Application of Predictive Analytics in Business Decision Making: A study of IT Companies
Akanksha Lodhe1, Mrunali Patil2, Nikita Mohite3, Shubham Kambale4, Asst. Prof. Aishwarya Komti5
1,2,3,4 Students MBA, 5Asst. Prof. MBA Dept.
1,2,3,4,5 Zeal Institute of Business Administration, Computer Application & Research, Pune-41
Abstract - This study examines how predictive analytics improves business decisions in IT companies. Today, IT organizations generate large amounts of data on employees, projects, and operations. Predictive analytics uses this data to enhance decision-making, forecasting, planning, and risk management.
The primary objective of this study is to examine how predictive analytics facilitates informed business decision-making in IT companies, particularly in areas such as project management, customer analytics, resource allocation, risk management, and budget and financial decisions. The study employs a descriptive research design and draws on both primary and secondary data. Primary data has been collected from 100 IT employees using a structured questionnaire through a purposive sampling technique. The scope of the study is limited to IT companies. Secondary data have been collected from reliable sources, including Gartner, McKinsey & Company, IBM Corporation (2021), and Mikalef, Panos et al. (2022).
The study's findings show that predictive analytics helps organizations make better decisions by using past data. It predicts future outcomes, enhances project management, enables better use of resources, reduces risks, and supports financial planning. However, its effectiveness depends on data quality, appropriate tools, and skilled employees.
The study concludes that predictive analytics is an important tool for improving business decision-making in IT companies and helps organizations move towards more data-driven and strategic decisions
Key Words: Predictive Analytics, Business Decision Making, IT Companies, Workforce Planning, Forecasting, Risk Management, Data Analysis, Business Analytics
