Authors: Krishnaben Kachiya
Abstract: Zero Based Budgeting Automation for UK CFOs in 2025 examines how predictive analytics can strengthen financial planning, improve cost optimisation, and support more effective resource allocation within organisations operating in the United Kingdom. Rising economic uncertainty, inflationary pressure, increasing regulatory expectations, and rapid digital transformation have encouraged Chief Financial Officers to move beyond traditional budgeting approaches that often rely on historical spending patterns. Zero Based Budgeting requires every expenditure to be justified from the beginning of each budgeting cycle, creating greater financial discipline and encouraging evidence based decision making. When combined with automation and predictive analytics, this approach enables organisations to identify inefficient spending, forecast future financial requirements, and improve strategic planning. The study investigates the contribution of predictive analytics in enhancing Zero Based Budgeting automation by analysing how advanced analytical techniques support expenditure forecasting, cost optimisation, financial transparency, and operational efficiency. The research also explores the role of automation technologies in reducing manual budgeting activities, improving data accuracy, accelerating budget preparation, and assisting Chief Financial Officers in making informed financial decisions. Furthermore, the study evaluates the organisational benefits and implementation challenges associated with adopting automated Zero Based Budgeting systems across different business sectors in the United Kingdom. A quantitative research methodology has been adopted to achieve the research objectives. Primary data will be collected through a structured questionnaire distributed among Chief Financial Officers, finance managers, financial analysts, budgeting professionals, and senior finance executives working in organisations across the United Kingdom. The collected data will be analysed using statistical techniques to examine the relationships between predictive analytics, budgeting automation, cost optimisation, and financial performance. The findings are expected to provide empirical evidence regarding the effectiveness of predictive analytics driven Zero Based Budgeting in improving financial decision making and organisational efficiency. The research contributes to the existing literature by integrating concepts of Zero Based Budgeting, financial automation, and predictive analytics within the contemporary financial management environment. It also provides practical recommendations for organisations seeking to modernise budgeting processes while improving cost control and strategic resource allocation. The findings will assist Chief Financial Officers, financial decision makers, technology providers, and business leaders in understanding how predictive analytics can transform budgeting practices and support sustainable financial management. The study ultimately demonstrates that automated Zero Based Budgeting supported by predictive analytics has the potential to improve organisational competitiveness, strengthen financial resilience, and create greater value through accurate forecasting and effective cost optimisation.
