Case Al.Capone

How Al.Capone Cut Inventory Turnover Time by 46% with LEAFIO AI

Founded in 2010, Al.Capone operates 120 stores across 12 of Poland's 16 provinces and carries an assortment of more than 2,500 SKUs.

Liquor store

  • 46%

    faster inventory turnover

  • 5.2%

    more sales

LEAFIO AI Transforms AI.Capone: Outstanding Results in Liquor Store Chain Operations

Al.Capone, a 120-store liquor retail chain in Poland, achieved a 46% faster inventory turnover and a 5.2% increase in sales after piloting LEAFIO AI's Inventory Optimization and Shelf Efficiency modules. The chain replaced decentralized, manager-driven ordering and manual planogram management with a centralized, data-driven system spanning its 2,500+ SKU assortment. These are initial pilot results, with the rollout continuing to scale across additional stores and SKUs.

Results at a Glance

Metric Result
Inventory turnover 46% faster
Sales +5.2%
Store network 120 stores across 12 of Poland's 16 provinces
Assortment under centralized management 2,500+ SKUs
Rollout status Stage 3 (scaling to additional SKUs and locations)

The Challenge: Decentralized Ordering and Manual Planogram Management

Al.Capone's replenishment processes were decentralized. Store managers placed orders based on sales data and subjective judgment, and inventory control was uncoordinated across the chain. The chain experienced overstocks and stock-outs, and suppliers had excessive influence over item selection.

To close these gaps, Al.Capone needed to:

  • Digitalize and centralize display management, previously handled by store managers with only partial supplier-provided display standards.
  • Centralize and automate ordering processes.
  • Establish comprehensive tracking of key inventory indicators, including stock levels, availability, overstocks, sales, and lost sales.
  • Base assortment decisions on in-depth analytics.

The Solution: A Centralized AI Platform for Inventory and Shelf Efficiency

Al.Capone's management board evaluated several vendors and selected LEAFIO AI. The rollout combined LEAFIO Inventory Optimization  for automated replenishment with LEAFIO Shelf Efficiency for digital planogram management, deployed as a single platform. Implementation teams from both LEAFIO AI Retail Solutions and Al.Capone worked together on the rollout, led on the client side by Commercial Director and Board Member Maciej Kureczko. His involvement helped ensure a smooth transition and a strong result for the business.

"The fundamental principles of LEAFIO AI also helped: every retail business, its processes, and operational needs are unique. This approach emphasizes the importance of implementing flexible solutions that adapt to current requirements." -  Maciej Kureczko, Commercial Director and Board Member of Al.Capone.

The stages of implementation:

Stage 1: The platform was integrated with the chain's current ERP system.

Stage 2: LEAFIO AI was launched for a limited number of SKUs, and Al.Capone specialists were trained to use the system.

Stage 3: LEAFIO AI tools are being scaled up to a larger number of selected SKUs.

Results: 46% Faster Inventory Turnover, 5.2% Sales Growth

The pilot delivered a 46% faster inventory turnover and a 5.2% increase in sales. It also enabled Al.Capone to:

  • Access deep analytical data, improving the speed and accuracy of decision-making.
  • Integrate assortment planning, procurement, and merchandising on a single platform, improving operational flexibility.
  • Build a foundation for further module integration across the network.
  • Ensure every store benefits from the same centralized system.
Store managers still ordering by instinct?

See how LEAFIO Inventory Optimization cut turnover time by 46% for Al.Capone.

Store managers still ordering by instinct?

"Our work with Al.Capone goes beyond software implementation. We're building a platform where ordering, planograms, and analytics work as one system. The pilot already delivered a 46% faster inventory turnover and 5.2% sales growth, and that's only the starting point. The project is ongoing, and our goal is to bring these results to all 120 stores and the full assortment." noted Jane Medwin, co-founder of LEAFIO AI.

The current results of the pilot run:

Before After
Digital planograms
Managing macro and micro space relied mainly on manual processes and staff experience. Checking planograms required in-person store visits, and product placement KPIs went untracked. This made it difficult to manage the growing chain. The process is now centralized and efficient. Using LEAFIO Shelf Efficiency, Al.Capone specialists create digital planograms and run daily monitoring and placement checks. The central office assigns tasks to store managers, who send photos of the displays through a mobile app.
Order processing
Results relied on the experience and decisions of store managers, later consolidated manually by the central purchasing department. Ordering processes are now centralized and standardized across the network. The system automates order formation and dispatch using current inventory levels and forecasted demand as inputs.
Automated order optimization
Manual reconciliation of orders with supplier requirements caused regular stock-outs and excess inventory. The process is now centralized and coordinated. The system considers average daily usage, current inventory levels, and goods in transit to calculate the optimal order quantity. This helped identify excessively high supplier requirements, leading to renegotiated terms.
Ordering schedule
Manual, ad hoc ordering reduced inventory management efficiency. The inventory replenishment system now runs on predefined schedules that match delivery frequency, improving consistency. Day-of-week coefficients in the ordering algorithm added a further layer of forecasting accuracy.
Supplier reliability
Matching incoming invoices with placed orders made it difficult to close orders, balance accounts, assess supplier reliability, and trace discrepancies. A direct link between each order and its delivery improved operational efficiency and supplier evaluation.
Inventory management
Overstocks and stock-outs went untracked under the previous approach. Overstocks and stock-outs are now calculated and analyzed daily using LEAFIO AI, which evaluates the effectiveness of ordering decisions.

"The LEAFIO AI system has elevated our operations to an unprecedented level. The results speak for themselves: we've achieved unparalleled efficiency, setting a new industry standard and demonstrating remarkable improvement," said Maciej Kureczko, Commercial Director and Board Member of Al.Capone.

About Al.Capone

Al.Capone is a specialized liquor retail chain in Poland. Founded in 2010, the company operates 120 stores across 12 of the country's 16 provinces. Its assortment includes more than 2,500 SKUs, spanning imported, local, and private-label spirits brands. This scale makes Al.Capone one of Poland's leading liquor retailers.

FAQ

How did Al.Capone improve inventory turnover with LEAFIO AI?

LEAFIO AI's automated replenishment system replaced Al.Capone's decentralized, manager-driven ordering process. The system calculates optimal order quantities from current stock levels, forecasted demand, and delivery schedules, delivering a 46% faster inventory turnover.

What LEAFIO AI products does Al.Capone use?

Al.Capone uses LEAFIO Inventory Optimization for automated replenishment and demand forecasting. The chain also uses LEAFIO Shelf Efficiency for centralized digital planogram management.

What was Al.Capone's main challenge before implementing LEAFIO AI?

Before LEAFIO AI, individual store managers at Al.Capone's 120 locations placed orders manually and independently. This decentralized approach caused overstocks, stock-outs, and gave suppliers excessive influence over assortment decisions.

What results has LEAFIO AI delivered for liquor retail chains?

In Al.Capone's case, LEAFIO AI delivered a 46% faster inventory turnover and 5.2% sales growth during the pilot phase. These results came from centralized ordering and digital planogram management across a 2,500+ SKU assortment.

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