Baltic Petroleum, a leading gas station operator in Lithuania, runs a network of 86 stations offering around 2,500 SKUs. To streamline replenishment and merchandising management, the company's leadership has decided to implement the comprehensive LEAFIO AI Retail Platform.
The company recognized the need to optimize its business processes and centralize stock and planogram management at the head office while focusing on improving performance indicators. In addition to the platform’s exceptional functionality, the LEAFIO AI team’s expertise and experience in Petrol station convenience store chains optimization projects were the deciding factors.
LEAFIO Inventory Optimization and LEAFIO Shelf Efficiency solutions, each with their functional focus, share a unified data exchange platform, creating a unique ecosystem for efficient inventory and shelf management.
The implementation process
LEAFIO Inventory Optimization and LEAFIO Shelf Efficiency solutions were implemented simultaneously following a classic three-stage methodology:
1) business process audit and data integration,
2) connecting a pilot assortment to orders and creating pilot planograms,
3) scaling to the entire network.
The client-side project team consisted of:
- Commercial Director, acting as the project manager.
- Two product group managers, business experts, future key users, and their four assistants handled inventory and shelf implementation tasks.
- Two IT specialists, including an IT project manager and a developer.
Communication format
The team interacted primarily online through video meetings and a working chat. This included regular Q&A sessions, weekly status meetings, and project committees summarizing the results at the end of each implementation stage. Additionally, project tasks were managed in a shared Trello space, progressing methodically in sprints according to the overall project work schedule.
Project 1: Inventory optimization and automated replenishment
How Baltic Petroleum managed inventory, promotions, and assortment before LEAFIO AI implementation
Before implementing LEAFIO Inventory Optimization, the order creation process was decentralized, with 84 gas station managers independently placing orders based on their experience. The process took about two hours per store, totaling 168 man-hours. This approach introduced a "human factor," leading to overordering and reduced control and transparency.
Suppliers' payment invoices were based on what they could deliver, making it impossible to compare ordered and delivered quantities or identify discrepancies.
Orders were sent through the electronic document exchange module and via email. Order schedules were maintained in Excel without integration into the software interface.
Internally, the company focused more on sales and margin analysis rather than inventory indicators such as surplus levels, lost sales, availability, and turnover. No convenient tool for the operational analysis of these indicators was available.
Promotional information was not integrated into the system and was maintained manually in Excel, risking data loss and compromising data integrity. This lack of integration with the current ordering system led to communication issues in supplying stores with promotional goods. Store managers manually determined order volumes based on their experience, often resulting in incorrect orders and causing either excess or shortages of promotional items.
There were no stable assortment matrices, and the assortment was the same for all store formats. At the same time, stores could order significantly fewer items than were available in the active matrix, and assortment management was handled by gas station managers rather than managers of product groups in the central office.
As a result, key inventory management challenges were:
- High overstock levels.
- Order accuracy issues due to human errors.
- Order schedules were not synchronized with the current ordering interface in stores.
- Difficulties in determining promotional stock quantities.
- Lack of a streamlined tool for analyzing order and stock indicators effectively.
- Fresh category management.
The lack of a systematic procedure for more frequent write-offs and inventory checks (typically once a month) was compounded by managers' subjective ordering in stores. This inconsistency affected the accuracy of inventory balances and consequently impacted the ordering process for such a sensitive category of goods as Fresh.
Changes in business processes driven by LEAFIO Inventory Optimization Solution
1. Centralized ordering process
The ordering process was centralized and is now carried out by 4 specialists at the central office instead of 84 gas station managers. This consolidation significantly freed up operational time for store managers while enhancing transparency and control across the network.
2. Dynamic аssortment management
Up-to-date assortment matrices were created and used to effectively manage product assortments across the network and plan store replenishment.
3. Enhanced fresh management
The write-off process in Fresh goods in both field operations and the accounting system was revised. This initiative aimed to ensure accurate balance reporting for optimal Fresh-algorithm orders, replacing the previous monthly procedure.
4. Using comprehensive inventory analysis tools
By implementing the LEAFIO Inventory Optimization system, the Baltic Petroleum team gained access to over 40 detailed reports and a visual dashboard. Different analytical tools were used in various stages of implementation to monitor key metrics and system performance.
- Insightful dashboard
During the pilot phase and ongoing operations, Baltic Petroleum actively utilized the user-friendly inventory dashboard and insights section displaying key indicators on stock levels, order processing, and assortment tracking.
- "Supplier Reliability" report
The "Supplier Reliability" report has proven invaluable in negotiations with suppliers, providing concrete data on order backlogs, under-deliveries, and late deliveries to drive service level improvements.
- "Phantom Inventories" report
The report facilitated an analysis of stagnant inventory items, prompting investigations into discrepancies such as accounting system inaccuracies, shelf availability, and relevance to store assortment matrices.
“Implementing LEAFIO Inventory Optimization has revolutionized our operations. The implementation period required a lot of our resources and some changes to our business logic, but after LEAFIO AI was implemented, it automated the order process, minimizing human involvement and ensuring meticulous control at every stage. By optimizing our personnel's time, we've enhanced our focus on customer service and operational efficiency. The comprehensive analytical reporting further empowers our decision-making, making us more agile and responsive in managing our business,” said Edvin Bachšijan, CEO at Baltic Petroleum.
Project 2: Merchandising automation and planogram management optimization
How Baltic Petroleum managed planograms before the LEAFIO Shelf Efficiency implementation
Before implementing the LEAFIO planogram optimization system, there was no comprehensive merchandising process. Stores independently decided on shelf placements, and category managers lacked visibility into whether there was space for the entire assortment. Additionally, planograms for individual items were not created.
An exception was the Beverages category, which had a basic planogram managed in Excel. Category managers sometimes requested photo reports from stores via the internal system to verify planogram compliance.
Key challenges in merchandising management
- Absence of a dedicated merchandising function: Product category managers partially handled merchandising tasks, but there was no distinct role for merchandising.
- Lack of standardized planograms: There was no clear understanding of where, how much, and what kind of goods could fit on the shelves. Gas stations independently decided on shelf placements without general layout rules.
- Non-digitized merchandising process: The manual process hindered the assessment of key merchandising metrics, such as sales per meter.
- Overstocking issues: The number of active items ordered exceeded the available shelf space.
- Lack of planogram implementation control: There was insufficient oversight to ensure planograms were followed accurately.
Changes in merchandising processes driven by LEAFIO Shelf Efficiency Solution
1. Full planogram management cycle
The process now includes a complete cycle of planogram management, from creation to implementation and control.
2. Dedicated merchandiser role
A new position was created to handle merchandising functions based on recommendations.
3. Enhanced analytics
With the solution implementation, the Baltic Petroleum team gained access to a comprehensive analytics module with detailed reports for both tactical and strategic merchandising management.
Key reports used during implementation:
- Assortment report: Ensures all required category products are on the shelf.
- LFL report: Analyzes sales dynamics in pilot categories and monitors shelf stock levels daily.
- Layout efficiency report: Calculates the efficiency of planograms, tracks changes, and compares sales dynamics with peer stores.
- Dashboard on tasks: Monitors task progress and control.
Total outcomes of LEAFIO AI’s Retail Platform implementation
Notably, the project achieved a payback period of just one month, with an impressive ROI of 1581% in the first year. This success was driven by the annual net profit generated from sales growth, accelerated turnover, and reduced operational costs for inventory management, which covered the initial investment entirely.
Enhancing business process efficiency and automating operations with the LEAFIO AI Retail Platform has significantly affected the KPIs across the Baltic Petroleum store chain.
We've observed the following positive KPI trends:
There has been significant improvement in reducing write-offs for Fresh products, achieved through system order management refinements. Within just 2 months, write-offs for the critical "Sandwiches" category decreased from 11% to 1.9%.
Digitizing and analyzing the existing planograms, along with making changes and regularly monitoring the updated layout, resulted in the following improvements at the pilot store compared to similar stores:
Benefits of the LEAFIO AI Retail Platform for Baltic Petroleum
- Reduced workload
- Fewer human errors
- Faster and more accurate order processing
- Dynamic assortment management with up-to-date assortment matrices
- Supplier reliability monitoring
- Enhanced transparency and control
- Digitized planogram management
- Improved planogram compliance
- Comprehensive tools for in-depth and real-time analysis of store KPIs
After completing the implementation phase, the LEAFIO AI and Baltic Petroleum teams continue to collaborate. Baltic Petroleum will transition to the Сustomer Success Department, which not only provides technical support but also assists in monitoring and analyzing key KPIs, optimizing processes, and implementing new functionalities from ongoing releases.
The LEAFIO AI team is enthusiastic about the partnership and confident that Baltic Petroleum is now well-equipped for further growth and success with the new tools.
