Tag Archives: Hyperion
HFM 11.1.2.2 – New Features: Part – 2
Configurable Dimensionality:
‘Configurable dimensionality’ is the significant update to this version. We can probably say that this is the long awaited and biggest change that developers made to HFM.
So what is ‘Configurable dimensions’ is all about? There had always been a need for HFM customers to go beyond the four Custom dimensions, which are provided by default for their business needs. For e.g. they worked by stuffing two different details like Balance Sheet movements and Products details into a single Custom dimension. This was being addressed by Oracle in this release. Now, the users can have as many custom dimensions as required for their implementation. Let us see how this can be done starting by creating a new classic application.
Creating application:
Desktop Client: Many existing functions are cut down in Win32 client. Now, it has only Profile Manager and Metadata manager, rest all functions are available via Web including Create Application task. Profile Manager is used to define the application profile (.per). It can be installed in any machine since it can only be used in offline mode and has no dependency on HFM server component.
In addition to defining Year, Periods and Frequencies, we can now define the number of Custom dimensions as a part of the application profile. So basically, when you create application using this profile file, all these custom dimensions are created. The size (Small, Medium or Large) for a custom dimension must be determined depending on the number of members its hierarchy contains. Custom1&2 by default, are Large size. As shown in the screenshot, we’ve created a total of 6 Custom dimensions.
Login to the Workspace to use this profile and create the application. As you can see, web server URL need not be provided.
I’ve loaded some sample metadata and data for few periods. !CUSTOM_ORDER section is introduced which specifies the order in which the custom dimensions are displayed. This has to be specified in the metadata load file.
- .app
- .xml
Now, let’s skip the complexities and move the data up the Value dimension. At this point, I’m eager to see the application database structure.
Sub-cube Architecture:
Financial Management stores its data in database blocks called subcubes rather than in records. Subcube contains Page and Subcube dimensions. The Page dimensions are Scenario, Year, Entity, Value and the Subcube dimensions contain all the members of ICP, Account, View and Custom dimensions (in our case 6 custom dimensions). So typically, for a single Page dimension intersection, if we have 100 accounts and 10 valid members for each Custom dimension and all intersections are populated, then it would be 100000000 records.
HFM stores all this data for these dimensions in three tables:
- DCE (Currency Subcube)
Stores Entity and Parent Currency values and their adjustments.
- DCN (Parent Subcube)
Stores remaining value dimension members
- DCT (Journal Transactions)
Stores Journal Transactions and when posted, they are transferred to DCE (<Entity Currency Adjs>/<Parent Currency Adjs>) or DCN ([Parent Adjs]/[Contribution Adjs])
In the below table, DPx_INPUT and DPx_INPUTTRANSTYPE are repeating fields for each period that the application contains. The columns are numbered from zero so for 12 periods, the column names will be DP0_INPUT to DP11_INPUT and DP0_INPUTTRANSTYPE to DP11_INPUTTRANSTYPE.
Compared to the older versions, the column structure almost remains the same. Interestingly, if you’ve noticed, in older versions, there are four LCUSTOMx columns one for each custom dimension. In this version, I anticipated that for each extra custom we add to the application, there would be a new column added to these tables like LCUSTOM5 etc. But the structure doesn’t even contain LCUSTOM3 & LCUSTOM4 and it is tempting to know how data for other Custom dimensions are identified. We are working to find out the same and any comments from the readers are really appreciated.
The supporting products for HFM viz. Financial Reporting, FDM, Application Upgrade Utility and existing HFM rule functions were also being updated to support HFM’s Configurable Dimensionality. Although we have the flexibility of adding any number of custom dimensions, time taken for calculations, consolidation and other performance issues need to be considered and application should be designed accordingly.
HFM 11.1.2.2 – New Features: Part – 1
UI Enhancements:
The new User Interface for HFM is definitely a notable update when compared to the earlier version. It is easier to navigate and includes some special features as well. This is an outcome of migrating EPM components like HFM and Planning to Oracle’s ADF (Application Development Framework).
Let’s take a look at all these UI enhancements –
Multiple applications in Workspace:
Different HFM applications can be opened at the same time.
Multiple modules in an application:
Different HFM application modules in each application can be opened simultaneously.
POV enhancements:
There are significant changes to the way we select dimensions to Rows and Columns. We can relate this approach to Hyperion Financial Reporting wherein we ‘drag and drop’ dimensions to Rows and Columns in dimension layout. This approach is simpler and made common to both data grids and data forms. We can also add dimensions manually in data forms.
Data grid enhancements:
Again, we can relate the creation of data grids to how we create the reports in Financial Reporting. In HFR, we create/design the report and run the report to view it. Similarly, we have Grid designer and Grid Viewer in data grids.
- Grid Designer
- Grid Viewer
Display options were docked to the right hand side thus decreasing the time wasted on navigation.
Another new feature is the indication of cell colors at the bottom of the Grid Viewer. This will be very helpful to the business users and they don’t need to reach support or documentation to understand the Cell Colors.
Data form enhancements:
Member selection process is pretty much similar to what we do in data grids. And there exists designer and viewer in data forms too. Export to/Import from Excel options were disabled.
- Designer
- Viewer
Favorite members in Member selection:
Frequently used members can be selected and saved as favorites. These are available across other modules of the application as well.
Loads and Extracts page:
Load and Extract tasks like Security, Metadata, Member Lists and Rules are consolidated in one single page.
Journals Module Enhancements:
Journal tasks functionality is pretty much same but with major changes in UI again. Journal reports module exists both as a separate task and as a part of Manage Journals (opens in a new window when clicked).
Intercompany transactions module is not available and will be included in the upcoming patch – 11.1.2.2.101. It might take some time for the old version users to get used to navigating the new interface. Hope we can leverage from these ADF features. There are other enhancements to the HFM Win 32 client and Custom dimension configuration, which will be covered in a different post.
EPM 11.1.2.2 – Planning New Features
As mentioned in my previous post here, EPM 11.1.2.2 has introduced a bevy of new features that customers have been asking for a while. Also, 11.1.2.2 theoretically is the actual Fusion release as all components now use ADF UI natively. In today’s post we shall cover the new features introduced in Planning 11.1.2.2.
UI Enhancements:
ADF branding is a lot more apparent with the 11.1.2.2 release. For example, all forms now use the native ADF based prompts, POVs and selectors. Also, the UI has been enhanced to give “Concertina” style menus so that it is easier to access related & relevant objects
Adhoc Grids use more of ADF features like swapping columns from rows to columns, pages to columns etc. Adhoc grids are more like BI EE 11g in UI.
Cell Data History:
This is one feature that planners and people who are part of the approval chain will really like i.e. showcase who has modified what data. Generally when plans are submitted for approval, the approver has to go through all the cells and find out what has changed manually. But with this feature its a lot easier to find out who has modified what cells. This can result in faster approvals and reduced effort spent.
For this to work Auditing at Cell Data level needs to be turned on.
Charts in Planning Forms:
Another key feature is in the ability to display the forms as charts in a Composite form. This way planners can immediately visualize the change in data.
More important drills are available on graphs as well – Now we need this capability in BI EE i.e. here the drills are all native Essbase drills (unlike in BI EE where we have to go through the RPD).
Grid Diagnostics:
Another significant new feature is the ability to find out poorly performing/designed forms by using the Grid Diagnostics feature. This will let us know the page load times, number of row retrieved, suppressed etc. Pretty handy tool especially for Administrators
Substitution Variables Management from Planning:
Another excellent & long-pending feature is the ability to manage & update the substitution variables used per plan type directly from Planning App. There is no more dependency on Essbase/EAS (of course they still reside there but no need to create there first in EAS) to create the variables
Predictive Planning & Crystal Ball:
Another very interesting new feature is the ability to predict future plan values using Crystal Ball (or called as Predictive Planning now). It is natively integrated into Smart View. By just clicking on a cell within a form, one can start predicting what will be the plan values. Crystal Ball provides a comprehensive set of statistics as well while providing a recommended value (on what basis the recommendation was done).
In addition there are other small enhancements like Group Based Approvals, Rolling Forecasts (Setup at form level), Multiple cell document attachments, De-support of Business rules etc. Also, from an architecture standpoint we can now have multiple Planning Managed Servers in a cluster thereby making it truly Highly Available. In the next post, we shall see the new features in HFM 11.1.2.2.
HPCM 11.1.2.2 – Detailed Profitability
2 Weeks back, EPM 11.1.2.2 released with a lot of new features. The number of new features are so much so that it will take at least 8 to 10 posts to go over all them in detail. I thought i will start off with writing about a new feature that is relevant to a project we are executing currently i.e. HPCM Detailed profitability. If you had looked at my previous post on HPCM here(which i will refer to as Standard Profitability), i would have walked through how HPCM works and how Essbase plays a vital part in the functioning of HPCM. Though it is & was a great product, there were certain drawbacks in using Standard Profitability. I will list them below
1. Use of Essbase added un-necessary complication in data loads & reporting
2. Essbase though was very good, the calculation scripts generated by HPCM warranted minimal exception based driver assignments (single-cell driver assignments) as that can slow down the calculations
3. Though the concept of stages was very good, to me for simple models exposing a lot of stages to end users was not only confusing but also results in a bloated Essbase cube.
4. In a 8 stage model with intra stage allocation enabled (and each stage having 3 dimensions), the Essbase database will have a total of 16*3=48 dimensions. A block storage cube with so many such dimensions generally does not scale well at all.
5. Using BI EE to report out of a HPCM cube requires carefully applied filters. It requires a very good understanding of not only Essbase & BI EE but also how HPCM stores data within Essbase.
6. There was no easy way to do a direct integration from relational tables – So all data before getting loaded into HPCM had to be processed externally to fit into Essbase formats.
7. Standard Profitability had a restriction of 3 dimensions per source stage. In many cases we might need more than 3 source dimensions per stage.
With the introduction of Detailed Profitability, Oracle has tried to address all the issues above by moving away & using relational databases for storing input & calculated data, instead of Essbase. According to the docs, this results in extremely high scalability as it supports unto 5 source stage dimensions & upto 25 target stage dimensions. Also, Detailed Profitability supports only 2 stages instead of the standard 8 stages. More importantly, Detailed Profitability is not a replacement for Standard Profitability. Rather it is another way of doing Profitability & Cost Management as Standard Profitability has its own advantages as well. In this post, we shall look at how Detailed Profitability works and how it is different from Standard Profitability.
Concepts of allocation, driver etc remain the same in both types of applications. But the key difference is in the architecture. At a high the architecture for Detailed Profitability is given below
As you see, by default when we create an application, the product install/configuration schema will be used as the Product Metadata schema. This schema will contain all the necessary tables for holding the Metadata like Models, Stages, Dimensions etc. The Model Data Schema replaces the Essbase ASO-BSO cubes in the older Standard Profitability application. So, to create a Detailed Profitability application we start off with building an application from EPMA as shown below
As you notice, we have a small new check box called Detail Application. This is what enables the Detailed Profitability Module. Then as before we start building the dimensions for the new application.
There is one thing we can notice. There is only one Local System dimension called MeasuresDetailed. There is no AllocationType dimension.
Other dimensions and the order of members etc all remain the same.
Lets now open the application and understand the workings of Detailed Profitability. By just opening the application we can notice 3 main things
1. There is no separate Trace Allocations screen – Interesting as this was one of the most important points that Oracle/Partners like us showcase while demoing the product. But again from a practice standpoint i think it is one of the least used features by power users.
2. There are a couple of new features like Model Data Registration, Stage Object Calculation etc which will take a look later in the article
3. Manage Database option is still there though Essbase is not there – Manage Database is used to deploy the reporting views (that supersede Essbase in Detailed Profitability)
The first step in defining the Model is to associate the Model Data Schema to the model. I was sort of expecting a profile to be created to point to a specific database schema, That is not the case. Instead, we will have to create a separate database schema and then create all our necessary source/target tables within that schema. Grant select/update access on all these tables to the main product schema. Once the grant is done, the schemas will start appearing in the Model Summary as shown below
Once we have chosen the Model Data Schema, we will have to register all the tables that we are going to use as a source & target as part of the Model Data Registration. This is where Detailed Profitability scores higher than the Standard Profitability. In most practical customer scenarios, all cost/revenue related data will be coming in directly from ERP sources (like GL). In such cases, it is easier to model them directly on the source tables rather than using a separate Essbase data source. Another most important aspect of the registration process is in ensuring that we have a source and destination measure dimension. A measure dimension is what qualifies the incoming and outgoing costs. Other dimensions are considered as attributes of the measures. We can have the same dimension used for source as well as destination.
As you see there are 3 types of tables
1. Source Tables – Vertical Or Horizontal
2. Destination Tables – Horizontal
3. Lookup Table – Horizontal
A vertical table means the measures are stored in a separate dimension instead of separate table columns (similar to Essbase measure dimension). Horizontal table means all measures are represented as columns. This designation is needed as Essbase is now superseded by Relational Tables.
In the same map the target the HRCostsAllocation table to Target Horizontally oriented table type.
Few things to remember while mapping a Destination Stage Table – It has to have a Working column with a numeric data type. It also should have a primary key constraint.
We now have the source and the destination defined. Lets now define the stages. As mentioned Detailed Profitability has only 2 stages (Source & Destination) as against a possible 8 stages in the Standard Profitability.
Lets now define the driver HeadCount as shown below
If you notice, there are a few things that have changed in the Driver definition screen. In the older HPCM, we will just be choosing the Driver Measure and then will be assigning the priority along with the location (source, destination, global etc). But here, since it is relational, we have a destination measure that has to be the driver. In addition, the driver is associated with an actual measure that will be used as a target for all allocations. If a measure is assigned at a driver level how do we then assign target intersections? That is all done through Assignment rules in Detailed Profitability.
After the assignments, lets deploy the views required for reporting
Lets now run the calculation
If we now look at the Destination table, we will see the post allocated results as shown below
This to me is so much easier to work with when compared with Standard Profitability. The allocations are a lot more clearer and of course we still have the same flexibility as the Standard Profitability. The most important aspect from my standpoint is the ability to do out of the box reporting using BI EE. This does not require separate custom Essbase models unlike the Standard Profitability.
Hyperion Profitability & Cost Management – Overview
Recently i have been doing lot more work on the Oracle EPM stack than on the Oracle BI stack. So, i will be writing more on the various Oracle EPM products like HFM, Planning, FDQM etc in the forthcoming weeks. To sort of kick start the series of postings, i thought i will begin an article on Hyperion Profitability & Cost Management also popularly known as HPCM. It is one of those products that is often overlooked, due to the overlap of features it has with other products like Essbase & Planning. It is sort of a targeted product with a solid technical foundation and uses Hyperion Essbase as its backend. On the outset, HPCM primarily provides Functional Users with the ability to automatically allocate Costs & Revenue to various departments, accounts thereby giving the ability to do proper & complete profitability reporting.
HPCM primarily has 3 main sweet spots
1. Every company will have indirect costs. For example, a Consulting company where Revenue is obtained through driving projects will have a lot of indirect costs like HR Costs, Admin Costs etc. HPCM provides an ability to allocate the costs back to the projects so that proper project profitability is derived. How the costs are allocated will be defined through HPCM itself. For example, if a company is running say 3 consulting projects with 20, 30 & 40 resources each, then the indirect costs are allocated back to the project based on the number of people(or time logged etc) in each project.
2. Every company will be storing the incoming Revenue & Costs in a Ledger. Due to various reasons, even the direct costs & revenue might not actually be tied back to a project (Consulting company example above). So, there might be a need to allocate the project based Direct Costs & Revenue as well to the Projects (allocation possibly by head count etc).
3. Allocation of Costs is pretty dynamic in nature depending on the type of business. It can vary quite frequently. So, the key is to ensure that the allocation logic can be changed frequently and easily. In addition, one more key point is to find the lineage back to the source on how the costs are obtained.
HPCM provides all the 3 above. If you are an Essbase or a Planning person, you could argue that we can do the same thing using these 2 products itself. Though true, in many cases Cost & Revenue allocation rules are defined by Functional Users. So, it is not possible for Functional users to create Business Rules/Calculation Scripts every time there is a change. In addition though Essbase is very good, it is very difficult to do a data lineage from a calculation script, to find out how the costs are allocated. Thats the main reason why, HPCM is a solution positioned primarily at Business/Functional users for providing that cost & Revenue Breakdown.
Though i have mentioned that HPCM is a functional tool, its underlying technology is very interesting. It has a relational metadata that stores the metadata related to HPCM. In addition each HPCM application will have 2 Essbase databases. One is Block Storage cube which will be used for the allocation & calculations. The other is a reporting Aggregate Storage cube which will be used for reporting. Data push from BSO and ASO is automatically available out of the box from HPCM. Also, one important point to note, change to dimensions, change to metadata, pushing data from BSO to ASO are all achieved within HPCM without writing any external code/scripts. Everything is done out of the box. This architecture is shown below.
In addition, the most interesting aspect of HPCM is the way it handles dimensions. This is what we will be covering in this article today. HPCM uses EPMA for managing its dimensions & attributes. HPCM as an application has 3 types of dimensions
1. System Dimensions – There are 2 System Dimensions – Measures & AllocationType. Generally while creating a HPCM application through the Wizard we can pre-create these 2 dimensions. AllocationType is used by HPCM internally for doing allocations. It is generally not needed to make any changes to this dimension. But Measures dimension is the most important dimension that HPCM uses for pushing costs & allocating them. We can create custom members in the Measure dimension if needed.
2. POV Dimensions – HPCM supports upto 4 point of view dimensions. These dimensions are generally for storing Year, Period, Scenario & Version. True to their names, they generally are used as POVs and are not used directly in any allocation (the POVs are always fixed in the calculation scripts).
3. Business Dimensions – Business Dimensions are those dimensions where allocations happen. These dimensions drive the allocation logic.
In addition HPCM also supports alias and attribute dimensions. For this article, i will use a simple case of demonstrating how to go about allocating HR Costs in a Consulting Company recognising its revenue through Projects. Lets make an assumption that on a monthly basis we record the HR Costs (including Salary paid to HR, other misc costs) etc. Lets also assume that we have 3 projects running in the company with the following break-up
a. Project A – 300 people full time
b. Project B – 500 people full time
c. Proejct C – 200 people full time
We will start off with creating the application through the Application Wizard (pre-create System Dimensions) and then we shall define the necessary dimensions.
We basically have 2 business dimensions – one for Accounts which will hold the HR Costs. Then we have the Project dimension which will record the revenue and costs specific to the project.
Lets deploy this application and then login to the application through Workspace.
In HPCM all allocation happens through stages. Stages is where allocation happen. HPCM supports uppto 9 stages. Each stage also supports intra stage allocation. Lets try to understand what this means from a Multi-Dimensional Essbase database Standpoint. In our example, we will have 2 stages. The first stage will have just the Accounts dimension – basically HRCosts in Accounts dimension will flow from Stage 1 to Stage 2 and will get allocated in Stage 2. So, Stage 2 will contain both the Accounts and Project dimensions.
After creating these 2 stages(ensure you also have a POV defined) lets go ahead and deploy this to Essbase from the Manage Database screen(both Calculation & Reporting Database). What you will notice is 3 things
1. There will be 2 essbase databases one suffixed with letter C and the other suffixed with letter R. C database is the Block Storage database that is used for allocation. R database is the Aggregated Storage database that will be used for reporting.
2. You will notice that for each stage there will be a corresponding set of dimensions prefixed by the Stage prefix given at the time of creation. So effectively, if there are 2 stages with 2 dimensions each, then Essbase will have 4 dimensions (though the 2 dimensions might be the same in EPMA).
3. You will also notice that each dimension will have a dummy member called NoMember. This is one of the most important members that controls the grain of the data. This member is the key in loading multi-grain data for allocation into HPCM.
Now that we have the Essbase cubes deployed as well, lets try to understand how the allocation logic works. To begin with lets assume for the month of Jan 2011, the HR Costs for the Consulting Company is say 1000 USD as shown below
This is the input data into Stage 1. So to load this in we will have be creating a text file and load it directly into Essbase. There are 3 options to load data into HPCM
1. Manual Data Entry – HPCM provides a screen where we can update data manually.
2. Staging Tables – We can load the data temporarily into a set of staging tables, and then from within HPCM we can push the data from Staging tables into Essbase.
3. Directly loading data into Essbase
In our case, we will load the data directly into Essbase as that will give more clarity on how HPCM works. For doing data load for Stage 1, remember we have a total of 9 dimensions in Essbase (Measures,AllocationType,Year, Scenario, Period, Version, ACAccount,PRAccount,PRProject). But our input data of HRCosts comes at a grain of only 7 dimensions (Measures,AllocationType,Year, Scenario, Period, Version, ACAccount). So, load this in we will have use the NoMember intersection of the remaining 2 dimensions (PRAccount & PRProject). The input data file to Essbase is shown below
CostInput,DirectAllocation,2011,Jan,Actual,Working,HRCosts,[PRAccounts].[NoMember],[PRProgram].[NoMember],1000
Our idea is to allocate the 1000 USD down to the 3 projects for the January Month. So, our end result should look like this
If you notice, the 1000 USD is split across the 3 projects based on the overall number of resources(Resource Count for each project/Total Resources*HRCost) in each project. So basically for the allocation to happen, we need to load the Resource Count data. Resource Count data for all projects and the individual projects have to be loaded as shown below
FixedDriverValue,DirectAllocation,2011,Jan,Working,Actual,HRCosts,HRCosts,Project A,300
FixedDriverValue,DirectAllocation,2011,Jan,Working,Actual,HRCosts,HRCosts,Project B,500
FixedDriverValue,DirectAllocation,2011,Jan,Working,Actual,HRCosts,HRCosts,Project C,200
Weight,DirectAllocation,2011,Jan,Working,Actual,HRCosts,[PRAccounts].[NoMember],[PRProgram].[NoMember],1000
In the above data file there are 2 things we can notice
1. We have used a measure called FixedDriverValue and Weight. We will see their significance a little bit later. For now think of them as intersections that will hold the Resource Count Data.
2. The first 3 records above have HRCosts repeated twice to load into both the Accounts dimension we have in the Essbase Cube. Again we will see the significance of why we are doing this below.
So far we have loaded all the necessary data into the Essbase Cubes and have also setup the stages. The next step is in defining the Allocation Logic. This is done through a concept called Drivers. From the Perspective of HPCM, drivers define how the allocation values get pushed from source to target. HPCM supports different allocations like Activity Based Costing etc through the concept of Drivers. In our case, the Driver for allocation is the Resource Count. Just to recap, within Essbase now we have dimensions catering to two stages – Stage 1 and Stage 2. This is illustrated below. So basically we have 3 separate sub-cubes each having its own intersection.
In the above diagram, whenever we want to do allocation there can be different ways of doing it. The 3 most common ways are
1. Allocation Based on Source – Here all the driver values are obtained from the source stage and data from source stage is then assigned to the Destination Stage based on the Source driver values.
2. Allocation Based on Destination – Here all the driver values are obtained from Destination stage and data from source stage is then assigned to the Destination Stage based on the Destination driver values.
3. Allocation Based on Source & Destination – Also known as Assignments – Here all the driver values are obtained from the intersection of Source & Destination and data from source stage is then assigned to the Destination Stage based on the Assignment driver values.
If you look at our Driver data above (3 records containing FixedDriverValue & 1 containing Weight), you can see that our driver (Resource Count) is loaded in 2 ways. First the FixedDriverValue is loaded at the intersection of Source & Destination stages. The second driver Weight is loaded at the Source Stage intersection. We have chosen these 2 measures (FixedDriverValue & Weight). We could have chosen any other measure like Rate, Volume etc. But each measure has a logical meaning and it is better to stick to the ones we think is logically close to what we are trying to do. If we are not able to use the existing measures and if they don’t relate to our driver names then we can create custom measures. So, this allocation handling through drivers is defined through the Driver Definition screen in HPCM.
As you see in our formula we are basically doing a division of each Resource Count from Stage 2 by the Total Resource Count in Stage 1. HPCM will automatically multiply the resulting values of the driver to the CostInput measure (input data) thereby allocating.
Once we have defined the driver the next step is to assign the driver to both the stages. HPCM allows us to have multiple drivers for each stage. And even within a single dimension in a stage we can define exceptions so that multiple drivers can be assigned within the same dimension. This way we can have allocation logic based not only on Resource Count but also on say Clocked Time of a resource in certain cases. Driver assignment is done through the Driver Selection screen in HPCM.
After the assignments, one other important feature of HPCM is its ability to assign allocations on a cell by cell basis. So, what we can do is, for each cell in the Source Stage we can assign the Destination cell(s) in the Destination Stage. That way we can clearly find out what intersections will get affected by what allocation logic. If you had to do them through say Essbase Calculation Scripts alone, it would have been such a laborious task not only while doing the allocations but also in maintaining them. In our example, lets assign the Data intersection of HRCosts in Stage 1 to the 3 Destination Projects in Stage 2 as shown below
Now lets run the Calculation & then immediately transfer the data to the ASO cube from the Manage Calculation screen.
If you now look at the data you can clearly see that each project now will have the corresponding costs allocated.
To validate how the costs have flown through the stages, HPCM provides an option to do a stage balancing report. This will show us how the costs have moved from stage to stage. In addition one biggest advantage of HPCM is, if there are any unassigned costs in the source, those will automatically move into Idle Costs (or we can configure it throw an error to ensure all costs are always allocated).
In terms of reporting, the ASO cube that HPCM provides will be more than sufficient. But based on what i have seen, we will have a lot of un-necessary dimensions especially when we are not concerned about the inter-stage essbase dimensions. In such cases, we can build our own ASO cube and extract only the necessary intersections that we need. But for now, i will showcase how BI EE 11g can be used for reporting again the native HPCM ASO cube. I will quickly show the lineage breakup reports as well
We start off with importing the ASO cube into BI EE which is pretty straight-forward as shown below.
Then lets start with building the report just for looking at our Stage 1 data. Remember Stage 1 input HRCosts data is loaded against NoMember intersections of the other dimensions. So we will have to explicitly filter to arrive at the right data.
Similarly to get the final allocated data we will have to apply filters as shown below
In the same way we can get the driver values directly from the cube using a simple BI EE report. All of these are shown in the form of a dashboard – showing how the costs from stage to stage using the drivers.