Is AI enhancing optimization of data-based processes in businesses? – By Aditya Abeysinghe
Optimization of business processes
Process optimization is the method of adjusting functionalities of a process to enhance it by minimizing issues, increasing efficiency, and reducing latency. This is performed by analyzing process functions and then detecting issues. In data-driven process analysis, a parameter is usually tuned while keeping other parameters unchanged.
Businesses use various data-based platforms to provide services. Virtual methods including websites and live methods including live customer support are used to provide such services. Most of these data-based processes have connections to other processes. Therefore, to efficiently provide business process optimization each process and processes that are connected should be changed to improve a service’s performance.
Issues of process optimization
When processes are connected the total time to complete a process is higher when some or all the processes are performed manually. Manual process optimization is difficult because often these have to be done when labor is available, approvals are required, and when some processes cannot be digitized due to business’ insider issues. Therefore, costs and the effort to optimize them are high and often cannot be properly enhanced.
Another issue with business process optimization is that certain processes cannot be optimized based on optimization of queries or based on changes to the logic of an application. A common example is the issue of finding to which group, from groups of customers, a new customer should be included. It is almost difficult to find the group from the data entered by a customer by querying similar customers’ data.
How AI is used for process optimization
Artificial Intelligence (AI) uses algorithms that are trained with a dataset. It is often used to automatically process large amounts of data. An advantage of AI models is that they can be used to automatically control several processes. Due to this, AI is used to automate processes using robotic process automation. By automating manual processes, issues with manual processes can be reduced as they are done with components that have been tested and the time to provide outputs is reduced.
In some optimizations processes need to be optimized by analyzing data based on similar groups and dividing new data to groups. This is difficult by database query-based analyzing techniques. In these cases, data needs to be processed by AI-based models or AI-based algorithms such that the accuracy of the output can be verified and multiple methods are not required to create the output. Also, usual methods cannot be used for techniques such as predicting patterns. AI-based techniques are used in situations where analyzing is often hard with usual analysis methods.
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