Tag Archives: Forecasting
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Leading Indicator Forecasting in SPP
What Is It?
A statistical forecast based on sales history is not the only type of forecast that is used in SPP. Sometimes the forecast needs to be based upon factors other than history such as installed base. For instance in A&D, the forecast can be more accurately executed based on installed base rather than historical sales. Leading indicators is a causal forecasting method. (This could be flight hours, or other equipment utilization numbers. These are also called causal factors, or non-demand factors and are notoriously hard to find in company databases.)
If you have information about the failure rate, you can define that in a coefficient. The system then multiplies this coefficient with the equipment that is on the market and can thus forecast how many service parts you will require in the future. The steps generally are:
- Equipment source must be tapped and extracted (equipment BOMs, installed based key figures, equipment master data from the BW)
- We then bring this into BW, perform a LI preparation service.
Then we select leading indicator folder.
SAP supplies the following leading indicators
- Installed base
- Operation time
- Number of users
You can also define your own leading indicators in addition to the ones provided by SAP. (You must assign the same leading indicator to all locations of a BOD.)
SPPLFISERVICE for Coefficient Determination
These leading indicators are then assigned to a planning profile. You need to select the SPPLFISERVICE. This service is the coefficient determining service. The system generates the demand histories for the leading indicators used. It then uses these histories to determine a value for the coefficient for each period in the past. To do so, it executes the planning service SPP: Preparation Service for Leading Indicator Based Forecast (SPPLFISERVICE).However, you do not need to run the LFI service. If you select either CONSTANT VALUE or MANUALLY ENTERED off of the Leading Indicator tab of the forecast profile. This leads us to an intermediate topic – the Foreast Profile Leading Indicator Tab. Goto this link to read this related topic. Then return to this post. Alternatively, open both posts and read them side by side.
http://www.scmfocus.com/sapplanning/2008/10/02/spp-leading-indicator-forecast-profile-tab/
Here is the SPPLFISERVICE, it is a standard service and can be accessed by creating a planningprofile and by attaching the service to this profile.
/N/SAPAPO/480000009
The service is in the product simple category.
Now we have selected the correct Process Profile category we can go to the next step and select the SPPLFISERVICE.
Now we can access this service by selecting this Leading planning profile that we just created.
If you use period based planning, SPP generates the forecast for a product either on the basis of past sales values or on the basis of leading indicators. If you can not meet your demand within your BOD, SPP covers demands either through external procurement or repair.
SPPFCSSERVICE for Forecasting
This generates the demand histories and performs forecasting. However, you can use the interactive forecasting screen instead. /N/SAPAPO/SPPFCST
On the other hand you can also tie up this service in a planning profile.
STEPS
- Based on the demand history generated in step one, the system generates the forecast for the leading indicator and the coefficient. For this you can either schedule the planning service SPP: Forecast Service (SPP_FCS_SERVICE) which generates the demand histories, or you can start the forecast manually in the interactive forecasting screen. This generates the forecast for the leading indicator. In doing so, it proceeds as specified by you in the Leading Indicator Values field on the Leading Indicator tab page in the forecast profile. You have the following options.
a. Forecasted – In this case the system performs the forecast on the basis of the demand history and takes into account the forecast profile that you have defined for the leading indicator
b. Determined from the Installed Base – In this case the system performs a naive forecast. I reads the values from the demand history from the InfoCube SPP: Installed Base Key Figures (9AIBASKF), and copies the value of the current period as the forecast value for future periods
c. Upload / Manually Entered – In this case you can either enter the forecast values manually in the Interactive Forecasting screen or upload them with a BADI
3. The system determines the leading indicator based forecast for your location product on the basis of the forecast values for the leading indicator and the coefficient. As in step 2, this step is either part of the planning service SPP: Forecast Service (SPP_FCS_SERVICE) or part of the interactive forecast that you can start manually in the Interactive Forecasting screen. To generate the leading indicator forecast for your location product, the system multiplies the forecast values of the leading indicator determined in step 2a by the forecast values of the coefficient determined in step 2b. it does so for each period in the future
4. You can display the calculated forecast values on the Interactive Forecasting screen.
Equipment Data
You can load equipment data into SCM from ECC via BI. In the standard, the system transfers equipment data from ECC into the characteristic 0EQUIPMENT in SAP BI. You must schedule this transfer in SAP BI with an InfoPackage.
Overall Sequence
1. The preparation service for leading indicator based forecasting checks all products of the product selection as to whether they are part of a supersession. If a product is part of a supersession, the preparation service checks whether the supersession is a one to one replacement. It is only in this case that the preparation service takes into account this supersession in leading indicator based forecasting. The preparation service for leading indicator based forecasting of the predecessor and successor product then generates a demand history as described below. The preparation service checks whether you have set the read BOM of LI flag in the service profile for the preparation service.
a. If you have set this flag, the system reads all equipment BOMs for the ERP system and check how often a product occurs in which equipment BOMs
b. If you have not set this flag, the system sets an equipment equal to a product.
2. The preparation service checks whether you have restricted your equipment with a selection in customizing or whether you want to take into account all equipment in leading indicator based forecasting. If you want to restrict the equipment taking into account in leading indicator based forecasting, you can define an equipment selection in Customizing. You can specify the semantics and values or value ranges for these semantics that the system is to take into account or not take into account in the selection.
3. The preparation service determines an entry location for all products of the product selection and checks, which leading indicator group you have assigned to this entry location. The system only performs step 4 for those leading indicators that are included in this leading indicator group.
4. If the installed base leading indicator occurs in your leading indicator group, the preparation service distinguishes between the installed base leading indicator and all other leading indicators as follows.
a. The preparation service determines the demand history of the installed base leading indicator form the information from step 1. To do so it counts how often a product occurs in total in all checked equipment BOMs. If you are not using equipment BOMs and an equipment corresponds to a product, the system only counts the equipment.
b. The preparation service determines the first stockholding locations for the product. To do so, it determines at which location the demand for the equipment occurred. If this location is a stockholding location, it determines this location is the first stockholding location. If this location is not a stockholding location, it goes up in the BOD until it finds a stock holding location and determines this location as the first stockholding location.
Whether a location is a stocked location is set here in the SPP Inv. Planning tab on the product location master.
Here the tab for leading indicator has a number of selections which determine if the leading indicator forecast is to be selected from installed based or are manually entered. The coefficient is then used to adjust your mean time between failure.
Forecast Service Profiles
Now we will discuss the planning service indicator.
For details on the Planning Service Manager goto our post on the topic at….
http://www.scmfocus.com/sapplanning/2008/09/28/spp-planning-service-manager
Just some initial screen shots which will be commented further from the forecast profile.
BADI
To define your own logic of wish to use the ATP check for determining the first stockholding location, you can implement the BADI /SAPAPO/EQUIPFIRSTSTOCK_PREP
SPP IMG Setup: Forecasting
Introduction
This post will describe the different settings for forecasting. All of these settings are underneath the Forecasting folder in the IMG under SPP.
IMG: APO –> Supply Chain Planning –> SPP –> Forecasting –> Define Forecast Service Profile
Forecasting Service Profiles
Service profiles are all all through the different functionality areas in SPP, just check the other IMG Setup posts on SPP. They are the major control features of SPP and the forecast service profiles cover everything from forecast disaggregation to phase in and phase out profiles to forecast approval. This includes the following:
As you can see there is really a tremendous amount of configuration available within this screen where you select the area you want to configure.
In addition to these areas of “functionality” configuration that is listed above, there is also the basic setup for the options below.
General Data
This is an example of setting up the general data. This screen has all the basic including the historical data key figure, and the forecast data. As with any forecasting system the basic parameters must be set which include:
The historical periods are how many previous periods are used to generate the forecast. The forecast periods is how many periods to forecast. The forecast date is today’s date.
SAP allows this to be setup differently per ID. This does provide a high level of flexibility, however, I am used to setting all of these values for an entire model, which I think is a lower maintenance way of managing a model then the way SAP has set this up here.
If we select general we get the following items view.
This shows the details of the general data that applies to the different forecast profiles. Clearly it has the periods declared, but also has historical data and forecast data selected. Here are the options for the Historical data selection.
Forecast
If we go back and select Forecast from the Dialog Structure we get the following options.
The options are primarily related to the minutia of the forecast such as how you want to forecast run. This includes whether to execute tripping or executing a composite forecast.
The phase in and phase out profile setup, which is so important for lifecycle planning is available also within this view.
On the Phase In Phase Out Profile in SPP and DP
For those familiar with DP, you should note the similarity between the phase in, phase out profiles in DP and similar functionality in SPP. The major difference is that in the phase in forecasting, it can be based on the bill of distribution, which does not exist in DP. There is an issue with only being able to perform attribute forecasting along one attribute, which I discuss here.
Something which I could not figure out is why the phase in and phase out new profile screens looked so different from the initial screens. I have the the phase out profile screen listed.
Now here is the new entry screen for the phase out profile.
So where and how are the details entered into the profile. This is a conundrum.
This functionality and setup is copied from DP. However, you can see that the phase in or phase out forecast can be based on the BOD in SPP, which does not exist of course in DP. According to SAP, this works in the following way.
In thePhase-In Forecast Based on BOD planning service, the system transfers the phase-in forecast that it previously executed at product level to the bill of distribution (BOD) and disaggregates the calculated forecast values. - SAP Help
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Problems with Phase In / Phase Out Profiles
As a general comment, after working extensively with the phase in and phase out profiles in DP, I am not a very big fan of them. This is something I could see doing in an external system which is better at manual adjustments. In APO if you want to setup a profile with a 2% increase, that is one profile. 2.5% increase is another profile. I have a full explanation of the issues withlife-cycleplanning listed in this article.
However, life cycle management is handled in the supply side of SPP on the SPP Properties tab of the Product Location Master.
http://www.scmfocus.com/demandplanning/2010/09/the-problem-using-dp-for-lifecycle-planning/
There are simply better ways to manage the life-cycle forecasting of products that what is available in SPP and DP. To read more about life cycle forecasting, see this post.
http://www.scmfocus.com/demandplanning/2010/10/life-cycle-demand-planning/
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Life cycle planning does not work in SNP as shelf life does not work.
http://www.scmfocus.com/sapplanning/2008/09/27/spp-product-master-setup/
Thus life-cycle functionality resides both in the supply planning software as well as demand planning.
Re-calculation
This is also where recalculation is performed. Re-calculation allows historical forecasts for product locations according to a new forecast model that are not initially available.
These are the major fields that control the re-calculation.
However, the actual recalculation is controlled by the service SPP_RECALC_HISTFCST
Leading Indicator
This is also where the leading indicator service is setup. The options for this are listed below. Its really basic at this level, in that the history to be used needs to be selected:
I have have been unable to get leading indicator to work properly due to an error with a structure. If anyone has luck with configuring it, email me and I can update this post. Leading Indicator is new as of 5.1 and does not appear to have the bugs worked out of it yet.
Here are some other posts on leading indicator in SPP.
http://www.scmfocus.com/sapplanning/2008/10/30/spp-leading-indicator-synopsis/
Automatic model selection is used to determine the sequence of the system to conduct forecast tests. Weighing factors can be setup which can be applied to each forecast test. This is completed in terms of the configuration here.
To go to the forecast profile, on the SAP Easy Access screen, choose Advanced Planning and Optimization -> Service Parts Planning (SPP) -> Forecast.
Smoothing Parameters
These are combinations of alpha beta and gamma which are used in exponential smoothing.
There is not much to creating a Smoothing Parameter. Just the following:
Profile Name, Counter, Alpha, Beta Gamma
Seasonal Coefficients
Profile Name, Period, Index
Leading Indicators
These are the characteristics and key figures that make up the leading indicator forecasting.
Under leading indicator groups the following semantics can be added.
IMG: APO –> Supply Chain Planning –> SPP –> Forecasting –> Define Leading Indicators
To find out about this leading indicator setup see the post below.
http://www.scmfocus.com/sapplanning/2010/09/26/leading-indicator-forecasting-in-spp/
Define Final Forecast Determination Profile
This is where the forecast key figures that you want the system to adopt in the final forecast. When calculating the forecast the system first checks with sequence entry 1 if it exists.
We have four options, that are listed above. It all deals with how the forecast is treated. You can see the current sequence of the configuration below.
Phase In and Out Groups
These are simply containers for phase in phase out profiles.
More configuration for each of the areas discussed above is available under the same menu:
IMG: APO –> Supply Chain Planning –> SPP –> Forecasting
Auto Model Selection
Auto Model Selection can be found by going to the following menu item:
IMG: APO –> Supply Chain Planning –> SPP –> Forecasting –> Define Automatic Model Selection
The Auto Model Selection is initiated if the normal forecast is not effective. For those who use DP, this should appear familiar. You can read about some of the issues of Auto Model Selection or “best fit” with DP in this post.
http://www.scmfocus.com/demandplanning/2010/07/getting-best-fit-to-work-in-sap/
As you can see, the Auto Model Selection performs the test for seasonality, trend, sporadic behavior, and dynamic moving average. That is each can have only one of these. It should be apparent to those who are used to the Auto Model Selection in DP that there is quite a lot more involved in setting up this function in SPP than in DP.
After an Auto Model selection is created it is selected for in the service profile.
Stability Periods
SPP also has the ability to prevent the forecast methodologies from changing too often. These are called stability periods. This stability period is very similar to the stability period that is used in SPP in the stocking and de-stocking service, which is on the supply planning side of SPP.
http://www.scmfocus.com/sapplanning/2008/09/29/spp-stocking-and-destocking/
These settings are made in the Forecast Profile, which is setup here.
SAP Easy Access: APO –> SPP –> Planning –> Forecasting –> Forecast Profile
The fields that can be altered to control the stability periods are the following:
As you can see, different stability periods (in months) can be applied to different forecasting methodologies. However, looking at all of these options, I am not sure how I would get client agreement as to what the stability periods should be. I think it would make sense to start off by simply setting all the stability periods to a standard interval and find out how often the client wants models to change full stop.
Forecast Parameters
Exponential smoothing parameters can be set in SPP and created as profiles. You can get to this screen though the following path.
IMG: APO –> Supply Chain Planning –> SPP — Forecasting –> Define Smoothing Factor Set
These profiles can then be applied to products. Thus just a few profiles could be assigned and control any number of products. The profiles are assigned in the Profile Name of Smoothing Factor Set on the Model Parameter tab of the Forecast Profile.
SAP Easy Access: APO –> SPP –> Planning –> Forecasting –> Forecast Profile
While this sounds pretty efficient, however, in fact, most forecasting solutions are moving away from directly setting the parameters for exponential smoothing in this way, but rather allow for these values to be optimized by the system. This approach also implements much more smoothly.
Interestingly, this is not the only place where smoothing parameters can be changed. In what SPP calls “fine tuning,” parameters can be changed on the Model Parameter tab of the Forecast Profile. However, I don’t think it is a good practice to give planners access to this, and also these controls are not a very intuitive way to change the forecast. For this reason, I am not going to go into detail on this area.
Why SAP DP Should Not be Used for Consensus Based Forecasting
The need for consensus based forecasting is great, however, attempting to do this with SAP only is a recipe for failure.
No Functionality in SAP
If you do a search for SAP and consensus based forecasting you can find a smattering of hits, however no real substance. The only related functionality that SAP APO DP offers is to allow different people to enter their forecasts into the planning book.
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Planning Book Problems and Limitations
The planning book is a rigid planning view with difficult to configure selection criteria (which are hidden during the viewing), and a series of measures, which are on rows while the columns show the planning buckets. The planning book has not been improved in any substantial way in at least 5 years and becomes very sluggish at high volumes. The planning book is not a very “inspirational” interface. In fact depressing might be a better description. It does a poor job informing the user and will never get the best out of them. Often promoted by SAP consultants who have never worked with other interfaces and because they are required to by their consulting firms.
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Making CBF Work
Consensus based forecasting (CBF) means getting people to enter their forecasts and in a timely manner, and being able to control the way the forecasts are combined to produce the final consensus forecast. However, the DP Planning Book was never designed to do any of this. Which is why I recommend other tools that have actually been designed for this task. However, not being able to do it, does not stop SAP being used to try to perform consensus based forecasting on projects. One of the reasons for this is that I have now concluded that most clients and the vast majority of big consulting firms just don’t understand how the right software can enable CBF. They essentially think that CBF can use the exact same tools and approach as non-CBF. A few of the requirements for CBF include the following:
- The user interface must be extremely simple to use and extremely easy to show both selections criteria and drill downs.
- The CBF process must be “gated.” That is the tool must allow for the various forecast inputs to be centrally managed and have their contribution to the final consensus forecast increased and decreased flexibly, based upon previous performance and without the individual forecasting groups knowing.
- The product used must have fast response times, and needs to provide analytics. This draws the forecasters in to using the system and investing in its use. It serves to both inform them and motivate them to provide their best forecast. Very badly designed interfaces are tolerated by corporate buyers because they neither use the system themselves nor appreciate how poor interfaces inhibit software implementation success.
- While not an absolutely necessity, there is some evidence that perhaps the traditional way of performing consensus based forecasting is not the best approach, and that the field of study of prediction markets has a lot of offer.
It is inadvisable to let SAP or any other software vendor select other software vendors for you. This is a clear conflict of interest which should not be watered down by the repeated use of the term “partnership.”
Putting The Kibosh on SAP Selected Software
If SAP eventually wakes up to the concept of CBF they may attempt to “partner” with a firm and offer them as a selected partner. I would very much recommend against having SAP select your software for you. These partnership arrangements primarily entail making the partner subordinate to SAP and all that is really provided to the client is some extremely hastily developed adapters that SAP can use to say the systems are “integrated.” They then present that vendor as the best vendor in the space, which more accurately should be described as the vendor that agreed to sign an extremely one-sided partnership agreement with them. Finally, the client pays SAP and then SAP pays the other software company and keeps between 40% and 70% of the money, greatly reducing the money available for further enhancing the product or even supporting it. To find more about this program see this link.
http://www.scmfocus.com/invoptmultiechelon/2010/01/its-time-for-the-sap-xapps-program-to-die/
As I said the large consulting companies don’t understand this, and will continue to push SAP DP or even SAP ERP Demand Management to do CBF. For this reason I have decided to add selection and advisement services in CBF software and how to integrate this software functionally and technically to SAP so SAP clients can have real CBF.
http://www.scmfocus.com/consulting/areas-of-specialty/consensus-based-forecasting/
Sourcing Forecast for SNP and DP
What Is It?
This link directs the sourcing process to the appropriate DP planning area from which to read the forecast and the allocation-related data. It notifies the sourcing process which DP time series key figure represents the final forecast at the customer location for the above-mentioned DP planning areWhat Is It?
This is where forecasts will come from to populate these areas. The configuration is very simple. You simply enter the transaction and then select the sourcing for each.
There will be a DP planning area, which will be linked to the ATP allocations. You cannot execute the SNP Optimizer with this DP planning area because the SNP Optimizer can only process the SNP relevant planning area. Therefore, a link has to be established between the DP and the SNP planning areas. During the Sourcing run, this link specifies which DP planning area needs to be read for the forecast and the allocation data. This link directs the sourcing process to the appropriate DP planning area from which to read the forecast and the allocation-related data. It notifies the sourcing process which DP time series key figure represents the final forecast at the customer location for the above-mentioned DP planning area. – SAP Help For SNP we will select the planning area we created in the planning area post.
Read more about planning areas here:
http://www.scmfocus.com/sapplanning/2008/01/05/planning-areas/
There will be a DP planning area, which will be linked to the ATP allocations. You cannot execute the SNP Optimizer with this DP planning area because the SNP Optimizer can only process the SNP relevant planning area. Therefore, a link has to be established between the DP and the SNP planning areas. During the Sourcing run, this link specifies which DP planning area needs to be read for the forecast and the allocation date.
