BPC - Predictive Algorithms, generating forecasts, modelling..

Hi,
What is the best way of generating an initial forecast based on historical data?
We've seen a sales demo which showed pre-defined algorithms being selected from a drop down list but cannot find any documentation on these..
Any pointers greatly appreciated...
...Thanks,
Chet.

James,
Thanks for your help with Chet's queries.
Sorry to keep going on about this but BPC has been positioned against another forecasting and planning product that offers predictive analysis and can generate a forecast based on historical data. (even Integrated planning can do this). So we are keen to show that BPC should still be considered as it also contains this functionality. Just increasing last years values by a %age is not going to keep BPC in the fight.
In the November 2007 webinar.
SAP Partner Community Webinar
November 2007
SAP Global Ecosystem & Partner Marketing
Slide 46
Why SAP® Planning and Consolidation?
has the following:
Predictive Analysis
�� Inference engine, automatic root cause analysis and cause/effect algorithms enable more accurate predictions over future
plans linked to corporate strategy.
�� Pro-actively delivers root-cause analysis vs. users searching for answers
Surely this cannot refer to the % and fix value functions you've mentioned above?
Thanks for your help
Regards
Tony

Similar Messages

  • 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

  • Need help with seasonal forecast model

    I am really struggling to get accurate forecast results for CBP using the seasonal forecast model. Our business has relatively constant consumption for 9 months of the year, say an average of 200,000 quantity per month. Then as we enter the 'holiday the season', there is a rapid increase in consumption to as much as 1.6 million per month in December.
    Seasonal model seems to work fine if my period indicator is monthly. But our consumption period and forecast needs to be daily. We have enough history going back to January 2010. Can somebody suggest what forecast view settings I should be trying? ... historical periods, intialization periods, periods per season, etc??
    I just can't seem to get the same forecasted holiday spikes for 2011 holiday season (Oct - Dec) or 2012.
    Thanks, Vlad

    Hi B.
    to expose an Adaptive RFC model to other DCs you must explicitly add the following entities to the public part of your DC:
    - Adaptive RFC Model entitiy
    - Logical Dictionary
    The Public Part Purpose must be defined as "Compilation".
    Important: To expose the Public Part to another DC you must explicitly trigger a DC Build (context menu item 'Development Component -> Build ...', so that the Public Part Archives is being generated. Without an existing PP archive the Client DC cannot 'see' the exposed Public Part Entities of the Service DC.
    Regards, Bertram

  • DP - Forecasting Models

    hi
    I need to work on forecasting models in my project. I read a lot of times on this subject various articles. I am still not understanding clearly the terms like Basic, trend, initialisation, Ex-forecast.. Is Ex Forecast generated by system automatically ? if so, what we should interpret from that ? its the forecast run in the past for comparison purposes. So if i run a forecast last month (oct 07) becomes ex forecast in Nov 07 ? What & How to do the Initialization ?
    Hope someone can pass the light on this
    thanks
    venkatesh

    Hi Venkat,
                      The basic idea behind using a statistical model is to analyze the historical sales trend and find a analogous mathematical equation there y use statistics to solve the equation. This equation depending on how the trend is have few constants. Like an equation y=ax1bx2cx3+..... where y is your forecast and x1, x2 and so on are independent variables and a,b,c,d are all constants.
    The statistical models here are using apha, beta, gamma and permo in place of these a,b,c,d. These indexes are used based on the curve.
    alpha index for basic value
    Beta index for Trend
    Gamma index for seasonal
    persmo index for outliers
                 Any curve always has basic value as it has to define where it starts from the base. If the curve is heading up or down, it has a trend (upward or downward) value. If the curve has a seasonal behavior like a sine or cosine curve, it also has a seasonal index associated with it.
    Basic: This value decides the vertical placement of the curve with respect to base. Higher the alpha(basic), higher the curve with respect to horizontal axis.
    Trend: Specifies the slope of the line
    Seasonal: Specifies divergence from basic value.
    Ex-post forecast: In the history available, you date back some time and consider part of the history as future. Then the history before this so considered forecast is used to forecast the future. You get a future curve and value. But you already have the future as it is history. This helps you compare the effectiveness of the forecasting model.
    Read this
    <a href="https://www.sdn.sap.comhttp://www.sdn.sap.comhttp://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/7a4025f8-0a01-0010-0fb2-b7ab22597675">document</a>
    This is the best source.
    If you select the ex-post forecast in univariate forecast profile, the system calculates the expost forecast and can be displayed below the history to compare.
    Hope this helps.

  • 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.

  • Unable to generate Logical Model Diagrams through Reverse Engineering

    Hi,
    I am currently using SQL Developer Data Modeler Version-3.0.04.
    I have generated Logical Model Diagrams from Relational Model Diagrams through Reverse Engineering (Done by pressing an" engineer to Logical Model button" on top panel of sql developer) .I saved the DMD file (source file) once i had done generating the logical diagrams.Now if i reopen the DMD and open the logical diagram again I found that most of the tables had lost their relationships.So i tried to regenerate the Logical Model Diagram again from the same Relational Diagram but it is not being generated unless i create a new Relational Diagram.Is there a way to generate multiple Logical Diagrams for the same Relational Diagram rather than creating a new one for each Logical Diagram to be created.
    Regards .
    Thanks in advance.

    Any comments on this issue?. Please let us know.

  • Long runtime when Generate Org model with CRM_R3_ORG_GENERATE. never finish

    Hi All,
    I tried to generate org.model with CRM_R3_ORG_GENERATE.
    But it ran for a long time. For a day and still not finished.
    I killed it and did again.  Same situation happen.
    I see process is running and use almost CPU time.
    Is this normal for this transaction? Can we tune it up?
    Note that our R/3 sale structure is quite large. The system is used by global.
    Thanks in advance for your advice
    Pichet A.

    I test extract list in  CRM_R3_ORG_GENERATE  to text file.
    It size is 87MB.
    Can I generate in background?

  • 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

  • How to generate org model through report

    How to generate org model using report .
    please share your information .
    thanks in advance ,
    sapcrm

    Hi,
    It's look like you are assuming that an organizational model can be created from external data input via a report. If so, then your assumption is wrong. There is no standard way to create a org. model from external input.
    As a standard practice SAP provided a report as mentioned in the previous reply. Using this report you can download ECC/R3 org. model into SAP CRM. This is the easy and best proven way of generating org. model in SAP CRM.
    Please let me know, if you need any further clarification
    Do not forget to reward if it helps
    Regards,
    Paul Kondaveeti

  • 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.

  • Generate Distribution Model ERP = EWM

    HI
    I am performing Generate Distribution Model ERP => EWM for new WH. Getting below error message.
    Method BUS2015.SAVEREPLICA exists in model view WMS
    Message no. BDDISTMODEL051
    Please Help to resolve as early
    Rgds
    Dinesh.P

    Hi Dinesh,
    When you are trying to Generate Distribution Model for your warehouse that time there are three fields one of those is your ERP warehouse number and Second is Logical System of EWM and third one is Distribution Model view. You might have entered a wrong model view name and then you tried to execute, system is giving you error that ".... method exists in model view WMS" that means you need to enter WMS model view in third field and then execute with radio button selected CREATE ENTRIES along with BOTH radio button selected.
    Thanks and regards
    Anoop Singh

  • 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

Maybe you are looking for