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Abstract.A methodological application of mass customization principles in engineer-to-order (ETO) processes is expected to lead to shorter lead times, increased quality as well as cost reductions. Product and process configurators, commonly used in mass customization processes, have to be adjusted according to ETO product and process requirements for their successful application in an ETO environment. In this paper the organizational requirements for a successful adaption of configurators to ETO processes are identified and structured. A Business Process Matrix capable of categorizing the implications of using product and process configurators in an ETO environment is developed.

Production plants are currently facing an increase in volatility and uncertainty of demand volumes. This environmental condition comes with highly fixed costs and capacity structures, which are mostly planned on the basis of forecasts and demand projections. Thereby, changing demand causes variances in manufacturing unit costs, endangering production plants' profitability, competitiveness and liquidity. Hence, synchronizing capacities and costs with demand volumes becomes an essential target for plant managers in the face of demand volatility and uncertainty. Approaching this target in practice entails various obstacles due to dynamic and interdependent target conflicts as well as a lack of a dedicated and applicable strategizing approach. In this paper, these obstacles are disclosed and evaluated based on action research cases.

Part 2: Knowledge Discovery and SharingInternational audienceThe pharmaceutical industry is undergoing a change. Different future developments such as the increasing amount of biopharmaceutical products and even stricter regulations increase the need for a reliable long range warehouse capacity planning. Results from a literature analysis indicate that managing these operations will mainly remain the responsibility of the pharmaceutical company itself and may not be outsourced. Hence, the capabilities must be built up within the pharmaceutical companies itself, too. However, none of the models identified in the literature can fulfill all requirements of a reliable and detailed long-range planning process in the pharmaceutical industry. Providing suggestions for further research areas, the paper contributes to the further development of more reliable planning processes