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Decision management

Suggest edit Updated on May 28, 2021

Make real-time decisions among thousands of potential choices by using decision management supported by machine learning.

Decision management features

With decision management, you can enhance your applications to help you predict customer behavior, optimize business processes, analyze natural language, and make informed decisions to better meet your customers' needs and achieve positive business outcomes.

The following features represent the decision management capability:

Decision strategy

Create comprehensive decision strategies to improve customer experience in every channel and deploy intelligent processes based on real-time, actionable insight into operational and behavioral data.

Data sets

Configure the data sources for storing your customer and analytical data. Data sets define collections of records and the means to write and read the data used in your decision strategies.

Data flows

Ingest, process, and move data from one or more sources to one or more destinations by creating data flows, which are scalable and resilient data pipelines.

Adaptive analytics

Predict customer behavior by using self-learning models. Use adaptive models in your decision strategies to increase the relevance of decisions.

Predictive analytics

Address your customers' needs by predicting customer behavior and business events. For example, you can determine the likelihood of customer churn, or chances of successful case completion.

Natural language processing

Effortlessly analyze and extract meaningful information from large volumes of text with the use of text analytics. Based on your findings, you can further improve business performance and customer experience.

Decision management products

Decision management is a Pega Platform capability. You can apply the decision management capability to your domain through licensing various Pega products.

Pega Customer Decision Hub

The most widely used decision management-based solution for one-to-one customer engagement that is designed to make next-best-action decisions for your customers. Pega Customer Decision Hub provides you with a best practice pattern that is based on how the industry leaders design their one-to-one customer engagement systems.

For more information, see the Pega Customer Decision Hub product page.

Pega Customer Service

The Pega Customer Service application uses the natural language processing capability of decision management for email routing. For more information, see the Pega Customer Service product page.

Pega Sales Automation

The Pega Sales Automation application uses decision management to predict the likelihood of an opportunity closing. For more information, see the Pega Sales Automation product page.

Pega Process AI

The Pega Process AI offering uses artificial intelligence and decision management features to create self-optimizing business processes. In Case Designer, you can use predictive models anywhere in a case to predict various case outcomes and route work based on predictions. For example, you can use AI to distinguish between complex and regular insurance claims, and route the regular claims for straight-through processing and the complex claims to experienced employees. For more information, see Introducing Pega Process AI and Pega Process AI.

Note:

Although you can build a deterministic decision-making logic into an application in Pega Platform with such functionality as decision tables, a standard Pega Platform license does not cover the use of the underlying decision management features, such as Decision Strategy Manager, Event Strategy Manager, or Prediction Studio.

What to do next

Explore the following topics to learn how to configure and use decision management features in your system:

  • Getting started with decision management

    Manage your company's customer interactions to deliver the right message, the right offer, and the right service at every level of the customer experience. With Pega Platform and the Next-Best-Action, you can tailor your decision management strategy to suit each of your customers, to deliver consistent quality across all channels.

  • Storing customer and analytical data

    After enabling the key decision strategy management services, configure the data sources for storing your customer and analytical data.

  • Processing data with data flows

    Data flows are scalable and resilient data pipelines that you can use to ingest, process, and move data from one or more sources to one or more destinations.

  • Reacting to real-time events

    Configure your application to detect meaningful patterns in the real-time flow of events and to react to them in a timely manner. By detecting event patterns through Event Strategy rules, you can identify the most critical opportunities and risks to help you determine the Next Best Action for your customers.

  • Improving customer experience by creating next-best-actions

    When your offers, business rules, and data sources for your decision framework are ready, gather all that data in decision and response strategies.

  • Predicting customer behavior

    Harness the power of artificial intelligence and machine learning to drive your business results by managing adaptive, predictive, and text analytics models in Prediction Studio.

  • Analyzing natural language

    Effortlessly analyze and extract meaningful information from large volumes of text with the use of text analytics. Based on your findings, you can further improve business performance and customer experience.

  • Simulating next-best-action changes

    To interpret how the strategies that you configure control the decision funnel, simulate the decision process and assess how your changes influence strategy results.

  • Managing business changes

    Use revision management to make everyday changes to, for example, the description or expiry date of a product, or even small changes to the risk score calculation.

  • Troubleshooting decision management components

    You can troubleshoot and resolve commonly encountered problems or errors with decision management components. Each problem or error is accompanied by a description, a cause, and a suggested solution.

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