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How to implement Pega Customer Decision Hub using the Pega Express™ delivery approach: The Prepare phase

Tim Odeh, 5 minute read

This is the third blog in a series that dives deeper into how to implement the Pega Customer Decision Hub, end to end, and in the right way. 

A Pega Customer Decision Hub™ project consists of four phases: Discover, Prepare, Build, and Adopt. This post covers the Prepare phase.

In an earlier post in this series I covered the Discover phase, elaborating on the Solution Alignment Workshop – an artifact that lets you verify a selected scope and business outcomes, as well as the project planning and setup of project teams. 
 
Now, to create real value, we need to dive a bit deeper into how to technically prepare the application. At the end of this phase, you are ready to implement genuine business use cases in the Pega Customer Decision Hub. 

In many of my scoping presentations and implementations, I use a simplified analogy to explain three phases in the Pega Express delivery approach (Prepare, Build, and Adopt):  

Prepare: “What the box stands on.” This involves setting up the system and being ready to configure your use cases. 

Build: “What you put in the box.” This involves configuring your use cases using Next Best Action Designer. 

Adopt: “The people who manage the box." This involves the processes and organization that allow you to run the Pega Customer Decision Hub. 
 
This post is about “setting up the box,” which consists of several tasks: 

  1. Sorting out your cloud infrastructure and applications 
     
  2. Preparing your best practice analytical data model 
     
  3. Setting up integrations with external applications and databases 

Sorting out your cloud infrastructure and applications

Pega helps you sort out your infrastructure and applications long before the project starts. We have come a long way since our on-premises implementations and now provide a Pega cloud-as-a-service approach to application provisioning. You need to discuss specific Decisioning metrics in advance with your Pega Business Officer to allow you to size and scale your application.  

In terms of application environments, the following are required for a “standard” Pega application:

Environment 

Cloud Instance 

Description 

Development 

Standard Sandbox 

Development, testing, and user acceptance testing 

Staging 

Large Sandbox 

Pre-production, staging, user acceptance testing, and/or limited performance testing 

Production 

Production 

A scaled environment that supports the production deployment of Pega Platform™, applications, and transactional use cases 

Specific to the Pega Customer Decision Hub, Pega Cloud Services will provide an added environment: the Business Operations environment. This environment allows you to simulate the offers that your decisioning engine would suggest, enabling you to test the decisioning recommendations you’ve configured. 

With a Pega Customer Decision Hub implementation, there are two things you need to consider from a data storage point of view:

  1. The standard cloud data storage that gets shipped with your Pega environment will be used to house specific Pega Customer Decision Hub data as well. Specifically, Interaction History and the Pega Customer Movie.  
     
  2. You must request an added datastore (called the Decision Data Storage). This added datastore, which the Pega application manages, is used by the Pega Customer Decision Hub to store recoding decisions that are used by the Adaptive Decision Manager (ADM) module. 

More detail about how Pega provides its cloud services can be found here. 

Once they have provisioned the environments, Pega’s Global Service Assurance team will onboard the client, including environment handoff, explaining the subscription services included in the agreement, how to work with Global Client Support, etc., after which the Pega Deployment Architect (typically a Lead System Architect and/or a Lead Decisioning Architect) can perform application configuration and integration.

Preparing your best practice analytical data model 

Now that we have our environment and application details available, we need to configure the data model. You must perform a data workshop to map customer data requirements against the best practice analytical data model. Again, we don't want to reinvent the wheel. Instead, we want to provide a standard model for your industry to start with that you can map to your own data sources. This data model is mapped against the standard logic template and you can extend it based on customer needs. The details for this are described here in the Minimum Lovable Product backlog. 

Setting up the integrations with external applications and databases 

Lastly, we need to connect the box up to the various sources and channels.  

This is based on your Microjourney scope, but will invariably include integrations to a content management system, various browser-based web and mobile application integrations, a contact center application, a DMP, a web analytics tools like Adobe or Google Analytics, or even a campaign management tool. For the majority, open API standards apply, and Pega created a set of standard integrations to the most common applications. 

For data source integration, three types of data sources apply: Streaming data, unstructured data, and structured data. For each, standard integration protocols apply.

Channel integration protocols typically consist of the following two steps: A request for a Pega Customer Decision Hub decision (GetNBA) and a response to this request (GetResponse). Below, you see the various options that may apply for your business. 

Detailed best practice integration patterns are described in the Reference Infrastructure Architecture page

So, we've progressed again! Now we're ready to start building out our use cases as part of the Build phase and we're ready to drive real value. If you want to know how, keep following my blog series and check out our recommended resources for detailed information on each of these topics. 

In upcoming blogs we’ll continue to dive deeper into the changes that need to take place across people, processes, and technology for an organization to experience the incredible business benefits of a Next Best Action engagement approach.

Recommended Resources: 

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About the Author

In his position as Pega’s director for business excellence, Tim Odeh helps leading global organizations apply AI in innovative ways to engage more effectively with customers, increase revenue, and drive operational transformation. 

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