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Dear Friends, I have a question: Can DDMRP run both sale orders and sale forecast, right?.

Congratulations Bruno🎉!

Any book you would recommend to understand the workings of the supply chain from beginner to pro level?

Meanwhile your North American market is failing miserably. We’re throwing away $20,000+ worth of materials away every month. Empower MX is the worst system I have laid my eyes on. Pretty soon you won’t have employees to even work on the customers planes.

While modeling a S&OP system is there any easy way to tackle innumerable constraints in say production processes, customer priorities, technical difficulties etc. or do we have to map each one piece by piece into the algorithm?

It would be amazing if you could start adding this to Spotify! 😀

Thanks for providing this format. I've enjoyed viewing it very much. One crucial thing in my opinion is when it comes to automated-decision making there are algorithms which produce "bad" decisions and algorithm which produce "good" decision. Unfortunately the assessment good/bad may come months or even years after the decision. While human communication is slow you may have strong counterparts in the arguments. So major weaknesses can be (theoretically) found early. When it comes to modelling I haven't seen a error free implementation. So my question is: How can you achieve reviews of automatically made decisions with respect to the correctness of the underlying assumptions in the modelling.

I am working in Order Management System under Supply chain management and I am doing online masters in Data science. I have already 7 years of experience in order management system. Is doing masters in DS right decision in my career?

Wow, inspiring, I cannot wait to read some of his books now (I’ll start with the tiny URL) and see how I can apply it to my company’s problems.

Amazing talk @Joannes and @Meinolf! I keep learning more from you guys than any conventional books. Is Lokad hiring?

Amazing talk. Thank you!

In one of my job as Supply Chain practicioner we build a process where we would look at differences between forecasts (one week vs previous week), trying to understand: * why did the forecast change for this product or product category or country or... * decide if we need to change our plans based on this change much more efficient than recalculating a full distribution plan every week

Which one would you or the guest recommend R or python? I prefer R as it is specifically built for statistics and its functional language is more approachable to someone with a math foundation than OOP of python. However most job listings require python for data science and such.

so how should a Business Administration student prepare for this future? Is everything we are studying a waste of time? On Coursera, I am personally studying OR, data science and R programming, although only for statistical decision making and modeling, not for programming. But your videos make it seem like even mathematical programming/linear programming, Statistical modeling and forecasting (prescriptive and predictive analytics) are wastes of time because software like yours and others will do this for us. Furthermore I have been sorely disappointed with Chatgpt R code generating abilities and data analysis. The supply chain scientist role on your website is a domain knowledge expert with data science skills. How can students like myself become SCM experts if your software is gonna make 90% of SCM jobs disappear. College and online courses, even masters degrees can only take one so far. but we will lack any work experience to become those so called domain experts. Some advice for this student would be greatly appreciated. Perhaps some succinct videos for Business student/industrial engineer/SCM or Non software engineering professionals. P.S. I read one of your bitcoin cash blogs a couple years ago and just recently discovered your website. I dont believe POW is 51% attack proof and we have empirical evidence on smaller chains. POS seems to be more resistant like Avalanche.

🤦 "promosm"

what is frontier though...i didn't get???

What we need to keep in mind is that LLMs are not the ideal solution for analytical tasks - though of course they excel in descriptive outputs. We are still waiting to see what Q Star will be in terms of quantitative skills and capabilities - that may be truly transformative...and not in a good way for long term professional employment opportunities for large numbers of people... GPT-4 is still a bit limited in many respects, but future iterations of it, Claude et al will be displaying true leaps in capability. Just hope the travelling salesman/routing problem can finally be easily solved.

Thank you!

Great talk! Was wondering what’s your take on an aggregate level SOP without going into each and every product but focusing on product families?

Fabulous! A must for Inventory Management teaching. Thank you!

Thank you, @Lokad. For the amazing content.

To learn how to code your own supply chain solutions, visit the links below: Envision workshop 1: docs.lokad.com/gallery/workshop-supplier-analysis/ Envision Workshop 2: docs.lokad.com/gallery/workshop-sales-analysis/

Excellent and very informative video! For talks that delve into math, can we also potentially get a reading list that Joannes or Lokad recommends to up and coming supply chain scientists?

Awesome podcast. Thanks for the content!

The question I have is, where are these 90% of back office workers gonna get new jobs? Looking at these kinds of jobs on the Bureau of Labor Statistics website, most of them only require a high school diploma.

I'm 3 classes away from a bachelor degree in supply chain transportation and logistic management. I work for the largest aerospace in the defense company in the world. Can a master degree in supply chain engineering or somehow becoming a supply chain scientist? Keep me safe in the supply chain domain. Thanks

Thanks for sharing! Like the video and concept very much. I just wonder how to we take ordering cost into account in this framework. Suppose there are two replenishment options: Option I: restock 10 every two reorder time cycles Option II: restock 5 every one reorder time cycles Suppose both options can cover the demand. This rewards function will prefer Option II instead of Option I. But if we take the ordering (shipment...) cost into account, Option I might be the right Option. Could you please comment on that? Thanks!

Wholesome and sensible conversation. Thanks for the post

Upfront: Really awesome lectures, it is really eye opening to see what is possible and actually useful in practice compared to classic supply chain textbook literature. I have a question regarding the broadcasting mentioned between 01:00:20 - 01:01:52. How many parameters get overall initialized in the autodiff block? (a): 1*3=3 for the <SKUs.Level> (1 for each SKU) and (b): 2*7=14 for <CD.DoW> (2 categories where each category has one parameter for each of the 7 days of the week)? And in Line 13, after having randomly "picked" a SKU, Envision "knows" which of the 14 <CD.DoW> parameters must be used for/in the Stochastic Gradient Descent because <Day> can only belong to one <DayOfTheWeek> and only one <Category> can belong to the picked <SKU>? If so, I guess I am just not used to anything being able to make/infer these connections on its own :D Best regards, Jan

Comparing the practice knowledge of Chat GPT to the common sense of a cat is completely missing the diffrence between cats common sense and instinct.

Try to understand it using auto translate 😂. Lokad content always interesting for me since not a lot of people cover material management in aviation MRO

Johannes, you make a good point about the spherical cow assumption in core engineering not ending up in field calculations, but the same not being true in supply chain. Very astute observation. For someone who transitioned into “data science” from mechanical engineering and then operations research, in my limited experience, I can propose a reason as to why this is the case. In engineering, we rarely had managers who weren’t engineers themselves first. So, everyone sort of spoke the same language of math and physics and simulations and it was easier to have conversations regarding these. However in supply chain, what I’ve found is, there is, by default organisational structure, a split between the planning side (scientists versed with stats) and the implementation side (planning managers who rely on “experience”). And somehow, the implementation side calls all the shots, so more often than not, the technical solution that is chosen by the company depends on the level of technical expertise of the most technically challenged planning manager.

Fantastic talk! Tkank you

Excellent topic

Thanks a lot ❤

MRO = Maintenance Repair and Overhaul

Hi! This video was very helpful. Thank you for simple explanation MRP and BOM

Thanks for another interesting conversation on teaching supply chain management (I loved the analogy of the cow represented by a sphere 🤣). As you know, Porto Polytechnic School of Engineering, in the Master's programme in Supply Chain Engineering and Management, as University of Toronto, is trying to implement the paradigm shift advocated by LOKAD in teaching supply chain management. So, it was very interesting to listen to Paul Jan experience.

Merci pour cette vidéo ! Vous pouvez partager des résultats sur les invendus de fin de saison? Vous arrivez à faire des implantations qui évoluent tous les mois? Plus souvent? Moins souvent?

These games both look like phenomenal teaching resources. I have been working in SCM and watching your lectures for about a year now and always kind of hoped Lokad would make the Board Game, so happy to see one and I cant wait to play it with some other SCM people!

Good info, thanks for sharing!

Excellent!!!

🙌🙌🙌

If you don’t advocate for Forecast accuracy as a measure of forecasting success (to call it in a way), and also don’t advocate for Forecast value added, what options you give to it? What is the adding value then? How would the company plan and measure its adding value?

cow as a sphere... nice analogy.

The guest is very knowledgeable about the subject of digital twin and explains the misconceptions in very well structured and simple manner. He is not critical at all about the digital twin instead he is trying to explain that the communication about digital twins is distorted and does not represent what actual digital twins is about and that all applications in the market are very far from representing a real digital twin.

Based on the example you gave, fill rate instead of 50%, it should be 40%, right?

Been looking for a clear explanation and found it here ! Thank you so much ☺️

The intricacies of supply chains indeed operate within the realm of overarching economic principles. Yet, it's intriguing how these principles often remain shrouded in relative obscurity and occasionally diverge from popular supply chain practices. It's important to note that while these practices may challenge some aspects of conventional economics, they aren't likely to fundamentally disprove its essence. Furthermore, the complex nature of supply chains mirrors the intricacies of systems - a concept that's relatively modern and regrettably misunderstood. Recognizing this, the forthcoming lecture aims to bridge the gap between economics and systems. Its objective is to uncover the symbiotic contributions of both disciplines in unraveling the complexities of real-world supply chain planning. By amalgamating the insights of economics and systems, this lecture promises a comprehensive exploration of supply chain dynamics that goes beyond theoretical boundaries. It's an exciting opportunity to deepen our understanding and approach planning challenges armed with a holistic perspective.