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.

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 a 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”.