Automated decision-making has revolutionized the way companies operate with less human intervention. As a result, managers and subject-matter experts can spend their time on more complicated tasks.
Decision engines lie at the heart of this digital transformation.
A decision engine uses input data and business rules to make decisions. This tool works best for decisions that need to be made often, accurately, and instantly.
What is a Decision Engine?
A decision engine is a customizable rules-driven solution that can run automated decisions using business rules created by the user. That means that decision engines can be set up in such a way to automatically make business decisions without having to rely on input from users.
A decision engine is a term that represents logic, often in the form of a rules flow, decision trees, or decision tables that can manage and automate decisions. Most decisions that provide business value tend to be complicated and composed of a sequence of smaller decisions.
Examples of Decision-Making
As companies gather more information from various data sources about consumers' preferences, decision engines can help them form closer relationships with their customers by offering personalized products or services. For example, a travel agency can install a decision engine on their website to show new and interesting travel destinations to specific visitors.
So, if a customer who exclusively buys holiday packages in the Caribbean is looking to go on a holiday, the website will place holiday packages in other destinations farther down the results page.
A decision engine can also be set up as a filtering system. For instance, if a customer were interested in purchasing a car online, the website could ask a series of binary questions in order to specify the particular criteria and refine the search results.
So, for example, there would be questions related to whether the user wants two or four-wheel drive, convertible, horsepower, and so on.
Different Ways to Express Decisions
Business decisions can be expressed as functions, business rules, decision tables, and decision trees.
Functions enable users to implement any business logic they need by writing code snippets in a tool-specific language.
Business rules are "if-then" conditional statements that outline how business applications should behave under certain conditions. Rules determine what an organization can and cannot do.
Business rules help carry out decisions that relate to business' pricing, product features, business model, and communication with customers.
They play a crucial role in helping to run day-to-day operations in companies but can also express various laws, best practices, business needs, and regulations.
A decision table displays values in rows and columns where each row describes a situation when given inputs (columns) result in certain outputs (also columns). In other words, each table contains a list of factors that outline what conditions cause a rule to trigger, along with the decisions to take and their effects.
Decision tables are best suited for running business rules that have several conditions. Users add a new condition simply by adding a new row or column.
Business users can create decision tables in Higson in which they define input and output columns and then populate data with values in rows.
As a result, they can effortlessly design complicated business scenarios without having to worry about running into issues that might hurt the operational efficiency of the company and without writing a single line of code!
In essence, decision trees are a visual representation of the decision execution process and represent the same information that appears in decision tables. A tree is a graph that uses the branching method to illustrate all the possible outcomes of any decision.
Decision trees are also well-suited for cases where a particular condition might have several different outcomes. However, while a decision tree may be easier to validate due to its visual nature, it's important to note that too many factors and conditions can make a decision tree too large and unmanageable.
In these situations, decision tables are the preferable option because you can split the decision path at the very beginning. As a result, you don’t have to deal with one sprawling tree, but rather several smaller ones.
How Companies Use Automated Decision Engines
Businesses across industries use decision engines to cut down on costs, implement best practices and policies, and improve the customer experience.
Decision engines are commonly used by airlines to streamline the pricing and purchasing process. For instance, automated decision-making applications can set pricing based on seat availability and the hour or day of purchase.
Automated decision engines can make instant decisions in emergency situations, such as turning off the water supply or the power grid in an area affected by a natural disaster.
Financial institutions use these engines to speed up loan applications, which tend to be repetitive and rely on consistent requirements. Also, decision engines flag potentially fraudulent transactions that require instant attention.
Decision engines help insurance companies instantly generate quotes for potential policyholders who enter their personal data online.
Automated healthcare care processes can recommend a particular treatment for a patient.
Decision Engines: Best Practices
Decision engines enable businesses to find the right balance between human intervention and automation. Intelligent automation still relies on the expertise of managers who create, review, and validate decisions. In order to optimize business processes, companies need to determine which decisions to automate and which ones require a human touch.
Many software solutions need experts to write and generate rules and supervise results. That is why we designed Higson, a powerful user-friendly software tool.
An Intelligent Decision-Making Process with Higson
Higson is a high-performance decision engine that uses, functions, business rules, and decision tables to automate and manage decisions.
Unlike rigid legacy systems that have hard-coded logic, Higson automates decisions with a powerful user-friendly graphical user interface for implementing complex decision logic and flexible open-API architecture for immediate decision processing.
As a result, non-technical subject-matter experts are able to manage your organization's decisions instantly, without having to wait for support from IT.
Get in touch with one of our experts to learn how your company can respond to changing market conditions and needs in just minutes.