Decision management
What is decision management?
Decision management applies technology to data, algorithms, and predefined rules in order to make informed decisions in the moment during interactions with customers or users. These decisions are often related to determining the "next-best-action" or response based on the specific context of the interaction and the individual's preferences or needs.
Why is decision management important?
Decision management enables organizations to deliver more tailored and effective interactions with their customers, prospects, or users, ultimately enhancing engagement, satisfaction, and outcomes. These dynamic, relevant interactions create lasting customer relationships, increasing customer lifetime value.
Benefits of decision management
- Optimize resource allocation. Because decisions are based on data and insights from real customers, users can better allocate resources to only the channels and tactics that make an impact.
- Improve conversion. By analyzing customer data and behavior, decision management increases the likelihood of engagement and conversion by accurately reaching only the intended audience.
- Drive loyalty with better personalization. Tailoring messages, offers, and experiences to the specific needs and preferences of individual customers enhances engagement and loyalty.
- Connect in real time. Never miss an opportunity to connect by analyzing data and making decisions in real time. Users can quickly adapt strategies and tactics based on changing market conditions, customer behavior, or performance.
How does decision management work?
Technology analyzes inputs like customer data, historical interactions, current behavior, and contextual information to generate personalized and relevant responses or actions or dynamically adjusts the interaction flow based on real-time feedback or changing circumstances.
Analyst Report
According to the Forrester Report, “Pegasystems dominates enterprise RTIM with its focus on customer-first business value.”
Key components of decision management
Decision support
Tools and capabilities that help users make informed decisions based on data and insights like predictive analytics, data visualization, and reporting functionalities.
Decision automation
Implementing systems and processes that automate routine decision-making tasks based on predefined rules or algorithms like marketing campaigns triggered by specific customer behaviors.
Decision optimization
Utilizing advanced AI algorithms to optimize complex decisions to achieve the best possible outcomes.
Decision execution
Enabling the seamless execution of decisions across various engagement channels and touchpoints, ensuring consistency in messaging and customer experiences.
The main challenges of decision management
The challenges associated with decision management require a holistic approach that encompasses people, processes, and technology, as well as a commitment to ongoing learning and adaptation to innovation and changing business environments.
Benefits of decision management
- Data quality and accessibility: Decision management relies heavily on data, and ensuring data quality and accessibility can be challenging due to data silos, inconsistent data formats, and incomplete or inaccurate data, which can hinder the effectiveness of decision-making processes.
- Integration of systems and data sources: Decision management often requires integration with various systems and data sources across the organization, such as CRM systems, marketing automation platforms, and data warehouses. Integrating these disparate systems and sources can be complex and time-consuming.
- Change management: Implementing decision management initiatives requires changes to existing processes, systems, and organizational structures. Stakeholders who are accustomed to traditional decision-making methods may be slow to adopt.
- Privacy and compliance concerns: Collecting and analyzing large amounts of customer data raises privacy and compliance concerns. Organizations must ensure that they comply with relevant regulations and implement robust data governance practices to protect customer privacy.
Product
Personalize every interaction across every channel – all in real time.
What are some use cases for decision management?
Every industry has unique challenges and opportunities. Decision management helps organizations across industries adapt to shifting trends, evolving customer needs, and changing regulations.Financial Services
Deliver a personalized approach to banking and financial services by presenting the right sales, service, or retention interaction at the right moment. Help clients build financial resilience and loyalty to your brand with empathetic customer experiences.
Communications
The communications landscape changes fast. With centralized decision communication, service providers can achieve fast time to market, meet customer expectations, reduce churn, and take control of complex systems and product portfolios.
Healthcare and Life Sciences
Improve loyalty, reduce costs, and break down barriers to simplified, personalized, satisfying member experiences. Engage patients by connecting systems and simplifying access. Improve results by automating processes, modernizing operations, and personalizing engagement.
Insurance
Identify in-market customers and trigger contextual offers automatically in-channel. Empower agents with real-time retention recommendations they can use when customers call in to cancel a renewal or policy. Find patterns that help identify customers who are likely to need service and reach out proactively using messaging tailored to the individual and situation.
How to implement decision management in the enterprise
Evolving traditional, functional, and organizational structures requires a staged approach. Ideally, adopting decision management technology occurs agilely, and roadmaps are developed for each opportunity as the organization works to transform at a pace that suits them.
- Implement AI-powered technology to sit at the center of all brand channels and functions as a central brain to unify customer data and make decisions quickly.
- Enable channels in a phased approach starting with IVR and customer service channels, move to integrating inbound channels, then focus on outbound.
- Establish a governance team – a collaboration between leaders to establish priorities, adapt big-picture strategy, and monitor progress against high-level organizational goals.
- Restructure and upskill your execution team to be a centralized cross-functional team, which controls the tactical implementation of the goals, objectives, and priorities established by the governance board.
- Develop a process that defines configurations, testing, and simulations, which are required to ensure that the right offers are in market as quickly as possible. Establish a continuous feedback loop between governance and execution to secure alignment across the organization.
Frequently Asked Questions about decision management
Decision management improves efficiency and accuracy by automating routine tasks, leveraging data analytics, standardizing processes, optimizing resources, and enabling real-time decisions.
A decision management system typically includes components such as business rules management, predictive analytics, optimization models, and decision automation. These components work together to capture business logic, analyze data, optimize decision outcomes, and ensure consistency and efficiency in the decision-making process.
AI boosts decision management by enhancing data analysis, automating routine decisions, predicting outcomes, personalizing customer interactions, enabling real-time decision-making, and improving risk management.
