A Telecommunication Industry giant in the Middle East
The company faced several challenges with budget forecasting, including improper utilisation of budget amount, inefficient financial planning, scattered data sources, poor data quality, the need for a dynamic solution, and separate forecasts for each department. These challenges resulted in financial losses, increased financial risks, and missed opportunities for growth.
The process involved collecting data from various sources, blending data, cleaning and transforming data, using time series forecasting, gathering results, and pushing results into Tableau.
By using this process, the company was able to address challenges such as improper utilisation of budget amount, inefficient financial planning, scattered data sources, poor quality of data, the need for a dynamic solution, and separate forecasts for each department.
The company obtained a comprehensive understanding of their financial situation, made informed decisions about financial planning and resource allocation, and improved financial performance.
The company created interactive dashboards and reports using Tableau to communicate financial information effectively and make data-driven decisions. It helped the company with budget forecasting and resulted in forecasted results at both an overall level and department level. These forecasts enabled the company to make informed decisions about financial planning and resource allocation and identify areas for improvement and optimisation.
The separate forecasts for each department allowed them to plan and allocate resources effectively based on their specific goals and objectives. Overall, the forecast results provided valuable insights into the company’s financial situation, enabling them to optimise their budget forecasting process and improve financial performance.
The key takeaway from the process implemented in the telecommunication company in the Middle East is that budget forecasting enabled the client to accurately estimate and forecast the budget amount. This allowed the company to make informed financial planning and resource allocation decisions, resulting in better financial performance.
By using time series forecasting and blending data from different sources, the company was able to obtain a comprehensive understanding of its financial situation. This allowed them to create separate forecasts for each department based on their unique needs and requirements. As a result, the company tackled underutilisation or overutilisation of the budget by different departments.