Smart Stock, Lean Warehouses: Optimizing Inventory with Run Rate Intelligence

Executive Summary

A leading wine and spirits supplier, managing 30+ global brands and serving over 1,700 distributors, sought to gain real-time visibility into its inventory run rate. Operating in a fragmented, forecast-heavy supply chain where sales may span years, the client needed smarter insights into what products were truly selling versus merely being shipped. By implementing an intelligent inventory run rate prediction solution, the client was able to optimize shipments, lower warehouse holding costs, and accurately forecast reorder levels—transforming planning from reactive to predictive. 

Read this case study to know more about how to implement smart inventory management strategies for lean warehouse operations and intelligent supply chain management. 

Problem Statement

The client, a wine and beverage supplier, imports and distributes premium alcohol brands across a wide distributor network. Inventory tracking traditionally stopped at the point of shipment—measured in cases of 6 or 12 bottles—without real visibility into sell-through rates at the distributor level. This disconnect created key challenges:

• No clarity on inventory run rate post-shipment
• Distributors’ forecasts did not always translate into real-time consumption
• Overstocking or understocking led to warehouse congestion or lost sales
• Delayed sales cycles (some SKUs taking years to move) made demand planning unreliable
• Difficulty in identifying slow vs fast movers, impacting stock and cash flow

The business needed a way to predict inventory run rate more accurately by integrating distributor-level sell-through trends and historical sales patterns.

Our Approach

The client needed to optimize inventory using smart warehouse technologies. The solution was structured into five key steps:

1. Data Integration

• Collated shipment data, distributor inventory reports, and sales data from multiple channels.
• Connected past and current year sales patterns with SKU-wise warehouse stock levels.

2. Run Rate Model Development

• Created a dynamic model calculating inventory run rate using:
  • Current stock on hand at distributor
  • Past and forecasted sales trends
  • Seasonal consumption patterns by region/SKU
  • Distributor-level throughput speed

3. Inventory Health Dashboard

• Built a visualization layer showing:
  • SKU-wise run rate (high, moderate, stagnant)
  • Days of inventory left per SKU per distributor
  • Potential dead stock alerts
  • Suggested reorder points and safety stock thresholds

4. Scenario Planning Tools

• Simulated reorder cycles based on multiple demand scenarios (e.g., festive seasons, new product launches).
• Provided alerts on which SKUs were overstocked vs understocked.

5. Stakeholder Training & Adoption

• Trained sales, supply chain, and distributor management teams on interpreting run rate insights.
• Set up automated reports and alerts for weekly action planning.

Our Solution

• Predicting run rates per SKU and region, by integrating real-time and historical data
• Flagging slow-moving stock for reallocation or promo planning
• Identifying reorder triggers based on predicted depletion rates
• Supporting better shipment planning, tailored to actual consumption velocity
• Enabling SKU prioritization—what to push, what to pause

Benefits

• Reduced warehouse congestion by identifying low-velocity stock early
• improvement in shipment planning accuracy, minimizing over-distribution
• Faster reorder decisions, decreasing stockouts
• Improved working capital efficiency by aligning inventory levels to true demand
• Increased supply chain responsiveness, supporting dynamic business needs

Key Updates & Learnings

• Distributor-level data granularity is critical—investing in digital reporting standards helped close visibility gaps.
• The “sale” must be redefined—not just shipment, but actual movement from distributor to consumer.
• AI models need continuous tuning—run rates shift with market seasonality, promotions, and macroeconomic factors.
• Business teams now use run rate dashboards weekly instead of monthly, making supply decisions far more agile.

By leveraging run rate intelligence, the company shifted from reactive inventory replenishment to proactive, demand-driven planning—freeing up capital and reducing warehouse congestion.

About CI Global

CI Global provides solutions for optimizing wine and beverage inventory, with a focus on areas such as real-time tracking, automated reordering, and integration with other restaurant management systems. Our approach aims to improve efficiency, reduce waste, and enhance decision-making for businesses in the hospitality and beverage industries. The solutions can be integrated with POS systems, accounting software, and other restaurant management tools to streamline operations. 

Users can access inventory data on the go from any device, offering flexibility and remote management capabilities. CI Global’s smart inventory management solutions are designed to adapt to the needs of businesses of all sizes, from small restaurants to large chains.

CI Global’s Expertise:

• CI Global is recognized as a “Transformation Catalyst for SMEs” by Nasscom Excellence Awards 2025. 
• We specialize in digital transformation across various systems, including ERP, CRM, PMS, and POS. 
• CI Global focuses on streamlining integrations, accelerating product compliance with automated testing, and reducing compliance-related errors. 
• Our solutions are designed to improve efficiency, enhance guest experiences, and drive business success. 

Questions we Receive from our Customers Regarding Inventory Optimization Solutions

1. How does run rate forecasting directly improve our shipment planning accuracy?

By aligning inventory movement with actual depletion patterns at the distributor level, run rate forecasting minimizes the lag between shipment and sell-through. This enables smarter, demand-driven shipment decisions, reducing both stockouts and overstock scenarios.

2. What’s the strategic value of integrating distributor-level sales data into our planning systems?

Distributor-level visibility transforms forecasting from assumption-based to evidence-based. It allows us to anticipate market responsiveness per SKU, leading to more agile decision-making and tighter control over working capital.

3. How does this solution support our long-term inventory cost optimization goals?

It optimizes inventory holding by identifying stagnating SKUs early and reducing unnecessary stockpiling. Over time, this shrinks carrying costs, improves warehouse efficiency, and frees up capital for higher-yield products. 

4. Can the model adapt to portfolio changes like new product introductions or brand expansions?

Yes, the model is built to incorporate dynamic inputs—including new SKUs—and rapidly learns from initial movement patterns. This ensures early-stage planning is not based on guesswork but on predictive insights.

5. What’s the expected ROI timeline from implementing run rate prediction analytics?

Organizations typically see measurable operational improvements—like reduced holding costs and improved shipment-to-sale ratios—within 1–2 quarters. The strategic value compounds as planning becomes more responsive and data-driven.

Closing Thought

Inventory isn’t just about stock—it’s about speed, relevance, and timing. By predicting run rate, the client transformed static inventory tracking into a living intelligence layer, guiding every shipment, shelf decision, and strategic move.