Forecasting the Future: AI and ML Reshape Artisanal Sales

In response to the complex needs of the client, a robust and intuitive web-based application was developed to revolutionize their sales forecasting process. This solution was intricately designed to encompass the full spectrum of forecasting requirements, from data ingestion and processing to advanced analytics and user interaction. Here’s a detailed breakdown of the key components of the solution:

• Web-Based Application Development: A sophisticated web application was developed to replace the existing manual, Excel-based system. This platform was engineered to handle large datasets, complex calculations, and provide comprehensive forecasting capabilities.
• Data Processing and Integration: The application was designed to automatically pull historical sales data from the client’s data warehouse. It seamlessly integrates this data with user-inputted market intelligence assumptions (MIA), ensuring that all relevant factors influencing sales are considered.
• Advanced Forecasting Models: Utilizing a suite of time-series forecasting models (SES, HWES, MA, ARIMA, VARMA), the application can generate accurate and detailed forecasts. These models were selected for their ability to handle different data patterns and forecasting needs. They can forecast at various hierarchical levels, from overall trends down to individual SKU levels.
• Adjustments for Market Events: A key feature of the solution is its ability to adjust historical data for significant market events, such as the COVID-19 pandemic. This ensures that forecasts are not skewed by extraordinary, non-recurring events.
• Integration of Market Intelligence Assumptions: The application allows users to input specific MIA at different levels (e.g., All, Style, Major Group, Minor Group, SKU), ensuring that forecasts are tailored to reflect anticipated market changes and trends.
• User Interface Design: The interface was crafted to be intuitive and user-friendly, catering to users with varying levels of technical expertise. This design approach ensures that the complex process of data input, model selection, and result interpretation is straightforward and accessible.

Innovations

• Custom Forecasting Algorithms: The development of bespoke algorithms tailored specifically to the client’s unique forecasting needs stands out as a key innovation. These algorithms are designed to handle complex data patterns and integrate various forecasting models seamlessly.
• Dynamic Market Intelligence Integration: A standout feature of the solution is its ability to dynamically incorporate Market Intelligence Assumptions (MIA) into the forecasting models. This innovation allows the client to input and adjust for non-historical data and trends, ensuring that the forecasts are not only data-driven but also contextually relevant.
• Adaptive Forecasting Models: The use of a range of time-series models like SES, HWES, MA, ARIMA, and VARMA, which are automatically selected based on the data characteristics, represents a significant advancement. This adaptability ensures optimal accuracy and relevance of the forecasts for different product & group levels as well as market conditions.
• Interactive Data Visualization and Reporting: The application includes advanced data visualization tools, enabling users to interact with the data and forecasts in a more meaningful way. This feature aids in better understanding and decision-making based on the forecast outputs.
• User-Centric Design Approach: The design and development of the application with a focus on user experience is an innovation in itself. It makes complex data processing and forecast generation accessible to a broader range of users, irrespective of their technical expertise.

High-Level Architecture

Components

• Data Integration and Management: Handles data flow from the data warehouse, ensuring efficient data processing and storage.
• Forecasting Engine: Implements various statistical models for accurate forecasting.
• User Interface (UI): Provides an intuitive platform for interaction with forecasting tools and data management.
• Security Layer: Ensures application security through user authentication and data protection.
• Market Intelligence Assumption (MIA) Handler: Manages the input and integration of MIAs into forecasts.
• Reporting and Visualization: Offers tools for detailed reporting and interactive data visualization.
• Administrative Dashboard: Enables user role management and application monitoring.
• Notification System: Keeps users updated on system status and important forecasting alerts.

Interactions

• The Data Integration Module feeds historical sales and MIA data into the Forecasting Engine for processing.
• The Forecasting Engine analyzes this data and outputs forecasts, which are then visualized and presented through the UI Module.
• The Security and Authentication Module interacts with all other modules to ensure data integrity and secure access.
• The Reporting and Visualization Module pulls processed data from the Forecasting Engine to create insightful reports and visual aids.

Core Technologies

• Backend: .NET 6 Web API, Azure Functions for data modeling
• Frontend: React for web applications
• Database: Microsoft SQL Server
• Deployment: Manual
• API Integration: REST API
• Authentication & Security: Custom JWT Authentication