16 Dec 2020 08:45
MAGNIT PJSC (MGNT) Magnit Begins Large-Scale Supply Chain Transformation 16-Dec-2020 / 11:45 MSK Dissemination of a Regulatory Announcement, transmitted by EQS Group. The issuer is solely responsible for the content of this announcement. Press-Release | Krasnodar | December 16, 2020
Magnit Begins Large-Scale Supply Chain Transformation The Company will implement a unified automated forecasting and replenishment system for all store formats, product categories, and distribution centers with the help of Relex Solutions' platform. This world-class AI-enabled software will encompass all functions of goods distribution, significantly increasing transparency of operations and helping flexibly adapt various processes in line with the Company's development. Krasnodar, Russia (December 16, 2020): Magnit PJSC (MOEX and LSE: MGNT; the Company), one of Russia's leading retailers, has started implementing a unified forecasting and replenishment (F&R) system built upon a cloud-based platform from Relex Solutions. It will be the largest project in Russian logistics and one of the most extensive undertakings of this kind in the world. The brand-new system based on AI and ML technologies will encompass 22,000 stores and 38 distribution centers and will be adapted to the Company's continuously updated software and business architecture. By implementing the system, Magnit plans to increase availability of assortment in its outlets, particularly for Fresh and Ultra-Fresh categories, optimize inventory, ensure a high level of service, and improve the quality and speed of interaction with suppliers. The launch of the platform will require minimal effort from Magnit in terms of infrastructure and technical support, while rapid roll-out will ensure a quick return on investment. The pilot project will be launched in 2021 at one of the distribution centers in Krasnodar, which serves more than 1,250 stores. Previously, Magnit used its own solution, which was no longer able to satisfy the rate and quality of the Company's development process. New system implementation will enable eliminating data misalignment, improving end-to-end planning opportunities, and avoiding a huge number of manually performed operations. The unified automated platform powered by Relex uses an extensive library of data, including information on sales, demand analysis, marketing activities, store performance, and customer behavior across all sales channels. By analyzing this information, the system is able to forecast the sales volume for each product in each store with maximum accuracy and plan deliveries in a way that fully satisfies the demand for products. The solution enables the Company to manage the settings and logic behind the calculations, which allows flexibly adapting them to the specifics of a particular product group, as well as freeing up specialists by entrusting routine operations to ML algorithms while focusing the employees' efforts on overcoming non-standard challenges. There will be a significant decrease in workload for business analysts and IT specialists who maintained the old system. Magnit's forecasting team has been instructed and retrained to work with the new software. In addition to that, the Company is currently recruiting new employees with the necessary qualifications. The talent pool of experts freed up due to these efforts will now be used in other projects. "Supply chains represent one of the key aspects of Magnit's digital transformation. We need modern process automation tools to develop our chain efficiently and effectively. The forecast and replenishment system by Relex will enable us to consider and meet customer preferences as accurately as possible and continue adapting our value proposition,"-commented Maria Dei, Magnit's Supply Chain Director. "Relex's forecasting and replenishment solution is optimally suited to the scope of Magnit's business. AI and ML technologies will enable the Company to effectively automate the replenishment processes and secure huge benefits, both financial and operational. This is probably the most ambitious retail supply chain transformation project that Russian and international retail will see in the next two years,"-said Nikolay Antimonov, Forecasting and Replenishment Project Director at Magnit Retail Chain. "We are extremely pleased to bring Relex's solutions to Magnit. This will be one of our largest supply chain projects in the world. Together with our integration partner, Ywis, we have worked out all the necessary processes at the preparatory stage and are now ready to start the implementation itself. We are sure that with Relex, Magnit will get huge business benefits. We look forward to the quick start of the project and the first results,"-added Stefano Scandelli, RELEX's Senior Vice President for EMEA&APAC.
For further information, please contact:
Dmitry Kovalenko Director for Investor Relations Email: dmitry_kovalenko@magnit.ru Office: +7 (861) 210-48-80
Dina Chistyak Director for Investor Relations Email: dina_chistyak@magnit.ru Office: +7 (861) 210-9810 x 15101
Media Inquiries Media Relations Department Email: press@magnit.ru
Note to editors:
Public Joint Stock Company "Magnit" is one of Russia's leading retailers. Founded in 1994, the company is headquartered in the southern Russian city of Krasnodar. As of September 30, 2020, Magnit operated 38 distribution centres and 21,154 stores (14,699 convenience, 469 supermarkets and 5,986 drogerie stores) in 3,819 cities and towns throughout 7 federal regions of the Russian Federation. In accordance with the unaudited IFRS 16 management accounts results for 1H 2020, Magnit had revenues of RUB 763.4 billion and an EBITDA of RUB 86.9 billion. Magnit's local shares are traded on the Moscow Exchange (MOEX: MGNT) and its GDRs on the London Stock Exchange (LSE: MGNT) and it has a credit rating from Standard & Poor's of BB.
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ISIN: | US55953Q2021 |
Category Code: | MSCU |
TIDM: | MGNT |
LEI Code: | 2534009KKPTVL99W2Y12 |
OAM Categories: | 3.1. Additional regulated information required to be disclosed under the laws of a Member State |
Sequence No.: | 89781 |
EQS News ID: | 1155570 |
End of Announcement | EQS News Service |
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