Sales and Operations Planning (S&OP

International Journal of Engineering Research in Africa ISSN: 1663-4144, Vol. 34, pp 171-188 doi:10.4028/www.scientific.net/JERA.34.171 © 2018 Trans Tech Publications, Switzerland

Submitted: 2016-12-07 Revised: 2017-10-20 Accepted: 2017-11-06 Online: 2018-01-19

Sales and Operations Planning (S&OP) Concepts and Models under Constraints: Literature Review Nabil Lahlouaa*, Abdellah El Barkanyb and Ahmed El Khalfic Faculty of Science and Techniques, Mechanical Engineering Laboratory, Sidi Mohammed Ben Abdellah University, B.P. 2202 - Route d’Imouzzer – FES, Morocco a

[email protected], [email protected], [email protected] *Corresponding author

Keywords: sales and operations planning, literature review, models, concepts, constraints.

Abstract. Globalization has had a significant impact on company’s management, particularly in the supply chain (lead time, investment in production capacity and technology, organization & management ...). The sales and operations planning (S&OP) include all the processes that link the strategic objectives of the enterprise with the production plan. The impact of the S&OP on operational performance was consistently and significantly demonstrated in the operational aspects of production; quality (conformity of production, product quality and reliability), delivery (the delivery agility, reliability of supply, manufacturing deadlines, lead times), stocks (reduction of inventory levels, inventory optimization) and flexibility (flexible volume and mix). Our objective in this paper is to present, in the first part, a literature overview of the sales and operations planning, and various research and models developed. In the second part, we will emphasize the transversal aspect of our research that involves both operational issues, tactical and strategic in a context subject to different constraints. Introduction The sales and operations planning (S&OP) plays a major role in coordinating sales, logistics and industry. The S&OP includes all process to establish the estimated production plan at the tactical level, linking the strategic objectives of the company with the operational issues of the production master plan to best balance the demand and offer; according to Feng et al. (2008) [9]. Through the S&OP, logistics and sales negotiate and coordinate to establish good production volumes on the product mix for sale. On one side, the logistics ensures of having sufficient stocks of parts and finished goods to absorb the inevitable hazards. And on the other side, commercial strives to maximize sales and control the mix to maximize profits. The purpose of the S&OP is to efficiently use the available production capacity to better respond to market demand in terms of cost, time and quality. Underutilization of capacity may prevent the company to conquer some markets. Inversely, overuse can cause high spending and large inventories if demand is overestimated. The S&OP is particularly important for international supply chains in an uncertain environment, where production management needs stability and visibility. Another major difficulty in coordination between sales and logistics concerns managerial and organizational aspects. Opposites and often conflicting objectives, lack of cross between the two entities and the fact that they are at the same level in the company induce that there is no clearly defined process for arbitrating conflicts and seek global optimum for the company : Rexhausen et al. (2012) [19]. Resolving these issues requires a strong involvement of the company’s management and the creation of crossfunctional teams. Approach and Research Methodology The approach of the research methodology is presented in this section. Since it is laborious to make a complete and exhaustive research of the topic, because the documentation is very sparse on All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans Tech Publications, www.scientific.net. (#106691824, University of Wollongong, Wollongong, Australia-04/02/18,00:19:53)

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various sources, we have opted to follow a specific approach by cross-analysis of (i) some mistresses issues related to our thematic and ( ii) procedural approach widely used in the research literature. Fig. 1 provides a mapping of our research methodology; How is treated S&OP in literature

What are the different concepts and models related to S&OP

Which aspects of constraints in the context of S&OP require more attention in academic research

Locating studies

Identifying keywords to search

Criteria and Study selection

Reporting and Synthesis

Fig. 1. Procedure and research methodology. Selection of computerized databases and Location studies. This step aims to identify relevant research sources. The recommendations of Thome et al. (2012) [20] and Tuomikangas and Kaipia (2014) [24] related to their research conduction in the same thematic advocate three databases : EBSCO, Emerald and ScienceDirect. According to the authors, these databases cover most scientific interest journals in the areas of operations management, organizational management, and social sciences. In our search, ScienceDirect database was mainly used, in addition to DOAJ (Directory of Open Access Journals) and Google Scholar. EBSCO and Emerald were used in a second part on the manual addition to reading and synthesizing summaries. Our research was carried out and stopped at the end of December 2015. Identifying keywords to search. The following keywords were used in the search: "sales and operations planning", with quotes to target our thematic and avoid simple words like schedule are returned in the search without bond interesting. Also other words were used as "SOP" and "S & OP" but have not given satisfaction over the results returned and were eliminated in the next phase. Criteria and Study Selection. To target our research, mistresses issues presented in Fig. 1 have provided guidelines and the following exclusion criteria were applied when reading the titles of articles, summaries and full texts if necessary: (i) redundant documents; (ii) incomplete documents or commercial purpose; (iii) documents do not address the S&OP as an overall concept (process planning or sales only). Results and categorizations. The database search identified 256 papers, and all abstracts were read by at least two authors. A full bibliography list is available from the principal author upon request. First, duplicate papers were excluded on the basis of articles’ titles, yielding 63 excluded papers. The second exclusion criterion, not full papers or commercial purpose, resulted in 39 further excluded papers. The third exclusion criterion resulted in 72 articles being excluded for not treating the S&OP as an overall concept. This research was completed manually by referring to the main publications which helped to add 28 new documents selected. The final total; 82 documents were selected for our literature search. See Fig. 2.


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Result database query 256 redundant documents 63 incomplete or commercial documents 39 documents do not address the S&OP as an overall concept 72 manual added 28 total retained 82

Fig. 2. Results of the literature search.

Fig. 3 shows the evolution in the number of papers selected for our literature review, interest in the subject believes increasing, as evidenced by the number of recently published articles on various aspects of the S&OP, the top of the peak is observed on 2014. the table 1 provides a detailed list of all papers.

Fig. 3. Number of publications on S&OP by year (N=82). Table 1. Papers selected by year and by source. Authors

Year

Chung-Hsing Yeh Mark J. Euwe A Gunasekaran Jan Olhager Genin Patrick

1997 1997 1999 2001 2001

Manoj K. Malhotra Hendrik Van Landeghem Martin Rudberg Bernhard Fleischmann

2002 2002 2003 2003

Lapide, L. Lapide, L. Jen-Ming Chen Charu Chandra Lapide, L. Bower,P. Mahesh Gupta D.J. van der Zee

2004 2004 2005 2005 2005 2005 2006 2006

Source International Journal of Production Economics Computers in Industry International Journal of Production Economics International Journal of Production Economics "Conception et Production Intégrées : CPI’2001, Fès 24-26 oct. 2001" Journal of Operations Management Journal of Operations Management Omega Handbooks in Operations Research and Management Science, Elsevier Journal of Business Forecasting Journal of Business Forecasting Computers & Operations Research Omega Journal of Business Forecasting Journal of Business Forecasting Technovation International Journal of Production Economics

Our Ranking(*) B A C A A A A C B A A A C A A C C

174


Source

Our Ranking(*) C A A C B C A A C A A C C B

Authors

Year

Lapide, L. Bower,P. Jaya Singhal J.E. Boylan Olhager, J. Hadaya, P. Grimson, J.A. Yan Feng Patrik Jonsson Affonso, R. Milliken, A. L. Robert Fildes Lapide, L. Nakano, M.

2006 2006 2007 2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009

Boyer,J.E. Ching-Hua Chen-Ritzo Ö. Yurt

2009 2010 2010

Ely Laureano Paiva Jan Olhager Paul Goodwin Erma Suryani Peter Nielsen Aris A. Syntetos Feng, Y. Ivert, L. K. Schlegel, G. L. Rogelio Oliva J. Váncza, L. Monostori Ruud H. Teunter Ching-Hua Chen-Ritzo Ivette Luna Inneke Van Nieuwenhuyse Lapide, L. Lapide, L. Milliken, A. L. Sodhi, M. S. Antônio Márcio Tavares Thomé G.J. Hahn G.J. Hahn Jan Olhager Daniel Rexhausen Kelleher, M. Mansfield, A. Thomé, A. M. T. Wang, J. Warren, L. Llanos Cuenca Mario Guajardo Anssi Käki Alexander,D. Stephan M. Wagner Nina Tuomikangas Can Eksoz

2010 2010 2010 2010 2010 2010 2010 2010 2010 2011 2011 2011 2011 2011 2011

Journal of Business Forecasting Journal of Business Forecasting Journal of Operations Management International Journal of Production Economics International Journal of Production Research Industrial Management & Data Systems International Journal of Logistics Management International Journal of Production Economics International Journal of Production Economics Production Planning & Control Journal of Business Forecasting International Journal of Forecasting Supply Chain Management Review International Journal of Physical Distribution & Logistics Management Journal of Business Forecasting European Journal of Operational Research In Woodhead Publishing Series in Food Science, Technology and Nutrition International Journal of Production Economics Computers in Industry European Journal of Operational Research Simulation Modelling Practice and Theory Computers in Industry International Journal of Production Economics International Journal of Production Research Industrial Management & Data Systems Journal of Business Forecasting Journal of Operations Management CIRP Annals - Manufacturing Technology European Journal of Operational Research European Journal of Operational Research International Journal of Forecasting Computers in Industry

2011 2011 2011 2011 2012

Journal of Business Forecasting Journal of Business Forecasting Journal of Business Forecasting Journal of the Operational Research Society International Journal of Production Economics

B B A A A

2012 2012 2012 2012 2012 2012 2012 2012 2012 2013 2013 2013 2013 2014 2014 2014

International Journal of Production Economics International Journal of Production Economics Journal of Engineering and Technology Management Journal of Operations Management Journal of Business Forecasting International Journal of Applied Forecasting International Journal of Productivity and Performance Management International Journal of Computer Integrated Manufacturing Journal of Business Forecasting Computers in Industry European Journal of Operational Research Computers in Industry Journal of Business Forecasting Business Horizons International Journal of Production Economics International Journal of Production Economics

B C A B B B A A A B B A C A A B

A A A A A A A A C A B A A C C C C A


Authors

Year

Source

175

Our Ranking(*) C

Jose Antonio Heredia 2014 Procedia CIRP Álvaro Lâm Laurent Lim 2014 International Journal of Production Economics Travis Toka 2014 Journal of Operations Management Carme Martínez-Costa 2014 International Journal of Production Economics Gilvan C. Souza 2014 Business Horizons Kenneth B. Kahn 2014 Business Horizons Alex Marques 2014 International Journal of Production Economics Thomas Ponsignon 2014 Omega Jeongsu Oh 2014 Computers in Industry Thomas Staeblein 2015 International Journal of Production Economics Patrik Jonsson, 2015 International Journal of Production Economics, Volume 168, Linea Kjellsdotter Ivert October 2015, Pages 118-130 Naeem Bajwa, Charles 2015 Omega, Available online 19 December 2015 R. Sox, Rafay Ishfaq (*) We have preceded a relevancy ranking of the document: (A) pertinent; (B) moderately pertinent; (C) pertinent. This original approach allowed us to put more focus on the full text of relevant articles.

A C A C C B A C A A B slightly

Reporting and synthesis. The next chapter synthesize the S&OP’ state of the art. Chapter IV gives the various concepts and positioning of the S&OP in the planning decisions hierarchy. Chapter V summarizes the main constraints and models found. How is it Treated the S&OP in Literature Malhotra and Sharma (2002) [4] begin their article with a question: "In Harvard Business Review published 25 years ago, Shapiro (1977) posed the question: marketing and manufacturing can co-exist". This question pinpoints the appearance of conflicting objectives, and often antagonistic of the two functions. In the early 1950s, Charles C. Holt, Franco Modigliani, John F. Muth, and Herbert A.Simon (HMMS) began work on a project, ‘‘Planning and Control of Industrial Operations’’, at the Graduate School of Industrial Administration (GSIA) at the Carnegie Institute of Technology. William W. Cooper, who was also at GSIA, initiated the project, and the Office of Naval Research supported it. This early work of HMMS in aggregate production planning has evolved into a major business process known as sales and operations planning; according to Singhal and Singhal (2007) [8]. The S&OP as terminology was originally in the articles on MRPII (manufacturing planning resources), or similar systems, where some authors have used interchangeably to refer to the term of the aggregate production planning (APP ). Since the 1980s, the significance of the S&OP has been expanded, and sales planning has been included in the process of S&OP. So the S&OP has two components; sales planning (based on demand) and production planning, which determines the capacity requirements, inventory levels and / or the level of the order book; according to Olhager et al. (2001) [2]. The S&OP includes all the processes that link the strategic objectives of the business with the production plan, to best adapt the supply (or capacity) to market demand; according to Feng et al. (2008) [9]. The S&OP is developed horizontally and involves numerous business functions (sales, finance, marketing, supply chain). The development of the S&OP was the subject of numerous studies varied in recent years. This research area is experiencing a growing interest among researchers and industrialists. Thomé et al. (2012) [20] present a detailed literature review on the S&OP, they show that this area of research is very sparse, varied and has many research opportunities. Tuomikangas and Kaipia (2014) [24] show the considerable impact of effective management of the S&OP on business performance through a platform and the coordination mechanisms that play a central role in the S&OP to align corporate strategy and operational planning. Lim et al. (2014) [25] show how the operational control has evolved over the last fifty years to go from a very operational level planning (production facility) at a more aggregated level

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(S&OP and more generally the overall supply chain planning), to better satisfy customers and link directly to suppliers through a concrete study of the automotive industry that has perfectly followed the trend, but highlighting the growing need for more flexibility in the S&OP, particulary the supply chain internationalization and the high volatility in demand. The supply chain concept (Christopher, 1992) has introduced the value of integration to business partners. This integration not only applies to the material flow from raw material supplier to finished product delivery, but also to the information flow from the market (i.e. the anonymous consumer) back to the supply chain partners. Supply chain management (SCM) mostly focuses on using of this information to optimize the material flow through the successive steps of inbound logistics, operations and outbound logistics across the supply chain. More recently the term demand chain management (DCM) has emerged, focusing on the marketing, sales and services part of the value proposition. Demand chain management tries to obtain more reliable and detailed information about (prospective) consumers. It provides feedback on changing customer taste, evolving product life cycles, and the impact of promotions. The integration of SCM and DCM will lead to supply chains which more often deliver the right products and services : Landeghem and Vanmaele (2002) [5]. Nothing is more important for a product-based firm than the ability to deliver the right quantities of the right product to the right customer at the right time, without stockpiling unnecessary inventory. This requires a continuous and balanced matching of product supply and demand. Betteraligned operational and strategic plans and a better balance of supply and demand would benefit firms in the forms of smaller inventories, higher utilization, lower costs, and happier customers. It would also increase firms competitive advantage. However, even today many organizations still operate under central control through functional departments. The linkage between sales and operations especially requires better integration and collaboration across operational silos. The outcomes of this disjointedness are delays and amplification of the information flow, suboptimal corporate plans, uncoordinated reactions within the business, insufficient operational flexibility, and discrepancies in supply and demand; according to Wagner et al. (2014) [23]. The same authors formalize a survey, presented in Table. 2, very telling of the benefits of alignment of all functions related to S&OP. Table 2. Benefits of aligning S&OP. S&OP is expected to significantly…

Mean

increase forecast accuracy 4.80 increase supply chain visibility and hence reduce the risk of supply chain disruption 4.59 reduce inventory levels and thus cost of capital while maintaining or improving 4.45 customer service levels improve customer satisfaction levels 4.31 improve product availability for marketing and promotional campaigns 4.27 reduce the number of expedited shipments and rush orders 4.26 reduce the amount of obsolete products 4.24 increase the return on assets (ROA) 4.20 increase capacity utilization 4.14 better balance production and sourcing costs against transportation and safety stock 4.00 costs drive revenue growth through clearer focus on high margin products 3.93 increase sales and generate top line revenues 3.90 Note: n=88; 5-point Likert scales with 1: ‘strongly disagree’ and 5: ‘strongly agree.’

Standard Deviation

0.53 0.58

0.68 0.82 0.89 0.82 0.77 0.85 0.82 0.92 1.02 1.03

Conceptualization and Positioning of the S&OP in the Hierarchy of Planning Systems Malhotra and Sharma (2002) [4] present in Fig. 4, a simple framework that lists the key areas of decision-making within a firm where opportunities exist for inter-functional integration between marketing and operations functions. The S&OP is between the strategic and tactical levels. They also emphasize the importance of:


177

• The alignment between the goals and objectives of marketing and production functions; • The alignment between product pricing and production costs; • Alignment between the manufacturing and distribution channels; • Problems in the supply and their interaction with the maintenance of the different segments of the market chain. Marketing Function Strategic

Operations Function

Strategic Planning Integration Strategic or Visionary Forecasting

New Product and/or Process development

Organizational Performance

Tactical Forecasting Marketing/Sales and Operations Planning (Demand Management) Operational Integration Tactical

Fig. 4. Marketing and operations integration framework within a firm. Landeghem and Van Maele (2002) [5] introduced the S&OP as a tactical level in the supply chain as shown in Fig. 5. Supply Chain Infrastructure and Planning Policies

Strategic Planning

Demand Chain Planning

Planning set points

Supply Chain Planning

Market parameters

Customer orders and Forecasts

Tactical Planning Material Flow Triggers

Purchasing

Manufacturing

Assembly

Distribution

Customers

Execution Planning

LEVEL Strategic

TYPICAL NAME Supply network design business planning

What is typically being decided (not exhaustive) Location of distribution centers, plants, buffer stocks, flexibility versus buffers, pull versus push, planning methods used, information systems adopted, . . .

Tactical

Sales & operations planning

Production volumes per product family, target levels of stock (both operational and safety), transport parameters (TL or LTL, mode), average capacity utilization, cost and cash requirements for the next planning period

Operational

Master production scheduling plant scheduling

Production volume and timing per product item (SKU), transportation orders, purchase orders, detailed capacity usage per shift

Fig. 5. Hierarchical levels in Supply Chain Planning.

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Genin et al. (2001) [3] report the principle of MRP (Material Requirements Planning) and how did the need for synchronization of the available quantities of materials, components and subassemblies in a context of fixed deadlines and stable products. The move to MRP II (Manufacturing Resources Planning) was justified by the need to take into account the resource capacity, production, procurement, subcontracting, storage, distribution, ... but also needs financial. adjustments to decisions about these resources are taken in advance to different levels in the light of their implementation deadline. So the MRP II planning structure has five levels and planning decisions as shown in Fig. 6: • Strategic plan ; • Sales and Operations Planing (S&OP) ; • Master Production Schedule (MPS) ; • Planning Requirements Components (MRP) ; • Workshop Piloting. DATA MANAGEMENT

PLANIFICATION

CAPACITY MANAGEMENT

1/ Strategic Plan

Orders forecast

Finished goods inventory

2/ Sales and Operations Plan

Global Resource Planning (Factories, Hiring ...)

3/ Production Schedule (MPS)

Global Capacity Planning (Critical Resources)

4/ Calculation of Net Needs (MRP)

Capacity Requirements Planning (detailed Resources)

5/ Shop Floor Control

Control: Inputs / Outputs Sequencing of operations

Nomenclatures

Inventories raw materials and subassemblies

Post load

Ranges

Fig. 6. Framework of hierarchical planning structure of MRP II. Genin et al. (2001) [3] also explain how the S&OP shall adjust the availability of resources on industrial factorys, labor, machine capacity, material inventories, etc .. to achieve the sales plan at defined dates. If these goals can not be reached, a decision of outsourcing can be taken. In some supply chains, the problem of the allocation of distribution volumes between sites is also treated at this level: the possible transfer of materials, testing and quality approvals with unavoidable delays which require to make these decisions in right moment. Lim et al. (2014) [25] specify the precise positioning of the S&OP in the hierarchy planning decisions, and that its scope can vary from one study to another, and depend on the context highly. Generally, management decisions in an organization are prioritized according to the following three levels (Anthony, 1965), illustrated in Fig. 7. The boundaries between these categories may differ depending on the context of study: • The strategic level concerns decisions over the long term to carry out the company's strategy. Strategic planning is based on aggregate data. • The tactical level includes medium term decisions on the use of resources and the planning of activities, from a more detailed level than the strategic plan (product family, finer temporal stitch, etc.). • The operational level includes short-term decisions to plan in detail the operations defined in the production plan at the finer details (finished products, components, production workshop, etc.).


HORIZON

DECISIONS EXAMPLES

Long-term 1 to 5 years

 New factory building  Distribution network conception

Mid-term 1 month to 1 year

 Sub-tracting  Load balancing between factory

Short-term 1 day to 1 month

 Scheduling  Sourcing

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Fig. 7. Hierarchy of planning levels, according to (Anthony, 1965). Chen and Chen (2005) [7] explain how the latest manufacturing technologies enhance crossfunctional interaction between manufacturing and marketing such as Flexible manufacturing system (FMS), just-in-time (JIT), quick response (QR), manufacturing resources planning (MRP II), and enterprise resource planning (ERP). In spite of increasingly emphasizing on the aspect of customer demands, many production decision-making processes do not take marketing’s dynamic nature into accountles. They schematize two processes as shown in Fig. 8: (a) coordinated decision process between marketing and production planning, (b) decentralized decision process between marketing and production planning. Coordination Center (maximizing the total profit) Supplier

Production / Purchase / Distribution Management

Demand Management

Master Planning

Demand Planning

Material Requirement Planning

Demand Fulfillment

Customer

Production Planning Distribution Planning Scheduling Transportation Planning

(a). Coordinated Process. Supplier

Purchasing

Production System (Minimizing the production cost)

Master Planning

Sales / Distribution (Maximizing the gross profit)

Customer

Material Requirement Planning Shop Control & Scheduling

(b). Decentralized Process.

Fig. 8. Decision process (coordinated and decentralized) between marketing and production planning.

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Fleischmann and Meyr (2003) [6] treat the supply chain planning matrix (SCP) and give an overview of the planning tasks in all possible supply chain as shown in Fig. 9. However, according to the type of supply chain under consideration, the importance of simple tasks of planning is quite different. In addition, the allocation of planning tasks for planning levels and the supply chain process is somewhat fuzzy because positioning can also vary depending on the type of supply chain. Procurement

 LONG TERM

 MIDTERM

 SHORTTERM

 Materials program ;  Supplier selection ;  Cooperation.

Production

 Plant location ;  Production system.

Distribution

Sales

 Physical distribution structure.

 Product program;  Strategic sales planning.

• Personnel planning; • Contracts ; • Material requirements planning.

• Master production scheduling ; • Capacity planning.

• Distribution planning.

• Mid-term sales planning.

- Personnel planning; - Ordering materials.

- Lot-sizing; - Machines scheduling; - Shop floor control.

- Warehouse replenishment ; - Transport planning.

- Short-term sales planning.

Flow of goods

Information flows

Fig. 9. Planning tasks according to the SCP-matrix. Feng et al. (2008) [9] show that although the concepts of SCP and S&OP are relatively new, the idea of coordinated planning can be traced back to as early as 1960 by Clark and Scarf (1960), who studied multi-echelon inventory/distribution systems. Since that time, research on coordination of various partial sections of the supply chain has been conducted. However, very few models have attempted to address the integration of sales, production, distribution, and procurement simultaneously. Based on this initial work, they proposed a modeling approach (a) to assess the value of the S&OP, with an extension to multi-site alternatives (b) as shown schematically in Fig. 10. Procurement

Production

Distribution

LONG TERM

Strategic planning

MID TERM

Supply chain based S&OP (SC - S&OP)

SHORT TERM

Procurement scheduling

Production scheduling

Transportation scheduling

Flow of goods

(a). General approach.

Sales

Order acceptance

Information flows


Procurement

Production

LONG TERM

Distribution

181

Sales

Enterprise strategic planning

MID TERM

Multi-site centralized Supply Chain based S&OP (SC - S&OP) Mill 1 Procurement scheduling



Order acceptance

Mill 2 SHORT TERM

Procurement scheduling



Order acceptance

Mill n Procurement scheduling



Flow of goods

Order acceptance

Information flows

(b). Multi-site alternative.

Fig. 10. The integrated S&OP in supply chain planning context. Stadtler and Kilger introduced a matrix approach for the structure of advanced planning systems as illustrated in Fig. 11. It includes four stages in a supply chain, i.e. procurement, production, distribution, and sales. The structure holds for an individual firm as well as an entire supply chain; according to Olhager (2010) [13]. Käki et al. (2013) [22] use the same model to link models to generic planning process in a typical advanced planning system as shown schematically also in Fig. 11. Procurement

Production

LONG TERM MID TERM

SHORT TERM

Distribution

Sales

Strategic Network Planning Master Planning

Purchasing and Material Requirements Planning

Production Planning

Scheduling

Distribution Planning Transport Planning

Demand Planning

Demand Fulfillment & ATP

Fig. 11. The supply chain planning matrix (based on Stadtler and Kilger 2000) and Typical planning modules of an Advanced Planning System (according to Meyr et al. 2002). Thomé et al. (2012) [20] propose a framework as depicted schematically in Fig. 12 summarizing the empirical results and gathering all "descriptors". These descriptors of the study summarize moderators or effects that occur between S&OP and its results.

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Business Plan Corporate Strategic Plan CONTEXT • Region/Country • Industry • Manufacturing Strategy • Product-Process Matrix • Product Aggregation • Hierarchical Planning • Planning Horizon

INPUTS • Functional Plans • Forecasts • Operational Constraints • Inventory • Budget • Costs

STRUCTURE and PROCESSESS Meeting and Collaboration (Participants, trust/Commitme nt, Regularity)

Organization (Empowerment, Teams, Steps/Agenda)

S&OP Metrics

Information Technology (Systems and software [transactional; Analytical], Models and simulation)

OUTCOMES Plans Integration • Marketing • Sales • Operations • Finance

Profit Optimization

Operations

Fig. 12. Literature search synthesis framework (according to Thomé et al. 2012). Wagner et al. (2014) [23] explained that the main purpose of the S&OP is to develop tactical plans that provide management the ability to strategically direct its businesses to achieve competitive advantage on a continuous basis by integrating customer focused marketing plans for new and existing products with the management of the supply chain. The process brings together all the plans for the business (sales, marketing, development, manufacturing, sourcing, and financial) into one integrated set of plans. Fig. 13 illustrates the vertical and horizontal alignment of the various plans. They linked together that S&OP is an ongoing process of monthly planning, reviewing, and evaluation to generate one set of integrated profit maximizing plans by ensuring the involvement of all key stakeholders. These plans comprise the game plan for each business function, whilst business performance is regularly reviewed, in order to strategically direct the organization. The process facilitates the sending of early warning signals when supply and demand are at risk of becoming imbalanced so that the company can respond quickly to changing market and operations situations. S&OP consists of five steps: • Data collection ; • Demand Planning ; • Procurement Planning ; • Pre-meeting ; • Implementation Meeting.


183

Vertical Collaboration and Alignment

Strategic / Business Plans

Sales and Operations Planning Manufacturing Plans

Supply side Plans

Sourcing Plans

Inventory Plans

Life cycle Plans

Demand side Plans Financial Plans

Budgeting

Investment Plans

Marketing Plans

Cash flow Plans

Sales Forecast

Horizontal Collaboration and Alignment

Fig. 13. Alignment of plans through S&OP. The S&OP and Production Systems under Constraints The field of production planning, or operations under constraints, is a very rich field of research since this area is vast and leads to various and many models with different hypotheses and objectives; Table. 3 summarizes the main models and constraints discerned following our literature search discussed in this document. Table 3. Main constraints retrieved concerning the S&OP. Reference Hendrik Van Landeghem et al. (2002) [5]

Jen-Ming Chen et al. (2005) [7]

Main ideas of the research - Robust planning based on risk assessment of the supply and demand chain; - Model based on Monte Carlo simulation; - Using the example of the beer’s game; - Case study showing the value of the robust planning in a European chemical company.

- Proposal of two political decision making, coordinated and decentralized, which determine the price and optimal production (lot size / scheduling) for an article that is deteriorating on a finite planning horizon; - Problem formulated as a dynamic programming model coupled with iterative search process associated with a numerical study;

Principal research method • Conceptual Model • Case study

• Mathema-tical model • Comparative Study

-

Constraints related to S&OP Supplier delivery time; Supplier Quality; Manufacturing yields; Time of transport ; Costs; Political Environment; Customs Regulations The available capacity The availability of contractors Delays of information; The demand; Price fluctuations. Deterioration of the articles; Price setting ; Size of production lots; Time variation of demand.

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Reference

Main ideas of the research

Jaya Singhal et al. (2007) [8]

- Early work in the 1950s, a team led by Holt, Modigliani, Muth, and Simon have conducted work on aggregate production planning and evolved into a major business process known as sales and operations planning. - Planning of the total production and its central role in operations management with the linking supply chains and other functions in the organization. - Presents the fundamentals of the S&OP process and a modeling approach to evaluate its impact before implementation ; - 3 models : (1) multi-site supply-chain-based S&OP (SC-S&OP), that integrates the cross functional planning of sales, production, distribution, and procurement centrally ; (2) multisite sales–production planning-based S&OP (SPS&OP), in which the joint sales and production planning is carried out centrally while the distribution and procurement are planned separately in each site ; (3) decoupled planning (DP), in which the sales planning is carried out centrally while the production, distribution, and procurement planning are performed separately and locally ; - The models are developed for an alternative multi-site manufacturing system that has different suppliers, produces different products and serves different customers on a make-to-order (MTO) basis where backlogs are allowed.

Yan Feng et al. (2008) [9]

Chen-Ritzo et al. (2010) [10]

Thomé et al. (2012) [20]

Principal research method • Literature review

• Conceptual Model • Mathema-tical model • Comparative models Study • Case study

-

- Addresses the problem of aligning demand and supply in configure-to-order systems ; - Stochastic Programming Methods (two stochastic models: an explosion problem model and an implosion problem model) ; - Practical Optimizations to face uncertain demand;

• Stochastic Models • Case study

- Systematic review of the literature on S&OP. The purpose of this systematic review is twofold : (i) to integrate the highly dispersed work on S&OP in order to identify and analyze S&OP as a business process and (ii) to assemble quantitative evidence of its impact on the performance of the firm ; - A Framework of literature search that embraces S&OP context information, inputs and goals, structure and processes, outcomes, and results.

• Literature review • Framework

-

Constraints related to S&OP Costs; Flexibility; Delivery delay ; Long-range capability; Mix-product; Supply levels; Time of order fulfillment; Balance of flows (sales, production, distribution, supply) Production capacity Sales delays Planning period Warehouse capacity (stocks) Truck loading requirements Shipping capacity of suppliers Shipping Site capacity Safety stock of raw materials Capacity inventories of raw materials Supply capacity of raw materials Seasonal variability of supply Placing orders Contractual Purchase quantity Configuration of uncertain orders Flow of component stocks Out of stock Flexibility supplier Goodwill sales targets Procurement Lead time Supply capacity Supplier constraints Production capacity Work force level Operational resources Production time Production flexibility Delivery capacity Delivery delay Transportation status Service capacity Service level targets Financial budgets Financial goals


Reference


Käki et al. (2013) [22]

- Importance of modeling uncertainty in risk management models, illustration by examples of inventory replenishment, purchasing and tactical planning of strategic capacity, which demonstrated how model results vary greatly when the hypotheses changing distribution of the application; - Shows that the models are sensitive to the shape of the distribution of the application, not only to simple parameters such as expected demand or the change in demand: asymmetry, minimum or maximum limits, or bimodal demand. - A S&OP problem based on the actual situation of Renault, a French global automobile manufacturer. The issue is to find the best tradeoff between sales requirements and industrial constraints while limiting inventories, emergency supplies and keeping delivery lead times reasonable for customers ; - A new planning method with simulation model based on flexibility rates is presented. The flexibility rates are defined to limit orders of a given type of vehicles, during a certain period.

Lim et al. (2014) [25]

MartínezCosta et al. (2014) [26]

- An up-to-date review on strategic capacity planning in manufacturing companies, with two main objectives: (i) to describe and analyze the strategic capacity planning problems; and (ii) to review the mathematical programming models proposed in the literature for dealing with these problems ; - A framework for capacity planning is presented, consisting of three main phases : problem definition (considering context, characteristics of the manufacturing system and specific factors that could influence the decision-making process),model design and solution procedure.

Principal research method • Case study • Guidelines (for efficient use of probability distributions in the decision models for operations management)

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• Simulation Model

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• Literature review • Framework

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185

Constraints related to S&OP Uncertain demand Installed capacity Distribution shape of demand Safety stocks Procurement costs

Volatile demand Diversity of products Distant suppliers Inventory levels Urgent procurement Delivery delay Impatient customers Logistical costs Inventory costs Loss of orders Flexibility rate Orders acceptance capacity Capacity of resources Inventory balance and finite budget Capital balance constraint Production profit Purchasing costs Renting capacity resources Salvage value of sold equipment Capacity constraints Balance between inventory and backlogging Budgets Capital available for acquiring the necessary resources Lower and upper bound for the capacity expansion Scale-up constraint Product life constraint Timing constraints Shipment balance constraint Distribution planning constraints

186


Reference


Ponsignon and Mönch (2014) [27]

- A simulation-based framework that allows for modeling the behavior of the market demand and the production system to study the performance of the two heuristic approaches to solve the problems of the Tactical Planning in semiconductor manufacturing ; - A genetic algorithm and a rule-based assignment procedure, is evaluated within a rolling horizon setting while considering demand and execution uncertainty. - Compare the order fulfillment system of German and Japanese auto makers as a sample of industrial practice; - Conducted two in-depth case studies at one German and one Japanese auto maker to map planning and scheduling functions along the order fulfillment process. Additionally, these results were linked with secondary data sources; - The sample reveals a great variation in manufacturing conditions, product variety, and managerial practices in order fulfillment. However, contrary to common perception, planning and scheduling processes differ much less between automakers even in the light of regional differences concerning order fulfilment, different levels of product variety and mixedmodel line manufacturing practice.

Staeblein and Aoki (2015) [28]

Principal research method • Framework based simulation

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• Survey • Framework • Case study

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Constraints related to S&OP Capacity limitations (bottlenecks of work centers) Unfilled firm orders Satisfaction of supply reservations Inventory levels Fixed production costs Additional demand forecasts NA

Conclusion and Perspectives This literature review has enabled us to analyze and summarize, in terms of concepts and models under constraints, the state of the art on existing S&OP. Categorizing items revealed an increase of published articles in recent years. This indicates the challenges that companies must identified in terms of demand changes and adjustment of supply accordingly. We have reviewed the key concepts related to S&OP and its positioning within the hierarchy of planning decisions. and as we explained how its scope can vary from one study to another, and are highly dependent on context. Some authors indicate that while the concepts of Supply Chain Planning and S&OP are relatively new, the idea of a coordinated planning can be traced back to the 1960s ... Other concepts show that the main purpose of the S&OP is to develop tactical plans that strategically ensure businesses gain competitive advantage on a continuous basis by integrating the different levels of the company (sales, marketing, development, manufacturing, procurement, and financial) in an integrated set vertically and horizontally. In a second phase we synthesized the main constraints described in the S&OP models, and we had observed the variety and multitude of these constraints that depending also on studies and context. This literature review also enabled us to identify the S&OP as a complex phenomenon that might benefit from academic research, especially empirical studies and specific models in depth. Our objective thereafter, is to underpin again research in this field by exploring advantage search areas. Then we will proceed with development and modeling, based on the "simulationoptimization", a S&OP’s problematic subjected to various constraints ...


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