There are a few things to consider when implementing a capability like this.Data storage, by the way, is not really one of them. Sure, billions of interactions may have to be captured, but it's offline storage which is cheap, and it's only the data that is actually used to make decisions. Therefore, data storage requirements go hand-in-hand with better informed (i.e. higher quality) decisions which means the additional returns will easily pay for more, cheap disk space (on-premise or in the cloud).
To be able to simulate, in detail, a customer journey over time and across channels, you can't glue together a herd of siloed customer strategies. It's quite alright to have separate channel systems, but the customer decisioning needs to be centralized. The "how" of the customer interaction (i.e. what it looks like and how it's executed) can be left to a specialized channel application of choice, but the decision as to "what" to talk about needs to be carefully orchestrated. Simulation is only one consideration here - a centralized decision hub also enforces consistency, leverages cross-channel learnings, and in general supports a customer-centric strategy.
A federated, loosely coupled customer decision capability may sound flexible but makes it nearly impossible to reliably replay the customer experience and simulate the effect of changes. To learn and adapt is critical in a dynamic environment, but some changes may not have enough precedents by which to learn. In that case, it's better to conduct a trial and error approach safely in the past than make the change in a production system and hope for the best. As we all know, hope is not a strategy.
Source: Computerworld Inc
Sign up for MIS Asia eNewsletters.