Definition Step (Optimization - Negotiation Guidance)
The aim of this step is to set the scope of the transactions. There is a single tab, composed of a configurator (left frame) and a dashboard (right frame).
Inputs
In the Definition step, you map the inputs and set the scope of the model. The user inputs are always on the left. By default the inputs are filled with values set during the deployment of the accelerator.
Transaction source – Datamart or Data Source used to calculate the segments. It must fill the requirements listed in https://pricefx.atlassian.net/wiki/spaces/ACC/pages/5141922376. Once provided, some fields based on it appear:
Transaction Filter – Allows you to filter the data. We recommend that you define at least these filters:
Positive cost, revenue, and quantity.
Optimization target in a realistic range, for example between -0.1 and 1.
Customer Field – Customer ID field. It is used to aggregate data by customer.
Product Field – Product ID/SKU field. It is used to aggregate data by product.
Quantity Measure – Field that indicates the quantity in a transaction.
Revenue Measure – Field that provides the transaction extended price which will be the basis of the analysis. It may be a net price, a gross price, or another, depending on the policy you want to simulate.
Margin Measure – Field providing the extended margin of the transaction. Similarly to the Revenue Measure, it is chosen according to the policy you want to simulate.
Optimization Target – Usually the margin rate or the discount rate (i.e. a value of 10% must be represented with the value 0.1). No null values are allowed in the optimization target field.
If you intend to use alignments later in the process, discount rate is a better choice as alignment will then take the list prices as a reference, which is generally more consistent and less volatile than the costs.
Your selection here (margin or discount rate) must be accompanied by a corresponding value in the Target Type option (below).Target Type – Select either Margin% or Discount% depending on what you have selected in the Optimization Target option above.
Weight Measure (optional) – Field that indicates the weight of a transaction row. If not set, all the Datamart rows are weighted equally. You may use the quantity field, for instance, if you want to weigh ten times more a transaction to sell ten products than one to sell only one product. For now, business alignments cannot be used if a “weight” is used.
List Price – Mandatory field if the metric is of type Discount %. It represents the price without any discount applied to it. It must be an extended value.
The revenue, margin, and list price values are used to simulate the transactions when the optimization target value changes. The mapped fields should be consistent: Optimization Target, Revenue Measure, and Margin Measure are checked together in case the Target Type is set to Margin%; Optimization Target, Revenue Measure, and List Price are checked together in case the Target Type is set to Discount%.
If needed, create some calculated fields in the transaction source: revenue, margin, margin rate (i.e., margin/revenue).
Use the check-boxes for additional filters ensuring calculations without exceptions. These parameters are checked by default. Note that the “Replace missing dimensions” replaces the null values of each dimension with a given string (by default, it is __missing__). If you uncheck this checkbox, the dimensions with null values will not be selectable as segmentation levels.
Dashboard
Once you apply the settings, the right panel provides:
Transactions in Scope – Data that are in the scope of the segmentation.
Filtered Out Transactions – Data that are filtered out by the set transactions filter.
Some data rows appear neither in the Transactions in Scope, nor in the Filtered Out Transactions. It is the case if a value is filtered out by the advanced filter, but its value is null and it is also filtered out with the opposite of the user filter. Please consider the Filtered Out Transactions portlet as source of information possibly missing data.
You can then click the Continue button (top right) which takes you to the Analysis step.