You’ve made the decision to invest in a Pricing and Revenue Management system, but architecting such a system can stretch the limits of any technology. A good Pricing and Revenue Management system design will ensure that your business will receive the right pricing recommendations, for the right customer, and just-in-time, without unnecessary churn. Building business-reasonable self-awareness into the system should be at the cornerstone of your organization’s design. Doing so will create a Pricing and Revenue Management system that performs well, eliminates the “black box” mentality, and increases the confidence for business-users. When going through the design process, the most important questions to ask are:
- What empirical metrics do my business-users need to make informed Pricing and Revenue Management decisions?
- What critical factors drive relevant changes in those metrics?
- How do we measure those changes and trigger the right Pricing and Revenue Management actions to take place when those events are detected?
It’s essential to identify the vital organizational drivers of change from both an analytical modelling perspective, and for system implementation. These are the primary benefits once the drivers of change have been identified:
- The drivers provide business-users with the tools that help to make predictive analytics more accurate;
- It informs the prescriptive analytics as to how efficiently a recommendation will move to a more optimal profit position and therefore resulting in the best tradeoff decisions;
- From a software architecture perspective, these factors determine the triggers for executing different analytical modules, and expose those factors to the business-users through proactive alerting;
- It eliminates unnecessary churn knowing up front whether a recalculation is truly warranted;
- It aids in right-sizing computing resources and storage to maximize system performance;
- This approach identifies the paramount factors, and it helps to ensure relevant and impactful information.
These benefits help to drive best practices for designing just-in-time price recommendations.