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Discovering the Process for New Product Development (NPD) in Machine Learning Software.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Discovering the Process for New Product Development (NPD) in Machine Learning Software./
作者:	Naqvi, Ali.
面頁冊數:	1 online resource (233 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-05, Section: A.
Contained By:	Dissertations Abstracts International84-05A.
標題:	Software. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29732049click for full text (PQDT)
ISBN:	9798352976135

Discovering the Process for New Product Development (NPD) in Machine Learning Software.
Naqvi, Ali.

Discovering the Process for New Product Development (NPD) in Machine Learning Software. - 1 online resource (233 pages)

Source: Dissertations Abstracts International, Volume: 84-05, Section: A.

Thesis (Ph.D.)--The University of Liverpool (United Kingdom), 2021.

Includes bibliographical references

American Institute of Artificial Intelligence, my employer, is seeking to launch a machine learning (ML) based product. The new product launch constitutes as a strategic initiative which the board has determined as necessary and critical for the survival of the business. ML is a rapidly expanding branch of artificial intelligence (AI).A generic New Product Development (NPD) process is composed of two subprocesses: the concept design subprocess and the product development subprocess. At present, data mining methodologies (for example, CRISP-DM, KDD, SEMMA) from the late 1990's are being widely used to develop ML products - including for NPD purposes. Recent research indicates that those methodologies are being viewed as too narrow, unsuitable, and incompatible with the growing needs of the machine learning's rapid adoption and that practitioners are searching for alternatives. Recent findings also indicate that the failure rate in ML products and services is high. To make the product launch successful, AIAI must deploy a reliable and functional framework. Launching a new product without a methodology or framework will be irresponsible and using the existing methodology will be too risky for the organization. Given the strategic nature of the product launch, AIAI has determined that there is a need to explore what would constitute as an appropriate NPD framework for ML products and services. This research was launched to achieve that goal.The fundamental question addressed by this study is: what is a new product development framework for designing and developing machine learning products?Many well-developed and time-tested frameworks exists in the conventional (non-ML) information systems development. Information systems development (ISD) paradigms in the IT field have a renowned status as many researchers have pointed out that all approaches and information systems methods (for example, Waterfall, Agile, Rapid Application Development, and others) are directly or indirectly linked to the paradigms and approaches. This study also explores how conventional ISD paradigms can help define or discover an ML NPD methodology. This inquiry is undertaken as action research in the active setting of launching the AIAI's ML product. Whether conventional paradigms and approaches apply, or new ones are discovered, it is hoped that the research will contribute to a deeper understanding of ML systems design and development and advance the knowledge of designing new ML technologies.To have a successful product launch, the Institute must proceed with this research. As such, the research and the project timings will be synchronized. It is expected that the actions related to the product launch will help drive the research and the research will help drive the actions to achieve the goals of the project. Product launch involves other colleagues and partners and collaboration between various groups is essential. In addition to addressing the critical business problem and making contribution to knowledge, it is hoped that through this experience I will develop myself as a practitioner-researcher, as a leader, and most importantly, as a human being.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798352976135Subjects--Topical Terms:

619355
Software.
Index Terms--Genre/Form:

542853
Electronic books.

Discovering the Process for New Product Development (NPD) in Machine Learning Software.
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502 $a Thesis (Ph.D.)--The University of Liverpool (United Kingdom), 2021.
504 $a Includes bibliographical references
520 $a American Institute of Artificial Intelligence, my employer, is seeking to launch a machine learning (ML) based product. The new product launch constitutes as a strategic initiative which the board has determined as necessary and critical for the survival of the business. ML is a rapidly expanding branch of artificial intelligence (AI).A generic New Product Development (NPD) process is composed of two subprocesses: the concept design subprocess and the product development subprocess. At present, data mining methodologies (for example, CRISP-DM, KDD, SEMMA) from the late 1990's are being widely used to develop ML products - including for NPD purposes. Recent research indicates that those methodologies are being viewed as too narrow, unsuitable, and incompatible with the growing needs of the machine learning's rapid adoption and that practitioners are searching for alternatives. Recent findings also indicate that the failure rate in ML products and services is high. To make the product launch successful, AIAI must deploy a reliable and functional framework. Launching a new product without a methodology or framework will be irresponsible and using the existing methodology will be too risky for the organization. Given the strategic nature of the product launch, AIAI has determined that there is a need to explore what would constitute as an appropriate NPD framework for ML products and services. This research was launched to achieve that goal.The fundamental question addressed by this study is: what is a new product development framework for designing and developing machine learning products?Many well-developed and time-tested frameworks exists in the conventional (non-ML) information systems development. Information systems development (ISD) paradigms in the IT field have a renowned status as many researchers have pointed out that all approaches and information systems methods (for example, Waterfall, Agile, Rapid Application Development, and others) are directly or indirectly linked to the paradigms and approaches. This study also explores how conventional ISD paradigms can help define or discover an ML NPD methodology. This inquiry is undertaken as action research in the active setting of launching the AIAI's ML product. Whether conventional paradigms and approaches apply, or new ones are discovered, it is hoped that the research will contribute to a deeper understanding of ML systems design and development and advance the knowledge of designing new ML technologies.To have a successful product launch, the Institute must proceed with this research. As such, the research and the project timings will be synchronized. It is expected that the actions related to the product launch will help drive the research and the research will help drive the actions to achieve the goals of the project. Product launch involves other colleagues and partners and collaboration between various groups is essential. In addition to addressing the critical business problem and making contribution to knowledge, it is hoped that through this experience I will develop myself as a practitioner-researcher, as a leader, and most importantly, as a human being.
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