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As more organizations move further into their digital transformation to gain a competitive advantage, customers and employees increasingly expect streamlined and personalized digital interactions, including self-service options. By using automation as the cornerstone of digital processes, businesses can create and redesign processes to increase productivity, accuracy and satisfaction. Decision management is the combination of machine learning with business rules to help organizations understand the appropriate actions to take in a process. Typically, companies use decision management as part of a larger business automation approach for business operations. After defining which processes to automate, the organization creates workflows that outline the process. When a decision about what action to take next in the workflow arises, you can create a decision model to help determine what happens next.
Business rules are the cornerstone of decision management. When the automation system comes to a decision point in the workflow, the software uses a business rule to decide what happens next. Business rules consist of a conditional statement and then an action to take depending on which condition is met. You can modify business rules as your processes or situations change. For example, a retailer organization uses automation for return fraud detection. When an employee enters a return into the POS, the automation system uses artificial intelligence (AI) to quickly process the customer’s return and purchase history. The system then uses the customer data with the business rule that’s been set up for the system so it can flag customers with more than four returns in the last 60 days. During the holidays, when returns are more common, organizations may change the rule to allow six returns in the last 60 days.
Organizations that use decision management as part of an overarching business automation approach often see the following benefits:
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