ReplenishIQ

Vendor-Managed Inventory reimagined

With ARBIS ReplenishIQ, manufacturers manage their customers' replenishment based on data—(semi-)automated and with full control.

ReplenishIQ
  • Sustainably reduce inventory levels
  • Reliably increase product availability
  • Minimize operational planning effort
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Reference

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ReplenishIQ

What is Vendor-Managed Inventory (VMI)?

In practice, different models determine who bears the responsibility for replenishment: the retailer, the manufacturer, or both together. While traditional setups leave the ordering decision entirely to the buyer, VMI actively shifts the primary responsibility to the manufacturer. This strategic shift enables a holistic optimization of the entire supply chain.

  • Efficient Resource Planning: Inclusion of production capacities, bottlenecks, and changeover cycles directly in the replenishment planning.
  • Minimized Effort: Operational ordering effort for the retailer is reduced to a minimum.
  • Holistic Optimization: Inventory levels, service levels, and process costs are improved across the entire supply chain.
BMI Buyer Managed Inventory
CMI Co-Managed Inventory
VRI Vendor Replenished Inventory
VMI Vendor Managed Inventory
What is Vendor-Managed Inventory (VMI)?

Market Analysis & Strategy

The Challenge:

FMCG supply chains are facing increasing structural pressure:

  • Rising costs across the entire supply chain.
  • High inventory levels combined with insufficient product availability.
  • Volatile demand, promotions, and pronounced seasonal effects.
  • Manual, fragmented planning processes with limited forecasting quality.
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Today, companies must simultaneously reduce inventories, increase service levels, and meet sustainability goals—all within an environment of increasing complexity and decreasing planning certainty.

The Solution:

Intelligent Steering with ReplenishIQ

ARBIS ReplenishIQ shifts the operational responsibility for replenishment from the customer to the manufacturer without replacing the human element. The system generates intelligent proposals based on daily inventory and sales data, as well as retailer promotion information. Manufacturers define targets, such as reach per SKU, and steer replenishment strategically.

Depending on the configuration, implementation is (semi-)automated, while final decisions can always be reviewed and released by human planners. Integrated truck-load optimization further ensures efficient transport utilization and reduced logistics costs.

Reduce Inventory

Reduce Inventory

The data-driven replenishment logic ensures low inventory levels with stable service levels, sustainably reducing stock without risking availability.

Intelligent Steering

Intelligent Steering

Automated proposals replace manual disposition—planners maintain control at all times, shifting focus to intelligent rather than manual planning.

Scalable Setups

Scalable Setups

Designed for real-world FMCG structures, ReplenishIQ is scalable across countries, warehouses, and customers to map complex multi-warehouse and multi-plant setups.

Master Volatility

Master Volatility

Promotional and special requirements are specifically accounted for and clearly separated from the baseline, making promotions and demand volatility manageable.

Consolidate Transports

Consolidate Transports

Integrated truck-load optimization reduces logistical volatility and transport costs by efficiently bundling and utilizing shipments.

Measurable Added Value

Insights from ECR studies and industry-wide VMI implementations demonstrate the typical performance improvements achievable through a structured Vendor-Managed Inventory approach:

Lower Out-of-Stock Rate

Lower Out-of-Stock Rate

Less Inventory

Less Inventory

Lower Planning Effort

Lower Planning Effort

Reduced Logistics Volatility

Reduced Logistics Volatility

Based on these benchmarks, companies using VMI solutions achieve significant results across the Supply Chain

  • Significant reduction in inventory levels while simultaneously increasing product availability.
  • Higher forecast and demand accuracy through daily consumption-based steering.
  • Tangible relief for planners due to fewer manual interventions and coordination efforts.
  • Minimized overstock, markdowns, and waste throughout the entire supply chain.

The actual effects achieved depend on the initial baseline, data quality, and the degree of automation in the respective VMI configuration.

Selected Features

ARBIS ReplenishIQ combines data-driven replenishment logic with high operational flexibility. It is specifically designed for complex FMCG realities—from multi-warehouse setups to promotion-driven demand peaks.

Data-Driven Replenishment Control

Data-Driven Replenishment Control

Processes daily sales and inventory data to derive intelligent replenishment proposals. Target and safety stock reaches can be defined individually per SKU, warehouse, and customer. External forecasts (e.g., from internal demand planning systems) can be optionally integrated or overridden.

Transparent Disposition & Decision Support

Transparent Disposition & Decision Support

Planners work in a dynamic view featuring article lists, KPIs, and time series (inventory, outflow, coverage, forecast). Historical trends, baseline vs. promotional outflows, and deviations are clearly visualized to provide a solid basis for manual releases or interventions.

Promotion and Action Logic

Promotion and Action Logic

Retailer-side promotions, pre-orders, and forecast information (e.g., via Salesforecast or DELFOR) are fully accounted for. Baseline and promotional effects can be reported separately. Rule-based and customer-specific extensions, such as automatic promotion detection, are available.

Integrated Logistics & Truck-Load Optimization

Integrated Logistics & Truck-Load Optimization

Ensures efficient transport utilization by bundling orders into optimized truckloads. This reduces logistical volatility and minimizes transport costs while maintaining high service levels.

Mapping Complex Supply Chain Setups

Mapping Complex Supply Chain Setups

Supports multi-warehouse and multi-plant scenarios with individual parameters, holiday/delivery calendars, and article-specific conversion or packaging logics. Successor and predecessor products are handled cleanly, including transition logic.

Integration & Scalability

Integration & Scalability

Integrates into existing ERP landscapes via standard EDI and file interfaces (e.g., INVRPT, DELFOR, PRICAT, IDoc, CSV/TXT). Orders can be automatically exported to defined interfaces. The system includes multi-language support, robust role/permission concepts, and is designed for scalable rollouts across various countries and retailers.

Trust & Practical Application

ARBIS ReplenishIQ is utilized by leading consumer goods manufacturers in complex supply chain environments. Developed for real-world FMCG requirements, the solution proves its value in daily operations—from managing promotion-driven volumes to international multi-warehouse setups.

Selected References:

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Frequently Asked Questions about ARBIS ReplenishIQ

What distinguishes ARBIS ReplenishIQ from traditional VMI solutions?

ARBIS ReplenishIQ views VMI as a controllable decision-making process, not a "black box." The solution generates transparent, data-driven replenishment proposals that can be implemented semi- or fully automatically depending on your configuration. In addition to sales and inventory data, the decision-making process incorporates promotions, target stock reaches, and logistical optimizations (e.g., truck-load utilization).

How much control do our planners retain?

Control remains with the human expert at all times. ARBIS ReplenishIQ supports planners with intelligent suggestions that can be reviewed, adjusted, and released manually. The degree of automation is flexibly configurable, ranging from purely supportive to largely automated.

What data is required for implementation?

The foundation consists of daily inventory and sales data from retailers. Additionally, retailer-side information on promotions and forecasts, as well as manufacturer-side data on production and delivery capacities, can be integrated. Upon request, scanner/POS data, internal company data, and existing forecast logics can also be included, allowing ReplenishIQ to adapt flexibly to your specific system landscape.
Auf Wunsch lassen sich außerdem Scanner-/POS-Daten sowie unternehmensinterne Daten und bestehende Forecast-Logiken integrieren. So passt sich ARBIS ReplenishIQ flexibel an die vorhandene System- und Datenlandschaft an.

How does ARBIS ReplenishIQ handle promotions and demand peaks?

Promotions and special campaigns are explicitly taken into account, provided the corresponding information is supplied by the retailer (e.g., via forecasts or pre-orders). Baseline and promotional effects can be reported separately, ensuring that temporary demand peaks do not distort the long-term replenishment logic.

With which ERP and planning systems can ARBIS ReplenishIQ integrate?

ARBIS ReplenishIQ integrates into existing ERP landscapes via standard EDI and file interfaces, particularly SAP-based systems. Supported formats include INVRPT, DELFOR, PRICAT, IDoc, and CSV/TXT. Orders and data can be imported and exported automatically.

How complex is the implementation?

The implementation period depends on the scope and complexity of the setup.

In practice, the timeline from project start to Go-Live is typically 2–3 months. For highly complex multi-country or multi-retailer scenarios requiring extensive foundational work, implementation can take up to 9 months.

Can ARBIS ReplenishIQ be scaled internationally?

Yes. ARBIS ReplenishIQ is designed for international use in the FMCG sector. It supports multiple countries, retailers, warehouses, and production plants, as well as varying calendar and logic versions and multi-language support.

Next Steps

Would you like to determine if a Vendor-Managed Inventory approach with ARBIS ReplenishIQ is the right fit for your organization? We would be happy to discuss your specific use case and demonstrate how your replenishment processes can be optimized through a data-driven, controlled approach.

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