Dear Mustafa sir, the whole UA-cam community, and the whole world are blessed to have you here. You answered all the questions that were coming into my mind as the video progressed. It was like you were reading my mind and answering all the questions that I have. Thank you sir
Hy, did this help you in planning in real life? I am a Production Planner myself and I want to know which forecast method people normally use in forecasting demand in real life scenarios.
@@fsociety_ It depends on the data. This one he presented works well if the data has obvious repeatable patterns that repeat every year, like the one shown in the chart. If it doesnt have that, this method will easily fail.
This is absolutely an AWESOME technique! The seasonal adjustment is exactly what I needed and I put this into actual use -- Thank you for helping me look good to my boss!
This is the best explanation I've found and it basically answered even the questions I didn't know I had. Thank you. I've subscribed to your channel as well.
few question what if there are "controllable" factors that will effect the demand, for example, huge random advertising, or getting new businesses to order the products in large number I mean it will not be just seasonal, is there a way to determine the future demand? I have one in mind but not sure if it's scientific.
Couple of people criticized that I didn't de-seasonalize before finding the trend. No one can prove that the model will be superior if we de-seasonalize. Below is a link with a small simulation with random dataset. You can refresh it in Excel using F9 or you can enter a value in an empty cell to refresh in Google. I calculated the MAPE for both deseasonalized and not deseasonalized models. I have shown empirically that there is no obvious benefit of removing seasonality before finding the trend parameters. docs.google.com/spreadsheets/d/1YVjz1IZT8Hd489ZCifAIM5yTiuyk0qdcoCrdWIbBruk/edit?usp=sharing
Thank you very much, your video is very useful. Also, I tested the excel sheet that simulates the difference between the two trending approaches and it seems like the the differences in error is indeed random. Do you know if there are any papers or studies suggesting otherwise? Where did people get this impression from, that one needs to de-seasonalise before finding the trend? I'd be interested if this is true over say 100k trials - I'll attempt to run a python script to test it and check the distribution of outcomes
lalu225 I haven’t looked at the literature but if someone proves that there is no benefit it may get published. It would be interesting to try this on a large number of datasets and report empirical output.
Thank you a lot Dr. Mustafa for this great video. I have 2 queries: - is there a name for this forecasting method ? - What about if you had a data set for one year only, 12 months ? (Means January do not repeat etc...). Anything will be applied differently then ?
Thank you so much for sharing this technique. Very clear and simple to understand for even beginner for demand planning Thank you so much. I will try to utilize this method in my workplace
Thanks for the video. I think In order to improve the forecast, we should deseasonalize the demand first and then apply a Linear regression to obtain the trend, instead of just doing the regression on original demand
Please see my other comment for that. I know that what you described is a common process but empirically there is no apparent benefit. There is a link to the empirical "evidence" in my comment. I am thinking about writing a research note on that.
Super helpful video, I am requesting you make more video other forecast methods or help with link if it's already available somewhere. Thanks a Ton Mustafa
How can I forecast with sinusoidal forecasting. For example if we have 120 in January, 150 in Feb, 180 in March, ... 500 in July, 600 in Aug, 500 in Sep, 400 in Oct, 350 in Nov, 250 in December, 180 in January next year, 250 in Feb next and so on for the next Month usually have Demand like sinusoidal forcast? Can u let me know? Thanks
It is a different model and we cannot claim superiority of one to the other on a dataset without looking at the error measures. It is possible to create an ARIMA model in Excel but it is not going to be efficient. You can use R for fast results.
@@mcanbolat the better way to solving through SARIMA model is using the Phyton? Thank you for your explanation. To take a detail prespective, we should looking the errors, in order to determine which method is fit, isnt it?
This is a hidden treasure. I am so glad I found this channel. Could you possibly explain if the seasonality index we have used so far is what we call exponential smoothing ?/
Could someone please help understand the period column that was plugged in here? Is that the correct way to do it or is it just a representation of certain values that we might have?
@@mcanbolat Then can u please tell me if a company only has past data for 1 year, how should it forecast future months and mitigate the seasonal effects?
this video was super helpful! thank you! i have a question to calculate the growth/decline in demand for past and forecasted period, would you advice i use the seasonal forecast trend figures for all periods or actual sales for the past period with the calculated seasonal forecast figure for the forecasted period ?
My friend, love your video. In this case im trying to get a forecast for 2022. It seems like that the rule aplies to all the cells, but just the first till january to december are my data por 2022?
I’d like to build the ‘forecast.ETs’ function in Excel manually for sales forecasting so I can control the smoothing constants. I can get close using the holt triple smoothing, but I can never get the exact answer as ‘=forecast.ETs’. Any idea what to do? I won’t get management buy in without proving ETS manually
This is what ChatGPT says but I am not sure if it is true: The FORECAST.ETS function in Excel utilizes the Exponential Smoothing (ETS) algorithm, specifically the ETS AAA (Additive Error, Additive Trend, Additive Seasonality) model.
Use the solver to minimize the sum of the absolute differences between Excel’s forecasts and your forecasts by changing the parameters. You may be able to estimate the parameters Excel is using by default. I don’t think Excel is optimizing those per dataset.
THIS VIDEO IS SO UNDERRATED, IT SHOULD BE ON THE TOP OF THE PAGES
exactly
Exactly. Love from India.
I agree
Absolutely
Nothing but the truth there.I passed an interview practical with this video.
Dear Mustafa sir, the whole UA-cam community, and the whole world are blessed to have you here. You answered all the questions that were coming into my mind as the video progressed. It was like you were reading my mind and answering all the questions that I have.
Thank you sir
Thank you!
This video is literally a must for everyone that works as a planner. It’s one of the best educational videos out there
Hy, did this help you in planning in real life? I am a Production Planner myself and I want to know which forecast method people normally use in forecasting demand in real life scenarios.
@@fsociety_ It depends on the data. This one he presented works well if the data has obvious repeatable patterns that repeat every year, like the one shown in the chart. If it doesnt have that, this method will easily fail.
Many videos are watching, so im here and only this video I got the answer. Thankyou, love from Indonesia.
This is absolutely an AWESOME technique! The seasonal adjustment is exactly what I needed and I put this into actual use -- Thank you for helping me look good to my boss!
This video gets the number 1 sport for the most informative 13 minutes of my planning life.
Thanks.
You answered all the questions that were coming into my mind as the video progressed.
Dr. Mustafa is a Genous. He makes complex work easy to do.
I don't comment much, but this video is amazing. I'm impressed that a video so short could be so informative.
Thank you!
Wow, incredibly helpful. I learned more from this video than I've learned from the actual class all semester.
This is the best video I came across on model for forecast
This is much clear explanation than my prof who has 30 years of experience. Thank you so much.
God you're a genius. No one else has explained forecasting using Excel for Production and Operations Management as well as you sir.
Thank you!
Sir, you are the man of career development, love your videos
just predicted my future bills on excel w/ this method, thanks a lot!
You should get an award for this video sir 🙌🏿🙌🏿🙌🏿
Thank god i found your video man. You don't know how much I needed this before my interview. LIFESAVERRRRR
Incredible vid. Helped me on my exam with seasonal linear trend forecasting
This video is so educating it made me post a comment. Couldn't be better. Thanks a million
Thank you!
It was great when you taught me years ago and it's even better now that I have some real world experience. Fantastic!
Thank you Peter! Nice to hear from you!
Excellent video. Thank you very much for your help Dr. Canbolat.
Thank you very much! Just what I was looking for. Super helpful!
One of the great video regarding forecasting. 👏 Thank you so much need more video like this. Thank you so much.
Very well depicted. Follows all baby steps. Must watch for a newbie learner!
Dear Mustafa, you are great.
Awesome Mustafa, very well explained........
This has helped me so much!! Thank YOU Mustafa!
Absolutely fantastic explanation. You sir are a star!
Thank you @mustafa. Saved my life with this video. Definitely subscribing.
This is the best explanation I've found and it basically answered even the questions I didn't know I had. Thank you. I've subscribed to your channel as well.
Simple to understand and Great video
amazing breakdown of the forecast methods!
I hardly comment on videos here but this is wow!!!!!!
AMAZING EXPLANATION- also learnt renaming of a range. thanks sir
thanks brother
i will start my new job as an executive manager for a small factory and this is going to help a lot
few question
what if there are "controllable" factors that will effect the demand, for example, huge random advertising, or getting new businesses to order the products in large number
I mean it will not be just seasonal, is there a way to determine the future demand?
I have one in mind but not sure if it's scientific.
@@MohaAlraed my take is that since those events weren't seasonal you shouldn't take it into account when doing your forecast.
Thank you Dr. Mustafa. You described very well.
Awesome video, easy explanation, great presentation. Thank you very much. 👍
Great forecast work and nice and straight forward. Many other examples are more limited and don’t go this far.
Amazing video, i was looking for something like this for a while. Subscribed.
Very nice!! Love it!! The only thing I would say add is a quick explanation of key terms. Slope, intercept, seasonality.
Incredibly helpful. Great walkthrough, I was able to replicate the process with my data and drive some great discussion.
I got everything that I need. Well explained. Thank you to the creator of this video.
New subscriber here 🤗
Thank you so much. You made my task so much easy with this nice video
Very very informative. Great explanation. Thank you so much!!
Thank you so much for sharing your knowledge! An amazing technique
I loved this method. Superb.
Thanks, so muchh the video was really clear and the document help a lot to put It in practise. thanks a lot again.
Excellent Video , Thank you so much Mustafa
This video was so incredibly helpful! I love how you explained everything.
Couple of people criticized that I didn't de-seasonalize before finding the trend. No one can prove that the model will be superior if we de-seasonalize. Below is a link with a small simulation with random dataset. You can refresh it in Excel using F9 or you can enter a value in an empty cell to refresh in Google. I calculated the MAPE for both deseasonalized and not deseasonalized models. I have shown empirically that there is no obvious benefit of removing seasonality before finding the trend parameters.
docs.google.com/spreadsheets/d/1YVjz1IZT8Hd489ZCifAIM5yTiuyk0qdcoCrdWIbBruk/edit?usp=sharing
Thank you very much, your video is very useful. Also, I tested the excel sheet that simulates the difference between the two trending approaches and it seems like the the differences in error is indeed random. Do you know if there are any papers or studies suggesting otherwise? Where did people get this impression from, that one needs to de-seasonalise before finding the trend? I'd be interested if this is true over say 100k trials - I'll attempt to run a python script to test it and check the distribution of outcomes
lalu225 I haven’t looked at the literature but if someone proves that there is no benefit it may get published. It would be interesting to try this on a large number of datasets and report empirical output.
Thabks for the videos man, I am an operations and supply chain management major and your videos are amazing.
Thank you a lot Dr. Mustafa for this great video.
I have 2 queries:
- is there a name for this forecasting method ?
- What about if you had a data set for one year only, 12 months ? (Means January do not repeat etc...). Anything will be applied differently then ?
Hi Mustafa, this was great! thanks a lot for your video!
Great Video, This Video should be at Top...Amazing learned alot and would like to use this in real life. Thank you so much 😊
Straightforward and practical presentation. Thank you.
Thank you so much for sharing this technique. Very clear and simple to understand for even beginner for demand planning Thank you so much. I will try to utilize this method in my workplace
you're the best! thanks for explaining
Bravo Monsieur,
Thank you for your explications.
Hi Mustafa, very helpful video. Your voice is also pleasant to listen to. Thank you!
Thank you!
Thank you so much! I've learned a lot from this video.
This is exactly what I was looking for!! Super helpful for my upcoming interview.
Nice one, I liked the seasonality index idea. It's very simple but still gives a decent accuracy.
Amazing! Thank you! I agree with FSK... you made this so easy!
Done. Thank you po, Ma'am!
best video for forecasting!!!
Great example my friend. Very useful!
perfect video! thank you very much for this!
This was extremely helpful, THANKYOU!
Great 👍🏻 explained well
Thank you, so much for this insight.
dude, it is a amazing video , very helpful. thank you a lot
Thank you for this very detailed review of forecasting! Amazing!!!! :)
Thanks a lot man, amazing tutorial!!!! So happy to find this :) just simply brilliant
I hope that you will keep doing forecast for different kind of business sales. That would be great
Well explained thank you so much Mustafa
subscribed after watching this..
Great video. Thanks so much! :)
Thank you Mustafa.. very clear & helpful!!
Nice video Mr. Canbolat.
This is really helpful. However, I am trying to do this for several skus (30) do you know the best way for me to do that?
I already posted a video on that. Please see the descriptions of the video.
@@mcanbolat thank you!
Very useful for for budgeting. Thank you for this great video.
sindex! Heck yeah. Great video.
Many thanks! Really good explained!
This was so helpful. Thanks
this should be on top
Thanks for the video. I think In order to improve the forecast, we should deseasonalize the demand first and then apply a Linear regression to obtain the trend, instead of just doing the regression on original demand
Please see my other comment for that. I know that what you described is a common process but empirically there is no apparent benefit. There is a link to the empirical "evidence" in my comment. I am thinking about writing a research note on that.
@@mcanbolat Srry I didnt read the description. Thanks. Seems pretty interesting the low benefit of deseasonalize before regression empiricaly.
very nice. plz discuss ARIMA and Seasonal arima
Thank you Mustafa! Very helpful!
Thanks, your video helps me a lot. If you can add some equations attached in the sheet, that‘s will much better. But, anyway, it is an amazing video!
Super helpful video, I am requesting you make more video other forecast methods or help with link if it's already available somewhere. Thanks a Ton Mustafa
How can I forecast with sinusoidal forecasting. For example if we have 120 in January, 150 in Feb, 180 in March, ... 500 in July, 600 in Aug, 500 in Sep, 400 in Oct, 350 in Nov, 250 in December, 180 in January next year, 250 in Feb next and so on for the next Month usually have Demand like sinusoidal forcast? Can u let me know? Thanks
That is possible, you need to set up a sinusodial function with parameters and optimize the parameters to fit the line using Excel Solver.
Thanks a lot, kindly share a spreadsheet to practice i would be really helpful
Y there is link thanks
This is GOLD. Thank you so much +MustafaCanbolat!
Thank you so much. does it different with Seasonal ARIMA? Moreover, can seasonal ARIMA determine by Excel 2013?
Thank you Sir
It is a different model and we cannot claim superiority of one to the other on a dataset without looking at the error measures. It is possible to create an ARIMA model in Excel but it is not going to be efficient. You can use R for fast results.
@@mcanbolat the better way to solving through SARIMA model is using the Phyton?
Thank you for your explanation.
To take a detail prespective, we should looking the errors, in order to determine which method is fit, isnt it?
That would work too, there is no better way. Yes, you need to check the error measure.
@@mcanbolat I got more or less 10% errors using this sindex. Is it too big?
Thank you
This is a hidden treasure. I am so glad I found this channel. Could you possibly explain if the seasonality index we have used so far is what we call exponential smoothing ?/
Thanks. They are quite different. I have a video on exponential smoothing.
This is so helpful thank you !! But how can we calculate the error MSE ?
Find the difference between the actual values and the forecast values. Square the differences (forecast errors) then find the average of the squares.
Could someone please help understand the period column that was plugged in here? Is that the correct way to do it or is it just a representation of certain values that we might have?
Hi! can we find the seasonal indices for data that only have 1-year of actual sales data?
Hi It may not give you a correct result as it only depends on one-period data, you should have multiple years for more reliable results.
@@mcanbolat Then can u please tell me if a company only has past data for 1 year, how should it forecast future months and mitigate the seasonal effects?
this video was super helpful! thank you!
i have a question to calculate the growth/decline in demand for past and forecasted period, would you advice i use the seasonal forecast trend figures for all periods or actual sales for the past period with the calculated seasonal forecast figure for the forecasted period ?
It would be more appropriate to use the actual data.
@@mcanbolat thanks Mustafa, to clarify forecasted periods growth would then be (forecast-actual)/actual right?
My friend, love your video. In this case im trying to get a forecast for 2022. It seems like that the rule aplies to all the cells, but just the first till january to december are my data por 2022?
I’d like to build the ‘forecast.ETs’ function in Excel manually for sales forecasting so I can control the smoothing constants. I can get close using the holt triple smoothing, but I can never get the exact answer as ‘=forecast.ETs’. Any idea what to do? I won’t get management buy in without proving ETS manually
This is what ChatGPT says but I am not sure if it is true: The FORECAST.ETS function in Excel utilizes the Exponential Smoothing (ETS) algorithm, specifically the ETS AAA (Additive Error, Additive Trend, Additive Seasonality) model.
@@mcanbolat yeah, that’s what I’m trying to implement. But I can’t tie it to the excel function
Use the solver to minimize the sum of the absolute differences between Excel’s forecasts and your forecasts by changing the parameters. You may be able to estimate the parameters Excel is using by default. I don’t think Excel is optimizing those per dataset.
@@mcanbolat yes, I use the solver. I’m still unable to reproduce the exact results of forecast.ets
Great video!