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Forecasting Excellence

Use best-practice forecasting models with or without AI and compare results in minutes.

LOGIBLOX enables you to use the power of a fully automated process to train various best-practice forecasting models. Find out whether your data is forecastable and select from the best performing forecasting method to get the best accuracy possible without any experience in data science.

Business Problem

Forecasting your sales or fincancial budget for the next month / quarter / year to align costly resources with e.g. inventory management, marketing campaigns, and staffing levels is a vital step in your business decisions process. However, most companies lack the expertise and resources to build (advanced) predictive models in-house.


By applying statistical techniques and predictive modeling, data analysts can generate forecasts that help organizations in budgeting, resource allocation, production planning, inventory management, sales forecasting, and other strategic decision-making processes.

Forecasting techniques can range from standard methods like moving averages and exponential smoothing to more advanced approaches like ARIMA (AutoRegressive Integrated Moving Average), exponential smoothing state space models, or machine learning algorithms. All of them are included in the LOGIBLOX Forecasting Excellence solution.

The LOGIBLOX Forecasting Excellence solution with its fully automated process, helps you to use the best forecasting model for your data without writing a single line of code. LOGIBLOX hides the complexity and leverages end-to-end machine learning, from data preparation to model training, comparing forecasting methods, accuracy and deployment. This involves the following steps in the background:

  • Data Preparation: Upload historical sales data into LOGIBLOX. We will automatically clean and preprocess the data, including imputing missing values and scaling numerical features.
  • Model Selection: LOGIBLOX will automatically select the best forecasting algorithm based on the data characteristics and the business objectives. LOGIBLOX supports various time series forecasting algorithms such as multi-variate SARIMA, Prophet, and LSTM.
  • Model Training: LOGIBLOX will train the selected model on the historical data and evaluate its performance using various metrics such as MSE, RMSE and MAPE.
  • Model Tuning: If the model's performance is not satisfactory, LOGIBLOX can automatically tune the hyperparameters of the model using techniques such as grid search and Bayesian optimization.
  • Model Deployment and your App: Once the model is trained and tuned, LOGIBLOX can deploy it via REST API or integrate it to your system or into a custom forecasting app or dashboard build with the LOGIBLOX APP Designer (Learn more).


In data analytics and in business, forecasting plays a crucial role in various domains and industries. It involves analyzing time series data, such as sales figures, transactions, usage, stock prices, demand patterns, or website traffic, to forecast future values or trends.

Without data science knowledge, you can easily leverage historical data patterns and statistical relationships to project future outcomes and guide business actions. By incorporating LOGIBLOX Forecasting Excellence, organizations can gain valuable insights into future trends, make proactive decisions, optimize operations, and achieve better business outcomes.

With LOGIBLOX, it`s very easy to:

  • check the forecastability of your current data set
  • detect patterns in your data that unlock value
  • learn from your historical data to predict future sales, workload, resource needs, budget and others


Our No-code approach can save valuable development time and reduce the risk of errors.

Better Accuracy

LOGIBLOX can automatically select the best forecasting algorithm and tune its hyperparameter to improve the model's accuracy.


LOGIBLOX can handle large volumes of data and automatically scale the computational resources as needed.

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