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A Conceptual Model for Financial Analytics Driven Enterprise Value Creation in Technology Firms
Subject area: Science,Engineering and Technology · Area of research: Financial Analytics
Abstract
This review presents a conceptual model for financial analytics-driven enterprise value creation in technology firms, emphasizing the integration of advanced analytical tools with strategic financial management. As technology enterprises increasingly rely on intangible assets such as intellectual property, digital platforms, and data ecosystems, traditional valuation approaches struggle to capture their full economic potential. The proposed model synthesizes frameworks from financial engineering, data analytics, and corporate strategy to establish a dynamic, evidence-based system for value measurement and enhancement. It highlights the role of predictive financial analytics, real-time performance dashboards, and AI-enabled decision engines in optimizing capital allocation, profitability forecasting, and shareholder value. The review further explores how financial analytics can drive innovation funding, improve risk-adjusted returns, and align financial performance metrics with long-term strategic growth. Through an examination of key case studies and academic literature, the paper identifies the enablers and barriers to financial analytics adoption in technology-intensive environments. The study concludes by proposing a structured pathway for integrating analytics maturity with enterprise value creation frameworks, supporting more agile, data-informed financial governance. The conceptual model serves as a strategic guide for executives, financial analysts, and policymakers aiming to enhance organizational competitiveness in a rapidly evolving digital economy.
Keywords
Financial Analytics; Enterprise Value Creation; Technology Firms; Predictive Modeling; Strategic Finance; Data-Driven Decision-Making
How to cite this paper
@article{1713358,
author = {Oluwaremi Ayoka Lawal, Titilayo Elizabeth Oduleye},
title = {A Conceptual Model for Financial Analytics Driven Enterprise Value Creation in Technology Firms},
journal = {Iconic Research And Engineering Journals},
year = {2018},
volume = {2},
number = {2},
pages = {174-186},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1713358.pdf},
abstract = {This review presents a conceptual model for financial analytics-driven enterprise value creation in technology firms, emphasizing the integration of advanced analytical tools with strategic financial management. As technology enterprises increasingly rely on intangible assets such as intellectual property, digital platforms, and data ecosystems, traditional valuation approaches struggle to capture their full economic potential. The proposed model synthesizes frameworks from financial engineering, data analytics, and corporate strategy to establish a dynamic, evidence-based system for value measurement and enhancement. It highlights the role of predictive financial analytics, real-time performance dashboards, and AI-enabled decision engines in optimizing capital allocation, profitability forecasting, and shareholder value. The review further explores how financial analytics can drive innovation funding, improve risk-adjusted returns, and align financial performance metrics with long-term strategic growth. Through an examination of key case studies and academic literature, the paper identifies the enablers and barriers to financial analytics adoption in technology-intensive environments. The study concludes by proposing a structured pathway for integrating analytics maturity with enterprise value creation frameworks, supporting more agile, data-informed financial governance. The conceptual model serves as a strategic guide for executives, financial analysts, and policymakers aiming to enhance organizational competitiveness in a rapidly evolving digital economy.},
keywords = {Financial Analytics; Enterprise Value Creation; Technology Firms; Predictive Modeling; Strategic Finance; Data-Driven Decision-Making},
month = {August},
}