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SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:October 26-28\nAsia Pacific Region\nRegistration\n\nDecember 7-9\nOnline Workshop\nRegistration\n \nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The workshop surveys the most commonly used business forecasting methods and will cover the following: \n\nHow various forecasting methods work\nPros and cons of each method\nHow to implement best practices in Forecast Pro (via demonstrations using real-world examples)\n\nThe core of the workshop is 13.5 hours of live interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors in real time as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 8 modules presented in the live sessions along with 4 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n \nWho should attend?\nThe 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. \n \n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nDay 2\nExtensions to Exponential Smoothing \nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nDay 3\nEvent-Index Models \nMultiple-Level Forecasting \nNew Product Forecasting \nOffice Hours\nQuestions & Answers \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nForecasting with Machine Learning \nDynamic Regression \nPresentation Descriptions\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. 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. \nExtensions to Exponential Smoothing\nThis session examines three useful extensions to the exponential smoothing model family. The first is the NA-CL model which will often improve forecast accuracy for data sets that exhibit a “selling season” whereby the majority of the demand occurs at specific times of the year (e.g.\, snow shovels\, flu vaccines\, etc.). The second is the Croston’s Intermittent Demand Model which is used to forecast data that exhibit frequent zero demand periods. The third is the Custom Component Model which allows some of the components to be estimated from the data and others to be customized by the forecaster. \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. \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. \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. \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. \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. \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. \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. \n\n\nRegistration\n\nOctober 26-28\nAsia Pacific Region\nRegistration\n\nDecember 7-9\nOnline Workshop\nRegistration\n\n\nRegistration Fee: The registration fee is $495 USD per attendee. A Team Discount price of $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 to 25 and attendees will be registered on a first-come-first-served basis. \nHours:  \nSeptember 21-23: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Daylight Time (UTC/GMT -4 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on Tuesday\, September 28. \nOctober 26-28: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (AEDT (UTC/GMT +11 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m. on Wednesday\, November 3. \nDecember 7-9\, 2021: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Standard Time (UTC/GMT -5 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on Tuesday\, December 14. \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\n\n\n\n\n\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. \n  \n\n\n\n\n\nOctober 26-28\nAsia Pacific Region\nRegistration\n\nDecember 7-9\nOnline Workshop\nRegistration
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-september-2021/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2021/04/BFS-September-2021-Workshop-Image-SMALL.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210511
DTEND;VALUE=DATE:20210514
DTSTAMP:20260416T021108
CREATED:20201222T155532Z
LAST-MODIFIED:20210520T153112Z
UID:10000046-1620691200-1620950399@dev.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:May 11-13\nSold Out\n\n25-27 de Mayo\nTotalmente Vendido\n\nSeptember 21-23\nRegistration\nOnline Workshop\n \nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The 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. \nThe core of the workshop is 13.5 hours of live interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors in real time as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 8 modules presented in the live sessions along with 3 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n \nWho should attend?\nThe 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. \n \n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nDay 2\nExtensions to Exponential Smoothing \nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nDay 3\nEvent-Index Models \nMultiple-Level Forecasting \nNew Product Forecasting \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nDynamic Regression \nPresentation Descriptions\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. 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. \nExtensions to Exponential Smoothing\nThis session examines three useful extensions to the exponential smoothing model family. The first is the NA-CL model which will often improve forecast accuracy for data sets that exhibit a “selling season” whereby the majority of the demand occurs at specific times of the year (e.g.\, snow shovels\, flu vaccines\, etc.). The second is the Croston’s Intermittent Demand Model which is used to forecast data that exhibit frequent zero demand periods. The third is the Custom Component Model which allows some of the components to be estimated from the data and others to be customized by the forecaster. \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. \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. \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. \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. \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. \n\n\nRegistration\n\nMay 11-13\nSold Out\n\n25-27 de Mayo\nTotalmente Vendido\n\nSeptember 21-23\nRegistration\nOnline Workshop\n\n\nRegistration Fee: The registration fee is $495 USD per attendee. A Team Discount price of $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 to 25 and attendees will be registered on a first-come-first-served basis. \nHours: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Daylight Time (UTC/GMT -4 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on the first Tuesday following the workshop. \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\n\n\n\n\n\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. \n  \n\n\n\n\n\nMay 11-13\nSold Out\n\n25-27 de Mayo\nTotalmente Vendido\n\nSeptember 21-23\nRegistration\nOnline Workshop
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-may-2021/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2020/12/SOLD-OUT-BFS-May-2021-Workshop-Image-SMALL-.png
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20210420
DTEND;VALUE=DATE:20210423
DTSTAMP:20260416T021108
CREATED:20210224T185307Z
LAST-MODIFIED:20210819T171051Z
UID:10000048-1618876800-1619135999@dev.forecastpro.com
SUMMARY:Live Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:April 20-22\nRegistration\nAsia Pacific Region\n\nMay 11-13\nSold Out\n\n25-27 de Mayo\nRegistro\nEn Español\n\nSeptember 21-23\nRegistration\nOnline Workshop\n \nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The 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. \nThe core of the workshop is 13.5 hours of interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 8 modules presented in the live sessions along with 3 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n \nWho should attend?\nThe 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. \n \n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nDay 2\nExtensions to Exponential Smoothing \nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nDay 3\nEvent-Index Models \nMultiple-Level Forecasting \nNew Product Forecasting \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nDynamic Regression \nPresentation Descriptions\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. 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. \nExtensions to Exponential Smoothing\nThis session examines three useful extensions to the exponential smoothing model family. The first is the NA-CL model which will often improve forecast accuracy for data sets that exhibit a “selling season” whereby the majority of the demand occurs at specific times of the year (e.g.\, snow shovels\, flu vaccines\, etc.). The second is the Croston’s Intermittent Demand Model which is used to forecast data that exhibit frequent zero demand periods. The third is the Custom Component Model which allows some of the components to be estimated from the data and others to be customized by the forecaster. \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. \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. \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. \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. \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. \n\n\nRegistration\n\nApril 20-22\nRegistration\nAsia Pacific Region\n\nMay 11-13\nSold Out\n\n25-27 de Mayo\nRegistro\nEn Español\n\nSeptember 21-23\nRegistration\nOnline Workshop\n\n\nRegistration Fee: The registration fee is $495 USD per attendee. A Team Discount price of $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 to 25 and attendees will be registered on a first-come-first-served basis. \nHours: The workshop will run from 10:30 a.m. to 3:00 p.m. each day (AEST (UTC/GMT +10 hours)). The office hours session will run from 10:30 a.m. to 12:30 p.m on the first Tuesday following the workshop. \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\n\n\n\n\n\n\n\nInstructors\n\nDinesh Shah\n \n \nDinesh Shah is a demand forecasting\, inventory management and planning\, and supply chain management professional with over 40 years of experience in the industry. He has helped over 150 Australian and Asia Pacific companies implement forecasting\, demand planning\, replenishment planning\, and advanced planning and scheduling solutions to effectively streamline their business processes in those areas. Dinesh has helped many well-known Australian and Asia Pacific Region companies significantly improve supply chain management processes to achieve significant reduction in inventories (in some cases as much as 50%)\, significant improvement in forecast accuracy (in some cases as much as 40-50% improvement)\, and significant improvements in customer service and productivity. He has also provided education in forecasting\, demand management\, sales and operation planning\, inventory management\, and supply chain management to more than 1500 people in 250+ companies. \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. \n\n\n\n\nApril 20-22\nRegistration\nAsia Pacific Region\n\nMay 11-13\nSold Out\n\n25-27 de Mayo\nRegistro\nEn Español\n\nSeptember 21-23\nRegistration\nOnline Workshop
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-april-2021/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2021/03/SMALL-USE-THIS-ONE-Asia-Pacific-Workshop-w-FP-logo-AP-tesx.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210209
DTEND;VALUE=DATE:20210212
DTSTAMP:20260416T021108
CREATED:20201021T143035Z
LAST-MODIFIED:20210506T221020Z
UID:10000043-1612828800-1613087999@dev.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:  \n  \n \n\nFebruary Sold Out\n\n\nMay Sold Out\n\n  \n\nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The 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. \nThe core of the workshop is 13.5 hours of live interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors in real time as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 8 modules presented in the live sessions along with 3 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n\n\nWho should attend?\nThe 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. \n\n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nDay 2\nExtensions to Exponential Smoothing \nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nDay 3\nEvent-Index Models \nMultiple-Level Forecasting \nNew Product Forecasting \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nDynamic Regression \nPresentation Descriptions\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. 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. \nExtensions to Exponential Smoothing\nThis session examines three useful extensions to the exponential smoothing model family. The first is the NA-CL model which will often improve forecast accuracy for data sets that exhibit a “selling season” whereby the majority of the demand occurs at specific times of the year (e.g.\, snow shovels\, flu vaccines\, etc.). The second is the Croston’s Intermittent Demand Model which is used to forecast data that exhibit frequent zero demand periods. The third is the Custom Component Model which allows some of the components to be estimated from the data and others to be customized by the forecaster. \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. \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. \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. \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. \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. \n\n\nRegistration\n\n\nFebruary Sold Out\n\n\nMay Sold Out\n\n  \n\nRegistration Fee: The registration fee is $495 USD per attendee. A Team Discount price of $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 to 22 and attendees will be registered on a first-come-first-served basis. \nHours: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Standard Time (UTC/GMT -5 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on the first Tuesday following the workshop. \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\n\n\n\n\n \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. \n  \n\n\n\n\n\nFebruary Sold Out\n\n\nMay Sold Out
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-february-2021/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2020/10/SOLD-OUT-Feb-21-Workshop-image-FP-LOGO.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20201117
DTEND;VALUE=DATE:20201120
DTSTAMP:20260416T021108
CREATED:20200730T150834Z
LAST-MODIFIED:20201029T162054Z
UID:10000041-1605571200-1605830399@dev.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:  \n \n\nNovember 17-19 Sold Out\n\nFebruary 9-11 Registration\n\n  \n  \n\nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The 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. \nThe core of the workshop is 13.5 hours of live interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors in real time as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 8 modules presented in the live sessions along with 3 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n\n\nWho should attend?\nThe 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. \n\n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nDay 2\nExtensions to Exponential Smoothing \nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nDay 3\nEvent-Index Models \nMultiple-Level Forecasting \nNew Product Forecasting \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nDynamic Regression \nPresentation Descriptions\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. 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. \nExtensions to Exponential Smoothing\nThis session examines three useful extensions to the exponential smoothing model family. The first is the NA-CL model which will often improve forecast accuracy for data sets that exhibit a “selling season” whereby the majority of the demand occurs at specific times of the year (e.g.\, snow shovels\, flu vaccines\, etc.). The second is the Croston’s Intermittent Demand Model which is used to forecast data that exhibit frequent zero demand periods. The third is the Custom Component Model which allows some of the components to be estimated from the data and others to be customized by the forecaster. \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. \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. \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. \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. \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. \n\n\nRegistration\n\nNovember 17-19 Sold Out\n\nFebruary 9-11 Registration\n\n  \n\nRegistration Fee: The registration fee is $495 USD per attendee. A Team Discount price of $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 to 22 and attendees will be registered on a first-come-first-served basis. \nHours: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Standard Time (UTC/GMT -5 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on the first Tuesday following the workshop. \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\n\n\n\n\n \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. \n  \n\n\n\n\nNovember 17-19 Sold Out\n\nFebruary 9-11 Registration
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-november-2020/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2020/07/November-Workshop_with_FPLogo-SOLD-OUT-.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200922
DTEND;VALUE=DATE:20200925
DTSTAMP:20260416T021108
CREATED:20200714T203805Z
LAST-MODIFIED:20200908T205802Z
UID:10000040-1600732800-1600991999@dev.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:September 22-24 Sold Out\n\n\nNovember 17-19 Registration\n\n  \n\nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The 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. \nThe core of the workshop is 13.5 hours of live interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors in real time as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 8 modules presented in the live sessions along with 3 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n\n\nWho should attend?\nThe 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. \n\n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nDay 2\nExtensions to Exponential Smoothing \nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nDay 3\nEvent-Index Models \nMultiple-Level Forecasting \nNew Product Forecasting \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nDynamic Regression \nPresentation Descriptions\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. 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. \nExtensions to Exponential Smoothing\nThis session examines three useful extensions to the exponential smoothing model family. The first is the NA-CL model which will often improve forecast accuracy for data sets that exhibit a “selling season” whereby the majority of the demand occurs at specific times of the year (e.g.\, snow shovels\, flu vaccines\, etc.). The second is the Croston’s Intermittent Demand Model which is used to forecast data that exhibit frequent zero demand periods. The third is the Custom Component Model which allows some of the components to be estimated from the data and others to be customized by the forecaster. \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. \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. \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. \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. \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. \n\n\nRegistration\n\nSeptember 22-24 Sold Out\n\n\nNovember 17-19 Registration\n\n\nRegistration Fee: The registration fee is $495 USD per attendee. A Team Discount price of $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 to 22 and attendees will be registered on a first-come-first-served basis. \nHours: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Daylight Time (UTC/GMT -4 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on the first Tuesday following the workshop. \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\n\n\n\n\n \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. \n  \n\n\n\n\nSeptember 22-24 Sold Out\n\n\nNovember 17-19 Registration
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-september-2020/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2020/07/September-Workshop_with_FPLogo-SOLD-OUT.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200818
DTEND;VALUE=DATE:20200821
DTSTAMP:20260416T021108
CREATED:20200630T205359Z
LAST-MODIFIED:20200730T150902Z
UID:10000039-1597708800-1597967999@dev.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:August 18-20\nSold Out\n\n\nSeptember 22-24 Registration\n\n\nNovember 17-19 Registration\n\n  \n\nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The 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. \nThe core of the workshop is 12 hours of live interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors in real time as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 9 modules presented in the live sessions along with 3 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n\n\nWho should attend?\nThe 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. \n\n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nExtensions to Exponential Smoothing \nDay 2\nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nEvent-Index Models \nDay 3\nMultiple-Level Forecasting \nNew Product Forecasting \nVirtual Workshop \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nDynamic Regression \nPresentation Descriptions\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. \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. \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. \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. \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. \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. \nVirtual Workshop\nThis session provides the opportunity for attendees to discuss their forecasting processes and challenges with the instructors and other attendees. When attendees are willing to share their Forecast Pro projects with the group (there are usually a few who do) we walk through their current approaches and make recommendations for improvements. \n\n\nRegistration\n\nAugust 18-20\nSold Out\n\n\nSeptember 22-24 Registration\n\n\nNovember 17-19 Registration\n\n\nRegistration Fee: The registration fee is $495 USD per attendee. \nClass size: Due to the interactive nature of the live presentations\, attendance is limited to 22 and attendees will be registered on a first-come-first-served basis. \nHours: The workshop will run from 11:00 a.m. to 3:00 p.m. each day (USA Eastern Daylight Time (UTC/GMT -4 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on the first Tuesday following the workshop. \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\n\n\n\n\n \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. \n  \n\n\n\n\nAugust 18-20\nSold Out\n\n\nSeptember 22-24 Registration\n\n\nNovember 17-19 Registration
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-august-2020/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2020/07/August-Workshop_with_FPLogo-SOLD-OUT.png
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20200721
DTEND;VALUE=DATE:20200724
DTSTAMP:20260416T021108
CREATED:20190805T132451Z
LAST-MODIFIED:20200720T133007Z
UID:10000033-1595289600-1595548799@dev.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:July 21-23 Registration\n\n\nAugust 18-20\nSold Out\n\n\nSeptember 22-24 Registration\n\n  \n\nWorkshop Overview\nYou will leave this comprehensive three-day educational course with an understanding of forecasting techniques\, including how they work and how to apply them in a real business environment. The 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. \nThe core of the workshop is 12 hours of live interactive presentations presented over a 3-day period. During the live sessions you will have the opportunity to pose questions to the instructors in real time as well as interact with the other attendees. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel and a 2-hour office hours session. The streaming channel provides on-demand access to prerecorded versions of the 9 modules presented in the live sessions along with 3 additional modules not covered in the live sessions. Office hours provide a 2-hour period the week after the live workshop where instructors will be available to answer questions regarding all topics covered in the workshop. \n\n\nWho should attend?\nThe 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. \n\n  \n \n\n\n\nAgenda At-a-GlancePresentation DescriptionsAgenda At-a-Glance\nDay 1\nIntroduction to Forecasting \nExponential Smoothing \nExtensions to Exponential Smoothing \nDay 2\nForecast Accuracy and Evaluation \nIdentifying Problems in Your Forecasting Process \nEvent-Index Models \nDay 3\nMultiple-Level Forecasting \nNew Product Forecasting \nVirtual Workshop \nAdditional On-Demand Presentations\nComponents of Data \nBox-Jenkins (ARIMA) Models \nDynamic Regression \nPresentation Descriptions\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. \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. \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. \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. \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. \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. \nVirtual Workshop\nThis session provides the opportunity for attendees to discuss their forecasting processes and challenges with the instructors and other attendees. When attendees are willing to share their Forecast Pro projects with the group (there are usually a few who do) we walk through their current approaches and make recommendations for improvements. \n\n\nRegistration\n\nJuly 21-23 Registration\n\n\nAugust 18-20\nSold Out\n\n\nSeptember 22-24 Registration\n\n\nRegistration Fee: The registration fee is $495 USD per attendee. \nClass size: Due to the interactive nature of the live presentations\, attendance is limited to 22 and attendees will be registered on a first-come-first-served basis. \nHours: The workshop will run from 11:00 a.m. to 3:00 p.m. each day (USA Eastern Daylight Time (UTC/GMT -4 hours)). The office hours session will run from 11:00 a.m. to 1:00 p.m on the first Tuesday following the workshop. \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\n\n\n\n\n \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. \n  \n\n\n\n\nJuly 21-23 Registration\n\n\nAugust 18-20\nSold Out\n\n\nSeptember 22-24 Registration
URL:https://dev.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-july-2020/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://dev.forecastpro.com/wp-content/uploads/2020/06/July-Workshop_with_FPLogo-.png
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