Conclusions and managerial implications

Supply chain managers are fully aware of the importance of driving business actions toward lead time control. However, they have trouble uncovering the actual financial consequences of lead times given the complexity of the analysis involved (de Treville et al., 2014). This fact seriously hampers decision making in the lead time field. To make the proper investments, practitioners must be able to identify those areas that have the greatest impact on supply chain performance. In this research, we evaluate the effects of adjusting several lead time levers on the financial performance of multi-echelon supply chains operating in a wide range of scenarios. First, we compare the impact of lead times on traditional supply chains (where the nodes follow local strategies) and collaborative supply chains (where a global strategy governs the system). We reveal that system policies not only produce more mean net profit than the interaction of local policies, but also the robustness of these systems is much higher6 a concept which is acquiring key importance in the current business scene. These arguments strongly stand up for the widespread deployment of these systemic approaches to supply chain management in practice. This study demonstrates that the financial performance of supply chains is significantly sensitive to both the mean and the variability of lead times. Although under the conditions explored the fixed component of lead times has proven to be more damaging than the range, the magnitude of our results underscores the importance of investing in the re-engineering of processes in order to improve simultaneously both dimensions of lead time. The financial improvement derived from cutting and stabilizing lead times partially occurs due to the increase in the CSL (external performance). This is mainly affected by lead time variability, especially in those nodes near the consumer. The net profit increase is also explained by the reduction of the operating costs (internal performance), which are more closely related to mean lead times. Interestingly, there are significant differences between how production and shipping lead times impact on both supply chain archetypes. In traditional systems, shipping lead times clearly overweigh the production lead time. This occurs due to the damaging Bullwhip Effect, which strongly emerges in these supply chains and deteriorates their dynamic response. On the contrary, the relative importance of production lead times grows in collaborative systems. It can be understood as a consequence of the integration of processes, which effectively deal with the Bullwhip phenomenon and increases the robustness of supply chains. Overall, our analysis reveals the huge capacity for increasing the net profit of supply chains that emerges from lead time reduction and stabilization. These savings generated by improving the operation of the supply chain may even justify a big investment in processes, methods, and means of lead time improvement, as we have observed through a sensitivity analysis looking at the trade-off between cost and service of lead times. In spite of the robustness of our findings, this study is not exempt of limitations. These, in turn, define directions for future research. These limitations are mainly related to the assumptions adopted in the supply chain model. Note that the economic model is based on linear cost functions. Considering other cost functions may be an interesting next step (e.g. we could analyze the impact of economies of scale), as it would be exploring the impact of other lead time distributions. The study of other inventory policies and its parameters (e.g. the safety stock, the review period, and the proportional controller) may also be a research line worth pursuing. Bringing into the analysis the effect of new variables and exploring interaction effects would also enrich the study. For example, considering the impact of the value of the product, e.g. through demand-driven prices, investigating multi-product environments (Saldanha et al., 2009), analyzing consolidation effects (Wanke, 2009), and/or considering capacity constraintswhich may dynamically displace the bottleneck of the systemmay provide insights to relevant questions. Last but not least, this article underscores agent-based and Taguchi techniques as powerful approaches for managers to face complex and dynamic organizational problems. Agent-based modelling and simulation allows to investigate issues that would be intractable through other techniques. Reproducing the real world in a controlled environment helps practitioners see the whole picture and enable business transformation. Complementarily, the Taguchi methods allow managers to consider not only the mean performance but also the robustness of the proposed solutions. The potential applications of these techniques are yet emerging in the supply chain field; hence, they enable managers to build competitive advantages in order to cope with increasingly competitive global scenarios that are built on complex interdependences.

1. Highlights the limitations of the research and future research scope on the topic in 4-5 sentence