Decision Management Systems: What Are They and When to Use Them?

on January 25, 2022

In this blog post, we introduce decision management systems for those who are new to them. First, we define decision management and decision management systems, Next, we cover the technologies that make up decision management systems. Then, we’ll give examples of use cases and the benefits they bring to the companies that use them.

What is Decision Management?

Decision management is a discipline and a set of technologies used to manage automated decisions in software applications and systems. With decision management, organizations treat the code responsible for making and executing decisions as a separate asset. We cover FAQs on decision management here.

Normative, Descriptive, and Prescriptive Models in Decision-Making

Broadly speaking, decision-making can be modeled in three ways. Descriptive models focus on what is by describing how decisions are made. Normative models focus on what ought to be by identifying optimal decisions under ideal or theoretical circumstances. Prescriptive models focus on what should be by prescribing the best decisions under real-world constraints. In general, decision management is concerned with operationalizing prescriptive models.

What are Decision Management Systems?

Decision management systems (DMS), also known as decision management suites (Gartner), digital or AI decisioning platforms (Forrester), decision management platforms, or decision engines are sets of technologies organizations use for decision management. DMS enable organizations to author, deploy, and manage decision logic. Our DMS, SMARTS™ Decision Manager, also provides tools for experimentation, real-time monitoring, building custom UIs, and more. Typically, DMS deploy decision logic as a decision service that can be invoked by other systems, processes, and services as needed.

What are the Underlying Technologies for DMS?

Specific technologies will vary from vendor to vendor (or organization to organization when they’re built in-house). However, most DMS will deliver the following capabilities:

  • Design/Authoring: An interface where users can author decision logic. SMARTS™ provides an easy-to-use graphical interface and supports multiple decision logic representations which can be combined. Representations include OMG DMN Decision Requirement Diagrams, decision tables, decision trees, decision graphs, point-and-click rules, scorecard models, lookup models, and machine learning models.
  • Storage/Versioning: A central repository which stores decision logic and other decision management assets. Most DMS, like SMARTS™, support versioning so that organizations can revert back to older versions when necessary as new business objectives and requirements arise.
  • Execution: An execution engine which runs decision logic in a live environment. SMARTS™ provides dedicated execution engines to optimize performance for each decision logic representation, including a compiled Rete-NT inference rules engine.
  • Monitoring: A log of events plus monitoring and auditing tools. For example, users can define real-time metrics, trigger alerts, and create visual reports in SMARTS™.

We address common questions about decision management technology in this post.

What are Decision Support Systems?

Decision support systems (DSS) are sets of technologies that support human decision-making. They provide tools to capture and analyze data. DSS include knowledge-based systems or expert systems. For example, in healthcare, a clinical decision support system can assist in medical diagnosis. The DSS proposes possible diagnoses based on patient data and its knowledge base of diseases and symptoms. Physicians then apply their own expert knowledge and experience to the possible diagnoses to come up with the right diagnosis.

What’s the Difference Between a DMS and a DSS?

The primary difference between them is that DMS focus on automating decisions while DSS focus on streamlining decision-making processes. In other words, the output of a DMS is usually an action, while the output of a DSS is usually an insight. In addition, businesses generally use DMS for more routine and repeatable decisions while they DSS for more strategic and less frequent decisions. However, there are exceptions and more overlap as DMS and DSS evolve. For example, a hospital can also use DMS for clinical decision support.

Where are Decision Management Systems Most Commonly Used?

Decision management systems work best with day-to-day operational decisions, usually in high volume and frequency, that are guided by formal laws, industry regulations, company policies, and business strategies. They are not suitable for mid to long-term decisions that companies make once a year or a quarter or decisions where high levels of uncertainty are involved. Here are common use cases:

  • Insurance organizations can use DMS for quoting, underwriting, and claims processing.
  • Banking or financial services organizations can use DMS for KYC and AML, fraud detection, and loan origination.
  • Healthcare organizations can use DMS for health risk assessment, benefit eligibility, and device monitoring.
  • Retail organizations can use DMS for invoicing, logistics, and merchandising.
  • Manufacturing organizations can use DMS for product configuration, pricing, and inventory management.

Many of our customers use SMARTS™ for fraud and credit risk management, automating thousands up to millions of transactions everyday.

What are the Key Benefits of Using Decision Management Systems?

Decision management systems have several benefits:

  • Separation of Decision Logic: DMS allow business analysts and domain experts to manage decision logic independently of the business systems that use them. Organizations can reduce IT and development costs that would have been necessary to code, implement, and maintain decision logic directly in the business systems. Decision management can operate on its own lifecycle rather than go through the standard software development lifecycle.
  • Consistency, Scalability, and Ease of Maintenance: The centralized repository of DMS enforces consistency across the systems that use the decision logic, makes it easy to apply existing decision logic to new systems, and simplifies maintenance.
  • Transparency: As decision logic is made explicit and events are logged in DMS, organizations can explain decisions, monitor performance, and audit decision logic execution for compliance and further analysis. As a result, organizations can reduce the risk of errors and biases in automated decision-making.

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Sparkling Logic Inc. is a Silicon Valley-based company dedicated to helping organizations automate and optimize key decisions in daily business operations and customer interactions in a low-code, no-code environment. Our core product, SMARTS™ Data-Powered Decision Manager, is an all-in-one decision management platform designed for business analysts to quickly automate and continuously optimize complex operational decisions. Learn more by requesting a live demo or free trial today.