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DTSTART;VALUE=DATE:20260202
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SUMMARY:Orlando Business Forecasting Workshop: Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:Orlando February 2-4 Workshop RegistrationContents \n\nWorkshop Overview & Highlights\nWho should attend?\nAgenda-at-a-glance\nVenue & Accommodations\nWorkshop Hours\nRegistration\nInstructors\n\n\n \nWorkshop Overview\nThis workshop surveys the most commonly used business forecasting methods\, explains how they work conceptually\, discusses their pros and cons\, and demonstrates best practices for implementing them in a real-world environment using Forecast Pro. You will leave with insight into all aspects of business forecasting and a working knowledge of proven forecasting methods. \n\n\nDuring the hands-on workshop sessions\, you will have the opportunity to solve your forecasting challenges by applying what you have learned using state-of-the-art software under the guidance of expert instructors. \n \n\nThe workshop will have various sessions on important forecasting topics: \n\nIntroduction to Forecasting\nComponents of Data\nTime series methods including Exponential Smoothing\, Box-Jenkins and the Croston’s intermittent demand model\nAdvanced techniques including event modeling\, top-down reconciliation\, dynamic regression\, and machine learning\nNew Product Forecasting methods\nForecast Accuracy and Evaluation\nLarge scale & multiple-level forecasting\nIdentifying Problems in Your Forecasting Process\n\n \nWho should attend?\nThis workshop is valuable for anyone whose job responsibilities include preparing or analyzing forecasts—some prior knowledge of statistics is helpful but not essential. The tutorials use Forecast Pro and real-world data to provide a deeper understanding of the forecasting methods and to show best practices; these lessons are applicable regardless of which forecasting software your organization uses. \nThe workshop also provides a great opportunity to network with your peers to discover how they’ve solved problems similar to your own and to compare notes on forecasting practices. You will be able to make valuable connections with other forecasters during breaks\, lunches and at Monday evening’s cocktail reception. \nOrlando February 2-4 Workshop Registration\nAgenda At-a-GlanceDetailed AgendaAgenda At-a-Glance\nMonday\, February 2: 9 am – 5 pm\n\n\n\n\nIntroduction to Forecasting\n\n\nExponential Smoothing\n\n\nEvent-Index Models\n\n\nEvening Cocktail Reception\n\n\n\n\n\nTuesday\, February 3: 9 am – 5 pm\n\n\n\n\nMachine Learning\n\n\nBox Jenkins (ARIMA) Models\n\n\nDynamic Regression\n\n\nMultiple-Level Forecasting\n\n\nWorkshop 1\n\n\n\n\n\nWednesday\, February 4: 9 am – 3:30 pm\n\n\n\n\nForecast Accuracy & Evaluation\n\n\nIdentifying Problems in Your Forecasting Process\n\n\nNew Product Forecasting\n\n\nWorkshop 2\n\n\n\n\nDetailed Agenda\nMonday\, February 2\nIntroduction to Forecasting\nA broad overview of business forecasting and its various uses within the organization. Topics include approaches to forecasting\, features of data\, the role of judgment\, selection of appropriate forecasting methods for varied data sets and resources for forecasters. \nExponential Smoothing\nA survey of exponential smoothing techniques with particular emphasis on the Holt-Winters family of models and Croston’s intermittent demand model. Topics include the pros and cons of using these models\, when they are best used\, how they work\, identifying model components\, parameter optimization and model diagnosis. \nEvent-Index Models\nEvent-index models extend the functionality of exponential smoothing models by providing adjustments for promotions\, strikes and other non-calendar based events. This session addresses how these models work\, how and when they should be used\, and how to customize their design to best suit your needs. \nEvening Cocktail Reception\nA cocktail reception will be held on Monday evening\, providing the opportunity to socialize and network after the first day of the workshop. Connect with other attendees and enjoy a drink while enjoying the beauty of the Hilton Orland Buena Vista Palace and nearby Disney Springs area. \nTuesday\, February 3\nForecasting With Machine Learning\nThis session overviews the basics and benefits of forecasting with machine learning (ML). Topics include the basics of machine learning powered forecasting\, when ML is likely to improve your forecasts\, how to use the completely automatic ML option in Forecast Pro and how to build custom ML models in Forecast Pro. \nBox Jenkins (ARIMA) Models\nAn exploration into the use of ARIMA models for business forecasting. Topics include the advantages/disadvantages of using these models\, how and when they should be applied\, automatic identification procedures and model diagnostics. \nDynamic Regression\nA detailed look into the ins and outs of regression forecasting. Topics include when regression models are best applied\, how to build the models\, ordinary least squares\, leading indicators\, lagged variables\, Cochrane-Orcutt models\, hypothesis testing and the use of “dummy” variables \nMultiple-Level Forecasting\nThis session explores hierarchical forecasting techniques. Topics include the need for forecasting at various levels\, product vs. geographical hierarchies\, reconciliation strategies\, top-down vs. bottom-up approaches\, the use of proportional allocation and adjustment for seasonality. \nWorkshop 1\nIn this first hands-on session attendees are guided through forecasting exercises\, applying ideas discussed during the lectures. Attendees will also have time to work with their own data with the help of the instructors. \nWednesday\, February 4\nForecast Accuracy and Evaluation\nA detailed look at evaluating the accuracy of forecasting methods. Topics include the distinction between within sample and out-of-sample errors\, a survey of error measurement statistics\, a summary of findings from forecasting competitions\, and an explanation of how to use both real-time tracking reports and simulations as predictors of model performance. \nIdentifying Problems in Your Forecasting Process\nApproaches for focusing on critical items when forecasting large volumes of data. Topics include evaluating and forecasting SKU data\, filtering and ABC (Pareto) classification\, outlier detection and correction\, exception reporting and measuring accuracy across multiple time series. \nNew Product Forecasting\nThis session explores various approaches for forecasting new products. Topics include the pros and cons of different methods based on a product’s classification and a review of popular methods including item supersession\, forecast by analogy and the Bass diffusion model. \nWorkshop 2\nIn this second hands-on session attendees will be guided through forecasting exercises\, applying ideas discussed during the lectures. Attendees will also have time to work with their own data with the help of the instructors. \n \nVenue & Accommodations\n☀️ Escape the Cold — We’ve secured discounted room rates available 3 days before and 3 days after the workshop. \nThe workshop will be held at the beautiful Hilton Orlando Buena Vista Palace\, just an 8-minute walk from Disney Springs. \nAttendees can reserve rooms at the special rate of $249 per night until January 9\, 2026. Reservations can be made here or by calling (407) 827-2727 and giving the call-in code BFW. \nHilton Orlando Buena Vista Palace\, Disney Springs Area\n1900 E Buena Vista Drive\nLake Buena Vista\, Florida 32830\n(407) 827-2727 \n \nWorkshop Hours \nMonday\, February 2: 9 am – 5 pm\nTuesday\, February 3: 9 am – 5 pm\nWednesday\, February 4: 9 am – 3:30 pm \nContinental breakfast and lunch (including a vegetarian option) will be provided daily for attendees. \nA cocktail reception will be held on Monday evening\, providing a relaxing environment for socializing and networking after the first day of the workshop. \n \nRegistration\nRegistration Fee: The registration fee is $1\,950 USD per attendee. A Team Discount price of $1\,550 per attendee is available to organizations registering 3 or more attendees. \nClass Size: Due to the interactive nature of the live presentations\, attendance is limited and attendees will be registered on a first-come-first-served basis. These workshops typically sell out\, so register now to secure your spot! \nCancellation Policy: The workshop is limited in size and we ask that if you must cancel to please inform us as soon as possible. Attendees may receive a full refund if cancellation is made 14 days or more prior to the start of the workshop. Registrants who fail to attend or cancel less than 14 days before the start date are not entitled to receive a refund. Personnel substitutions may be made at any time. \nOrlando February 2-4 Workshop RegistrationWorkshop Attendees are eligible to receive a 10% discount (up to a maximum of $750 USD) on the purchase of new Forecast Pro licenses. \n  \nInstructors\n\nEric Stellwagen\nEric Stellwagen is the co-founder of Business Forecast Systems\, Inc. (BFS) and the co-author of the Forecast Pro software product line. With more than 30 years of expertise in the field\, he regularly presents workshops and publishes on the topic of business forecasting\, and is widely recognized as a leading educator on the subject. Drawing upon his extensive consulting experience helping organizations to address their forecasting challenges\, Eric infuses his classes with practical approaches and uses real-world data to illustrate concepts. He has worked with many leading firms including Coca-Cola\, Kraft\, Merck\, Nabisco\, Owens-Corning and Verizon and has presented workshops for a variety of organizations including APICS\, the International Institute of Forecasters (IIF)\, the Institute of Business Forecasting (IBF)\, the Institute for Operations Research and the Management Sciences (INFORMS)\, and the University of Tennessee. Eric served on the board of directors of the IIF for 12 years and is currently serving on the practitioner advisory board of Foresight: The International Journal of Applied Forecasting. \nFranklin Rea \nFranklin Rea brings over 15 years of expertise in data analysis\, technology\, marketing operations\, and mathematics to his role at BFS. With a background in the enterprise software sector\, Franklin has navigated varied industries such as cyber-security\, campaign management\, and sales training and enablement. In addition\, he has worked as a college-level mathematics instructor. At BFS\, Franklin serves as a trainer and solutions consultant\, assisting clients in maximizing their utilization of the Forecast Pro software\, and providing a problem-solving approach and valuable insights to everyday forecasting questions. Franklin holds an M.S. in Mathematics from Northeastern University and received his undergraduate degree from Dartmouth College.
URL:https://dev.forecastpro.com/event/orlando-2026-business-forecasting-workshop-techniques-best-practices-application-using-forecast-pro/
LOCATION:Orlando\, FL
CATEGORIES:Forecast Pro Event
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DTSTART;VALUE=DATE:20240226
DTEND;VALUE=DATE:20240229
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CREATED:20231218T162629Z
LAST-MODIFIED:20240207T155314Z
UID:10000068-1708905600-1709164799@dev.forecastpro.com
SUMMARY:Business Forecasting Workshop: Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:Sold Out\n \nContents\n\nWorkshop Overview & Highlights\nWho should attend?\nAgenda-at-a-glance\nVenue & Accommodations\nWorkshop Hours\nRegistration\nInstructors\n\n \nWorkshop Overview\nThis workshop surveys the most commonly used business forecasting methods\, explains how they work conceptually\, discusses their pros and cons\, and demonstrates best practices for implementing them in a real-world environment using Forecast Pro. You will leave with insight into all aspects of business forecasting and a working knowledge of proven forecasting methods. \nDuring the hands-on workshop sessions\, you will have the opportunity to solve your forecasting challenges by applying what you have learned using state-of-the-art software under the guidance of expert instructors. \n\n\n\nThe workshop will have various sessions on important forecasting topics:  \n\nIntroduction to Forecasting\nComponents of Data\nTime series methods including Exponential Smoothing\, Box-Jenkins and the Croston’s intermittent demand model\nAdvanced techniques including event modeling\, top-down reconciliation\, dynamic regression\, and machine learning\nNew Product Forecasting methods\nForecast Accuracy and Evaluation\nLarge scale & multiple-level forecasting\nIdentifying Problems in Your Forecasting Process\n\n \n\n \nWho should attend?\nThis workshop is valuable for anyone whose job responsibilities include preparing or analyzing forecasts—some prior knowledge of statistics is helpful but not essential. The tutorials use Forecast Pro and real-world data to provide a deeper understanding of the forecasting methods and to show best practices; these lessons are applicable regardless of which forecasting software your organization uses. \nThe workshop also provides a great opportunity to network with your peers to discover how they’ve solved problems similar to your own and to compare notes on forecasting practices. You will be able to make valuable connections with other forecasters during breaks\, lunches and at Monday evening’s cocktail reception. \nSold Out\n\nAgenda At-a-GlanceDetailed AgendaAgenda At-a-Glance\nMonday\, February 26: 9 am – 5 pm\n\nIntroduction to Forecasting\nComponents of Data\nExponential Smoothing\nForecast Accuracy and Evaluation\nWorkshop 1\nEvening Cocktail Reception\n\n\nTuesday\, February 27: 9 am – 5 pm\n\nBox Jenkins (ARIMA) Models\nEvent-Index Models\nLarge-Scale Forecasting\nMultiple-Level Forecasting\nWorkshop 2\n\n\n\nWednesday\, February 28: 9 am – 3:30 pm\n\nNew Product Forecasting\nDynamic Regression\nForecasting With Machine Learning\nWorkshop 3\n\n\nDetailed Agenda\nMonday\, February 26\nIntroduction to Forecasting\nA broad overview of business forecasting and its various uses within the organization. Topics include approaches to forecasting\, features of data\, the role of judgment\, selection of appropriate forecasting methods for varied data sets and resources for forecasters. \nComponents of Data\nAn in-depth look at the different components found in time series data including trends\, seasonal patterns\, business cycles\, trading-day variations\, interventions (events) and noise. Discussion includes the forms the components can take\, spotting local vs. global components\, interpretation of business cycle indicators and the use of decomposition routines. \nExponential Smoothing\nA survey of exponential smoothing techniques with particular emphasis on the Holt-Winters family of models and Croston’s intermittent demand model. Topics include the pros and cons of using these models\, when they are best used\, how they work\, identifying model components\, parameter optimization and model diagnosis. \nForecast Accuracy and Evaluation\nA detailed look at evaluating the accuracy of forecasting methods. Topics include the distinction between within sample and out-of-sample errors\, a survey of error measurement statistics\, a summary of findings from forecasting competitions\, and an explanation of how to use both real-time tracking reports and simulations as predictors of model performance. \nWorkshop 1\nThis first hands-on session familiarizes attendees with the use of the Forecast Pro software package as they are guided through sample exercises applying the ideas discussed during the lectures. \nEvening Cocktail Reception\nA cocktail reception will be held on Monday evening\, providing the opportunity to socialize and network after the first day of the conference. Connect with other attendees and enjoy a drink while enjoying the poolside Oasis Bar & Grill. \n  \nTuesday\, February 27\nBox Jenkins (ARIMA) Models\nAn exploration into the use of ARIMA models for business forecasting. Topics include the advantages/disadvantages of using these models\, how and when they should be applied\, automatic identification procedures and model diagnostics. \nEvent-Index Models\nEvent-index models extend the functionality of exponential smoothing models by providing adjustments for promotions\, strikes and other non-calendar based events. This session addresses how these models work\, how and when they should be used\, and how to customize their design to best suit your needs. \nLarge-Scale Forecasting\nApproaches for focusing on critical items when forecasting large volumes of data. Topics include evaluating and forecasting SKU data\, filtering and ABC (Pareto) classification\, outlier detection and correction\, exception reporting and measuring accuracy across multiple time series. \nMultiple-Level Forecasting\nThis session explores hierarchical forecasting techniques. Topics include the need for forecasting at various levels\, product vs. geographical hierarchies\, reconciliation strategies\, top-down vs. bottom-up approaches\, the use of proportional allocation and adjustment for seasonality. \nWorkshop 2\nIn this session\, attendees are guided through forecasting exercises and have time to work with their own data with the help of the instructors \nWednesday\, February 28\nNew Product Forecasting\nThis session explores various approaches for forecasting new products. Topics include the pros and cons of different methods based on a product’s classification and a review of popular methods including item supersession\, forecast by analogy and the Bass diffusion model. \nDynamic Regression\nA detailed look into the ins and outs of regression forecasting. Topics include when regression models are best applied\, how to build the models\, ordinary least squares\, leading indicators\, lagged variables\, Cochrane-Orcutt models\, hypothesis testing and the use of “dummy” variables \nForecasting With Machine Learning\nMachine Learning and AI have emerged as transformational methodologies with a multitude of applications—facial recognition\, medical diagnosing and self-driving cars—to name but a few. But can Machine Learning be used to improve your forecasting? Recent forecasting research suggests that it can. This session will discuss the basics and benefits of automated Extreme Gradient Boosting (XG Boost) an effective and accurate Machine Learning algorithm recently implemented in Forecast Pro. \nWorkshop 3\nThis final session consists of a regression example after which attendees have time to work with their own data. \n\n\n\n\n\nVenue & Accommodations\nImage courtesy of https://www.wyndhamlakebuenavista.com/ \n\nThe workshop will be held at Wyndham Lake Buena Vista located just minutes from Disney Springs and the theme park. Attendees can reserve rooms at the hotel at the discounted rate of $99 per night until February 11\, 2024. Reservations can be made online by clicking here or via phone by calling (877) 999-3223. \nWyndham Lake Buena Vista Disney Springs Resort Area\n1850 Hotel Plaza Boulevard\nLake Buena Vista\, FL 32830-8406\nhttps://www.wyndhamlakebuenavista.com/ \n(407) 828-4444 \n\n\nWorkshop Hours \nMonday\, February 26: 9 am – 5 pm\nTuesday\, February 27: 9 am – 5 pm\nWednesday\, February 28: 9 am – 3:30 pm \nLunch (including a vegetarian option) will be provided daily for attendees. \nA cocktail reception will be held on Monday evening\, providing a relaxing environment for socializing and networking after the first day of the workshop. \n\nRegistration\nRegistration Fee: The registration fee is $1\,750 USD per attendee. A Team Discount price of $1\,395 per attendee is available to organizations registering 3 or more attendees. \nClass Size: Due to the interactive nature of the live presentations\, attendance is limited and attendees will be registered on a first-come-first-served basis. These workshops typically sell out\, so register now to secure your spot! \nCancellation Policy: The workshop is limited in size and we ask that if you must cancel to please inform us as soon as possible. Attendees may receive a full refund if cancellation is made 14 days or more prior to the start of the workshop. Registrants who fail to attend or cancel less than 14 days before the start date are not entitled to receive a refund. Personnel substitutions may be made at any time. \n \nSold Out\n\nWorkshop Attendees are eligible to receive a discount of up to $750 USD when licensing Forecast Pro Software.  \n \n\nInstructors\n\nEric Stellwagen\n \nEric Stellwagen is the co-founder of Business Forecast Systems\, Inc. (BFS) and the co-author of the Forecast Pro software product line. With more than 30 years of expertise in the field\, he regularly presents workshops and publishes on the topic of business forecasting\, and is widely recognized as a leading educator on the subject. Drawing upon his extensive consulting experience helping organizations to address their forecasting challenges\, Eric infuses his classes with practical approaches and uses real-world data to illustrate concepts. He has worked with many leading firms including Coca-Cola\, Kraft\, Merck\, Nabisco\, Owens-Corning and Verizon and has presented workshops for a variety of organizations including APICS\, the International Institute of Forecasters (IIF)\, the Institute of Business Forecasting (IBF)\, the Institute for Operations Research and the Management Sciences (INFORMS)\, and the University of Tennessee. Eric served on the board of directors of the IIF for 12 years and is currently serving on the practitioner advisory board of Foresight: The International Journal of Applied Forecasting. \nSarah Darin\n \nSarah Darin has 20  years of experience with statistical consulting\, sales forecasting\, regression modeling and marketing analytics. Sarah holds a Master’s of Science in Statistics from the University of Chicago\, where she also served as a Lecturer for two years. She has consulted for clients across a broad range of industries\, including Consumer Packaged Goods\, Telecommunications\, Technology\, Retail\, Automotive and Finance. Before joining BFS\, Sarah was Vice President of Consulting Services at Nielsen where she focused on custom analytic solutions for the CPG and Expanded Vertical practices\, teaching customers how to efficiently integrate\, manage\, model and forecast large-scale datasets. Sarah’s ability to understand and explain statistical concepts in the context of real-world\, messy data makes her an ideal instructor for this workshop. Sarah received her undergraduate degree in Applied Mathematics from Harvard University. \nFranklin Rea \n \nFranklin Rea brings over 15 years of expertise in data analysis\, technology\, marketing operations\, and mathematics to his role at BFS. With a background in the enterprise software sector\, Franklin has navigated varied industries such as cyber-security\, campaign management\, and sales training and enablement. In addition\, he has worked as a college-level mathematics instructor. At BFS\, Franklin serves as a trainer and solutions consultant\, assisting clients in maximizing their utilization of the Forecast Pro software\, and providing a problem-solving approach and valuable insights to everyday forecasting questions. Franklin holds an M.S. in Mathematics from Northeastern University and received his undergraduate degree from Dartmouth College. \n\n\nSold Out
URL:https://dev.forecastpro.com/event/orlando-2024-business-forecasting-techniques-best-practices-application-using-forecast-pro/
LOCATION:Orlando\, FL
CATEGORIES:Forecast Pro Event
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20191015
DTEND;VALUE=DATE:20191019
DTSTAMP:20260416T074901
CREATED:20190604T153529Z
LAST-MODIFIED:20190626T165021Z
UID:10000029-1571097600-1571443199@dev.forecastpro.com
SUMMARY:Dynamics AX User Group Summit
DESCRIPTION:Click here for more information\n  \nThe Summit is the premier annual conference for North American users of the Microsoft Business Applications platform. Stop by the Forecast Pro booth to see how to improve your demand forecasting with our comprehensive solution that smoothly integrates with Dynamics AX.
URL:https://dev.forecastpro.com/event/ax-user-conference/
LOCATION:Orlando\, FL
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