A Methodology for Simulation Conceptual
Modelling that Embeds the SCOR Process
Reference Model
Dr. Miles Weaver,
School of Management, Edinburgh Napier University
m.weaver@napier.ac.uk
@DrMilesWeaver
Dr. Pavel Albores,
Aston Business School
Dr. Doug Love,
Aston Business School
#SimCM
Outline
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Importance of conceptual
modelling and need for a
SCM2
Requirements
(Specification) - (what do
we need the conceptual
model to do)
Outline design - (what
procedure is needed to
arrive at this conceptual
model)
•
Illustration of the SCM2 and the
incorporated key concepts
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–
General guidelines for building
an ‘effective’ conceptual
modelling
Embedding the utility of a
process reference model (e.g.
SCOR)
What is a simulation conceptual model?
A simulation conceptual model (SimCM):
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Documents and details the explicit statement of assumptions and
relationships to be included in the simulation model in accordance
with the problem statement (Manuj et al., 2009)
A non-software specific description of the simulation model that is
to be developed, describing the objectives, inputs, outputs,
content, assumptions and simplification of the model (Robinson,
2004; 2008)
Uniqueness for simulation purposes:
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‘process’ to be followed – at the heart of this is setting the model
boundary & level of detail (model content)
‘output’ – the description of the computer model to be built is as
‘simple as possible’ (by drawing assumptions & simplifications) and
is both credible & valid
Simulation conceptual modelling
for SCM applications
•
Evaluating supply chain problems is important (Stewart, 1997); difficulty is
that they are inherently complex and dynamic systems (e.g. Davies, 1993;
Levy, 1994; Beamon, 1998)
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Simulation is an approach that is often used for evaluating SC problems;
extent of research is great (Weaver, 2010)
•
Creating a conceptual model is often regarded as the most important
stage of a simulation project (Law, 1991); but little is written on the
subject (Robinson, 2004b).
•
SimCM is a ripe area for research (Robinson, 2006, 2010). Even in the SCM
domain, Manuj et al., (2009) noted that further development in this area can
improve the rigour of simulation studies
•
No methodologies exist that could guide a user through the creation of a
conceptual model (Weaver, 2010).
The ‘idea’ behind the SCM2
Domain-specific
SimCM procedure for
SCM applications
Incorporate existing
SimCM guidance from
the literature
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Embed domainknowledge in the
form of a process
reference model
+
Incorporate a general
process, general principles,
methods for validation,
advice on simplification?
Provide inputs to the process
of SimCM (i.e. setting the
model boundary & detail) and
standard descriptions?
Relationship between the requirements and
outline design for SCM2
Outline design
(what procedure is needed to arrive at
this conceptual model)
General guidelines
for building an
‘effective’
conceptual
modelling
Embedding the
utility of a process
reference model
(e.g. SCOR)
General process for
conceptual modelling
Incorporating existing
guidance to build a ‘valid’
and ‘credible’ model
Incorporating existing
guidance to keep the model
as ‘simple’ as possible
Using SCOR to describe
supply chain improvements
Using SCOR to describe
supply chain objectives
Using SCOR to determine
the interconnections with the
supply setting
Requirements (Specification)
(what do we need the conceptual model to do)
Requirements for
building an ‘effective’
conceptual model
Validity &
Model
Credibility simplicity
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Requirements for conceptual modelling for SCM
application (domain-specific requirement)
SC
complexity
SC detail
SC
objectives
Supply
setting
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Phase 2:
Phase 1:
Determine how each
objective is to be measured
Describe the supply problem
Point of entry
Output: Description of the processes
that provide data used to calculate
each objective
Output: Description of the
improvement(s) to be evaluated, for
a given objective(s) within its supply
setting
A formal problem formulation and structuring
methodology or unstructured problem from
client
Phase 6:
Phase 3:
Phase 7:
Determine how each
improvement is to be
represented
Output: Description of the processes
that represent each improvement
Document and validate the
conceptual model
Output: A valid description of the computer
model to be developed
Design the level of detail
necessary to implement the
model
Output: Description of the model
components and interconnections that
represent the actual practices included
in the model
Phase 4:
Determine how the inputs
and their sources
interconnect within the
model and with its
immediate supply setting
Output: List of inputs and candidate
processes for possible inclusion in
the model boundary
Phase 5:
Formulate the model boundary
Output: List of processes and inputs
included in the model
Iterate for each PROMOTED process decided in phase five
Build a prototype and use
sensitivity analysis to extend
the model boundary and
level of detail
Output: Refinement of the model
boundary and level of detail
Experimental situation:
CoffeePot Case
Q: Where and how to cost
effectively manufacture
products in a global and
complex supply setting?
Efficient manufacturing scenario
in a low-cost area with either
shipments made in:
(S1) small (by air)
(S2) large quantities (by road
and ship).
Further detail on the CoffeePot case:
Taylor, G. D., Love, D. M., Weaver, M. W., & Stone, J. (2009). Determining inventory service support levels
in multinational companies. International Journal of Production Economics, Vol. 116 No. 1, pp. 1–11.
Phase one:
Describe the supply problem
Output: The supply problem is described from the
perspective of the client
Statement
of
objective(s) of study
Output
from
1.1
Description
of
improvements
to
change the existing
system
Output
from
1.2
Description of
problem setting
Output
from
1.3
the
Statement of how
each
improvement
could achieve the
desired impact on the
objective(s)
Output
from
1.4
Statement of supply chain problem
A multi-national manufacturing company (MNC) is deciding how to cost effectively manufacture
products in a global setting. The aim is to determine how much finished goods stock (reduce supply
chain assets) to have on hand to support sales at a 95% desired service level (increase supply chain
reliability).
A MNC has an efficient manufacturing facility in a low-income/low-cost location (i.e. Asia or Africa)
and a warehouse in a high-cost area where the product is primarily distributed and sold. Shipments
are currently made in large quantities, with a cost effective and slow shipping method (road and
sea). The MNC wants to consider the impact of a change in the shipping method, by shipping in
small quantities, with an expensive and fast shipping method (all air) on the defined objective.
The MNC has an efficient manufacturing facility in a low-income/low-cost location (i.e. Asia or
Africa) and a warehouse in a high-income/high-cost location where the product is primarily
distributed and sold (i.e. North America or Western Europe). The capacity for an efficient
production facility is defined as one which has a low cost of capital and shipping in economic
quantities. The method for shipments from a low-cost manufacturing location to a warehouse in a
high-cost area can be larger, cost effective and slow, or small, expensive and fast. It is assumed that
the product selected is a coffee maker (Mr Coffee Expert Model) which is representative of a
functional product type.
An off-shore location offers advantages to reduce cost (e.g. Alguire, Frear and Metcalf, 1994; Fagan,
1991; Monczka and Trent, 1991). The study seeks to examine how much finished goods inventory
at hand is needed in the warehouse to satisfy a defined customer service requirement at lowest
cost. The shipment size, speed and cost will affect how much finished stock is available at hand. If
there is insufficient inventory stock-out will occur leading to the service level not being met, while
too much inventory will satisfy the requirement but will incur a cost.
Simulation is a good method to evaluate this problem as it will allow a user to adjust the re-order
point to obtain a desired service level and review the implications on finished goods inventory
costs.
Key Concept 1: Embedding
SCOR in a generic procedure
for simulation conceptual
modelling can aid in the
description of a problem from
the perspective of the client
using standard terminology and
domain-specific process detail
Phase two:
Determine how each objective is to be measured
Output: The objective is described in terms of how it will be
measured
Statement of how each objective will be measured
Perf. Att.
Perf.
metric
level
Perf. metric
Definition of metric calculation
Output from 2.1
Process
elements
Output from 2.2
Assets
Level 3
metric
AM3.16: Inventory days of
supply
(Value of finished goods inventory/(COGS/365))
Delivery
reliability
Level 2
metric
RL.2.2: Delivery performance to
customer commit date
The percentage of orders that are fulfilled on the customer's originally scheduled or committed date = [Total
number of orders delivered on the original commitment date] / [Total number of orders delivered] X 100%
Key concept 2: Embedding SCOR in a generic procedure for
simulation conceptual modelling can aid in determining how an
objective can be measured using standard descriptions of typical
performance attributes and metrics; plus data collection needs
from associated business processes at different levels of detail
Actor
M’ment
span
Output from 2.3
S1.4
WH
Process
D1.8
WH
Process
D1.3
D1.12
D1.13
WH
WH
WH
Process
Process
Process
Phase three:
Determine how each improvement is to be represented
Output: The improvement is described in terms of
how it is to be represented
Statement of how each process is to represent each improvement
Improvement option
Output from step 1.1.2
A MNC has an efficient manufacturing facility in a low-income/low-cost location (i.e. Asia or Africa) and a warehouse in a high-cost area where the product is primarily
distributed and sold. Shipments are currently made in large quantities, with a cost effective and slow shipping method (road and sea). The MNC wants to consider the
impact of a change in shipping method by shipping in small quantities, with an expensive and fast shipping method (all air) on the defined objective.
Key Concept 3: Embedding SCOR in a generic procedure for
simulation conceptual modelling can aid in determining how each
improvement can be represented by business processes to
implement each improvement at different levels of detail
Level of
process
detail
Business
process
Output from step 3.1
Actor
Output
from 3.2
Level 3
D2.10
Fact.
Level 3
D2.11
Fact.
Level 3
D2.12
Fact.
Level 3
D2.13
Fact.
Phase four:
Determine how the inputs and their sources interconnect
within the model and with its immediate supply setting
Output: Provide a list of model inputs and candidate process elements (NB
supplies information only to formulate the model boundary)
Key Concepts 4 and 5: Embedding SCOR in a generic
procedure for simulation conceptual modelling can aid in
determining the model boundary by providing information
on the relationships between business processes (i.e.
interconnections between inputs and outputs germane to
each process element)
Key concept 4: Identification of core process
elements and their inputs generated from a
source process element
Description of the
supply problem
Description of how each
objective is to be measured
e.g.S1.4 (WH), D1.8 (WH), D1.3 (WH),
D1.12 (WH), D1.13 (WH))
Description of each
improvement to be
represented
e.g. D2.10 (F), D2.11 (F), D2.12 (F),
D2.13 (F)
Example of SCOR inputs and outputs to a
decomposed business process
Source: SCOR V.9 (2008)
Phase four:
Determine how the inputs and their sources interconnect
within the model and with its immediate supply setting
Output: Provide a list of model inputs and candidate process elements (NB
supplies information only to formulate the model boundary)
Key concept 5: Process elements that have yet to
be included in the model can be classed as
‘candidates’ for possible inclusion
Does the source process element (that generates each input to
be fed) exist as a CORE or PROMOTED process element?
Phase five:
Formulate the model boundary
Output: Provide a list of processes and inputs included in the model
Key concept 6: Decision rules can be used to consider which business
processes to include within the model boundary from identifying the critical
relationships between (core processes) and within the setting (real world) of
the processes that are associated with each objective and improvement
Simplify – Promote – Test - Exclude
Rule 1: Will the input to be generated from the candidate process
element effect model behaviour by significantly impacting on the
objectives of study?
Phase five:
Formulate the model boundary
Output: Provide a list of processes and inputs included in the model
Key Concept 7: Included
process elements are
considered in turn to identify
those that could be simplified
Decision rules can be embedded in a
generic procedure to simplify inputs
to the model and to determine when
no further processes should be
included in the scope of the model (i.e.
model boundary is set)
Simplify – Promote – Test - Exclude
Rule 2: Can the input be generated in a simplified
form (i.e. a random distribution or fixed value), so
that there are no further inputs to the process?
Embedding SCOR in a generic procedure for
SimCM can (not in the scope of presentation):
•
Key concepts 1 – 5: Aid in providing
clear domain-specific guidelines for
extracting information from a pre-defined
process reference model and when
necessary focus consultation with
people who are knowledgeable about the
system being represented
•
Key concept 8 & 9: Aid in focusing
consultation with people who are
knowledgeable about the system being
represented to determine the detail of
the actual practice that needs to be
included from the descriptions provided
for each process element included in the
model boundary and simplified inputs
Example of SCOR inputs and outputs to a decomposed
business process
Source: SCOR V.9 (2008)
Summary & implications for further work
Domain-specific
SimCM procedure for
SCM applications
Incorporate existing
SimCM guidance in the
literature
=
Embed domainknowledge in the
form of a process
reference model
+
1. Develop a web-based application that can automate a number of the steps
2. Further refinement and validation of the SCM2
•
Feasibility & utility with a range of process reference models in different
industrial contexts