Inventory classification based on decoupling points

Production & Manufacturing Research

2018

Self Cite

Continuous flow is the guiding star for lean thinking and considered the ideal state for value streams. Despite this objective, it is seldom possible to obtain a state of continuous flow in a wider context. Decision makers face dynamic environments, and variable internal preconditions require a flow-thinking approach that provides support in response to these challenges. In the present study, the underlying logic of flow thinking is first identified as the key management layer, and thereafter the effectiveness of flow is targeted. The vision of continuous flow is challenged by different exogenous requirements that result in flow discontinuities. Flow thinking is then used to identify 10 decision categories based on these discontinuities, each related to a type of decoupling point and classified as time-based (exogenous) or conversion-based (endogenous). The flow-thinking approach is finally applied in three different contexts: a time-phased product structure, a modularized approach for planning and control, and a mixed-model value stream.

Section: Systems and Flow Structuresmentioning

confidence: 99%

An ontology for flow thinking based on decoupling points – unravelling a control logic for lean thinking

Production & Manufacturing Research

2018

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“…Figure 2) to emphasize that this is mainly a separator between different decision domains rather than a stock point per se (Wikner, 2014). In line with Shingō (1981), the relation between the supply lead time S (Shingo called this lead time 'product lead time' P) and the delivery lead time D is decisive for the positioning of the CODP and the CODP is thus a demand-based decoupling point (Wikner & Johansson, 2015). The lead time S covers both internal manufacturing lead time and external lead time of purchased materials.…”

Section: Flow Driver and The Codpmentioning

confidence: 99%

Triadic perspective on customization and supplier interaction in customer-driven manufacturing

Production & Manufacturing Research

Bäckstrand

2017

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Customization and customer-driven manufacturing are both explicitly based on the focal actor's interaction with the customer actor. The impact of these aspects on the internal operations of the focal actor is relatively well known compared to the limited number of studies performed on the impact on the focal actor's supplier. The purpose here is therefore to investigate how the concept of customization complements the concept of customer-driven and how customer requirements affect interaction between a supplier and the supplier's supplier in a triad. Frameworks for different perspectives are developed where match and mismatch between the actors on the perception of flow driver and flow differentiation is highlighted. The frameworks are then applied on a case company to illustrate application.

“…The SA-FA-CA triad introduced above can be seen as consisting of a consumption system (the CA) and a supply system (the SA and the FA in sequence), according to Wikner and Johansson (2015). The supply system can, in turn, be divided into an internal supply system and an external supply system.…”

Section: The Podpdifferentiating Supply Based On Process Controllabilitymentioning

confidence: 99%

“…The framework derived is designed for use by companies analyzing their supplier interactions, and can be seen as a logical extension to Stavrulaki and Davis (2010) work, but providing more guidance concerning the interaction between the SA and the FA. Three concepts from the literature are used and described to analyze this interaction: delivery strategy is related to the CODP (Hoekstra and Romme, 1992), supplier relations related to the control strategy are defined with reference to the purchase order decoupling point (PODP) (Wikner and Johansson, 2015) and the purchasing portfolio matrix (Kraljic, 1983) is used as a baseline for developing a framework for differentiated supply. Six interaction configurations are identified and three risk strategies highlighted.…”

Section: Introductionmentioning

confidence: 99%

Customer-differentiated triadic interaction based on decoupling points

Bäckstrand

Johansson

2017

JGOSS

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Purpose The integration of supply chains together with the disintegration of individual actors in the supply chain shifts the focus from actors to challenges in the interaction between actors. This paper aims to identify risk strategies for different supplier interactions in triadic configurations to outline supply strategies. Design/methodology/approach Companies participating in a research project recounted the challenges they faced regarding the integration of customer order-based management and supply from a triad perspective. Six triad configurations were identified, based on the literature, resulting in three risk strategies, which were empirically illustrated in practice by the participating companies. Findings A key finding is that a triad perspective for a customer-differentiated approach to supplier interaction results in a material classification that highlights the circumstances in which to apply “balance efficiency”, “postpone”, “balance responsiveness” and “speculate” supply strategies. Research limitations/implications The research has focused on process drivers and controllability, and the results may require careful interpretation when there is a mix of standardized and customized products because further interaction differentiation may then be required. Practical implications The strategies developed herein provide guidelines for differentiated supplier interaction with explicit focus on triads where customer actors directly influence supplier actors. This approach highlights how outsourcing must be carefully executed when supplier actors are involved in delivery to customer orders. Originality/value The paper sheds new light on how customer requirements impact supplier interaction in terms of decoupling points related to both delivery strategy and control strategy. The study also presents a novel application of the Kraljic matrix in in terms of risk strategies in different triad configurations.