Increasing accuracy and robustness of order promises

Abstract

Accurate order promising is a key requirement for customer satisfaction. Nevertheless, practitioners struggle with the reliability of the delivery dates they promise to customers. Consequently, the costs of demand fulfilment soar due to intensified communication, emergency processes in logistics and acquisition of costly external production resources. We identify and formalise product and process flexibilities in supply chains that can be exploited in production planning. Product flexibility is the possibility to produce several kinds of products from one predecessor product. Process flexibility is the possibility to use one production process to manufacture several products. In order to increase the accuracy and robustness of delivery dates, we develop an order promising methodology able to deal with demand mix uncertainty and heterogeneous customer order lead times. The approach anticipates changes in production plans made possible by product and process flexibilities. In a numerical study based on a case from the semiconductor industry, we demonstrate that our method increases the accuracy and robustness of order promises. For the studied case, we find that the consideration of process flexibility is more important for the generation of accurate and robust order promises than the consideration of product flexibility.

A contract portfolio perspective on the role of customer order lead times in demand fulfilment processes with supply shortage

“…Most publications in this field, however, study the influence of unbiased or biased ADI for given production control strategies (Karaesmen, Buzacott, and Dallery 2002;Claudio and Krishnamurthy 2009;Karrer, Alicke, and Günther 2012;Altendorfer and Minner 2014). What is often not considered, is that final customer orders often have different lead times (see also Seitz and Grunow 2017), and that this difference in the timing of ADI turning into actual orders has a large impact on the efficient allocation of capacities. As these ADI agreements and final order lead times are important parts of contracts in business-to-business settings, in this paper, we investigate the influence of the design of contract portfolios determining order lead times and ADI on the supply chain performance for a given demand fulfilment process.…”

Data driven supply allocation to individual customers considering forecast bias

“…Majority of the proposed methods, however, are based on optimisation. While a few approaches promise orders based on a given finished product supply (Pibernik, 2005(Pibernik, , 2006Seitz and Grunow, 2017), most contributions integrate order promising with production planning functionalities in assemble-to-order or make-to-order environments (Ball et al, 2003;Zhao et al, 2005;Tsai and Wang, 2009;Lin et al, 2010;G€ ossinger and Kalkowski, 2015), distribution planning functionalities (Jung, 2010) or a combination of both (Venkatadri et al, 2006;Yang and Fung, 2014).…”