My previous posts about Journey Orchestration Engines (JOEs) have all pointed to new products. But some older systems qualify as well. In some ways they are even more interesting because they illustrate a mature version of the concept.
The Customer Decision Hub from Pega (formerly PegaSystems) is certainly mature: the product can trace its roots back well over a decade, to a pioneering company called KiQ Limited, which was purchased in 2004 by Chordiant, which Pega purchased in 2010. Obviously the system has been updated many times since then but its core approach to optimizing real-time decisions across all channels has stayed remarkably constant. Indeed, some features the product had a decade ago are still cutting edge today – my favorite is simulation of proposed decision rules to assess their impact before deployment.
Pega positions Customer Decision Hub as part of its core platform, which supports applications for marketing, sales automation, customer service, and operations. It competes with the usual enterprise suspects: Adobe, Oracle, Salesforce.com, IBM, and SAS. Even more than those vendors, Pega focuses on selling to large companies, describing its market as primarily the Fortune 3000. So if you’re not working at one of those firms, consider the rest of this article a template for what you might look for elsewhere.
The current incarnation of Customer Decision Hub ihas six components: Predictive Analytics Director to build offline predictive models, Adaptive Decision Manager to build self-learning real-time models, Decision Strategy Manager to set rules for making decisions, Event Strategy Manager to monitor for significant events, Next Best Action Advisor to deliver decisions to customer-facing systems, and Visual Business Director for planning, simulation, visualization, and over-all management. From a journey orchestration perspective, the most interesting of these are Decision Strategy Manager and Event Strategy Manager, because they’re the pieces that select customer treatments. The other components provide inputs (Predictive Analytics Director and Adaptive Decision Manager), support execution (Next Best Action Advisor), or give management control (Visual Business Director).
Decision Strategy Manager is where the serious decision management takes place. It brings together audiences, offers, and actions. Audiences can be built using segmentation rules or selected by predictive models. Offers can include multi-step flows with interactions over time and across channels. Actions can be anything, not just marketing messages, and may include doing nothing. They are selected using arbitration rules that specify the relevance of each action to an audience, rank the action based on eligibility and prioritization, and define where the action can be delivered.
The concept of “relevance” is what qualifies Decision Hub as a JOE. It measures the value of each action against the customer’s current needs and context,. This is the functional equivalent of defining journey stages or customer states, even though Pega doesn’t map how customers move from one state to another. The interface to set up the arbitration rules is where Decision Hub’s maturity is most obvious. For example, users can build predictive model scores into decision rules and can set up a/b tests within the arbitration to compare different approaches.
Event Strategy Manager lets users define events based on data patterns, such as three dropped phone calls within a week. These events can trigger specific actions or factor into a decision strategy arbitration. It’s another way of bringing context to bear and thus of ensuring each decision is appropriate to the customer’s current journey stage. Like arbitration rules in Decision Strategy Manager, the event definitions in Event Strategy Manager can be subtle and complex. The system is also powerful in being able to connect to nearly any type of data stream, including social, mobile, and Internet of Things devices as well as traditional structured data.
I won’t go into details of other Decision Hub components, but they’re equally advanced. Companies with the scale to afford the system can expect it to pay for itself: in one published study, the three-year cost was $7.7 million but incremental revenue was $362 million. Pega says few deployments cost less than $250,000 and most are over $1 million. As I say, this isn’t a system for everyone. But it does set a benchmark for other options.