Profitability and Cost Management

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    Alecsandra Mlynarzek
    PCMCS Out-of-the-Box (OOTB): 3. Intelligence and...
    Topic posted April 22, 2019 by Alecsandra MlynarzekBronze Trophy: 5,000+ Points, last edited September 12, 2019 by Hemal KapasiBronze Trophy: 5,000+ Points, tagged Activity Based Costing, Allocations, Calculation, Costing, Customer Profitability, PCM, Profitability Analysis, Tip 
    120 Views, 1 Comment
    Title:
    PCMCS Out-of-the-Box (OOTB): 3. Intelligence and Dashboarding: Profit Curves
    Summary:
    Out of the box features with PCMCS - Profit Curves
    Content:

    Over the past few months I have identified 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 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 post 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 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

    Comment

     

    • Ayeshan Peiris

      Hi Alecsandra,

      This post is a useful one. I have a clarification. For a profit curve in PCMCS, this note mentions about category analysis which uses attribute dimensions to analyze based on categories (Attributes). I want to know this option is available for bar charts and pie charts also? I have a requirement to create bar charts and pie charts based on an attribute dimension on the row of the charts. Your expertise on this is highly appreciated.

      Thanks,

      Ayeshan