| dc.description.abstract | Engineer-to-Order (ETO) production entails designing or redesigning, engineering, fabricating, and assembling products for specific customer orders. Companies manufacturing big-sized, high-value, and heavy-duty industrial products such as machine tools, power generation equipment, agricultural machinery, maritime equipment, etc., are perhaps the largest group of adopters of the ETO strategy (Adrodegari et al. 2015; Cannas and Gosling 2021; Gosling and Naim 2009; Zennaro et al. 2019). Adopting the ETO strategy allows these companies to deliver highly customized, technologically competitive, and innovative solutions to fulfill specific customer requirements (Hicks, McGovern, and Earl 2000). However, operating with the ETO strategy also introduces significant complexity and uncertainty to planning tasks in these contexts (Alfieri, Tolio, and Urgo 2012; Alfnes et al. 2021; Carvalho, Oliveira, and Scavarda 2016; Shurrab, Jonsson, and Johansson 2020b).
Due to customer-specific design, engineering, procurement, and production activities, the duration of the order-fulfillment process, i.e., delivery lead time, is typically long in ETO contexts. Estimating these long delivery lead times is a complex planning task since there is a wide range of factors influencing the lead times for different order-fulfillment activities. Furthermore, product and process specifications are often uncertain until the late stages of the order-fulfillment process in ETO contexts because of customer-specific design and engineering activities, further adding to the challenges of estimating the delivery lead times. While it is challenging to plan, estimate, and quote reliable delivery lead times in ETO contexts, the reliability of the quoted lead times is a critical factor for ETO companies in maintaining their delivery precision and competitiveness (Amaro, Hendry, and Kingsman 1999; Cannas et al. 2020; Grabenstetter and Usher 2014; Hicks, McGovern, and Earl 2000). The planning task of estimating these lead times and order delivery dates, known as delivery date setting, has motivated numerous academic studies over the past decades. However, ETO companies still struggle with effectively setting delivery dates while tendering for new customer orders.
The extant research on delivery date setting suggests that cross-functional coordination, i.e., coordination across functions such as sales, engineering, procurement, production, etc., positively influences the effectiveness of ETO companies’ delivery date setting process (Shurrab, Jonsson, and Johansson 2020a, 2020b; Zorzini, Corti, and Pozzetti 2008; Zorzini et al. 2008; Zorzini, Stevenson, and Hendry 2012). The planning concept known as Sales and Operations Planning (S&OP) is a widely advocated approach for improving cross-functional coordination and overcoming functional silos in planning processes. S&OP has been effective in various non-ETO production contexts (Kristensen and Jonsson 2018; Thomé et al. 2012b; Tuomikangas and Kaipia 2014). However, the application of S&OP for cross-functionally coordinated planning in ETO contexts has not been explored previously, and recent reviews on S&OP call for studies to fill this gap (Kreuter et al. 2022; Kristensen and Jonsson 2018). Motivated by the need for (1) improving cross-functional coordination in delivery date setting and (2) exploring S&OP applications in ETO contexts, this doctoral study has investigated how ETO manufacturers can design their S&OP process for effectively quoting delivery dates. To this end, the study has addressed three main research questions using case studies from the maritime equipment manufacturing industry and two systematic reviews of the existing literature.
RQ1: How do the characteristics of an engineer-to-order manufacturer influence the design requirements for sales and operations planning?
The first research question aimed to understand how S&OP design requirements are influenced by an ETO manufacturer’s contextual characteristics. This question was answered through a single case study of a maritime equipment supplier, with some additional insights from a systematic literature review. The findings indicate that the influence of ETO environments’ contextual characteristics on S&OP design requirements is significant and complex. Long product delivery lead times and order-driven engineering, procurement, and production activities imply that S&OP design requirements in ETO contexts starkly differ from the S&OP process designs traditionally advocated and implemented in mass production contexts, where S&OP primarily addresses forecast-driven production and inventory planning for product families. Low production volumes and long delivery lead times impose that S&OP should be order-driven. Various order-specific activities and parallel or simultaneous execution of orderfulfillment activities for various orders impose that S&OP is performed with a multi-project perspective with material availability constraints and capacity constraints from production and engineering resources. Diverse and highly specialized production resources impose higher levels of detail and granularity in planning capacity for production resources. The results from the case study highlight that delivery date setting is one of the main tactical planning tasks S&OP should support in ETO contexts. A synthesis of previous research provides various factors influencing coordination needs for delivery date setting in the S&OP process, e.g., product complexity, degree of customization, contextual uncertainty, etc., that managers must consider while designing their S&OP process.
RQ2: What are the available tools, methods, and frameworks for setting delivery dates within sales and operations planning in engineer-to-order manufacturing?
The second research question aimed to map the state of the art of the artifacts supporting delivery date setting in ETO contexts. This question was addressed through a systematic literature review on delivery date setting. The review shows that most of the contributions in the extant research have focused on developing planning and decision-support tools, e.g., optimization models, mathematical models, planning heuristics, etc. However, most of these contributions have focused on estimating production lead times, while the estimation of procurement and engineering lead times have been overlooked. The extant literature also provides some frameworks for guiding planning process design. However, these do not address the cross-functional planning needs of ETO contexts since most of these frameworks are based on make-to-order production contexts. The review reveals the need for developing process reference frameworks for delivery date setting as one of the items on the agenda for future research, motivating the final research question of this study.
RQ3: What are the main sales and operations planning activities and information flows for delivery date setting in engineer-to-order contexts?
The third research question aimed to identify the main cross-functional planning activities and information flow that should be considered in ETO manufacturing companies while designing the S&OP process for setting delivery dates. This question was addressed by systematically reviewing the literature on planning in ETO contexts. The review identifies 13 main S&OP activities for delivery date setting in ETO contexts clustered under the broad S&OP subprocesses of sales planning, engineering planning, procurement planning, and production planning. Sales planning selects and prioritizes customer enquiries and coordinates with different functions to formulate a response for the potential customer. Engineering planning defines the product’s preliminary specifications and assesses the complexity, workload, and duration of the detailed engineering activities required after order confirmation. Procurement planning identifies critical suppliers and subcontractors and the time required for procuring items from these actors. Production planning assesses the workload and duration of the production activities. The review identifies various information flows associated with each S&OP activity, such that each information flow provides a set of planning inputs for a particular planning activity. The planning activities and information flows are synthesized into an S&OP framework for delivery date setting in ETO contexts. The proposed framework can support practitioners in mapping, analyzing, and designing or redesigning their delivery date setting process with an emphasis on cross-functional coordination, which previous empirical studies have found to improve the effectiveness of delivery date setting. Two case studies of maritime equipment suppliers are presented to illustrate the framework’s application for mapping and analyzing planning activities in the delivery date setting process. The granularity of the framework is expected to enable practitioners to assess the relevance of specific planning activities and information flows for their particular contexts.
The findings of the doctoral study (1) highlight the significance and complexity of the influence of ETO environments’ contextual characteristics on S&OP design requirements and underline how S&OP requirements in ETO contexts differ from other production contexts; (2) provide the state of the art of artifacts supporting delivery date setting at the S&OP level in ETO contexts and highlight the various knowledge gaps that should be addressed to improve state of the art and better support the planning task in practice; (3) emphasize the need for planning frameworks to guide the design of the S&OP process for delivery date setting; (4) present the main planning activities and information flows that managers in ETO companies should consider while designing their S&OP process for delivery date setting; (5) highlight how the required planning activities and information flows may vary across ETO contexts.
While many ETO companies, in practice, commit to delivery dates without planning the resources and capacity required to meet those delivery promises, the thesis argues that planning is essential for ensuring that promised delivery dates are feasible to meet. While orderpromising without planning may occasionally be necessary for winning orders in low-demand markets, managers in ETO contexts must not accept this as the standard operating procedure to avoid overtime, subcontracting, and delay penalty costs in high-demand periods. To this end, the S&OP framework proposed by this doctoral study can aid ETO companies in systematically designing their delivery date setting and tendering process. | en_US |
