{"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:\/\/teststage.bix-consulting.com\/en\/vermeidung-von-out-of-stock-situationen\/","title":{"rendered":"Avoidance of out-of-stock situations"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8220;1&#8243; disabled_on=&#8220;on|on|on&#8220; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;||0px||false|false&#8220; disabled=&#8220;on&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_row use_custom_gutter=&#8220;on&#8220; gutter_width=&#8220;2&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; background_color=&#8220;#F4F4F4&#8243; border_radii=&#8220;off|20px|20px||&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_column type=&#8220;4_4&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_text _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;|20px||20px|false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;]<\/p>\n<h4>Challenge<\/h4>\n<p style=\"text-align: justify;\">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<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;0px||0px||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_column type=&#8220;4_4&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_post_title title=&#8220;off&#8220; meta=&#8220;off&#8220; force_fullwidth=&#8220;off&#8220; image_width=&#8220;60%&#8220; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; background_color=&#8220;#F4F4F4&#8243; custom_margin=&#8220;||||false|false&#8220; custom_padding=&#8220;||||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][\/et_pb_post_title][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;0px||||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_column type=&#8220;4_4&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_text _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; background_color=&#8220;#F4F4F4&#8243; custom_padding=&#8220;20px|20px|20px|20px|false|false&#8220; border_radii=&#8220;off|||20px|20px&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;]<\/p>\n<h4>The approach<\/h4>\n<p style=\"text-align: justify;\">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<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8220;1&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_margin=&#8220;||||false|false&#8220; custom_padding=&#8220;0px||||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_row use_custom_gutter=&#8220;on&#8220; gutter_width=&#8220;2&#8243; make_equal=&#8220;on&#8220; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; background_color=&#8220;#F4F4F4&#8243; border_radii=&#8220;on|20px|20px|20px|20px&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_column type=&#8220;4_4&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_text _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;|20px||20px|false|false&#8220; hover_enabled=&#8220;0&#8243; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220; sticky_enabled=&#8220;0&#8243;]<\/p>\n<h4>Challenge<\/h4>\n<p style=\"text-align: justify;\"><span>Unexpected customer demands lead to supply shortages, as the existing stocks have not been optimally distributed among the various warehouses. This usually happens because previous manually performed analyses on a calculated range of individual materials have reached their quantitative limit so that unexpected fluctuations cannot be taken into account.<\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8220;1&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_margin=&#8220;||||false|false&#8220; custom_padding=&#8220;0px||0px||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_row _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;||0px||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_column type=&#8220;4_4&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_post_title title=&#8220;off&#8220; meta=&#8220;off&#8220; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; border_radii=&#8220;on|20px|20px|20px|20px&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][\/et_pb_post_title][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8220;1&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_margin=&#8220;||||false|false&#8220; custom_padding=&#8220;||0px||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_row _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;0px||0px||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_column type=&#8220;4_4&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_text _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; background_color=&#8220;RGBA(255,255,255,0)&#8220; custom_padding=&#8220;20px|20px|20px|20px|false|false&#8220; hover_enabled=&#8220;0&#8243; border_radii=&#8220;off|||20px|20px&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220; sticky_enabled=&#8220;0&#8243;]<\/p>\n<h4>The approach<\/h4>\n<p style=\"text-align: justify;\">With the help of machine learning, a model of customer requirements is created based on historical data. In this way, simulations that optimize the entire inventory system by redistributing the existing stocks in such a way that both OOS situations and overstocks can be avoided. By using exception reporting, situations can be automatically identified that require manual intervention. In addition, all required information and possible solution options can be provided by these reports.<\/p>\n<p style=\"text-align: justify;\">By using the biX AI Tools, the solution approach can be fully integrated into your SAP system.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8220;1&#8243; _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;||0px||false|false&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_row _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; background_color=&#8220;#F4F4F4&#8243; border_radii=&#8220;on|20px|20px|20px|20px&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_column type=&#8220;4_4&#8243; _builder_version=&#8220;4.16&#8243; _module_preset=&#8220;default&#8220; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220;][et_pb_text _builder_version=&#8220;4.21.0&#8243; _module_preset=&#8220;default&#8220; custom_padding=&#8220;|20px||20px|false|false&#8220; hover_enabled=&#8220;0&#8243; global_colors_info=&#8220;{}&#8220; theme_builder_area=&#8220;et_body_layout&#8220; sticky_enabled=&#8220;0&#8243;]<\/p>\n<h4>Your benefit<\/h4>\n<p style=\"text-align: justify;\"><span>Due to the optimal distribution of the existing stocks among the various warehouses, additional sales can be realized. At the same time unnecessary costs can be prevented by high stocks of individual materials.<\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>","protected":false},"excerpt":{"rendered":"<p>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":"","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],"modified_by":"admin","_links":{"self":[{"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/posts\/2678"}],"collection":[{"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/comments?post=2678"}],"version-history":[{"count":0,"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/posts\/2678\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/media\/2824"}],"wp:attachment":[{"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/media?parent=2678"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/categories?post=2678"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/teststage.bix-consulting.com\/en\/wp-json\/wp\/v2\/tags?post=2678"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}