{"id":5186,"date":"2020-05-01T16:54:06","date_gmt":"2020-05-01T20:54:06","guid":{"rendered":"https:\/\/smartcorp.com\/planning_for_intermittent_demand_spare_parts-copy\/"},"modified":"2021-01-05T14:21:56","modified_gmt":"2021-01-05T18:21:56","slug":"planning-forecasting-inventaris-intermitterende-vraag","status":"publish","type":"page","link":"https:\/\/smartcorp.com\/nl\/planning-forecasting-inventory-intermittent-demand\/","title":{"rendered":"Planning voor intermitterende vraag"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;4.7.4&#8243; custom_margin=&#8221;||0px||false|false&#8221; custom_padding=&#8221;19px||22px||false|false&#8221;][et_pb_row admin_label=&#8221;row&#8221; _builder_version=&#8221;3.25&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.0.47&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.7.4&#8243; header_font=&#8221;Open Sans|700|||||||&#8221; header_font_size=&#8221;22px&#8221; header_2_font=&#8221;Open Sans|600|||||||&#8221; header_2_font_size=&#8221;19px&#8221; header_2_line_height=&#8221;1.5em&#8221; header_3_font=&#8221;Open Sans||||||||&#8221; header_3_font_size=&#8221;16px&#8221; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; hover_enabled=&#8221;0&#8243; z_index_tablet=&#8221;500&#8243; text_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; text_text_shadow_vertical_length_tablet=&#8221;0px&#8221; text_text_shadow_blur_strength_tablet=&#8221;1px&#8221; link_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; link_text_shadow_vertical_length_tablet=&#8221;0px&#8221; link_text_shadow_blur_strength_tablet=&#8221;1px&#8221; ul_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; ul_text_shadow_vertical_length_tablet=&#8221;0px&#8221; ul_text_shadow_blur_strength_tablet=&#8221;1px&#8221; ol_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; ol_text_shadow_vertical_length_tablet=&#8221;0px&#8221; ol_text_shadow_blur_strength_tablet=&#8221;1px&#8221; quote_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; quote_text_shadow_vertical_length_tablet=&#8221;0px&#8221; quote_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_2_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_2_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_2_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_3_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_3_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_3_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_4_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_4_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_4_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_5_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_5_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_5_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_6_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_6_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_6_text_shadow_blur_strength_tablet=&#8221;1px&#8221; box_shadow_horizontal_tablet=&#8221;0px&#8221; box_shadow_vertical_tablet=&#8221;0px&#8221; box_shadow_blur_tablet=&#8221;40px&#8221; box_shadow_spread_tablet=&#8221;0px&#8221; use_border_color=&#8221;off&#8221; header_line_height=&#8221;1.5em&#8221; header_3_line_height=&#8221;1.4em&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<h1>Demand planning and forecasting for Intermittent Demand: Optimizing Inventory Using Probabilistic Modeling<\/h1>\n<h3>How do you plan the right inventory levels when you have intermittent demand, the seemingly random, highly sporadic usage pattern that is especially prevalent with spare parts?<\/h3>\n<div align=\"justify\">Most parts and materials planning organizations rely on traditional forecasting approaches, rule of thumb methods, and \u201cplanned\u201d maintenance schedules to determine stocking requirements. This Video will discuss these approaches, why they often fail, and how new probabilistic forecasting methods can make a big difference to your bottom line.<\/div>\n<p>[\/et_pb_text][et_pb_code _builder_version=&#8221;4.7.4&#8243; background_color=&#8221;#ffffff&#8221; z_index_tablet=&#8221;500&#8243; saved_tabs=&#8221;all&#8221;]<iframe class=\"embeddedObject shadow resizable\" name=\"embedded_content\" scrolling=\"no\" frameborder=\"0\" type=\"text\/html\" <!-- [et_pb_line_break_holder] -->        style=&#8221;overflow:hidden;&#8221; src=&#8221;https:\/\/www.screencast.com\/users\/greg.hartunian\/folders\/Default\/media\/5a04b225-89f5-4d45-8eb4-a06fbe329866\/embed&#8221; height=&#8221;607&#8243; width=&#8221;1280&#8243; webkitallowfullscreen mozallowfullscreen allowfullscreen><\/iframe>[\/et_pb_code][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;4.7.4&#8243; background_color=&#8221;#efefef&#8221; custom_padding=&#8221;22px||22px||false|false&#8221;][et_pb_row admin_label=&#8221;row&#8221; _builder_version=&#8221;3.25&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.0.47&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;3.27.4&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; z_index_tablet=&#8221;500&#8243; text_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; text_text_shadow_vertical_length_tablet=&#8221;0px&#8221; text_text_shadow_blur_strength_tablet=&#8221;1px&#8221; link_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; link_text_shadow_vertical_length_tablet=&#8221;0px&#8221; link_text_shadow_blur_strength_tablet=&#8221;1px&#8221; ul_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; ul_text_shadow_vertical_length_tablet=&#8221;0px&#8221; ul_text_shadow_blur_strength_tablet=&#8221;1px&#8221; ol_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; ol_text_shadow_vertical_length_tablet=&#8221;0px&#8221; ol_text_shadow_blur_strength_tablet=&#8221;1px&#8221; quote_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; quote_text_shadow_vertical_length_tablet=&#8221;0px&#8221; quote_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_2_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_2_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_2_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_3_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_3_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_3_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_4_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_4_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_4_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_5_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_5_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_5_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_6_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_6_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_6_text_shadow_blur_strength_tablet=&#8221;1px&#8221; box_shadow_horizontal_tablet=&#8221;0px&#8221; box_shadow_vertical_tablet=&#8221;0px&#8221; box_shadow_blur_tablet=&#8221;40px&#8221; box_shadow_spread_tablet=&#8221;0px&#8221; use_border_color=&#8221;off&#8221;]<\/p>\n<h2>Probabilistic forecasting: A fundamental aspect of supply chain management is accurate demand forecasting.<\/h2>\n<p>We address the problem of forecasting intermittent (or irregular) demand, i.e. random demand with a large proportion of zero values. This pattern is characteristic of demand for service parts inventories and capital goods and is difficult to predict. We forecast the cumulative distribution of demand over a fixed lead time using a new type of time series bootstrap. To assess accuracy in forecasting an entire distribution, we adapt the probability integral transformation to intermittent demand. Using nine large industrial datasets, we show that the bootstrapping method produces more accurate forecasts of the distribution of demand over a fixed lead time than do exponential smoothing and Croston\u2019s method.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; custom_padding_last_edited=&#8221;on|desktop&#8221; admin_label=&#8221;section&#8221; module_id=&#8221;contact&#8221; _builder_version=&#8221;3.22&#8243; background_color=&#8221;#444444&#8243; custom_padding_tablet=&#8221;50px|0|50px|0&#8243; custom_padding_phone=&#8221;&#8221; transparent_background=&#8221;off&#8221; padding_mobile=&#8221;off&#8221; make_fullwidth=&#8221;off&#8221; use_custom_width=&#8221;off&#8221; width_unit=&#8221;on&#8221; locked=&#8221;off&#8221;][et_pb_row admin_label=&#8221;row&#8221; _builder_version=&#8221;4.5.1&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_margin=&#8221;0px||0px||false|false&#8221; custom_padding=&#8221;0px||0px||false|false&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.0.47&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; text_orientation=&#8221;center&#8221; background_layout=&#8221;dark&#8221; module_alignment=&#8221;center&#8221; custom_margin=&#8221;0px||0px||false|false&#8221; custom_padding=&#8221;0px||0px||false|false&#8221; use_border_color=&#8221;off&#8221;]<\/p>\n<h5 class=\"as-h1s\">Contact Us Today for More Information<\/h5>\n<p>If you request a demo, one of our specialists will show you how Smart can help, using your own inventory data!<\/p>\n<p>[\/et_pb_text][et_pb_text admin_label=&#8221;Horizontal Demo Form div&#8221; _builder_version=&#8221;4.6.3&#8243; 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style=\"height:1px;\">\n\t<p>&nbsp;\n\t<\/p>\n<\/div>\n<div class=\"smartdemoform\">\n\t<p style=\"text-align: center;\"><br \/>\n<input class=\"wpcf7-form-control wpcf7-submit has-spinner\" type=\"submit\" value=\"Submit\" \/>\n\t<\/p>\n<\/div>\n<div class=\"smartdemoform\">\n<div class=\"wpcf7-response-output\" aria-hidden=\"true\"><\/div>\n<\/div>\n<div style=\"clear: both;\">\n<\/div>\n<p><script>\ndocument.addEventListener( 'wpcf7mailsent', function( event ) {\n location = 'https:\/\/smartcorp.com\/thank_you_business\/';\n}, false );\n<\/script>\n<\/p><p style=\"display: none !important;\" class=\"akismet-fields-container\" data-prefix=\"_wpcf7_ak_\"><label>&#916;<textarea name=\"_wpcf7_ak_hp_textarea\" cols=\"45\" rows=\"8\" maxlength=\"100\"><\/textarea><\/label><input type=\"hidden\" id=\"ak_js_1\" name=\"_wpcf7_ak_js\" value=\"43\"\/><script>document.getElementById( \"ak_js_1\" ).setAttribute( \"value\", ( new Date() ).getTime() );<\/script><\/p>\n<\/form>\n<\/div>\n\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Vraagplanning en prognoses voor intermitterende vraag. Nieuwe probabilistische prognosemethoden kunnen een groot verschil maken bij het optimaliseren van de voorraad: <\/p>","protected":false},"author":34,"featured_media":5172,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"<p>We are often asked what the difference is between these two important performance metrics. While they are both important for measuring how successful a business is in meeting demand, their meaning is very different. \u00a0If not understood and incorporated into the strategic inventory planning process, inventory will be inefficiently allocated resulting in lower\u00a0customer service and higher carrying costs.\u00a0\u00a0We've illustrated the difference in this 4 minute recording using Microsoft Excel.<\/p><p>[video width=\"1280\" height=\"682\" mp4=\"https:\/\/smartcorp.com\/wp-content\/uploads\/2016\/09\/Service-Level-vs-Fill-Rate.mp4\"][\/video]<\/p><p>Smart Operational Analytics automatically calculate historical service levels & fill rates across any item.\u00a0 Summary reports provide overall and item specific performance with comparisons to historical inventory values.\u00a0\u00a0<\/p><p>\u00a0<\/p>","_et_gb_content_width":"","content-type":"","footnotes":""},"class_list":["post-5186","page","type-page","status-publish","has-post-thumbnail","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Demand planning and forecasting for Intermittent Demand.<\/title>\n<meta name=\"description\" content=\"Demand planning and forecasting for Intermittent Demand. 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