Pega streamlines digital transformation

Pegasystems has introduced the latest evolution of its Pega Infinity™ software suite to help speed and simplify digital transformation (DT) initiatives. With enhanced low-code, intelligent automation, and AI capabilities, Pega Infinity version 8.6 empowers business users to deliver differentiated user experiences with powerful development capabilities that deliver DT at scale for even the largest and most sophisticated global enterprises.

The need for DT today is unavoidable: according to Gartner, nearly 70 percent of boards of directors reported that the pandemic and economic challenges are fast-tracking digital initiatives – with worldwide IT spending expected to reach $4 trillion in 2021. But despite this pent-up demand and massive spending, there’s still no guaranteed recipe for DT success. These far-reaching initiatives are often threatened by siloed projects, disconnected systems, and complicated deployments that slow time to value and miss expectations. 

The new version of Pega Infinity helps businesses crush the deep complexity that stands in the way of successful DT with a Center-out™ approach. The latest enhancements help improve back-end process efficiencies, streamline front-end customer service processes and interfaces, and enable real 1:1 customer engagement to drive meaningful and lasting transformation. With the speed, scale, and flexibility of Pega Infinity, employees can work smarter to drive impactful outcomes, while end customers can enjoy faster, easier, and more personalized experiences that help increase customer satisfaction and loyalty.

Available by the end of this quarter, Pega Infinity 8.6 will feature new enhancements to Pega Platform™, Pega Customer Service™, and Pega Customer Decision Hub ™ that enable business leaders to:

• Accelerate time to market with new app development, design, and process orchestration capabilities for both professional and citizen developers in Pega Platform, such as:

o Easy-to-design UIs – New low-code capabilities in Pega Platform help enable both professional and citizen developers to easily design exceptional modern user interfaces for their apps. By complementing enhanced front-end design features with proven back-end processing abilities, Pega empowers enterprises to create sophisticated yet simple user experiences on a single low-code platform. For more detailed information, click on our companion announcement released today.

o Self-optimizing AI-powered process optimization – Pega Process AI brings Pega’s market-leading AI and decisioning capabilities together with Pega’s low-code process automation software to help organizations optimize their business and customer operations in real time. This native combination of intelligence and automation delivers the only solution that can self-optimize and intelligently triage millions of incoming customer requests, transactions, and other events at enterprise scale. This helps enable fast and effective event resolutions while helping lower operating costs and simplify employee and customer experiences. For more details, click on our previous announcement on this feature.

o Workflow orchestration across applications – Previously on a limited trial basis, Pega Process Fabric® becomes available to all users so employees can manage their work in a single location. This helps them work smarter by providing a unified worklist that consolidates tasks from multiple apps – both Pega and non-Pega – in a single location. AI helps ensure the most important work gets top priority. This interwoven and intelligent view of work eliminates inefficient screen switching while providing better visibility and insight into critical customer needs. 

• Simplify customer service with new streamlined capabilities in Pega Customer Service such as:

o   Enhanced channel choice: Pega has extended its advanced messaging capabilities into its flagship Pega Customer Service Digital Customer Engagement Edition. This helps allow more businesses to give their customers additional control over how and where they communicate with them. For example, a customer can initiate conversations in their preferred channel - including web messaging (chat), SMS, and third-party messaging apps such as WhatsApp, Facebook Messenger, Twitter, and Apple Business Chat – via a single messaging widget embedded on the client website and switch between channels without disrupting the conversation.

o   Expanded Microjourney™ offerings: New Microjourneys for the financial services, insurance, and communications industries provide preconfigured service cases that help efficiently and intuitively resolve common service incidents for customers. These new microjourneys complement a library of over 180 preconfigured service cases available for Pega Customer Service.

o   Simpler feature configurations: New enhancements help allow business and IT managers to quickly configure and manage even more Pega Customer Service functions – such as intelligent virtual assistants, search, and customer verification. Updates are now more easily configured using Pega’s powerful low-code capabilities in Pega’s App Studio.

• Deliver more personalized engagements faster with new AI features for marketers and data scientists in Pega Customer Decision Hub such as:

o   More relevant real-time engagement: New capabilities in Next-Best-Action Designer empower marketers to modernize customer journeys and add context to their next-best-action decisions. Now users can map all actions and treatments to specific journey stages, then use data from each customer’s journey as predictors that inform their decisioning models. Taken together, this helps improve the relevance of every interaction with that customer in real time.

o   Automated AI model management: New Machine Learning Operations (MLOps) capabilities give data scientists an automated, end-to-end process for deploying, updating, and replacing the models used in their next-best-action decision strategies via Pega APIs. Plus, with Shadow Mode, users can compare the performance of the current model to the candidate model using real production data prior to deployment to ensure it will deliver the expected lift.