{"id":19941,"date":"2022-06-10T10:00:35","date_gmt":"2022-06-10T09:00:35","guid":{"rendered":"https:\/\/www.argonandco.com\/?post_type=article&#038;p=19941"},"modified":"2022-05-30T13:59:40","modified_gmt":"2022-05-30T12:59:40","slug":"calculate-your-own-customer-centric-on-time-delivery-performance-using-transactional-order-lines","status":"publish","type":"article","link":"https:\/\/www.argonandco.com\/en\/news-insights\/articles\/calculate-your-own-customer-centric-on-time-delivery-performance-using-transactional-order-lines\/","title":{"rendered":"Calculate your own customer centric On-time delivery performance using transactional order lines"},"content":{"rendered":"<h2>The Main Metric<\/h2>\n<p>On-time delivery (OTD) is the main metric to measure the efficiency of supply chain processes in your organization.\u00a0 It is an indicator of how capable your organization is to meet customer demand in terms of the requested delivery date (RDD). <span data-contrast=\"none\">Many businesses create a monthly aggregated average of OTD that gives a false sense of security on how well their supply chain is genuinely performing in the eyes of the customer.<\/span> Failing to meet your customers\u2019 requests can lead to all sorts of negative outcomes. Worst case? You lose your customers to competitors.<\/p>\n<p><span data-contrast=\"none\">In fact, throughout our daily work, we experience a vast array of different interpretations and calculations of the on-time delivery\u202fmetric. This indicates that customer-centric Outside-In&#x2122; thinking is not at the heart of every organisation. Over recent years we have made the following observations regarding the measurement of On-time delivery:<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0a7\" data-font=\"Wingdings\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Wingdings&quot;,&quot;469769242&quot;:[9642],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0a7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"none\">OTD is simply measured as a ratio of the number of units delivered On-time divided by the number of total units shipped on a monthly base<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0a7\" data-font=\"Wingdings\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Wingdings&quot;,&quot;469769242&quot;:[9642],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0a7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"none\">It is often not clear how the number of units On-time is calculated, e.g. what exactly is On-time<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li data-leveltext=\"\uf0a7\" data-font=\"Wingdings\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Wingdings&quot;,&quot;469769242&quot;:[9642],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0a7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"none\">OTD calculation reference points are unclear, e.g. are they based on the requested delivery date (RDD), first confirmation date or last confirmation date?<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0a7\" data-font=\"Wingdings\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Wingdings&quot;,&quot;469769242&quot;:[9642],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0a7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"none\">The shipment dates are used for actual delivery date (ADD), not the delivery arrival date at the customer\u2019s premises (ADD_C)<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0a7\" data-font=\"Wingdings\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Wingdings&quot;,&quot;469769242&quot;:[9642],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0a7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"none\">Early deliveries without customer approval (e.g. month end pressure) are defined as delivered on time, although they are not!<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0a7\" data-font=\"Wingdings\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Wingdings&quot;,&quot;469769242&quot;:[9642],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0a7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"none\">OTD is regularly calculated at an order level, not at a detailed order line level<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0a7\" data-font=\"Wingdings\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Wingdings&quot;,&quot;469769242&quot;:[9642],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0a7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"none\">There is confusion about delivery windows at customer premises<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"none\">All those observations are symptoms of a distorted view of On-time delivery\u202fas the metric of your supply chain performance. Frequently, we see surprised looks when we present OTD results at a transactional level that are not anywhere near the 90% On-time performance that was expected by the management.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h2><b><span data-contrast=\"none\">Try to calculate your On-time (OTD) Baseline performance, using transactional order line data:<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"none\">In order to get a clear understanding of your current On-time (OTD) delivery performance that your customers are truly experiencing, you need the shipping date (ADD) and the customer wish date (RDD) for every order position shipped in the time frame you are observing.\u00a0 Let us now build your OTD baseline performance:<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<ol>\n<li><span data-contrast=\"none\">Choose a time frame of, ideally, 365 days<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"none\">Define OTD as the difference between shipping date (ADD) and the <\/span><b><span data-contrast=\"none\">original<\/span><\/b><span data-contrast=\"none\"> customer wish date (RDD) for every order line in the time frame<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"none\">If you have the goods arrival date (ADD_C) at the customers premises use this instead<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"none\">Calculate your 95<\/span><span data-contrast=\"none\">th<\/span><span data-contrast=\"none\"> and your 5<\/span><span data-contrast=\"none\">th<\/span><span data-contrast=\"none\"> percentiles of this distribution or show it graphically on a Probability Plot<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"none\">Add up the absolute returned days of the percentiles to your On-time delivery (OTD) this is your <\/span><span data-contrast=\"none\">Outside-In&#x2122; <\/span><span data-contrast=\"none\">SPAN Metric<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<\/ol>\n<p><span data-contrast=\"none\">So, tell me, what are your percentages of order lines that are exactly on-time?\u00a0 How many are late and how many are early? What is your SPAN metric and what does it tell you? What might be possible root causes for your baseline performance and <\/span><span data-contrast=\"none\">the<\/span><span data-contrast=\"none\"> SPAN you calculated? What would you do to reduce the SPAN?<\/span><\/p>\n<p><span class=\"NormalTextRun SCXW166801228 BCX0\">You are invited to connect with me and share your <\/span><span class=\"NormalTextRun SCXW166801228 BCX0\">thoughts<\/span><span class=\"NormalTextRun SCXW166801228 BCX0\">, experience<\/span><span class=\"NormalTextRun SCXW166801228 BCX0\"> and comments.<\/span><\/p>\n","protected":false},"featured_media":19948,"template":"","categories":[1],"region":[256],"class_list":["post-19941","article","type-article","status-publish","has-post-thumbnail","hentry","category-uncategorised"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Calculate your own customer centric On-time delivery performance using transactional order lines - Argon &amp; Co<\/title>\n<meta name=\"description\" content=\"Many businesses create a monthly aggregated average of OTD that gives a false sense of security on how well their supply chain is genuinely performing in the eyes of the customer. 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