Variance analysis provides insights about the past performance of the Demand Driven Operating
model and is used for parameter related decisions during DDS&OP
Did we execute according
to the defined process?
Did we meet the
defined targets?
Do the model assumptions
match reality?
Signal integrity status
Service level (OTIF)
ADU bias
Replenishment quantity adherence
On-hand stock buffer adherence
(Buffer integrity status)
DLT bias
…
Are defined parameters
appropriate?
Homogeneity of SKUs performance
and variance per segment -> Is
segmentation appropriate?
…
Variability Segment ->
variability factors appropriate?
Lead Time Segment ->
lead time factors appropriate?
On-hand stock bias
Excess inventory
…
Flow index (order frequency)
…
Process adherence
Slide 54
Target achievement
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
Assumption validity
Parameter suitability
Tactical
Demand-Driven S&OP
1
Review
2
Tactical
Projection
3
Strategic
Configuration /
Reconciliation
4
Exploitation
5
Recommendation &
Strategic Projection
Tactical Projection is the step to project DDOM performance under different scenarios to identify risks
(like shortages) and opportunities (like shorter lead times)
Prepare for known or planned events affecting supply, capacity and demand
Supply disruptions, e.g. due to
suppliers plant shut down or weather
conditions
Seasonality
Promotions
Demand evolution
Product portfolio changes (phase-in,
change over, phase-out)
Change of transportation modes
Other exceptions
Demand
Supply
New manufacturing processes
Planned capacity changes, e.g. shift
reduction or opening of a new
distribution facility
Temporary capacity changes: plant
shut-down and maintenance
Capacity
Tactical projection
Evaluate demand
scenarios
DDMRP
Decide on
preproduction
Capacity extension
Buffer
sizing/adjustments
Derive and adjust operational DDMRP parameters
Shift models
Exception handling
Inventory projection
Feedback on target buffers to align capacities
Maintenance
Slide 55
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
Replenishment
decisions
Tactical
Demand-Driven S&OP
1
Review
2
Tactical
Projection
3
Strategic
Configuration /
Reconciliation
4
Exploitation
5
Recommendation &
Strategic Projection
Basically, there are three way to improve the performance towards the primary DDMRP objective of
reducing the buffers while keeping a high level of customer service
Three ways to achieve the primary DDMRP improvement objective
Where the improvement
came from
1. Lead Time reduction
2. Variability reduction
Max
Max
Avg
Min
Min
Improvement Objective:
Reduce the buffers without
service erosion
3. MOQ Reduction
MOQ
All contents © copyright 2018 Demand Driven Institute, all rights reserved.
Slide 56
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
MOQ
Tactical
Demand-Driven S&OP
1
Review
Tactical Exploitation – Identify opportunities for short range supplements to flow
Increase the contribution in the tactical horizon
Two basic approaches:
1. Increase volume: produce and sell more units of product
2. Increase rate: increase contribution margin per capacity
unit of key resource
Both approaches do NOT change the fixed cost base,
therefore high impact on ROI
What is possible within the tactical horizon?
If it goes outside the tactical horizon, treat it as strategic
recommendation
Slide 57
| © CAMELOT 2020 | Demand-Driven Supply Chain Planning Lecture 8: Summary & Discussion
2
Tactical
Projection
3
Strategic
Configuration /
Reconciliation
4
Exploitation
5
Recommendation &
Strategic Projection
Lecture overview
1. Approach to demand-driven transformation
2. Selected key aspects of
demand-driven transformation
Organization
Adjust roles to reflect activity changes due to shift to
demand-driven
People & Culture
Build the required capabilities
Align people by using appropriate incentives
3. Company example: How DDMRP affects supply chain roles
Demand-Driven Supply Chain Planning Module 7.2 – Organization & Transformation
© CAMELOT 2021
Slide 2
ADJUST ROLES TO REFLECT ACTIVITY CHANGES DUE TO SHIFT TO DEMAND-DRIVEN
Practical aspect within companies is how operating models and underlying software are supporting
the end-to-end management of the supply chain – a break out of the local functional silos is required
Operating models established in the past
Customer
Orders
Forecast
Demand-Driven operating models for the new normal
Customer
Orders
Forecast
MPS
MPS
MPS
simultane
Durchführung
MRP
Disponent
Sequencing
Sequencing
Rhythm Wheel
Configuration
MRP
Fertigungssteuerer
CRP
Sequencing
CRP
Leveled
FLOW Sync.
MRP
Stock Buffer
Parametrization
Konfiguration &
Parametrisierung
zentrale
Durchführung
Linienplaner
ERP / MRP based
Production Planning
Customer
Orders
Forecast
CRP
DDRWP
APS based
Production Planning
zentrale Durchführung möglich,
aber nicht sinnvoll da Lokalität von Vorteil
dezentrale
Durchführung
weniger Kompetenzen notwendig
High-level overview (lecture 2.1)
DD-Sync
DDMRP
Planungsausführer
Demand-Driven based
Production Planning and Supply Planning
Focus of the course (lectures 4.1 ff.)
*DDMRP: Demand driven material requirements planning | DDRWP: Demand driven cyclical rhythm wheel planning | CRP: Capacity requirements planning | APS: Advanced planning system | MPS: Master production schedule
Demand-Driven Supply Chain Planning Module 7.2 – Organization & Transformation
© CAMELOT 2021
Slide 7
ALIGN PEOPLE BY USING APPROPRIATE INCENTIVES
Intended behavior needs to be managed to realize the potential of a demand-driven transformation
work which is often a huge challenge
TYPICALLY, A TRANSFORMATION LEADS TO RESISTANCE
THAT NEEDS TO BE ADDRESSED
A COMBINATION OF SOFT METHODS AND METRICS IS
KEY TO ACHIEVE THE INTENDED BEHAVIOR
Shift of values, aspirations or
behaviors
Use soft methods
Shift in strategies, processes,
practices and systems
Identify and leverage change agents
Perceived loss of control caused by people’s feelings
Limited capacity
to change
Drive behavior change and support by
building understanding, skills and using
role models
Set up communication program
Lack of
competencies
Explained on next slide
Lack of
confidence
Lose of comfort
zone
Align intended
behavior with
metrics
Build a consistent metrics hierarchy for
aggregation and drill-downs
Ensure that metrics drive behavior into
the right direction
Resistance to transformation
Demand-Driven Supply Chain Planning Module 7.2 – Organization & Transformation
Select a few top-level metrics based on
strategic requirements
© CAMELOT 2021
Slide 17
ALIGN PEOPLE BY USING APPROPRIATE INCENTIVES
Company performance is driven by delivering value to the customer – thus, an end-to-end
optimization of the processes is relevant, not a silo optimization based on functional metrics
SC Performance Management based on conventional metrics
E2E SC Performance Management based on Flow Metrics
Company performance
Purchasing
Unit price
Production
OEE
SCM
Inventories
Inventories
Company performance
Sales
Service Level
Purchasing
Typical functional
metrics / targets
Exemplary
conflict
Production
SCM
Sales
Integrated E2E process view
Flow
Common
target
E2E performance management based on Flow Metrics
In most cases, company performance is measured and steered by
measuring and steering the performance of functional departments
To ensure an overall company optimum, integrated E2E processes have
to be measured and steered – avoiding contradicting targets
Typically, cost based functionally focused metrics are used to evaluate
the performance of functional departments
Flow Metrics must be designed to support FLOW in the organization
Flow Metrics have to be part of a holistic metric system that considers
potential conflicts and drives the organization’s behavior towards
common targets
As targets with regard to those functional metrics are conflicting in
many cases, this leads to silo optimization and not to an overall
company optimum
Demand-Driven Supply Chain Planning Module 7.2 – Organization & Transformation
© CAMELOT 2021
Slide 20
APPROACH TO DEMAND-DRIVEN TRANSFORMATION
The approach to drive the transformation journey needs to involve changing the “thoughtware“ to
win support in the organization
Realization
Evaluation
„Im Kopf“
Thoughtware
Pilot
Implementation
Feasibility
Show that it works in
live system
Understanding
Curiosity
Awareness
Learn that DemandDriven SCM exists
1
Generate buy-in to
explore further steps
2
Create operational
understanding
Prove concept and
benefits
5
Realize benefits
6
4
3
Demand-Driven Supply Chain Planning Module 7.2 – Organization & Transformation
© CAMELOT 2021
Slide 29
Dr. Josef Packowski
CEO
Camelot MC AG
Theodor-Heuss-Anlage 12
68165 Mannheim, Germany
Tel: +49 621 86298-800
office@camelot-mc.com
www.camelot-mc.com