{"id":2678,"date":"2021-05-11T14:20:17","date_gmt":"2021-05-11T12:20:17","guid":{"rendered":"https:\/\/devstage.bix-consulting.com\/?p=2678"},"modified":"2023-06-16T11:53:10","modified_gmt":"2023-06-16T09:53:10","slug":"vermeidung-von-out-of-stock-situationen","status":"publish","type":"post","link":"https:\/\/www.bix-consulting.com\/en\/vermeidung-von-out-of-stock-situationen\/","title":{"rendered":"Avoidance of out-of-stock situations"},"content":{"rendered":"

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Herausforderung<\/h4>\n

Ein in europaweit agierendes Unternehmen bietet Tankkarten f\u00fcr seine ca. 250.000 Gesch\u00e4ftskunden an. Das Gesch\u00e4ftsmodell beinhaltet f\u00fcr das Unternehmen ein hohes finanzielles Risiko, da es prozessbedingt in Vorleistung (Kostenabgang vor Zahlung des Endkunden) geht. Die H\u00f6he der Vorleistung betr\u00e4gt pro Monat einen 10-stelligen Betrag! Ziel muss es demnach sein, die Wahrscheinlichkeit eines Zahlungsausfalls zu minimieren.<\/p>\n

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Unser L\u00f6sungsansatz<\/h4>\n

biX Consulting hat auf Basis von KI ein Modell entwickelt, welches die Problematik der Kundenbewertung deutlich optimiert. Im Rahmen von Big Data werden sekundenschnell interne sowie externe Daten zusammengef\u00fchrt, verarbeitet und daraus eine verl\u00e4ssliche Aussage zur Bonit\u00e4t des (Neu)-Kunden getroffen. Mit dieser L\u00f6sung wird die Wahrscheinlichkeit des Ausfallsrisikos elementar reduziert.<\/p>\n

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Herausforderung<\/h4>\n

Unerwartete Kundennachfrage f\u00fchrt zu Lieferengp\u00e4ssen, da die vorhandenen Best\u00e4nde nicht optimal auf die verschiedenen Lager verteilt wurden. Dies geschieht meist dadurch, dass bisherige manuelle Analysen auf einer berechneten Reichweite der einzelnen Materialien an ihre quantitative Grenze sto\u00dfen und unerwartete Schwankungen nicht ber\u00fccksichtigt werden k\u00f6nnen.<\/span><\/p>\n

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Unser L\u00f6sungsansatz<\/h4>\n

Mit Hilfe von Maschinellem Lernen wird auf Basis historischer Daten ein Modell der Kundenbedarfe erstellt. Hierdurch k\u00f6nnen Simulationen erstellt werden, die durch Umverteilung der vorhandenen Best\u00e4nde das gesamte Bestandssystem so optimieren, dass sowohl OOS-Situationen als auch \u00dcberbest\u00e4nde vermieden werden k\u00f6nnen. Durch Einsatz von Exception Reporting k\u00f6nnen automatisiert Situationen aufgezeigt werden, die ein manuelles Eingreifen erfordern und gleichzeitig alle ben\u00f6tigen Informationen und m\u00f6gliche L\u00f6sungsoptionen zur Verf\u00fcgung gestellt werden.<\/p>\n

Mit den biX AI Tools kann der L\u00f6sungsansatz vollst\u00e4ndig in Ihr SAP System integriert werden.<\/p>\n

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Ihr Nutzen<\/h4>\n

Durch die optimale Verteilung der vorhandenen Best\u00e4nde auf die verschiedenen Lager k\u00f6nnen zus\u00e4tzliche Ums\u00e4tze realisiert und gleichzeitig unn\u00f6tige Kosten durch hohe Lagerbest\u00e4nde einzelner Materialien verhindert werden.<\/span><\/p>\n

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Development of an AI model based on Machine Learning for early identification of customer needs to avoid OOS-situations<\/p>","protected":false},"author":6,"featured_media":2824,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","_lmt_disableupdate":"","_lmt_disable":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"iawp_total_views":15,"footnotes":""},"categories":[32],"tags":[43,39,26,45,29,31,48,40,95,94,38,27,44,41,50,42,49,46,47,97,96],"class_list":["post-2678","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-use-cases","tag-beratung","tag-big-data","tag-bix","tag-bix-beratung","tag-bix-consulting","tag-bix-sap","tag-consulting","tag-data-science","tag-oos","tag-out-of-stock","tag-ratingen","tag-sap","tag-sap-beratung","tag-sap-bw","tag-sap-consulting","tag-sap-hana","tag-sap-solutions","tag-service","tag-solution","tag-vermeidung-von-out-of-stock","tag-vermeidung-vermeidung-von-oos"],"modified_by":"admin","_links":{"self":[{"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/posts\/2678","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/comments?post=2678"}],"version-history":[{"count":0,"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/posts\/2678\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/media\/2824"}],"wp:attachment":[{"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/media?parent=2678"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/categories?post=2678"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bix-consulting.com\/en\/wp-json\/wp\/v2\/tags?post=2678"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}