Forecasting involves analyzing past data and identifying patterns, relationships, and trends within the data. These patterns are then used to develop mathematical models or statistical techniques that can be used to predict future values or behavior. The accuracy of the forecast depends on the quality and relevance of the historical data, the appropriateness of the forecasting techniques used, and the assumptions made during the process.

 In addition to using various statistical methods, we also employ machine learning techniques to improve long term or short term forecast of your sales, revenue or profit.

There are several methods and techniques used in forecasting, including time series analysis, regression analysis, exponential smoothing, moving averages, trend analysis, and machine learning algorithms. The choice of the forecasting method depends on various factors, including the type of the data available, the nature of the problem, the time horizon of the forecast, and the level of accuracy required.

Bsstats helps in various domains such as economics, finance, sales and marketing, supply chain management, weather prediction, population growth, and more. It helps business in demand forecasting, inventory management, production planning, budgeting, and resource allocation. Bsstats also assists governments and policymakers in making decisions related to infrastructure development, public health, energy consumption, and environmental planning.