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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">kaz29</journal-id><journal-title-group><journal-title xml:lang="ru">Вестник Казахстанско-Британского технического университета</journal-title><trans-title-group xml:lang="en"><trans-title>Herald of the Kazakh-British Technical University</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1998-6688</issn><issn pub-type="epub">2959-8109</issn><publisher><publisher-name>Казахстанско-Британский Технический Университет</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.55452/1998-6688-2021-18-4-20-25</article-id><article-id custom-type="elpub" pub-id-type="custom">kaz29-363</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ФИЗИКО-МАТЕМАТИЧЕСКИЕ И ТЕХНИЧЕСКИЕ НАУКИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>PHYSICAL, MATHEMATICAL AND TECHNICAL SCIENCES</subject></subj-group></article-categories><title-group><article-title>МОДЕЛИРОВАНИЕ, РЕКОМЕНДАЦИИ И АНАЛИЗ СПРОСА ПЛАНИРОВАНИЯ В СЕКТОРЕ</article-title><trans-title-group xml:lang="en"><trans-title>MODELLING, RECOMMENDATION AND ANALISYS OF DEMAND PLANNING IN FMCG</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3712-5726</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бақытбек</surname><given-names>Б.</given-names></name><name name-style="western" xml:lang="en"><surname>Bakytbek</surname><given-names>B.</given-names></name></name-alternatives><bio xml:lang="ru"><p>050000, Алматы</p></bio><bio xml:lang="en"><p>Bakytbek Bekzat, Master of Technical Sciences, Demand Planning manager</p><p>050000, Abay avenue, 109b, Almaty</p></bio><email xlink:type="simple">bbakytbek@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0146-6633</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бектембаева</surname><given-names>А. Р.</given-names></name><name name-style="western" xml:lang="en"><surname>Bektembayeva</surname><given-names>A. R.</given-names></name></name-alternatives><bio xml:lang="ru"><p>050000, Алматы</p></bio><bio xml:lang="en"><p>Bektembayeva Aidana Rizaevna, Master of Technical Sciences, Senior expert E-Commerce</p><p>050000, Timiryazev st. 28b, Almaty</p></bio><email xlink:type="simple">Aidana.bektem@gmail.com</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">PepsiCo Kazakhstan<country>Казахстан</country></aff><aff xml:lang="en">PepsiCo Kazakhstan<country>Kazakhstan</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru">Beeline<country>Казахстан</country></aff><aff xml:lang="en">Beeline<country>Kazakhstan</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>24</day><month>12</month><year>2021</year></pub-date><volume>18</volume><issue>4</issue><fpage>20</fpage><lpage>25</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Бақытбек Б., Бектембаева А.Р., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Бақытбек Б., Бектембаева А.Р.</copyright-holder><copyright-holder xml:lang="en">Bakytbek B., Bektembayeva A.R.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://vestnik.kbtu.edu.kz/jour/article/view/363">https://vestnik.kbtu.edu.kz/jour/article/view/363</self-uri><abstract><p>Большинство быстроразвивающихся компаний по производству потребительских товаров (Fast-moving consumer goods – FMCG) преследуют две основные цели, чтобы добиться успеха на рынке. Во-первых, это максимизация прибыли, а во-вторых, оптимизация или минимизация затрат. Если компания сможет сбалансировать эти два ключевых показателя эффективности (key performance indicator – KPI), у нее есть все шансы на то, чтобы быть конкурентоспособной и успешной в своей области деятельности. Команда Supply Chain (SC), и в частности планирование спроса (Demand Planning – DP), играет решающую роль в достижении целей, упомянутых выше, с помощью систем моделирования рекомендаций. Команда по Supply chain – это те, кто может преобразовать потребности бизнеса в значимые и измеримые числа для supply chain, поддерживая здоровый уровень запасов и доставляя необходимые товары с максимальной свежестью и доступностью. Далее мы опишем и проанализируем, как добиться лучших результатов по сравнению с текущими решениями для конкретной компании PepsiCo, путем моделирования и анализа планирования спроса в секторе FMCG в целом.</p></abstract><trans-abstract xml:lang="en"><p>Most of the fast-moving consumer goods companies (FMCG) have two main targets in order to become successful on the market. First, it is profit maximization and the second one is cost optimization or minimization. If the company can hold those two key performance indicator (KPIs) in balance, it has all the odds to be competitive and successful in the field of operation. Supply Chain (SC) team and in particular Demand planning (DP) plays a crucial role in achieving those targets mentioned above with help of recommendation modelling systems. Demand planning team are those who can translate business needs into meaningful and measurable numbers for Supply Chain keeping healthy inventory level and delivering the goods that needed with the best freshness and availability possible. Further, we will describe and analyze how to achieve better results vs. current solutions on specific company called PepsiCo via modelling and analyzing Demand Planning in FMCG sector overall.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>прогнозирование</kwd><kwd>анализ</kwd><kwd>система рекомендаций</kwd><kwd>машинное обучение</kwd><kwd>большие данные</kwd><kwd>обучение с учителем</kwd><kwd>набор данных</kwd><kwd>планирование спроса</kwd><kwd>FMCG</kwd><kwd>цепочка поставок</kwd></kwd-group><kwd-group xml:lang="en"><kwd>prediction</kwd><kwd>analyze</kwd><kwd>recommendation system</kwd><kwd>machine learning</kwd><kwd>big data</kwd><kwd>supervised training</kwd><kwd>dataset</kwd><kwd>Demand Planning</kwd><kwd>FMCG</kwd><kwd>Supply Chain</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Anshuman Gupta and Costas D. 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