{"id":2572,"date":"2014-10-22T19:27:32","date_gmt":"2014-10-22T23:27:32","guid":{"rendered":"https:\/\/demand-planning.com\/?p=2572"},"modified":"2014-10-22T19:27:32","modified_gmt":"2014-10-22T23:27:32","slug":"safety-stock-forecasting-and-sop","status":"publish","type":"post","link":"https:\/\/demand-planning.com\/2014\/10\/22\/safety-stock-forecasting-and-sop\/","title":{"rendered":"Safety Stock, Forecasting, and S&OP"},"content":{"rendered":"

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

Most practitioners of Sales & Operations Planning<\/strong><\/a> would agree that the focus of an S&OP Process should be on the mid-to-long range horizon, and typically at a volume\/aggregate level.\u00a0 However, I am often surprised when some of these same practitioners indicate that backward-looking Demand planning KPIs like Forecast Accuracy and Forecast Bias, as well as safety-stock concepts and tools, have no place in a discussion of S&OP.\u00a0 To the contrary, I would argue that they should be front and center!<\/p>\n

Those of us who have worked as Demand Planners<\/strong><\/a>, or have overseen the function, are familiar with the saying that there is only one thing that we can say about our demand plans with 100% accuracy: \u201cThey are wrong.\u201d This is true, but it is the degree of incorrectness that is important to understand.\u00a0 When we review Product Category plans during the Demand Agreement Process, it is helpful to understand what our bias has historically been.\u00a0 Even where we are fortunate enough to show a history of bias in both directions, it is worth knowing how \u201cclose to the pin\u201d we are typically able to operate.\u00a0 This allows us to appropriately guide leadership on the confidence level and margin of error behind our estimates.\u00a0 This becomes even more critical within the Supply Agreement Process where decisions about capacity utilization, and in some cases regarding the expansion or idling of capital assets, are made.\u00a0 Without an understanding of historical bias and its drivers, we may be led astray or worse yet lead others to make bad decisions.<\/p>\n

Given this context, some skeptics come around to the usefulness of a \u201crear view\u00a0mirror\u201d KPI such as Forecast<\/strong><\/a> Bias playing a role in our typically forward-looking S&OP Process<\/strong><\/a>.\u00a0 Forecast Accuracy, especially at a SKU level, may be a more difficult KPI to \u201csell.\u201d\u00a0 It should not be.\u00a0 Better management of working capital and an improved ability to forecast cash flow are almost always cited among the objectives of a S&OP Process.\u00a0 As we look at our working capital, across most industries and companies we will see our inventory fall into five buckets: Safety Stock, Cycle Stock, Decoupling Stock, Anticipation Inventory, and Pipeline Inventory.\u00a0 While the magnitude of that first bucket, Safety Stock, may vary in magnitude relative to the other buckets and company-to-company, it is nearly always significant both in its working capital impact as well as its ability to smooth our operations and deliver customer satisfaction.\u00a0 In most companies safety-stock exists primarily to buffer a specific type of variability, and that is either variability in demand or, more often than not, variability between forecast and actual demand.\u00a0 Therein lies the importance of understanding Forecast Accuracy when working towards a best-in-class S&OP Process.<\/p>\n

Having established the relevance of our Demand Planning<\/strong><\/a> KPIs, and having recognized the importance of safety-stock in achieving S&OP\u2019s working capital objectives, we can now turn our attention to understanding what a robust Safety-Stock Planning Program should look like.\u00a0 Based on more than a decade of experience across three industries and three continents, as well as extensive benchmarking<\/strong><\/a>, I feel it is fair to say that there is no single solution to the challenge of establishing and periodically reviewing safety-stock levels.\u00a0 Instead, it is much more important to match organizational strengths and capabilities to an appropriate method.\u00a0 The much maligned \u201ctribal knowledge\u201d approach to safety-stock can actually be remarkably effective in an organization with tenured staff and a mature product portfolio.\u00a0 Sophisticated IT tools that apply statistical methods to establish safety-stocks at the appropriate nodes in a multi-echelon network can deliver amazing results for a company with the\u00a0skill set, systems, human resources, and data\u00a0availability to design and feed such a tool.\u00a0 Other methods including ABC-aligned safety-stocks, service-adjusted safety-stock, review of working capital employed, or simple statistical safety-stock all have applications.\u00a0 The know-how to choose the proper methods for a given organization, at a given point in time, is a skill that any practitioner of S&OP can benefit from!<\/p>\n

Erik C. Hjerpe<\/strong>
\n Senior Director of Supply Chain<\/strong>
\n TreeHouse Foods<\/strong><\/p>\n

Erik Hjerpe recently presented at the 2014 Best Practices Conference at Disney’s Yacht & Beach Club Resort<\/a>.<\/strong>\u00a0 Erik is Director of Supply Chain at TreeHouse Foods, a Chicago-based organization providing quality food products primarily for the private label and food-service industries. He has over 10 years of global experience across multiple industries managing facets of the supply chain, including sales and operations planning, demand planning, scheduling, logistics and warehousing, customs compliance, lean operations design, and ERP implementation.<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Most practitioners of Sales & Operations Planning would agree that the focus of an S&OP Process should be on the mid-to-long range horizon, and typically at a volume\/aggregate level.\u00a0 However, I am often surprised when some of these same practitioners indicate that backward-looking Demand planning KPIs like Forecast Accuracy and Forecast Bias, as well as […]<\/p>\n","protected":false},"author":3828,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[33],"tags":[277,82,271,60,255,61,263,62,275,41,281,64,65,66,162,34,67,39,68,260,69,70,273,35,42,43,44,279,36,76,248,48,81,251,236,264,284,37,252,73,74,270,258,38,280],"class_list":{"0":"post-2572","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-ibf","36":"tag-ibp","37":"tag-innovation","38":"tag-institute-of-business-forecasting-and-planning","39":"tag-inventory-management","40":"tag-marketing","41":"tag-metrics","42":"tag-new-products","43":"tag-predictive-analytics","44":"tag-sop","45":"tag-sales","46":"tag-sales-operations-planning","47":"tag-sales-forecasting","48":"tag-sap","49":"tag-siop","50":"tag-supply-chain","51":"tag-training"},"_links":{"self":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/2572"}],"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\/3828"}],"replies":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/comments?post=2572"}],"version-history":[{"count":0,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/2572\/revisions"}],"wp:attachment":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/media?parent=2572"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/categories?post=2572"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/tags?post=2572"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}