1. 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.ukm.weaver@napier.ac.uk @DrMilesWeaver #SimCM Dr. Pavel Albores, Aston Business School Dr. Doug Love, Aston Business School

2. Outline Importance of conceptual modelling and need for a SCM 2 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 SCM 2 and the incorporated key concepts –General guidelines for building an ‘effective’ conceptual modelling –Embedding the utility of a process reference model (e.g. SCOR)

3. What is a simulation conceptual model? A simulation conceptual model (SimCM): 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: ‘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

4. 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) 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).

5. The ‘idea’ behind the SCM 2 + = Domain-specific SimCM procedure for SCM applications Incorporate existing SimCM guidance from the literature Embed domain- knowledge in the form of a process reference model Provide inputs to the process of SimCM (i.e. setting the model boundary & detail) and standard descriptions? Incorporate a general process, general principles, methods for validation, advice on simplification?

6. Relationship between the requirements and outline design for SCM 2 Outline design (what procedure is needed to arrive at this conceptual model) Requirements (Specification) (what do we need the conceptual model to do) Requirements for building an ‘effective’ conceptual model Requirements for conceptual modelling for SCM application (domain-specific requirement) Validity & Credibility Model simplicity SC complexity SC detail SC objectives Supply setting General guidelines for building an ‘effective’ conceptual modelling 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 Embedding the utility of a process reference model (e.g. SCOR) Using SCOR to describe supply chain improvements Using SCOR to describe supply chain objectives Using SCOR to determine the interconnections with the supply setting

7. Phase 1: Describe the supply problem Output: Description of the improvement(s) to be evaluated, for a given objective(s) within its supply setting Phase 3: Determine how each improvement is to be represented Output: Description of the processes that represent each improvement Phase 2: Determine how each objective is to be measured Output: Description of the processes that provide data used to calculate each objective 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 Phase 7: Document and validate the conceptual model Output: A valid description of the computer model to be developed Phase 6: 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 Point of entry A formal problem formulation and structuring methodology or unstructured problem from client 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 Iterate for each PROMOTED process decided in phase five

8. 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.

9. Phase one: Describe the supply problem Output: The supply problem is described from the perspective of the client 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

10. Phase two: Determine how each objective is to be measured Output: The objective is described in terms of how it will be measured The supply chain performance metric is described using the hierarchy of metrics presented by SCOR at three different levels. 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

11. Phase three: Determine how each improvement is to be represented Output: The improvement is described in terms of how it is to be represented 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

12. 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)

13. 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)

14. 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?

15. 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 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?

16. Phase five: Formulate the model boundary Output: Provide a list of processes and inputs included in the model 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 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 Key Concept 7: Included process elements are considered in turn to identify those that could be simplified 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?

17. Simplify – Promote – Test - Exclude SIMPLIFY candidate process element that WILL generate inputs that will effect model behaviour by significantly impacting on performance measures AND CAN be simplified in a simplified form (either a fixed value or distribution) PROMOTE candidate process element that generate inputs that will effect model behaviour by significantly impacting on the performance measures AND CANNOT be simplified in a simplified form (either a fixed value or distribution) TEST candidate process elements if a decision cannot be made about whether the input to be generated will have an effect on model behaviour by significantly impacting on performance measures EXCLUDE candidate process elements if the inputs to be generated WILL NOT affect model behaviour by significantly impacting on performance measures

18. Phase five: Formulate the model boundary (2) Promoted process elements and simplified inputs Inputs and source process element that were promoted Simplified inputs Customer N/A (Customer) Customer Replenish Signal; (Customer) Customer Order Warehouse Receipt Verification (S1.2, S1.3); Scheduled Receipts (S1.1); Delivery Plan (P4); Sourcing Plans (P2); Validated Order (D1.2); Scheduled Receipts (S1.1); Planning Data (EP.3); Order Backlog (D1.11); Load Information (D1.5); Finish Goods Inventory Target Levels (ED.4); Product On Order (S1.1); Packed product (D1.10); Daily Shipment Volume (D1.4); Picked product (D1.9); Shipment Routes (D1.6, D1.7) Product Inventory Location, Finished Goods Inventory Location; Service Levels; Product Inventory Target Levels; Order Rules Factory Picked product (D2.9); Production Schedule (M2.1); Finished Product Release (M2.6); Information Feedback (M2.1 – 6); Order Signal (D2.3); Delivery Plans (P4); Load Information (D2.5); Booked Order (D2.2); Consolidated Orders (D2.4 Shipping Parameters and Documentation (ED.6); Inventory Availability (M2.2); DC/Vendor Transit Time (N/A)

19. Phase five: Formulate the model boundary (3) Candidate process elements promoted in each round Number of iterations between phase five and six Candidates process elements promoted in step 5.2.2 FactoryWarehouseCustomer Initiated with core process elements D2.10, D2.11, D2.12, D2.13S1.4, D1.8, D1.3, D1.12, D1.13N/A Iterative round 1 D2.9S1.2, S1.3, S1.1, P4, P2, D1.2, D1.11 None identified (S1.1 – simplified) Iterative round 2 M2.1, M2.6, D2.7, D2.8D1.5, ED.4 Iterative round 3 P3, M2.3, M2.4, M2.5, D2.6D1.4, D1.10 Iterative round 4 D2.3, P4D1.9 Iterative round 5 D2.3, D2.5, D2.4D1.7 Iterative round 6 D2.2D1.6

20. 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)

21. Summary & implications for further work + = Domain-specific SimCM procedure for SCM applications Incorporate existing SimCM guidance in the literature Embed domain- knowledge 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 SCM 2 Feasibility & utility with a range of process reference models in different industrial contexts