Out-of-the-Box Features: Profitability and Cost Management Cloud Service (PCMCS) – Intelligence and Dashboarding: Queries

Welcome back to the Profitability and Cost Management out-of-the-box features series!

Here, you’ll gain insight to fully leverage the features bundled with an Enterprise Cloud Subscription which includes Profitability and Cost Management. The focus of this post is: PCM queries – artifacts that represent or extract data in an easily consumable format.

At the end of this blog post, the below topics should be familiar to the reader:

  1. Define PCM Queries
  2. Queries Use Cases
  3. How to Launch Queries in PCM
  4. Query Options
  5. Data Extract Format
  6. Common Errors and Warnings
  7. Alternate Uses of PCM Queries

*The contents of this blog post are based on the standard Bikes (BkML30) application. Deploying the PCM Demo Bikes application can be achieved via the PCM landing page — “Creating a Sample application button” (from version 19.06 onwards).

1. What is a PCM Query? 

PCM Queries are predefined statements with execution mechanics like Smart View retrievals.

Queries can be launched in one of three ways:

  1. Via the PCM Graphical User Interface (GUI)
  2. Automatically through EPM Automate/REST API commands
  3. Within Dashboards and Intelligence analysis reports (covered in greater detail in a this previous post).

2. Queries Use Cases 

Queries are versatile artifacts that have a list of use cases limited only by the user’s imagination. The most common use cases are:

  1. Data Validation – leveraged both for input as well as post-allocated results. Queries can be created and stored in a PCMCS instance. Their definition is similar to a Smart View query, with Columns, Rows, and Point of View (POV) selections. More details are found in the queries options section. PCM Queries have drill-through capability – applicable only to base level queries, leveraging the Cloud Data Management functionality.
  2. Driver/Adjustment Data Entry Template – while queries do not rise to the capabilities of a PBCS/EPBCS web data entry form, they manage to solve the issue of “directional intersections” in an elegant manner. By defining the base level intersections where driver data should reside and storing that query definition, users avoid the need for offline sheets for data entry.
  3. Refined Data Clear Selection – queries can be leveraged to trigger narrow or specific data clears aimed at replacing partial data sets. During a clear POV action, users can select a predefined query to restrict the clear scope. This feature optimizes data loads enabling users to restrict the replacement of input data to only those intersections that are required to be replaced. Think of it as a predefined FIX statement or a predefined tuple.
  4. Simplified Task Lists  – An example of this capability is explained in detail within the “Alternative uses” section of this blog.
  5. Journal Entry or Data Warehouse export – formatted data exports that can be leveraged as Journals within a GL submission process, in .csv extracts, without any custom formatting functionality like header, footer, record count, date/time stamp, etc.

3. How to Launch PCM Queries 

There are several Graphical User Interfaces (GUI) as well as automation options to launch queries.

1.  Intelligence Menu Section – clicking the query name opens a Smart View connection within an Excel session, prompting users to enter their Cloud credentials. If the Excel session is not terminated, credentials will persist for all subsequent query launches.
Blog Post.Alec Intelligence Menu Section Picture

From the Actions button, users can also launch a direct .csv export of each query. The exported file will be placed within the File Explorer section and is available for download. Users can define the number of decimals they choose to extract – up to a maximum of 7 – and whether or not they choose to perform a base-level export or an aggregated data export.

2.  Manage Queries Section – this menu includes all the capabilities found within the Intelligence menu section along with the ability to edit, delete, or create new queries.

3.  EPM Automate Command – if the desire is to launch a query and generate a .csv file in an automated manner, the requirement can be achieved by executing the following command: epmautomate exportqueryresults APPLICATION_NAME fileName = FILE_NAME [queryName = QUERY_NAME] [exportOnlyLevel0Flg=true]The .csv file generate is very similar to a data warehouse extract file with all dimensions displayed in columns and separated by a space delimiter.

By omitting the queryName parameter, the automation will execute a full base-level data extract of the PCM application in the native ASO format. (non-columnar, optimized for native ASO data load).

Alternatively, if the query must be used in a targeted data clear, the request can be launched via automation:  epmautomate clearpov APPLICATION_NAME POV_NAME [QUERY_NAME] PARAMETER = VALUEstringDelimiter = “DELIMITER”

Example:

epmautomate clearpov BksML 2019_Jan_Actual queryName=BksML_2019_Jan_clear_query isManageRule=false is InputData=false isAllocatedValuses=fasle is AjustmentValues=false stringDelimiter

When uisng targeted data clears, no other parameters can be enabled, such as isManagerRule, isInputData, isAllocatedValue, or isAdjustmentValues.

4.  Rest API Command – just like EPM Automate, REST API is used for automation (lights-out processing). EPM Automate leverages REST API in the background. The difference between REST API and EPM Automate is not the scope of this post; however, one of the main differences between the two is the enhanced logging level available with REST API, which is why implementation partners may favor REST vs EPM Automate.

https://<SERVICE_NAME>-<TENANT_NAME>.<SERVICE_TYPE>.<dcX>.oraclecloud.com/epm/rest/v1/applications/Ex3F3/jobs/exportQueryResultsJob

{“queryName”: “Proftiability – Product”,”fileName”: “ProfitabilityProduct2019.txt”,”exportOnlyLevel0Flg”:”true”}

The syntax for a targeted data clear is the following:

https://<SERVICE_NAME>-<TENANT_NAME>.<SERVICE_TYPE>.<dcX>.oraclecloud.com/epm/rest/{api_version}/applications/{application}/povs/{povGroupMember}/jobs/clearPOVJob

{“isInputData”:”true”,”queryName”:”myQueryName”,”stringDelimiter”:”_”}

4. Query Options 

PCM has a few displays and data extract options that can be stored with the query, and more that can be selected during run time via the GUI or through automation scripts. The settings can be separated into two categories:

1. Optional Query-Store Settings

Option 1: Use Aliases: If not deselected, the member name will be used instead.

Option 2: Suppress Missing data during execution. If not selected,

Option 3: Include Attribute Dimensions

Option 4: Order of columns (ignored during granularity override selected at run-time)

2. Mandatory Query-Stored Settings

Option 5: Column/Row Selection

Each dimension reference must indicate whether it is to be used in the Row, Column, or Point of View (POV). It is possible to save queries with no POV reference, the only mandatory selections being those of Columns and Rows.

Any dimension member selection marked as POV will be displayed either in the POV menu/floating box within Smart View or as the header record content if the POV box is disabled in Smart View.

Blog Post.Alec Mandatory Query-Stored Settings

This is a screenshot with the alternative of the POV box disabled.  Users will be able to see a representation of all dimensions that were a part of the toggle POV box when the POV was enabled.

Blog Post.Alec Mandatory Query-Stored Settings2

The selection of Row, Column, and POV will be bypassed during data extracts, whether launched through the menu or via the EPM Automate or REST API commands. All data extracts will list out the members referenced in the selection for each dimension followed by a single data column.

3. Optional GUI Run – time Settings:

Option 6: Export only level-0 data. This will force the query to produce base-level data intersections for all members where a base level has not already been selected in the query. Depending on the size and granularity of data, the query can take anything between 30 seconds up to several hours. Create multiple queries to support the larger data extracts or define the right level of granularity required for the target system to avoid slow extracts or even failures when exceeding the 5-mil records limit.

Option 7:  Rounding precision – extends to a maximum of 7 decimals.

Blog Post.Alec Optional GUI Run-Time Settings.png

Generating data with an increased number of decimals should be paired up with the Application setup of decimals detail as there is no point in generating a data extract with 5 decimals when the application is configured to only support up to 2. This configuration option is available in the Application menu and can be revisited and updated at any point in time.

If neither of these two optional GUI run-time settings are selected, the report will pull the level of granularity established within the query, whether setup at base level or at aggregated level intersections.

4. Optional Automation Settings: 

Option 8: Changing the precision of data extracts when launching queries via EPM Automate or REST API can be achieved via the parameter roundingPrecision with values ranging from (-6) to 7. By default, the EPM Automate exportqueryresults will extract data values with 2 decimal characters. Consider whether or not extracting data with multiple decimals is required, especially if the application Allocation Precision parameter has not been set to higher than the standard value of 2 decimals.

Blog Post.Alec Option8

5. Data Extract Format 

The Smart View query extract format will stay constant regardless of the choice of menu where it is launched.  The .csv file format; however, has a few variances depending on the options selected either during build or during run time.

The .csv format file generated will lose references to POV/Column/Row. As mentioned previously, the resulting file will look like a data warehouse extract – very similar to what can be achieved via an export script within a Planning Cloud Business Rule or Essbase export calc script.

If end users choose to perform a base-level extract override during run time or through Automation commands, the .csv extract will lose the predefined order of the dimensions setup in the query definition.

Regardless of the level of the data extracted (upper or base level), all members within a .csv file extract will be enclosed in double quotes. The delimiter will be “tab” and cannot be overridden or replaced from within the PCM GUI.

This is an example of the query “Profitability – MultiDimension” that is available with the Demo Bikes model. The query extract was launched via the GUI with 7 decimals and with no granularity override (no base level extract option selected at run-time):

Blog Post.Alec Data Extract Format

This is an example of the same query “Profitability – MultiDimension”– launched with 7 decimals and base-level members selection/override at run-time:

Blog Post.Alec Data Extract Format2

When comparing the above screenshots, the order of the columns was clearly altered. This is due to the base-level override selected during run time, and it is an important detail in case the .csv file must be used as a data feed to an external system.

6. Common Warnings and Errors 

Although this section does not represent an exhaustive list of errors, it covers the most common query-related issues a user may encounter along with the corresponding solution.

Warning message: “Query has invalid members. Save the Query to permanently remove the invalid references. To validate the entire Point of View, go to Model Validation without saving.”

Blog Post.Alec Common Warning and Errors

This is a generic message that can indicate either a warning or a true error.

Potential causes for this warning message: if row selections represent top-of-the-house (or so called Generation 0) members; in other words, the Dimension name, while queries may run and produce results, the warning will pop up every time the query is launched via the GUI.

In order to fix this warning, the row selection must be made on any other member or subset of members that is not referencing the Generation 0 / top-of-the-house member.

Second cause for the same warning message: a true error resulting from a member referenced in a query that has either been renamed or removed from the application. In this case, the query is pointing to a Generation 0 / top-of-the-house member, but that selection was not intentional. In most cases when this warning occurs, the obsolete member name reference was automatically removed and either replaced with the top level of the corresponding dimension or simply left blank:

Blog Post.Alec Second Cause for the same warning message

If the user wants to validate which reference was removed due to a metadata update, there is an option to run Model Validation* reports on queries to find out more details:

Blog Post Alec Model Validation 1

*More details on the Model Validation tabs and options will be covered in a future blog post.

In this example, the member STAT1201 has been renamed as STAT120. Because the query references STAT1201, the user is prompted to renew the Account reference selection within the query.

CAUTION: if the user receives this warning and saves the query before launching the Model Validation report, the previous member selection reference (which is now obsolete) is removed and replaced with the Dimension top member. This means that short of restoring the query from a prior snapshot, the user will no longer have a prior reference of the member that has been removed.

The number of query result cells exceeds the limit set by the QUERYRESULTLIMIT.

Blog Post.Alec Errors

Reference the advice given in Option6 (Optional GUI Run time settings section) to reduce the size of your query. This query limit cannot be manually updated by end users or administrators of the Profitability application.

7. Alternate Uses of PCM Queries 

One of the long-awaited features in PCM is the ability to create forms, menus, and task lists like those within Planning and Budgeting Cloud applications. In the absence of such features (which should be coming in future updates), queries can become an easy-to-use alternative. In the prior sections, we explored how queries can be leveraged as data entry guidance mechanisms like forms, data extract tool, and narrow-scope data removal tool. The one feature not discussed yet is the Task List alternative.

By creating predefined queries and listing them in a specific sequence, administrators can dictate the order of operations for either the setup/data load/pre-allocated values or the validation of a PCM model after the allocation process was completed. The listing below is very similar to the concept of Task Lists in PBCS/ EPBCS, and while PCM administrators cannot customize this list by user ID, it still offers that step-by-step guidance that an end user may find useful.

Blog Post.Alec Alternate Usues of PCM Queries

A few tips to keep in mind when leveraging queries in a Task list format:

  1. There are a limited number of characters for each query name. The limit is clearly enforced when editing the name of an existing query. Users can go beyond the limit of number of characters when building a new query from scratch, but this results in an ADF interface error message, and it is most likely a bug which will be addressed in future releases.
  2. The order of the queries is based on the name – descending or ascending. There is no option to customize query order (similar to up/down arrows that allow us to move tasks in Planning or PBCS). This restriction forces the naming convention to be similar to the above example.
  3. There is no option to restrict access at the query level. There are security restrictions/data grants that can be set up for each user to restrict access to the data within the PCM app, but there is no restriction to disable or not display a query or list of queries.

8. Conclusion on PCMCS Queries 

PCM Queries offer a wide array of functionalities that enable users to interact with PCM data throughout the entire processing cycle.

Queries can be used as Data Entry Form to define data entry templates for drivers, or for adjustments when launched via Smart View. By storing the intersections where data is expected to be entered in a query, end users don’t have to worry that they are sending values to the incorrect intersection. Once the query is saved, it can be leveraged multiple times. The references via formulas or hierarchy relationships (Parent, Descendant, Level 0, etc.) will dynamically build the latest metadata selection with each query launch, eliminating the risk of not submitting a driver value because an intersection was not displayed in a Smart View selection.

Queries can also be leveraged as data export mechanism for target systems. The .csv format extract at base-level or upper-level, in column format, can be consumed by most, if not all ETL tools.  There are certain restrictions with queries for data export such as number of records that can be extracted at one time as well as considerations with using dynamic member references. In such cases, the ASO Essbase reporting leading practices must be dusted off and put to good use. What is common sense in the ASO Essbase world should be a good benchmark in the PCM world as well.

Predefined queries are also a good use of resources when troubleshooting allocation results or analyzing data. While PCM queries do not have prebuilt intelligence capability to call out differences month-on-month – a feature that is present in Account Reconciliation Cloud Solution – they can support validation and troubleshooting efforts after the PCMCS allocation process is completed.

The “Out-of-the-Box” series is slowly closing the list of items available in the PCM Intelligence screens, but we are not done yet with all that PCM has to offer!

Keep a close eye on this space for future posts on Cloud Data Management, Model Validation, and Backup and Restore features within PCMCS.

For comments, questions or suggestions for future topics, please reach out to us at infosolutions@alithya.comSubscribe to receive notifications about new posts about Cloud updates and other Oracle Cloud Services such as Planning and Budgeting, Financial Consolidation, Account Reconciliation, and Enterprise Data Management.  Follow Alithya on social media for the latest information about EPM, ERP, and Analytics solutions to meet your business needs.

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Alithya’s PowerShell Accelerator for Ground-to-Cloud EPM

Oracle provides a powerful toolset for interaction with the EPM Suite through a set of REST APIs and a downloadable product called EPM Automate that provides for command line access to a significant portion of the REST APIs.  At many of our customers, we implement scripts to orchestrate and schedule processes.  These processes execute EPM jobs, transfer metadata and data to the EPM Suite, and download data from the EPM Suite.

We believe in standards to facilitate common implementations across our large customer base and to manage the evolving nature of Oracle’s EPM Suite.  Standardization improves our ability to support our customers, and we have taken steps to consolidate our scripting into a single preferred service accelerator that provides high-quality, implementation-proven script utilities in a packaged delivery.

When we started this effort, we established a set of criteria for what we wanted to accomplish:

  1. Provide scripts that work in either Windows or Linux environments.
  2. Apply scripting best practices in a packaged delivery.
  3. Improve quality, delivery performance, and supportability by having a set of scripted functions that are unit tested prior to first use at a customer.
  4. Provide a standard approach to setup of jobs including signing into EPM Automate.
  5. Provide a standard logging framework.
  6. Provide exception handling including emailing.
  7. Provide a standard approach to archival of transferred files.
  8. Provide a standard approach to post procedure clean-up of temporary files.
  9. Provide ability to run scripts individually and together.
  10. Allow the calling scripts to be easily readable.

Why PowerShell?

Establishing the programming language was foundational and involved conversations about batch, Bash and PowerShell.  Although each language has advantages and weaknesses, the Product team selected PowerShell for the following reasons:

  • Robust interpreted programming language that includes standard capabilities such as variable, functions, loops, exception handling, etc.
  • Native on Windows environments with a nice development environment, PowerShell-ISE.
  • Can invoke commands and batch scripts easily.
  • Intended future direction for Microsoft with strong on-line support.
  • Open-sourced and available on Linux, testing showed that little or no modification to scripts is required for use in Linux environments.

What are we Providing?  A Working Example

We provide a packaged set of utilities called EPMAutomatePowerShellUtilities as an accelerator to development of ground-to-cloud scripts.  EPM Automate is in the name because we primarily use EPM Automate to accomplish an action, but also use the REST APIs when EPM Automate does not provide the required action.

To highlight the accelerator, lets document a working example with a customer implementing a Profitability and Cost Modeling Cloud Service (PCMCS) solution.

Customer is providing dimensional data and content data files and needs the following actions:

  • Upload Dimensional Data and integrate into PCMCS
  • Upload Content Data and Run Allocations
  • Download Post Allocated Results
  • Run all the above as a Single Script

First, the Boiler Plate

All customer scripts have the following boiler plate to provide common behavior

try

{

  • $PSScriptRoot/config/properties.ps1
  • $epmautomatepowershellutilities/Utilities.ps1

    Pre-Job-Run $Profile

    #Place your actions here!

}

catch

{

    Email-Exception

}

finally

{

    Post-Job-Run

}

What is going on?

  • try … catch … finally – allows for exception handling and script resolution in a common pattern. Standardized exception handling improves the quality of the ETL process by ensuring that support personnel are notified via email for any process execution stoppage.
  • – $PSScriptRoot/config/properties.ps1 – loads the variables required to run the scripts. For example, we load $ApplicationName which is the PCMCS application with which we are working.  The properties.ps1 is a text file that requires very little maintenance after initial setup.
  • – $epmautomatepowershellutilities/Utilities.ps1 – loads all the custom functions we provide.
  • Pre-Job-Run $profile – sets up job and makes it ready to run including signing into EPM Automate.
  • #Place your actions here! – this is where the custom actions are placed. See Scripts 1, 2, 3, and 4 below for examples of custom actions.
  • Email-Exception – when an exception occurs, then email an error message including a zip of the temporary folder that contains process log and any other files that were created by custom actions.
  • Post-Job-Run – clean up after custom actions are complete by signing out of EPM Automate and optionally removing temporary folder (configurable).

Script 1: UploadDimensionData.ps1 – Upload Dimensional Data and Integrate into PCMCS

We won’t repeat the boiler plate and focus on the custom actions:

Upload-DimData-And-Load $ApplicationName “$inboxFolder\Dimensional Data”

Enable-App $ApplicationName

Deploy-Cube $ApplicationName -KeepData -RunNow

Readability is a huge factor here.  We really don’t need to explain what these custom actions are doing, but let’s highlight a couple of things.  First, the called function often looks a lot like a corresponding EPM Automate command; for example, “Enable-App” corresponds to the EPM Automate command “enableApp.”  Second, we provide more complex calling functions such as “Upload-DimData-And-Load” to perform a set of common actions that run multiple commands – in this case the upload of multiple files – and then run the loadDimData command for all the uploaded files.  Behind the scenes, an archive copy with a timestamp is placed in an archive folder for each of the uploaded files.

Script 2: UploadData.ps1 – Upload Content Data and Run Allocations

Again, without boiler plate:

Clear-POV $ApplicationName “VR_Working;SC_Forecast” -InputData -AllocatedValues -POVDelimiter “;”

Copy-POV $ApplicationName “NoVersion,SC_Forecast” “VR_Working,SC_Forecast” -isManageRule

Upload-Data-And-Load -ApplicationName $ApplicationName -Path “$inboxFolder\data” -DataLoadValue “OVERWRITE_EXISTING_VALUES”

Run-Calc -ApplicationName $ApplicationName -ModelPOV “VR_Working;SC_Forecast” -ExeType “ALL_RULES” -ClearCalculated -ExecuteCalculations -RunNow -isOptimizeReporting -POVDelimiter “;”

You’ll see a mix of EPM Automate analogs and a complex function that uploads all the content data and loads them into PCMCS.  Again, the archival of uploaded files occurs during the Upload-Data-And-Load function.

Script 3 – DownloadResults.ps1 – Download Post Allocated Results

The custom actions are:

Export-Query-Results $ApplicationName “PCMCSDataExport.txt” “Post_allocated”

Download-File “profitoutbox\PCMCSDataExport.txt”

Script 4 – JustDoIt.ps1 – Perform all Three Steps

The boiler plate is built so that the Pre-Job-Run, Email-Exception, and Post-Job-Run understand when they are inside a calling script.  This allows you to create a parent script to run multiple other scripts without modification of the called scripts.

Focusing on the custom actions:

. $PSScriptRoot\UploadDimensionData.ps1

. $PSScriptRoot\UploadData.ps1

. $PSScriptRoot\DownloadResults.ps1

In this parent script, EPM Automate is logged into a single time.  Any exception results in full stop and a single email sent with an integrated process log.

Final thoughts

The accelerator provides a high-quality framework allowing Alithya to focus on customer requirements and the actions needed to integrate with Oracle’s Cloud EPM suite.  The low level, expected behaviors, such as exception reporting, logging, emailing, and file archival are available on day 1 of the engagement.  With a focus on readability, these scripts are easily transferred to the support organization for long-term sustainability.

For long-term support, the customer can update the REST API version via the properties.ps1 file, and Oracle is providing EPM Automate updates that do not break prior scripts.  If EPM Automate has a breaking change, the customer can update the utilities themselves or request an updated set from Alithya.  Feedback from our customer base is positive with specific comments about the readability of the utilities and quality of initial deployment.

Overall, the accelerator is reducing the effort and time to deploy ground-to-cloud processes while improving the quality of deployment by reducing the time spent creating and debugging scripts.

Additionally, long-term support costs are lower through standardization of implementation patterns that allow support personnel to focus on what the script is accomplishing rather than how it is accomplishing it.

For comments, questions or suggestions for future topics, please reach out to us at infosolutions@alithya.comSubscribe to receive notifications about new posts about Cloud updates and other Oracle Cloud Services such as Planning and Budgeting, Financial Consolidation, Account Reconciliation, and Enterprise Data Management.  Follow Alithya on social media for the latest information about EPM, ERP, and Analytics solutions to meet your business needs.

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Alithya Leverages the Power of Oracle Hyperion FDMEE

One of the biggest challenges of every organization nowadays is to provide reliable data for a clear business outlook. This essential activity is more critical than ever now that the solutions for hosting data are increasingly varied, with multiple scenarios involving on-site hosting, Cloud, and hybrid solutions. However, there are solutions that allow companies to efficiently and seamlessly navigate amongst the different hosting solutions. Alithya Group (NASDAQ: ALYA, TSX: ALYA) (“Alithya”) is well positioned to advise its clients on this topic.

Efficient management of data requires solid know-how.

As companies attempt to develop long-term guidance in this area, Alithya ensures that its clients’ data hosted in different environments continue to be used effectively. Alithya’s Data Governance and Integration practice includes specialists in Data Integration to help free up resources leveraging FDMEE for data validation and to maximize FDMEE with its offering for financial data application review.

Alithya’s Tony Scalese published a book providing deeper understanding of FDMEE.

Banking on the numerous mandates Alithya Group has been entrusted by its clients as a market-leading provider of Oracle Enterprise Performance Management Platform solutions, the company leverages the power of Oracle Hyperion Financial Data Quality Management, Enterprise Edition (FDMEE) to help organizations enhance the quality of internal controls and reporting processes. The extensive Alithya team specializing in these FDMEE solutions has among its ranks a widely recognized expert in the market, Tony Scalese, VP of Technology at Alithya and Oracle ACE, who published The Definitive Guide to Oracle FDMEE [Second Edition], in May 2019.

Connecting current on-premise and future Cloud solutions.

“As thought leaders, we are committed to providing essential resources to help clients enhance the quality of internal controls and reporting processes,” stated Chris Churchill, Senior Vice President at Alithya. “Our Data Governance and Integration practice aligns offerings with best practices and includes a team of dedicated experts as well as some of the most comprehensive resources in the industry.”

Sharing real-world FDMEE deployment strategies.

It is the great interest of Tony Scalese for the integration of data and the sharing of his great knowledge with a maximum of interested parties that led him to publish books on Oracle FDMEE. After a first edition that was very successful in 2016, he just launched the second edition of The Definitive Guide to Oracle FDMEE. Since many organizations are now considering or have begun migrating to the Cloud, the book provides a deeper understanding of FDMEE by informing readers about such topics as batch automation, Cloud & hybrid integration, and data synchronization between EPM products.

“FDMEE can integrate not only with on-premise applications, but also Oracle EPM Software as a Service (SaaS) Cloud Service offering,” says Tony. “It provides the foundation for Cloud Data Management and Integrations which are embedded in each of the EPM Cloud Services.  A deep understanding of FDMEE ensures that integrations built on-premise or in the Cloud function well and stand the test of time.”

Out-of-the-Box Features: Profitability and Cost Management Cloud Service (PCMCS) – Intelligence and Dashboarding: Traceability

Traceability is the buzz word in any regulated industry. Being able to prove the numbers is crucial to all businesses, but it can be very time consuming and complex for companies that operate across multiple and diverse lines of business with a large pool of Channels, Services, Customers or Products. Shared Services implementations require a clear understanding of the flow of costs.

Where is this cost coming from?

Why have I been charged so much more this month for the same service compared to last month ?

These questions should be easy to answer. Unfortunately, not all profitability analysis technologies are able to support a quick turnaround for providing the required level of detail.

PCMCS has more than one option to easily provide much-needed answers.

The Rule Balancing report is one of numerous out-of-the-box (OOTB) features included with an Oracle Cloud Service subscription able to support data traceability and transparency. For more details about the type of information the report provides and to learn the ease with which it can be set up for your application, review this comprehensive blog post.

Besides Rule Balancing reports, PCMCS OOTB features support transparency within allocations and/or profitability models with Traceability maps.

The focus of the current post is how to access, build, and use Traceability maps.

The order in which I am covering the PCMCS OOTB features is directly related to the Intelligence menu options available in PCMCS.  As a recap, the 6 menu options are listed below:

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 1  1.  Analysis Views (How to create them, customize them and use them here)

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 2  2.  Scatter Analysis (Setup and configuration covered here)

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 3  3.  Profit Curves (Usage and features covered here)

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 4  4.  Traceability

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 5  5.  Queries

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 6  6.  Key Performance Indicators

The contents of this blog are based on the standard Bikes (BkML30) demo application, so you can follow the step-by-step details without having to go through an app setup from scratch. You can load and deploy this application directly from your PCMCS Instance through a couple of clicks via the Application menu using the + / Create button.

Traceability – Intro

The traceability maps, whether in PCMCS or in on-premise HPCM, allow users to graphically visualize the allocation flow. A chosen business segment can be traced through the allocation steps, either backwards or forwards, starting from a predefined point. Images  make up the map of a data point either flowing into the selection of members chosen by an end user to troubleshoot or flowing out of that selection into subsequent allocation steps.

Alex Mlynarzek - Traceability - 5-21-19 - Image 1

Alex Mlynarzek - Traceability - 5-21-19 - Image 2

Traceability is a great tool for troubleshooting specific intersections of detailed data such as base level accounts against a specific department. However, when there is a need to identify patterns or troubleshoot allocation results at a higher level, the Standard Profitability (the first on-premise version of the Profitability module) Traceability maps are not geared to handle such requests. In order to perform a high-level analysis in Standard Profitability models, users would have to revert to Smart View or Financial Reports.

Being able to trace data at a summarized level of detail is the key difference between traceability in Management Ledger applications and traceability in Standard Profitability. Management Ledger allows end users to select the level within the hierarchy where they desire to launch or generate traceability, whether base level or otherwise.

Traceability – Setup

The starting point of any traceability map in Management Ledger is Model Views.  If you are interested in learning how to build and use Model Views, spend a few minutes reviewing this prior post.

List of steps necessary to launch a traceability report in Management Ledger applications:

  1. Select a valid Point Of View (POV). The POV must contain data in order to display any traceability results.
  2. Choose a prebuilt Model View – example: IT Support Activities.
  3. Select a tracing dimension which will represent the detail that is the focus of your analysis (Accounts, Departments, Entities, Business Units, Segments, etc). The selected tracing dimension determines the focus or scope of your analysis and will be the one dimension that is displayed at base level detail or any other generation within the hierarchy.
  4. Trace Forward and Use Generation Selection boxes are selected by default.  Not selecting “Trace Forward” allows users to perform a “Trace Backward” action; in other words, figure out how the model arrived at a data value for a selected intersection, rather than how a data value was allocated out from that intersection to other recipienAlex Mlynarzek - Traceability - 5-21-19 - Image 3

A report with the “Use Generation Selection” filter disabled will display the data at the base level for the Trace Dimension (in this example, Entity).

Note: If a message is received indicating the Flash Player version is not up-to-date, check that pop-ups are enabled on the page to allow the download of the required update.

Alex Mlynarzek - Traceability - 5-21-19 - Image 4

Alex Mlynarzek - Traceability - 5-21-19 - Image 5

If the traceability report does not generate any results, check that the allocation rules were successfully completed for the referenced POV. Alternatively, if the POV calculated is successful, but data is not displaying on the Trace Screen, check that the application variables are correctly setup for Current Year, Period, and Scenario. Also ensure the Account dimension maps are specified in the Dimension Settings screen.

Traceability – Display Options and Filters

Traceability screens have 5 display options:

  1. Vertical (Top Down)
  2. Horizontal (Left to Right)
  3. Tree
  4. Radial
  5. Circle

Within the traceability analysis, users can focus on a single rule. The tracing dimension in the previous example is Entity. The tracing dimension is the focus of the traceability reports – following how data was allocated into or out of a base level Entity.

Alex Mlynarzek - Traceability - 5-21-19 - Image 6

To isolate a specific rule and separate it in a standalone diagram, click Shift+Enter or select the graphical option on the top of the Rule ID box.

Alex Mlynarzek - Traceability - 5-21-19 - Image 7

End users have the choice of displaying the aliases/descriptions of the Entities rather than the code member names. If aliases have not been uploaded in the metadata of the application, then the report will still reference the member name codes, regardless of this choice.

The following traceability report will display how operating expenses are reallocated /redistributed from each support entity (like IT, Facilities, IT, etc.) to the production entities using predefined driver configurations referenced in the Rule box.

Alex Mlynarzek - Traceability - 5-21-19 - Image 8

Select the “Trace Forward” filter and keep constant all other prior selections in the initial traceability screen to display IT Support Activity charge out.

Alex Mlynarzek - Traceability - 5-21-19 - Image 9

The “forward tracing” of IT allocations represents how data is allocated out to consuming departments such as Finance, Marketing, Outside Sales, Assembly, etc.  Remember the focus of the trace screen depends on the “Tracing dimension” selected. In this example, Entity was the tracing dimension.

The top box, R0009, shows us the Rule Name relevant for IT allocations, the ruleset reference, the Driver used to allocate data to Targets – in this case : Desktop Laptop Users, regardless of Activity performed (NoActivity reference) as well as the amount / dollar value of the allocation : Allocation Out 1.338.000.

Users have the flexibility to allocate data partially (to allocate only a % of the total value instead of 100%). That is what the Contribution % reference in the R0009 box represents. In this rule, the administrator/rule designer decided to fully allocate the IT cost to the consuming department instead of allocating it partially. Therefore, the 100% reference is displayed.

In the case of the Bikes ML (Management Ledger) application, the Entity dimension has 4 generations. When talking about generations, the larger number, in this case number 4, represents the lowest level of detail. Generation 0 represents the Dimension name; Generation 1 represents the first set of children; Generation 2 represents the Children of Children, etc.

Below is a radial display of the contribution charge out at base Entity level when no generation selection was made prior to launching the traceability report:

Alex Mlynarzek - Traceability - 5-21-19 - Image 10

We can see in this diagram how much each Target Department was charged for their IT bill.  The contribution from the IT department to each target is displayed as a %.

Change the generation reference from 4 to 3. The higher the number of the generation, the more summarized the detail. The change of Generation reference will result in a summarization of the members of the Entity dimension to one level higher than seen previously.

Alex Mlynarzek - Traceability - 5-21-19 - Image 11

Notice how there is no longer an Entity breakdown at base level as we had in the previous screen when Generation 4 was selected, and the contribution percentages have been summarized to display the contribution % at a node level.

In situations where a dimension has many levels within the hierarchies or an increased volume of base level members, the generation selection proves useful as it allows users to group data sets and display them in the same diagram without compromising the level of detail.

Traceability – Customization

As mentioned at the beginning of this post, PCMCS comes with several features to support traceability and troubleshooting, one of these features being the Rule Balancing report. In situations where the traceability maps are insufficient to support a meaningful conversation regarding bill out values, and a deeper dive into an individual rule is necessary, the Rule Balancing report covers such a request.

While the traceability report has evolved in comparison to the Standard Profitability model, its usage is limited to situations where there is a need to troubleshoot specific data points while also having a visual representation as support.

The most common alternative to graphical traceability reports are ad hoc reports in Smart View, either built from scratch or launched via the Rule Balancing report (described in detail in a previous post).

Conclusion on OOTB features: Traceability

Business segment profitability analysis represents the analysis of operations and profitability of individual segments (e.g. Lines of Business, Products, Channels, Customers, Services) within a company. Business segment reporting requires all costs to be divided into one of the two categories:  direct /traceable costs or indirect/nontraceable costs.

In PCMCS, all costs are transparent and fully traceable. An indirect cost value can easily be traced throughout the flow of the allocation model all the way down to the business segment being analyzed. The indirect allocated volume can be explained through step-by-step analysis, high level traceability maps, and OOTB reports listing out the rules impacting the distribution of such cost.

Using a combination of Model Views, Rule Balancing reports combined with Traceability analysis and Smart View ad hoc retrievals, there should be no doubt regarding the source of a data value within PCMCS. Metric data validation – situations where the intersections for each metric are customized to such extent that building a Rule Balancing report or an individual Model View is not efficient nor effective – is mostly performed via Smart View.

In a nutshell, traceability provides significant benefits:

  • users can trace both revenue and cost based on predefined model views.
  • traceability can flow forward or backward from a starting point.
  • users can review the final contribution % (driver details are not displayed on this screen).
  • users can toggle between different display options and focus on specific rules for focused analysis.

Subscribe to our mailing list to receive updates for new blog posts related to PCMCS Queries, KPIs, Model Validation, System Reports, Data Integration using Cloud Data Management, as well as the OOTB Application Backup and Restore functionality.

Is there a PCMCS-related topic that you would like to see covered in more depth?  Email us at infoSolutions@alithya.com.

Out-of-the-Box Features: Profitability and Cost Management Cloud Service (PCMCS) – Intelligence and Dashboarding: Profit Curves

Welcome back to this series of blog posts to cover out-of-the-box (OOTB) features of Profitability and Cost management Cloud Service (PCMCS). There is a need within the Oracle Cloud client community to discover what can be achieved with the tools provided when subscribing to one or more Oracle Cloud Services. A lack of awareness of the features included with your subscription is an unmeasured cost and a missed opportunity to gain much needed insight without further spend.

PCMCS applications – whether built for Fully Allocated P&L Solutions, Transfer Pricing, Shared Services Allocations or Customer/Product Profitability – have OOTB reporting capabilities available via the Intelligence menu that offer insight into allocation models with reduced effort. Here, we’ll explore how to set up, configure, and use such features and fully leverage the functionality that is included in the Oracle Cloud subscription cost.

The order in which I am covering the OOTB features is directly related to the Intelligence menu options available in PCMCS.  The 6 menu options are:

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 1  1.  Analysis Views (learn how to create, customize, and use them here)

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 2  2.  Scatter Analysis (discover how to set up and configure them here)

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 3  3.  Profit Curves (this blog post focuses on Profit Curves)

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 4  4.  Traceability

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 5  5.  Queries

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 6  6.  Key Performance Indicators

The content of this blog is based on the standard Bikes (BkML30) demo application, so you can follow the step-by-step information without having to go through an app setup from scratch. You can load and deploy this application directly from your PCMCS instance through a couple of clicks via the Application menu using the + / Create button.

 

Profit Curves – What Are They?

If you are looking for a graphical representation for the concentration of your profit by either Customer, Products, Channels, or Funds, look no further than the Profit Curves section in PCMCS. Profit Curves, also referred to as Whale Curves, are used to identify which cluster of Customers, Channels, or Products generate the most profit. Profit Curves display a graphical representation of the relationship between economic profit and the quantity of output sold.

The details of the profit or net income split by unit/service/customer displayed in a Profit Curve identify issues with:

  • expansion of a production line
  • breadth of services that may have a negative impact on profit
  • onerous clients consuming numerous resources without justifying the cost for the profit gained from their engagement
  • potential costing issues of “over” or “under” costing products (for example, overburdening a product or product line inappropriately);  a cost study should be performed to determine the appropriate allocation
  • pricing

Information illustrated with a Profit Curve can be enlightening and help to put the focus on specific customers, products, or channels where the greatest profit attention is needed, indicating situations where a few products, services, or clients create enough profit to maintain the rest of the company’s offering. Profit Curves are key to strategic decision making, especially when dealing with competing projects and limited resources.

During one of my recent PCMCS implementations, a Profit Curve proved valuable when the client’s staple product, advocated as being its best and most profitable, was discovered to be the least profitable after the implementation of an accurate cost allocation methodology in PCM!

The easy-to-follow Profit Curve provides the foundational insight needed to rapidly shift gears across product lines, ensuring alignment of management decisions backed up by real information.

 

Building a Profit Curve

There are several Profit Curves available in the Demo application BksML30. In order to build a Profit Curve, there must be a corresponding Analysis View that can be leveraged as the basis for data selection. See a step-by-step guide on how to build an Analysis View here.

Analysis Views can contain multiple references to Measures and/or Accounts; however, the Profit Curve using the Views analyzes and displays only one measure at a time.  Users can choose to define names for the X and Y axis to add clarity to the Profit Curve information consumers.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 1.png

Here is an example of a Profit Curve:

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 2

The curve displays a listing of Net Income generated by Customer.

From a Quarter-to-Date perspective (the Period selected at the top of the View), this Profit Curve indicates that all customers are profitable.  That may raise questions about whether or not the overhead is allocated appropriately or an even spread is used, thus skewing the results.

Note: Data in the BksML30 model at the time this Profit Curve was generated was calculated only for January, confirming the Profit Curve display, as the profit by customer distribution was evened out at Quarter-to-Date level.

The details of each customer/product/channel/segment and how much net income each is generating can be reviewed in the Category Analysis section. From a cost management and process improvement point of view, the right side is the most important.  This side generally represents customers/products/channels with a negative profit or that cost the company money.  While these customers/products/channels can’t always be eliminated, they can be watched and reviewed for pricing changes.

Using a PCMCS Profit Curve

There are options to filter data by the POV dimension, Period, or by metrics tied to Customers. For example, we can exclude from the analysis any Customers with Operating Expenses that are considered marginal. After defining the required filters, we can refresh the Profit Curve and review the newly generated pie charts.  Filters can be added to all available metrics and can be stacked up to generate any custom report.

Below is an example of the same “All Customers” Profit curve, limited to January and with a selection of all Customers who had a Net Income smaller than 1 positive unit (USD or the currency defined in the PCM model) thereby highlighting Customers creating losses.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 3

In the Details section of the Profit Curve, there is a count of 886 customers with a Net Income smaller than 1.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 4100% of the customers analyzed based on the specified criteria are unprofitable. The “Actual Profit” in this Details section can be translated into “Actual Loss” as the total accumulated value across the 886 customers is US$ -1,148,670.

If there are doubts regarding the data intersection for the remaining dimensions in the PCM model such as Product or Entity, we can analyze related information through the configuration icon located next to the “Add Filter” menu. These selections are predefined in the Analysis View that was used during the creation of the Profit Curve, and you will not be able to modify them unless you modify the underlying View.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 5

If questions are raised during the analysis on the Profit Curve screen and a list of details by Customer is requested, we have the option to launch a report from the “Analysis Links” menu under the Category section.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 6

A report in the following format will be generated to display the Customer detail records along with all the other settings defined in the Analysis View.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 7

This report can be exported in .xls format (“Export to Excel” option), and it represents a base level data dump report, in column format, containing multiple generations and references to attribute dimensions.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 8

Note: When launching this report, users must check that the parameters have transitioned correctly from the previous screen. The Period parameter, which is saved to be Quarter-to-Date on the original Analysis View used in the Profit Curve diagram, will override any other selection made during run time analysis. If there is a need to revert to a specific month before launching the Export to Excel, users will have to make this update on the Filter /POV area and perform a data Refresh.

We can make changes to the Analysis View to add further details (for example, Cost of Goods).

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 9

For the 886 customers that are not profitable, we can dive deeper into their Cost of Goods data, Operating Expenses, or analyze whether or not the products sold are so heavily discounted that they no longer generate a margin.

 

Pie Charts Related to PCM Profit Curves

 

We can further analyze the resulting Profit Curve data by using the available predefined categories tied to the Attribute dimensions available in the PCMCS application, in the underlying Analysis View displayed in the adjacent Pie Chart.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 10

The available categories to display the Pie Chart data for the Profit Curve chosen are the following:

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 11

When selecting the Region category/attribute, we learn that the Southeast area contains 26,07% of all the unprofitable customers.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 12

If we change the Focus of the Category to be on Top 10% most unprofitable customers by Amount vs. All Customers/Number of Customers, the following information is displayed:

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 13
Alex Mlynarzek - Profit Curves - 4-18-19 - Image 14

The Pie Chart reveals that the Southeast region has the highest number of unprofitable customers both by Number of Customers as well as by Total Amount/Loss.

When adding a filter based on Customer Generation 3 which distinguishes between Department Stores and Specialty Retailers, it looks like 87.64% of the Top 10% most unprofitable customers are from Department Stores.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 15

A look at the 4th generation in the Customer dimension where we can analyze the split of the losses at Customer level indicates that one store is responsible with 65.17% of all losses within the top 10% most unprofitable Customers.

Alex Mlynarzek - Profit Curves - 4-18-19 - Image 16The Pie Chart is the only artifact that is refreshed based on the selections of the Category Analysis menu while the Profit Curve remains constant based on the selections in the POV and filter criteria.

While all users of PCMCS can generate/launch Profit Curve reports and export their associated Analysis Views, in order to create and set up a Profit Curve report, the PCMCS administrator must update the requesting user’s permissions. As with all Intelligence screens within PCMCS, the Viewer role allows the use of these artifacts, not its creation or setup.

Concluding Thoughts About OOTB Features: Profit Curves

If you have been following the posts in this blog series, you’ve become aware of the dashboarding opportunities at your disposal with a PCM subscription. The listing of PCMCS OOTB features is a good starting point for comparing any other profitability and cost management tools on the market, regardless of vendor and technology employed.

Creating insightful dashboards is now at the tips of end users’ fingers, no longer involving complex requirements gathering processes and iterating between different display options. PCMCS users have the ability to build and customize their own dashboards. As a result, IT staff is no longer burdened with reporting requests or artifact migration between environments.

Subscribe to our mailing list for updates on the next blog post covering Traceability, Queries, and KPIs. Don’t think the PCMCS OOTB features blog series will stop at the Intelligence menu options! There is more to come on Model Validation, System Reports used for maintenance and troubleshooting, Integration with Cloud Data Management, and the Application Backup and Restore functionality. All this and more will be covered in future blog posts, so watch this space for updates.  If there is a PCMCS-related topic that you would like to see covered in more depth, email us at infosolutions@alithya.com.

Out-of-the-Box Features: Profitability and Cost Management Cloud Service (PCMCS) – Intelligence and Dashboarding: Analysis Views and Scatter Analysis

PCMCS Out-of-the-Box (OOTB) Features:  2. Intelligence and Dashboarding – Analysis Views and Scatter Analysis

Two teams of consultants with similar amounts of experience and prestige guarantee that they can perform an application implementation to the highest quality: one at a higher cost, but shorter timeframe; and the other at a lower cost, but in a longer timeframe?  All other considerations being equal, should I save money, or should I save time?

A few days ago, I released my first blog post on PCMCS, covering Rule Balancing reports usage and customization. This post builds on that first post to cover intelligence capabilities, some of which are only available in the Cloud version of the PCM software.

There are 6 menu options when accessing the Intelligence menu within PCMCS.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 1  1.  Analysis Views

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 2  2.  Scatter Analysis

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 3  3.  Profit Curves

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 4  4.  Traceability

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 5  5.  Queries

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 6  6.  Key Performance Indicators

This post covers the first two menu options to explain how to set up Analysis Views and how to use Scatter Analysis.

Analysis Views

Analysis Views are the first set of reports available to end users within the PCMCS user interface.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 7

These views represent a way to predefine and save intersections of members for future review.  The selections within Analysis Views are open to all dimensions within the PCMCS application at various levels within the hierarchies. This is the first step you need to take towards building or defining a dashboard for your PCMCS application.

If you cannot create or edit an analysis view, then you need to reach out to your PCMCS administrator in order to review and adjust your security settings.

The example Analysis Views for this post are based on the “Demo Bikes” application that can be deployed with a few clicks in your PCMCS instance BksML30.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 8

A data slice is a combination of rows and columns along with the page selection, which, in this case, is the Period dimension.

Any dimension that is not specified in any of the 3 areas (row, column, page) will be read at top level and will be displayed in the settings menu.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 9

The Add Filter section allows you to filter the columns based on specific numerical values. In this case, the columns are represented by the Product dimension selections.

To create an analysis view, click on the plus (+) sign on the main menu. The three tabs displayed will allow you to define a name and description as well as the setup for row and column dimensions. You cannot select more than a dimension for either rows or columns.

Within the Row dimension selection, you can leverage different formulas applicable to the hierarchies within PCM such as Children of member, Member and children, Level 0 descendants, etc.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 10

Columns do not have options for member formulas beyond the usage of User preferences.

The row dimension will allow you to display further information such as generation or level details. For example, for the Product dimension, we can display the generation 3 and 4 information alongside the level 0 members, allowing us to expand our analysis to different product categories, or types.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 11

Selecting new members within the Analysis Views will not impact the original data definition. If you choose to display data for any month other than the one that was setup and saved in the Analysis view, you can do so because the Page parameter is open to end user modifications. If; however, you want to update and store a selection change within the analysis view, you must perform such update via the Edit menu instead of simply selecting a new parameter on the screen in view mode.

You may need to utilize the concept of period ranges when using Analysis Views in order to dynamically reference specific members of your Period dimension.

Defining a current period for the application is mandatory in order to be able to create formulas dependent on time. This action is available via the Application menu by selecting the Edit application option and navigating to the tab called Dimension settings. Here is where you can define the current Period and the Current Year for your PCMCS application.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 13

These settings will be applied when using the “Single…” or “Current” selection options within Analysis Views. Single (-1) Level 0 selection represents, in this case, the month of May, since the current Period selection for the PCMCS application is June. The Single (-1) Level 1 selections return Q1, since June is in Q2.

Scatter Analysis

Scatter Analysis graphs will compare one member’s values against another member’s values. The two members selected must be within the same dimension. Your PCMCS Demo application may not have any sample Scatter Analysis graphs. However, you can create one by leveraging the Analysis Views at your disposal.

You can launch Analysis Views from within Scatter graphs.

Note that saved Scatter Analysis cannot be reused or referenced in dashboards. You should use this section to create graphs for ad-hoc use outside of the dashboarding capability.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 14

If you need to include Scatter Analysis within your dashboards, you will have a corresponding menu item that allows you to create dashboards within the list of available items.

You can select an existing Analysis view, but you must reselect your X-axis and Y-axis dimension references.

Alex Mlynarzek - Analysis Views and Scatter Analysis - 2-28-19 - Image 15

Conclusion:  PCMCS Intelligence – Analysis Views and Scatter Analysis

While there are many alternative reporting solutions to use in conjunction with PCMCS applications, assuming that both time and money are of essence in any project implementation, it is safe to conclude that using the PCMCS OOTB reporting features would be cost effective as well as efficient. The Intelligence screens shared in this post are included in the PCMCS subscription cost, and any end user of a PCMCS application with the right level of access can take charge and build the desired reports, saving end users in a location accessible to their peers while spending no time in iterations of reporting requirements and data validations.

The PCMCS OOTB reporting features support not only troubleshooting, but also detailed analysis and reporting within one screen.  Such capabilities should not be ignored as they will surely add meaningful insight into finance teams’ day-to-day use of PCMCS.

If you need advice and guidance on how to leverage the PCMCS reporting capabilities for existing or future applications, reach out to our team of PCMCS experts at infosolutions@alithya.com.

The remaining intelligence menus will be covered in subsequent posts over the next few weeks. If you are interested in receiving notifications of such posts, subscribe to notifications.

Out-of-the-Box Features: Profitability and Cost Management Cloud Service (PCMCS) – Rule Balancing Reports

PCMCS Out-of-the-Box (OOTB) Features:  1. Rule Balancing Reports

The other day, I was thinking about the times I used to study Finance, and specifically about a course regarding Interest and how it represents the value of Time. What is the cost, or value, of one’s time? – is it high, resulting in a higher interest rate per period, or is it low, resulting in a low interest rate per period? How much time am I willing to spend working in order to get that new car? How much time do I have before that competitor will outrun me and snatch that market share from me?

This was how I started thinking about various out-of-the-box features (OOTB). Such features are often key in deciding whether to acquire a software/service/product because the one resource that we constantly complain about not having enough of is “time.”

You are now reading the first blog post on OOTB features in PCMCS covering one of the most used Reports for data analysis as well as troubleshooting profitability calculation results. At the end of this blog post, you should know what Balancing reports are, where to find them, how to use them, and also how to further expand them with minimal time and effort invested.

What are Rule Balancing Reports?

Rule Balancing reports provide quick insight into the validity of the application results. These reports are powerful OOTB artifacts that can be further configured to cater to any custom application requirements in order to support validation of calculation results as well as contribution analysis and traceability.

The PCMCS OOTB Rule balancing report is initially based on a Default Model View with a standard selection of upper level members for each dimension. Starting from this Default Model View, the administrators or users of the PCMCS applications can perform a deep dive analysis on more granular intersections and configure detailed reports for a ruleset or a group of rulesets they choose to investigate.

The Default Rule Balancing report is available as soon as the application has been deployed, and it can be accessed via the Main Navigator menu found under the Manage section.

Alex Mlynarzek - PCM Rule Balancing - 2-7-19 - Image 1I will be using the default BikesML30 application to demonstrate the capabilities of the Rule Balancing reports. If you have loaded your sample application and cannot see any results in the Rule Balancing reports, check that you ran your end-to-end calculations for any given POV from the Manage Calculation Menu. The POV I have chosen for this demonstration is FY16, January, Actual Scenario.

As you open the Rule Balancing menu, the Default Model View is the only view available when you initially set up your application and your allocation rules. Any other Rule Validation reports that you see within the Demo application besides the Default Model View have been built and configured outside of the out-of-the-box list of features.

What are PCMCS Model Views?

A Model View represents a predefined data slice within the PCMCS application; consider the model views as a set of selections of members for each dimension that displays only the relevant data points for a required intersection.

Rule Balancing Report Example

After running the entire set of allocation rules within the Demo BksML30 application, the Rule Balancing report should look like this:

Alex Mlynarzek - PCM Rule Balancing - 2-7-19 - Image 2

The description of each rule selected will be displayed along with the rule number. The rules will be displayed in the order that they were launched following the user-defined sequencing, regardless of the actual Rule Number/Rule ID that has been assigned.

  • The “Input” column enables users to confirm that what was loaded into the application matches the expected values received from the source system.
  • The Allocation In and Allocation Out columns validate the allocations performed by the application from both a balance perspective (Allocation In should be equal and opposite to Allocation Out) and a numeric one.  The balance aspect is particularly of interest when allocations are executed with custom calculation rules.  In these cases, two separate rules are typically required, one for the “credit out” and one for the “debit in.”  As such, there is a greater risk that the formulas for the outbound and inbound values will not produce amounts equal and opposite in total, thereby causing an undesired imbalance.  In these situations, the Allocation In and Allocation Out values are shown on two separate rows, and they quickly illustrate to the user the success of their calculations.

Rule Balancing and Smart View Ad Hoc Reports

Any highlighted data point/data value in the Balancing screen will allow you to further investigate the allocation step through a Smart View ad hoc report. These hyperlinks represent pre-built/pre-defined queries that point directly to the Essbase database, allowing you to further expand the analysis of a selected data point.

Alex Mlynarzek - PCM Rule Balancing - 2-7-19 - Image 3

When you click on the highlighted number, a Smart View link will be downloaded to your workstation.

As an example, you can see how the detail for Net Change looks like for the Custom calculation rule R0001 – Utilities Expense Adjustment in a Linked report in Smart View.

Alex Mlynarzek - PCM Rule Balancing - 2-7-19 - Image 4

The column headers for the Rule Balancing report will list the relevant Balance dimension members. If there are members that are not populated, these will be automatically filtered out of the view. You can choose to display them by selecting View -> Columns and tagging the members you would like to display on your report – whether they have data or not.

Alex Mlynarzek - PCM Rule Balancing - 2-7-19 - Image 5

For further information on what each of these Balance dimension members represent, check out my blog post on Demystifying the Balance dimension in PCMCS.

You can view and edit the model view definition in the collapsed area between the POV and the Balancing report.

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The Input data on this customized Model View is pertinent only to Operating Expenses rather than the entire pool of data. This is the reason that the total USD value may be different from data displayed on the Default Model View report.

You can perform ad hoc edits to the Model View as you are using it, but none of the newly made selections will be stored. If you want to apply permanent changes to a specific Model View selection, you will have to edit the Model View in the corresponding menu.

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Your Model Views can be defined in the same order of operations as your allocations, or you can choose to create Model Views that are more detailed and dive deeper into a custom grouping of rules, regardless of the ruleset to which they might belong. The only dimensions displayed in your Model View selection are the Business dimensions. POV, Balance, Rule, and Attribute dimensions are not represented and therefore are not open for selection. The data points you define in the Model view will apply to all relevant rules IDs that generated the new cells.

Enhancing and Customizing Your Rule Balancing Reports

In the Demo BikesML30 application, there are several standard Rule Balancing reports that are split by Ruleset while others are named “Trace.” The Trace Model views are built in order to support point troubleshooting of allocation areas that are either complex or open to high variation during each run.

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If you want to use the Rule Balancing report values outside of the ad hoc capacity, you can export the report into XLS, but remember that such an export will not represent a Smart View report – it will simply be a listing of the information presented on the Rule Balancing screen, as some members displayed here do not have a direct equivalent in the application (Running Remainder, Running Balance). This export option can be found in the Actions menu, export to Excel, or by selecting the button in the below screen capture.

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A new workbook is downloaded called RuleBalance, and the entire set of data displayed on your screen will be available in XLS.

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PCMCS Rule Balancing Drawbacks

Rule Balancing does not allow filtering based on Attributes, UDAs, or Names.

Rule Balancing hyperlinks open SmartView tabs called Linked View, and any new selections of links within the Rule Balancing report will overwrite the contents of the existing tab. If you start developing a report by using Rule Balancing, remember to always rename the tab in case you want to kick off another report for a secondary data point within the same workbook.

Common Issues When Using Rule Balancing Reports

“Rule Balancing Report Links Don’t Work”

Your workstation must have Smart View installed before using the hyperlink feature within PCMCS. The latest Smart View version is available for download through the Navigator main menu under the Installations section.  For more guidance on generic EPM product patching, read the blog post Patch Today! Don’t Delay!

When selecting a hyperlink in the Rule Balancing report, you should be able to see that a download has started. As you click on the downloaded content, a new Excel tab will open, and you will be prompted to enter your Cloud credentials in order to have access to the requested data point intersections. If you do not have Excel open at the time you are accessing the downloaded content, the prompt to enter your Cloud credentials may not appear on the screen.

“I Can’t See Any Data in the PCMCS Rule Balancing Report.”

If data is not displayed on the screen, you are looking at one of the following situations:

  1. There is no data loaded and/or calculated for the POV at the intersections you have defined in the Rule Balancing report. Check your job console to see if such tasks have been triggered and completed successfully.
  2. Your security setup is restricting you from seeing any data values. Reach out to your administrator to adjust data grants or application access.
  3. (This used to happen occasionally during on-premise implementations) If your Business dimensions are tagged as Label Only, check that the first child contains values. You may be able to see data at base level intersections within your application, yet the Rule Balancing report shows no vales due to the Dimension Type, Member Storage, or Aggregation operators you have defined in the metadata.

“I Can’t Create a PCMCS Model View.”

This restriction is based on provisioning. Reach out to your PCMCS Administrator for assistance with your profile or settings.

Rule Balancing Wrap Up

Rule Balancing reports are easy to set up and use.  They retrieve data quickly, are accessible to all application users through the same menu, and they should be the first stop during a model run to quickly identify if there were any issues with data allocations.

Because Rule Balancing is a fast reporting tool with a predefined template OOTB, it is one of the commonly used troubleshooting reports for PCMCS, which can be leveraged for quick balance checks. It is also a mechanism for quick report building at detailed Rule level, a faster alternative to reading the Rule definition and manually replicating the intersections in a Smart View report.   Because these reports are system generated and their hyperlinks are based on application and rules set-up, there is no room for manual errors when building validations.

Save precious time by leveraging the PCMCS OOTB functionality. The next post in this series covers Intelligence screens – Analysis Views and Scatter Analysis.  If you have further questions on the usage of Balancing Reports within PCMCS, please reach out to our team of PCMCS experts at infosolutions@alithya.com.

Implementing Zero Based Budgeting: Setting Up Your Environment

The previous post – Implementing Zero-Based Budgeting: The Requirements – outlined two key components of a successful zero-based budgeting program:  a culture change and a centralized system. We recommended creating a centralized system with Oracle Planning and Budgeting Cloud Service (PBCS)/Enterprise Plainning and Budgeting Cloud Service (EPBCS) because of the many advantages it provides such as an environment with data depth.

Even with a zero-based budgeting blueprint, many companies are still hesitant to go “all in” thinking that a zero-based budgeting program implementation requires too much time and resources. The introduction of Cloud services such as Oracle PBCS/EPBCS makes the implementation of a centralized financial system easier than ever, greatly reducing the barrier to entry.

This final post in this series shares the power of a PBCS/EPBCS environment to achieve the greatest success with a newly implemented zero-based budgeting program.

How Can PBCS/EPBCS Environments Enhance the ZBB Experience?

There are four key ways to gain the most from a PBCS or EPBCS environment, including the setup of targets and accountability metrics that offer more meaningful data and greater transparency when making budgeting decisions.

Clients are often given target settings goals in management meetings or over the phone, but we demonstrate for them how to integrate this into their budgeting systems. On numerous occasions, Alithya has been contracted to implement target settings where leadership sets growth targets and the systems flows down the revenue by service, product line, etc. In turn, analysts match the underlying details.

Not surprisingly, this is a common request because target setting has been a long-time tradition during the budget process. By setting up this target setting process in PBCS\EPBCS, an off-line process is instead online and is molded with the overall budgeting system process.  Combining that with the zero-based budgeting mantra allows targets to be set and provides analysts with their needed baseline.  Moreover, analysis can be done on departments that take the typical “reduce expenses by 10% approach” to archive the target number instead of the more insightful zero-based budget journey.  Yes, target setting in a centralized system is easier, but the benefit of a centralized system is the ability to see how teams react to the new target.  Did they take the traditional “reduce budget percentages to fit the numbers,” or did they look at their budget as a whole and analyze each line item and question the numbers organically?

After targets are set and the budget is approved, we look at the said cost saving come to fruition.  A centralized system allows capital projects or initiatives to be tracked to help systematically measure the expenditures of cost savings activities found during the zero-based budget discovery. This provides a clear picture of what each department is doing and holds them more accountable for project decisions. It is an achievement to complete a zero-based budget “diet,” but holding teams accountable brings them to the next level of the zero-based budget “lifestyle.”

In essence, this new budgeting environment provides better insight into data – insight that ultimately allows savings to be found more effectively. For example, if you want to see the cost of direct materials, this centralized system can be set up to capture the costs in order to analyze and keep track of the different KPIs that reduce or increase overall costs.

Another example of how this works is by segmenting down employee costs such as travel. Instead of having a run rate of 10% of direct labor or travel costs, determine what job or tasks required that travel and use this KPI to negotiate travel expenses to further drive down costs.  Essentially, use PBCS/EPBCS as a tool to capture KPIs (e.g. travel costs by job) and determine the best use of travel dollars and – more importantly – negotiate with vendors on key travel.

Lastly, a budgeting environment provides clarity to help teams make better informed decisions about future initiatives. With the ability to see all of the underlying data points in a single location, it is possible to identify past sales and marketing campaigns and expenditures that led to profitable customers. Therefore, zero-based budgeting teams that took the initiative to determine the best sales and marketing costs to benefit analysis from the ground up are able to dedicate more resources (e.g. dollars, people, etc.) to winning strategies.  This is in contrast to the traditional budgeting approach of “10% rate of marketing spend year-of-year” that often masks the winning and more importantly losing marketing initiatives. Moreover, such planning and availability of different data points helps draw key inferences that allow sales and marketing teams to be more successful.

Summary 

Utilizing a Cloud service such as Oracle PBCS/EPBCS makes it easier for companies to implement a centralized system and achieve success with a zero-based budgeting program. PBCS/EPBCS environments can and should be set up in a way that enhances the zero-based budgeting experience. This is achieved by integrating target setting goals and establishing accountability metrics that allow a deeper dive into budget data while providing greater transparency to make better informed decisions.

To learn more about zero-based budgeting best practices and to get professional help with your Oracle PBCS/EPBCS environments, feel free to contact our team of experts.

Implementing Zero-Based Budgeting: The Requirements

A Culture Change and a Centralized System

The first post in this 3-post series – Implementing Zero-Based Budgeting: Benefits, Myths, and Goals – covers the benefits of zero-based budgeting. To summarize, it enables you to achieve long-term savings that result in sustainable growth and holds your financial analysts accountable for the cost figures they approve and how they are managing the overall budget. This allows more effective recognition of any unwanted costs and how you that money can be shifted into other growth areas within the company.

However, to reap the benefits of a zero-based budgeting program, a culture change is needed first at certain levels within the company. The goal is to eventually have the entire company complete this culture shift, but it is best to start small. Along with a change in culture, a centralized reporting system needs to be created as well to provide teams the ability to share real-time numbers with each other to achieve the goals of this new budgeting program.

Better Than a Quick Fix

What exactly is meant by a culture change? This means starting small and fostering this culture change in other departments starting with Finance. To be successful with this new program, other departments will eventually have to jump on board with this new budgeting approach. These departments will need to step up in analyzing their own costs and how they can save more without diminishing their capabilities.

For example, while financial analysts talk to the shop floor to see where costs can be reduced, the HR department should work with Finance to determine how it can become leaner. Moreover, the IT department should take the lead on negotiating with its vendors to find any areas that can be saved. These are just a few examples of how different departments can step up to the plate; implementing a successful zero-based budgeting program will requires team effort.

Changing the culture doesn’t happen overnight. Senior leaders should take the lead in fostering this change. To ensure that everyone is on the same page, managers need advocate the new approach within their respective departments.

Incentives also help teams to buy into this new budgeting approach.  Although incentives for growth metrics may already exist, additional incentives can effectively encourage staff to find ways to reduce costs for the metrics they manage.

Some examples of incentive metrics are the realized ROI based on the requested capital expenditure and the total cost saving dollars resulting from a zero-based budgeting program. For the former, this can mean moving to the Cloud to save money or reducing redundant tasks by introducing centralized software. For the latter, it can be exemplified by achieving a 10% cost reduction per phone.

Best Practice to Achieve Success

A crucial component of the success of a zero-based budgeting program is an officer who governs the entire process from start to finish. This individual (or team) should contain deep knowledge of the budgeting process. Naturally, s/he will not know the ins and outs of each department, so that is why s/he needs to be an ambassador to department leaders. The officer will also provide oversight to ensure that past bad habits of budgeting do not return to plague this new program. And lastly, s/he must be dedicated to the craft of continuous improvement which means seeking outside counsel when needed.

As mentioned earlier in the post, a culture change needs to be accompanied by a centralized reporting system. Alithya has helped clients implement Oracle Planning and Budgeting Cloud Service (PBCS) and Enterprise Planning and Budgeting Cloud Service (EPBCS) and overcome the deficiencies of Excel-based models. These models lose sight of what the true cost numbers are because past budgets are simple anchors of history rather than detailed breakdowns of cost. Moreover, these numbers become siloed within the vast library of Excel models. With Oracle PBCS or EPBCS, budgets can be highly surgical and help leaders in the company pinpoint reductions.

A centralized system allows the capture of all changes in a single location in real-time, and it provides insight into how effectively managers seek cost savings. This can be used as a key indicator to determine if their actions are in line with this new methodology.

Furthermore, centralization not only holds managers more accountable, but it also empowers them to create innovative cost-saving solutions. Driven by incentives, staff will burn with a clear purpose to find new ways to achieve sustainable growth for the company and be rewarded for hard work.

Recapping What It Takes to Achieve ZBB Success

The goal is to create a cost savings culture that allows more capital to be invested into growing parts of the company. To be successful, follow the best practices outlined, starting with a culture change within the company and giving your teams a centralized PBCS and EPBCS system to more clearly see all data points. The hard work does not stop here, though! The next post delves into setting up a zero-based budgeting system.

Implementing Zero-Based Budgeting: Benefits, Myths, and Goals

If you are in the finance world, then you probably have heard of zero-based budgeting. Investopedia defines zero-based budgeting as “a method of budgeting in which all expenses must be justified for each new period. The process…starts from a “zero base,” and every function within an organization is analyzed for its needs and costs.”

There are many reasons that financial professionals decide to use zero-based budgeting. For one thing, it goes hand-in-hand with a centralized system where information can be shared – something at which Excel spreadsheets are terrible. Furthermore, developing a centralized system enables you to scale to your needs as your company grows. Lastly, it enables financial analysts to spend more of their work week analyzing data instead of curating a financial system and worrying if the numbers match.

At Alithya, we have found with our past clients that a successful zero-based budgeting implementation resolves numerous problems. The two main things clients hope to achieve is growth across multiple business units and developing sustained cost reduction. With zero-based budgeting, you can earn long-term savings that can directly translate into sustainable growth.

Earning Long-Term Cost Savings

Zero-based budgeting becomes a daily exercise in cost savings for your financial teams. One method in achieving cost savings is renegotiating costs. For example, instead of taking the run-rate of 3% from last year’s numbers, perhaps you can contact your vendors to bargain for a better deal or switch to a different vendor with a more competitive price. Or how about having your analysts ask the IT department why it costs $38.03 per phone? What makes up that entire $38.08? Don’t assume that there aren’t any negotiable components of a cost.

The reason zero-based budgeting is so effective at long-term savings is that it is not a one-off fix. Many teams tend to implement one-off fixes, and then find that those fixes do not provide sustainable cost savings. A common example is offshoring your call center which might get you an immediate win in the cost column. However, this strategy typically reduces customer service quality while also limiting your ability to evolve with your business as it grows.

When enacting this type of program, you will analyze the costs of your business at every level. This may seem tedious, but what you will find is a clearer understanding of where your money is going. This can mean acquiring a greater understanding of contract labor costs as well as improving purchasing and procurement procedures, just to name a few. Moreover, when properly implemented, zero-based budgeting can reduce SG&A costs by 10 to 25 percent, often within as little as six months,” according to McKinsey & Company.

Debunking Myths Surrounding Zero-Based Budgeting

There are many myths surrounding zero-based budgeting that have sadly created an artificial barrier that CFOs and their teams do not want to cross. Many financial professionals think that it means cutting the budget down to the bare bones, but rather, a zero-based budgeting program analyzes costs from the top-down. Moreover, it is the CFOs’ duty to outline cost-cut targets so that their team’s efforts are focused.

Another misconception is that zero-based budgeting only helps with cutting the costs of SG&A. Actually, it can do much more, such as breaking down the Cost of Goods Sold (COGS) and help teams make investment choices on the capital expenditure with the greatest ROI.

Just because your business is not in decline or stagnating doesn’t mean that you can’t adopt a zero-based budgeting program. If you are already achieving growth, you can use this type of budgeting method to keep the overall business leaner so that you can provide more runway for growing business units.

Do you really start from zero? This is a common question that we are asked, and many people think because of its name that you do always start from zero. Technically, this is true, but this is the core component that drives the cost management culture change that will be introduced in the next post in this series.

However, not all things have to start from zero. At Alithya, we have been through many implementations where parts of the P&L are driver-based or zero-based. This can be achieved with a detailed, structured, and interactive system (like Oracle PBCS/EPBCS) that gives you real-time feedback.

How Does Oracle PBCS and EPBCS Help Achieve ZBB goals?

The main feature you acquire when you implement an Oracle PBCS or EPBCS system with your zero-based budgeting program is deeper analytics. This data enables you to dig into the “why and how” of your P&L.

For example, you could pose the question what driver did they use? Did they just simply take last year’s actuals and add 3%? Did they take a cost-per-head and budget it manually, or did they take the easy way out? All are important questions that force finance teams to be more accountable when it comes to everyday decisions.

Recapping the Benefits of ZBB

By implementing a zero-based budgeting program with a centralized system, you can hold your analysts more accountable to cost figures while making them own up to how the costs are managed. It allows you to recognize any unwanted costs that can be diverted into certain growth areas as well as breed a culture of cost reduction and visibility. The latter requires that you to start a culture change within your team. It is an essential part of having success with a zero-based budgeting program which is why we will cover it in greater detail in the next post.