OMA

 

OMA is the largest wholesale and retail chain of building materials and tools, as well as goods for home and garden in Eastern Europe. Founded in 1992, the company is constantly expanding and today includes 38 sales facilities represented by retail stores, wholesale bases, and stores of the franchise system under the OMA brand. The largest OMA store occupies an area of more than 10,000 m2.

OMA LLC company - is:

• An assortment of more than 70,000 unique items.
• 45,000 people visit the retail network and online stores every day.
• 1,000 suppliers from 25 countries.
• More than 5,000 legal entities a month choose OMA as their wholesale supplier.
• Products of the network are supplied to 18 700 Eastern Europe organizations.

Most of the brands have established themselves as quality benchmarks: Bosch, Caparol, Keramin, Makita, ISOVER, PAROC, Ceresit, KNAUF, Tarkett, TekhnoNIKOL, Condor. Being one of the leaders in the volumes of supply of these products in Eastern Europe, the company offers the most favorable conditions for its customers. OMA also produces its private label products: dry construction mixes Wunder, FüLL paint and varnish materials, goods for leisure and garden SATO, and others.

The company "OMA" has been managing inventory for 2.5 years using the system LEAFIO Inventory Optimization. But the process of decision-making, system integration, and implementation was non-standard and required a lot of effort on the part of the customer and the contractor.

In the process of examining the business processes of inventory management of the company "OMA", the following difficulties were highlighted:

• The presence of a large assortment (about 1.5 million goods in warehouses) and a multi-level organizational structure in the procurement system (purchasing specialists (~50 people), category managers, heads of departments, and logisticians).
• At such a scale, a huge amount of time is spent on monitoring each element of the system: the introduction of current data, adjustments to orders, analysis of the effectiveness of managers and the inventory management system as a whole;
• Formation of chain orders occurred in semi-hand mode with the help of the commodity-accounting system Astor by the rules of min-max and counting stock for a minimum of 60 days, i.e. work on the system Pushing. This methodology was outdated and did not justify itself while forming orders did not take into account such parameters as packages, min. order of the supplier, safety stocks at stores, and others. Such management forced managers to adjust each order, which increased labor costs and reduced the quality of the orders themselves;
• Lack of informative analytics to identify problem areas and work with them: the company had no way to measure lost sales and surplus, or to quickly analyze other KPIs for the inventory management system in different sections and periods;
• The parameter Safety Stock (Safety Buffer) - the number of goods for the display which is not intended for sales and should always be in stock - was not supported. Also, the following data was not kept in the current state of such data: multiplicity of packs, binding of goods to the main supplier, order schedules, and others;
• A large number of suppliers required the ability to influence them, using a tool to assess the contribution of each supplier, as well as an analysis of its reliability and other KPIs in the context of its products.

All of the reasons mentioned above had a negative impact on the order's correctness, and consequently on the efficiency of the entire company. To maintain the network performance, as well as strategic development plans and ensure operational efficiency, the leadership of OMA LLC needed a tool of management and control of the network inventory, which is the main asset of the company.

The management of OMA Ltd. took a very responsible approach to choose a solution for inventory management. They considered various software products that would be easy and fast to implement, would not require additional human resources, and would cover most of the requirements and functions in inventory management. Before making the final decision to start the project, conducted many iterations with LEAFIO for a detailed review of the functions of the LEAFIO Inventory Optimization solution and identifying all the pitfalls.

Important factors in choosing an inventory management system were:

Methodology

A variety of algorithms allows a unified approach to the management of different goods. For example, to manage commodities with stable demand, an algorithm is based on Systems Constraint Theory, an approach that allows not to use forecasting, but to rely on the principle of pulling and responding to real demand. In order to work with goods with high demand volatility, the company's analysts have developed a new algorithm, CDA (consumption-driven algorithm). To manage goods at the central warehouse the algorithm allows taking into account demand at all stores. Such mechanisms of dynamic commodity management help to ensure constant product availability with minimal stocks in the system.

ANALYTICS

In addition to operational visualizations of problematic areas of inventory management right on the system's dashboard, the LEAFIO Inventory Optimization solution has a flexible block of analytics that allows you to track the dynamics of the company's key indicators: lost sales, surplus, turnover. The client was very interested in the analytics by suppliers on the above-mentioned indicators, as well as the ability to assess the reliability of the supplier, which is influenced by the timeliness and completeness of order fulfillment.

Transparency, clarity, and support

The implementation of the project is divided into successive stages according to the approved plan with a set timeline for its implementation. In the course of the project, the LEAFIO team conducts detailed user training, both within the system, as well as on the methodology of management. Support takes place at all stages of the project and after its completion with the provision of technical and methodological advice on an ongoing basis.

Price/performance ratio

The system is based on the SaaS (Software as a Service) model, so there is no need to invest in additional hardware (server), purchase software, or self-programming, as well as a long time-consuming system configuration. Payment is made in the form of monthly lease payments upon use of the system.

Before launching the project, the client identified the following main objectives:

• Automation of the process of forming orders and managing the level of inventory, reducing the influence of the human factor.
• Calculation and minimization of goods pits (lost sales), as well as analysis and reduction of excess inventory.
• Reducing turnover through the chain.
• Control over the main indicators of the inventory management system.

The inventory management system implementation project consisted of three phases:

Stage 1.

Setting up the integration between the client's accounting system 1C Astor and inventory management system LEAFIO Inventory Optimization.

Stage 2.

Pilot launch LEAFIO Inventory Optimization and user training.

Stage 3.

Scaling - connecting the entire target assortment to LEAFIO Inventory Optimization.

At each stage of implementation user training was conducted:

• Seminar training on the TOC inventory management methodology.
• Learning how to work with the program, its algorithms, and settings. 
• Learning how to work with the reporting system.

As well as project committees on the results of the work done after each stage.

Below, consider in detail each stage, the tasks that were performed during the project, and the effects.

The main task of the first phase - is to set up a daily automatic exchange of data between the client's ERP system and LEAFIO Inventory Optimization Solution.

This stage is the most important and time-consuming for both sides of the project because the success of the project directly depends on the correctness of the company's business processes and the correctness of the incoming data.

At the beginning of the project, a detailed audit of the current business processes was conducted, and the inventory management system as it is, as well as the customer's requirements for the automatic ordering system were studied.

In the process of studying the client's specifics, it was revealed that some business processes needed to be reconfigured. One of the most important tasks at the start was to move OMA from a Pushing system to a Pulling system. The Pull system was the basis of the company's inventory management and involved storing inventory at the SP (storage points) and DC (distribution center) for a minimum of 60 days of sales. To convince the customer to switch to Pulling, a simulation was done (Fig. 1) that shows the potential to reduce inventory by a factor of 3. Pulling implies the delivery of goods to SPs oriented on the real demand for goods at a particular warehouse and the lead time.

During the first stage, we found that much data needed to be updated.

In particular, assortment matrices, binding the main supplier, updating MOQ (minimum supplier order) and USQ (order quantum) parameters, and formalization of order schedules. Considering the scale of the company this process had to be automated and controlled, which we managed to do by joint efforts. For example, the customer maintained Types of Goods in the accounting system, based on which we automatically determined matrices. To solve the issue of MOQ and USQ, we created an algorithm that depended on the mode of delivery, storage point, and supplier. For operational control of this process, a schedule was created online, with deadlines and those responsible to fill in the missing information.

Another difficulty was the lack of a Safety Buffer (SB) parameter.

This is the amount of product, which is not for sales but for display which should always be available. Given the amount of assortment (about 1.5 million products on SP) To start the project, a temporary solution was made using the functionality of the LEAFIO Inventory Management Solution - the calculation and maintenance of inventory in days of sales, for different categories for different periods.

It is worth noting that during the implementation of such large-scale projects, you can not do without a clear and effective methodology of project management. In this project, we used Agile and Scrum methodology. At the beginning of each iteration, we always do the planning, i.e. we highlight the list of tasks from the general backlog of the project, and at the end, we do a retrospective and review the work done.

Standups, like the daily 15-minute team meetings and the Trello tool, helped all participants keep their hand on the pulse and understand at any given time what stage the project is at, what tasks should be done, and in what time frame, what has already been done.

When all the preparatory work was completed, the client's specialists were trained in the methodology of inventory management and work in the system.

Here I want to mention the customer's team and their contribution to the success of the project. Despite the amount of work, we successfully and on time began the second phase - Piloting.

The goal of the second stage is a detailed study of the system algorithms and the formation of the first orders for suppliers.

Given the difficult organizational structure in terms of inventory management, it was decided to create and train a "pilot team", which included 6 category managers, 2 administrators (business analysts who were involved from the first stage), and the project manager from the customer side. Thanks to this, it was possible to understand all the blocks and settings of the system in detail. It is important to note the work of the administrators, who created a powerful knowledge base with personal video tutorials on each block of the system.

During the pilot launch, ~20% of the vendors were connected, by direct supply to SP.

During this phase, initial Stock Buffers - target inventory levels at each storage location - were calculated. After the initial calculation (which is based on sales statistics), the system continues to monitor the goods and adjusts the buffers itself according to the actual consumption of goods. Thus, the Dynamic Buffer Management algorithm functions

Due to the peculiarities of the project, in addition to the standard functionality of the system

LEAFIO Inventory Optimization Solution, other settings were used. For example, the settings for Substitute Goods Families (Fig. 4) allow the client to make substitutions for alternative items. In this case, the system allows you to take into account the history of alternative goods and their parameters, as well as to run the algorithm for the output of the residuals of the old item.

Another peculiarity of the project was both requirements from suppliers on the minimum amount, weight, and volume of orders, as well as strict limitations on the budget for some orders. To solve these problems, the function block "Optimization" helped, where you can set the minimum and the maximum value of the order per supplier. Here you can also configure the division of orders by transport.

Consequently, all supplier requirements are taken into account automatically, without wasting extra time adjusting each order.

In the third stage, the entire target assortment was connected to the inventory management system LEAFIO Inventory Optimization Solution by direct deliveries to SP, after which all franchising stores were connected, then deliveries through DC, and the last stage was orders from DC to External suppliers.

On an active assortment, the system automatically generates and sends orders to suppliers daily, depending on the agreed order schedules. Auto-sending orders (without checking by managers) is 60%, and given the specifics of the business, it is a very good result.

Also, during the project implemented and actively used the reporting system to monitor the status of stocks. It was at the third stage, after the set of statistics of data in the system, that detailed training on working reporting and several meetings on the dynamics of the major indicators of the stock system (surplus, lost sales, turnover).

Already after 2 months of work in the system, we noticed the first results - a significant reduction in the surplus of the pilot groups

The "Last week/week before" report provides the client with the ability to compare the dynamics of these indicators in the context of warehouses, and groups, and go deeper into specific SKUs. With this report, managers quickly identify products with deteriorating dynamics (the indicator is highlighted in red) and can take corrective action.

It is worth noting that reporting in the system LEAFIO Inventory Optimization Solution built method Drill-Down, which allows you to first assess the picture as a whole, to understand the trends and problems, and then already go deeper for a more detailed and substantive study of the problems. In the system LEAFIO Inventory Optimization Solution, there are about 40 reports. The main reporting units: are ABCD analysis, Suppliers, Analysis by SKU, the network indicators, the causes of missed sales, and Goods with problem balances.

As stated in the prerequisite, the client did not have the ability to measure missed sales and surplus, so the Weekly Inventory Dynamics (Figure 7) became a frequently used report. The report is used to track the dynamics of inventory, and all the main indicators - turnover, surplus, missed sales, sales, and average inventory level, for the company as a whole or using samples (warehouse, manager, supplier, group, etc.).

LFL analysis (like-for-like) is very important. The report allows you to track changes in the indicators of the state of stocks for a long period in different time sections, as well as display the dynamics for two selected similar periods. You can analyze the reasons for changes in detail in the Analysis by SKU reports.

It is very interesting that for DC it is possible to select the type of turnover calculation taking into account the consumption of goods at the stores - then when calculating the total consumption, in addition to the consumption of goods at the DC itself, the consumption of goods at the stores for which the supplier is the DC is also taken into account.

OMA LLC has more than 1,000 suppliers, so the ability to assess the reliability and contribution of each to the inventory structure is critical. The block of reporting on suppliers consolidates all important data, which concerns a particular supplier.

This client report is used to determine supplier reliability, which is valuable when negotiating contract terms with counterparties. In addition, thanks to supplier analytics, it is possible to analyze the assortment based on sales, comparison of purchases with sales, missed sales with surplus, balances, and turnover in dynamics by months or weeks.

In OMA LLC, a stock management system LEAFIO Inventory Optimization has been implemented and now controls 95% of the entire assortment. Through the implementation of this project, the client was able to:

• Connect 95% of the entire assortment to the LEAFIO Inventory Optimization Solution, which in turn allowed:
  - Reduce the time for order processing;
  - Eliminate human factor as the cause of errors;

• Transfer to the auto-replenishment (without human involvement) 100% of orders by the scheme stores - DC, in turn, 60% of the total assortment.

• Make the ordering process transparent, with the ability to identify problematic positions and subsequent analysis of each ordered SKU.

• Get an analytics system to measure the performance of the company as a whole and of managers individually, which allows to quickly track and influence such undesirable phenomena as missed sales and surplus.
• Optimize inventory levels: in 12 weeks after launching the system on pilot groups, inventories were reduced by 15% and surplus sales decreased by 10% (on pilot groups), while sales increased; surpluses and missed sales decreased.
• From plugging into today (March 2019 and March 2021) improved turnover by 18% (6 days). Sales are up 32% (based on the company's own SP).
• Gain leverage over suppliers, with a separate block of analytics, especially supplier reliability scores.