Quantitative Analysis of Predictive Business Analytics for Dynamic Decision-Making: A Survey-Based Study on Organizational Strategy Optimization

Abstract

Predictive Business Analytics (PBA) is the data-driven approach which involves statistical modeling, machine learning algorithms as well as the past history of data to improve strategic decision making for the betterment of the organization. With market dynamics becoming more and more complex, predictive analytics adoption is becoming an absolute necessity in order to enhance the decision making time, accuracy in forecasting and reducing the cost of operations. This paper takes a look on the level of PBA adoption across industries and the impact it has on the key business performance indicators. Quantitative research design based on a survey was used to collect data from 250 professionals from different sectors such as finance, retail, healthcare, manufacturing and technology. Key observations were made with an analysis of descriptive statistics, correlation analysis, multiple regressions and ANOVA to establish relationships between chosen predictors and organizational outcomes. Understanding that organizations that use predictive analytics provide 76.6% improvement in forecasting accuracy and 73.3% improvement in decision making speed and as a result are able to increase agility of strategic operations. Nevertheless, difficulties of integration (56.8%), skill shortages (51.4%), and high implementation costs (47.9%) were considered as bottleneck to extensive uptake. The result of the studies illustrates industry-wide discussion over developing workforce development and better infrastructure, as well as incorporating AI and automation into predictive analytics. As predictive analytics are part of business intelligence and business optimization, the body of knowledge on reporting their role empirically for users is growing, and this study provides an example. Insights can be helpful in making efforts in refining the use of analytics in an organization, improving the level of competitive advantage therefore increasing the long term sustainability of that organization in such data driven environment. Future research is conducted on models of adoption specific to the sector and the evolving effect of AI in predictive business analytics.