{"id":587,"date":"2009-12-29T10:45:38","date_gmt":"2009-12-29T17:45:38","guid":{"rendered":"https:\/\/demand-planning.com\/?p=587"},"modified":"2009-12-29T10:45:38","modified_gmt":"2009-12-29T17:45:38","slug":"building-demand-forecasting-models-for-atm-machines-the-time-value-of-money-risk","status":"publish","type":"post","link":"https:\/\/demand-planning.com\/2009\/12\/29\/building-demand-forecasting-models-for-atm-machines-the-time-value-of-money-risk\/","title":{"rendered":"Building Demand Forecasting Models for ATM Machines & the Time Value of Money Risk"},"content":{"rendered":"
\"\"<\/a>

Mark Frost<\/p><\/div>\n

\"\"<\/a>

D. Reilly<\/p><\/div>\n

The \u201ctime value of money\u201d is at stake when you are trying to forecast demand at ATM machines and of course, customer satisfaction. Trying to get the right amount of cash for pay day and holidays requires some pretty complicated models to get this right.\u00a0 The reality is that these methods and approaches of forecasting daily cash demand are just as necessary when forecasting what is perceived to be \u201csimpler\u201d problems.\u00a0 The S&OP process has treated the importance of a baseline forecast as just a \u201cstepping stone\u201d.\u00a0 A big reason why the S&OP process is leaned on so heavily is baseline forecasts are often generated using a simplistic model that doesn\u2019t capture patterns into a model, but rather fits a pre-specified model to the data.\u00a0 A quality baseline model and forecast can alleviate a lot of the work downstream. Another comment about adjusting forecasts is that if it is for a reoccurring reason it can be added as a causal variable to the model and utilized \u201cin-line\u201d or also \u201cin-model\u201d.<\/p>\n

When building a forecasting model, it\u2019s important to recognize how variables like \u201cday of the week\u201d, \u201cweek of the year\u201d, \u201cday of the month\u201d,\u00a0 and holidays can capture the swings in demand and allow you to plan for them.\u00a0 It\u2019s not just the holidays, but the days before and after the holidays that need special consideration as demand ebbs and flows around these events.<\/p>\n

Furthermore, we often hear \u201cI am fed up with fixing forecasts\u201d.\u00a0 This can be alleviated by taking a more rigorous approach to identifying patterns rather than have some list of 50 models to be forced onto a data-set \u201choping for the best\u201d without any care for what patterns are occurring in the data.\u00a0 The \u201cone size fits all\u201d modeling approach by taking 50 models and forcing them on a data-set is like fitting a square peg in a round hold.\u00a0 Customized suits are exactly that.\u00a0 Custom suits are yes custom and they take a little work requiring the expense of a tailor, but you have a proper fitting product at the end of the process. \u201cOne size fits all\u201d can result in a hat that just doesn\u2019t fit your head as we have seen!<\/p>\n

Join us at IBF\u2019s Supply Chain Forecasting & Planning Conference in Phoenix<\/a> to further discuss the above.\u00a0 Plus, our discussions will also cover \u201cmotherhood and apple pie,\u201d what you need to know to make better decisions about what makes a good baseline forecast.<\/p>\n

Your comments and feedback are welcome here!<\/p>\n

Mark Frost
\nDirector of Business Strategy and Decision Science
\nFiserv<\/a><\/p>\n

David Reilly
\nSr. Vice President
\nAutomatic Forecasting Systems<\/a><\/p>\n

See MARK FROST & DAVID REILLY <\/strong>Speak in Phoenix at IBF’S:<\/strong><\/p>\n

<\/strong><\/p>\n

<\/strong><\/p>\n

\"http:\/\/www.ibf.org\"<\/strong><\/a><\/p>\n

$695 (USD) for Conference Only!<\/strong><\/a><\/p>\n

February 22-23, 2010
\nPhoenix, Arizona USA<\/strong><\/a><\/p>\n

<\/p>\n

<\/p>\n

<\/p>\n

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

The \u201ctime value of money\u201d is at stake when you are trying to forecast demand at ATM machines and of course, customer satisfaction. Trying to get the right amount of cash for pay day and holidays requires some pretty complicated models to get this right.\u00a0 The reality is that these methods and approaches of forecasting […]<\/p>\n","protected":false},"author":85,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[33],"tags":[128,129,65,34,35,130,36,131,37,38],"class_list":{"0":"post-587","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-forecasting-and-planning","7":"tag-atm","8":"tag-best-fit-model","9":"tag-demand-forecasting","10":"tag-demand-planning","11":"tag-forecasting","12":"tag-forecasting-model","13":"tag-ibf","14":"tag-ibf-conference","15":"tag-sop","16":"tag-supply-chain"},"_links":{"self":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/587"}],"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\/85"}],"replies":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/comments?post=587"}],"version-history":[{"count":0,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/587\/revisions"}],"wp:attachment":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/media?parent=587"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/categories?post=587"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/tags?post=587"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}