Seasonality in Time Series: Integrate it into Demand Forecasting (Full Excel Tutorial)
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- Опубліковано 2 сер 2024
- Download the seasonal time series and forecasts here: abcsupplychain.com/download-s...
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How do you deal with monthly, quarterly, or yearly cycles in your business? 🔄 🤷♂️
Integrating them into your forecasts is essential to allocate the right resources (time, money, people) at the right time 📆
I just made a new step-by-step Excel tutorial to identify, calculate, and integrate seasonality into your forecasts.
In the comments, let me know how you deal with seasonality!
▬▬▬▬▬▬▬▬▬▬▬ CHAPTERS ▬▬▬▬▬▬▬▬▬▬▬▬
00:00 Intro
00:32 Why you need to integrate seasonality into your forecasts
01:35 Seasonal Factors
02:30 Temporality
03:46 Seasonality for statistical forecasts
03:53 Amazon example in Excel
04:13 How to detect seasonality
05:18 Seasonality per Quarter
06:41 Base 100 (Normalization)
08:24 Seasonal Forecast (Quarter)
09:02 Bike industry example in Excel
09:42 Seasonality per month
12:35 What to do if you don't have enough historical data
12:54 How to deal with outliers
13:08 Why use demand rather than sales
13:31 Value vs Quantity
13:59 Which level of aggregation? (granularity)
15:01 How to get a more reliable forecast?
►MY BLOG : abcsupplychain.com/
#forecasting #seasonality
Download the Excel (Free) here : abcsupplychain.com/download-seasonality-forecast/ 🎁
Join my Free Demand Forecasting WEBINAR : abcsupplychain.com/demand-forecasting-webinar/? 🚀
Very helpful
Very helpful video for me
Your videos are excellence and worth watching. Thanks for the ideas and knowledge shared
Thanks Leo, I appreicate the Feedback 🎉
excellent work!!
keep us entertained with your hard work.. just one suggetion try to make video from scratch, in most of your video you alredy prepared chat or feeded data.
Hi do you have some courses that you offer for demand forecasting?
i wrote the comment ont the old fitting video but because its propably not gonna be seen i want to send it here again
My university just copied this exercise one-to-one, didn't even change the numbers, and claimed it's a new database for VW. This is feel like straight up plagiarism
they even used the finised exel document as the solution they showed on the screen same colors same everything
Hello from Ukraine 🇺🇦! Please advice what should I do if FORECAST.ETS.SEASONALITY() gives zero (0)? For example, if there is no seasonality in data or it can't be calculated because of chaotic sales😢....thnks
Bonjour, j'ai une question concernant l'augmentation des prix d'achat qui se répercutent automatiquement sur les prix de vente et donc les revenus. Comment appréhender ce paramètre ?
Hi Sebastien (just answering you in English for my English channel 😉).
Consider two scenarios regarding how price changes affect demand:
-If changing the price impacts demand (which it usually does), I recommend checking out my Forecasting Expert course. In this course, I cover how to manage price elasticity effectively. You can find more details at: abcsupplychain.com/demand-forecasting-course/
-If changing the price does not significantly alter demand, it's advisable to normalize the sales data if the product price fluctuates frequently within the year. However, if the cost price only changes annually, no further adjustments are necessary.
Quick question, I have a strange data set. There's no similar seasonality within 3 years of historical data. And the sales history sometimes just fluctuates whether its increasing or decreasing. I've tried SES, Holt Method and Holt Winter Methods, but the error is so high. Can you help me?
Hi! I would advise you to focus on 1. removing outliers to get cleaner data 2. segmenting your data more to better identify patterns 3. considering the impact of external factors to identify other demand drivers
If you want to go further, check my complete Forecasting Expert course: abcsupplychain.com/demand-forecasting-course/
@@abcscTHANKS! But, lets say I remove January 2021. I cannot use the seasonality in Holt Winters bcs I cannot find the reference of the same month in 2022. What are you suggesting? Using a different approach? I was thinking about using ARIMA or SARIMA, but I cannot code it in phyton.
Ive found it, its either Croston Method or Syntesos-Boylan Approximation, both works great at minimum error
@@ruliajipriambudi4736I was about to say ARIMA but you can’t code in Python 😂
@@ruliajipriambudi4736 Great, those techniques are good for intermittent demand or "slow-movers" where demand occurrences are irregular and sparse.