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SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:Contents\n\nWorkshop Overview\nWho should attend?\nAgenda-at-a-glance\nForecast Pro User Conference + Workshop Bundle\nRegistration\nInstructors\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. \nThe workshop also includes 2 weeks of access to the workshop’s streaming channel. 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. \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 \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\nForecast Pro User Conference + Workshop Bundle\nWe are offering a Workshop + User Conference bundle. If you register for the 2022 Forecast Pro User Conference you can add this workshop to your live or online User Conference registration for a discounted workshop price of $200 per person. The Forecast Pro User Conference will take place September 19 – 21\, 2022. \nIf you have any questions please contact skhadr@forecastpro.com. \nRegistration\n\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. \nHours:  \nSeptember 7-9\, 2022: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Daylight time (UTC/GMT -4 hours)). \nCancellation Policy: 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 
URL:https://www.forecastpro.com/event/online-workshop-business-forecasting-techniques-best-practices-application-using-forecast-pro-september-2022/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2022/01/BFS-September-2022-Workshop-Image-SMALL.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20220503
DTEND;VALUE=DATE:20220506
DTSTAMP:20260417T180906
CREATED:20220124T205520Z
LAST-MODIFIED:20220322T154752Z
UID:10000054-1651536000-1651795199@www.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:May 3-5\nOnline Workshop\nRegistration\n\nSeptember 7-9\nOnline Workshop\nRegistration\n\nUser Conference\n+ Workshop\nBundle\n \nContents\n\nWorkshop Overview\nWho should attend?\nAgenda-at-a-glance\nForecast Pro User Conference + Workshop Bundle\nRegistration\nInstructors\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\nForecast Pro User Conference + Workshop Bundle\nWe are offering a Workshop + User Conference bundle. If you register for the 2022 Forecast Pro User Conference you can add this workshop to your live or online User Conference registration for a discounted workshop price of $200 per person. The Forecast Pro User Conference will take place September 19 – 21\, 2022. \nIf you have any questions please contact skhadr@forecastpro.com. \nRegistration\n\n\n\nMay 3-5\nOnline Workshop\nRegistration\n\nSeptember 7-9\nOnline Workshop\nRegistration\n\nUser Conference\n+ Workshop\nBundle\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:  \nMay 3-5\, 2022: 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\, May 10. \nSeptember 7-9\, 2022: The workshop will run from 11:00 a.m. to 3:30 p.m. each day (USA Eastern Daylight time (UTC/GMT -4 hours)). \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\n\n\nMay 3-5\nOnline Workshop\nRegistration\n\nSeptember 7-9\nOnline Workshop\nRegistration\n\nUser Conference\n+ Workshop\nBundle
URL:https://www.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-may-2022/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2022/01/BFS-May-2022-Workshop-Image-SMALL.png
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DTSTART;TZID=America/New_York:20220407T133000
DTEND;TZID=America/New_York:20220407T143000
DTSTAMP:20260417T180907
CREATED:20220125T231329Z
LAST-MODIFIED:20220329T213322Z
UID:10000052-1649338200-1649341800@www.forecastpro.com
SUMMARY:Free Webinar: Simplifying Inventory Replenishment using Forecast Pro
DESCRIPTION:Click Here to Register Now!\nDescription:\nCombining inventory replenishment models with dynamic forecasting can improve the corporate planning process and help optimize your supply chain. Using some of the new features found in Forecast Pro TRAC v7\, it’s now easier than ever to implement efficient replenishment models that leverage all of Forecast Pro’s forecasting capabilities. \nIn this educational one-hour live webinar\, Marco Arias Vargas\, Founding Partner of Macrologistica and seasoned supply chain educator\, will review: \n\nhow to improve supply chain performance using replenishment models\ncommonly used replenishment strategies and pitfalls\nhow to implement replenishment models using Forecast Pro\nkeys for tailoring a replenishment strategy to meet the needs of your organization\n\nMarco will demonstrate several replenishment models built using Forecast Pro TRAC and discuss the benefits of better inventory management. \nCan’t attend the live webinar? Register for the session and we will notify you via email when the recording is available for on-demand viewing. \n  \nClick Here to Register Now!
URL:https://www.forecastpro.com/event/free-webinar-simplifying-inventory-replenishment-using-forecast-pro/
LOCATION:Online Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2022/01/Inventory-Webinar-Photo-SMALL.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20220215
DTEND;VALUE=DATE:20220218
DTSTAMP:20260417T180907
CREATED:20210712T211438Z
LAST-MODIFIED:20220215T223537Z
UID:10000057-1644883200-1645142399@www.forecastpro.com
SUMMARY:Taller En Línea: Técnicas de Pronósticos de Demanda\, Mejores Prácticas y Aplicaciones Utilizando Forecast Pro
DESCRIPTION:15-17 de febrero\nTaller En Línea\nRegistro\n\nContenido\nDescripción del Taller \nQuién debería asistir \nAgenda y Descripciones de Presentación \nRegistro \nInstructores \nDescripción del Taller\nAl finalizar este extenso taller de 3 días\, los participantes tendrán conocimiento y comprensión de técnicas de pronósticos\, incluyendo su funcionamiento y aplicación en un ambiente de negocios real. El taller se enfoca en los métodos de pronósticos de demanda que son más comúnmente utilizados\, explica conceptualmente cómo funcionan\, discute sus ventajas y desventajas\, y demuestra las mejores prácticas para implementarlos en un ambiente de trabajo real utilizando Forecast Pro. \nEl taller consta de 13.5 horas de presentaciones en vivo\, distribuidas a lo largo de 3 días. En estas sesiones tendrás la oportunidad de hacer preguntas a los instructores en tiempo real\, así como interactuar con los demás participantes. \nEl taller también incluye un acceso por 2 semanas al canal de streaming del taller y una sesión de 2 horas de consulta libre. El canal de streaming proporciona acceso a versiones pregrabadas de los 8 módulos presentados durante el taller\, así como 4 módulos adicionales que no son cubiertos en las sesiones en vivo. Las horas de consulta libre consisten en un periodo de 2 horas la semana posterior al taller donde los instructores se encontrarán disponibles para contestar preguntas sobre los temas cubiertos en el taller. \n \n¿Quién debería asistir?\nEl taller es de gran valor para cualquier persona cuyas responsabilidades en el trabajo incluyan la preparación o análisis de pronósticos – tener conocimiento previo de estadística no es esencial para este taller. Los tutoriales utilizan Forecast Pro y datos de casos reales para proporcionar un entendimiento a fondo de los métodos de pronósticos y para demostrar las mejores prácticas; estas lecciones son aplicables sin importar el programa o software de pronósticos que tu organización utilice. \n \n  \n \n\n\n\nAgenda de un VistazoDescripciones de PresentaciónAgenda de un Vistazo\nDía 1\nIntroducción a los Pronósticos \nSuavización Exponencial \nDía 2\nExtensiones de Suavización Exponencial \nPrecisión y Evaluación de los Pronósticos \nIdentificando Problemas en tu Proceso de Pronósticos \nDía 3\nModelos de Índices de Eventos \nPronósticos en Múltiples Niveles \nPronósticos de Productos Nuevos \nPresentaciones Adicionales Reproducibles\nComponentes de los Datos \nModelos Box-Jenkins (ARIMA) \nPronóstico con Machine Learning \nRegresión Dinámica \nDescripciones de Presentación\nIntroducción a los Pronósticos\nUna vista general a los pronósticos de la demanda y sus múltiples usos dentro de una organización. Los temas incluyen enfoques de pronósticos\, características de los datos\, el rol del juicio y experiencia\, selección de métodos de pronósticos apropiados para conjuntos de datos variados y recursos para Forecasters. \nComponentes de los Datos\nUn vistazo a profundidad de los distintos componentes encontrados en datos de series de tiempo incluyendo tendencia\, patrones estacionales\, ciclos de negocios\, variaciones por días del calendario\, intervenciones (eventos) y ruido. La discusión incluye las formas que pueden tomar los componentes\, detección de componentes locales vs. globales\, interpretación de indicadores de ciclos de negocios y el uso de rutinas de descomposición. \nSuavización Exponencial\nUna variedad de técnicas de suavización exponencial con un énfasis particular en la familia de modelos Holt-Winters. Los temas incluyen las ventajas y desventajas de utilizar estos modelos\, cuándo es mejor utilizarlos\, cómo funcionan\, identificación de componentes del modelo\, optimización de parámetros y diagnóstico de modelos. \nExtensiones de Suavización Exponencial\nEsta sesión analiza tres útiles extensiones a la familia de modelos de suavización exponencial. La primera es el modelo NA-CL que usualmente mejorará la precisión de los pronósticos para conjuntos de datos que muestran una “demanda de temporada” donde la mayoría de la demanda ocurre en momentos específicos del año (por ejemplo\, vacunas contra la influenza). La segunda es el Modelo de Demanda Intermitente de Croston que es utilizado para pronosticar datos que muestran periodos con demanda de cero frecuentemente. La tercera es el Modelo de Componentes Personalizados que permite estimar algunos componentes desde los datos y que el Forecaster los ajuste. \nModelos Box-Jenkins (ARIMA)\nUn análisis del uso de los modelos ARIMA para pronósticos de la demanda. Los temas incluyen las ventajas y desventajas de utilizar estos modelos\, cómo y cuándo deben de ser aplicados\, procedimientos de identificación automática y diagnósticos de modelos. \nPrecisión y Evaluación de los Pronósticos\nUn análisis detallado a la evaluación de la precisión de los métodos de pronósticos. Los temas incluyen la diferenciación entre errores del modelo y fuera de la muestra\, una variedad de estadísticas para medición de errores\, un resumen de resultados de competencias de pronósticos y una explicación sobre cómo utilizar reportes de seguimiento y realizar simulaciones como técnica de predicción de desempeño del modelo. \nIdentificando Problemas en tu Proceso de Pronósticos\nEnfoques para concentrarse en artículos críticos cuando se pronostican grandes cantidades de datos. Los temas incluyen la evaluación y generación de pronósticos a niveles de artículo\, clasificación ABC (Pareto) y filtros\, detección y corrección de datos atípicos\, reportes de excepciones y medición de precisión en múltiples series de tiempo. \nModelos de Índices de Eventos\nLos modelos de índices de eventos extienden la funcionalidad de los modelos de suavización exponencial al proporcionar ajustes para promociones\, paros o faltantes y otros eventos que no se basan en el calendario regular. Esta sesión habla sobre cómo funcionan estos modelos\, cómo y cuándo deben ser utilizados y cómo personalizar su diseño para que se ajuste mejor a tus necesidades. \nPronósticos en Múltiples Niveles\nEsta sesión analiza las técnicas de pronósticos de jerarquías. Los temas incluyen la necesidad de pronósticos en diferentes niveles\, jerarquías de producto vs. geográficas\, estrategias de reconciliación\, enfoques top-down vs. bottom-up\, el uso de asignación proporcional y ajustes de estacionalidad. \nPronósticos de Productos Nuevos\nEsta sesión analiza una variedad de enfoques para pronósticos de productos nuevos. Los temas abarcan las ventajas y desventajas de diferentes métodos basados en la clasificación de un nuevo producto y una revisión de métodos típicos incluyendo remplazos de artículos\, pronóstico por analogía y el modelo de difusión de Bass. \nPronóstico con Machine Learning \nEsta sesión describe los conceptos básicos y los beneficios de la previsión con Machine Learning (ML). Los temas incluyen los conceptos básicos de la previsión basada en el aprendizaje automático\, cuándo es probable que ML mejore sus previsiones\, cómo utilizar la opción ML completamente automática en Forecast Pro y cómo crear modelos AA personalizados en Forecast Pro. \nRegresión Dinámica\nUn análisis detallado de los pros y contras de los pronósticos de regresión. Los temas incluyen cuándo es mejor aplicar modelos de regresión\, cómo construir estos modelos\, mínimos cuadrados ordinarios\, indicadores que conducen un comportamiento\, variables defasadas\, modelos Cochrane-Orcutt\, prueba de hipótesis y el uso de variables “dummy”. \n\n\nRegistro\n\n15-17 de febrero\nTaller En Línea\nRegistro\n\n\nCosto del Registro: El costo de registro es de $495 USD por participante. Un Descuento de Equipo se encuentra disponible para organizaciones que registren a 3 o más participantes. \nNúmero de Participantes: Debido a la naturaleza interactiva de las presentaciones en vivo\, la asistencia se limita a 25 participantes. \nHorario:  \n15-17 de febrero: El taller será impartido de 9:00 am a 1:30 pm cada día (Hora Estándar Central (UTC/GMT -6)). La sesión de horas de consulta libre se llevará a cabo de 9:00 a.m. a 11:00 a.m. martes\, 22 de febrero. \nPolíticas de Cancelación: El taller tiene un cupo limitado y le pedimos que si requiere cancelar nos informe lo antes posible. Los participantes podrán recibir un reembolso total si su cancelación se realiza 14 días o más anteriores al inicio del taller. Los participantes que no se presenten o no realicen la cancelación con mínimo 14 días de anticipación no recibirán un reembolso. Sustitución de participantes se puede realizar en cualquier momento. \n\n\n\n\n\n\n\n\nInstructores\nEste taller está siendo presentado por FBP Systems\, en colaboración con Business Forecast Systems\, para apoyar a la comunidad de pronósticos de habla hispana. \n\nArmando González \nArmando González es el director de FBP Sytems\, un distribuidor autorizado de Forecast Pro. Armando es también un Consultor Internacional con muchos años de experiencia en la implantación de procesos de pronósticos\, mejora de procesos con simulación\, así como análisis y modelado de negocios. Ha impartido innumerables cursos de técnicas de pronósticos\, simulación de procesos y modelos de toma de decisiones para múltiples en México y Latinoamérica. Entre algunas de estas empresas: Coca Cola\, Merck\, Heinz\, Eaton\, Brigthstar\, General Mills\, Etc. Armando es un colaborador en la traducción al español del software de pronósticos estadísticos para negocios\, Forecast Pro y es un instructor de Forecast Pro\, herramienta de pronósticos y planeación de demanda. \n  \n\n\nDaniel González\nDaniel González ha colaborado con FBP Systems y BFS desde 2017. Colaborador en la traducción del Manual de Usuarios de Forecast Pro versión español. Actualmente se especializa en Administración de la Cadena de Suministro en Humber College\, localizado en Canadá. Su experiencia en el entorno global le ha proporcionado conocimiento y herramientas útiles a través de una variedad de industrias. \n\n\n\n\n\n\n\n15-17 de febrero\nTaller En Línea\nRegistro
URL:https://www.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-october-2021-spanish/
LOCATION:Taller Interactivo Virtual En Vivo
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/07/Februrary-2022-Spanish-Workshop-Image-SMALL.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220127T133000
DTEND;TZID=America/New_York:20220127T143000
DTSTAMP:20260417T180907
CREATED:20220107T162535Z
LAST-MODIFIED:20220125T222722Z
UID:10000056-1643290200-1643293800@www.forecastpro.com
SUMMARY:Free Webinar: Practical Strategies for Forecasting Weekly and Daily Data
DESCRIPTION:Click Here to Register Now!\nDescription:\nCreating accurate weekly or daily forecasts is more challenging than creating accurate monthly forecasts\, but if this is what your business requires\, don’t worry! There are several practical approaches— including some that are often overlooked— that your team can adopt to improve your weekly or daily forecasts. \nIn this live one-hour educational webinar\, Eric Stellwagen and Sarah Darin will discuss strategies for forecasting weekly and daily data\, and some issues that may come up when working with this data. Through real-life case studies you will learn practical approaches for: \n\ndefining the calendar\naccommodating week 53\ncorrecting for the number working days\ntracking holidays\nforecasting multiple cycles (e.g.\, day of week and week of year)\nconverting between different periodicities\n\nEric and Sarah will also demonstrate multiple approaches\, including seasonal simplification\, event models and machine learning\, that can improve daily and weekly forecast accuracy in Forecast Pro. \nCan’t attend the live webinar? Register for the session and we will notify you via email when the recording is available for on-demand viewing. \n  \nClick Here to Register Now!\n 
URL:https://www.forecastpro.com/event/free-webinar-practical-strategies-for-forecasting-weekly-and-daily-data/
LOCATION:Online Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2022/01/roman-bozhko-PypjzKTUqLo-unsplash001.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20211207
DTEND;VALUE=DATE:20211210
DTSTAMP:20260417T180907
CREATED:20210621T210633Z
LAST-MODIFIED:20211101T224546Z
UID:10000053-1638835200-1639094399@www.forecastpro.com
SUMMARY:Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:December 7-9\nOnline Workshop\nRegistration\n\n15-17 de febrero\nTaller En Línea\nRegistro\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\n\n\nDecember 7-9\nOnline Workshop\nRegistration\n\n15-17 de febrero\nTaller En Línea\nRegistro\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:  \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. \n15-17 de febrero: El taller será impartido de 9:00 am a 1:30 pm cada día (Hora Estándar Central (UTC/GMT -6)). La sesión de horas de consulta libre se llevará a cabo de 9:00 a.m. a 11:00 a.m. martes\, 22 de febrero. \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\n\n\nDecember 7-9\nOnline Workshop\nRegistration\n\n15-17 de febrero\nTaller En Línea\nRegistro
URL:https://www.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-december-2021/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/06/COMPRESSED-BFS-December-2021-Workshop-Image-2mp.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Mexico_City:20211117T090000
DTEND;TZID=America/Mexico_City:20211117T100000
DTSTAMP:20260417T180907
CREATED:20210908T182129Z
LAST-MODIFIED:20211025T223609Z
UID:10000058-1637139600-1637143200@www.forecastpro.com
SUMMARY:Seminario Web Gratuito | ¿Qué es Suavización Exponencial y Cuándo Debería Utilizarlo?
DESCRIPTION:¡Regístrate Ahora!\nDescripción:\nNo es de extrañar que muchos forecasters prefieran los modelos de suavización exponencial: son fáciles de aplicar\, generan pronósticos precisos y pueden automatizarse. Acompáñanos en este seminario web gratuito para aprender sobre las ventajas y desventajas de estos métodos de pronósticos populares y aprende cómo mejorar tus pronósticos utilizando modelos de suavización exponencial. \n  \nAl final de este seminario web de una hora\, aprenderás: \n\nCuándo utilizar suavización exponencial\nCómo construir modelos de suavización exponencial\nCómo interpretar los resultados para tomar decisiones comerciales\n\n  \n¿Quién debería asistir?\nEste seminario web es de gran valor para cualquier persona cuyas responsabilidades en el trabajo incluyan la preparación o análisis de pronósticos – tener conocimiento previo de estadística no es esencial para este Webinar. Durante el Webinar se hablará sobre los detalles de suavización exponencial\, una descripción profunda de estos métodos y se proporcionarán las herramientas para que puedas aplicar de manera efectiva modelos de suavización exponencial a tus propios datos. \n  \nInstructor: \nArmando González\, director de FBP Systems\, se basará en su amplia experiencia en el área de pronósticos de negocios para proporcionar una explicación completa de estos métodos de pronósticos populares. \n  \nEste seminario web está siendo presentado por FBP Systems\, en colaboración con Business Forecast Systems\, para apoyar a la comunidad de pronósticos de habla hispana. \n  \n¿No puedes asistir al seminario web en vivo? Regístrate para la sesión y te notificaremos cuando la grabación esté disponible para su reproducción. \n  \n¡Regístrate Ahora!\n 
URL:https://www.forecastpro.com/event/seminario-web-gratuito-suavizacion-exponencial/
LOCATION:Seminario Web en Línea
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/09/Spanish-Exponential-Smoothing-Webinar-2MP.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211028T133000
DTEND;TZID=America/New_York:20211028T143000
DTSTAMP:20260417T180907
CREATED:20210802T202823Z
LAST-MODIFIED:20210927T214956Z
UID:10000059-1635427800-1635431400@www.forecastpro.com
SUMMARY:Free Webinar: How to Forecast New Products
DESCRIPTION:Click Here to Register Now!\nDescription:\nLet’s face it—forecasting new products is difficult. With little or no historic data\, many traditional forecasting methods just won’t work. \nSo how do you forecast new products? \nIn this one-hour webinar\, Eric Stellwagen and Sarah Darin will share some insights. They will survey different approaches for effectively forecasting new products and discuss the role of judgment and market research. \nEric and Sarah will review the following classifications for new products and discuss pros and cons of various forecasting methods used for each category: \n\nReplacement products\nProduct line extensions\nNew-to-company products\nNew-to-world products\n\nUsing real-world examples\, Eric and Sarah will demonstrate popular methods for new product forecasting including product mapping (aka item supersession)\, forecasting by analogy\, custom component models\, assumption-based models and the Bass diffusion model. \nCan’t attend the live webinar? Register for the session and we will notify you via email when the recording is available for on-demand viewing. \n  \nClick Here to Register Now!\n 
URL:https://www.forecastpro.com/event/free-webinar-how-to-forecast-new-products/
LOCATION:Online Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/08/October-2021-Webinar-no-overlay-Compressed.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20211026
DTEND;VALUE=DATE:20211029
DTSTAMP:20260417T180907
CREATED:20210712T211824Z
LAST-MODIFIED:20211101T225128Z
UID:10000060-1635206400-1635465599@www.forecastpro.com
SUMMARY:Live Online Workshop: Business Forecasting Techniques\, Best Practices & Application Using Forecast Pro
DESCRIPTION:December 7-9\nOnline Workshop\nRegistration\n\n15-17 de febrero\nTaller En Línea\nRegistro\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\n\n\nDecember 7-9\nOnline Workshop\nRegistration\n\n15-17 de febrero\nTaller En Línea\nRegistro\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:  \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. \n15-17 de febrero: El taller será impartido de 9:00 am a 1:30 pm cada día (Hora Estándar Central (UTC/GMT -6)). La sesión de horas de consulta libre se llevará a cabo de 9:00 a.m. a 11:00 a.m. martes\, 22 de febrero. \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\nThis workshop is presented by Supply Chain Business Solutions\, in collaboration with Business Forecast Systems\, to support the forecasting community in the Asia Pacific Region. \n\nDinesh Shah\n \n \nDinesh Shah is Founder and Director of Supply Chain Business Solutions\, an authorized Forecast Pro distributor. Dinesh 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\n\n\nDecember 7-9\nOnline Workshop\nRegistration\n\n15-17 de febrero\nTaller En Línea\nRegistro
URL:https://www.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-october-2021/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210921
DTEND;VALUE=DATE:20210924
DTSTAMP:20260417T180907
CREATED:20210401T170002Z
LAST-MODIFIED:20210923T211213Z
UID:10000049-1632182400-1632441599@www.forecastpro.com
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://www.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-september-2021/
LOCATION:Live Online Interactive Workshop
CATEGORIES:Forecast Pro Event
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BEGIN:VEVENT
DTSTART;TZID=America/Mexico_City:20210824T100000
DTEND;TZID=America/Mexico_City:20210824T110000
DTSTAMP:20260417T180907
CREATED:20210802T202241Z
LAST-MODIFIED:20210803T160559Z
UID:10000061-1629799200-1629802800@www.forecastpro.com
SUMMARY:Seminario Web Gratuito |  Precisión y Evaluación de los Pronósticos: un paso esencial para mejorar tu proceso de pronósticos
DESCRIPTION:¡Regístrate Ahora!\nDescripción:\nPara mejorar el proceso de pronóstico en su organización\, es fundamental medir y monitorear el desempeño para saber qué está funcionando y qué no. Puede lograr esto y obtener otros beneficios importantes si realiza un seguimiento de la precisión del pronóstico. En esta sesión educativa de una hora aprenderás: \n  \n\nPor qué es importante realizar un seguimiento de la precisión\nLas diferencias entre errores dentro y fuera de la muestra\nEnfoques para medir el error de pronóstico\nLos pros y los contras de las medidas de precisión populares\nCómo implementar el seguimiento de precisión\nCómo los informes de excepciones pueden agilizar el proceso de revisión\n\n  \nEn este seminario web en vivo de una hora\, Armando González\, director de FBP Systems\, demostrará cómo aplicar las mejores prácticas y evitar errores comunes utilizando ejemplos con datos corporativos reales. Este seminario web está siendo presentado por FBP Systems\, en colaboración con Business Forecast Systems\, para apoyar a la comunidad de pronósticos de habla hispana. \n  \n¿No puede asistir al seminario web en vivo? Regístrate para la sesión y te notificaremos cuando la grabación esté disponible para su reproducción. \n  \n¡Regístrate Ahora!\n 
URL:https://www.forecastpro.com/event/seminario-web-gratuito-precision-y-evaluacion-de-los-pronosticos/
LOCATION:Seminario Web en Línea
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/08/Accuracy-w-FP-logo-compressed.png
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210722T133000
DTEND;TZID=America/New_York:20210722T143000
DTSTAMP:20260417T180907
CREATED:20210429T164159Z
LAST-MODIFIED:20210622T162707Z
UID:10000051-1626960600-1626964200@www.forecastpro.com
SUMMARY:Free Webinar: What Is Machine Learning — and Will It Improve My Forecasts?
DESCRIPTION:Click Here to Register Now!\nDescription:\nMachine Learning and AI have emerged as transformational methodologies with a multitude of applications—facial recognition\, medical diagnosing and self-driving cars—to name a few. \nBut can Machine Learning be used to improve your forecasting? Recent forecasting research suggests that it can. \nIn this webinar Sarah Darin overviews the basics and benefits of automated Extreme Gradient Boosting (XG Boost)\, an effective and accurate Machine Learning algorithm recently implemented in Forecast Pro. \nDuring this one-hour webinar you will learn: \n\nThe basics of Machine Learning powered forecasting\nWhen ML is likely to improve your forecasts\nHow to use the completely automatic ML option in Forecast Pro\nHow to build custom ML models in Forecast Pro\n\n  \nClick Here to Register Now!\n 
URL:https://www.forecastpro.com/event/free-webinar-what-is-machine-learning-and-will-it-improve-my-forecasts/
LOCATION:Online Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/04/ML-Webinar-Image-FINAL.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210715T133000
DTEND;TZID=America/New_York:20210715T143000
DTSTAMP:20260417T180907
CREATED:20210708T175615Z
LAST-MODIFIED:20210819T211259Z
UID:10000055-1626355800-1626359400@www.forecastpro.com
SUMMARY:Free Webinar: What’s New in Forecast Pro TRAC v7?
DESCRIPTION:Click Here to Register Now!\nDescription:\nIntroducing Forecast Pro TRAC Version 7!\nIn this one-hour webinar\, Erik Subatis and Sarah Darin will provide an overview of four new functionalities in Version 7: \n• Machine Learning\n• Product Mapping\n• Forecast Value Add Reporting\n• Excel Collaboration Enhancements\nThis webinar will demonstrate how to use these new functionalities in Forecast Pro using real-life examples.\nCan’t attend the live webinar? Register for the session and we will notify you when the recording is available for on-demand viewing. \nClick Here to Register Now!\n 
URL:https://www.forecastpro.com/event/free-webinar-whats-new-in-forecast-pro-trac-v7/
LOCATION:Online Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/07/Whats-New-in-Forecast-Pro-TRAC-v7-Webinar-Image-adjusted-for-site.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210525
DTEND;VALUE=DATE:20210528
DTSTAMP:20260417T180907
CREATED:20210127T194919Z
LAST-MODIFIED:20220121T185037Z
UID:10000047-1621900800-1622159999@www.forecastpro.com
SUMMARY:Taller En Línea: Técnicas de Pronósticos de Demanda\, Mejores Prácticas y Aplicaciones Utilizando Forecast Pro
DESCRIPTION:15 – 17 de febrero\nTaller En Línea\n  \nConozca más sobre el taller en línea del 15 al 17 de febrero.\nDescripción del Taller\nAl finalizar este extenso taller de 3 días\, los participantes tendrán conocimiento y comprensión de técnicas de pronósticos\, incluyendo su funcionamiento y aplicación en un ambiente de negocios real. El taller se enfoca en los métodos de pronósticos de demanda que son más comúnmente utilizados\, explica conceptualmente cómo funcionan\, discute sus ventajas y desventajas\, y demuestra las mejores prácticas para implementarlos en un ambiente de trabajo real utilizando Forecast Pro. \nEl taller consta de 12 horas de presentaciones en vivo\, distribuidas a lo largo de 3 días. En estas sesiones tendrás la oportunidad de hacer preguntas a los instructores en tiempo real\, así como interactuar con los demás participantes. \nEl taller también incluye un acceso por 2 semanas al canal de streaming del taller y una sesión de 2 horas de consulta libre. El canal de streaming proporciona acceso a versiones pregrabadas de los 8 módulos presentados durante el taller\, así como 3 módulos adicionales que no son cubiertos en las sesiones en vivo. Las horas de consulta libre consisten en un periodo de 2 horas la semana posterior al taller donde los instructores se encontrarán disponibles para contestar preguntas sobre los temas cubiertos en el taller. \n\n¿Quién debería asistir?\nEl taller es de gran valor para cualquier persona cuyas responsabilidades en el trabajo incluyan la preparación o análisis de pronósticos – tener conocimiento previo de estadística no es esencial para este taller. Los tutoriales utilizan Forecast Pro y datos de casos reales para proporcionar un entendimiento a fondo de los métodos de pronósticos y para demostrar las mejores prácticas; estas lecciones son aplicables sin importar el programa o software de pronósticos que tu organización utilice. \n\n  \n\n\n\n\nAgenda At-a-GlanceDescripción de las PresentacionesAgenda At-a-Glance\nDía 1\nIntroducción a los Pronósticos \nSuavización Exponencial \nDía 2\nExtensiones de Suavización Exponencial \nPrecisión y Evaluación de los Pronósticos \nIdentificando Problemas en tu Proceso de Pronósticos \nDía 3\nModelos de Índices de Eventos \nPronósticos en Múltiples Niveles \nPronósticos de Productos Nuevos \nPresentaciones Adicionales Reproducibles\nComponentes de los Datos \nModelos Box-Jenkins (ARIMA) \nRegresión Dinámica \nDescripción de las Presentaciones\nIntroducción a los Pronósticos\nUna vista general a los pronósticos de la demanda y sus múltiples usos dentro de una organización. Los temas incluyen enfoques de pronósticos\, características de los datos\, el rol del juicio y experiencia\, selección de métodos de pronósticos apropiados para conjuntos de datos variados y recursos para Forecasters. \nComponentes de los Datos\nUn vistazo a profundidad de los distintos componentes encontrados en datos de series de tiempo incluyendo tendencia\, patrones estacionales\, ciclos de negocios\, variaciones por días del calendario\, intervenciones (eventos) y ruido. La discusión incluye las formas que pueden tomar los componentes\, detección de componentes locales vs. globales\, interpretación de indicadores de ciclos de negocios y el uso de rutinas de descomposición. \nSuavización Exponencial\nUna variedad de técnicas de suavización exponencial con un énfasis particular en la familia de modelos Holt-Winters. Los temas incluyen las ventajas y desventajas de utilizar estos modelos\, cuándo es mejor utilizarlos\, cómo funcionan\, identificación de componentes del modelo\, optimización de parámetros y diagnóstico de modelos. \nExtensiones de Suavización Exponencial\nEsta sesión analiza tres útiles extensiones a la familia de modelos de suavización exponencial. La primera es el modelo NA-CL que usualmente mejorará la precisión de los pronósticos para conjuntos de datos que muestran una “demanda de temporada” donde la mayoría de la demanda ocurre en momentos específicos del año (por ejemplo\, vacunas contra la influenza). La segunda es el Modelo de Demanda Intermitente de Croston que es utilizado para pronosticar datos que muestran periodos con demanda de cero frecuentemente. La tercera es el Modelo de Componentes Personalizados que permite estimar algunos componentes desde los datos y que el Forecaster los ajuste. \nModelos Box-Jenkins (ARIMA)\nUn análisis del uso de los modelos ARIMA para pronósticos de la demanda. Los temas incluyen las ventajas y desventajas de utilizar estos modelos\, cómo y cuándo deben de ser aplicados\, procedimientos de identificación automática y diagnósticos de modelos. \nPrecisión y Evaluación de los Pronósticos\nUn análisis detallado a la evaluación de la precisión de los métodos de pronósticos. Los temas incluyen la diferenciación entre errores del modelo y fuera de la muestra\, una variedad de estadísticas para medición de errores\, un resumen de resultados de competencias de pronósticos y una explicación sobre cómo utilizar reportes de seguimiento y realizar simulaciones como técnica de predicción de desempeño del modelo. \nIdentificando Problemas en tu Proceso de Pronósticos\nEnfoques para concentrarse en artículos críticos cuando se pronostican grandes cantidades de datos. Los temas incluyen la evaluación y generación de pronósticos a niveles de artículo\, clasificación ABC (Pareto) y filtros\, detección y corrección de datos atípicos\, reportes de excepciones y medición de precisión en múltiples series de tiempo. \nModelos de Índices de Eventos\nLos modelos de índices de eventos extienden la funcionalidad de los modelos de suavización exponencial al proporcionar ajustes para promociones\, paros o faltantes y otros eventos que no se basan en el calendario regular. Esta sesión habla sobre cómo funcionan estos modelos\, cómo y cuándo deben ser utilizados y cómo personalizar su diseño para que se ajuste mejor a tus necesidades. \nPronósticos en Múltiples Niveles\nEsta sesión analiza las técnicas de pronósticos de jerarquías. Los temas incluyen la necesidad de pronósticos en diferentes niveles\, jerarquías de producto vs. geográficas\, estrategias de reconciliación\, enfoques top-down vs. bottom-up\, el uso de asignación proporcional y ajustes de estacionalidad. \nPronósticos de Productos Nuevos\nEsta sesión analiza una variedad de enfoques para pronósticos de productos nuevos. Los temas abarcan las ventajas y desventajas de diferentes métodos basados en la clasificación de un nuevo producto y una revisión de métodos típicos incluyendo remplazos de artículos\, pronóstico por analogía y el modelo de difusión de Bass. \nRegresión Dinámica\nUn análisis detallado de los pros y contras de los pronósticos de regresión. Los temas incluyen cuándo es mejor aplicar modelos de regresión\, cómo construir estos modelos\, mínimos cuadrados ordinarios\, indicadores que conducen un comportamiento\, variables defasadas\, modelos Cochrane-Orcutt\, prueba de hipótesis y el uso de variables “dummy”. \n\n\nRegistro\n\n15 – 17 de febrero\nTaller En Línea\n\n\nCosto del Registro: El costo de registro es de $495 USD por participante. Un Descuento de Equipo se encuentra disponible para organizaciones que registren a 3 o más participantes. \nNúmero de Participantes: Debido a la naturaleza interactiva de las presentaciones en vivo\, la asistencia se limita a 25 participantes. \nHorario: El taller será impartido de 9:00 am a 1:00 pm cada día (Hora De Verano Central (UTC/GMT -5)) con 30 minutos adicionales que serán dedicados a aclarar dudas de los participantes. La sesión de horas de consulta libre se llevará a cabo de 9:00 a.m. a 11:00 a.m. el primer martes posterior al taller. \nPolíticas de Cancelación: El taller tiene un cupo limitado y le pedimos que si requiere cancelar nos informe lo antes posible. Los participantes podrán recibir un reembolso total si su cancelación se realiza 14 días o más anteriores al inicio del taller. Los participantes que no se presenten o no realicen la cancelación con mínimo 14 días de anticipación no recibirán un reembolso. Sustitución de participantes se puede realizar en cualquier momento. \n\n\n\n\n\n\n\nInstructores\n\nArmando González \nArmando González es un Consultor Internacional con muchos años de experiencia en la implantación de procesos de pronósticos\, mejora de procesos con simulación\, así como análisis y modelado de negocios. Ha impartido innumerables cursos de técnicas de pronósticos\, simulación de procesos y modelos de toma de decisiones para múltiples en México y Latinoamérica. Entre algunas de estas empresas: Coca Cola\, Merck\, Heinz\, Eaton\, Brigthstar\, General Mills\, Etc. Armando es un colaborador en la traducción al español del software de pronósticos estadísticos para negocios\, Forecast Pro y es un instructor de Forecast Pro\, herramienta de pronósticos y planeación de demanda. \n  \n\n\nDaniel González\nDaniel González ha colaborado con FBP Systems y BFS desde 2017. Colaborador en la traducción del Manual de Usuarios de Forecast Pro versión español. Actualmente se especializa en Administración de la Cadena de Suministro en Humber College\, localizado en Canadá. Su experiencia en el entorno global le ha proporcionado conocimiento y herramientas útiles a través de una variedad de industrias. \n  \n\n\n\n\n15 – 17 de febrero\nTaller En Línea
URL:https://www.forecastpro.com/event/workshop-forecasting-techniques-applications-and-best-practices-may-2021-spanish/
LOCATION:Taller Interactivo Virtual En Vivo
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/01/SOLD-OUT-Spanish-Workshop-Image-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210511
DTEND;VALUE=DATE:20210514
DTSTAMP:20260417T180907
CREATED:20201222T155532Z
LAST-MODIFIED:20210520T153112Z
UID:10000046-1620691200-1620950399@www.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://www.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://www.forecastpro.com/wp-content/uploads/2020/12/SOLD-OUT-BFS-May-2021-Workshop-Image-SMALL-.png
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210429T143000
DTEND;TZID=America/New_York:20210429T153000
DTSTAMP:20260417T180907
CREATED:20210412T201607Z
LAST-MODIFIED:20211021T165052Z
UID:10000050-1619706600-1619710200@www.forecastpro.com
SUMMARY:Free Live Webinar | Staying On Track: How to Prevent Short-Term Forecast Uncertainty From Derailing Your Long-Term Demand Planning
DESCRIPTION:April 29\, 2021 @ 2:30pm – 3:30pm EDT\nClick Here to Register Now!\nDescription:\nIf the past year has taught us anything\, it is that unusual times create great uncertainty\, particularly when it comes to short-term forecasting. During these times it is natural to become reactive and focus on the short-term\, however\, losing sight of your long-term demand planning assumptions can be a recipe for disaster. \n  \nDuring this webinar\, Timm Reiher and Todd Ferguson\, two demand management experts from Oliver Wight will discuss strategies for managing uncertainty and explore techniques in demand planning to help you bridge the short and the long term. The webinar will also include a demonstration of how to use the Forecast Pro software to generate both short and longer-term forecasts. \n  \nBy the end of this one-hour webinar you will learn: \n\nHow inaccurate short-term forecasts can influence long-term planning\nHow to apply demand planning strategies that bridge the short and long term\nHow to manage unconstrained demand in a constrained supply environment\nHow to prepare forecasts when it is not business as usual\n\n  \nClick Here to Register Now!\n\nSpeakers: \nTimm Reiher\n \n \nTimm Reiher\, an Oliver Wight principal\, is an expert in Demand Management\, Sales Operations\, Product and Portfolio Management\, Integrated Business Planning\, and is a Certified Instructor for the Oliver Wight Demand Management and Demand Labs executive education courses. With more than 20 years of experience in industry\, his background spans product management\, sales and account management\, customer service\, sales operations\, data warehouse systems\, and CRM (customer relationship management) improvement initiatives. \n  \nSince joining the Oliver Wight team\, Timm has worked with a wide range companies and industries including government (Department of Defense)\, consumer packaged goods\, food and produce\, farming\, chemicals\, high-tech\, packaging\, pharmaceutical\, and heavy industry. Timm is skilled at assessing current company practices\, coaching and facilitating the design of best-practice future states\, and providing “shoulder-to-shoulder” support for practitioners and business leaders while implementing all aspects of Integrated Business Planning including Demand Management and Product Innovation. \nTodd Ferguson \n \nTodd Ferguson\, an Oliver Wight principal\, offers insights and solutions to help companies achieve improved financial performance. His background includes over two decades of experience in sales\, order fulfillment\, demand management and Integrated Business Planning across a wide variety of industries. Current and former clients include Cargill\, Dow Chemical\, Facebook\, General Electric\, Tiffany and Zeus Industrial Products. \n  \nTodd’s experience includes people and process improvement and hands-on implementation of tools including SAP APO Demand Planning. He led the implementation of a Demand Management function for Weir Oil & Gas\, an upstream oil and gas leader that specializes in the manufacture of high-pressure well service pumps and related flow control equipment. In this role\, he drew on his skill as a Demand Planning expert to help define and continuously improve the company’s Integrated Business Planning process. Todd has a deep understanding of the underlying tools required to support an effective Demand Management process. \n  \nClick Here to Register Now!\n 
URL:https://www.forecastpro.com/event/free-live-webinar-staying-on-track-how-to-prevent-short-term-forecast-uncertainty-from-derailing-your-long-term-demand-planning/
LOCATION:Online Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2021/04/April-2021-Webinar-Image-SMALL-HIGHER-LOGOS.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210420
DTEND;VALUE=DATE:20210423
DTSTAMP:20260417T180907
CREATED:20210224T185307Z
LAST-MODIFIED:20210819T171051Z
UID:10000048-1618876800-1619135999@www.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://www.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://www.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:20260417T180907
CREATED:20201021T143035Z
LAST-MODIFIED:20210506T221020Z
UID:10000043-1612828800-1613087999@www.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://www.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://www.forecastpro.com/wp-content/uploads/2020/10/SOLD-OUT-Feb-21-Workshop-image-FP-LOGO.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210128T110000
DTEND;TZID=America/New_York:20210128T120000
DTSTAMP:20260417T180907
CREATED:20201222T154547Z
LAST-MODIFIED:20210105T230805Z
UID:10000045-1611831600-1611835200@www.forecastpro.com
SUMMARY:Free Live Webinar: What is Exponential Smoothing and When Should I Use it?
DESCRIPTION:Click Here to Register Now!\nDescription:\nIt is no surprise that exponential smoothing models are favored by many corporate forecasters — they are easy to apply\, create accurate forecasts\, and can be automated. Join this free live webinar to understand the pros and cons of these popular forecasting methods\, and learn how to improve your forecasts using exponential smoothing models. \n  \nBy the end of this one-hour webinar you will learn: \n\nWhen to use exponential smoothing\nHow to build exponential smoothing models\nHow to interpret the results to drive your business decisions\n\n  \nWho Should Attend:\nIf your job responsibilities include preparing or analyzing forecasts\, this webinar is for you! The webinar will discuss the ins and outs of exponential smoothing\, providing a deeper understanding of these methods and allowing you to effectively apply exponential smoothing models to your own data. \nSpeakers: \nEric Stellwagen and Sarah Darin will draw from their extensive expertise in forecasting approaches to provide a comprehensive overview of these popular forecasting methods.
URL:https://www.forecastpro.com/event/free-live-webinar-exponential-smoothing/
LOCATION:Free Live Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2020/12/001-FP-Logo-Exponential-Smoothing-Man-On-Computer-1-2-e1609885879713.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201211T090000
DTEND;TZID=America/New_York:20201211T100000
DTSTAMP:20260417T180907
CREATED:20201023T201447Z
LAST-MODIFIED:20201222T154659Z
UID:10000044-1607677200-1607680800@www.forecastpro.com
SUMMARY:Free Live Webinar: Pragmatic Insight on Forecasting During the Global Pandemic
DESCRIPTION:Click Here to Register Now!\n  \nSarah Darin and Erik Subatis will be guest presenters as part of the Centre for Marketing Analytics and Forecasting (CMAF) of Lancaster University’s “Friday Forecasting Talks” webinar series. \nAbstract: Just as the COVID-19 pandemic has disrupted all our lives\, it has had a major impact on virtually all businesses. While some businesses have seen demand surge\, others have seen it plummet. While some businesses continue to observe a disruptive influence on demand\, others have seen demand stabilize to a new normal. Many companies continue to struggle with stockouts and longer lead times. \nThis webinar will provide pragmatic insight into how to use Forecast Pro’s methods and techniques to create accurate forecasts during the global pandemic. Drawing upon their extensive expertise in forecasting approaches that have been successfully used during this and other business disruptions\, Sarah and Erik will provide an overview of how Forecast Pro can be used to account for the impact of Covid-19 in statistical models and how to efficiently integrate judgmental overrides in large scale forecasting projects. Erik and Sarah will profile several business categories\, review the methods that are best suited to each group and demonstrate these approaches in Forecast Pro TRAC using real-world examples. \nAbout CMAF’s “Friday Forecasting Talks”: Centre for Marketing Analytics and Forecasting of Lancaster University is organizing a series of free webinars\, called “Friday Forecasting Talks”. These webinars will consist of six talks loosely united by the idea of reducing the gap between research and practice\, delivered by academics and practitioners. \n\n  \n \nClick Here To Register Now!\n \nCMAF Friday Forecasting Talks
URL:https://www.forecastpro.com/event/free-live-webinar-pragmatic-insight-on-forecasting-during-the-global-pandemic-2/
LOCATION:Free Live Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2020/09/covid-meeting-with-FP-logo.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20201117
DTEND;VALUE=DATE:20201120
DTSTAMP:20260417T180907
CREATED:20200730T150834Z
LAST-MODIFIED:20201029T162054Z
UID:10000041-1605571200-1605830399@www.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://www.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://www.forecastpro.com/wp-content/uploads/2020/07/November-Workshop_with_FPLogo-SOLD-OUT-.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201022T110000
DTEND;TZID=America/New_York:20201022T120000
DTSTAMP:20260417T180907
CREATED:20200902T143316Z
LAST-MODIFIED:20201022T202615Z
UID:10000042-1603364400-1603368000@www.forecastpro.com
SUMMARY:Free Live Webinar: Forecasting Demand in the Face of a Pandemic: What now?
DESCRIPTION:Click Here to Register Now!\n  \nAt the onset of the pandemic\, BFS presented webinars intended to provide guidance on how to create your forecasts throughout all phases of a pandemic—including the initial stage\, the uncertain months ahead and the subsequent “new normal”. In this webinar\, James Berry\, Director of Training and Sarah Darin\, Senior Consultant\, will provide updated guidance on forecasting in the midst of a pandemic\, now that we are well immersed in the current crisis and have a better understanding of how businesses have been impacted. Using real data\, James and Sarah will provide an overview of the Forecast Pro methods and techniques that can help you generate more accurate forecasts as we enter a “new normal”. \nWe anticipate that this webinar will include an extended Q&A session\, and we encourage people to reach out in advance with questions you may have. If you would like to submit a question in advance\, please email sdarin@forecastpro.com with subject line “Webinar question”.
URL:https://www.forecastpro.com/event/free-live-webinar-forecasting-demand-in-the-face-of-a-pandemic-what-now/
LOCATION:Free Live Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2020/09/covid-meeting-with-FP-logo.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200922
DTEND;VALUE=DATE:20200925
DTSTAMP:20260417T180907
CREATED:20200714T203805Z
LAST-MODIFIED:20200908T205802Z
UID:10000040-1600732800-1600991999@www.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://www.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://www.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:20260417T180907
CREATED:20200630T205359Z
LAST-MODIFIED:20200730T150902Z
UID:10000039-1597708800-1597967999@www.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://www.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://www.forecastpro.com/wp-content/uploads/2020/07/August-Workshop_with_FPLogo-SOLD-OUT.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200721
DTEND;VALUE=DATE:20200724
DTSTAMP:20260417T180907
CREATED:20190805T132451Z
LAST-MODIFIED:20200720T133007Z
UID:10000033-1595289600-1595548799@www.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://www.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://www.forecastpro.com/wp-content/uploads/2020/06/July-Workshop_with_FPLogo-.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200716T110000
DTEND;TZID=America/New_York:20200716T120000
DTSTAMP:20260417T180907
CREATED:20200622T165221Z
LAST-MODIFIED:20200701T120402Z
UID:10000038-1594897200-1594900800@www.forecastpro.com
SUMMARY:Free Live Webinar: How Bell’s Brewery Improved Supply Planning with Forecast Pro
DESCRIPTION:Click Here to Register Now!\n  \nIn this webinar\, Blake Violette\, Forecast Manager at Bells Brewery\, will discuss implementing Forecast Pro and how to manage a successful first year.  Blake will give an overview of some of the challenges Bell’s Brewery faced in their implementation process\, as well as some of the benefits they have reaped from integrating Forecast Pro into their forecasting and S&OP processes
URL:https://www.forecastpro.com/event/free-live-webinar-how-bells-brewery-improved-supply-planning-with-forecast-pro/
LOCATION:Free Live Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2020/06/selective-focus-photography-of-people-having-a-toast-full-with-fp-logo.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200428T103000
DTEND;TZID=America/New_York:20200428T113000
DTSTAMP:20260417T180907
CREATED:20200423T164937Z
LAST-MODIFIED:20211013T154129Z
UID:10000036-1588069800-1588073400@www.forecastpro.com
SUMMARY:Free Live Webinar: Forecasting Demand in the Face of a Pandemic
DESCRIPTION:Click Here to Register Now!\n  \nJust as the COVID-19 pandemic is disrupting all of our lives\, it is having a major impact on virtually all businesses. You are probably wondering how to create your demand forecasts given the pervasive uncertainty that this unprecedented global event has triggered. \nIn this Webinar Eric Stellwagen\, CEO\, and Sarah Darin\, Senior Consultant\, will provide pragmatic insight into how to create your forecasts throughout all phases of the pandemic—including the current initial stage\, the uncertain months ahead and the subsequent “new normal” that will emerge. Drawing upon their extensive expertise in forecasting approaches that have been successfully used during other business disruptions\, they will profile several business categories\, review the methods that are best suited to each group and demonstrate these approaches in Forecast Pro TRAC using real-world examples. \nNote: even if you can’t attend the live Webinar\, by registering now you will be automatically notified when the recorded session is available for viewing on demand.
URL:https://www.forecastpro.com/event/free-live-webinar-forecasting-demand-in-face-of-pandemic/
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2020/04/cvirus-connection-4884862_1920.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200123T133000
DTEND;TZID=America/New_York:20200123T143000
DTSTAMP:20260417T180907
CREATED:20191021T202916Z
LAST-MODIFIED:20210322T140339Z
UID:10000035-1579786200-1579789800@www.forecastpro.com
SUMMARY:Free Live Webinar: Tracking Accuracy: An Essential Step to Improve Your Forecasting Process
DESCRIPTION:Click Here to Register Now!\n  \nTo improve the forecasting process in your organization\, it is critical to measure and monitor performance to know what is working and what isn’t. You can achieve this—and realize other significant benefits—by tracking forecast accuracy. In this educational one-hour session you will learn: \n• Why it is important to track accuracy\n• The differences between within-sample and out-of-sample errors\n• Approaches to measuring forecast error\n• The pros and cons of popular accuracy measures\n• How to implement accuracy tracking\n• How exception reports can streamline the review process \nIn this one-hour live Webinar\, Eric Stellwagen\, CEO\, and Sarah Darin\, Senior Consultant at Business Forecast Systems\, Inc.\, will demonstrate how to apply best practices and avoid common pitfalls using examples with real corporate data. \nNote: even if you can’t attend the live Webinar\, by registering now you will be automatically notified when the recorded session is available for viewing on demand.
URL:https://www.forecastpro.com/event/free-live-webinar-tracking-accuracy-an-essential-step-to-improve-your-forecasting-process/
LOCATION:Online Webinar
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2019/10/tracking-accuracy-webinar.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20191113
DTEND;VALUE=DATE:20191115
DTSTAMP:20260417T180907
CREATED:20190918T174728Z
LAST-MODIFIED:20190918T181914Z
UID:10000034-1573603200-1573775999@www.forecastpro.com
SUMMARY:Foresight Practitioner Conference
DESCRIPTION:Click here for more information\n  \nThis year’s conference—organized by the respected practitioner journal Foresight—explores the potential impacts of Artificial Intelligence on forecasting and planning. How will jobs and organizations be affected when AI amplifies\, supplements and even substitutes for forecaster and planner roles? Eric Stellwagen\, CEO and co-founder of BFS\, will present A Winning Combination for Increasing Accuracy: AI-based Automatic Forecasting & Domain Knowledge.
URL:https://www.forecastpro.com/event/foresight-practitioner-conference/
LOCATION:Chapel Hill\, North Carolina
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/jpeg:https://www.forecastpro.com/wp-content/uploads/2019/09/Rizzo_Dubose_front-lawn-horizontal-side-CRPD1440x460-e1568830624280.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20191022T133000
DTEND;TZID=America/New_York:20191022T143000
DTSTAMP:20260417T180907
CREATED:20190722T163736Z
LAST-MODIFIED:20190722T212213Z
UID:10000032-1571751000-1571754600@www.forecastpro.com
SUMMARY:Free Live Webinar: Smart Strategies for Designing\, Implementing and Improving an Effective Demand Forecasting Process
DESCRIPTION:Click Here to Register Now!\n  \nFor many companies\, developing a successful forecasting process can seem daunting considering the challenges that may arise at each step along the way. In this educational one-hour live Webinar\, James Berry\, Senior Consultant at Business Forecast Systems\, Inc. will review a framework to help your forecasting team create a roadmap for designing\, implementing and improving upon your forecasting process. \nDrawing upon his extensive experience\, James will discuss the practical challenges organizations face when creating and implementing forecasting processes—and reveal pragmatic ways to overcome them. With a focus on best practices\, he will address: \n\ncreating a forecast process\nsetting up hierarchies and data effectively\nincorporating outside data\ncollaborating with others to establish the final forecasts\nmeasuring and tracking forecast accuracy\ngaining acceptance for the forecasts within the organization\n\nUsing real-world examples\, James will demonstrate how Forecast Pro can be used to support effective forecasting processes.
URL:https://www.forecastpro.com/event/free-live-webinar-smart-strategies-for-designing-implementing-and-improving-an-effective-demand-forecasting-process/
CATEGORIES:Forecast Pro Event
ATTACH;FMTTYPE=image/png:https://www.forecastpro.com/wp-content/uploads/2019/07/oct-webinar-thumbnail-with-logo.png
END:VEVENT
END:VCALENDAR