Paper Title
Strategies for Product Roadmap Execution in Financial Services Data Analytics
Article Identifiers
Authors
HARSHITA CHERUKURI , ER. OM GOEL , DR. LALIT KUMAR,
Keywords
Product Roadmap, Financial Services, Data Analytics, Objective Setting, , Stakeholder Engagement, Iterative Development, Agile Methodologies, Machine Learning, Predictive Analytics, Market Trends, Data Privacy, Regulatory Compliance, Data Governance, Integration, Cross-Functional Teams
Abstract
ABSTRACT The rapid evolution of financial services and the increasing complexity of data analytics necessitate effective strategies for executing product roadmaps. This study explores strategies for product roadmap execution within the context of financial services data analytics, focusing on aligning product development with strategic business goals and technological advancements. The financial services industry is characterized by stringent regulatory requirements, high data volumes, and a dynamic competitive landscape, making robust roadmap execution critical for success. The research highlights key components of a successful product roadmap, including clear objective setting, stakeholder engagement, and iterative development. Effective objective setting involves defining measurable goals that align with both market demands and organizational strategy. Stakeholder engagement ensures that diverse perspectives, including those of customers, regulatory bodies, and internal teams, are considered, facilitating better decision-making and prioritization. Iterative development, supported by agile methodologies, allows for continuous feedback and adjustments, enhancing the adaptability of the roadmap. Furthermore, the study examines the role of advanced data analytics techniques, such as machine learning and predictive analytics, in informing and refining roadmap strategies. Leveraging these techniques enables financial institutions to anticipate market trends, identify emerging opportunities, and mitigate risks, thereby aligning product development efforts with real-time insights. Challenges such as data privacy concerns, regulatory compliance, and integration with existing systems are also addressed. The research suggests strategies for overcoming these challenges, including adopting robust data governance frameworks, ensuring compliance through regular audits, and employing scalable technologies that facilitate seamless integration. The findings emphasize the importance of a collaborative approach to product roadmap execution, where cross-functional teams work together to align on goals and adapt to changing circumstances. By implementing these strategies, financial services organizations can enhance their ability to deliver innovative and compliant data analytics solutions that meet market needs and drive competitive advantage.
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How To Cite
"Strategies for Product Roadmap Execution in Financial Services Data Analytics", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 1, page no.d750-d758, January-2023, Available :https://ijnrd.org/papers/IJNRD2301389.pdf
Issue
Volume 8 Issue 1, January-2023
Pages : d750-d758
Other Publication Details
Paper Reg. ID: IJNRD_226492
Published Paper Id: IJNRD2301389
Downloads: 000121123
Research Area: Engineering
Country: ghaziabad, up, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2301389.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2301389
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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