M. Riesener, C. Dölle, J. Tittel, G. Schuh, Maximilian Reuß, E. Rebentisch
{"title":"Development of an Indicator Model for Anticipation of Strategy Implementation Failures","authors":"M. Riesener, C. Dölle, J. Tittel, G. Schuh, Maximilian Reuß, E. Rebentisch","doi":"10.1109/ICIEA49774.2020.9101992","DOIUrl":null,"url":null,"abstract":"Strategy is the fundamental means to plan and obtain a competitive advantage. Studies suggest that an extensive gap exists between strategy intent and strategy implementation outcomes, indicated by a low rate of achieved objectives. Especially manufacturing companies face a situation of shorter strategy-to-implementation timespans. Frontloading and the customer-induced demand for continuous innovation lead to shorter product life cycles and force manufacturing companies to adapt quickly. Whereas the number of tools and models for strategy design and good implementation practices is vast, attempts to quantify and anticipate strategy implementation failure risk are almost nonexistent. This paper introduces a new model based on quantifiable and easily available indicators for a topic that remains otherwise solely qualitatively addressed in literature. Following a use-case adapted selection of indicators, a methodology for analysis and prediction is proposed using logistic regression analysis. The model's performance is tested and validated with publicly available data from 14 car manufacturers over 20 years. The results show a statistically significant predictive power for strategy implementation failures and suggest the future use of the model as a tool in strategy implementation processes.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA49774.2020.9101992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Strategy is the fundamental means to plan and obtain a competitive advantage. Studies suggest that an extensive gap exists between strategy intent and strategy implementation outcomes, indicated by a low rate of achieved objectives. Especially manufacturing companies face a situation of shorter strategy-to-implementation timespans. Frontloading and the customer-induced demand for continuous innovation lead to shorter product life cycles and force manufacturing companies to adapt quickly. Whereas the number of tools and models for strategy design and good implementation practices is vast, attempts to quantify and anticipate strategy implementation failure risk are almost nonexistent. This paper introduces a new model based on quantifiable and easily available indicators for a topic that remains otherwise solely qualitatively addressed in literature. Following a use-case adapted selection of indicators, a methodology for analysis and prediction is proposed using logistic regression analysis. The model's performance is tested and validated with publicly available data from 14 car manufacturers over 20 years. The results show a statistically significant predictive power for strategy implementation failures and suggest the future use of the model as a tool in strategy implementation processes.