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Arbitration strategy

Updated on August 4, 2022

The Arbitration strategy is responsible for setting up the attributes that will be used in the final priority calculation (P * C * V * L). These settings are managed within Next-Best-Action Designer and saved into decision data rules (DDRs).

Pega Customer Decision Hub

A high-level view of the strategy is shown first, and then each section will be described in more detail.

The Arbitration strategy

The strategy first sets the FinalPropensity property to be based on the action or treatment propensity. Then the strategy sets the business value. By default, the action-level business value is used. Modify the business value extension point strategy to change this.

Business value extension point

After that, if the Business levers are enabled, the strategy determines business purpose weighting, first at the issue level and then the group level. These weightings are added together and then normalized. For example, a total weighting of 55 sets a final weighting of 1.55.

Business levers

The strategy then applies context weighting by looking at the Container and Event payloads and searching for a matching Key and Value pairs for each issue and group. If a match is found, the weighting is added to the weight for the specified issue and group. This weighting is also normalized, so a total weighting of 55 sets a final weighting of 1.55.

The next step is to calculate Q & A related context – if any. By default, there is none, but it can be added via the QnAContextWeightingExt extension point.

After the properties are calculated and normalized based on the settings configured in Next-Best-Action Designer, the Priority property is set using the following formula: .FinalPropensity * .ContextWeight * .Value * .Weight.

Then all actions and treatments are prioritized based on Priority in descending order.

Prioritization component
  • Previous topic NBA Strategy framework components: Arbitrate through NBA Post-Process extension
  • Next topic Calculate Business Value strategy

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