Feature Adoption Best Practices

This video provides a brief overview of Pega best practices for feature adoption for Pega Customer Decision Hub™. Develop best practices in each of the organizational transformation areas based on deep product knowledge and years of delivery experience with businesses across the globe. This amalgamation of effective strategies helps organizations make the best of their Customer Decision Hub implementation. There are two main aspects of best practices for feature adoption:

1. An organization must have an established process to sustain a successful technical and business transformation and continue to add value to its business by continuing to use the best features and latest developments from Customer Decision Hub. This process should be feasible and future-proof.

2. Based on extensive experience working with organizations, there are a few features that are top considerations when it comes to adoption if not already in use. As a consultant, you must prepare to explain and enable organizations on these features.

Begin by exploring the feature adoption process. This best practice is crucial for tailoring the adoption process to the specific needs of each organization to ensure that they can continually take advantage of the latest features in Customer Decision Hub.

The feature adoption process consists of three key steps: Understand, Select, and Adopt.

Step 1: Understand
• Gain a comprehensive understanding of available features in Customer Decision Hub. The Lead Decisioning Architect (LDA) and the Head of 1:1 Customer Engagement or Product Owner of the Pega Customer Decision Hub application lead this task. Use resources such as Pega Documentation and the Pega Customer Decision Hub Community page.

Step 2: Select
• Identify gaps in current processes and select features to be adopted. The LDA and the Head of 1:1 Customer Engagement/Product Owner of the Customer Decision Hub application lead this step. Evaluate potential features based on impact on business operations, alignment with strategy, feasibility, effort required, and both business and technical needs.

Step 3: Adopt
• Adopt the identified features. The Head of 1:1 Customer Engagement, along with the LDA and the capabilities team, lead this process. Plan and prioritize in the Governance Forum to ensure that the implementation follows best practices. Fully integrate new features into business processes to maximize their impact.

Understanding available features is critical. The Lead Decision Architect, in collaboration with the Head of 1:1 Customer Engagement, should explore Pega Documentation and Pega Community pages and subscribe to events such as Pega Customer Decision Hub Community Events and PegaWorld to stay up to date. Pega consultants and/or the Customer Success Manager (CSM), Account Executive (AE), and Solution Consultants (SC) can support by elaborating on features and providing further resources from Pega

Select the features most beneficial to the specific needs of organizations. The Lead Decision Architect and the Head of 1:1 Customer Engagement, supported by Pega consulting, if engaged, should prioritize features based on relevance to the business objectives of the organization, technical feasibility and effort.

Align features with the overall strategy, considering business and technical needs, feature maturity, and effort required for implementation. Questions to ask include: What are you trying to optimize? What is the objective? Are you aiming to expand product lines or customer segments or improve transparency in the performance of Customer Decision Hub

Identify potential features required by mapping them to the business operations process. Review your business-as-usual workflow and compare it to the best practice process.

Ask yourself the following questions: Does your existing process include all the key steps, and does the appropriate Customer Decision Hub support these features? For instance, to plan, build, and test changes, are you enabling the business-as-usual (BAU) users to handle change requests across various channels, validate changes, and deploy them into production at a fast pace that fits the business needs? If the answer is no, evaluate 1:1 Operations Manager.

During the last stage of Review and Optimize, after deploying new Actions and Treatments into production, are you reporting and monitoring the overall performance of Customer Decision Hub effectively? Impact Analyzer is a great tool for doing that by default. If any steps can be improved or added, it might indicate a feature gap that requires attention.

Adopt the selected features. The Head of 1:1 Customer Engagement leads this step, supported by the LDA, the enterprise capabilities team, and Pega consulting if engaged. Plan and prioritize in a Governance Forum, ensuring implementation follows best practices. Apply new features, including changes to people and processes, to sustain the benefits.

Common features and tools can significantly enhance the organization's use of Customer Decision Hub, which helps ensure that it maximizes the value of its investment. For the latest details about these features, see Pega Documentation.

Next-Best-Action customer journeys in Customer Decision Hub increase the relevancy of predictions by using customer journey stages. This feature integrates customer journeys with one-to-one customer engagement, which enables marketers to map out true customer journeys powered by decisioning capabilities. It is not a prescriptive path tool but aligns Next Best Actions with the customer's journey dynamically.

The Business Operations Environment (BOE) is essential for simulating and optimizing decision strategies with production-level data by supporting different change types and proactively optimizing business outcomes. This environment allows for realistic testing, managing different change cadences, and proactively identifying under-served customer groups with tools such as Value Finder.

After the data migration pipeline is in place, there are three main ways that users can use the BOE environment:

1. Because production-like data is available, testing is closer to real life; great simulations and tests are available.
2. Support different pipelines for the project versus business-as-usual changes to manage the difference in the cadence of change for business-as-usual compared to longer-term project changes safely and easily. Tools such as 1:1 Operations Manager enable less technical users to implement simple changes safely.
3. Use simulations to brainstorm ideas or run Value Finder to identify under-engaged customer groups. Then, proactively develop new actions to better engage with them.

1:1 Operations Manager is an agile change management tool alongside Customer Decision Hub that streamlines the process of submitting, prioritizing, and managing change requests. With this tool, business users can handle change requests across various channels, validate changes, and deploy them into production efficiently without overwhelming the quality assurance process.

Intelligent Treatments is a feature that uses generative AI to create and refine Next-Best-Action treatments. The AI creates this content by using diverse tones and perspectives to ensure empathy is maintained. Intelligent Treatments can help create content for these conversations, and then scale them rapidly.

Next, explore a few simulation tools.

Value Finder is a powerful tool in Customer Decision Hub that helps users identify and profile under-served customers. By understanding which customer segments are less engaged, businesses can adjust their engagement strategies to meet these customers' needs better. This tool helps in closing communication gaps, thereby improving overall customer satisfaction and business results.

Scenario Planner simulations allow you to understand the performance of your decision framework better. It helps ensure that strategies deliver desired results, which impacts the right KPIs by exploring how close the simulation results might be to meeting the expected targets of stakeholders. Compare two simulations side by side, one before and one after a change, and draw out key performance changes, such as change in cash revenue and change in projected responses.

Audience Simulation in Next-Best-Action Designer helps users simulate the impact of changes to their Next-Best-Action strategies and view customer distribution at each level of arbitration. This tool is useful for understanding how different engagement policies can affect customer behavior by providing detailed insights into the decision framework's performance.

Distribution tests enable you, as a consultant, to understand the distribution of actions across a selection of customers, such as the number of times that the system selects particular Actions as the Next Best Action for a particular group of customers. By running preconfigured reports, you can see the distribution of Actions across your customer base. Visualize if you have the right reach or spread. Understand how the introduction of a new Action affects reach overall. Is there any dilution of the reach of other Actions as a result? Will the new Action reach the proportion of customers that you expect?

Despite the best intentions of organizations, bias related to factors such as age, ethnicity, or gender can unintentionally creep into a Next-Best-Action strategy and skew the outcomes. This bias can result in regulatory violations, discriminatory customer engagements, and even a loss of public trust. Ethical Bias Check provides a way to proactively detect bias in Next-Best-Action strategies and then adjust the offending algorithm or business rule accordingly to provide a more balanced and ethical outcome for everyone.

Next, explore some of the reporting tools in Customer Decision Hub.

By default, Action Performance Tracker provides a report that automatically tracks how each of the Next Best Action is doing on a day-to-day basis, and then proactively alerts if something goes wrong, such as whether the system is displaying a new Action enough or if acceptance of an Action drops dramatically. This feature is geared towards specific KPIs and is interactive and useful to users with an operational focus. Run in Production or BOE.

Impact Analyzer helps users continuously test Next-Best-Action health and show stakeholders that the system is working the right way and creating value. It automates a series of test and control tests that show the lift in customer engagement and customer value, the effectiveness of models and Rules, and the sources of value. It also evaluates the performance of Adaptive Models and the lift achieved from machine learning, which is important to the analytics users, who are key stakeholders.

You have reached the end of this video. What did it show you?
• The importance of feature adoption for Customer Decision Hub adoption.
• Key stakeholders and their roles in the transformation process.
• Effective means of communication for enablement, workshops, and one-on-one activities.
• The timeline for addressing feature adoption during minimum lovable product (MLP) delivery.
• Key tasks and methodologies for feature adoption in an MLP.