{"id":811,"date":"2010-04-30T12:01:35","date_gmt":"2010-04-30T19:01:35","guid":{"rendered":"https:\/\/demand-planning.com\/?p=811"},"modified":"2010-04-30T12:01:35","modified_gmt":"2010-04-30T19:01:35","slug":"grab-your-data-and-come-speed-date-with-me","status":"publish","type":"post","link":"https:\/\/demand-planning.com\/2010\/04\/30\/grab-your-data-and-come-speed-date-with-me\/","title":{"rendered":"Grab Your Data and Come Speed Date with Me"},"content":{"rendered":"
\"\"<\/a>

Maria Simos CEO e-forecasting.com<\/p><\/div>\n

When you come to a conference, all you want is to talk to as many people as you can so you can learn what everyone else is doing and learn from them. \u00a0Speaking with one attendee, they shared how in their group, there is only four demand planners, spread across the globe.\u00a0 The benefit of attending events like the IBF Best Practices Conference<\/a> is that you are now in a room with hundreds in the same position.\u00a0 But still, how to talk to as many as possible?\u00a0 How about some speed dating!\u00a0 So that’s what about 100 or so attendees chose to do with the late afternoon session at the conference.\u00a0 We were broken up into several different groups each with a different topic to discuss. We worked our way around the room a few times so that we would have a chance to discuss the topics we were most interested in. Each topic was led by table monitors.\u00a0 With so many great topics to choose from, it was a hard decision, but \u00a0I chose to head \u00a0over to the JDA led table first and listened in on the discussion about \u201cImproving forecasting and planning with consumption (POS) and syndicated data\u201d led by Danny Halim.<\/p>\n

The group quickly began sharing how they are all ‘trying’ to use consumption data in their demand forecast.\u00a0 Digging deeper into the reason for the repeated use of the word \u201ctrying\u201d, several issues came up regarding the reliability of \u00a0POS data.\u00a0 Several fellow date-ees shared their systems for cleaning the data, or merging several different sources to make it more comprehensive.\u00a0\u00a0 Some companies manually merge them together, while others have built complex systems to forecast inventory levels based on POS data provided by major retailers such as Walmart. It is essential to find a system that works to clean the bad data in order to make it usable. The phrase ‘garbage in, garbage out’ was used frequently although I would say these daters were real pros at sharing and I found myself\u00a0 not \u00a0wanting to get up and move on to another table as the discussion was really exciting.\u00a0 I hope to see some break-out sessions on this topic at future IBF events.<\/p>\n

I headed over to the next table where the topic was \u201cwhat forecasting system works best for you\u201d?\u00a0 All daters were sharing at first was whether \u00a0their organization goes top bottom or bottom up.\u00a0 Not to be left out, there were also a few working from the middle out.\u00a0 The demand forecasting world does not discriminate and accepts all creeds! Two daters shared that their group does both (bottom up and top bottom) and then reconcile the forecasts.\u00a0 Another shared how they begin with a price line item forecast then dollarize it by working with the marketing team and use this to drive the financial forecast.\u00a0 To do this, they create assumptions upfront on the industry, start with a baseline and use this target for demand planning functions.\u00a0 Not everyone \u00a0shared happy stories of their forecasting process.\u00a0 One person explained that their sales department does not participate in providing input into the forecast, event though they are the closest to the demand and the customers..\u00a0 The ideas presented in the Keynote Presentation by Gerry Fay of Avnet EM Velocity came up as ways to combat some of the issues the table faced. Some of these were demand sensing and responding, and command and control.\u00a0 A few other different approaches presented were forecasting at the SKU level then weighting forecasts by different group functions at certain levels depending on the timing, conflicts with upper management when they do not see what they want in the forecast, forecast ownership and having the sales team provide forecast as a change in trend, rather than level.\u00a0 Again, when table switching was called for, it was hard to leave but by this point everyone was so warmed up to sharing I looked forward to seeing how the last table would go.<\/p>\n

Our last group date was led by Mike Gilliand of SAS and we talked about \u201cnew product forecasting\u201d.\u00a0 Around the table the range of new products spanned \u00a0from 5-40%.\u00a0 Forecasting by analogy is the method most commonly used for new product forecasting.\u00a0 The focus on the higher levels of uncertainty and risk were brought up, and the strong need to make sure management realizes this as new products roll out.\u00a0 Also, the importance of tracking past new product forecast reports was part of the discussion as well.\u00a0 Is your sales team consistently over-shooting? Keep this in mind.\u00a0 One major takeaway was to make sure and track what assumptions were used when you are making the forecast.\u00a0 If you carefully track these, it will assist in making the forecast better and help the team in the long run.\u00a0 The general consensus of the table was that it takes roughly six months, for the most part, to know if a new product is going to succeed before entering it into the standard S&OP process for the organization.<\/p>\n

And with that, speed dating was done and all minds were racing.\u00a0 The level of sharing within the group continued to grow and we all moseyed over to the cocktail reception where the speed dating conversations continued and mini-crab cakes, succulent ripe California strawberries and JDA signature martinis were our award for being such great daters and sharers of demand planning lessons.<\/p>\n

Maria E. Simos is CEO of e-forecasting.com, an economic research and consulting company based in Durham, NH with clients ranging from media, academics, federal banks, major manufacturers to other consulting firms.\u00a0 In her role, Ms. Simos works to further develop the reach of e-forecasting\u2019s economic data and reporting capabilities. She also works closely with clients to ensure that they are receiving the important forecasts, economic data and support needed to be successful. She promotes the work of e-forecasting.com and provides economic analysis through her twitter account (@mesimos) and via other social media outlets.\u00a0 Ms. Simos holds a Master\u2019s Degree in Management from Carnegie Mellon University where she focused her research on management and network analysis. Her research explored social and business networks and their tie in to culture in organizations. \u00a0Her undergraduate study was completed at the Tepper School of Business at Carnegie Mellon.<\/p>\n","protected":false},"excerpt":{"rendered":"

When you come to a conference, all you want is to talk to as many people as you can so you can learn what everyone else is doing and learn from them. \u00a0Speaking with one attendee, they shared how in their group, there is only four demand planners, spread across the globe.\u00a0 The benefit of […]<\/p>\n","protected":false},"author":166,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[33],"tags":[65,34,147,35,36,48,149,150],"class_list":{"0":"post-811","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-forecasting-and-planning","7":"tag-demand-forecasting","8":"tag-demand-planning","9":"tag-e-forecasting-com","10":"tag-forecasting","11":"tag-ibf","12":"tag-institute-of-business-forecasting-and-planning","13":"tag-maria-simos","14":"tag-new-product-forecasting"},"_links":{"self":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/811"}],"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\/166"}],"replies":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/comments?post=811"}],"version-history":[{"count":0,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/811\/revisions"}],"wp:attachment":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/media?parent=811"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/categories?post=811"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/tags?post=811"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}