Call to Action

Webinar: Take a tour of Sparkling Logic's SMARTS Decision Manager Register Now

The ten most frequently asked questions about decision management


Written by: Hassan LâasriPublished on: May 17, 2022No comments

Decisions are at the core of every organization, be it a Fortune 100 company, a start-up, or a governmental agency. In this blog post, we provide answers to the ten most frequently asked questions about decision management.

1) What is decision management technology?
There are two types of decision-making technologies. The first are descriptive in that they implement how people make choices among alternatives based on their beliefs and preferences. The second are normative in that they implement regulations, policies, or strategies regardless of the beliefs or preferences of those who follow the decisions. There is no single definition that differentiates the two technologies. But there is a consensus to name the second decision management. So, when you hear or read someone referring to decision management, think of technologies implementing formal laws, industry regulations, company policies, and business strategies.

2) What is the difference between business rules and decision management?
Business rules implement industry regulations, business policies, or subject matter knowledge in the form of if-then statements or conditional action procedures. To execute, a rule engine checks all the predicates/conditions and fires the statements/procedures. To select which statement to add or procedure to run, the rule engine relies on heuristics that are part of the industry regulation, business policy, or subject matter.

Decision management is more than that. Behind the terminology of decision management, we would find multiple technologies. The simplest are decision tables, trees, and graphs. The most sophisticated combine business rules and predictive models. If we take the example of SMARTS, it integrates eight decision engines into the same platform. Depending on the problem at hand, one may choose one or the other, or even combine them in the same set-up.

3) What types of decisions do decision management technologies automate?
Like any technology, decision management technologies are not a one-size-fits-all solution for every decision problem. They are not suitable for long-term or midterm slow decisions that companies make once a year or a quarter. In these cases, optimization technologies are more used. They are not also suitable for cases with uncertainty and where probabilistic technologies such as probabilistic graphical models are used.

Decision management technologies are best suited when there is a substantial number of decisions and calculations that are often nested, often invoked, and likely to change often. Therefore, one must consider a decision management product for the operational and day-to-day decisions that companies make in the thousands and sometimes millions in a single day.

4) In which industries are decision management technologies primarily used?
Decision management technologies are primarily used by companies working in highly regulated industries such as financial services, insurance, and healthcare. They allow the implementation of legal requirements in the nervous system of companies, in front-, middle- and/or back-office. But you can find them in other industries such as telecommunications for network, service, or customer management, in retail for product recommendation, and even in media for content personalization.

5) For what applications are decision management technologies used?
Although not dedicated to finance, insurance, and healthcare, decision management technologies are widely used for loan origination, risk management, fraud detection, and money laundering prevention. These are typically cases where organizations make decisions and calculations thousands and sometimes million times a day and may change based on the market dynamics or global economy, or updates to regulations or business strategy.

Decision management technologies can also be used for data transformation as a better alternative to scripting languages to move, unify, and enrich data from one layer to another of a data platform or marketplace. In fact, decision management technologies can be used to automate every complex non-linear process such as the ones we find in product configuration or condition-based diagnosis.

6) Who are the users of decision management technologies?
The users of modern decision management systems are not IT people but businesspeople. So, they come with features that allow non-specialists to use them without IT intervention. With modern decision management systems, IT only takes care of the first installations and configurations, the systems come with everything necessary to ensure the governance and security of the applications developed as well as the ease of integrating them into the corporate IT architecture. If we take the example of SMARTS again, it comes with an easy-to-use graphical authoring interface, pre-deployment rule testing, rule repository with version control and rollback, large-scale simulation, real-time decision performance monitoring, and much more.

7) How is decision management related to data analytics?
There are three types of data analytics. First, descriptive analytics that allows companies to get a status of how they are performing against their goals. Then, predictive analytics whose scope of analysis is no longer just on what had happened in the past months and years, but on what might happen if there are no significant changes in industry regulations, market dynamics, and company strategy. Then, prescriptive analytics that transforms insights from both descriptive and predictive analytics into decisions and actions with the support of decision management technologies. In this sense, decision management technologies operationalize data analytics.

8) Is decision management data-based or knowledge-based?
The “data vs. knowledge” debate is an old debate about whether knowledge about a subject should be hand coded or machine learned. A first camp of researchers and practitioners sought to encode this knowledge in the form of rules and an inference engine that runs on these rules to supply answers to user questions. A second camp sought to develop programs that learn from available data using statistical methods to generate models that can make predictions from unseen data. At Sparkling Logic, we support a pragmatic approach that consists in using data, knowledge, or both depending on the problem and the situation at hand.

9) What are explainable or understandable decisions?
As more and more of our personal, professional, and social activities are managed by data and algorithms, bias and discrimination become a big concern for companies, particularly those operating in highly regulated industries such as credit, insurance, and healthcare. Decisions, whether for eligibility, pricing, recommendation, or personalization must be understood by all the stakeholders —not only by the business, credit, or risk analyst, but also by the customer-facing businesspeople and the customer. SMARTS’ latest version, Vienna, implements understandable decisions through additional visual features that go beyond intuitive business rules writing. For instance, users can use the play-by-play feature to watch the decision happen before their eyes while refining the expected behavior.

10) How do decision management technologies avoid bias?
In our vision, one of the best ways to reduce biases, is to make decisions explicit (like the rules of laws) so that those who implement the decisions can test them out, one at a time or in groups, and visualize their outcomes in dashboards. Business rules with dashboards help to detect the consequences of decisions before putting them into production. Decisions should be kept separate from the rest of the system calling those decisions — the CRM, the loan origination system, the credit risk management platform, etc.

About


Sparkling Logic is a company at the forefront of technological innovation in decision management. We help businesses automate their operational decisions with a powerful decision management platform, designed for business analysts first.

Our motto is “your decisions, our business.” Using SMARTS, organizations have automated complex decisions in days, not weeks, or months. Our mission is to enable customers to implement the most demanding decisioning requirements and to easily maintain and improve them over time.

Sparkling Logic SMARTSTM (SMARTS for short) is a decision management platform that enables creating, testing, deploying, and improving automated data-based decisions in an integrated easy-to-use environment.

Unlike other tools that focus solely on the authoring and maintenance of business rules, SMARTS is decision-centric and focuses on measuring and improving business outcomes in the context in which our clients work, especially with complex regulations.

If you envision modernizing or developing a decision management application, we can help. Just contact us or request a free trial.

Call to Action

SMARTS Decision ManagerSparkling Logic SMARTS is a decision management platform that empowers business analysts to define decisions using business rules and predictive models and deploy those decisions into an operational environment. SMARTS includes dashboard reporting that allows organizations to measure the quality of decisions both during development and post deployment. Learn more about how SMARTS can help your organization improve decisions.
© 2023 SparklingLogic. All Rights Reserved.