{"id":2751,"date":"2015-01-16T11:15:23","date_gmt":"2015-01-16T16:15:23","guid":{"rendered":"https:\/\/demand-planning.com\/?p=2751"},"modified":"2015-01-16T11:15:23","modified_gmt":"2015-01-16T16:15:23","slug":"ibf-webinar-series-alan-milliken-transforming-big-data-into-supply-chain-analytics","status":"publish","type":"post","link":"https:\/\/demand-planning.com\/2015\/01\/16\/ibf-webinar-series-alan-milliken-transforming-big-data-into-supply-chain-analytics\/","title":{"rendered":"IBF Webinar Series – Alan Milliken: Transforming Big Data into Supply Chain Analytics"},"content":{"rendered":"

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

Alan Milliken recently presented an outstanding IBF webinar entitled\u00a0Transforming Big Data into Supply Chain Analytics<\/strong>.<\/p>\n

Alan’s presentation on the use of Big Data was not only informative but extremely insightful.\u00a0 Using practical examples, Alan explained the significance of using descriptive analytics (e.g. reports, KPI’s, dashboards) to report performance, how the use of predictive analytics will improve processes, and the steps needed to become an “analytics practitioner” within the supply chain.<\/p>\n

As a follow up to his IBF Webinar<\/strong><\/a>, Alan was kind enough to address some unanswered questions we were unable to discuss at the conclusion of the presentation.\u00a0 If you would like to receive an email copy of his webinar presentation please feel free to contact us at the IBF at knowledge@ibf.org.<\/p>\n

Q: What is the name of the software you are using to store and query data?<\/strong>
\nA:<\/strong> SAP Business Warehouse; Bex and Office Analysis<\/p>\n

Q: Is it a requirement that you should get specialized software for predictive analysis?<\/strong>
\nA:<\/strong> Absolutely not, Microsoft Excel is fine.<\/p>\n

Q: Regarding forecastability, the ABC\/XYZ attributes, are those<\/strong>
\nattributes tied to specific SKU in the master data. How often<\/strong>
\ndo you “refresh” those attributes?<\/strong>
\nA:<\/strong> YES; update frequency varies with dynamics in the unit. Twice per
\nyear is most frequent.<\/p>\n

Q: Do you recommend using the Customer Requested delivery<\/strong>
\ndate or the shipment date for your Planning KPI Reporting, e.g<\/strong>
\nForecast Accuracy.<\/strong>
\nA:<\/strong> Obviously, request date is best and we use this to measure\u00a0 ‘On
\nTime Delivery’. Whether you go to the effort to adjust data to
\nmeasure forecast accuracy after the fact depends on the frequency
\nof occurrence and the effort required.<\/p>\n

Q: Can analytics be of much help in industries which are highly<\/strong>
\ninfluenced by season and climate, particularly where demand<\/strong>
\nvariation is high and the sales window period is very small?<\/strong>
\nA:<\/strong> Analytics are definitely applicable to businesses like our AgChem
\nunit. However, they tend to be more complex for seasonal
\nproducts. For example, the influence of outside climate and
\nprobability studies are common.<\/p>\n

Q: Can you clarify the forecast accuracy calculation scope? When<\/strong>
\nit says CM +2 lag, is that a 3\u00admonth aggregate or a single month<\/strong>
\nperiod?<\/strong>
\nA:<\/strong> Current month (CM) + 2 months lag means the forecast accuracy
\nfor April is based on what the forecast was in January. If it takes
\n90 days to produce or acquire the product this is the correct lag.<\/p>\n

Q: Do you think Data Mining, when combined with Business<\/strong>
\nintelligence will help in better Demand Predictability for Business?<\/strong>
\nA:<\/strong> It already does. We refer to our front \u00adend tool as Supply Chain
\nIntelligence and we use it to generate forecasting KPI\u2019s and
\ngenerate standard exception reports. It also provides the capability
\nfor custom queries and reports.<\/p>\n

About Alan Milliken:<\/strong><\/em><\/p>\n

Alan is currently a Senior Manager on the Supply Chain Capability Development Team at BASF, the world’s leading chemical company. His prior roles of Manager of Business Process Education in North America and Business Process Consultant, along with his 22 years of experience in Production, Logistics, Process Control, Quality Control, Operator Training, Industrial Engineering and Scheduling\u2026.makes Alan one of the world\u2019s foremost experts. <\/em><\/p>\n

Alan is an IBF Certified Professional Forecaster<\/strong><\/a> (CPF) and has been published in countless publications and books. Alan is also the 2013 recipient of IBF’s Excellence in Business Forecasting & Planning award for his outstanding contributions to the field. AND finally, Alan holds a BS Degree in Industrial Engineering from Auburn University and an MBA in Management from Clemson University.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Alan Milliken recently presented an outstanding IBF webinar entitled\u00a0Transforming Big Data into Supply Chain Analytics. Alan’s presentation on the use of Big Data was not only informative but extremely insightful.\u00a0 Using practical examples, Alan explained the significance of using descriptive analytics (e.g. reports, KPI’s, dashboards) to report performance, how the use of predictive analytics will […]<\/p>\n","protected":false},"author":3689,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[33],"tags":[277,82,271,60,255,61,263,62,275,41,281,64,65,66,162,34,67,39,68,260,69,70,273,35,42,43,44,279,133,36,76,248,48,81,251,236,264,284,37,252,73,74,270,258,38,280],"class_list":{"0":"post-2751","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-forecasting-and-planning","7":"tag-analytics","8":"tag-apics","9":"tag-apo","10":"tag-best-practices","11":"tag-big-data","12":"tag-business-forecasting","13":"tag-certification","14":"tag-collaborative-forecasting","15":"tag-cpf","16":"tag-data-cleansing","17":"tag-data-mining","18":"tag-demand-forecast","19":"tag-demand-forecasting","20":"tag-demand-management","21":"tag-demand-planner","22":"tag-demand-planning","23":"tag-demand-planning-and-forecasting-conference","24":"tag-economic-forecasting","25":"tag-executive-sop","26":"tag-finance","27":"tag-forecast-accuracy","28":"tag-forecast-error","29":"tag-forecast-value-added","30":"tag-forecasting","31":"tag-forecasting-metrics","32":"tag-forecasting-models","33":"tag-forecasting-system","34":"tag-fundamentals","35":"tag-fva","36":"tag-ibf","37":"tag-ibp","38":"tag-innovation","39":"tag-institute-of-business-forecasting-and-planning","40":"tag-inventory-management","41":"tag-marketing","42":"tag-metrics","43":"tag-new-products","44":"tag-predictive-analytics","45":"tag-sop","46":"tag-sales","47":"tag-sales-operations-planning","48":"tag-sales-forecasting","49":"tag-sap","50":"tag-siop","51":"tag-supply-chain","52":"tag-training"},"_links":{"self":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/2751"}],"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\/3689"}],"replies":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/comments?post=2751"}],"version-history":[{"count":0,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/2751\/revisions"}],"wp:attachment":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/media?parent=2751"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/categories?post=2751"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/tags?post=2751"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}