DEMAND - Strategic Forecasting

Forecasting demand is crucial for business profitability, reducing inventory costs, and mitigating the risk of lost sales due to stockouts. Specialized tools integrated with your ERP system analyze market trends and demand for your products, providing short-term, medium-term, and long-term forecasts.

Analytical Demand Forecasting Methods - 100% Web Application

    

Welcome to our suggestions for the new Internet

Structure

Designed for large-scale sales data processing and product demand forecasting:

Our system is engineered to efficiently manage extensive sales data and accurately predict product demand. Whether your business operates on a local or global scale, our tools are adept at handling the intricacies of various sales environments, ensuring reliable forecasts that support informed decision-making and operational efficiency.


Ten selected methods are implemented for their effectiveness, sourced from contemporary literature:

We've carefully chosen ten advanced forecasting methods known for their effectiveness and backed by current research. These methods are tailored to address diverse forecasting challenges, such as seasonal fluctuations and market dynamics. By integrating these cutting-edge techniques, our platform enables businesses to anticipate demand trends with precision, empowering them to optimize inventory levels, minimize costs, and capitalize on emerging opportunities.

Methodologies

Parallel application of multiple cross-validated methods

The program is open-content, meaning all implemented processes are documented in the literature and their typologies are included in the package. While it's not mandatory to apply all methods simultaneously (one can choose just one), combining and cross-validating results is recommended to achieve highly accurate forecasts for short-term, medium-term, and long-term product demand.

  • ARIMA (AutoRegressive Integrated Moving Average):
    ARIMA models use past values and differencing to forecast future values. They're effective for time series data with trends and seasonality.

  • Neural Networks:
    Neural networks learn patterns in data, making them powerful for complex, nonlinear relationships and sequential forecasting tasks.

  • Croston Methods:
    Designed for intermittent demand, Croston's method separates forecasting into models for the probability and size of non-zero demand periods.

  • SSA Decomposition Models (Singular Spectrum Analysis):
    SSA decomposes time series into components like trend and seasonality using eigenvector techniques, useful for nonlinear patterns.

  • Adaptive Smoothing:
    Adaptive smoothing adjusts smoothing parameters automatically based on data, ideal for responding to changing trends and patterns.

  • Exponential Methods:
    Exponential smoothing assigns exponentially decreasing weights to past data, effective for capturing trends and seasonal patterns.

  • Regression Analysis:
    Regression models forecast demand based on relationships with independent variables, suitable for identifying factors influencing sales.

  • Recurrent Plots:
    Recurrent plots visualize autocorrelation by comparing a time series with its lagged values, helpful for identifying cyclic patterns.

  • Maximum Entropy:
    Maximum entropy models estimate probability distributions using maximum information entropy principles, suitable for uncertain or sparse data.

  • Holt-Winters' Seasonal Method:
    Holt-Winters' method extends exponential smoothing to include seasonal components, effective for forecasting seasonal time series data.

The DEMAND program fills a market gap by combining classical with cutting-edge forecasting methods, cross-validated in a user-friendly environment with automatic parameter tuning.

Integration

The program integrates seamlessly with your ERP via web services but can also operate independently, reading Excel or CSV files. Results can be exported in Excel or CSV format for any further use.

In conclusion, forecasting demand accurately is not just a competitive advantage but a necessity in today's dynamic markets. With DEMAND, businesses can leverage a comprehensive toolkit to anticipate market needs effectively and optimize their operations accordingly.