FMCG

Fast-Moving Consumer Goods

Agile Data Management for Demand Forecasting and Supply Planning

Integrating sales, inventory, and market data to support demand forecasting, supply planning, inventory optimization, and real-time operational monitoring.

Industry Background

Closing the Gap Between Insight and Execution

Fast-moving consumer goods are defined by high purchase frequency, short product lifecycles, and demand shaped by seasonality and promotions. As sales channels multiply across e-commerce, brick-and-mortar, and new retail formats, the ability to integrate and act on data across all channels has become a core competitive capability.

High-Frequency Demand Volatility

Massive transaction volumes and rapidly shifting consumer preferences require systems that can respond in real time.

Short Product Lifecycles

Shrinking windows from launch to discontinuation demand extreme agility in supply chain planning.

Omnichannel Data Integration

Unifying e-commerce, brick-and-mortar, and new retail data to eliminate silos and enable end-to-end coordination.

Challenges

Second-Level Performance Requirements for Supply Planning

Demand forecasting and merchandise planning require repeated cross-department review and adjustment before decisions are finalized. Planning cycles that take too long slow down discussions and delay decisions — making sub-10-second response times a hard requirement.

Complex Workflows with High Consistency Demands

Plan adjustments span multiple levels (group, subsidiary, channel, store) and multiple time horizons (annual, quarterly, monthly, weekly), requiring frequent rollbacks, recalculations, and result synchronization. Without reliable transaction control and concurrency management, data inconsistencies directly undermine execution.

High Cost of Multi-Source Data Integration

Supply planning draws on market research, historical sales, inventory status, channel feedback, and sentiment data — scattered across different systems and components, requiring significant effort to integrate and standardize.

Existing Solutions Cannot Balance Performance and Reliability

Relational databases provide transaction guarantees but lack the performance needed for sub-10-second planning. In-memory compute solutions like Spark offer speed but lack transactional integrity — leaving enterprises caught between the two.

DolphinDB Solution

Rich Plugin Ecosystem

External table connectors for existing databases and a broad plugin library for data buses, message queues, and external services significantly reduce system integration overhead.

High-Performance Compute

Columnar storage and vectorized computation enable fast cleansing, aggregation, and feature extraction across TB to PB-scale datasets, shortening data preparation cycles.
Built-in functions and machine learning modules address the full data engineering pipeline — from multi-source ingestion and ETL to feature engineering, model training, and forecasting.

Transactional Consistency

Transaction mechanisms and MVCC (multi-version concurrency control) support high-concurrency reads and writes across multiple users and planning levels — ensuring data remains consistent, traceable, and executable throughout the planning process.

Key Benefits

Lower Data Engineering and Integration Costs

A unified platform simplifies multi-source ingestion, ETL, and feature engineering — eliminating redundant development and system fragmentation. Reliable transaction mechanisms ensure data consistency, reducing plan rework and execution risk.

Faster Decisions and Greater Business Agility

Second-level merchandise planning and demand forecasting with dynamic adjustment across multiple channels and planning levels — significantly improving decision speed and execution agility in response to market shifts and demand changes.

Ready to Sharpen Your FMCG Business Agility?

Discover how DolphinDB can help your team:

Unify high-frequency sales, inventory, channel, and promotional data in one platform

Analyze sales velocity and movement in real time to support rapid replenishment and distribution decisions

Identify regional, channel, and product trends using time-series and behavioral data

Ensure transactional consistency so operational plans can be reliably executed