Due to the rapidly changing business environment and the increasing demands of consumers, traditional operational systems are failing to adapt or be flexible enough to apply analytical techniques that make the most of the vast amount of available data.
What amounts to “Big Data” varies greatly between enterprises but the fact is that most organizations don’t take full advantage of their exiting data, much less the tidal wave of Big Data coming from new data sources like social media. With decision management systems, organizations are able to take full advantage of all their data by seamlessly integrating the results of predictive analytics models and business rules, leveraging all their data, into their operational systems.
Decision management systems are adaptive, analytic and agile. Because they are services, they are by design adaptive, automatically learning from their successes and failures in order to constantly improve decisions. These systems also take the wealth of available data and analyze it to improve the quality of the decisions being made. New regulations and situations are a staple in all businesses, and these systems are agile enough to cope with rapid changes.
How Are Decision Management Systems Built?
The first step in creating a decision management system involves focusing on the operational decisions that are repeatable and have an impact on key business measures like customer satisfaction and retention, fraud prevention, risk management, compliance, turn-around time, and more. Once these decisions are identified and modeled using the Decision Model and Notation (DMN) standard, we build decision services that are delivered within the enterprise’s existing application architecture. The results are then monitored, analyzed and returned to the system in order to continuously improve its decision-making process.
Decision management systems were initially used in the finance industry to minimize fraud and risk, and are now rapidly being adopted by every known industry. These systems provide significant return on investment due to significant improvement in risk management, operational efficiency and customer responsiveness, boosting business performance across the board.
How Is It Different From Traditional Applications Or Processes?
While traditional approaches and business technologies still have a part in the creation of decision management systems, using these alone will result in systems that are difficult to adapt and are frequently inflexible. To truly make use of agile decision management systems that capitalize on Big Data, enterprises need to expand their current architecture to include Business Rules Management Systems (BRMS), Predictive Analytics and Data Mining and Optimization using the proven decision management approach. Decision Requirements Models based on DMN underpin the approach, and create the framework to deliver a powerful ROI on these technology investments.
Are you interested in ways that decision management can transform your business? Click here to connect with Decision Management Solutions for a free consultation.