Business rule mining is a very important part of the continuous decisioning process.

Generally, business rules are modeled by domain experts and operations teams in decision automation scenarios. But what if you see a behaviour in your operational system from your customers, clients, etc. but you don’t know the business rules? This is where the need for business rule mining arises to extract, analyse, and understand business rules from customer or market data

Business rule mining is the ability of a system allowing you to extract rules from data. In this process, you connect the data FlexRule Designer and it will analyze the data and extract the rules from it.

Business rule mining

The overall process of business rule mining for continuous decisioning approach.

The business rule mining enables business analysts, or operation people take the historical data from operational database and systems, provide them to the business rule mining module and FlexRule Designer processes the data, automatically apply multiple different Machine Learning algorithms, and represents a readable form of rules such as below:

if (Outlook == 'sunny') and (Humidity <= 70) then Play = 'yes'
if (Outlook == 'sunny') and (Humidity > 70) then Play = 'no'
if (Outlook == 'overcast') then Play = 'yes'
if (Outlook == 'rain') and (Windy == false) then Play = 'yes'
if (Outlook == 'rain') and (Windy == true) then Play = 'no'

Ready to Use – Simulate, Debug, Deploy and Explain

FlexRule Designer will take it one step further and prepare and model a Decision Table and Fact Concept related to those rules automatically and will add them to the project.

Decision tablefact concept

Now you can start debugging and simulation activities, play with the rules by feeding relevant values for inputs (conditions), and retrieve the results (outputs):

business rule mining - golf example

As you see in the below screenshots, after rules execution is completed, the result is set to “Yes”.

business rule mining - parameters window result

One of the benefits of this approach is because the decision is now driven by rules rather than a particular Machine Learning trained model, you have the full visibility and explainability on why a specific decision is made:

Event viewer to show explainability

Continuous Decisioning

Business rule mining is a very important part of the continuous decisioning process. The business rule mining module enables you to utilize a Machine Learning with a couple of clicks without having the knowledge of a data scientist and extract the business rules from your data.

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By building this process into any continuous integration such as a CICD pipeline and deliver a continuously decisioning platform by looking at the latest dataset in systems, extract the business rules, build the decision model, test, debug, approve and go to production. Here is how the continuous decisioning cycle is:

continuous decisioning cycle using business rule mining techniques

With this approach, you can keep monitoring and measuring the Decisions KPI constantly and improve them as needed in an iterative and incremental manner.

Published September 3rd, 2020 at 11:00 pm