Forecast model for Summer / Winter

Experts-
Need your help in customizing Forecast model in material master (Forecasting tab). Where these are defined in configuration? How to create new forecast model for Summer and Winter?
Here we are dealing with seasonal demands for purchasing different materials.
I am trying to figure out how to define Season codes for summer and winter? So I can flag material for Summer/Winter? As well as run forecast based on these codes? I understand that I can define season model or trend model, but in that case I will be unable to define which material is for summer and which one is for winter?
Looking forward for your inputs-
Thanks in advance.

Started using MRP controller for summar and winter parts.

Similar Messages

APODP How Forecast model for different product can be define ?

Hi Gurus,
I had forecast 1000 products and in that thousand products i have 300 slow moving products and 700 fast moving products.
I had taken Linear regression model for this products and run the forecast. My question is i wanted to forecast 300 slow moving products with Seasonal Model , can anyone please mention how we can forecast 1000 products with two different forecast models?
Waiting for your answers
Regards & Thanks
Raj

Hi Raj,
A little concept clarification here. The was forecasting model works is"
1. You create a forecasting model giving a key figure for which you want to forecast and assign a univariae or MLR or composite profile to it assigning a key figure which you want to use as history and a statistical model. (TCODE: MC96B)
2. Create a selection profile in interactive planning screen (TCODE: SDP94). Select all the products you want to plan for in this profile along with other selections.
3. Assign forecasting profile to the profile. This way you can assign different forecasting models to different profiles.
In your case,
1.Create two forecasting profiles one with Linear regression and the other with Seasonal model.
2. Create 2 selection profiles one with the 300 products and other with the other 700 products.
3. Assign Linear regression to one selection profile and seasonal model to another profile.
Hope this elaborates the solution. Please let us know if you have any other questions.
Thanks.

Best way to know correct forecast model - process chain set up with multiple forecast models

Hi Experts,
I need your help in selecting best forecast model for our company. We have some of the models already used for our company, and because of multiple models used it is taking very long time for process chain to finish. There is no existing documentation available on which model was used why initially. Please help me to make out forecasting process smooth.
- What is the best way to know, which forecast model is correct and should be used for our forecasting process.
- In case multiple forecasting models are really required to be used, please suggest ways to optimally schedule them in process chain.
- At times we get messages like "not enough data available" for specific model - any way to avoid this.
- How to optimally use parallel processing profiles forecasting process in process chain.
- Things which should be avoided.
Request your help, please share your experiences.
Regards
NB

Hi Neelesh,
There are many points you need to consider to redesign forecast process for your company/client.
You need to select the best suited forecast model first depending on the business. This has to be well tested & agreed by business users. Complexity will be an outcome of this exercise with business users. Best id to give then a brief intro on all available models & then help them selection the best one as per their requirement.
Auto selection models are generally more time taking & should be used only when you have no idea at all on the business/demand pattern.
Run time will depend how you are clubbing the CVCs to get the forecast generated & also parallel processing. For parallel processing profile you will need to do trial & error testing along with help from Basis team on how many free dial up processes are available.
Even you can run many forecast calculations in parallel if the product/cvcs are totally different. - As per my personal experience maximum run time reduction can be achieved here.
Daily run is not advisable except only for businesses where you have too much dynamism in demand planning i.e. you expect the demands to be changed overnight. Most of the companies run forecast on monthly basis or at weekly basis at the max.
"Not Enough data" will be a problem if you are having the irrelevant models used in forecast profiles. This means users are not bothered to maintain the needed data for he forecast calculations or they are not aware at all of the situation. Running such models on daily basis is not advised at all. Better users should use interactive forecasting & saving the results in such cases.
Just to give a crude example we get forecast calculated on monthly basis for approximately 4 lac cvcs in less than 3 hrs using moving avg, seasonal linear regression, seasonal trend, croston models. We use parallel profiles also everywhere with 10 blocks & 500 cvc/block.
Hope this helps. Let me know if you have nay more questions & also the results using any of this.
Regards,
Rahul

IDOC date interval for Profile values during Summer/winter change

Hi SDNers,
I have a Mail-to-IDoc Scenraio, where I need to import profile values with 15 min time intervals. Everything is OK except for the date of Summer/Winter change. For example the normal day has 96 intervals where the Day during which Summer->Winter time change occurs must contain 100 intervals. I tried the combination in various ways but in vain. I recieve SQL dup rec error or Invalid date error. Any suggestions how to implement this in an efficient manner.
Thanks in advance
regards
satish

Sachin,
No offence intended, but , it would be helpful if you can also tell us how you arrived at the soltuion.
Regards,
Bhavesh

Which Forecasting Model/ Forecasting Stratergy is suitable for Steel Plant

Hello Friends,
Could you pl suggest me Which Forecasting Model/ Forecasting Stratergy is suitable for Steel Plant.Any one having the steel plant experiance pl suggest me .
Edited by: sivaram2411 on Jan 19, 2011 6:37 AM

Hi Sivaram,
I haven't worked in Steel but worked in Cement industry. Cement is another input to construction industry, just like steel. In India, both have seasonal demand. But I would give a generic suggestion here, though you can check with your network in other steel companies having similar product offering as yours, about the forecasting model they follow.
Choice of forecasting model is not industry dependent. Because within the same industry, each player has a different product mix, different set of customers and in different geograhies. Forecasting model is selected based on the analysis of historical data. So you can take last 2 years available data to start with.
Demand Planning provides the following statistical forecasting models: constant model, trend model, seasonal model, trend and seasonal model, Croston method with exponential smoothing, linear regression, and causal models with multiple linear regression (MLR).
Time series models are the most commonly used forecasting methods.
The flow chart is like this:
Raw Data collection --> Data analysis --> Analyzed data --> Forecasting Model selection
You can use plotting as a method of Data analysis,
We need to find the best forecasting model, so that it gives us the most accurate demand. There is no systematic approach for the selection of a forecasting model and you need to find the best for you by trial and error.
The following factors impact the model selection: (1) Forecast Horizon (2) Data Availability / Requirements (3) Pattern of Past Data (4) Level of Detail in the Forecast (5) Cost Factors (6) Accuracy and (7) Ease of Application.
So use the historical data, analyse it, try using the available forecasting methods one by one to forecast for a period during which the actual data is already available with you and find the one which is best matching the actual figures. The model giving most accurate results, or the one with least forecast error, would be the one you are looking for.

Formula or Methodology used for Seasonal & Linear Regression Forecast Model

Hi all,
I am using the Forecast Model 35 (Seasonal & Linear Regression Model) for Statistical Forecast generation.
Now I am facing the Issue that my Model 35 is consistently Under Forecasting.
Can anyone let me know what Formula or Logic is used by the Model to generate the Statistical Forecast.What are the Parameters that can really improve the Under Forecasting trend for Model 35.
kindly help...
Thanks & Regards,
Vishal.S.Pandya.

Couple of quick checks that you should do
1. Make sure there is no Like Profile active for that planning object that is interfering
2. Do a Strategy 56 to test for season and trend. See if streatgy 56 indeed recommends regression model
3. If strategy 56 fails for season or trend, and you enforce seasonal or linear regression model - i would expect to see the behaviour you are seeing
4. Make sure there are adequate time buckets for forecast initialization
5. Make sure the forecast initialization buckets are representative of the forecasts and are not outliers
IN this regard do check
http://help.sap.com/saphelp_scm50/helpdata/en/19/06f74ee2ed11d3b78d0000e82debc6/content.htm
http://help.sap.com/saphelp_scm50/helpdata/en/96/d261f8e39011d3b78e0000e82debc6/content.htm

Calculation of Safety Stock and Reorder Point under Forecast Model T

Hi Gurus!
Happy Holiday!
I would like to ask for your assistance on how the the safety stock and reorder point was calculated with the following values available. I would really appreciate it if you could give me details on the calculation.
Below are the values:
Basic data
Forecast date        01.12.2009        Unit                  CTN
Forecast model       T                 Service level         0.0
Period indicator     M                 Paramtr profile
Control data
Initialization                                Tracking limit        4.000
Model selection      A                 Procedure selection   2
Parameter optimizatio                Optimization level    F
Alpha factor         0,10               Beta factor           0,10
Gamma factor       0,00              Delta factor          0,30
Basic value           5.464-           Trend value          5.603-
MAD                      4.758            Error total              4.722
Safety stock         1                   Reorder pnt.          1
No. of values
Consumption           6                Forecast periods       1
Initial. periods      0                Fixed periods          0
Periods per season   12
Historical data
Period                Original     Corrected value
11.2009                3.000              3.000
10.2009                0.000              0.000
09.2009                0.000              0.000
08.2009                9.000              9.000
07.2009               21.000             21.000
06.2009               20.300             20.300
Forecast results
Period                Original     Corrected value
12.2009                0.000              0.000
Appreciate your assistance!
Thank you and Happy Holidays!
Ji

Sweth, you are asking for consulting, and in my opinion it is way beyond what can or should be reasonable to achieve in such a forum. You are asking complex questions, that most probable have more than one possible answer.
I suggest that you get on-site help from a knowledgeable and experienced consultant. These are crucial business issues, and should be dealt seriously.

Several forecast models

Hi,
I need to see the result of several forecast models. how to do it ?
Do I need to create n number of forecast profie to see the result of n number of forecast models or in one profile I can see the result of n number of forecast models.
Thanks a lot in advance,
Prabhat

Hi Senthil,
Thanks for your answer. I am getting lot of help from you.
You are correct that in the second tab we can change the models and see the different result based on the model we select.
But the thing is - there we have only few models to select for but when we create the forecast profile we get lot of options to select the forecast model.
Is it possible to to show the result of various forecast models under one forecast profile.or Do I need create multiple forecast profile for multiple models.
Thanks once again for your support.
Thanks,
Prabhat

Finding the forecasting model selected by Model 56

Hi,
If I use statistical model 56 and run statistical forecasting, how do I know strategy 56 is finally selecting? I see the errors and the parameters when I click the "forecast comparison" icon. But I wan to know which model the system finally selected? Is there any tale that tells me that?
How do I do the assignment of forecasting model to a selection id and forecast and see the results in the background? ANy tables, programs???
Thanks.

Hi Sinivas,
Thanks for the reply. But I am asking is to see what model 56 finally decides to go with? I mean trend or seasonal or....how can I know that the automatic model has selected a particular model after testing for all the models.
Hope this is clear.

Creating a New Forecasting profile for MRP

Hi there,
Please can somebody let me know how do I create a new Forecasting profile for MRP.
I want to see this in table MRPR once created. (field PROPR).
Kind Regards,

Dear marelizen
Use transactio code MP80.
Creating a Profile
The information contained in this info object is relevant to the material master for industry and to the article master for retail. Retail customers are requested to substitute:
article for material
requirements planning for material requirements planning or MRP
1. In the Material Master menu, choose Profile ® MRP profile or Forecast profile ® Create.
The initial screen appears.
2. Enter the name you want to give the profile.
If you want to use an existing profile as a reference, enter its name under Copy from so that the system can copy its values to the new profile.
3. Choose Selection screen.
The selection screen appears. It shows all the fields that can be copied to the MRP or Forecasting screen in the material master record.
4. Enter a profile description and select the fields you want the profile to contain, specifying whether each field is to be copied to the material master record as a fixed value or as a default value.
It is not possible to select Fixed lot size and Maximum stock level in a single MRP profile. However, if you select Maximum stock level, you must also select Lot size (materials planning).5. Choose Data screen.
MRP profile data is spread over two screens. To switch from one screen to the other, choose Data screen 1 or Data screen 2.
When you access the data screen from the selection screen, the system checks whether the fields selected are allowed to appear in the same profile.
The data screen appears, containing only the fields you selected on the selection screen. The fixed values and default values are displayed in different colors. All fixed values are required fields except where the field can also be left blank.
If, in the forecast profile, you enter N or 0 as the forecast model, no forecast is made.
Like forecast model N, if you enter forecast model 0 when maintaining a forecast profile, you will be unable to maintain any other field in the profile.
Unlike forecast model N, forecast model 0 deletes any existing forecast values when you change the material. This ensures that these values are no longer included in materials planning.
6. Enter the corresponding values and save the profile.
If the system detects inconsistencies or errors, it asks you to change the fields selected on the selection screen and/or to correct the values. Otherwise, the initial screen appears, where you can begin to create another profile.
warm regards
Ramakrishna

Forecast model K (Constant with smoothing factor adjustment)

Hi All,
i am using forecast model K in materail master. I would like to know the system calculation on forecast value?
For Example:
Consumption qty maintained in material master for last 3 months.
Period          Total consumption
04.2011     100
03.2011     150
02.2011     200
When i am using Forecast model K, system is calculating as follows,
Period       Orig. HV   Corr. HV   Ex-post FV     Orig. FV
M 02.2011          200        200
M 03.2011          150        150        200
M 04.2011          100        100        155
M 05.2011                                                           106
05.2011     Forecast value is 106, Basic value is 105.500, Error total is -105 and MAD is 27.
I would like to know the system calculation of these value. Particularly Basic value and MAD.
And also the difference between Forcast Model D and K if possible.
When i am using Forecast model D, system is calculating as follows,
Period       Orig. HV   Corr. HV   Ex-post FV Orig. FV
M 02.2011          200        200
M 03.2011          150        150        200
M 04.2011          100        100        190
M 05.2011                                           172
Basic value 172.000,         MAD 38,         Error total -140
Thanks in advance,
Babu

MODEL K:
Constant Model with First-Order Exponential Smoothing
The constant model with first-order exponential smoothing is derived as in formula (5). A simple transformation gives the basic formula for exponential smoothing as shown in (6).
To determine the basic value, you only require the basic value from the preceding period, the last past consumption value and the alpha smoothing factor. The smoothing factor weights the most recent consumption values more than the less recent ones, so that they have a stronger influence on the forecast.
The forecast value is the basic value for the last period for which historical data is avaialble, that is the last ex-post period.
where k> n
How quickly the forecast reacts to a change in consumption pattern depends on what value you give the smoothing factor. If you set alpha to be 0, the new average is equal to the old one and the basic value calculated previously remains; that is, the forecast does not react to current consumption data. If you give alpha the value 1, the new average equals the last consumption value.
The most common values for alpha lie between 0.1 and 0.5. An alpha value of 0.5 weights past consumption values as follows:
1st historical value : 50%
2nd historical value : 25%
3rd historical value : 12.5%
4th historical value : 6.25%
and so on.
The weightings of past consumption data can be changed by one single parameter. Therefore, it is relatively easy to respond to changes in the time series.
The constant model of first-order exponential smoothing derived above is applicable to time series that do not have trend-like patterns or seasonal-like variations.
MODEL D:
I think that simple constant model is just a normal average.

Forecasting models and errors

Hi Expeing
I have following queries with regard to the forecasting Techniques:
1)How can we identify the periods in Seasonality?How to judge the seasonal periods to be taken for running the seasonal forecasting models?
2)How the errors are used in judging the forecast?As we have 6 errors what is the importance of the errors(MAD,MAPE,MSC,MPE,RMSC)?
What error should be taken as consideration while forecasting?
Why some planners only consider MAD and some planners only consider MAPE ,MSC while judging the forecast models?What is the difference between MAD,MAPE,MSC,MPE &RMSE
Please throw some light on the above questions.Your reply is highly awarded.
with regards
sai

Dear Sai,
No answer can be exhaustive .I have tried to explain as short as possible.
For Identification of periods of seasonality ,it is important to clean the historical data from abnormal high and low sales.Abnormal high sales can be caused by sporadic opportunities and low sales may happen due to natural calamities. These unnatural sales should be removed in consultation with business people to get clear picture.
Seasonal variation is measured in terms of an index, called seasonal index. It is an average that indicates the percentage of an actual observation relative to what it would be if no seasonal variation in a particular period is present
Measuring Forecast Errors
Method and Purpose
Mean squared error (MSE): Measures the dispersion of forecast errors; large errors get more weight than when using MAD. Therefore, it is sensitive to non-normal data contaminated by outliers, and such data are common.
Mean absolute deviation(MAD):Measures the dispersion of forecast errors.Measures the size of errors in units. Though it is a good measure for single product forecast, but if we aggregate MAD over multiple items, there is a possibility of high volume products dominating the results. MAD is a linear metric for error and gives same weight to all errors , large or small.
Mean absolute percent error (MAPE):Measures the dispersion of forecast errors relative to the level of demand.It measures the size of error in percentage terms. A MAPE of .19 suggests that on average the difference between the forecasted and actual values is 19%. MAPE is scale sensitive and therefore meaningless for low volume data or data with zero demand periods.
RMSE:The quadratic error provides estimates that are more linked to variance and standard deviation of demand distribution. RMSE is a quadratic metric for error and tends to overweight large errors.
Regards,
Samir Baruah

Forecast Model in Demand planning and E book Sap trainingcourse

Dear Experts ,
I am Exploring differnt Forecast Model , like constant
model, trend model, seasonal model, trend and seasonal model, Croston method
with exponential smoothing, linear regression, and causal models with multiple
linear regression (MLR).
is there any SAP links or material or course availabe to learn more about Forecasting Techniques that we can use in Demand Planning in APO
if you have idea please help me to learn .. i am really starving for this techniques
Thanks in advance
Cheers & Thanks
Raj

Hi Raj
Below link will give you entire information on forecasting models, forecasting accuracy technequues etc,:
http://help.sap.com/saphelp_apo/helpdata/en/33/437a37b70cf273e10000009b38f8cf/frameset.htm
For MLR refer the following link:
http://help.sap.com/saphelp_apo/helpdata/en/ac/216ba4337b11d398290000e8a49608/frameset.htm
Which is the best model to use:
You should try running forecasting using various model(seasonal, seasonal linear, linear, constant etc) and comapre
the forecast accuracy and find out which one is the best suitable.
Another way is to choose auto model which will select the best possible forecast strategy and give the result.
I hope thos will help you.
Please let us know if you require any more information.
Thanks
Amol

Best SOP Model for MRO Type Industry?

Hello all,
At the company I work for, we currently utilize SAP's SOP module for flexible planning of roughly 200,000+ MRO materials. SAP comes standard with 18 or so forecast models out of the box that can be used to determine the best forecast of materials. We are currently doing some analysis around what the best model is as a result of seeing our current forecast strategy, (Seasonal trend based on the Winters method,) working for us but doesn't pick up trends very well leading to a lot of forecast corrections.
Question to the group. In an industry that has a lot of volitility of it's materials demand over periods, what model have you used to help pick up trends over short periods of time?
Any insight would be greatly appreciated.

Hello,
Are you using S&OP on HANA or SOP in ECC - PP. ?

Forecast model changing

Hi
For a material in material master iam maintaining forecast model as "J".
The other parameters maintained are:
selection procedure-2
tracking limit-4
reset automatically- is checked
model selection-A
ALPHA FACTOR AND GAMMA FACTOR MAINTAINED
initialization-X
Now when i run the program RMPROG00, then in isee that the forecast model changes to "blank" or "D", "S". pls tell me how this change is happening?

Hello Dinakar,
I am also facing the similar issue, Are you able to get rid of this issue.
regards,
JPS

Forecast model for Summer / Winter

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