{"id":39324,"date":"2022-01-27T15:38:58","date_gmt":"2022-01-27T15:38:58","guid":{"rendered":"https:\/\/staging.consileon.de\/maschinelles-lernen-im-handel-heute-und-morgen\/"},"modified":"2022-03-25T13:03:43","modified_gmt":"2022-03-25T13:03:43","slug":"machine-learning-in-trade-today-and-tomorrow","status":"publish","type":"post","link":"https:\/\/prelive.consileon.de\/en\/blog\/2022\/01\/27\/machine-learning-in-trade-today-and-tomorrow\/","title":{"rendered":"Machine learning in retail: today and tomorrow"},"content":{"rendered":"\n<p>How many mixed rye breads should a bakery chain bake next Monday? Ideally, every customer gets the bread of their choice without a loaf left over. Many factors go into the calculation, including sales the previous week, whether next Monday is a vacation, or whether the bread is currently being advertised. Translating them into input values for a computer program, it can calculate demand in several ways, for example:<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" id=\"h-weight-the-factors-and-add-up\"><strong>Weight the factors and add up<\/strong><\/h5>\n\n\n\n<ul class=\"wp-block-list\"><li>Initial value: sales last Monday<\/li><li>if vacations, then minus 10 loaves<\/li><li>if advertising, then plus 20 loaves<\/li><li>1., 2., 3. \u2026<\/li><\/ul>\n\n\n\n<h5 class=\"wp-block-heading\" id=\"h-consider-all-cases-individually\"><strong>Consider all cases individually<\/strong><\/h5>\n\n\n\n<ul class=\"wp-block-list\"><li>1st method: Weight the factors and sum them up.<\/li><li>2nd method: Consider all cases individually<\/li><li>if vacations and advertising, then plus 7 loaves of bread<\/li><li>1., 2., 3., \u2026<\/li><\/ul>\n\n\n\n<p>The prediction becomes more accurate the more data is included, e.g. also the Monday rye mixed bread sales curve of the last years. The program learns from such data &#8211; hence the term <a href=\"https:\/\/en.wikipedia.org\/wiki\/Machine_learning\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>machine learning (ML).<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>End-to-end digitization requires machine learning. Research, technology and practical experience now make it possible. Learn more in this article.<\/p>\n","protected":false},"author":58,"featured_media":37238,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"image","meta":{"_acf_changed":false,"footnotes":""},"categories":[15,88,76],"tags":[],"class_list":["post-39324","post","type-post","status-publish","format-image","has-post-thumbnail","hentry","category-news","category-publications-en","category-software-development-en","post_format-post-format-image"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.5 (Yoast SEO v24.5) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Machine learning in retail | IT &amp; Management Consulting | Consileon<\/title>\n<meta name=\"description\" content=\"&quot;End-to-end digitization requires machine learning. Research, technology and practical experience now make it possible.&quot;\" \/>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Machine learning in retail: today and tomorrow\" \/>\n<meta property=\"og:description\" content=\"&quot;End-to-end digitization requires machine learning. 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