Forecast tuning in demantra

Hello All,
We are analyzing client data and found about 2/3 of the item location combinations in mdp matrix are too young to generate the forecast.
what else can be looked at to analyze the data.
Regards

Hello Kirit,
Please check whther your max_sales_date, last_date_backup on sys_params table is set according to the clients history data.
For eg if you are on a dev instance and your instance is as old as Sept 2009 and your max_sales_date is set as Feb 2010 then this will make most of your item location combination young.
So set the dates approroriately.
Update prop_changes on mdp_matrix to 1 and then execute proport.
Also check your dying time and mature age parameter.
Best Regards
Thomas

Similar Messages

Forecasting Models in Demantra

Hi All,
Does any one tried with only enabling certain models in Demantra. In business modeler, I enabled only regression in model library and ran the engine. I compared with demantra forecast with all the models checked. There is no change in demantra forecast. Is it the expected behaviour. Inspite of user input, demantra goes only by the recommendation from baysean model?
Thanks
Ramkri

Hi
Plz check the following
Demantra - Reciveing flat line forecast (Naive)
Forecast Engine forecasting 2.5 to 3 times more than expected
Statistical Forecast - generates the same forecast qty for all periods
Demantra: Very good historical fit -> Bad forecast
forecast tuning in demantra
Hope it will help
Tks
MJ

Multiple Forecast Streams in Demantra

Hey,
I've noticed release note for 7.2 includes the following enhancement:
"You may want to create statistical forecasts from multiple demand streams.
You can generate a forecast from any data stream, for example, booking history and shipment history. Each data stream has a unique engine profile and version."
I haven't been able to find much documentation about this option.
Has anyone implemented a solution using that ? Know any HOW-TO documents available?
I'm thinking of using it for forecasting - item sales, and item returns from customers.
How should SALES_DATA be loaded for that scenario? How should engine be run?
Thanks alot for any reply,
Aaron

Hi All,
Forecasting with multiple demand stream means that you can generate multiple forecasts based on different demand stream. By demand stream, i mean the historical data stream on which you want to generate the forecast.
There can be situations where you may require to generate forecast for different purpose.Like Aaron mentioned, you may want to generate a forecast based on the order/booking history and/or you may want to generate a forecast based on the returns history. For this purpose you need to create different engine profiles.Engine profile is nothing but a set of engine parameters with specific values. Oracle Demantra provides some predefined profiles for different purposes, and you can define additional engine profiles, as needed. When you run the Analytical Engine, you specify the engine profile to use.
Now coming to the HOW-TO part:
1) The quantity_form (system parameter) contains an expression that is used by the engine to retrieve and aggregate demand stream data from the SALES_DATA table. Make sure that the quantity_form expression for a specific engine profile points to database columns containing the historical demand stream desired for the profile. Meaning, if you want to generate a forecast based on booking history then the quantity_form should point to the booking history stream in the sales_data table. Likewise for returns history, point the quantity_form to returns history stream in sales_data table.
2) Create a series to view the forecast generated by the engine profile.
3) The newly created engine profiles gets added to the list of engine profiles in the system parameters.You can select the required engine profile and generate the forecast.
4) View, Edit or compare the forecast created in step 4 by creating a worksheet with all the forecast generated.
I hope this brings more clarity to the queries/replies posted earlier.
Regards,
Shekhar
Edited by: Shekhar on Feb 18, 2009 10:02 AM

Demantra forecast disappears intermittently from ASCP.

Demantra forecast disappears intermittently from ASCP. Need to run Upload local forecast workflow again and then the plan run to view the forecast again, Can anyone tell why is this happening?
However the forecast entries are not disappearing from the Denorm table.
Thanks
Somanath

if the data is available in denorm table, then some planning program is causing this issue. demantra worflow or forecast publish from demantra works fine.

Lead time information in Demantra

Hi
For a POC, We need to get lead time data from ERP(R12) to Demantra. Can I use Lead time as one of the attributes in data model? is there any other better way to represent the same in Demantra?
What are the inputs for forecast generation in Demantra (Other than Historical series, Causal factors and engine/non engine parametes)
Thanks
DNP

Mismatch of forecast values having similar history on 7.2.0.2 VS 6.2.6
Hi,
check the following
Hope it will help you
Demantra - history period to be considered for forecast ???
Forecast generation horizon
Demantra Forecast clarification
System Parameter
Demantra - sytem parameter - max_fore_sales_date
Thanks
MJ

Can Demantra Forecast at a National level?

Good afternoon Forum,
I posted a thread about a month ago and am back again to hear some more good advice and information. I work in a business group which supplies spare parts nationally through regional distribution centers for a large industrial equipment installed base. Despite me being against this, our management has decided to use Demantra to forecast parts usage at the National level and then force down to the regional distribution centers to take a percentage of parts based on past percentage of the total, rather than roll up the individual regional forecasts to create a total.
My question is can Demantra be set to do this? What would it take? Besides being less accurate at a regional level, what other drawbacks are there?
Thanks in advance for any assistance you can provide.
Best regards,
ABoyNamedJoe

Hi Maggie,
To solve the proble, I think the best way is to create something like dummy entity, which is usually called adjustment entity as Alwin mentions.
Please remember not making any child entity of the adjustment entity. Otherwise, the adjustment entity won't be base-level member anymore, and you can not post data.
Hope it helps.
Atsushi

Can demantra(7.2) forecast at hourly level??

I have a requirement where the forecast needs to be done at hourly level .
Can it be done in demantra ?
As per implementation guide for demantra 7.2 , it seems it can be done. Implementation guide says :
"The base time unit is specified during configuration to a length that is appropriate for
your planning cycle. Oracle provides three sizes of base time unit (day, week, or month)
and *can support hourly time units if needed*."
Please let me know, if you know the details of such setup
Regards

Hi,
I think i was not able to explain the question well . I know that the forecast cycle can be run each hour.
My question is : can the forecast be generated at hourly bucket ?
can we give history in terms of hourly bucket and get the forecast in hourly bucket too?
The time level aggrgation may look like : - hour -> day -> week -> month
As per data model, there seems to be only three time bucket option is there i.e. day , week and month.
But as per implementation guide , we can also forecast in hourly bucket. if it can be done , can some body let me know what the extra step required .
Regards

Forecasting the need of spare parts in Demantra

Hello everyone,
I would really appreciate if anyone who's had dealt with the following issue help us,
The thing is - we want to forecast 3 different kind of items:
1. Main items we sell - for examples - machines.
2. Accessories for machines we sell. A certian accessory can be used with several type of machines. (Cables, Batteries etc.)
3. Spare parts we need to keep in stock in order to provide repair services for our customers.
Each machine we sell has a different set of spare parts used when repairing.
The forecast for machines is a typical demantra model forecast.(sales forecast by the book).
My question is regarding the forecast for the spare parts we need for repairs.
We know that demand for a certain spare part is influenced by how many machines which use that part were sold to customers.
Also - it depends how common is the use of that part when fixing those machines that need service.
(some parts get broken more frequently etc).
Also since we provide fixed price insurance for customers, they dont "see" spare parts price as a factor.
(they dont naturally "buy" the parts).
How can demantra tie the forecast for the spare part to sales history of machines? Can demantra forecast service ?(which behaves alot different than sales). It is obvious that forecasting demand for spare parts with looking only at each part's history will not provide best forecast results.
Any insights anyone?
I'm pretty sure most implementations faced that issue - regarding the forecast of parts for service -
Would appreciate any reply,
Thanks alot,
Aaron.
Edited by: user10894682 on 07:30 05/02/2009

Hi Aaron,
Per my understanding,you sell machines as well as their accessories.So forecasting for them is by the book where you would be using the demand for machine as well as for accessories..
As far as the service parts' forecasting is concerned, Oracle has a seperate module for Service & Spare parts planning based on Demantra's forecasting engine.
Spare Parts Planning(SPP) has the following features:
1. Forecast accurately with built in Demantra's Forecasting engine
2. Replenish spares based on Single plan model
3. Distribute spares using SPP's plan
4. One single UI to carry out all 3 above processes for improved productivity
5. Forecasting based on Shipments, Spares Usage, and Returns
6. Plan based on Service parts failure rates calculations
7. Integrated with various APS modules like Demantra DM, CP, IO, and ASCP.
From demantra's perspective you may try out the following:
Since you provide fixed price insurance for customers,you would definitely be keeping track of the service provided like what spare was replaced and probably how many of the same spare have been replaced for a particular customer over a period of time. Also as per the insurance you must have specified that a particular spare would be replaced only x number of times within a span of say 6 months or 12 months.
You may utilize these information to classify the spares based on the frequency of use viz. very frequent, medium frequent and less frequent and associate some factor to it.You can club this information as well as the spare parts demand coming out of the BOM (bill of material) of the machine along with each part's history and come up with a forecast that can be more relied upon.
I hope this helps.
Regards,
Shekhar

ASCP Plan Is Not Able To Read Global Forecast For Options Published By Demantra

ASCP plan is not able to read global forecast for options published by Demantra
ASCP plan is not able to read global forecast for options published by Demantra. Only Model Forecast is being read into ASCP plan.
1) We are publishing global forecast from Demantra at CTO/Zone/Week level and it is getting published properly to ASCP denorm table.
2)There is no forecast explosion being done in ascp (plan option explode forecast is not checked)
3)The sourcing rule is set at zone level for the model saying source from an organization (org code 11)
4) The profile: msc:-Organization containing generic BOM for global forecasting is set to 22 which is a reference org
5) Now when we run the plan the model forecast goes to org 11 but the option forecasts do not go properly
6) We have just one line created for the option (production forecast) with a wrong quantity
7) Demantra has forecasts for both Model and options

Looking at the error message "The Network Adapter could not establish the connection" , It appears hostname and port may be incorrect. Review the targets.xml under E:\oracle\product\10.2.0\db_1\SAP_solman_SDB\emd and
emoms.properties under E:\oracle\product\10.2.0\db_1\SAP_solman_SDB\config folder to make sure host ( sap_solman) and port (1527) are correct.
As far as setting the environment variables goes, you can go to control panel -> system -> advanced -> environment variables and set the ORACLE_HOME and ORACLE_SID
-Ramesh

Demantra Forecast clarification

hi everyone,
a small clarification. supposing forecast has been generated for the entire list of items during the analytical engine run once.
now when i am running the engine again, i want to retain the forecast generated previously during the last run for some items.
is there a way to do this.
also how do i find out if a particular run of the engine(run previously) has been in dp or pe mode.
regards,
karthi sankar!

Hey there,
For your requirement, cleary what you need to use is the LOB functionality (Line of Business).
In this functionality, you set the engine to run on a subset of your data.
You define which data by setting system parameters - engine - shell - Integration1LOBLevel: Defines the Table name by which you segment your data.
and - engine - shell - Integration1LOBPopulation - to define the members to be included.
Segmentation can be done by any level in your model.
Example: Say you have a level called Item Type. Then - Level = Item Type.
And to find the Population - you need to query the table Demantra created for this level (t_ep_Xxx) and note the id's for the members you want to include in the engine run.
There is an LOB workflow that you need to run.
First stage - looks at those system parameters and for all other members update prediction_status to '96' which means no forecast.
Then engine is run only on that population combinations only.
Then there's a stage that copies all other combination previous forecast, because it mustnt be changed, it also copies back the correct predication_status before it was run over by 96.
You can read more in the Implementation guide, although I have to say documentation is not that detailed.
Hope this helps,
Aaron

The three members in Demantra level Forecast System Status represent what?

There are three members in Demantra level Forecast System Status. Good For Forecast, Young Address, and Dead Address. What do each of these mean and how does it work?

Hi,
98 (Young) — Sales for this combination are too new to be used for prediction.
99 (Dead) — Sales for this combination are not recent enough to be used for prediction.
1 (Live or Active)—Neither young nor dead.
Tks
MJ

Demantra - history period to be considered for forecast ???

In the current system I have 5 years of history sales data - but for my forecast I need to consider data only for the last 3 years.
Are "history length" and "start date" are the only parameters which decide the history length or is there any other parameter also considered in deciding the length of history to be considered for forecast generation.
Appreciate your response.
thx and rgds,
Pankaj

Hi,
Check whether the following parameters fulfill your requirement.
StartAverage
AverageHorizon
PromotionStartDate
last_date
Tks
M J

How to install Demantra on 64-bit machine so that all components work?!!

I'm using 64-bit windows 7. I first installed Oracle DB 10.2.0.4 x64, then Demantra 7.3 x64. Some component of Demantra didn't work, wouldn't open giving me the following error "Can't connect to database Oracle library OCI.dll or ORA803.dll couldn't be loaded". Only then I read official installation notes for Demantra which say:
You can run Oracle Demantra on either a 32-bit or 64-bit Oracle database. However, the Oracle Demantra Installer and these applications run in 32-bit mode, so you must use the 32-bit Oracle database client to install Oracle Demantra and use these applications:
* Business Modeler
* Member Management
* Chaining Management
* Oracle Demantra forecasting engine
How do I "use the 32-bit Oracle database client to install Oracle Demantra"? Give me a bit more detailed answer if you can, as I'm not an expert. Thank you.

Hi Milind,
Unfortunately, I don't have Oracle SID and access to metalink. We're about to get into contractual agreement, but it's still in the workings. My original problem was solved by way of using virtual machine (32 XP) on top of Windows 7 64. However there are other issues standing in the way of our training. Do you know whether 7.3.0.1 has seeded demo data? (7.2 had it, and 7.3.0 didn't). Desperately need to a big nice rich dataset for 7.3. Any help greatly appreciated.
Yuriy

Could anyone please tell me how to tuning my program?

I have already executed the program with SE30.
I think that the program has some problem SQL in form
"GET_BACK_ORDER       (Fetch VBAP, Net % = <b>26.2</b>)" and
"GET_PENDING_ORDER (Fetch AUFK, Net % = <b>25.7</b>)"
but I can not find the data that I want from others table and I don't know how to tuning both form.
Source code for Review of Sales Forecast
REPORT ZLPPRP26
        LINE-SIZE 573
        NO STANDARD PAGE HEADING.
T A B L E S                                                        *
TABLES: pbed,      "Independent Requirements Data
        pbim.      "Independent Requirements for Material
TABLES: afko,      "Order header data PP orders
        aufk,      "Order master data
        t399x,     "Plant/order type
        tj02t,     "Text Status for check status of Process Order
        s003,      "Sale Order
        vbep,      "Sales Document: Schedule Line Data (QTY)
        vbap,      "Sales Document: Item Data (Material)
        vbup,      "Sales Document: Item Status
        mchb,      "Stock
        mcha,      "Stock description
        mara.      "General Material Data
*................................ Include ISO declarations
INCLUDE zstprpi1.
T Y P E S                                                          *
TYPES: boolean(1).
TYPE-POOLS : slis.
W O R K I N G   S T O R A G E   D A T A                            *
DATA: BEGIN OF wa_pbim,
        matnr LIKE pbim-matnr,     " MATERIAL NO.
        werks LIKE pbim-werks,     " PLANT.
        bedae LIKE pbim-bedae,     " REQUIREMENT TYPE.
        versb LIKE pbim-versb,     " VERSION.
        pbdnr LIKE pbim-pbdnr,     " REQUIREMENT PLAN NO.
        bdzei LIKE pbim-bdzei,     " INQ REQUIREMENT POINTER.
        vervs LIKE pbim-vervs,     " STATUS ACTIVE-INACTIVE.
      END OF wa_pbim.
DATA: BEGIN OF wa_pbed,
        pdatu LIKE pbed-pdatu,     " FINISH DATE
        bdzei LIKE pbed-bdzei,     " INQ REQUIREMENT POINTER.
        aenam LIKE pbed-aenam,     " NAME OF PERSON CHANGE.
        laeda LIKE pbed-laeda,     " DATE CHANGE.
        meins LIKE pbed-meins,     " UM.
        plnmg LIKE pbed-plnmg,     " PLAN QTY.
        entlu LIKE pbed-entlu,     " PERIOD INDICATOR
        perxx LIKE pbed-perxx,     " PLANNING PERIOD
      END OF wa_pbed.
DATA: BEGIN OF wa_marc,
        matnr LIKE marc-matnr,      " MAT CODE
        werks LIKE marc-werks,      " PLANT
        maabc LIKE marc-maabc,     " Class
        dismm LIKE marc-dismm,     " MRP Type
        dispo LIKE marc-dispo,     " MRP Controller
        eisbe LIKE marc-eisbe,     " Safety Stock
        bstfe LIKE marc-bstfe,     " Fix
        bstmi LIKE marc-bstmi,     " Min
        bstma LIKE marc-bstma,     " Max
      END OF wa_marc.
DATA : BEGIN OF wa_mchb,
        matnr LIKE mchb-matnr,     " Mat Code
        werks LIKE mchb-werks,     " Plant
        clabs LIKE mchb-clabs,      " UR
        cinsm LIKE mchb-cinsm,      " QI
        cspem LIKE mchb-cspem,      " BL
        lgort LIKE mchb-lgort,     " Storage Location
        charg LIKE mchb-charg,     " Batch
      END OF wa_mchb.
DATA : BEGIN OF wa_all_material,     " **MAIN OF PROGRAM**
        matnr LIKE mara-matnr,     " Mat Code
        werks LIKE marc-werks,      " Plant
        maabc LIKE marc-maabc,     " Class
        dismm LIKE marc-dismm,     " MRP Type
        dispo LIKE marc-dispo,     " MRP Controller
        meins LIKE mara-meins,     " UoM
        mseht LIKE t006a-mseht,    " UoM Text
        maktx LIKE makt-maktx,     " Mat Description
      END OF wa_all_material.
DATA: BEGIN OF wa_ind_req,
        matnr LIKE pbim-matnr,     " MATERIAL NO.
        werks LIKE pbim-werks,     " PLANT.
        bedae LIKE pbim-bedae,     " REQUIREMENT TYPE.
        versb LIKE pbim-versb,     " VERSION.
        pbdnr LIKE pbim-pbdnr,     " REQUIREMENT PLAN NO.
        bdzei LIKE pbim-bdzei,     " INQ REQUIREMENT POINTER.
        vervs LIKE pbim-vervs,     " STATUS ACTIVE-INACTIVE.
        pdatu LIKE pbed-pdatu,     " FINISH DATE กรณี DAY Period
        aenam LIKE pbed-aenam,     " NAME OF PERSON CHANGE.
        laeda LIKE pbed-laeda,     " DATE CHANGE.
        plnmg LIKE pbed-plnmg,     " PLAN QTY.
        entli LIKE pbed-entli,     " Date type (1day, 2week, 3month)
        perxx LIKE pbed-perxx,     " PLANNING PERIOD
      END OF wa_ind_req.
DATA: BEGIN OF wa_ind_req1,
        matnr LIKE pbim-matnr,     " MATERIAL NO.
       meins LIKE pbed-meins,     " UM. [Tiwa 31072006]
        plnmg LIKE pbed-plnmg,     " PLAN QTY.
        entli LIKE pbed-entli,     " Date type (1day, 2week, 3month)
        perxx LIKE pbed-perxx,     " PLANNING PERIOD
        pdatu LIKE pbed-pdatu,     " FINISH DATE กรณี DAY Period
      END OF wa_ind_req1.
DATA: BEGIN OF wa_ind_rep,
        matnr LIKE pbim-matnr,     " MATERIAL NO.
        cw4    LIKE pbed-plnmg,     " PLAN QTY of week from user
        nw1    LIKE pbed-plnmg,     " PLAN QTY next month week1
        nw2    LIKE pbed-plnmg,     " PLAN QTY next month week2
        nw3    LIKE pbed-plnmg,     " PLAN QTY next month week3
        nw4    LIKE pbed-plnmg,     " PLAN QTY next month week4
        nw5    LIKE pbed-plnmg,     " PLAN QTY next month week5
        mxx    LIKE pbed-plnmg,     " PLAN QTY next month(Period Month)
        ntotal LIKE pbed-plnmg,     "
      END OF wa_ind_rep.
DATA: BEGIN OF wa_sales_hist,
        spbup    LIKE s003-spbup,      " Period to analyze
        vkorg    LIKE s003-vkorg,      " Sales Organization(Plant)
        matnr    LIKE s003-matnr,      " Mat Code
        aemenge LIKE s003-aemenge, " incoming orders Qty
        ummenge LIKE s003-ummenge, " Billing Qty
        ssour    LIKE s003-ssour,   " for key
        vrsio    LIKE s003-vrsio,   " for key
        spmon    LIKE s003-spmon,   " for key
        sptag    LIKE s003-sptag,   " for key
        spwoc    LIKE s003-spwoc,   " for key
        vtweg    LIKE s003-vtweg,   " for key
        spart    LIKE s003-spart,   " for key
        bzirk    LIKE s003-bzirk,   " for key
        kunnr    LIKE s003-kunnr,   " for key
      END OF wa_sales_hist.
DATA: BEGIN OF wa_sales_report,
        matnr    LIKE s003-matnr,      " Mat Code
        m_3      LIKE s003-aemenge, " incoming orders Qty m-3
        m_2      LIKE s003-aemenge, " incoming orders Qty m-2
        m_1      LIKE s003-aemenge, " incoming orders Qty m-1
        m_0      LIKE s003-aemenge, " incoming orders Qty m-0
        estim    TYPE P DECIMALS 3,
        avg_sale TYPE P DECIMALS 3,
      END OF wa_sales_report.
DATA: BEGIN OF wa_back_order,
        matnr    LIKE vbap-matnr,     " Mat Code
        wmeng    LIKE vbep-wmeng,     " Order quantity
        bmeng    LIKE vbep-bmeng,     " Confirmed quantity
       vrkme    LIKE vbep-vrkme,     " Sales unit [Tiwa 31072006]
      END OF wa_back_order.
DATA: BEGIN OF wa_backord_rep,
        matnr    LIKE vbap-matnr,     " Mat Code
        back     LIKE vbep-wmeng,     " Order quantity
      END OF wa_backord_rep.
DATA: BEGIN OF wa_pending_order,
        objnr    LIKE jest-objnr, " Object
        matnr    LIKE afpo-matnr, " Material
        psmng    LIKE afpo-psmng, " Order Item QTY
        wemng    LIKE afpo-wemng, " GR QTY
        amein    LIKE afpo-amein, " UoM for Inhouse Prod
      END OF wa_pending_order.
DATA: BEGIN OF wa_pending_rep,
        matnr    LIKE afpo-matnr, " Material
        psmng    LIKE afpo-psmng, " Order Item QTY
      END OF wa_pending_rep.
DATA: BEGIN OF wa_batch_safety,
        matnr    LIKE marc-matnr, " Mat Code
        eisbe    LIKE marc-eisbe,     " Safety Stock
        bstfe    LIKE marc-bstfe,     " Fix
        bstmi    LIKE marc-bstmi,     " Min
        bstma    LIKE marc-bstma,     " Max
      END OF wa_batch_safety.
DATA: BEGIN OF wa_vbep,
        vbeln    LIKE vbep-vbeln, "Sales Document
        posnr    LIKE vbep-posnr, "Sales Document Item
        wmeng    LIKE vbep-wmeng, "Order quantity in sales units
        bmeng    LIKE vbep-bmeng, "Confirmed quantity
      END OF wa_vbep.
DATA: BEGIN OF wa_vbap,
        vbeln    LIKE vbap-vbeln,    "Sales Document
        posnr    LIKE vbap-posnr,    "Sales Document Item
        matnr    LIKE vbap-matnr,    "Material Code
        kwmeng   LIKE vbap-kwmeng,   "Order Qty.
        kbmeng   LIKE vbap-kbmeng,   "Comfirmed Qty.
        klmeng   LIKE vbap-klmeng,   "Back Order.
      END OF wa_vbap.
DATA: BEGIN OF wa_vbup,
        vbeln    LIKE vbup-vbeln, "Sales Document
        posnr    LIKE vbup-posnr, "Sales Document Item
      END OF wa_vbup.
DATA: BEGIN OF wa_vbfa,
        VBELV    LIKE vbfa-VBELV,   "Preceding SO
        POSNV    LIKE vbfa-POSNV,   "Preceding item of an SD document
        VBTYP_N LIKE vbfa-VBTYP_N, "Document category J = D/O
        RFMNG    LIKE vbfa-RFMNG,   "QTY in D/O
        MATNR    LIKE vbfa-MATNR,   "Material
        VBELN    LIKE vbfa-VBELN,   "Subsequent SD Doc.
        POSNN    LIKE vbfa-POSNN,   "Subsequent item of an SD document
      END OF wa_vbfa.
DATA: matclss LIKE marc-maabc,      " SLECTION OPTION
       mrpcont LIKE marc-dispo,      " SLECTION OPTION
       p_week   LIKE scal-week,       " Apply from parameter P_WEEK
       p_week4 LIKE scal-week VALUE 999999, "add in 270706
       tmpweek LIKE scal-week,       " return of FORM date_2_week
       tmpdate LIKE scal-date,       " return of FORM week_get_1st_day
       tmp_next_week LIKE scal-week, " return of FORM next_week.
       yyyymm_nextmonth(6) TYPE C,
       firstdate_of_week_of_monthend LIKE scal-date, "1stของweekสุดท้าย
       all_mat_found TYPE I VALUE 1. " Use in FORM read_all_material
DATA : next_month      LIKE scal-date,
       next_next_month LIKE scal-date,
       next_month_w1   LIKE scal-week,
       next_month_w2   LIKE scal-week,
       next_month_w3   LIKE scal-week,
       next_month_w4   LIKE scal-week,
       next_month_w5   LIKE scal-week,
       next_next_month_w1 LIKE scal-week,
       next_next_month_w2 LIKE scal-week,
       next_next_month_w3 LIKE scal-week,
       next_next_month_w4 LIKE scal-week,
       next_next_month_w5 LIKE scal-week.
DATA : prev_month LIKE scal-date, "GLOBAL
       prev_month0(6) TYPE C,      "Current Month
       prev_month1(6) TYPE C,
       prev_month2(6) TYPE C,
       prev_month3(6) TYPE C.
DATA : date1_in_currweek4_1 LIKE scal-date VALUE 99999999, "MON
       date2_in_currweek4_1 LIKE scal-date VALUE 99999999, "TUE
       date3_in_currweek4_1 LIKE scal-date VALUE 99999999, "WED
       date4_in_currweek4_1 LIKE scal-date VALUE 99999999, "THU
       date5_in_currweek4_1 LIKE scal-date VALUE 99999999, "FRI
       date6_in_currweek4_1 LIKE scal-date VALUE 99999999, "SAT
       date7_in_currweek4_1 LIKE scal-date VALUE 99999999. "SUN
DATA : date1_in_currweek4 LIKE scal-date, "MON
       date2_in_currweek4 LIKE scal-date, "TUE
       date3_in_currweek4 LIKE scal-date, "WED
       date4_in_currweek4 LIKE scal-date, "THU
       date5_in_currweek4 LIKE scal-date, "FRI
       date6_in_currweek4 LIKE scal-date, "SAT
       date7_in_currweek4 LIKE scal-date. "SUN
DATA : date1_in_nextmonth_week1 LIKE scal-date, "MON
       date2_in_nextmonth_week1 LIKE scal-date, "TUE
       date3_in_nextmonth_week1 LIKE scal-date, "WED
       date4_in_nextmonth_week1 LIKE scal-date, "THU
       date5_in_nextmonth_week1 LIKE scal-date, "FRI
       date6_in_nextmonth_week1 LIKE scal-date, "SAT
       date7_in_nextmonth_week1 LIKE scal-date. "SUN
DATA : date1_in_nextmonth_week2 LIKE scal-date, "MON
       date2_in_nextmonth_week2 LIKE scal-date, "TUE
       date3_in_nextmonth_week2 LIKE scal-date, "WED
       date4_in_nextmonth_week2 LIKE scal-date, "THU
       date5_in_nextmonth_week2 LIKE scal-date, "FRI
       date6_in_nextmonth_week2 LIKE scal-date, "SAT
       date7_in_nextmonth_week2 LIKE scal-date. "SUN
DATA : date1_in_nextmonth_week3 LIKE scal-date, "MON
       date2_in_nextmonth_week3 LIKE scal-date, "TUE
       date3_in_nextmonth_week3 LIKE scal-date, "WED
       date4_in_nextmonth_week3 LIKE scal-date, "THU
       date5_in_nextmonth_week3 LIKE scal-date, "FRI
       date6_in_nextmonth_week3 LIKE scal-date, "SAT
       date7_in_nextmonth_week3 LIKE scal-date. "SUN
DATA : date1_in_nextmonth_week4 LIKE scal-date VALUE 99999999, "MON
       date2_in_nextmonth_week4 LIKE scal-date VALUE 99999999, "TUE
       date3_in_nextmonth_week4 LIKE scal-date VALUE 99999999, "WED
       date4_in_nextmonth_week4 LIKE scal-date VALUE 99999999, "THU
       date5_in_nextmonth_week4 LIKE scal-date VALUE 99999999, "FRI
       date6_in_nextmonth_week4 LIKE scal-date VALUE 99999999, "SAT
       date7_in_nextmonth_week4 LIKE scal-date VALUE 99999999. "SUN
DATA : date1_in_nextmonth_week5 LIKE scal-date VALUE 99999999, "MON
       date2_in_nextmonth_week5 LIKE scal-date VALUE 99999999, "TUE
       date3_in_nextmonth_week5 LIKE scal-date VALUE 99999999, "WED
       date4_in_nextmonth_week5 LIKE scal-date VALUE 99999999, "THU
       date5_in_nextmonth_week5 LIKE scal-date VALUE 99999999, "FRI
       date6_in_nextmonth_week5 LIKE scal-date VALUE 99999999, "SAT
       date7_in_nextmonth_week5 LIKE scal-date VALUE 99999999. "SUN
DATA : t_fieldcat   TYPE slis_t_fieldcat_alv.
I N T E R N A L   T A B L E S                                      *
DATA: it_pbim           LIKE wa_pbim          OCCURS 0 WITH HEADER LINE,
      it_pbed           LIKE wa_pbed          OCCURS 0 WITH HEADER LINE,
      it_stock          LIKE wa_mchb          OCCURS 0 WITH HEADER LINE,
      it_stock_rep      LIKE wa_mchb          OCCURS 0 WITH HEADER LINE,
      it_ind_req        LIKE wa_ind_req       OCCURS 0 WITH HEADER LINE,
      it_ind_req1       LIKE wa_ind_req1      OCCURS 0 WITH HEADER LINE,
      it_ind_rep        LIKE wa_ind_rep       OCCURS 0 WITH HEADER LINE,
      it_tmp_sales_hist LIKE wa_sales_hist    OCCURS 0 WITH HEADER LINE,
      it_sales_hist     LIKE wa_sales_hist    OCCURS 0 WITH HEADER LINE,
      it_back_order     LIKE wa_back_order    OCCURS 0 WITH HEADER LINE,
      it_pending_order LIKE wa_pending_order OCCURS 0 WITH HEADER LINE,
      it_sales_report   LIKE wa_sales_report OCCURS 0 WITH HEADER LINE,
      it_backord_rep    LIKE wa_backord_rep   OCCURS 0 WITH HEADER LINE,
      it_batch_safety   LIKE wa_batch_safety OCCURS 0 WITH HEADER LINE,
      it_pending_rep    LIKE wa_pending_rep   OCCURS 0 WITH HEADER LINE,
      it_all_material   LIKE wa_all_material OCCURS 0 WITH HEADER LINE,
      t_vbap            LIKE wa_vbap          OCCURS 0 WITH HEADER LINE,
      t_vbep            LIKE wa_vbep          OCCURS 0 WITH HEADER LINE,
      t_vbfa            LIKE wa_vbfa          OCCURS 0 WITH HEADER LINE,
      t_vbup            LIKE wa_vbup          OCCURS 0 WITH HEADER LINE.
R A N G E S                                                        *
RANGES: r_month    FOR pbed-pdatu,
        r_matnr    FOR pbim-matnr.
S E L E C T - O P T I O N S   A N D   P A R A M E T E R S          *
SELECTION-SCREEN: BEGIN OF BLOCK bk1 WITH FRAME TITLE text-007.
PARAMETERS:     p_werks LIKE pbim-werks OBLIGATORY. "DEFAULT '1100'.
SELECT-OPTIONS: s_matnr FOR mara-matnr.
SELECT-OPTIONS: s_matc   FOR matclss.
SELECT-OPTIONS: s_mrpc   FOR mrpcont OBLIGATORY.
PARAMETERS :    p_month LIKE s003-spbup OBLIGATORY.
SELECTION-SCREEN : END OF BLOCK bk1.
M A C R O   C O M M A N D   D E F I N I T I O N                    *
DEFINE m%print_right.
write at sy-linsz ''.
END-OF-DEFINITION.
MAIN PROGRAM                                                       *
START-OF-SELECTION.
PERFORM date_2_week USING sy-datum. "return to tmpweek
PERFORM get_last_week_of_month.
PERFORM process_get_month_for_sales.
PERFORM get_week_next_month.
PERFORM get_week_next_next_month.
PERFORM get_date_in_currweek4.
PERFORM get_date_in_week_in_nextmonth.
PERFORM read_all_material.
IF all_mat_found EQ 1.        "Found some of material
    PERFORM read_stock.
    PERFORM read_pbim_pbed_data.
    PERFORM get_sales_history.
    PERFORM get_back_order.
    PERFORM get_pending_order.
    PERFORM print_report.
ENDIF.
*&      Form read_pbim_pbed_data
FORM read_pbim_pbed_data.
yyyymm_nextmonth = next_month+0(6).
SELECT pbimmatnr pbimwerks pbim~bedae
         pbimversb pbimpbdnr pbimbdzei pbimvervs
         pbedpdatu pbedaenam pbed~laeda
         pbedplnmg pbedentli pbed~perxx
INTO TABLE it_ind_req
FROM pbim
INNER JOIN pbed
        ON pbimbdzei = pbedbdzei
FOR ALL ENTRIES IN it_all_material
WHERE pbim~vervs = 'X' AND      "Active Version
        pbim~werks = p_werks AND
        pbim~matnr EQ it_all_material-matnr AND
        ( ( pbedperxx = next_month_w1 AND pbedentli = 2 ) OR
          ( pbedperxx = next_month_w2 AND pbedentli = 2 ) OR
          ( pbedperxx = next_month_w3 AND pbedentli = 2 ) OR
          ( pbedperxx = next_month_w4 AND pbedentli = 2 ) OR
          ( pbedperxx = next_month_w5 AND pbedentli = 2 ) OR
          ( pbedperxx = p_week        AND pbedentli = 2 ) OR
          ( pbedperxx = p_week4       AND pbedentli = 2 ) OR "27072006
          ( pbed~pdatu between date1_in_currweek4 AND
                               date7_in_currweek4 ) OR
          ( pbed~pdatu between date1_in_currweek4_1 AND   "add 27072006
                               date7_in_currweek4_1 ) OR "add 27072006
          ( pbed~pdatu between date1_in_nextmonth_week1 AND
                               date7_in_nextmonth_week1 ) OR
          ( pbed~pdatu between date1_in_nextmonth_week2 AND
                               date7_in_nextmonth_week2 ) OR
          ( pbed~pdatu between date1_in_nextmonth_week3 AND
                               date7_in_nextmonth_week3 ) OR
          ( pbed~pdatu between date1_in_nextmonth_week4 AND
                               date7_in_nextmonth_week4 ) OR
          ( pbed~pdatu between date1_in_nextmonth_week5 AND
                               date7_in_nextmonth_week5 ) OR
          ( pbedperxx = yyyymm_nextmonth AND pbedentli = 3 ) ).
LOOP AT it_ind_req.
    wa_ind_req1-matnr = it_ind_req-matnr.
    wa_ind_req1-plnmg = it_ind_req-plnmg.
    wa_ind_req1-entli = it_ind_req-entli.
    wa_ind_req1-perxx = it_ind_req-perxx.
    wa_ind_req1-pdatu = it_ind_req-pdatu.
    COLLECT wa_ind_req1 INTO it_ind_req1.
ENDLOOP.
PERFORM get_ind_rep.
PERFORM get_batch_safe.
ENDFORM.
*&      Form get_batch_safe
FORM get_batch_safe.
DATA: wl_marc LIKE marc,
        safety LIKE marc-eisbe VALUE 0,
        fix     LIKE marc-eisbe VALUE 0,
        min     LIKE marc-eisbe VALUE 0,
        max     LIKE marc-eisbe VALUE 0.
LOOP AT it_all_material.
    CLEAR : wl_marc, safety, fix, min, max.
    SELECT SINGLE * FROM marc INTO wl_marc
    WHERE matnr = it_all_material-matnr AND
           werks = p_werks.
    IF sy-subrc EQ 0.
      safety = wl_marc-eisbe. " Safety Stock
      fix    = wl_marc-bstfe. " Fix
      min    = wl_marc-bstmi. " Min
      max    = wl_marc-bstma. " Max
    ENDIF.
    it_batch_safety-matnr = it_all_material-matnr.
    it_batch_safety-eisbe = safety. " Safety Stock
    it_batch_safety-bstfe = fix.     " Fix
    it_batch_safety-bstmi = min.     " Min
    it_batch_safety-bstma = max.     " Max
    APPEND it_batch_safety.
ENDLOOP.
ENDFORM.
*&      Form get_ind_rep
FORM get_ind_rep.
DATA: cw4     TYPE P VALUE 0 DECIMALS 3,
        nw1     TYPE P VALUE 0 DECIMALS 3,
        nw2     TYPE P VALUE 0 DECIMALS 3,
        nw3     TYPE P VALUE 0 DECIMALS 3,
        nw4     TYPE P VALUE 0 DECIMALS 3,
        nw5     TYPE P VALUE 0 DECIMALS 3,
        mxx     TYPE P VALUE 0 DECIMALS 3, "Add in 12/07/2006 by Tiwa
        ntotal TYPE P VALUE 0 DECIMALS 3.
LOOP AT it_all_material.
    CLEAR: ntotal, cw4, nw1, nw2, nw3, nw4, nw5, mxx, wa_ind_rep.
    LOOP AT it_ind_req1 WHERE matnr = it_all_material-matnr.
      IF ( ( ( it_ind_req1-perxx EQ p_week ) AND
             ( it_ind_req1-entli EQ 2 ) ) OR
           ( ( it_ind_req1-pdatu EQ date1_in_currweek4 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date2_in_currweek4 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date3_in_currweek4 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date4_in_currweek4 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date5_in_currweek4 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date6_in_currweek4 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date7_in_currweek4 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-perxx EQ p_week4 ) AND
             ( it_ind_req1-entli EQ 2 ) ) OR
           ( ( it_ind_req1-pdatu EQ date1_in_currweek4_1 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date2_in_currweek4_1 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date3_in_currweek4_1 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date4_in_currweek4_1 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date5_in_currweek4_1 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date6_in_currweek4_1 ) AND
             ( it_ind_req1-entli EQ 1 ) ) OR
           ( ( it_ind_req1-pdatu EQ date7_in_currweek4_1 ) AND
             ( it_ind_req1-entli EQ 1 ) ) ).
        cw4 = cw4 + it_ind_req1-plnmg.
      ELSEIF ( ( ( it_ind_req1-perxx EQ next_month_w1 ) AND
                 ( it_ind_req1-entli EQ 2 ) ) OR
               ( ( it_ind_req1-pdatu EQ date1_in_nextmonth_week1 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date2_in_nextmonth_week1 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date3_in_nextmonth_week1 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date4_in_nextmonth_week1 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date5_in_nextmonth_week1 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date6_in_nextmonth_week1 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date7_in_nextmonth_week1 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) ).
        nw1 = nw1 + it_ind_req1-plnmg.
      ELSEIF ( ( ( it_ind_req1-perxx EQ next_month_w2 ) AND
                 ( it_ind_req1-entli EQ 2 ) ) OR
               ( ( it_ind_req1-pdatu EQ date1_in_nextmonth_week2 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date2_in_nextmonth_week2 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date3_in_nextmonth_week2 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date4_in_nextmonth_week2 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date5_in_nextmonth_week2 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date6_in_nextmonth_week2 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date7_in_nextmonth_week2 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) ).
        nw2 = nw2 + it_ind_req1-plnmg.
      ELSEIF ( ( ( it_ind_req1-perxx EQ next_month_w3 ) AND
                 ( it_ind_req1-entli EQ 2 ) ) OR
               ( ( it_ind_req1-pdatu EQ date1_in_nextmonth_week3 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date2_in_nextmonth_week3 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date3_in_nextmonth_week3 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date4_in_nextmonth_week3 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date5_in_nextmonth_week3 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date6_in_nextmonth_week3 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date7_in_nextmonth_week3 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) ).
        nw3 = nw3 + it_ind_req1-plnmg.
      ELSEIF ( ( ( it_ind_req1-perxx EQ next_month_w4 ) AND
                 ( it_ind_req1-entli EQ 2 ) ) OR
               ( ( it_ind_req1-pdatu EQ date1_in_nextmonth_week4 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date2_in_nextmonth_week4 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date3_in_nextmonth_week4 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date4_in_nextmonth_week4 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date5_in_nextmonth_week4 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date6_in_nextmonth_week4 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date7_in_nextmonth_week4 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) ).
        nw4 = nw4 + it_ind_req1-plnmg.
      ELSEIF ( ( ( it_ind_req1-perxx EQ next_month_w5 ) AND
                 ( it_ind_req1-entli EQ 2 ) ) OR
               ( ( it_ind_req1-pdatu EQ date1_in_nextmonth_week5 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date2_in_nextmonth_week5 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date3_in_nextmonth_week5 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date4_in_nextmonth_week5 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date5_in_nextmonth_week5 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date6_in_nextmonth_week5 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) OR
               ( ( it_ind_req1-pdatu EQ date7_in_nextmonth_week5 ) AND
                 ( it_ind_req1-entli EQ 1 ) ) ).
        nw5 = nw5 + it_ind_req1-plnmg.
      ELSEIF ( ( it_ind_req1-perxx EQ yyyymm_nextmonth ) AND
               ( it_ind_req1-entli EQ 3 ) ).
        mxx    = mxx + it_ind_req1-plnmg.
        ntotal = ntotal + it_ind_req1-plnmg.
      ENDIF.
    ENDLOOP.
    ntotal = ntotal + ( nw1 + nw2 + nw3 + nw4 + nw5 ).
    wa_ind_rep-matnr   = it_all_material-matnr.
    wa_ind_rep-cw4     = cw4.
    wa_ind_rep-nw1     = nw1.
    wa_ind_rep-nw2     = nw2.
    wa_ind_rep-nw3     = nw3.
    wa_ind_rep-nw4     = nw4.
    wa_ind_rep-nw5     = nw5.
    wa_ind_rep-mxx     = mxx.
    wa_ind_rep-ntotal = ntotal.
    IF wa_ind_rep-ntotal > 0.
      APPEND wa_ind_rep TO it_ind_rep.
    ENDIF.
ENDLOOP.
ENDFORM.
*&      Form date_2_week
FORM date_2_week USING inp_date.
CLEAR tmpweek.
CALL FUNCTION 'DATE_GET_WEEK'
    EXPORTING
      date = inp_date
    IMPORTING
      week = tmpweek
    EXCEPTIONS
      date_invalid = 1
      others = 2.
ENDFORM.
*&      Form get_date_in_currweek4
FORM get_date_in_currweek4.
PERFORM week_get_1st_day USING p_week. "return to tmpdate
date1_in_currweek4 = tmpdate.                "MON
date2_in_currweek4 = date1_in_currweek4 + 1. "TUE
date3_in_currweek4 = date2_in_currweek4 + 1. "WED
date4_in_currweek4 = date3_in_currweek4 + 1. "THU
date5_in_currweek4 = date4_in_currweek4 + 1. "FRI
date6_in_currweek4 = date5_in_currweek4 + 1. "SAT
date7_in_currweek4 = date6_in_currweek4 + 1. "SUN
IF p_week4 NE 999999.
    PERFORM week_get_1st_day USING p_week4. "return to tmpdate
    date1_in_currweek4_1 = tmpdate.                  "MON
    date2_in_currweek4_1 = date1_in_currweek4_1 + 1. "TUE
    date3_in_currweek4_1 = date2_in_currweek4_1 + 1. "WED
    date4_in_currweek4_1 = date3_in_currweek4_1 + 1. "THU
    date5_in_currweek4_1 = date4_in_currweek4_1 + 1. "FRI
    date6_in_currweek4_1 = date5_in_currweek4_1 + 1. "SAT
    date7_in_currweek4_1 = date6_in_currweek4_1 + 1. "SUN
ENDIF.
ENDFORM.
*&      Form get_date_in_week_in_nextmonth
FORM get_date_in_week_in_nextmonth.
*Date in week1 of next month
PERFORM week_get_1st_day USING next_month_w1. "return to tmpdate
date1_in_nextmonth_week1 = tmpdate.                      "MON
date2_in_nextmonth_week1 = date1_in_nextmonth_week1 + 1. "TUE
date3_in_nextmonth_week1 = date2_in_nextmonth_week1 + 1. "WED
date4_in_nextmonth_week1 = date3_in_nextmonth_week1 + 1. "THU
date5_in_nextmonth_week1 = date4_in_nextmonth_week1 + 1. "FRI
date6_in_nextmonth_week1 = date5_in_nextmonth_week1 + 1. "SAT
date7_in_nextmonth_week1 = date6_in_nextmonth_week1 + 1. "SUN
*Date in week2 of next month
PERFORM week_get_1st_day USING next_month_w2. "return to tmpdate
date1_in_nextmonth_week2 = tmpdate.                      "MON
date2_in_nextmonth_week2 = date1_in_nextmonth_week2 + 1. "TUE
date3_in_nextmonth_week2 = date2_in_nextmonth_week2 + 1. "WED
date4_in_nextmonth_week2 = date3_in_nextmonth_week2 + 1. "THU
date5_in_nextmonth_week2 = date4_in_nextmonth_week2 + 1. "FRI
date6_in_nextmonth_week2 = date5_in_nextmonth_week2 + 1. "SAT
date7_in_nextmonth_week2 = date6_in_nextmonth_week2 + 1. "SUN
*Date in week3 of next month
PERFORM week_get_1st_day USING next_month_w3. "return to tmpdate
date1_in_nextmonth_week3 = tmpdate.                      "MON
date2_in_nextmonth_week3 = date1_in_nextmonth_week3 + 1. "TUE
date3_in_nextmonth_week3 = date2_in_nextmonth_week3 + 1. "WED
date4_in_nextmonth_week3 = date3_in_nextmonth_week3 + 1. "THU
date5_in_nextmonth_week3 = date4_in_nextmonth_week3 + 1. "FRI
date6_in_nextmonth_week3 = date5_in_nextmonth_week3 + 1. "SAT
date7_in_nextmonth_week3 = date6_in_nextmonth_week3 + 1. "SUN
*Date in week4 of next month
IF next_month_w4 NE 999999.
    PERFORM week_get_1st_day USING next_month_w4. "return to tmpdate
    date1_in_nextmonth_week4 = tmpdate.                      "MON
    date2_in_nextmonth_week4 = date1_in_nextmonth_week4 + 1. "TUE
    date3_in_nextmonth_week4 = date2_in_nextmonth_week4 + 1. "WED
    date4_in_nextmonth_week4 = date3_in_nextmonth_week4 + 1. "THU
    date5_in_nextmonth_week4 = date4_in_nextmonth_week4 + 1. "FRI
    date6_in_nextmonth_week4 = date5_in_nextmonth_week4 + 1. "SAT
    date7_in_nextmonth_week4 = date6_in_nextmonth_week4 + 1. "SUN
ENDIF.
*Date in week5 of next month
IF next_month_w5 NE 999999.
    PERFORM week_get_1st_day USING next_month_w5. "return to tmpdate
    date1_in_nextmonth_week5 = tmpdate.                      "MON
    date2_in_nextmonth_week5 = date1_in_nextmonth_week5 + 1. "TUE
    date3_in_nextmonth_week5 = date2_in_nextmonth_week5 + 1. "WED
    date4_in_nextmonth_week5 = date3_in_nextmonth_week5 + 1. "THU
    date5_in_nextmonth_week5 = date4_in_nextmonth_week5 + 1. "FRI
    date6_in_nextmonth_week5 = date5_in_nextmonth_week5 + 1. "SAT
    date7_in_nextmonth_week5 = date6_in_nextmonth_week5 + 1. "SUN
ENDIF.
ENDFORM.
*&      Form get_week_next_month
FORM get_week_next_month.
DATA : date_by_week_of_parameter LIKE scal-date,
         date LIKE scal-date,
         week LIKE scal-week.
PERFORM week_get_1st_day USING p_week. "return to tmpdate
CALL FUNCTION 'LAST_DAY_OF_MONTHS'
    EXPORTING
      day_in             = tmpdate
    IMPORTING
      LAST_DAY_OF_MONTH = next_month
    EXCEPTIONS
      DAY_IN_NO_DATE     = 1
      OTHERS             = 2.
next_month = next_month + 1. "YYYYMMDD 2006.xx.01
PERFORM date_2_week USING next_month. "return to tmpweek
week = tmpweek.
PERFORM week_get_1st_day USING week. "return to tmpdate
date = tmpdate.
IF next_month NE date.
    PERFORM next_week USING week.
    next_month_w1 = tmp_next_week.
    week = tmp_next_week.
ENDIF.
next_month_w1 = week.          "**WEEK1**
PERFORM next_week USING week.
week = tmp_next_week.
next_month_w2 = week.          "**WEEK2**
PERFORM next_week USING week.
week = tmp_next_week.
next_month_w3 = week.          "**WEEK3**
PERFORM next_week USING week.
PERFORM week_get_1st_day USING tmp_next_week. "return to tmpdate
IF tmpdate4(2) EQ next_month4(2).
    week = tmp_next_week.
    next_month_w4 = week.        "**WEEK4**
    PERFORM next_week USING week.
    PERFORM week_get_1st_day USING tmp_next_week. "return to tmpdate
    IF tmpdate4(2) EQ next_month4(2).
      week = tmp_next_week.
      next_month_w5 = week.      "**WEEK5**
    ELSE.
      next_month_w5 = 999999.
    ENDIF.
ELSE.
    next_month_w4 = 999999.
    next_month_w5 = 999999.
ENDIF.
ENDFORM.
*&      Form get_week_next_next_month
FORM get_week_next_next_month.
DATA : date LIKE scal-date,
         week LIKE scal-week.
CALL FUNCTION 'LAST_DAY_OF_MONTHS'
    EXPORTING
      day_in             = next_month
    IMPORTING
      LAST_DAY_OF_MONTH = next_next_month
    EXCEPTIONS
      DAY_IN_NO_DATE     = 1
      OTHERS             = 2.
next_next_month = next_next_month + 1. "YYYYMMDD 2006.xx.01
PERFORM date_2_week USING next_next_month. "return to tmpweek
week = tmpweek.
PERFORM week_get_1st_day USING week. "return to tmpdate
date = tmpdate.
IF next_next_month NE date.
    PERFORM next_week USING week. "Return to tmp_next_week
    week = tmp_next_week.
ENDIF.
next_next_month_w1 = week.          "**next_next_month WEEK1**
PERFORM next_week USING week.
week = tmp_next_week.
next_next_month_w2 = week.          "**next_next_month WEEK2**
PERFORM next_week USING week.
week = tmp_next_week.
next_next_month_w3 = week.          "**next_next_month WEEK3**
PERFORM next_week USING week.
PERFORM week_get_1st_day USING tmp_next_week. "return to tmpdate
IF tmpdate4(2) EQ next_next_month4(2).
    week = tmp_next_week.
    next_next_month_w4 = week.             "**next_next_month WEEK4**
    PERFORM next_week USING week.
    PERFORM week_get_1st_day USING tmp_next_week. "return to tmpdate
    IF tmpdate4(2) EQ next_next_month4(2).
      week = tmp_next_week.
      next_next_month_w5 = week.           "**next_next_month WEEK5**
    ELSE.
      next_next_month_w5 = 999999.
    ENDIF.
ELSE.
    next_next_month_w4 = 999999.
    next_next_month_w5 = 999999.
ENDIF.
ENDFORM.
*&      Form GET_SALES_HISTORY
FORM get_sales_history.
DATA : m_3 LIKE s003-aemenge VALUE 0,
         m_2 LIKE s003-aemenge VALUE 0,
         m_1 LIKE s003-aemenge VALUE 0,
         m_0 LIKE s003-aemenge VALUE 0.
SELECT s003spbup s003vkorg s003~matnr
         s003aemenge s003ummenge
         s003ssour s003vrsio s003spmon s003sptag
         s003spwoc s003vtweg s003spart s003bzirk s003~kunnr
INTO TABLE it_tmp_sales_hist
FROM   s003
WHERE ( s003~spbup = prev_month0 OR
           s003~spbup = prev_month1 OR
           s003~spbup = prev_month2 OR
           s003~spbup = prev_month3
         ) AND
         s003~vkorg = p_werks AND
         s003~matnr IN s_matnr.
LOOP AT it_tmp_sales_hist.
    CLEAR wa_sales_hist.
    wa_sales_hist-spbup   = it_tmp_sales_hist-spbup.
    wa_sales_hist-vkorg   = it_tmp_sales_hist-vkorg.
    wa_sales_hist-matnr   = it_tmp_sales_hist-matnr.
    wa_sales_hist-aemenge = it_tmp_sales_hist-aemenge.
    wa_sales_hist-ummenge = it_tmp_sales_hist-ummenge.
    COLLECT wa_sales_hist INTO it_sales_hist.
ENDLOOP.
LOOP AT it_all_material.
    CLEAR : m_3, m_2, m_1, m_0, wa_sales_report.
    LOOP AT it_sales_hist WHERE matnr = it_all_material-matnr.
      IF it_sales_hist-spbup = prev_month3.
        m_3 = it_sales_hist-ummenge.
      ELSEIF it_sales_hist-spbup = prev_month2.
        m_2 = it_sales_hist-ummenge.
      ELSEIF it_sales_hist-spbup = prev_month1.
        m_1 = it_sales_hist-ummenge.
      ELSEIF it_sales_hist-spbup = prev_month0.
        m_0 = it_sales_hist-ummenge.
      ENDIF.
    ENDLOOP.
    wa_sales_report-matnr = it_all_material-matnr.
    wa_sales_report-m_3   = m_3.
    wa_sales_report-m_2   = m_2.
    wa_sales_report-m_1   = m_1.
    wa_sales_report-m_0   = m_0.
    wa_sales_report-avg_sale = ( m_3 + m_2 + m_1 ) / 3.
    IF ( ( m_0 > 0 ) OR ( m_1 > 0 ) OR ( m_2 > 0 ) OR ( m_3 > 0 ) ).
      APPEND wa_sales_report TO it_sales_report.
    ENDIF.
ENDLOOP.
ENDFORM.
*&      Form PROCESS_GET_MONTH_FOR_SALES
FORM process_get_month_for_sales.
"Current Month
PERFORM week_get_1st_day USING p_week.    "return to tmpdate
prev_month0 = tmpdate+0(6).
"Month -1
PERFORM get_prev_month USING tmpdate.     "return to prev_month
prev_month1 = prev_month+0(6).
"Month -2
PERFORM get_prev_month USING prev_month. "return to prev_month
prev_month2 = prev_month+0(6).
"Month -3
PERFORM get_prev_month USING prev_month. "return to prev_month
prev_month3 = prev_month+0(6).
ENDFORM.
*&      Form GET_PREV_MONTH
FORM get_prev_month USING inp_date LIKE sy-datum.
inp_date+6(2) = '01'.
CALL FUNCTION 'MONTH_PLUS_DETERMINE'
EXPORTING
    months        = -1
    olddate       = inp_date
IMPORTING
    newdate       = prev_month.
ENDFORM.
*&      Form GET_LAST_DAY_OF_MONTH
FORM get_last_day_of_month USING inp_date LIKE sy-datum.
DATA : last_day_of_month LIKE scal-date.
CALL FUNCTION 'RP_LAST_DAY_OF_MONTHS'
EXPORTING
    day_in                 = inp_date
IMPORTING
   LAST_DAY_OF_MONTH       = tmpdate
EXCEPTIONS
   DAY_IN_NO_DATE          = 1
   OTHERS                  = 2.
ENDFORM.
*&      Form WEEK_GET_FIRST_DAY
FORM week_get_1st_day USING inp_week LIKE scal-week.
CALL FUNCTION 'WEEK_GET_FIRST_DAY'
    EXPORTING
      week = inp_week
    IMPORTING
      date = tmpdate
    EXCEPTIONS
      week_invalid = 1
      others        = 2.
ENDFORM.
*&      Form NEXT_WEEK
FORM next_week USING inp_week LIKE scal-week.
CALL FUNCTION 'NEXT_WEEK'
    EXPORTING
      current_week       = inp_week
    IMPORTING
      NEXT_WEEK          = tmp_next_week.
ENDFORM.
*&      Form GET_BACK_ORDER
FORM get_back_order.
DATA : back              TYPE P VALUE 0 DECIMALS 3,
         subtract          TYPE P VALUE 0 DECIMALS 3,
         do_qty

Hi ,
Replace your select statements as below in
subroutines get_back_order and get_pending_order.
Let me know your status of program from your rewards.
Regards,
Sankar
FORM get_back_order.
ranges : r_posnr for vbrp-posnr.
r_posnr-low = '000000'.
r_posnr-high = '999999'.
r_posnr-sign = 'I'.
r_posnr-option = 'BT'.
append r_posnr.
SELECT vbapvbeln vbapposnr vbap~matnr
vbapkwmeng vbapkbmeng vbap~klmeng
INTO TABLE t_vbap FROM vbap
WHERE
( vbeln LIKE '21%' OR " Sales Order
vbeln LIKE '25%' OR " Exchange
vbeln LIKE '26%' ) and
posnr in r_posnr and
matnr IN s_matnr AND
werks = p_werks
FORM get_pending_order.
SELECT jestobjnr afpomatnr afpopsmng afpowemng
INTO TABLE it_pending_order
FROM aufk
INNER JOIN afko
ON aufkaufnr = afkoaufnr
INNER JOIN afpo
ON afkoaufnr = afpoaufnr
INNER JOIN jest
ON aufkobjnr = jestobjnr
FOR ALL ENTRIES IN it_all_material
WHERE
jest~stat = 'I0002' AND "Status REL
jest~inact <> 'X' AND
afpo~matnr EQ it_all_material-matnr AND
aufk~werks = p_werks.

How to purge Sales Data in Oracle Demantra

Hi Demantra experts,
I have one doubt in demantra:
Suppose the user has loaded the historical data say Sales History data in SALES_DATA table.
And after running the Analaytical Engine , forecast has been generated as well.
Later he found that it was a wrong data and now it should be removed.
If the user wants to remoe these records from SALES_DATA table .
What is the process of purging the records?
Thanks,
Neeraj.

Thanks a lot for your help.
I checked the metalink note. It deals with removing the data from temporary tables and not the base tables.
The Temprary tables acts like interface tables. We need to populate the records in the respective temp table and run the .bat file
However the record stays in the temp table after the .bat file has loaded the data in base tables.
The suggested metalink note provides script to cleanup the temp tables of demantra.
My requirement is to remove the records from base tables.
Thanks,
Neeraj.

Forecast tuning in demantra

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