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Data-Driven Product Strategy and Business Analytics Research
Subject area: Management and Commerce · Area of research: Business Analytics and Product Strategy
DOI: https://doi.org/10.64388/IREV8I5-1714429
Abstract
The paper discussed the application of data-driven product strategy and business analytics within contemporary product development and innovation. This paper, through an integrative review of academic literature and industry framework, integrates knowledge on the usage of data-based product planning, the product lifecycle management supported by big data, and the strategic decision-making based on analytics. Findings revealed that data radically changed the way that organizations felt the opportunities in the market, their vision of products, and maximized their offerings. This paper also highlighted key challenges, such as data fragmentation, organizational resistance, and model reliability limitations that restricted the complete implementation of analytics-based models. Hence, an integrative framework was created to show how analytics can be integrated into the visioning, planning, and ongoing optimization processes. Finally, this paper concluded that data-driven product strategy is an important organizational capability that enables more adaptive, customer-centric, and competitive product outcomes.
Keywords
Product Strategy; Business Analytics; Product Lifecycle Management; Predictive Analytics; Cyber-Physical Systems; Big Data; Digital Transformation; Decision Support Systems.
How to cite this paper
@article{1714429,
author = {Kehinde Arigbolo},
title = {Data-Driven Product Strategy and Business Analytics Research},
journal = {Iconic Research And Engineering Journals},
year = {2024},
volume = {8},
number = {5},
pages = {1499-1504},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1714429.pdf},
abstract = {The paper discussed the application of data-driven product strategy and business analytics within contemporary product development and innovation. This paper, through an integrative review of academic literature and industry framework, integrates knowledge on the usage of data-based product planning, the product lifecycle management supported by big data, and the strategic decision-making based on analytics. Findings revealed that data radically changed the way that organizations felt the opportunities in the market, their vision of products, and maximized their offerings. This paper also highlighted key challenges, such as data fragmentation, organizational resistance, and model reliability limitations that restricted the complete implementation of analytics-based models. Hence, an integrative framework was created to show how analytics can be integrated into the visioning, planning, and ongoing optimization processes. Finally, this paper concluded that data-driven product strategy is an important organizational capability that enables more adaptive, customer-centric, and competitive product outcomes.},
keywords = {Product Strategy; Business Analytics; Product Lifecycle Management; Predictive Analytics; Cyber-Physical Systems; Big Data; Digital Transformation; Decision Support Systems.},
month = {November},
doi = {https://doi.org/10.64388/IREV8I5-1714429}
}