Thank you. This video is informative and clearly explained. I didnt find the video or music distracting as I was thinking whilst listening to the narration. I am about to start a demand planning role and this helped me grasp the basics. I really appreciate how you have taken the time to reply with such detail to the questions in the comments.
Thank you so much for your wonderful feedback! 😊 I'm absolutely thrilled to hear that you found our video helpful and that it provided clarity for your upcoming demand planning role. We're here to make sure our content is informative yet easy to follow, and I'm delighted that you didn't find the video or music distracting. Your appreciation means the world to us! Don't hesitate to reach out if you have any more questions in the future. Best of luck with your new role in demand planning! 🌟 If there's anything else you need, we're here to help. Happy learning! 🚀✨
Your voice is so good and pleasing that I forget to concentrate on the actual topic. But I find the background video very distracting, specially those vehicles moving in city. Lol
Hi ! I'm working as a material planner in a multinational company. I'd like to know who has better salary: 1. Supply Planner, 2. Capacity Planner, 3. Demand Planner. My idea is in 2-3 years become one of these and I'd like to know which one has better salary potential. Many thanks ! :)
Hello there! thank you for commenting. I think they are all great areas of supply chain to go into. But in my opinion, the one with the most potential for growth is as a Supply planner. I believe that is the case because Supply Planning entails both capacity requirements planning and demand and forecast planning. This means that supply planner will have to know both because it is the bigger umbrella position that operates both. I have added a link on some additional info on all 3 positions if you are interested. Supply planner salary: www.glassdoor.com/Salaries/supply-planner-salary-SRCH_KO0,14.htm Capacity planner salary: www.glassdoor.com/Salaries/capacity-planner-salary-SRCH_KO0,16.htm Demand Planner salary: www.glassdoor.com/Salaries/demand-planner-salary-SRCH_KO0,14.htm
Dear Friends, I understand that demand plan is the supply chain department's forecast based on sales history and market sensitivity, and it is used to counter the sale forecast from sales department, right ?.
Yes, the demand plan uses quantitative data (sales numbers from previous months/years) and also qualitative data (expert's opinion or input) to create a prediction of what the company thinks will sale. Once this demand plan is created, you can then create a supply plan (which tells the company what to procure or produce in order to satisfy that anticipated demand). Hope that helps!
@@MVCLogisticsAcademy Good intro. Question: how do you see ML (Machine Learning) and Big Data playing a part in Demand Planning? For example, "origins" of Demand Planning use typical sales, orders, etc data... but what if we could leverage 'big data' from the internet to teach a system (using ML) to find & learn from trends in other markets, data from other companies, public data, social media data, etc? Are there any practical examples of this being used for Demand Planning currently?
hello, thank you for commenting, and for your patience on a reply. From my experience, and from doing some research, I see machine learning (ML) and big data playing a significant role in demand planning by enabling organizations to more accurately forecast demand, optimize inventory levels, and reduce costs. By leveraging big data from a variety of sources such as the internet, companies can use ML algorithms to analyze and identify patterns and trends that may not be immediately apparent through traditional data analysis. -One example of how big data and ML can be used in demand planning is by analyzing data from social media platforms such as Twitter, Facebook, and LinkedIn. By monitoring conversations related to products or services, organizations can gain insights into customer preferences, sentiment, and emerging trends. This information can then be used to adjust demand forecasts and inventory levels accordingly. -Another example is using public data such as weather and economic data to predict demand fluctuations. For instance, a retailer can leverage weather forecasts to predict demand for seasonal items such as clothing or outdoor gear, and adjust inventory levels accordingly. To leverage big data from the internet to teach a system using ML, organizations can use techniques such as natural language processing (NLP) to extract meaningful insights from unstructured data such as social media posts or news articles. By combining this data with internal data such as sales data or historical demand data, organizations can build more accurate demand forecasting models. Practical examples of big data and ML being used for demand planning currently include: -Amazon's recommendation engine: Amazon uses ML algorithms to analyze customer data and provide personalized product recommendations based on individual preferences and purchase history. -Walmart's demand forecasting system: Walmart uses ML algorithms to predict demand for products and adjust inventory levels accordingly, helping to reduce stock-outs and overstocks. -Coca-Cola's supply chain optimization: Coca-Cola uses ML algorithms to optimize their supply chain by analyzing data from sales, inventory, and production to forecast demand and adjust production accordingly. Overall, the use of big data and ML in demand planning has the potential to significantly improve supply chain efficiency and reduce costs. Companies will need to leverage data from a variety of sources and use advanced algorithms, which will help them gain insights into customer preferences and emerging trends while adjusting inventory levels accordingly to improve customer satisfaction and profitability.
Sorry about that, I cannot edit the music out at the moment because this was done with an editor I no longer have access to. BUT! I will be making an updated video on Demand Planning in the coming days, so stay tuned, thanks for watching 🙂
Hey there! 😄 Absolutely, you're spot on! With the current semiconductor situation, forecasting has become more critical than ever, especially for components like LED drivers and ICs. It's like peering into the crystal ball and planning ahead for the next 1 to 2 years! 🌟💡 The demand for these semiconductors can be quite unpredictable, and having accurate forecasts is essential to ensure a smooth supply chain and meet the needs of our customers. It's like navigating through a dynamic landscape, and we're up for the challenge! 💪🚀 working in Supply chain for these products, we have to be dedicated to staying on top of market trends, collaborating with suppliers, and keeping a close eye on industry developments to make sure we're prepared for whatever comes our way. Thanks for bringing up this important topic, and we're thrilled to have you as part of our community! Keep sharing your valuable insights, and together, we'll navigate the world of semiconductors and make great strides in our supply chain journey! 🌐📈 Let's keep moving forward and lighting up the future! 💡🌟
thank you for the feedback, we have started making less distracting videos with more talking/narrative style. Hope you can check them out and let us know what you think!
Thank you. This video is informative and clearly explained.
I didnt find the video or music distracting as I was thinking whilst listening to the narration.
I am about to start a demand planning role and this helped me grasp the basics.
I really appreciate how you have taken the time to reply with such detail to the questions in the comments.
Thank you so much for your wonderful feedback! 😊 I'm absolutely thrilled to hear that you found our video helpful and that it provided clarity for your upcoming demand planning role. We're here to make sure our content is informative yet easy to follow, and I'm delighted that you didn't find the video or music distracting. Your appreciation means the world to us!
Don't hesitate to reach out if you have any more questions in the future. Best of luck with your new role in demand planning! 🌟 If there's anything else you need, we're here to help. Happy learning! 🚀✨
This is the key for a sustainable economy with less overproduction and better consum! Love it!
You're so welcome! tks for your comment.
Your voice is so good and pleasing that I forget to concentrate on the actual topic. But I find the background video very distracting, specially those vehicles moving in city. Lol
thankyousomuch!💚💚
You're welcome 😊
Hi ! I'm working as a material planner in a multinational company. I'd like to know who has better salary: 1. Supply Planner, 2. Capacity Planner, 3. Demand Planner. My idea is in 2-3 years become one of these and I'd like to know which one has better salary potential. Many thanks ! :)
Hello there! thank you for commenting.
I think they are all great areas of supply chain to go into. But in my opinion, the one with the most potential for growth is as a Supply planner. I believe that is the case because Supply Planning entails both capacity requirements planning and demand and forecast planning. This means that supply planner will have to know both because it is the bigger umbrella position that operates both.
I have added a link on some additional info on all 3 positions if you are interested.
Supply planner salary:
www.glassdoor.com/Salaries/supply-planner-salary-SRCH_KO0,14.htm
Capacity planner salary:
www.glassdoor.com/Salaries/capacity-planner-salary-SRCH_KO0,16.htm
Demand Planner salary:
www.glassdoor.com/Salaries/demand-planner-salary-SRCH_KO0,14.htm
Thank you, this video was informative.
May I suggest to use static background? It is very distracting and draws attention from the content. I could not watch more than two minutes.
Dear Friends, I understand that demand plan is the supply chain department's forecast based on sales history and market sensitivity, and it is used to counter the sale forecast from sales department, right ?.
Yes, the demand plan uses quantitative data (sales numbers from previous months/years) and also qualitative data (expert's opinion or input) to create a prediction of what the company thinks will sale. Once this demand plan is created, you can then create a supply plan (which tells the company what to procure or produce in order to satisfy that anticipated demand). Hope that helps!
@@MVCLogisticsAcademy Good intro. Question: how do you see ML (Machine Learning) and Big Data playing a part in Demand Planning? For example, "origins" of Demand Planning use typical sales, orders, etc data... but what if we could leverage 'big data' from the internet to teach a system (using ML) to find & learn from trends in other markets, data from other companies, public data, social media data, etc? Are there any practical examples of this being used for Demand Planning currently?
hello, thank you for commenting, and for your patience on a reply.
From my experience, and from doing some research, I see machine learning (ML) and big data playing a significant role in demand planning by enabling organizations to more accurately forecast demand, optimize inventory levels, and reduce costs. By leveraging big data from a variety of sources such as the internet, companies can use ML algorithms to analyze and identify patterns and trends that may not be immediately apparent through traditional data analysis.
-One example of how big data and ML can be used in demand planning is by analyzing data from social media platforms such as Twitter, Facebook, and LinkedIn. By monitoring conversations related to products or services, organizations can gain insights into customer preferences, sentiment, and emerging trends. This information can then be used to adjust demand forecasts and inventory levels accordingly.
-Another example is using public data such as weather and economic data to predict demand fluctuations. For instance, a retailer can leverage weather forecasts to predict demand for seasonal items such as clothing or outdoor gear, and adjust inventory levels accordingly.
To leverage big data from the internet to teach a system using ML, organizations can use techniques such as natural language processing (NLP) to extract meaningful insights from unstructured data such as social media posts or news articles. By combining this data with internal data such as sales data or historical demand data, organizations can build more accurate demand forecasting models.
Practical examples of big data and ML being used for demand planning currently include:
-Amazon's recommendation engine: Amazon uses ML algorithms to analyze customer data and provide personalized product recommendations based on individual preferences and purchase history.
-Walmart's demand forecasting system: Walmart uses ML algorithms to predict demand for products and adjust inventory levels accordingly, helping to reduce stock-outs and overstocks.
-Coca-Cola's supply chain optimization: Coca-Cola uses ML algorithms to optimize their supply chain by analyzing data from sales, inventory, and production to forecast demand and adjust production accordingly.
Overall, the use of big data and ML in demand planning has the potential to significantly improve supply chain efficiency and reduce costs. Companies will need to leverage data from a variety of sources and use advanced algorithms, which will help them gain insights into customer preferences and emerging trends while adjusting inventory levels accordingly to improve customer satisfaction and profitability.
This reveal majority buy until people calculate extra production to logistic handle in auchan.
Where is the academy located?
thanks, very helpful, but i need more...also, can you recommend demand and supply planning online certification course and institution.
Hello, thanks. We offer supply chain courses that offer a lot more information on demand planning. You can check it out at www.mvclogisticsacademy.com
probelm when you start your video with banging music , the boss thinks im not learning
Sorry to hear that, I have reduced the intro music in more recent videos.
Your video is great but I hait when there is music while explaining. You can reduce volume or remove music when you explain.
Sorry about that, I cannot edit the music out at the moment because this was done with an editor I no longer have access to.
BUT! I will be making an updated video on Demand Planning in the coming days, so stay tuned, thanks for watching 🙂
Now days with semiconductors.. Forecasting means 1 to 2 years 😭😭
Especially LED drivers and most ICs (integrated circuits)
Hey there! 😄 Absolutely, you're spot on! With the current semiconductor situation, forecasting has become more critical than ever, especially for components like LED drivers and ICs. It's like peering into the crystal ball and planning ahead for the next 1 to 2 years! 🌟💡
The demand for these semiconductors can be quite unpredictable, and having accurate forecasts is essential to ensure a smooth supply chain and meet the needs of our customers. It's like navigating through a dynamic landscape, and we're up for the challenge! 💪🚀
working in Supply chain for these products, we have to be dedicated to staying on top of market trends, collaborating with suppliers, and keeping a close eye on industry developments to make sure we're prepared for whatever comes our way.
Thanks for bringing up this important topic, and we're thrilled to have you as part of our community! Keep sharing your valuable insights, and together, we'll navigate the world of semiconductors and make great strides in our supply chain journey! 🌐📈 Let's keep moving forward and lighting up the future! 💡🌟
very distracting video
thank you for the feedback, we have started making less distracting videos with more talking/narrative style. Hope you can check them out and let us know what you think!
Poor background music selection.. Annoying and Distracting
Trying our best, we are definitely working on improving our audio. Thank you for the feedback.