Commerce Standard Process Enhancements

In addition to supporting 24D Commerce features, Oracle CPQ 24D provides Standard Process support for the following enhancements:

The Keyword Search for Transaction Number is automatically enabled when a new Standard Process is created.
The "Add From Favorites" main document action is now available on the transaction layout when a new Standard Process is created. This action allows users to quickly access their Favorites List directly from the Transaction UI.
A default Deal Analytics tab is automatically added to the transaction layout when a new Standard Process is created.

Standard Process Support for Deal Analytics

A default Deal Analytics tab is automatically added to the transaction layout when a new Standard Process is created. Refer to Oracle CPQ Administration Online Help > Pricing > Deal Management for more information about analytics.

Oracle CPQ 24D adds the following Commerce items to new and existing Standard Processes:

Main Document (Transaction) Attributes

html_main_price_optimization (_s_html_main_price_optimization) Holds Win Probability with Optimization graph. Populated when 'Total Discount %', Customer Segment and Total Contract Value (Net) are populated and 'Calculate WP OP Revenue' action is triggered.
html_main_scatterplot (_s_html_main_scatterplot) Holds header lever scatter plot graph.
html_main_timeseries (_s_html_main_timeseries) Holds Time Series graph.
Optimal Primary Driver (Discount%) (_s_optimalPrimaryDriver) Optimal Discount% returned from Price Optimization analytic 'Optimized Discount%'.
Optimal Target Value (_s_optimalTargetValue) Optimal Target Value returned from the Price Optimization based analytic 'Optimized Discount%'.
Optimal Win Probability (_s_optimalWinProbability) Optimal Win Probability value returned from price optimization analytic 'Optimized Discount%'.
Price Score List Based (_s_priceScoreListBased) Price score for the transaction using List Based calculation method. In order to see a value in this, please add some lines and set the 'Line Item Grid Columns' to 'PriceScoreSet'.
Price Score Margin Based (_s_priceScoreMarginBased) Price score for the transaction using Margin Based calculation method. In order to see a value in this, please add some lines and set the 'Line Item Grid Columns' to 'PriceScoreSet'.
Price Score Simple Margin Based (List Price Basis) (_s_priceScoreSimpleMarginListPrice) Price score calculation using Simple Margin Based method and List Price as Basis attribute. In order to see a value in this, please add some lines and set the 'Line Item Grid Columns' to 'PriceScoreSet'.
Price Score Simple Margin Based (Net Price Basis) (_s_priceScoreSimpleMarginNetPrice) Price score calculation using Simple Margin Based method and Net Price as Basis attribute. In order to see a value in this, please add some lines and set the 'Line Item Grid Columns' to 'PriceScoreSet'.
Price Score Simple Margin Based (Unit Cost Basis) (_s_priceScoreSimpleMarginUnitCost) Price score calculation using Simple Margin Based method and Unit Cost as Basis attribute. In order to see a value in this, please add some lines and set the 'Line Item Grid Columns' to 'PriceScoreSet'.
Use Transaction For Analytics? (_s_useTransactionForAnalytics) This is used as a filter attribute for analytics. When set to True, values in this transaction will be used by analytics.
Win Probability (_s_winProbability) Win Probability value returned from the WP analytic named
Win Probability Without Optimization (_s_winProbNoOptimization) Holds win probability without Optimization graph.
Win Probability Net Revenue Value Prediction (_s_winProbRevPrediction) Win Probability Net Revenue Value Predicted by the Price Optimization Analytic 'Optimized Discount%'.

Sub-Document (Transaction Line) Attributes

html_line_scatterplot (_s_html_line_scatterplot) Hold line scatter plot graph.
Last Price Paid (_s_lastPricePaid) The most recent price at which the part/model was quoted.
Last Price Paid (CustomerId) (_s_lastPricePaidCustomerId) The most recent price at which the part/model was quoted to the customer.
Price Score Margin Based (_s_priceScoreMarginBased) Margin Based Method price score calculation for a line.
Price Score List Based (_s_priceScoreListBased) List Based Method price score calculation for line.
Price Score Weighting (_s_priceScoreWeighting) Weighting attribute for price score calculation at the transaction level.
Price Score Simple Margin Based (Net Price Basis) (_s_priceScoreSimpleMarginNetPrice)
Price Score Simple Margin Based (Unit Cost Basis) (_s_priceScoreSimpleMarginUnitCost)
Price Score Simple Margin Based (List Price Basis) (_s_priceScoreSimpleMarginListPrice)
Line Discount Guidance Floor (_s_lineDiscountGuidanceFloor) Lower bound of the line discount guidance.
Line Discount Guidance Ceiling (_s_lineDiscountGuidanceCeiling) Upper bound of the line discount guidance.
Line Discount Guidance Max (_s_lineDiscountGuidanceMax) Max of the line discount guidance.
Line Discount Guidance Meter Gauge (_s_lineDiscountGuidanceMeterGauge) Holds line discount guidance graph.
html_line_timeseries_l (_s_html_line_timeseries) Holds line time series graph.

Main Document (Transaction) Actions

Calculate WP OP Revenue (_s_calculateWPOPRevenue) Calculates WP OP Revenue Value.
Calculate Win Probability (_s_calculateWinProbability) This action is responsible for triggering Win Probability value.
Last Price Paid Trigger Action (_s_lastPricePaidTriggerAction) Action to invoke Last Price Paid.
Update Price Guidance (_s_updatePriceGuidance) Action to update price guidance.

Oracle CPQ 24D adds the following Commerce Analytics to new Standard Processes:

Line Item Discount Guidance by Historical Data (_s_lineltemDiscountGuidanceByHistoricalData) The line level price guidance visualization for current price or discount values.
Quote Discount Guidance by Price Optimization (_s_quoteDiscountGuidanceByPriceOptimization) The header level price guidance visualization for current price or discount values.
Win Probability (_s_winProbability) The machine learning predictive model generated metrics to predict win probablity based on historical data.
Optimized Discount % (_s_optimizedDiscount) The machine learning predictive model generated price optimization to maximize either margins or net revenue.
Line Time Series (_s_lineTimeSeries) The line level time series analytic graph that displays pricing trends in a time series chart.
Time Series (_s_timeSeries) The header level time series analytic graph that displays pricing trends in a time series chart.
Last Price Paid (_s_lastPricePaid) The last price paid metric that provides historical price information.
Line Scatter Plot (_s_lineScatterPlot) The line level scatter plot analytic graph that displays data points as a comparison set in a scatter plot chart.
Scatter Plot (_s_scatterPlot) The header level scatter plot analytic graph that displays data points as a comparison set in a scatter plot chart.

The Standard Process provides out-of the box functionality for analytics, keyword search, proposal documents, and favorites.

Steps to Enable

You don't need to do anything to enable the new functionality for a newly created Standard Process.

Enable Keyword Search for the Transaction Number

If required, complete the following steps to enable the Keyword Search for the Transaction Number.

Navigate to Admin > Process Definition Commerce
Select Data Columns from the Navigation menu for the applicable Commerce process,
Click on the "Transaction : Transaction Number (transactionID_t)" link.
Select the Keyword Search Enabled option.
Click Update.

Create Deal Management Analytics

If required, refer to Oracle CPQ Administration Online Help > Pricing > Deal Management to create new analytics.

Add Commerce Items to the Transaction Layout

If required, refer to Oracle CPQ Administration Online Help > Commerce > Transactions > Layout Editor to add new items to the Transaction UI. (e.g. Add from Favorites action, Analytics)