Labeling Postponement-Strategy for the Supply Chain for Hair Care Products
Process without postponement-strategy (a) und new process with postponement-strategy (b)
Process without postponement-strategy (a) und new process with postponement-strategy (b)

Global operating companies are often confronted with uncertainties resulting from an increasing variety of products, shorter life cycles and a volatile development of demand. In order to cope with this uncertainty flexible, fast and reactive processes are needed. In this context, the so-called postponement-strategy is a possible approach. This approach can be described as the strategic postponement of decisions regarding product differentiation in order to sustain neutral conditions as long as possible. Manufacturing and assembly processes for customization may thus be postponed until a certain customer order exists.

The objective of the cooperative research project is the development of a simulation model for analysing the impact of a postponement-strategy in the hair care industry (see fig. 1). Therefore, the temporal and geographical decoupling of the filling process from the labelling process is analysed. The postponement of the labelling process allows for a more demand-driven generation of different country-specific variants. For this specific application, lower safety stocks, a higher machine availability and less obsolete product variants are possible advantages of a postponement-strategy. But in addition, also expenses have to be taken into consideration. Costs for the implementation and further expenditures resulting from the temporal and geographical decoupling need to be included in the analysis.

Overall, the selection and design of a suitable postponement-strategy depends on various influencing factors. As a methodology in the area of supply chain design, simulation offers the possibility of analysing these influencing factors in detail. Thereby, the impact of stochastic variables on the interdependencies within a postponement-strategy can be modelled. Based on this approach, different scenarios for implementing a postponement-strategy can be compared in simulation experiments. Overall the question may thus be answered whether a simulation based analysis is a suitable decision support when a postponement-strategy is considered.

Key Data:

Runtime: December 2017 until Mai 2018

Partner: Kao Manufacturing Germany GmbH

  • Modeling approach: Discrete-event and agent-based
  • Performance criterion: Logistics and production key performance indicators of various postponement scenarios, robustness of the scenarios against fluctuations in demand, variable sales forecast quality, lot sizes and set-up times