The Implementation of a Cash-Flow-Based Mathematical R&D Project Selection Model

Bernhard Lienland
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Abstract

Customer project selection is a challenge for many industrial companies. An inappropriate project selection approach can lead to constraint violations, high fixed costs, and suboptimal portfolios. To overcome these problems a cash-flow-based linear optimization model was developed in partnership with a tier-1 automotive supplier. Implementation barriers had been verified through a case study conducted at two organizational hierarchies. Results suggest that an application at the operating levels is possible. At higher levels, though, product and firm complexity require major implementation efforts. This article serves theorists as well as practitioners in multiple regards. First, an overview of existing project selection methods and their application in practice is provided. Additionally, the supplier's current appraisal process is depicted. Second, operations research implementation barriers are identified and validated for the adoption of the proposed mathematical project selection approach. Third, a guideline including procedures to overcome experienced difficulties is presented.
基于现金流的R&D项目数学选择模型的实现
客户项目选择是许多工业公司面临的一个挑战。不恰当的项目选择方法可能导致违反约束、高固定成本和次优投资组合。为了克服这些问题,我们与一家一级汽车供应商合作开发了一个基于现金流的线性优化模型。通过在两个组织层次上进行的案例研究,验证了实施障碍。结果表明,在操作层面的应用是可能的。但是,在更高的层次上,产品和公司的复杂性需要大量的实现工作。本文在多个方面为理论家和实践者服务。首先,概述了现有的项目选择方法及其在实践中的应用。此外,描述了供应商当前的评估过程。其次,为采用所提出的数学项目选择方法,识别并验证了运筹学实施障碍。第三,提出了克服经验困难的指导方针。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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