{"id":765,"date":"2010-04-07T08:18:44","date_gmt":"2010-04-07T15:18:44","guid":{"rendered":"https:\/\/demand-planning.com\/?p=765"},"modified":"2010-04-07T08:18:44","modified_gmt":"2010-04-07T15:18:44","slug":"the-cost-of-being-right-at-yokohama-tire-and-improving-forecasting-accuracy","status":"publish","type":"post","link":"https:\/\/demand-planning.com\/2010\/04\/07\/the-cost-of-being-right-at-yokohama-tire-and-improving-forecasting-accuracy\/","title":{"rendered":"Yokohama Tire Canada: Forecast Accuracy and the Cost of Being Right"},"content":{"rendered":"
\"\"<\/a>

Jonathon Karelse <\/p><\/div>\n

Demand planning and forecasting is a process which, because of its intrinsic focus on \u201cerror\u201d, too often invites misguided efforts at producing perfection.\u00a0 Like the alchemists\u2019 quest for gold, the goal is illusory and may cost more than any benefit it yields.\u00a0 Consider that the result of demand planning is only profitable to the extent that it is actionable \u2013 that is, if links above or below in the participant\u2019s supply chain are unable to respond to the data, it might be a purely academic exercise.\u00a0 Consider further that if the participant\u2019s supply is already near-optimal, the benefit of any marginal incremental gains might be offset by the disproportionate effort required to effect those gains.<\/p>\n

The idea of diminishing marginal returns is one which is easily understood as a concept, but too many forecasting and planning practitioners are anathema to their raison d\u2019etre<\/em> within an organization.\u00a0 And the mandate for forecasting perfection is often created by senior management; the very group who should be most aware of the cost\/benefit of their organization\u2019s activities.\u00a0 Any case for imperfect forecasting, therefore, must ultimately be underpinned by an incremental benefit.<\/p>\n

The process that we undertook at Yokohama Tire (Canada) was as follows:<\/p>\n

    \n
  1. Clearly identify the problem<\/strong> and demarcate the extent to which its resolution is actionable.<\/li>\n
  2. Estimate the cost\/benefit of its resolution<\/strong> and clearly apply a financial metric.<\/li>\n
  3. Evaluate judgment inputs as a means to that end.<\/strong> By making use of existing business intelligence and ability which may not have been leveraged fully in the process, we precluded the need for additional investment in software, consultants or headcount.<\/li>\n<\/ol>\n

    During my upcoming presentation session at IBF’s San Francisco event at the end of April 2010, I will share the means by which we addressed each step of this process and, I hope, allow participants to learn from and avoid some of the mistakes we made along the way.<\/p>\n

    Of course, we would enjoy hearing your lessons learned on improving forecasting accuracy here.\u00a0 Looking forward to continuing a dialogue.<\/p>\n

    Jonathon Karelse
    \nNational Marketing Manager
    \n    Yokohama Tire<\/a><\/p>\n

    <\/a>See JONATHON KARELSE from YOKOHAMA TIRE Speak in San Francisco at IBF’s:<\/a><\/strong><\/p>\n

    \"\"<\/a><\/p>\n

    $895 USD for Conference Only!<\/strong><\/a><\/p>\n

    April 28-30, 2010 (3 Days)
    \nSan Francisco, California USA<\/strong><\/a><\/p>\n

    <\/p>\n

    <\/p>\n

    <\/p>\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

    Demand planning and forecasting is a process which, because of its intrinsic focus on \u201cerror\u201d, too often invites misguided efforts at producing perfection.\u00a0 Like the alchemists\u2019 quest for gold, the goal is illusory and may cost more than any benefit it yields.\u00a0 Consider that the result of demand planning is only profitable to the extent […]<\/p>\n","protected":false},"author":149,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[33],"tags":[65,66,34,35,140,141,36,37,74,38,142],"class_list":{"0":"post-765","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-forecasting-and-planning","7":"tag-demand-forecasting","8":"tag-demand-management","9":"tag-demand-planning","10":"tag-forecasting","11":"tag-forecasting-accuracy","12":"tag-forecasting-error","13":"tag-ibf","14":"tag-sop","15":"tag-sales-forecasting","16":"tag-supply-chain","17":"tag-yokohama-tire"},"_links":{"self":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/765"}],"collection":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/users\/149"}],"replies":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/comments?post=765"}],"version-history":[{"count":0,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/765\/revisions"}],"wp:attachment":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/media?parent=765"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/categories?post=765"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/tags?post=765"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}