{"title":"软件初创公司产品开发的度量框架","authors":"Narendranath Shanbhag, E. Pardede","doi":"10.1142/s0218495819500110","DOIUrl":null,"url":null,"abstract":"Business cases and customer problem spaces are evolving quicker than ever before and more startups are moving to adopt the lean startup methodology to match this speed of changing customer needs. This phenomenon, however, comes with its own set of opportunities and challenges for startups to build great products, while catering to customer pain points. To this end, there is a need for a metrics framework which can help startups succeed in creating good software solutions and building successful business models around these solutions. Metrics can help measure the effectiveness of the product in relation to the customer problem and help drive key decisions in both the product and business aspects of the startup. This paper reviews current frameworks on metrics for software products, studies the appropriateness in the context of software startups and proposes a metrics framework to help provide good software experiences, while subsequently building good business models around these experiences. The framework is designed to cover aspects of both the product and business space, ranging from considerations of the problem space identification to the evolution of the solution. The proposed framework is validated using a case study approach of a successful startup. The framework aims to help startups in their journey to success by providing an end to end, structured approach to metric identification.","PeriodicalId":45304,"journal":{"name":"Journal of Enterprising Culture","volume":" ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2019-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1142/s0218495819500110","citationCount":"3","resultStr":"{\"title\":\"A Metrics Framework for Product Development in Software Startups\",\"authors\":\"Narendranath Shanbhag, E. Pardede\",\"doi\":\"10.1142/s0218495819500110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Business cases and customer problem spaces are evolving quicker than ever before and more startups are moving to adopt the lean startup methodology to match this speed of changing customer needs. This phenomenon, however, comes with its own set of opportunities and challenges for startups to build great products, while catering to customer pain points. To this end, there is a need for a metrics framework which can help startups succeed in creating good software solutions and building successful business models around these solutions. Metrics can help measure the effectiveness of the product in relation to the customer problem and help drive key decisions in both the product and business aspects of the startup. This paper reviews current frameworks on metrics for software products, studies the appropriateness in the context of software startups and proposes a metrics framework to help provide good software experiences, while subsequently building good business models around these experiences. The framework is designed to cover aspects of both the product and business space, ranging from considerations of the problem space identification to the evolution of the solution. The proposed framework is validated using a case study approach of a successful startup. The framework aims to help startups in their journey to success by providing an end to end, structured approach to metric identification.\",\"PeriodicalId\":45304,\"journal\":{\"name\":\"Journal of Enterprising Culture\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2019-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1142/s0218495819500110\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Enterprising Culture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s0218495819500110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Enterprising Culture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0218495819500110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS","Score":null,"Total":0}
A Metrics Framework for Product Development in Software Startups
Business cases and customer problem spaces are evolving quicker than ever before and more startups are moving to adopt the lean startup methodology to match this speed of changing customer needs. This phenomenon, however, comes with its own set of opportunities and challenges for startups to build great products, while catering to customer pain points. To this end, there is a need for a metrics framework which can help startups succeed in creating good software solutions and building successful business models around these solutions. Metrics can help measure the effectiveness of the product in relation to the customer problem and help drive key decisions in both the product and business aspects of the startup. This paper reviews current frameworks on metrics for software products, studies the appropriateness in the context of software startups and proposes a metrics framework to help provide good software experiences, while subsequently building good business models around these experiences. The framework is designed to cover aspects of both the product and business space, ranging from considerations of the problem space identification to the evolution of the solution. The proposed framework is validated using a case study approach of a successful startup. The framework aims to help startups in their journey to success by providing an end to end, structured approach to metric identification.