Planning risks or risky planning? A multiple-case study on how S&OP can cope with supply chain risks

(1)

Planning risks or risky planning? A multiple-case study on

how S&OP can cope with supply chain risks

University of Groningen

Faculty of Economics and Business

MSc Supply Chain Management

Sido de Haan

S.J.de.Haan.3@student.rug.nl

s2812444

+31 627094849

Supervisors: D.P. van Donk & K. Scholten

Deadline: 27

th

of July 2016

Word count: 12.650

Abstract

This research aims to explore whether and how the standardized S&OP process can cope with supply chain risks. A multiple-case study was conducted, analysing the process of seven organizations in the process-industry. Findings show that S&OP can cope with supply chain risks in multiple ways: maintaining a detailed planning object, performing the process on a monthly granularity, supplementing the standardized process by risk-driven activities, conducting scenario management and performing S&OP on multiple planning levels. S&OP’s ability to cope with supply chain risks is improved by: Cross-activity involvement, high IT-supportiveness, accurate forecasts and structural evaluation mechanisms. The findings provide additional insights and understandings on managing risks within the standardized S&OP process. In a practical sense, the results can be used as a benchmark for S&OP managers to improve their abilities to cope with supply chain risks within their S&OP process.

(2)

2

Figures and Tables

Figure 1: Conceptual Model ... 7

Figure 2: Coding procedure ... 11

Figure 3: Mechanism 1. Involvement of supply planners in demand planning ... 18

Figure 4: Mechanism 2. Perceived IT-supportiveness ... 19

Figure 5: Mechanism 3. Perceived forecast accurateness (demand & supply) ... 19

Figure 6: Mechanism 4. Structural evaluation ... 20

Table 1 & 2: S&OP setup and process-parameters ... 5

Table 3: Case descriptions & Setup of the S&OP processes ... 9

Table 4: Data collection details ... 10

Table 5: Safeguarding measures for reliability & validity ... 11

Table 6: S&OP activities constituting the processes of the cases ... 12

Table 7: Focus of the scenarios and constraints ... 16

Table 9: S&OP’s planning orientation ... 17

(3)

3

1. Introduction

Recent literature highlights the need for planning approaches with a dynamic nature (e.g. Thomé et al., 2012 and Ivert et al., 2015), able to embrace risks and capable to adapt to contingencies occurring within or outside the organization’s supply chain (Sing and Lee, 2013). A planning approach receiving increasing attention is the Sales and Operations Planning (S&OP) (e.g. Grimson and Pyke, 2007; Thomé et al., 2012; Tuomikangas and Kaipia, 2014; Ivert et al., 2015), a “one-size-fits-all-approach” (Noroozi and Wikner, 2014, p.1), that is typically characterized by its standardized and formalized nature (Proud, 1999 IN Noroozi, 2014; Ivert and Jonsson, 2010; Tuomikangas and Kaipia, 2014). The commonly acknowledged downside of such a standardized process as S&OP is its inability to cope with risks, which requires variability and adaption to different situations and the environment (Weiss and Maher, 2009). Therefore, this research aims to explore whether and how the standardized S&OP can cope with supply chain risks.

S&OP aims to match demand and supply on the tactical horizon (e.g. Thomé et al., 2012; Tuomikangas and Kaipia, 2014) by aligning the involved business functions and supply chain partners (Stadtler, 2005). Yet, many risks can interfere with this aim. Therefore, it is remarkable that extant literature considering risks in S&OP is scarce. One of the few articles attempting to address this topic is the research of Sodhi and Tang (2010), who are proposing an approach to tackle demand-related risks by performing demand planning (one of the activities of S&OP), with a simulation-model. To complement Sodhi and Tang (2010), Ivert et al. (2014) and Ivert et al. (2015) took a broader view, also considering supply and process-related risks. They found that although S&OP is a generic and standardized process with formal designs, organizations are trying to adjust S&OP’s design according to the contingencies within the planning environment, to be able to comply with S&OP’s aim. While the previous researchers show an increasing interest of factors influencing the standardized S&OP design, Sodhi and Tang (2010), Ivert et al. (2014) and Ivert et al. (2015) all conclude that a lot of research still needs to be done concerning S&OP: “[…] the initial finding about the dynamic nature of S&OP needs further research” (Ivert et al., 2015, p. 767). In supplementing these researches, this research will consider risks as organizational contingencies. The limited number of articles focussing on S&OP and risks only considered unforeseeable risks implying an unknown distribution of the potential disruptive-event, which requires a reactive, ad-hoc approach (Ivert et al. 2014). However, risks can also be foreseeable via anticipatory and proactive approaches by organizations (Payne, 2015).

Therefore, this research aims at determining how S&OP can cope with foreseeable supply chain risks.

In exploring S&OP’s ability to cope with foreseeable supply chain risks, a multiple-case study was employed. Therewith, we follow the recommendations of Thomé et al. (2012) and Ivert et al. (2014) to describe the S&OP processes in a great level of detail, which increases the understanding of how the planning process works and adapts to contingencies within the organization’s environment.

(4)

4 when impending supply chain risks occur, resulting in a better alignment between demand and supply. Successfully coping with foreseeable supply chain risks can also enhances the organization’s revenues, inventory management, customer-service management, product commercialization and the performance of the supply chain as a whole.

(5)

5

2. Theoretical background

2.1. Sales and Operations Planning and setup & process-parameters

S&OP is commonly defined as: “a business process that links the corporate strategic plan to the daily operational plans and enables companies to balance demand and supply for their products (Gregory, 1999; Wight, 1999 and Dwyer, 2000)” in Grimson and Pyke (2007 p. 323). According to the terminology of Lawrence and Lorsch (1967), S&OP is considered as a cross-functional ‘integrative-device’, allowing managers to strategically direct their business by aligning internal operations such as marketing, operations, and finance (Thomé et al., 2012). S&OP ensures that the various plans of the different departments are reconciled, which enables coordination and consensus (Oliva and Watson, 2011). This is also known as the internal S&OP, which is the focus of this study without compromising the importance of coordination with suppliers and customers within the supply chain, a prerequisite of successfully conducting S&OP (Lapide, 2005 and Grimson and Pyke, 2007).

In general, literature agrees on a twofold purpose of S&OP: (1) horizontal alignment by balancing supply and demand (e.g. Thomé et al., 2012; Feng et al., 2013 and Wagner et al., 2014) and (2) vertical alignment by aligning the strategic business plan with the operational business plans to create consensus among them (e.g. Oliva and Watson. 2011; Feng et al., 2013 and Wagner et al., 2014). In achieving these purposes, S&OP typically takes two perspectives: (1) the organizational perspective, focussing on the people involved in S&OP and the intra-and intercompany coordination in the supply chain, and (2) the process-perspective, focussing on “formal and standardized processes for conducting S&OP” (Tuomikangas and Kaipia, 2014, p. 255). Within this research, we maintain the process-perspective, which allows us to consider the S&OP process as a whole entity, rather than sets of non-related entities as done by Ivert et al. (2014) and Ivert et al. (2015). S&OP consists out of the general elements of a process (inputs, activities and outcomes (Thomé et al., 2012)), which are influenced by setup-parameters in the sense that these set the scope and basic principles for the process. Table 1 & 2 provide a summary of literature indicating the different parameters used by academia conducting their study within the S&OP context. Since many different authors use the parameters, we can infer that literature agrees that they constitute the S&OP process. Therefore, the remainder of this section further explains the setup- and the process-parameters.

Setup-Parameters

(e.g. Lapide, 2005; Grimson and Pyke, 2007; Ivert et al. 2015)

Definition

(Grimson and Pyke, 2007;

Wallace & Stahl, 2008)

1. S&OP Planning object refers to the level of detail with which the S&OP is executed (SKU- or product-group level)

2. S&OP Planning frequency refers to the frequency with which the S&OP activities are arranged (granularity is monthly)

3. S&OP Planning horizon refers to the time horizon the process spans (typically: 3-18 months)

Table 1 & 2: S&OP setup and process-parameters

Process-Parameters

(e.g. Thomé et al. 2012; Ivert et al. 2014)

Definition

(Wallace & Stahl, 2008; Ivert et al. 2014)

1. S&OP Inputs refers to the separated plans of the different departments, constraints (e.g. production capacity) and goals (e.g. reducing inventory levels)

2. S&OP Activities consist out of 5 steps: (1) forecast generation, (2) demand planning (3) supply planning (4) reconciling both plans (5) presenting and settling the final plans

(6)

6 Process Parameters refer to the inputs, activities and outcomes of S&OP. Due to S&OP’s cross-functional nature, individual plans of departments and facilities need to be aligned in order to achieve S&OP’s goals of horizontal and vertical alignment (Thomé et al., 2012; Feng et al., 2013 and Wagner et al., 2014). The individual plans, along with the departmental constraints and goals serve as inputs for the S&OP process. Once all inputs are collected, the activities can be executed. The first activity is the forecast generation and finally the aligned plan is presented to and settled by the executive board (Ivert et al. 2014) (see Table 1 & 2). This final plan serves as the outcome of the process. Olhager et al. (2001) argue that decision-making within the S&OP activities is typically targeted towards modifying demand to match the supply, or modifying supply to match demand.

Setup Parameters set the scope and basic principles for constructing the S&OP processes (Grimson and Pyke, 2007; Jonsson and Mattson, 2009). Grimson and Pyke (2007) made a commonly used separation, arguing that the setup consists of the planning object, planning horizon and planning frequency (see Table 1). There is some discussion in extant literature regarding the planning object. Where Oliva and Watson (2011) and Noroozi (2014) suggest that the planning object should solely focus on product-groups, Thomé et al. (2012) suggest that the planning object can be either on Stock-Keeping-Unit (SKU) level (providing a sufficient level of detail in decision-making) or on product-groups. Ivert et al., (2015) even mentions a third option, in which the planning object varies among the different S&OP activities. This implies that each S&OP activity (see Table 1) focuses on different planning objects (e.g. demand planning focuses on product-groups, but supply planning focuses on SKUs). Changing the planning object among the different activities is considered highly ineffective because it is time-consuming (Barbosa-Póvoa, 2014). At the same time, this is opposing to the idea of standardization, which S&OP is meant to bring about. In terms of planning frequency, standardization leads to a monthly cycle in which the five S&OP-activities (see Table 1) are conducted (e.g. Wallace & Stahl, 2008; Ivert et al., 2014 and Ivert et al., 2015). Rather than a monthly standardized pace, Grimson and Pyke (2007) argue, however, that the most mature-form of conducting S&OP is arranging activities driven by emerging events (e.g. material shortages of a critical component or a natural disaster), rather than having a fixed set of activities each time interval. The planning horizon varies between three months and three years (Grimson and Pyke, 2007). However, most literature emphasizes on a planning horizon of 6-18 months due to marketing cycles and seasonality profiles of most organizations (e.g. Schorr, 2007; Noroozi & Wikner, 2014 and Ivert et al., 2015).

(7)

7

2.2. Foreseeable and unforeseeable risks

Risks are commonly defined as the relationship between potential negative outcomes of an event (based on severity and impact) and the distribution of the related probabilities for each of these potential negative outcomes (Rao and Goldsby, 2009; Aqlan and Lam, 2015). Supply chain risks stem from different sources (see e.g. Jüttner et al., 2003; Christopher and Peck, 2004 and Tang and Tomilin, 2008). However, Norrman and Jansson (2004) argue that the sources of supply chain risk do not determine the approach to cope with the risk. This approach depends on the disruptive nature of the risk. Therefore, risk identification is fundamental as it creates awareness for decision-makers of potential risks causing disturbances. Shao (2013) and Payne (2015) distinguish between foreseeable risks (preventive maintenance resulting in capacity shortages or entrance to a new market which results in a significant increase in demand) and unforeseeable risks (natural disasters or supplier bankruptcy). Where organizations have the ability to come up with countermeasures to cope proactively with foreseeable supply chain risks (Norrman and Jansson, 2004), unforeseeable risks require a reactive, ad-hoc approach (Shao, 2013 and Ivert et al., 2014).

The separation of foreseeable and unforeseeable supply chain risks is important in setting the scope for this research. Due to S&OP’s intended focus on the tactical horizon (Thomé et al., 2012), unforeseeable risks materializing on the operational horizon are excluded purposefully from the planning process. The standardized monthly granularity of the process does not allow making immediate decisions, which is required in a crisis-situation (Grimson & Pyke, 2007). Ivert et al. (2015) even argue that unforeseeable risks require an ad-hoc approach, rather than the standardized structure of the S&OP process. Therefore, unforeseeable risks are consciously excluded from this study, where the focus will thus be on foreseeable supply chain risks.

2.3. S&OP and foreseeable risks

Given the intertwined nature of the setup-parameters and S&OP activities (see Table 1 & 2) (Thomé et al., 2012), it can be assumed that both affect how organizations can cope with foreseeable supply chain risks. Yet, to date the limited amount of studies concerning supply chain risks in relation to S&OP only considered unforeseeable supply chain risks, which require a fundamental different approach than foreseeable supply chain risks. In addition, these researchers considered S&OP setup parameters and S&OP activities as two distinct set of parameters, which results in a fragmented view of reality. Maintaining the process-perspective allows us to consider S&OP as a whole consisting of setup parameters and S&OP activities. We will consider how both are able to cope with foreseeable supply chain risks. Foreseeable risks allow the organization to determine countermeasures, implying that the organization still has the ability to anticipate on the risk and thereby mitigate its impact (Payne, 2015). This resulted in the conceptual model depicted in Figure 1.

(8)

8

3. Methodology

In exploring the S&OP process and its ability to cope with foreseeable supply chain risks, we apply a multiple-case study approach for a variety of reasons. First, case research is considered to be explicitly suitable for exploratory purposes, aiming to understand the phenomenon (the S&OP process) which is difficult to quantify, not well understood and needs to be investigated in-depth within its natural setting (Yin, 1994). In addition, the scarcity of literature concerning S&OP processes, and how to cope with foreseeable supply chain risks makes a case study approach particularly suitable for this research. Third, Yin (1989) and McLachlin (1997), argue that the choice of the research method depends on three conditions: (1) the form of the research question, (2) whether or not control is required over behavioural events and (3) whether or not the research focuses on contemporary events. Due to the explorative nature of this study, the researcher has no control over behavioural events, the focus is on a contemporary event (monthly S&OP process) and the research question is a “how”-question. Hence, case study is most appropriate for this research. Lastly, by employing a case study methodology we follow the recommendations of Thomé et al. (2012) and Tuomikangas, and Kaipia (2014), who are stressing the need for case studies describing the S&OP process in-depth. The advantage of case research is its ability to obtain “rich-data”, most likely reflecting organizational contingencies such as supply chain risks and how these are coped with by S&OP. The S&OP process is the unit of analysis of this research. The process has a clear start (when the forecasts of demand and supply are generated) and end (when the executive board settles the aligned and integrated developed plan) as determined by the S&OP activities in the context of the S&OP setup-parameters (see Table 1 & 2 and Figure 1) (Tuomikangas and Kaipia, 2014 and Ivert et al., 2015).

3.1. Research Context

The research context is the process industry. The process industry is characterized by its inflexibility and continuous nature of the production processes (Gaglioppa et al. 2008, Noroozi, and Wikner, 2014). Noroozi (2014) argues that S&OP has mainly been considered in discrete-production environments (automobile and computer-industries), which are characterized by its flexibility and discontinuous nature of the production processes (Noorozi and Wikner, 2014), and are therefore fundamentally different from process industries. The characteristics of the process industry imply that risks will have a severe impact on the production processes. Additionally, supply chains of process industries are considered as physical-efficient based on the terminology of Fisher et al. (1997). An implication of such a physical-efficient supply chain is its relatively low level of inventory, which makes them vulnerable to many risks (Barbosa-Póvoa’s, 2014). Proper risks management is therefore important within the process industry, since supply chain risks might have a severe impact on the continuity of the production processes. In addition, Noroozi (2014, p.12) indicates that: “earlier studies about S&OP in process industries are to a large extent quantitative, limited to a specific type of industry (e.g. chemicals, food) and even case-specific. Thus, the lack of conceptual models and theories applicable to all process industries is evident”.

(9)

9

3.2. Case Selection

All cases represent a specific S&OP process of a company within the process industry, which is the unit of analysis under scrutiny. Table 3 shows the descriptions of the seven cases that were investigated along with the setup-parameters. Theoretical replication logic was used by selecting cases based on the different setup-parameters. Due to the differences in setups, we expect that the way in which the S&OP processes cope with foreseeable supply chain risks differ among the cases. For instance, the planning horizon of Case D and Case F starts from month 0, implying that they also consider the operational horizon within their process, where the other organizations intentionally maintain a tactical (and strategic) focus starting to plan from month 3.

Furthermore, we selected cases producing fundamentally different products (see Table 3). The products produced vary from consumer products (with or without perishability) to industrial products. All cases are relatively big organizations with more than 1350 employees. The cases are classified to industry-groups to ensure anonymity of the participated organizations. Selecting cases producing different types of products improves the external validity of this research such that the results are generalizable beyond a specific product-industry.

Cases Industry Planning object Planning frequency / granularity

Planning horizon

Case A Non-perishable consumer products

SKU-level Monthly 3-36 months

Case B Perishable consumer products

Product-group Monthly 3-18 months

Case C Perishable consumer products

Case D Industrial Products Entire business setup Monthly 0-18 months Case E Industrial Products Product-group Monthly 3-36 months

Case F Perishable consumer products

SKU-level Monthly 0-24 months Case G Perishable consumer

products

Table 3: Case descriptions & Setup of the S&OP processes

3.3. Data collection

(10)

10 which improves the reliability of the obtained information, and thereby the inferences of the research (Yin, 1994). After conducting the interviews, some follow-up questions via mail were sufficed concerning interview data that was unclear. All interviewees were asked to send an S&OP-slide deck in advance, such that we knew what to expect during the interviews and to prepare in-depth questions regarding the documentation obtained. Having this S&OP documentation along the qualitative interview data enables data triangulation (Denzin, 1978 and Yin, 2009). Table 4 provides an overview of the obtained data sources and further information regarding the interviews.

The interview-protocol was developed with a second researcher under guidance of supervisors. Due to the explorative nature of the research, questions were partly based on existing literature regarding S&OP and supply chain risks of Sodhi and Tang (2010), Ivert et al., (2014) and Ivert et al., (2015). To ensure the quality of the interview-protocol, the initial guide was pre-tested to make sure that the information obtained from the interviews was sufficient to answer the main question of the study. The interview-protocol evolved during the data collection and analysis to address specific topics, which were found relevant in answering the study’s research question. The entire interview protocol is included in Appendix 1.

Cases Job titles Length of the interviews

Data sources

Case A Interviewee A1: Production Director

Interviewee A2: Factory Scheduling Manager

1. 99 minutes 2. 86 minutes

2 interviews, S&OP slide deck

Case B Interviewee B1: Supply Chain Director Interviewee B2: Enterprise S&OP Manager

2 interviews, S&OP slide deck and scenario presentations

Case Interviewee C1: Category Supply Manager Interviewee C2: IBP Manager

2 interviews, Scenario format

Case D Interviewee D1: Manager Supply Planning NL Interviewee D2: Manager Supply Planning UK

2 interviews, S&OP deck and scenario presentations

Case E Interviewee E1: S&OP Planner Europe Interviewee E2: Head of Strip S&OP

2 interviews, S&OP meeting structure

documentation, S&OP slide deck, S&OP movie

Case F Interviewee F1: S&OP Planner Interviewee F2: S&OP Planner

2 interviews, S&OP slide deck, scenario presentations

Case G Interviewee G1: S&OP Planner

Interviewee G2: Supply Planning Manager

2 interviews, S&OP slide deck, scenario presentations

Table 4: Data collection details

3.4. Data Analysis

(11)

11 planning horizon or planning object, or to the S&OP activities, like: forecast generation or demand planning. This also allowed for the identification of potential setup-parameters, which were not considered in extant S&OP literature (for instance: planning levels). Subsequently, the interpretive third-order codes could be derived from the earlier coding-steps: e.g. high concreteness of countermeasures / low concreteness of countermeasures or high involvement among the activities / low involvement among the activities. The third-order codes allowed us to draw inferences regarding the text-fragments. Where possible, the text fragments were allocated towards a specific setup-parameter, which allowed for a structural comparison of these setup-parameters among the cases. Each coding step involved, enabled to move gradually towards a more abstract level. The coding procedure is depicted in Figure 2 and an excerpt of the code-tree is given in Appendix 2.

In ensuring reliability and validity throughout the data collection and data analysis, different quality safeguarding measures were taken to account following (Yin, 2009). The measures applied are depicted in Table 5.

Reliability and validity Quality safeguarding measures

Reliability  An interview protocol was developed and used in

order to standardize the interviews conducted

 A case study database was developed in Excel

 Interviews were transcribed accurately

 2 interviewees per case

External validity  Cases were selected within the overarching process-industry, but the products produced by each case varied significantly

 Existing theory formed the basis of the concepts under scrutiny

Construct validity  Triangulation by using multiple researchers and data sources

 Appliance of semi-structured interviewing techniques

 Pilot-testing of the initial interview-protocol

 Interviewees reviewed the transcriptions (follow-up contacts if required) Interview Data Data reduction (first-order-codes) _Descriptive codes (second-order-codes) Interpretive codes (third-order-codes) Setup-parameters

(12)

12

4. Findings

Following, we present our findings along the setup-parameters: planning object, planning frequency and planning horizon. Additionally to the ones known from literature (see Table 1), we also discovered a fourth setup-parameter: planning level. This additional parameter influences the way in which S&OP copes with foreseeable supply chain risks. Overall, we found that in coping with supply chain risks during the S&OP process, scenario-management techniques are applied. In particular, we discovered that cross-activity involvement, high IT-supportiveness, accurate forecasting and structural evaluations improve S&OP’s ability to cope with foreseeable supply chain risks. These mechanisms apply to all parameters and activities and therefore discussed in the final part of this section. For guiding purposes, Table 6 depicts the S&OP activities constituting the S&OP processes of the cases.

4.1. S&OP Planning Object

We found that the planning object influences risks in the sense that the more detailed the planning object is, the higher the level of concreteness in the countermeasures to cope with the foreseeable risks will be.

Planning on SKU-level allows for a great level of detail in executing the S&OP activities: “We do not want to know how much we are growing on an aggregated level; we want to know whether we grow with tins or packs. […] that information is essential”. (Case A2). Where Case A has consciously chosen for planning on SKU-level, Case F is forced to plan on such a detailed level due to the high variations in the product-turnover. The concreteness of the countermeasures to mitigate the impact of the foreseeable risk is positively influenced by the planning object maintained: “[…] when it becomes clear that a certain product is not available, it will be discussed thoroughly, and countermeasures will be generated in a high level of detail. The members of the pre-S&OP know all the details” (Case F1). Due to the high level of detail maintained when conducting S&OP on SKU level, the level of data-visibility will also be improved. This in turn allows tracing and validating the obtained data easily: “For instance, Spain always sells 4,000 kilo of product X, and now they forecasted 10,000 kilo. Then I personally called the person responsible for the forecast in Spain, and asked him what was going on, thus really challenging the end-markets. […] They could then respond whether it was a mistake, or that a promotion was launched for that specific product, […]” (Case A2).

Cases planning on a lower level of detail face difficulties in determining concrete countermeasures: “We focus on product-group level, […] in our countermeasures we try to be as concrete as possible,

Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6

Case A Forecast generation

- Demand planning Supply planning Pre-S&OP Global S&OP

Case B Forecast generation

- Demand planning Supply planning Pre-S&OP Enterprise S&OP Case C Forecast generation - Category demand-planning Category supply-planning - Executive-supply review Case D Forecast generation - S&OP-declaration External sales-review - S&OP Case E Forecast generation

- Demand planning Supply planning Reconciliation Planning Group meeting

Case F Forecast generation

- Pre-S&OP S&OP Master S&OP

(13)

13 but that is often difficult” (Case C1). Logically, this would imply that all organizations should just shift their focus from the aggregated planning object towards the more detailed SKU-level. However, there are factors influencing whether or not an organization is able to plan on SKU-level: “In total we have more than 20,000 SKUs, thus within S&OP we do not plan on SKU-level, not in this system. That would make everything way too complex” (Case E2). Additionally, the product variety of the organization influences the choice whether or not to plan on the SKUs, as indicated by Case G.

While planning on SKUs brings about advantages in the forecasting, demand planning and supply planning stage (see Table 6), it also requires a shift from SKU-level towards a more aggregated level. This shift is required since the level of detail becomes too high in the finalizing activities of the S&OP process: “The crucial conversations are discussed within the Master-S&OP, which is on executive level. Product names are rarely mentioned within those meetings, thus a high level of aggregation” (Case F1). However, it seems that this shift is not inherently problematic because the initial focus of the activities in which the risks are identified (risks in demand, risks in supply and risks in balancing both) are performed on SKU-level. This is turn allows for obtaining early indications when things shift towards a potential negative outcome. Thus, planning on SKU-level positively affects obtaining early indications of a potential risk.

Opposing to the high level of detail maintained when planning on SKU-level is planning on an aggregated level. Aggregation is considered disadvantageous for the level of detail on which risks can be identified: “Decentral S&OP focuses on smaller risks, which are incorporated into the plan. […]. For us as central S&OP, it does not really matter whether one region does a bit more than another region. Basically we have a risk-pooling effect in the aggregation between decentral and central, where small risks will compensate among the different regions” (Case B2). Early indications regarding a potential risk might therefore not be noticed: “The indications we have received were too late. What you want is determining the right moment to switch, when you see the current performance is shifting and requires intervention” (Case E2). Hence, planning on an aggregated product-group level does not allow identifying risks in a great level of detail due to risk-pooling effects within the aggregation process.

(14)

14

4.2. S&OP Planning frequency

The monthly process facilitates a highly standardized schedule to ensure attendance of the S&OP representatives during the S&OP activities. Ensuring a high level of attendance enables awareness of risks and familiarity of the countermeasures agreed upon among the S&OP members.

An enabler and prerequisite of ensuring attendance of the S&OP members and awareness of risks among them is maintaining a fixed, predetermined activity-schedule: “We have a monthly pace for our S&OP process, which is the same for all our factories. We even have a fixed S&OP-calendar for all levels on which S&OP is conducted, […].” (Case A1). Case A has fixed S&OP schedules, which are executed standardly every month at prescribed and predetermined dates (e.g. forecast generation is done at the final working day of the month). This ensures attendance, and familiarity with the S&OP activities among the participators of the process. Case E also has a fixed S&OP-calendar; however, the attendance at the activities varies significantly resulting in the fact that certain representatives or departments are unaware of the risks at play within the organization and the status of the countermeasures agreed upon: “Our calendar is designed in such a way that all activities are taking place at a fixed working-day. […] For instance conducting a meeting every fourth working day of the month. […] the disadvantage of this is that for example the reconciliation-meeting, takes place in April on a Monday, in May on a Tuesday, sometimes on a Thursday. Thus, the day on which the activity is executed shifts every month. What we currently experience is that the attendance varies, since most managers have fixed schedules: every third Monday of the month this meeting, etc. (Case E2). This shows that while the frequency is standardized (monthly), there are still variations in how the S&OP activities can be executed which in turn influences the way S&OP can cope with supply chain risks as not everybody can attend. Therefore, Case A and D stress the need to arrange meetings at fixed time intervals. However, as indicated by Case D: absence is sometimes inevitable. Therefore, they highlight the importance to have a list of alternative, well-informed deputies: “In our occupation we have in every function back-up. A factory can also have a shutdown when I am on holidays, […]. Therefore, everybody should have well-informed deputies, who have the same decision power as the ones they replace” (Case D2). The alternative deputy-list ensures awareness of the risks and familiarity of the status of the countermeasures among all departments participating in S&OP.

4.3. S&OP Planning horizon

We found that the planning horizon of the cases ranges from operational to strategic. Focussing on the operational horizon appears to influence and facilitate the ability to supplement the standardized S&OP activities with risk-driven activities. In coping with the risks identified on all horizons, scenario management is commonly applied within the process of S&OP.

(15)

15 provides them a sufficient amount of time to determine countermeasures to mitigate the identified risk’s impact. Both cases have different enablers for maintaining such a broad horizon. Where the stability in the demand enables such a broad horizon for Case A, Case E is somewhat forced to maintain the horizon due to the long lead times typically characterizing the industry they are in. Remarkably is that both organizations currently face issues in maintaining the predetermined horizon: “Currently we are mainly focussing on the short-term, operational horizon” (Case A1) and “The focus is too much on the operational horizon, implying that we consider incidents as incidents over and over again” (Case E2). The explanation of this operational focus seems to lay in the fact that both organizations are currently dealing with a big reorganization, implying that the priorities shift away to other processes. This means that they perceive not being able to fulfil S&OP’s initial aims to maintain a tactical focus. However, where these cases consider the focus on the operational horizons as negative and opposing to S&OP’s aims, Case D and F consciously include the operational horizon within their S&OP process.

Considering the operational horizon along with tactical horizon implies that risks occurring on the short-term are also incorporated in the process. Interestingly is that both cases launch extra S&OP activities once a risk has been identified on the short-term horizon, requiring immediate decision-making and countermeasures. This provides them the flexibility that required when impending risks occur, where the other cases seem to wait until a risk occurs and subsequently react and exclaim a crisis-situation: “[…], we do not solve anything within our S&OP process. When impending risks occur, you just put people together in a room, and they need to make immediate decisions, […]. That is really a crisis-situation, which are solved by crisis-teams” (Case F2). Even though the risks occur on a short-notice, Case D and F try to proactively cope with them by launching such additional activities, which are therefore considered as risk-driven and “pre-standardized” in the sense that the representatives of the activity are already predetermined. However, the content of the activities is concentrated towards the specific risk faced. The activities are called: Exceptional S&OP (Case D) and Intermediate S&OP (Case F). As the name already suggest, S&OP is in the lead in launching these activities: “(…Referring to a super-tanker which might be unable to moor due to bad weather predictions...). We already felt that this could happen, and thus we launched an exceptional S&OP-meeting. Such activities are launched for risks with a significant impact which require decisions-making immediately […]” (Case D1). This risk could have implied that the factories of Case D were unable to produce due to the lack of raw materials, which would have significant financial implications due to the continuity of their production processes. Case F launches an activity labelled as Intermediate S&OP: “(…Referring to potential problems with the harvest...) We could not wait until the next S&OP cycle; therefore the Supply Chain Director launched an intermediate S&OP-meeting. All stakeholders (mostly on managerial-level) were invited to discuss the risk. […]. Everyone is expected to free-up its agenda and attend” (Case F2). The additional activities back-up and supplement the standard S&OP activities when the impact of the risk is significant. Launching and performing the additional activities within S&OP is enabled by the organization’s planning horizon.

(16)

16 Scenario management is performed in the finalizing activities of S&OP, after the consolidation of the demand and supply plans. The gaps resulting from aligning demand and supply are structurally worked-out in alternative ways: scenarios. “We generated several scenarios whether or not we should invest in an additional production line. As you can see here, in order to comply with the increasing demand, we required extra capacity” (Case A2). The scenarios are generated before and presented during the pre-S&OP (or reconciliation activity) (see Table 6): “Based on the consolidated demand and supply, we generated several scenarios. The first scenario is; what if we shut down these three lines? What does that imply? […]. The fifth scenario is what if we utilize this factory completely. […]. That are the different scenarios we have taken into consideration during the reconciliation meeting.” (Case E2). By presenting the most-likely scenarios, awareness of the risk’s impact among the S&OP members is created, additionally, it also enables the determination of alternative plans which can be formally approved in the final S&OP, such that the entire organization knows what to do when the risk materializes (e.g. when A happens, we shift to plan B, when B happens we shift to plan C).

Interestingly is that the focus of the scenarios and constraints discussed during the interviews varies significantly. The cases can be allocated to three different groups, as depicted in Table 7. The differences in focus can be devoted to the organizational and industry characteristics. Case B and F are corporations, implying that they have push-material supply, hence focussing on supply-scenarios. Case D and E are in the industrial product-industry, which is characterized by its capital-intensiveness: “A typical characteristic of our industry, and therefore also the focus of the S&OP process is the 100% utilization of the production-lines” (Case E2), hence capacity-availability scenarios. The remaining cases’ focus is on complying to the demand, since they are producing consumer-products, hence demand-related scenarios. From this difference, we can infer that even though the cases are in the process industry, there is a difference in focus, which seems to be a result of the different organizational and industry characteristics. Remarkable is that only two cases (Case D and Case G) adjusted its S&OP activities, by specifically targeting the process towards the risks they deem as most-important (see Table 6). Case D first determines the capacity-availability in the S&OP-declaration meeting for the upcoming 18 months, and then focuses on the demand, which underlines the focus on capacity (see Table 6). Case G starts its S&OP process with a portfolio-management review in which all individual products’ sales are evaluated and the promotions in all its markets are aligned. This S&OP activity underlines the acknowledgements of the importance of the customer’s needs and the demand-driven orientation of the process.

Focus of the process and scenarios

Cases Foreseeable risks discussed during the interviews

Explanation

Supply issues, coping with the material supply

Case B A significant increase in the supply of raw materials, due to European law creation

The organization faces a significant increase in the supply due to changes in the European Laws. Due to the push material supply, the organization is forced to cope with it

Case F Harvest expectations because the production-campaign was postponed by one week last year due to bad weather conditions

The weather conditions of last year resulted in the problem that the production-campaign was postponed by one week. Due to the organization’s seasonality profile and push-material supply, production was not possible that week

Capacity issues, making sure that the capacity is 100% utilized

Case D Constraints regarding preventive maintenance of a storage tank

Focus on utilizing all capacity on 100%. Also the continuity of the process requires preventive maintenance to planned accurately

Case E Due to the closing of a facility, reallocating production

Utilizing all capacity on 100% due to the high capital-intensiveness typically characterizing their industry

Demand issues, ensuring that supply can always comply to the demand

Case A A significant reduction in demand due to European law creation

Due to new European laws, packaging adjustments are required which results in lower demand levels

Case C Potential new market Arranging extra capacity to comply with demand

Case G Potential new customer Arranging extra capacity to comply to the demand

(17)

17

4.4. S&OP Planning level

Various cases indicated that their S&OP process is conducted on different levels, where each level has a different orientation. The orientation also influences the risks identified and coped with by the S&OP process. The S&OP planning levels of the cases are depicted in Table 8.

Case Planning level of the sample cases

Other levels on which S&OP is performed

Case A Central Decentral

Case B Central Decentral

Case C Central Decentral

Case D Central -

Case E Central -

Case F Central -

Case G Decentral Central

Table 8: S&OP’s planning orientation

The S&OP processes on the various levels are conducted in parallel, where the output of the decentral-process serves as the input for the central decentral-process. An advantage of performing S&OP on a decentral level is the ability to identify risks specifically targeted towards the market or factory: “We have a central and decentral process, […]. The decentral process indicates the risks and opportunities of their specific market (demand) or their specific factory (supply). They exactly know what is going on there” (Case C2). The decentral planners are regarded to be the specialists of their specific markets and factories in the sense that they know what the trends will be in demand, and what the potential issues are in the capacity-availability. This also creates awareness at the central S&OP, regarding risks faced by the decentral S&OP: “It might be the case that there are many small risks identified by the decentral S&OP, which implies that we as central S&OP need to plan more carefully” (Case C2). The impact of the risks discussed in both levels seems to differ, where the decentral-process is mainly discussing and coping with relatively ‘small’ risks, the central process is targeted towards ‘big’ risks: “At the decentral processes they will discuss smaller risks than we do. Thus, small deviations in demand or supply are discussed in the decentral process. For instance, if one business-unit does less, and another does more, they will compensate one another, and will therefore not return in our central process” (Case B2). This seems to be confirmed by the only case of the research’s sample, conducting S&OP on a decentral level: “Our decentral-process is filtering the crucial conversations which need to be discussed on a higher level at the central S&OP-cycle” (Case G2). Even though Case D does not have a decentral-S&OP process, the factory managers generate the supply plans for the same reasons as conducting a decentral process: utilizing decentral specialism.

(18)

18

4.5. Cross-activity involvement, IT-supportiveness, forecasting & evaluation

Cross-activity involvement, IT-supportiveness, accurate forecasting and structural evaluation are underlying mechanisms that improve S&OP’s ability to cope with supply chain risks.

Cross-activity involvement

Cross-activity involvement facilitates awareness among participants of the issues and risks at play in the other activities: “I consider myself (Category-Supply planner) as a customer of the demand-meetings, such that I know the issues and risks at different markets” (Case C1). This information can be taken into account when the supply plan is determined. Additionally, this involvement of a supply planner in the demand meeting allows for clarification of supply issues already during the demand-planning activity, which results in more accurate decision-making. The focus of this research was on supply planners, implying that the cross-activity involvement refers to supply planners involved in the demand-planning activity. The cross-activity involvement of all cases is depicted in Figure 3.

Figure 3: Mechanism 1. Involvement of supply planners in demand planning

Case A and C have a high involvement of the supply-planning delegation in the demand-planning activity: “We always participate in the demand planning for informational purposes; we obtain information regarding the backgrounds, market-developments, risks and opportunities. As said, the purpose is purely obtaining information which can be used and taken into account when determining the supply-plan” (Case C2). The opposite is Case F, which maintains S&OP’s strict role division: “Sales has its own meetings, […]. What they discuss there…? I have no idea, but we should obtain the output of those meetings” (Case F1). The lack of cross-activity involvement seems to be one of the main causes of a big risk the organization has faced recently: “With Christmas, our supplier faced a flood, implying that they were unable to supply. Consequently, we were unable to supply our biggest Customer X, […]. It turned out that just at that moment, Customer X wanted more products, which was not indicated by the demand-planners. I have some doubts about how this could all happen, […]. What did sales promise to Customer X without asking us to confirm whether we were able to facilitate that increase?” (Case F2). Previous example highlights the importance of cross-activity involvement, which facilitates awareness of risks and issues at play at other S&OP activities.

IT-supportiveness

In coping with foreseeable risks in S&OP, constraint analysis and scenario management techniques are considered fundamentally important. The quality with which these two practices can be performed is affected by the perceived IT-supportiveness. The perceived supportiveness is depicted in Figure 4. The perceived supportiveness of the IT-tooling in place mainly stems from loading time to generate multiple what-if scenarios: “We cannot say, lets calculate this scenario quickly, since the loading-time takes 6 hours…” (Case G1). Because of this lengthy process, it is hard to calculate and present different scenarios within the S&OP activities: “[…] it would have been nice that we can just present different scenarios to the executive board. This is scenario A, this is scenario B, and these are the

1 2 3Case A Case B Case C Case D Case E Case F Case G

Mechanism 1: Cross-activity involvement

Cross-activity involvement

(19)

19 opportunities and risks: pick one. Thereby, having software enabling and supporting us in doing so” (Case F2). Thus, determining alternative what-ifs is hardly possible due to the time it takes to run different scenarios. The supportiveness of the IT-systems at Case D and E are perceived to be high (see figure 4): “Run times of a couple of hours are highly ineffective. […]. We are all human beings, and if one person mistakenly includes the wrong figures into the system, it would cost you 4 hours. Therefore, we invested significantly in our IT-tooling, and now the run-time of the scenarios is about 30 minutes” (Case E2). Quick loading-times enable the organization to generate multiple scenarios, which can be proposed to the executive board during the final S&OP meeting. In addition, this positively influences the speed of decision-making on executive level regarding alternative plans and countermeasures.

Accurate Forecasting

Accurate forecasting is another factor improving S&OP’s ability to cope with foreseeable supply chain risks, since forecasting has a direct effect on the process’s ability to foresee supply chain risks and subsequently develop scenarios and countermeasures in an early stage. Since this is the first activity in the S&OP process (see Table 6), it is fundamentally important that the output is realistic. The perceived quality of both demand and supply forecasts is depicted in Figure 5, where none of the organizations is completely satisfied with the generated forecasts. In improving the quality of the forecasts, and thereby S&OP’s ability to identify risks within the predetermined horizon, forecast-validations are considered important: “It is fundamentally important that the generated forecasts are validated thoroughly, […]. As they usually indicate, rubbish-in is rubbish-out” (Case E2). However, as another interviewee puts it: “It is not done very often anymore, often not at all, demand validation” (Case A1). Lacking validation steps in the process results in difficulties of maintaining the tactical focus S&OP should intentionally bring about: “You would expect that S&OP is all about the tactical horizon, however, at the moment we are mainly focusing on the operational horizon...” (Case A1). Another factor influencing the quality of the forecast is individual target setting: “Sales-managers indicate to sell 3 thousand tons of products X, and it turns out to be only thousand tons. He probably wants to achieve its individual targets, […]” (Case D2). Thus, incentive alignment is also important in improving the accurateness of the generated forecasts.

1 2 3 4 5Case A Case B Case C Case D Case E Case F Case G

Mechanism 2: Perceived supportiveness of IT-tooling

Perceived supportiveness of IT-tooling

1 = very low perceived IT-supportiveness 2 = low perceived IT-supportiveness 3 = medium perceived IT-supportiveness 4 = high perceived IT-supportiveness 5 = very high perceived IT-supportiveness

Figure 4: Mechanism 2. Perceived IT-supportiveness

1 2 3 4 5 Case A Case B Case C Case D Case E Case F Case G

Mechanism 3: Perceived forecast accurateness

Perceived demand forecast accurateness Perceived supply forecast accurateness

1 = very low perceived quality of the forecasts 2 = low perceived quality of the forecasts 3 = medium perceived quality of the forecasts 4 = high perceived quality of the forecasts 5 = very high perceived quality of the forecasts

(20)

20

Structural evaluation

Where S&OP is constantly fixated on the future, the ability to cope with foreseeable supply chain risks improves when there is an evaluation mechanism at place. The general tendency is that once a plan has been settled in the final S&OP, a new planning-cycle emerges in which everybody shifts their focus one month further in the future. However, evaluating decisions and countermeasures determined in previous S&OP processes, enables learning in being better able to anticipate on future risks: “We are much more evaluating the decisions made in previous S&OP cycles. […]. Closing-the-loop, and learn from earlier decisions. That is something which has definitely been put on the agenda, which enables us to learn from the past, and apply that knowledge to better anticipate on risks in the future” (Case D1). Case D is the only organization always reconsidering the decisions made and countermeasures taken in previous S&OP cycles (see Figure 6) on which a plenary discussion takes place in the final S&OP (see Table 6). They devoted half of the final S&OP meeting on ‘closing-the-loop’. The other cases incidentally reconsidered the decisions made: “We are too much focussed on the future and too less on evaluating previous decisions and using that knowledge to deal with new risks” (Case B1) or “Actually… no we do not evaluate […]. We do not evaluate the scenarios, and check whether the decisions were appropriate. But it could be interesting I think...” (Case C2). Thus, even though the benefits of evaluating seems to be acknowledged, six of the seven organizations still did not find a way to conduct this evaluation in a structural manner.

Figure 6: Mechanism 4. Structural evaluation

5. Discussion

This study investigated whether and how the S&OP process can cope with foreseeable supply chain risks. By maintaining the process perspective proposed by Tuomikangas and Kaipia (2014), we were able to consider S&OP as a whole. It turns out that the S&OP setup-parameters and S&OP activities influence the way in which the process copes with foreseeable supply chain risks. While this relationship is partly known from literature (Sodhi and Tang, 2012, Ivert et al., 2014 and Ivert et al., 2015), we found a new setup-parameter that was not considered beforehand which also influences S&OP’s ability to cope with foreseeable risks. Thereby, we extend earlier studies of e.g. Wallace and Stahl (2002), Grimson and Pyke (2007), Ivert et al. (2014) and Ivert et al, (2015). Our study contributes valuable empirical insights to the S&OP process and the way it can cope with foreseeable supply chain risks. Organizations adjusting the standardized S&OP design (in terms of planning object, frequency, horizon and levels) (e.g. Wallace and Stahl, 2002; Lapide, 2005 and Grimson and Pyke, 2007) towards their specific organizational characteristics, improve their abilities to cope with foreseeable supply chain risks.

1 2 3 4Case A Case B Case C Case D Case E Case F Case G

Mechanism 4: Structural evaluation

Structurally evaluate decisions and countermeasures agreed upon in earlier S&OP processes

1 = never

2 = sometimes, incidentally 3 = structurally

(21)

21

5.1. S&OP Planning object

Cases maintaining a detailed planning object were able to determine countermeasures with a high level of concreteness, such that everybody knew which affirmative actions were required to be executed and what each individual’s specific role was to mitigate the risk’s impact. Additionally, the visibility of the demand and supply data is also positively influenced by maintaining a detailed planning object. This allows for accurate forecast validations. The countermeasures and accurate validations referred to are determined in the first three activities of the process, since a shift in planning object is required once continuing to the pre-S&OP and final S&OP activities (see Table 6). Where Barbosa-Póvoa (2014) considers this shift as ineffective and time-consuming, the results of this research suggest that in terms of coping with foreseeable supply chain risks this shift is effective. Performing the initial three S&OP activities on SKU-level enables a high level of specificity in the identification of potential supply chain risks and setting-out concrete countermeasures. Aggregating this in the last two activities and indicating the potential risks found earlier, ensures awareness of the risks throughout the entire S&OP process. Therefore, we propose that:

P1a. The more detailed the planning object is in the forecast generation, demand planning and supply

planning, the more concrete the countermeasures will be, which in turn positively influences the management of foreseeable risks

Organizations maintaining a high level of aggregation face difficulties in setting-out concrete countermeasures to mitigate the risk’s impact. However, some cases indicated that aggregation to product-families was inevitable. This need stems from the number of SKUs and the product variety, thereby confirming earlier findings of Olhager and Rudberg (2002) and Ivert et al. (2015). The specificity with which risks are identified is reduced when aggregation takes place, since effects of risk pooling will emerge. Kerr and Tindale (2010) argue that aggregation is inherently disadvantageous for the information accuracy and will in turn negatively influence decision-making. Thus, our findings suggest that:

P1b. The lower the level of detail maintained in the planning object, the lower the level of

concreteness of the countermeasures to mitigate the foreseeable risk’s impact and the lower the accuracy of identifying supply chain risks

One case (Case D, industrial products) plans on the entire business setup, rather than the planning objects prescribed in literature. This planning object is not considered in extant S&OP literature. Focussing on the entire business setup is a consequence of the highly customized, in-house developed Advanced Planning System utilized by the organization. Coping with foreseeable supply chain risks requires a high level of flexibility and adaptability of the production processes, since a risk could specifically be targeted towards one production process, but might require adjustments for the entire business setup. Flexibility and adaptability are two characteristics typically lacking in the process-industry (Noroozi, 2014). However, the production processes of this organization are considered flexible and adaptable in the sense that the setup of the process (quality of raw materials, temperatures) can be adjusted directly if needed. Due to the identification of a new planning object, and its implications, we propose that:

P1c. Planning on the entire business setup is a consequence of the utilized IT-tooling and requires a

(22)

22

5.2. S&OP Planning frequency

All cases follow a monthly planning frequency, prescribed by literature (e.g. Olhager & Rudberg, 2002; Grimson and Pyke, 2007 and Ivert et al. 2015). This indicates that in terms of the frequency, S&OP is highly standardized. Even though this standardized monthly pace of conducting the process, the way in which the activities are executed still varies, which influences the attendance of the participants during the S&OP activities. Attendance is important since plenary discussions about identified supply chain risks and the status of previously agreed countermeasures will take place. As Grimson and Pyke (2007, p.324) argue, attendance can be ensured when the activities take place: “at regularly scheduled and fixed intervals”. In ensuring attendance, a strict and formal schedule needs to be generated: “by formal we mean that there are very specific data formats, meeting agendas and an S&OP meeting calendar” (Boyer, 2009, p. 4). This schedule should indicate meetings on fixed time intervals, such that the attendance during the S&OP activities is improved. Based on this finding, we suggest:

P2a. The monthly frequency facilitates a highly standardized schedule, which positively influences the

attendance during the activities, and in turn increases the awareness of risks and previously agreed countermeasures, which will mitigate the foreseeable risk’s impact

5.3. S&OP Planning horizon

S&OP’s goal is generating alignment within the organization, by balancing demand and supply (Thomé et al., 2012; Feng et al., 2013 and Wagner et al., 2014). An inherent feature of balancing demand and supply is the identification of gaps between both. Therefore, S&OP is regarded as a risk identification mechanism due to its continuous search for gaps in the predetermined horizon. Not all cases follow the tactical horizon prescribed in literature (e.g. Grimson and Pyke, 2007). Two cases consciously include the operational horizon in their S&OP process, which allows them to supplement their standardized S&OP process by risk-driven activities. These activities enable immediate decision-making and information sharing which is required due to the product-volumes processed by the cases. The idea of risk-driven activities seems to correspond with event-driven S&OP explained Grimson and Pyke (2007, p. 326) in which they argue: “[…] the highest state of S&OP maturity is when the activities are triggered by events […]. Conducting event-driven meetings that supersede the scheduled ones rather than waiting until the regularly scheduled S&OP in addressing the event”. Hence, S&OP members meet on an as-needed basis to deal with exceptions. Where Hahn et al. (2000) and Grimson and Pyke (2007) refer to complete S&OP processes initiated on an as-needed basis in coping with exceptions, the cases refer to specific S&OP activities targeted towards coping with the risks, which might be the first step towards a complete event-driven S&OP process. Examples of such exceptions are “competitor’s actions (promotions, pricing) or operational problems (yield rates, supply chain disruptions) (Hahn et al. 2000; Rooney & Bangert, 2002)” in Grimson and Pyke (2007, p. 325). Interestingly is that the exceptions prescribed all refer to events occurring on the operational horizon, which seems to imply a shift of S&OP’s focus from purely tactical towards an amalgamation of the tactical and operational horizon. Since the additional activities are enabled by the planning horizon maintained, we suggest:

P3a. Maintaining both the operational and tactical planning horizon within S&OP allows for

Planning risks or risky planning? A multiple-case study on how S&OP can cope with supply chain risks