ReplenishAI™ for Enhanced Forecasting and Replenishment

Solve Inventory Challenges with AI/ML-Driven Demand Pattern Clustering

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Are you struggling to identify seasonal demand trends and the items that behave similarly during the season? Do you know what the lift is for those product groups and how long the season lasts?

Developing those models can be time-consuming and error prone. In addition, having an inaccurate model and items inaccurately associated with those models will cause inferior forecasts and result in poor inventory management and lost sales.

TrueCommerce's ReplenishAI™ uses advanced technology to create demand pattern clusters, that once processed into our Vendor Managed Inventory application will provide incredibly accurate forecasts.

Companies are currently challenged by:

Manual clustering

Time-consuming and labour-intensive process to group items by demand pattern.

People working and choosing EDI provider

Missed sales

Backward-looking forecasts fail to capture sudden demand spikes.

Inefficient analytics

Unable to capture subtle trends that affect product demand.

Overly broad profiles

Items that could be grouped more efficiently are lumped into one-size-fits-all profiles.

High inventory costs

Excess stock leads to wasted working capital and inefficiencies.

Features of ReplenishAI™

Innovative Replenishment

TrueCommerce leads the VMI industry in innovation with the integration of Artificial Intelligence (AI) and Machine Learning (ML). Our platform transforms how companies forecast demand and manage inventory, offering faster, more accurate, and data-driven results.

Advanced Demand Clustering

Using AI/ML, ReplenishAI™ analyzes your entire product portfolio, grouping items with similar demand patterns into clusters—delivering results in just one hour, compared to the weeks or months required by manual methods.

Smarter Forecasting with AI/ML

The system processes demand patterns for thousands of items, smoothing data and applying clustering algorithms to deliver accurate sales profiles. These profiles are fed into the VMI forecasting function, allowing for more precise replenishment cycles based on real-world demand trends.

Accurate, Dynamic Sales Patterns

Our AI/ML models create specific yearly demand trend patterns for products. These patterns consider regional and seasonal variations, ensuring your inventory forecasts are aligned with actual market needs.

Accuracy Improvement

AI-driven demand pattern clusters deliver an increase in demand forecasting accuracy against a manual process. In a pilot of the application, the AI profiles beat the manual forecasts for 68% of the products managed. The results were coming into the season with a more accurate forecast and exiting the season with less inventory on hand.

Optimised Inventory Management

With more accurate forecasts, companies reduce missed demand, optimise days of supply, and improve working capital utilisation.

3 Key Advantages of AI/ML-Enhanced VMI

Improved uniformity in sales profiles, providing more consistent inventory management.

Identification of hidden sub-trends that manual analysis often misses, allowing for better decision-making.

New sales profiles are generated that were previously overlooked, unlocking new demand opportunities.

Why AI/ML Forecasting Matters for Your Business

Under-forecasting can lead to significant revenue losses due to stockouts and missed sales opportunities. By integrating TrueCommerce ReplenishAI, companies can see exactly how much demand they’ve missed in the past and calculate the potential revenue impact.

Start optimising your supply chain today. Use ReplinishAI™ to drive more accurate forecasts, maximise sales opportunities, and reduce excess stock, leading to more efficient use of working capital.

ReplenishAI™ for Enhanced Forecasting and Replenishment

Solve Inventory Challenges with AI/ML-Driven Demand Pattern Clustering

Are you struggling to identify seasonal demand trends and the items that behave similarly during the season? Do you know what the lift is for those product groups and how long the season lasts?