One of the key objectives of digital migration is to preserve subscriber history.
This is especially true post-M&A, where subscribers might need to be moved between providers, potentially leading to mismatches between offerings and terms in the legacy and new systems. Then there’s the business imperative to move as many subscribers as quickly as possible. This allows you to take full advantage of your new capabilities, while keeping operating and maintenance costs to a minimum. And while most subscribers will be eligible for migration, some might be assessed as undesirable and ineligible. Even eligible subscribers may need processing or “treatment” as part of the process.
The challenge to get it right, the first step of your digital transformation must be to carefully analyze your capabilities – potentially hundreds of them plus all their permutations (e.g. timing release of new features, considering each subscriber’s preferred communication method). Then, once you’ve mapped all the constraints, you need to consider whether it’s worth changing the order of new feature development in order to migrate more subscribers sooner. Such segmentation also ensures your subscribers don’t become overwhelmed by the changes.
Another key is a dynamic dashboard, which can provide a snapshot of the project at any point in time, with the latest forecasts and recommendations, and enabling access to both the business and development teams. The framework must also include the capability to perform “what if” analyses, so you can check how any proposed program changes will affect your forecasted number of successful migrations.
Harnessing data to accelerate migration
Amdocs End-to-End Analytical Framework provides ongoing intelligent analytics to accelerate your conversion program. It does this through a combination of data analysis capabilities, machine learning models and BI tools that provide timely data and insights. Amdocs End-to-End Analytical Framework provides service to multiple groups in the organization by synthesizing them into a consistent framework.
“We successfully converted millions of subscribers faster, with a superior customer experience. This product migration would have been impossible without the Amdocs Conversion Analytics Framework"
Ultimately, the goal is to create self-service tools which enable the migration without putting the organization under undue pressure. This means ensuring that the backend accommodates all the features required for the frontline teams to switch subscribers, treating, and handling any issues that arise, for example, a subscriber may need to switch their SIM, or they may need to be informed that a feature has reached end-of-life.
Conversion of millions of subscribers usually takes 12-18 months and requires different analytics at various stages, as well as an overall mechanism to forecast the conversion pace throughout the project.
Analytical stages
Eligibility forecast
Identify which subscribers are eligible for migration based on hundreds of rules that map the features of both systems. Eligible subscribers may be suitable for immediate or future conversion, while others may first require “treatment”.
Treatment cohorts
Establish cohorts of subscribers who are cleared for migration but require treatment prior to conversion. For example, a subscriber may need to take a specific action, such as accepting the proposed change, or they may simply need to be notified of the change.
Treatment adoption forecast
Forecast the adoption of subscribers who require treatment. Some subscribers might be subject to timing restrictions – such as if their phone lease is about to expire, or if they require a capability that’s simply not yet available. This absolutely crucial stage entails identifying the optimal order in which to develop and implement any treatments to ensure rule compliance.
Conversion segmentation
Converting subscribers to the new system means the next bill they receive will be generated by system B. The conversion must be throttled by capacity as well as operational and network considerations. Segmenting the conversions appropriately enables you to predict and handle post-conversion issues.
Conversion reject forecast
Forecast which subscribers might reject the conversion.
Post-conversion behavior
Analyze post-conversion subscriber usage patterns and whether they are experiencing fewer or more problems and churning at a different rate.
Conversion rate forecast
Deliver real-time forecasts of the conversion progress for the complete duration of the migration process, starting with the eligibility forecast as a baseline. The forecast factors time-based events such as capability releases and treatments. Additional forecasts predict the treatment success rate and the impact of frontline and capacity and bottlenecks.