Forecasting Impact

This episode of Forecasting Impact features Professor Lauren B. Davis discussing her research on applying stochastic modeling and forecasting to food bank operations. Lauren shares how she began forecasting with a local food bank, which led her to focus on forecasting the highly uncertain supply of food donations. She details the food banks' donation sourcing process, the management of their supply chains, and the application of models like exponential smoothing, support vector regression, and ensemble methods to predict donation volumes.Professor Davis addresses challenges in forecasting at various aggregation levels (network vs. location-specific), using optimization models for equitable allocation of limited supply, and the significance of storage and agency capacity limits. She emphasizes the importance of equity as an objective, the complexity of modeling true demand, and the crucial role of visual analytics and co-design with food bank partners. The episode underscores the practical impact of forecasting in humanitarian supply chains and the necessity of linking models with operational decisions.

In this episode, we sit down with Rami Krispin, a data scientist at Apple and active producer in forecasting, to explore his journey into forecasting and data science. He shares what first sparked his interest in the field and how that passion led him to develop key contributions, including the Hands-On Time Series Analysis with R book and the TSstudio package. We discuss his motivation for writing the book, who it's for, and how TSstudio and other R packages he has developed have helped practitioners in the forecasting space. He also gives us a sneak peek into his upcoming book, Applied Time Series Analysis and Forecasting with R, and the new topics it will cover.We then dive into the challenges of deploying forecasting models at scale and the role of MLOps in making machine learning projects production-ready. As a Docker Captain, our guest explains how Docker has changed his approach to time series forecasting and MLOps. We also discuss best practices for forecasting, common mistakes practitioners make, and strategies for improving reproducibility. Looking ahead, we talk about where time series forecasting is heading, the differences between R, Julia, and Python in this space, and how each ecosystem serves different needs. You can follow his work on LinkedIn, subscribe to his newsletter, and stay updated on his latest projects.Website: https://linktr.ee/ramikrispinLinkedIn Page: https://www.linkedin.com/in/rami-krispin/

In this episode, Dr. Laila Akhlaghi and Professor Bahman Rostami-Tabar host a discussion on healthcare product forecasting in Eastern Africa with Harrison Mariki from Tanzania and Danielson Kennedy Onyango from Kenya. Harrison, founder of Afya Intelligence, discusses leveraging AI to improve forecasting for 7,000 primary healthcare facilities in Tanzania, addressing data quality and supply chain challenges. Ken, from inSupply Health, highlights the use of open-source tools and human-centered design to enhance forecasting accuracy and efficiency in Kenya. Both emphasize the importance of local talent, trust, and co-creation in developing effective forecasting solutions.

In this episode of Forecasting Impact, we had the privilege of hosting Professor Jan Kleissl, a leading expert in solar power forecasting. Professor Kleissl began by sharing his journey into solar forecasting, emphasizing the growing importance of renewable energy in addressing climate change. He explained the critical role solar forecasting plays in balancing energy grids, ensuring reliability, and integrating renewable energy at scale. The discussion delved into the technical challenges of forecasting, such as dealing with weather variability, and explored the challenges ahead for NET Zero and power transformation in the field.  We further explored the practical applications of accurate solar forecasting, with Professor Kleissl highlighting how it benefits grid operators and consumers by optimizing energy distribution and reducing costs. He shared insights into decentralized energy resources and fostering innovation. He recommended the following paper for readers interested in solar power forecasting and its role in the energy market: The Value of Day-Ahead Solar Power Forecasting Improvement, published in Solar Energy. 

In this episode, hosts Arian Sultan and Laila Akhlaghi discuss financial tools that enable healthcare markets to function more efficiently and how forecasting plays an important role in their execution with Hema Srinivasan of MedAccess. Hema Srinivasan is a senior advisor to MedAccess, supporting work to identify and execute opportunities for financial tools to help lower prices and increase the availability of medical products. She supports the Health Markets team in sourcing and developing pipeline opportunities for the deployment of MedAccess' tools, managing the monitoring and implementation of transactions post-execution, and analyzing development impact throughout the partnership development and implementation process. This episode explores her career and how she has used forecasting to develop market-shaping mechanisms and the methodologies that have led to increases in access to life-saving medical products. This includes analyzing market failures, identifying leverage points for intervention, and implementing policies or programs to rectify imbalances. The episode discusses how these interventions can lead to sustainable and scalable impacts, particularly in sectors where market inefficiencies hinder progress. It highlights interventions that lower prices and increase access to pharmaceuticals, diagnostics, and other medical products in low and middle-income countries (LMICs).

In this episode, hosts Mariana Menchero and Faranak Golestaneh explore the cutting-edge world of foundation models for time series forecasting with guests Azul Garza Ramírez, cofounder of Nixtla, and Mononito Goswami, one of the developers of MOMENT, a family of open-source foundation models for general-purpose time series analysis. The conversation delves into the backgrounds of these innovators and their journey into the realm of time series analysis and forecasting.The podcast explores the guests' transition into working with foundation models for time series forecasting. The guests describe the empirical approach they took, inspired by the success of Transformers in other domains like video, images, and text. Their experiments with adapting these models to time series data yielded exciting results, leading to the development of new products and tools.The conversation sets the stage for a deep dive into the challenges and opportunities presented by foundation models in time series forecasting. The discussion highlights the need for massive, diverse datasets and the potential for these models to learn patterns and extrapolate to new data effectively.This episode underscores the rapid advancements in time series forecasting and the growing importance of foundation models in pushing the boundaries of what's possible in this field. It offers listeners a glimpse into the minds of innovators who are shaping the future of time series analysis and its applications across various industries.

In this episode, hosts Mariana Menchero and Faranak Golestaneh explore the cutting-edge world of foundation models for time series forecasting with guests Azul Garza Ramírez, cofounder of Nixtla, and Mononito Goswami, one of the developers of MOMENT, a family of open-source foundation models for general-purpose time series analysis. In this episode, we discuss the guests' transition into working with foundation models for time series forecasting. The guests describe the empirical approach they took, inspired by the success of Transformers in other domains like video, images, and text. Their experiments with adapting these models to time series data yielded exciting results, leading to the development of new products and tools. The conversation sets the stage for a deep dive into the challenges and opportunities presented by foundation models in time series forecasting. The discussion highlights the need for massive, diverse datasets and the potential for these models to learn patterns and extrapolate to new data effectively.This episode underscores the rapid advancements in time series forecasting and the growing importance of foundation models in pushing the boundaries of what's possible in this field. It offers listeners a glimpse into the minds of innovators who are shaping the future of time series analysis and its applications across various industries.

In this episode of "Forecasting Impact," hosts George Boretos & Arian Sultan Khan explore the intersection of Neuroscience with Forecasting & AI with guest Kai Markus Mueller, an acclaimed neuroscientist and a pioneer in Neuropricing.Kai, who began his journey in psychology with aspirations of becoming a child psychotherapist, eventually shifted his focus to cognitive psychology and neuroscience. His transition from academia to the industry led to the invention of Neuropricing that utilizes fMRI and EEG to understand consumer behavior and predict responses to advertising and pricing.The podcast delves into Kai's innovative work, highlighting how brain activity can often predict consumer behavior more accurately than traditional self-reported methods, with success stories such as Starbucks coffee pricing research and Pepsi's strategy in Turkey.Kai explains the practical applications of neuroscience in business, such as storyboard testing for advertising effectiveness and discusses the integration of AI with neuroscience to enhance predictive models.He also shares insights on balancing his various roles as an entrepreneur, professor, and industry practitioner, emphasizing the importance of a supportive team.Looking ahead, Kai sees immense potential for neuroscience and AI to transform business strategies, pricing, and drive marketing success.The conversation underscores the growing mainstream acceptance and practical benefits of these advanced technologies in various industries.

In this episode, we had the privilege of hosting Mitchell O'Hara-Wild, data scientist and lead developer of the widely used and highly acclaimed forecasting packages, Fable and Feasts. Mitchell is a PhD candidate at Monash University, Australia. He shared insights on a wide range of topics, including his journey into data science and forecasting, the reasons behind the development of the popular Fable package, and his views on AI in forecasting. We also discussed Mitchell's research on DAGs (Directed Acyclic Graphs) in the context of forecast reconciliation, as well as his consulting experience forecasting COVID-19 cases in Australia. Moreover, we had the opportunity to talk about his experience delivering workshops to researchers and practitioners through the IIF's Forecasting for Social Good community (F4SG) and at useR! conferences. Listen to this podcast and learn more about Mitchell's remarkable work in the realm of forecasting, software development, and the future of forecasting in the era of AI.

In this episode, we spoke to Joannes Vermorel, founder and CEO at Lokad, a quantitative supply chain software company.  Joannes discussed how supply chain theory is broken down, and that we need to think in terms of paradigms and modules rather than models for solving supply chain problems. He talked about issues in time series forecasting and judgmental forecasting. He emphasized how critical it is to have a holistic view of the problem, to aim for optimization of the entire system. and to acknowledge that we often don't know the metric to be optimized and it requires some experimentation. We also discussed how Lokad is deploying AI pilots to address some of the important problems in supply chain. To learn more about Lokad, visit https://www.lokad.com/ or check them out on YouTube. 

In this episode, we spoke to Laurent Ferrara, Professor of International Economics at SKEMA Business School. Laurent discussed the role of nowcasting, particularly in the realm of macroeconomic nowcasting. He delved into the details of the models and methods that have been proven effective in this domain. Laurent also talked about GDP nowcasting using Google data and shared some intriguing results from his recent research.Laurent is the program chair of the 44th International Symposium on Forecasting, which will be held in Dijon, France. He provided an overview of the conference program and explained why we should attend!

In this episode of our podcast, we delve into the intricate world of machine learning (ML) deployment with Dr. Eric Siegel, author of the book AI Playbook, Mastering the Rare Art of Machine Learning Deployment. Dr. Siegel, once an avid advocate of ML, now approaches the field with a disciplined yet optimistic perspective. He shares invaluable insights on how businesses can effectively implement ML strategies. Our discussion revolves around a range of compelling topics, from the inspiring story of Jack from UPS, who leveraged his psychology background to revolutionize parcel delivery, to the common pitfalls that cause many ML projects to fail. Eric elucidates the six crucial steps for ML deployment, emphasizing the importance of ethical considerations in this rapidly evolving field. Whether you're a student, a business leader, or just an AI enthusiast, this episode offers a treasure trove of knowledge and strategies to navigate the complex landscape of machine learning deployment. 

Our guests are Michele Trovero, leader of the Forecasting R&D group at SAS, and Spiros Potamitis, Data Scientist and Product Marketing Manager at SAS. We delved into the intriguing intersection of Language Model-based AI (LLMs) and forecasting software. We explored the openness of forecasting software providers to embrace LLMs and discussed the profound impact these models could have on the industry. Michele and Spiros shared insightful examples of LLM applications. They elaborated on the way code generation capabilities powered by LLMs would enhance the development of forecasting software and the user experience. Additionally, they explored how LLMs could democratize forecasting, and discussed other tools and technologies that could contribute to this goal. We also discussed the typology of models behind LLMs, and their applicability in forecasting, as well as the limitations and enablers in using AI-pretrained models in forecasting.   The discussion extended to SAS Visual Forecasting and Model Studio, shedding light on their functionalities and workings.Michele and Spiros speculated on the areas of focus for forecasting software companies, enhanced automation in forecasting, shifts in user consumption patterns, and anticipated integrations between forecasting systems and other technologies.They recommended the following for further study: 1. How Will Generative AI Influence Forecasting Software? by Michele Trovero and Spiros Potamitis, Foresight: The International Journal of Applied Forecasting. 2. A Glimpse into the Future of Forecasting Software, by Spiros Potamitis, Michele Trovero, Joe Katz, Foresight: The International Journal of Applied Forecasting. 

Martie-Louise Verreynne is a Professor in Innovation and Associate Dean (Research) in the Faculty of Business, Economics and Law, at the University of Queensland.Prof. Martie-Louise Verreynne joined us to discuss the evolving partnership between academia and industry. While not a new concept, it has significantly transformed over the years, with over 40% of global patents now stemming from this collaboration, underscoring its growing importance in innovation. We examined the keys to success and common barriers such as differing priorities, resources, IP, paperwork, and objectives.Martie-Louis discussed her recent work on collaborations between Small and Medium-sized Enterprises (SMEs) and universities, highlighting the complexities of balancing diverse interests. We also explored successful university-industry collaborations in forecasting and their significant impacts. The pandemic has emphasized the importance of agility, which has influenced collaboration dynamics. Looking ahead, she envisions universities playing a central role in shaping the future of university-industry collaboration, continuing to drive innovation for the benefit of society and industries.

In this episode, we delved into the dynamic realm of transportation forecasting, exploring a wide array of ideas and questions. Our discussion with David began by examining the primary data sources and methodologies that drive modern transportation forecasting. We continued by highlighting the pivotal role of real-time data, GPS technology, and advanced algorithms in providing accurate insights into traffic patterns, public transit ridership, and the trajectory of mobility trends.  We also discussed the integration of emerging technologies like autonomous and electric vehicles, showcasing their transformative potential in shaping transportation models and infrastructure. From a consulting and practical perspective, we explored the challenges of ensuring the accuracy and reliability of transportation forecasts and contemplated the influence of AI and machine learning on the future of transportation forecasting. 

In this episode, we host three scientists, Dr. Stephan Kolassa, Dr. Bahman Rostami-Tabar, and Prof. Enno Siemsen. They are the authors of "Demand Forecasting for Executives and Professionals." In this episode, we delve into discussions about their book.We discuss their motivations for writing this unique guide for professionals and the need for such a book. We explore the pivotal role of forecasting in business decisions and unpack key principles and methodologies. Our conversation navigates through causal models, stressing the importance of understanding the forecasting process. We highlight the profound impact of AI, machine learning, and human judgment in forecasting, considering cognitive biases and the potential of large language models.The interview continues with discussions about the integration of demand forecasting in organizations, noting ethical considerations, reasons behind forecasting failures, and common hurdles encountered in evaluating forecast quality. We conclude by providing resource recommendations for further exploration of the topic and advice for executives eager to enhance their demand forecasting skills.You can learn more about their book at https://dfep.netlify.app/ and order at https://www.routledge.com/Demand-Forecasting-for-Executives-and-Professionals/Kolassa-Rostami-Tabar-Siemsen/p/book/9781032507729.

In this episode, we delve into the inspiring academic journey of two sisters from the heart of Sri Lanka. Dr Priyanga Dilini Talagala and Dr Thiyanga Talagala. Dr Priyanga is a Senior Lecturer at the University of Moratuwa, specialising in statistical machine learning and data mining, with a fervent commitment to open-source software for reproducible research. Dr Thiyanga is a Senior Lecturer at the University of Sri Jayewardenepura, focusing on large-scale time series forecasting, data visualization, and machine learning interpretability methods.  We had a delightful discussion and learned about their backgrounds, their transition to and from Australia, and their perspectives on the evolving landscape of forecasting in Sri Lanka. We also discuss the status of academic collaboration with industry, the unique facets of Sri Lanka's higher education system, and the role of cultural and societal dynamics in academic communities. They shared their mentoring work and availability for forecasting opportunities in Sri Lanka. 

In this episode, we hosted Professor George Athanasopoulos, President of the International Institute of Forecasters (IIF) and Head of the Department of Econometrics and Business Statistics at Monash University. George gave an overview of the IIF's current plans and new initiatives, including the Practitioners chapter, publishing papers in the International Journal of Applied Forecasting, the forecasting distinguished lecture series, and plans for the International Symposium on Forecasting, among others. He also shared his career experience in forecasting and how he has grown in the field to his current position. George also mentioned to his research experience in hierarchical forecasting, his teaching success, and the recent stories on co-authoring and translating the famous book "Forecasting: Principles and Practice." into Greek.George recommends the following books and papers as influential in his career:Forecasting: Principles and Practice, RJ Hyndman, G Athanasopoulos,  Otext.Tsay, R. S. (1991) "Two canonical forms for vector ARMA processes." Statistica Sinica 1, 247–69.Hyndman, R., Koehler, A. B., Ord, J. K., & Snyder, R. D. (2008). "Forecasting with exponential smoothing: the state space approach." Springer Science & Business Media.Panagiotelis, A., Athanasopoulos, G., Gamakumara, P., & Hyndman, R. J. (2021). "Forecast reconciliation: A geometric view with new insights on bias correction." International Journal of Forecasting, 37(1), 343-359

In this episode, we had the honour of having three guests on our panel: Prof Rob Hyndman, Professor of Statistics from Monash University, Federico Garaz, CTO and co-founder of Nixtla, and Eric Stellwagen, CEO and Co-founder of Business Forecast Systems.  We discussed a range of topics on the role of software in forecasting, the latest status, and future trends in forecasting software. The panel shed light on the importance of incorporating operational information in software and integrating decision information in the software.  We discussed some of the challenges in implementing forecasting software and getting them to work.The panel shared insights and tips for excelling in forecasting software. Eric recommended defining what you want to accomplish, and the needs that you want to fill before choosing any software. Fede recommended Nixtla as a resource on various forecasting software and Forecasting Principles and Practices by Rob Hyndman and George Athanasopoulos as a reference book. Rob recommended books by Hadley Wickham as great resources.

Eric Siegel is a leading consultant and former Columbia University professor. He is the founder of the popular Predictive Analytics World and Deep Learning World conference series.  In this episode, Eric shares his decades of experience in predictive analytics. He discusses why ML is useful, and how predictive analytics have been used in business. Eric shares his view on prescriptive analytics, AI, and also explains uplift-modelling concepts, and why it is hard and so powerful.  Eric's RecommendationsBooks:Competing on Analytics: Updated with a New Introduction, The New Science of Winning by Thomas H. Davenport, Jeanne G. Harris, 2017Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst, by Dean Abbot Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel Papers: Sculley, David, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-Francois Crespo, and Dan Dennison. "Hidden technical debt in machine learning systems." Advances in neural information processing systems 28 (2015). Elder IV, John F. "The generalization paradox of ensembles." Journal of Computational and Graphical Statistics 12, no. 4 (2003): 853-864. 

Scott Cunningham is Professor of Public Policy at the University of Strathclyde and is the Editor-in-Chief of the journal, Technological Forecasting & Social Change. In this episode, we talked about technological forecasting and social change. Prof. Cunningham gave an overview of how technological forecasting, policy, and business are interwoven, and how a systematic view is important in predicting the long-term pattern in technology. He described the broader context of tech mining, and why it is important to have mid to long-term forecasts. Recommendations for books and papers: The Book of Why, by Dana Mackenzie and Judea Pearl(Paper) Vehicle Ownership and Income Growth, Worldwide: 1960-2030 by Joyce Dargay, Dermot Gately and Martin Sommer 

In this episode, we talk to Prof. Tao Hong, a Distinguished Professor at the University of North Carolina at Charlotte. Tao provides his insights on the future of energy forecasting research, and why we need to focus on reproducibility. He discusses the Global Energy Forecasting competitions, and what we have learned from them. He also sheds light o n the importance of industry and academic collaboration, and a business model that he has implemented successfully.He recommends the following reading for interested readers who want to go deep into forecasting and, specifically, energy forecasting:BooksForecasting Principles and Practice, by Rob Hyndman, and George AthanasopoulosMatrix Analysis and Applied Linear Algebra by Carl D MeyerPaperProbabilistic electric load forecasting: A tutorial review, T Hong, S Fan, International Journal of Forecasting, V 32 (3), 2016. 

In this episode, we spoke to Prof Galit Shmueli, Tsing Hua Distinguished Professor at the Institute of Service Science, and Institute Director at the College of Technology Management, National Tsing Hua University. Galit talked with us about the multi-disciplinary work she has done over the years, as well as the differences between statistical models that are purposed for predicting as opposed to explaining. We also discussed causal inference and how it can be used to estimate behaviour modification by the tech giants. We continued and talked about the ethics and the complexity of that landscape.  Galit's recommended books:  1.    The age of surveillance capitalism, Shoshana Zuboff 2.     Books on causality:     • The book of Why, Dana Mackenzie and Judea Pearl      • Causal Inference in Statistics: A Primer, Judea Pearl, Madelyn Glymour, and Nicholas P. Jewell      • Causality, Judea Pearl  3.     Mostly Harmless Econometrics: An Empiricist's Companion, Joshua D. Angrist, ‎Jörn-Steffen Pischke 

In this episode, we spoke with Dr. Ataman Ozyildrim from The Conference Board.  We discussed leading economic indicators and its importance in tracking the economy's business cycle. He provided his insights on the current situation of the economy. He continued by pointing to the changes in supply chain trends. We also talked about the digital economy and measuring innovation in organisations.  This is only a glimpse into the many excellent insights from Ataman and The Conference Board.  Recommended book: Business Cycles: Theory, History, Indicators, and Forecasting by Victor Zarnowitz Recommended paper:  On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates by FX Diebold, M Shin, B Zhang 

Nikolaos Kourentzes is Professor of Predictive Analytics at the University of Skövde (Sweden) in the Artificial Intelligence Lab as well as a member of the Centre for Marketing Analytics and Forecasting, at Lancaster University in the United Kingdom. In this episode, Nikos talks about the role of AI and judgement in forecasting, and what we as forecasters need to learn from other fields such as algorithmic learning. He continues with a discussion on temporal and hierarchical forecasting problems. On a more personal note, he shares with us his background, career and philosophy on the "why” behind the problems. And, finally, he discusses his new book, Principles of Business Forecasting, 2nd edition as well as recommendations for forecasting books and papers.

Polly Mitchell-Guthrie is the VP of Industry Outreach and Thought Leadership at Kinaxis.In this episode, Polly talks to us about the collaboration between the academic and business worlds. She tackles topics such as possible synergies, building trustful cooperation and proper forecasting communication. She also shares with us the forecasters' ABCs rule.Listen to find out more!

Trevor Sidery is a Lead Data Scientist at Tesco PLC. In this episode, Trevor unveils the mystery of how astrophysics and fluid dynamics studies leads to forecasting.Trevor discusses the forecasting process within large retail company, and which business component models are predicting and how models are selected. He elaborates on best practices on scaling forecasting models on large amount of time series.

Jim Hoover is a clinical professor and Director of Business Analytics and Artificial Intelligence Center at the Warrington School of Business, University of Florida. In this episode, Jim shares some of his experiences in the US Navy where he worked in several decision-making roles and used forecasting/operation research tools for over two decades. Jim emphasises the importance of open source software development and calls for academic cooperation on building an open access platform for sharing the best forecasting practices with industry practitioners and SMEs. He also shares his thoughts on bridging the gaps between industry and academia.Jim recommends Forecasting Principles and Practices by Rob Hyndman and  George Athanasopoulos as a great textbook for forecasters. 

 Our next guest is Len Tashman, Professor Emeritus of business administration at the University of Vermont, US. He is the founding and continuing editor of Foresight: The International Journal of Applied Forecasting.Len tells us how the “Foresight” journal was established in 2005, the main idea behind it, and how it is going now. This journal provides up-to-date research for practitioners and forecasters, and it has an impressive background story. Len highly recommends a prominent book by Daniel Kahneman “Thinking, Fast and Slow” as well as a new book released by Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein, “Noise: A Flaw in Human Judgment”.

Jennifer Castle is an Economics Fellow at Magdalen College, Oxford University and a research fellow at Climate Econometrics, Oxford University.Jennifer talks about economic forecasting models and the role of structural breaks (e.g., Covid pandemic) in forecasting. We also discuss climate change and how it can be forecasted using econometric tools and scenario analysis.Jennifer recommends two books Fortune Tellers by Walter Friedman and The Undercover Economist by Tim Harford, and one paper-book chapter, 'Towards a Theory of Economic Forecasting', In Hargreaves, C. (Ed.) (1994), Non-stationary Time-series Analysis and Cointegration, with M.P. Clements.

Evangelos Spiliotis is a Research Fellow at the Forecasting and Strategy Unit, National Technical University of Athens (NTUA). He co-organised the M4 and M5 Forecasting Competitions and is an organiser of the M6 competition.Evangelos talks about his research directions, highlighting the role of machine learning algorithms in time series forecasting within current business processes. He also discusses the M competitions which have been organized by Professor Spyros Makridakis and Evangelos for the last several years. The M6 competition, a competition on forecasts of stock price (returns) and risk, is live now and will be finalised in February 2023.Evangelos recommends Forecasting: Principles and Practice (3rd ed) by Rob J Hyndman and George Athanasopoulos and Practical Time Series Forecasting with R: A Hands-On Guide by Galit Shmueli and Kenneth C. Lichtendahl Jr.He also recommends the following papers: Forecasting: Theory and Practice by Petropoulos et al., Retail forecasting: Research and Practice by Fildes, Ma and Kolassa, and the special International Journal of Forecasting issues on the M competitions. 

Our next guest is Paul Goodwin, Emeritus Professor at the University of Bath, United Kingdom.Paul is a fantastic speaker, well-known for his research in judgemental forecasting, and author of numerous books. This conversation developed into several exciting tracks. We discussed uncertainty and human perception, a combination of statistical models (especially in spreadsheets) and judgments, and their use in the current forecasting software.Paul recommends Principles of Business Forecasting by Keith Ord, Robert Fildes and Nikolaos Kourentzes. 

This episode's guest is Elaine Deschamps, Executive Director of the Washington State Caseload Forecast Council, an independent state agency. Elaine has spent 25 years in public service, previously as Senior Fiscal Analyst for the Washington State Senate Ways and Means Committee, in charge of the low-income health care and public health budgets.Elaine explains how public service forecasting works and the role of judgment and scenario planning in policy settings. Also, we talk a bit about a “new normal” in the Covid era and the challenges it imposes on forecasters.Elaine recommends “Foresight” Guidebooks, especially “Improving Your Forecasting Process”, “Forecasting Methods Tutorials”, and “Forecast Accuracy Measurement: Pitfalls to Avoid and Practices to Adopt”.

Our next guests are John Boylan, Professor and Director of Centre for Marketing Analytics and Forecasting (CMAF) at Lancaster University (UK), and Aris Syntetos, Professor of Operational Research and Operations Management at Cardiff University. John and Aris have recently published a book titled “Intermittent Demand Forecasting: Context, Methods and Applications”, a book aimed at practitioners and early career researchers which summarises everything known about intermittent demand forecasting up to date. In this episode, we introduce this book and then talk about good practices for research and industry collaborations.John recommends “Inventory and Production Management in Supply Chains” by E. Silver, D. Pyke, D. Thomas, and Aris talks about “Statistical forecasting for inventory control” and “Smoothing, Forecasting and Prediction of Discrete Time Series” by Robert Goodell Brown.

This episode's guest is Dr. Anne Robinson, Chief Strategy Officer at Kinaxis. Anne is a thought leader in the field of analytics and digital transformation, with expertise in operations, supply chain and strategy.In this episode, Anne talks about her career path from academia to the customer and software vendor experience. We also discuss the role of trust and analytical and soft skills that are key to success in the field. What are the crucial components of agile planning, forecasting and supply chain management? Anne shares her vision and ideas, enjoy!

Our next guest is Feng Li, Associate Professor of Statistics in the School of Statistics and Mathematics at Central University of Finance and Economics in Beijing, China.    In this episode, he describes the current status of forecasting science and practice in China, his research focus, and his lab KLLAB, where he and his wife Dr Yanfei Kang are focused on computing, forecasting and learning with massive machines. We also discussed in depth one of his papers entitled "Time series forecasting with imaging". 

Our next guest is Professor Nada Sanders, Distinguished Professor in Supply Chain Management at Northeastern University, US. She has written several books (e.g., “Big Data Driven Supply Chain Management” (Pearson), “Foundations of Sustainable Business”, “Forecasting Fundamentals”), her latest publication is “The Humachine: Humankind, Machines, and the Future of Enterprise”.In this episode, Nada emphasizes the important role of humans in decision-making and predictions. Despite humans' fallacies and biases, we bring valuable contextual information into analytics. While there are many open questions about the use of human judgment in forecasting, another level of complexity is arising—the use of algorithms and support systems. Nada also encourages academics and practitioners to work together, especially given the global problems in supply chain and forecasting that have arisen with the COVID pandemic. Nada recommends “Judgment and Choice” by Robin Hogarth and the collective body of papers by Robert Fildes and Paul Goodwin.

This episode's guest is Pierre Pinson, Professor of Operations Research at the Technical University of Denmark (DTU), Department of Technology, Management and Economics (Management Science division), and Editor-in-Chief for the International Journal of Forecasting. In this episode, we talk about weather forecasting and communicating uncertainty to a broader audience. Following the current trends, we discuss energy consumption and the possibility of using renewables across the world. Pierre also shares his experience being Editor-in-Chief of the IJF and his views on the future of forecasting. Pierre recommends Forecasting: Principles and Practice (3rd ed) by Rob J Hyndman and George Athanasopoulos, and also the paper “Computing and graphing highest density regions” by Rob Hyndman.

In this episode, we had the honour to host Dr. Bahman Rostami-Tabar from Cardiff University. Bahman is a Senior Lecturer (Associate Professor) in Management Science at Cardiff Business School. His research focuses on forecasting, modelling and its link to decision making, particularly in forecasting for social good. He is the organizer of the Forecasting for Social Good workshops which investigate how and where forecasting can be used to create societal impact. He is also the organiser of the Democratising Forecasting workshops, an initiative sponsored by the International Institute of Forecasters, which provides forecasting tools in developing countries. In addition, he hosts a book club on forecasting — if you want to improve your forecasting skills, you can join along.Bahman's book suggestions include Forecasting: Principles and Practices, by Rob J Hyndman and George Athanasopoulos, and Demand Forecasting for Managers, by Enno Siemsen and Stephan Kolassa.

Our next guest is Michael Gilliland, Product Marketing Manager at SAS, member of the board of directors of the International Institute of Forecasters (IIF) and Associate Editor of Foresight: The International Journal of Applied Forecasting.In this episode, Mike tells us how he started his career in forecasting and became a part of the IIF. We also discuss ML/AI methods' role in forecasting and the potential problems and challenges. At the end of this talk, Mike gives several recommendations for must-reads.

This special episode is dedicated to the International Institute of Forecasters (IIF) and the International Symposium on Forecasting (ISF). George Athanasopoulos, the current IIF President, is the Professor and Deputy Head of the Department of Econometrics & Business Statistics at Monash University, Australia. Pam Stroud has been the IIF Business Director for the last 15 years. In this episode, we talk about some details of conference organisation, funny "behind the scenes" stories, and new features and directions.If you miss the warm and friendly atmosphere of the ISFs, join us in this lovely chat!

Our next guest is Spyros Makridakis, Professor at the University of Nicosia, the director of the Institute For the Future (IFF), and an Emeritus Professor at INSEAD. Spyros is also one of the co-founders of the IIF and has significantly contributed to the field by running famous forecasting M-competitions.In this episode, we get his advice on how to build a forecasting career and why strategy is so important. He shares his opinion on the best current forecasting methods and practices.  Spyros recommends some of his favourite books,  Forecasting Methods for Management and Business Forecasting: Practical Problems and Solutions, along with these papers Accuracy of Forecasting: An Empirical Investigation, and A brief history of forecasting competitions.

This episode's guest is Stephan Kolassa, Data Science Expert at SAP Switzerland AG, Honorary Researcher, and Associate Editor for the practitioner-oriented journal Foresight: The International Journal of Applied Forecasting.Stephan's varied work allows him to bring insights from business into academia, combining the best of both worlds. This episode discusses his day-to-day job, his research, and advice on how to build a connection between the two.Stephan mentioned his recent webinars:Forecasting Retail Demand: https://youtu.be/sUlToPvftFw Forecast Accuracy: https://youtu.be/pD_yEmEQCeo

This episode's guest is Gloria González-Rivera, Professor of Economics and Associate Dean, College of Humanities, Arts and Social Sciences, at the University of California Riverside, USA. In the episode, we discuss important topics such as the issues with diversity in our community and how to advocate for positivity and open-mindedness, especially in connections between academic forecasters and practitioners. These collaborations and relationships are critical to the industry's progress. Gloria also shares her forecasting story and philosophy for life.

Our second guest is Robert Fildes, Distinguished Professor and Director of the Centre of Marketing Analytics and Forecasting (CMAF) at Lancaster University, UK.Robert is one of the founding fathers of the IIF, alongside J. Scott Armstrong, Spyros Makridakis, and Robert Carbone. This episode explores Robert's experience working towards his PhD in statistics at the University of California, his professional experience in the forecasting world, and the founding of the IIF.

Our first guest is the well-known forecaster Rob Hyndman, Professor of Statistics and Head of the Department of Econometrics & Business Statistics at Monash University, Australia. In this episode, we talk about his career, projects, challenges, a history behind his R packages, and some consultancy work tips. 

Welcome to our "Forecasting Impact", a podcast by the International Institute of Forecasters. We will bring the best academics and practitioners from around the globe to discuss forecasting in various applications and share their knowledge and experience. Mahdi Abolghasemi will be hosting this show with the support of the "Early Career Researchers" group.  We hope you enjoy it!