Out-of-the-Box Features: Profitability and Cost Management Cloud Services (PCMCS) - Intelligence and Dashboarding: Key Performance Indicators (KPIs)

Published February 26 2020 by Alecs Mlynarzek
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Welcome to the next post in the Profitability and Cost Management out-of-the-box features series!

If you are interested in the Intelligence capabilities included with your PCM Cloud subscription, visit the links below, each of which highlights a valuable out-of-the-box PCM feature.

  1. Analysis Views and Scatter Graphs:  The Basics
  2. Profit Curves:  Building and Interpreting Them
  3. Traceability:  What is it and How Can it be Used?
  4. Using Queries to Build Validation Reports and Data Extracts

This post explores Key Performance Indicators – how they can be built in Profitability and Cost Management and the value they provide to analysis.  Visit the previous post Key Performance Indicators (KPIs): Importance and Usage to learn more about KPIs in general.

This information builds on the previous KPI-related post and provides insight into these concepts:

  1. Building KPIs in Profitability and Cost Management Cloud
  2. Leveraging KPIs in Profitability Dashboards

This following content is based on the standard Bikes (BkML30) application.  Deploying the PCM Demo Bikes application can be achieved via the PCM landing page – “Create a Sample application button” (starting with version 19.06 onwards).

Building KPIs in Profitability and Cost Management Cloud

Once your financial analysts have defined the most meaningful KPIs for your business and the required information is available to start setting them up, where do you start?

Step 1. Create and deploy the corresponding measures that will store the performance statistics.

For example, in the BksML30 Demo model, there are two prebuilt Performance Statistics KPI members:

*Note: The level of grain you set up in your master data should match the level of grain in your KPI metric.

Profitability and Cost Management Cloud applications are built on a technology called Aggregate Storage Option (ASO). Generally, KPIs are calculated through dynamic member formulas in Multi-Dimensional eXpressions (MDX). While all this information can sound a bit confusing, rest assured, there is a lot of good documentation available to ramp up on MDX and it is not as complicated as the name suggests.

List of ASO MDX formulas available for ASO applications:

 https://docs.oracle.com/cd/E57185_01/ESBTR/calc2mdx.html

The list of functions valid for PCM may change over time, so check the latest Oracle documentation. One drawback of on-premise implementations is to constantly monitor what features and functions are available for the version of software you currently own. With Cloud implementations, unless there is a true issue that prevents upgrading, it is much easier to keep track of what is and is not available for your version, as upgrades are pre-scheduled and included in your environments’ routine maintenance.

Link for EPM Cloud updates releases:

https://www.oracle.com/webfolder/technetwork/tutorials/tutorial/cloud/epm/wn/epm/epm-wn.htm

KPI Use Case example in PCM

The first statistical metric available in the BksML30 Profitability demo application STAT1501 represents Net Income divided by Net Revenue, more commonly known as Profit Margin.

An alternative to tying KPI Member Formulas in the Master Data definition like shown in the screenshot above would be to calculate the stored KPI through a Custom Calculation in Profitability and Cost Management. The following example is what the same Member Formula would look like if written through a Custom Calculation.

Besides mentioning the Rule and Balance dimension members, the final syntax is not all that different.

The advantage of taking the route of a Custom Calculation is that the Power User, if familiar with MDX statements’ syntax, should be able to manipulate the formulas at his discretion, as many times as needed, without the need to involve the Master Data Management responsible.

Note: An application Administrator can update KPI Member Formulas and deploy Profitability applications. A Power User cannot deploy applications. The alternative route of Custom Calculations breaks the dependency between a Power User, who will own the Profitability application calculation methodology, and the Administrator, who will most likely perform regular maintenance duties.

The disadvantage of calculating KPIs in Custom Calculations is that users would have to wait for the calculation to run before they would see the final KPI value. With member formulas, the result of the KPI calculation is immediately available during retrieve.

Custom calculations OR Member Formulas?

How do you decide which route to take with a KPI or any calculated metric within Profitability and Cost management applications? Here is a short list of ideas to consider when making such a decision:

  1. Complexity of MDX script - if the member formula becomes too onerous, one option would be to separate it in parts (distinct members) and make it easier to troubleshoot or follow the calculation logic. Multiple member formulas that have Order of Operation dependency may be more difficult to follow compared to custom calculation rules that have an easy to manipulate sequence field.
  2. Maintenance – a member formula is static across Points of View (years, scenarios, versions) and is part of the Master Data that may be generated by an external system. Changing a member formula may require going through processes outside of the Profitability application. In comparison, a custom calculation is open to immediate updates that can also vary by Point of View (POV).
  3. Functionality - Not all MDX functions that work in member formulas will also work in custom calculations. A static list of what is included with Profitability and Cost Management custom calculations would not be relevant, as each month’s Cloud update brings new functionality. Test formulas in custom calculations before signing off on the chosen solution.
  4. Formula length – valid for both member formula as well as custom calculations. The number of characters in a custom calculation is lower than the number of characters allowed in member formulas. However, splitting a member formula across multiple metadata members to cater for a lengthy function can prove to be onerous compared to splitting a custom calculation into several rules.
  5. Timing – having to run the Profitability model to see the KPI calculation result vs having the result immediately available through a dynamic member formula may be the decisive factor between the two options. If the Profitability model takes hours to run and there are no intermediary allocation results to derive the KPI result, it is advisable to set up the KPI formula in a member formula instead of a custom calculation.
  6. Dependencies – Custom calculations are the preferred alternative in circumstances where your KPI formula depends on intermediary allocation points and cannot be resolved via a simple conditional logic (IF or CASE statement).

Once the decision is made regarding the approach – member formula or custom calculations, it is time to define how end users will consume this information.

The steps described in the following sections are tied into each of the tabs available for KPI setup in Profitability and Cost Management applications. The order in which the steps are described is based on the order available in the menu as of Jan 2020.

Step 2. Base Definition tab: find a relevant reporting name for your KPI, a meaningful description, and choose the population dimension.

*Note: Profitability and Cost Management Intelligence screens have the flexibility to create KPIs and store them as Work in Progress (not Enabled). Only the enabled KPIs will be available to use within Dashboards.

The Computation Option available at the bottom of the KPI setup screen is pertinent to KPIs that use a multiperiod function. For example, in the case of a KPI that is set up to display a Quarterly value or Half Year value, users can choose to display either an Average or a Sum of the metric over the defined period. Tied into the Computation option is a comparison criterion (available in the Comparison tab) that allows variance analysis over the defined period.

Step 3. Data Slice tab: displays all the dimension and member selections made for the current KPI. If no selection has been made for a dimension, it will display the “top-of-the-house” reference enclosed between <>.

Notice in the below example taken from the Demo BksML30, << Department Stores Customer Service Change Over Prior Quarter>> KPI, how the Period dimension reference reads “Current.”

As mentioned in my previous Profitability and Cost Management blog posts, references can be defined for Current Year and Current Period for each application. These references work similarly to the concept of sub vars in Essbase. They are ways for an Administrator to control what is considered the “Current Time Period” and are set up at Application level within the Dimension Settings menu.

Besides the “Current” member reference which is static until the moment the Administrator makes the monthly update in the application, there are also several predefined Member Formulas from which a user can choose.

For further information on the formulas, such as <<Single(-1) Level0>>, read the previous post Out-of-the-Box Features: Profitability and Cost Management Cloud Service (PCMCS) - Intelligence and Dashboarding: Analysis Views and Scatter Analysis .

Step 4. (OPTIONAL) The “Statistics” tab enables you to select amongst several options that will automatically be included in the calculation of the KPI, such as:

  • Rank: what rank/ performance relative to other data points?
  • Average: what is the average KPI value?
  • Median: what is the median point of KPI data values – midpoint of frequency distribution.
  • Quartile: division of the KPI data pool into 4 groups, based on the available data values.

The statistical option chosen will be applied to the KPI value at run time.

For the purpose of this explanation, I took as an example the KPI called <<QMart Store 001 Profit Margin Percentage>>. The Population dimension chosen is Customer, and the request is to display an average value across all Customers under a specific selection of Population Members.

Step 5. (OPTIONAL) To add more information to the KPI value and guide the user towards understanding his data, there is an option in the “Score Category” tab to add different valuation gates paired with a message, a concept also called “score carding” or “traffic lighting” in day-to-day finance analysis.

In the example of the KPI <<QMart Store 001 Profit Margin Percentage>>, there are 5 gates or yardsticks that will indicate whether a customer is profitable, unprofitable, or if its value is critical and needs immediate attention.

Depending on the evaluation logic defined, you can move the criteria up or down on the evaluation ladder.

Step 6. (OPTIONAL) If you are using the “Score Category” tab, you can compare the current KPI numbers against another reference – like a variance analysis between time periods or scenarios. In the “Comparison” tab, you can define the “Comparison Dimension” and “Comparison Member.”

For the example below, the comparison is against the Period dimension.

Step 7. (OPTIONAL) This represents the final tab in the KPI setup within Profitability and Cost Management Intelligence screens. The “Display Options” tab enables you to define a Prefix and a Suffix.

Examples of Prefixes could be currency references. For Suffix references, we could add %, “Pct.,” etc.

Conclusion

KPI setup in Profitability and Cost Management applications is a straight-forward process once the KPIs’ names and the applicable formulas have been defined.  Multiple considerations should be made regarding KPI selections, and a balance of financial/non-financial and leading/lagging indicators should be set up where possible.

With a few selections in the Profitability and Cost Management Intelligence menu, end users can create and validate metrics that can provide context and guidance when analyzing performance. Layered within Dashboards alongside Analysis Views, KPIs tell a story in one screen, indicating issues when there are predefined ranges or underlying variances compared to prior periods. Gone are the days when it took significant effort to set up a new KPI, calculate it, store the result, and then build the corresponding reports. With the right level of access, Profitability and Cost Management users can perform all of these tasks independently and do so within a few minutes, as long as they have a clear vision of what the KPI should measure, and if they have access to the necessary data points required to build it.

Even in circumstances where you have reporting solutions that already perform a lot of the analysis proposed by the Intelligence and Dashboarding tools in the Cloud, make the most of your investment into Profitability and Cost Management and leverage all there is to benefit from the tool.

Even in circumstances where you may already have a reporting solution on top of new or existing Profitability applications, the Dashboarding capability should still be explored. The simple fact that a higher-level analysis can be performed immediately after data is loaded or calculated within the tool represents an advantage. Reaction times can be reduced, as the analysis can reside within the PCM application without the need to wait for it to be exported to another system or application.

Let me know your thoughts on the KPIs in Profitability and Cost Management. Reach out to us at infosolutions@alithya.com if you would like to see more about Intelligence and Dashboarding capabilities within Profitability and Cost Management.

This is the last out-of-the-box blog Intelligence menu-related post, but the list of features included with your Oracle Cloud license is far from over. Upcoming posts will be about System Reports that support troubleshooting, analysis, and quick reaction to allocation results; painless and automated Backup and Restore capability; lights-out monthly patching and how it can affect your process hierarchy; and last but not least, the light integration tool - Cloud Data Management – pros, cons, and implementation considerations.

For comments, questions, or suggestions for future topics, please reach out to us at infosolutions@alithya.com.  Visit our blog regularly for 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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