Customer Enquiry Management in a Global Competitive Context: A Comparative Multi-Case Study Analysis

Business-to-Business (B2B) relationships, such as between a manufacturer and a customer, are increasingly important during the Customer Enquiry Management (CEM) process, particularly so for non-Make-To-Stock (non-MTS) companies operating in industrial markets. Few empirical studies have explored the CEM practices adopted by firms in practice. A study of the Italian capital goods sector by Zorzini et al. (2007) is a recent exception. Moreover, most studies have approached CEM from a cross-department integrated perspective but in the digital economy, and with globalization, outsourcing and extended supply chains, CEM needs to be approached from a broader supply chain-oriented perspective, incorporating B2B exchanges. This paper builds on the study by Zorzini et al. (2007) by conducting multi-case study research with seven UK-based companies in the capital goods sector, including three sales and support companies with offshore manufacturing. By adopting a cross-national research perspective, it assesses whether the proposed theory applies to other capital goods firms outside Italy. By also adopting a supply chain perspective of CEM it investigates current industry practice in B2B markets and explores whether cross-functional coordination and formalization issues can be extended into a global context. Evidence from the UK generally supports prior theory, confirming links between high levels of coordination, formalization of the CEM process and improved performance. Some refinements are proposed, for example, in order to make the theory suitable for a global context. The characteristics of a supply chain are important factors that affect CEM. This research has managerial implications for improving the CEM process in non-Make-To-Stock (non-MTS) capital goods companies from both an intra and an inter-organisational (B2B) perspective. Coordination with partners along the supply chain is needed at the enquiry stage and constraints linked to global customers should be considered when structuring the

Managing design variety, process variety and engineering change: a case study of two capital good firms

Many capital good firms deliver products that are not strictly one-off, but instead share a certain degree of similarity with other deliveries. In the delivery of the product, they aim to balance stability and variety in their product design and processes. The issue of engineering change plays an important in how they manage to do so. Our aim is to gain more understanding into how capital good firms manage engineering change, design variety and process variety, and into the role of the product delivery strategies they thereby use. Product delivery strategies are defined as the type of engineering work that is done independent of an order and the specification freedom the customer has in the remaining part of the design. Based on the within-case and cross-case analysis of two capital good firms several mechanisms for managing engineering change, design variety and process variety are distilled. It was found that there exist different ways of (1) managing generic design information, (2) isolating large engineering changes, (3) managing process variety, (4) designing and executing engineering change processes. Together with different product delivery strategies these mechanisms can be placed within an archetypes framework of engineering change management. On one side of the spectrum capital good firms operate according to open product delivery strategies, have some practices in place to investigate design reuse potential, isolate discontinuous engineering changes into the first deliveries of the product, employ ‘probe and learn’ process management principles in order to allow evolving insights to be accurately executed and have informal engineering change processes. On the other side of the spectrum capital good firms operate according to a closed product delivery strategy, focus on prevention of engineering changes based on design standards, need no isolation mechanisms for discontinuous engineering changes, have formal process management practices in place and make use of closed and formal engineering change procedures. The framework should help managers to (1) analyze existing configurations of product delivery strategies, product and process designs and engineering change management and (2) reconfigure any of these elements according to a ‘misfit’ derived from the framework. Since this is one of the few in-depth empirical studies into engineering change management in the capital good sector, our work adds to the understanding on the various ways in which engineering change can be dealt with

The impact of resources on decision making

Decision making is a significant activity within industry and although much attention has been paid to the manner in which goals impact on how decision making is executed, there has been less focus on the impact decision making resources can have. This article describes an experiment that sought to provide greater insight into the impact that resources can have on how decision making is executed. Investigated variables included the experience levels of decision makers and the quality and availability of information resources. The experiment provided insights into the variety of impacts that resources can have upon decision making, manifested through the evolution of the approaches, methods, and processes used within it. The findings illustrated that there could be an impact on the decision-making process but not on the method or approach, the method and process but not the approach, or the approach, method, and process. In addition, resources were observed to have multiple impacts, which can emerge in different timescales. Given these findings, research is suggested into the development of resource-impact models that would describe the relationships existing between the decision-making activity and resources, together with the development of techniques for reasoning using these models. This would enhance the development of systems that could offer improved levels of decision support through managing the impact of resources on decision making

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Boon or curse? A contingent view on the relationship between strategic planning and organizational ambidexterity

Numerous scholars have attempted to explain which factors allow for organizational ambidexterity. Strategic planning, as a possible antecedent, has not been considered so far. This is surprising because strategic planning is among the most widely used strategic decision-making tools in management practice and one of the most extensively studied concepts in management research. In addition, prior research has demonstrated the potential of strategic planning to impact innovation-related outcomes—both positively and negatively. Here, we investigate the association between strategic planning and organizational ambidexterity using a survey of 217 senior executives. We highlight the importance of considering how executives use strategic planning. Our results support the hypothesis that strategic planning's positive or negative association with organizational ambidexterity is contingent on other organizational factors. Our findings reveal that strategic planning is only positively associated with organizational ambidexterity when leaders' innovation orientation is extraordinarily high. We further contextualize this interaction effect by considering the environmental uncertainty perceived by the top management. This work contributes to the literature by examining the antecedents of organizational ambidexterity

Modeling the Structure and Complexity of Engineering Routine Design Problems

This paper proposes a model to structure routine design problems as well as a model of its design complexity. The idea is that having a proper model of the structure of such problems enables understanding its complexity, and likewise, a proper understanding of its complexity enables the development of systematic approaches to solve them. The end goal is to develop computer systems capable of taking over routine design tasks based on generic and systematic solving approaches. It is proposed to structure routine design in three main states: problem class, problem instance, and problem solution. Design complexity is related to the degree of uncertainty in knowing how to move a design problem from one state to another. Axiomatic Design Theory is used as reference for understanding complexity in routine design