Improving automation of work with an accessible business processes analizer.

Abstract

Process Mining use is growing, as more and more companies recognize the benefits it provides.

Studying and monitoring processes can be extremely valuable to increase efficiency by cutting costs, exploiting synergies, recognizing and improving operations which are particularly prone to failure or are particularly repetitive, and therefore there is potential for automation.

Process Mining is particularly interesting for larger companies with many processes to keep under control. In this case, it is worthy for those companies to hire full time process mining experts who can operate all the necessary analysis and give the results.

Smaller companies do not generate enough data to justify a full-time employee working on that, so they can only rely on consultancy, which is clearly more expensive on the long run.

The research problem this thesis seeks to answer is: can we develop a general Process Mining tool that would give non-expert users natural language answers to key process efficiency questions?

This is a broad question and relies on the definition of a "key process efficiency question". In this case we take into account as main goal for the user to find the best way to automate their process. This conjunction between process analysis and automation has been researched previously, concluding that automating a process starting from its worst performing activities is a good way to achieve the best results, and Process Mining techniques can provide the necessary information to automate activities in the correct order.

Since this experiment is aimed at communicating this to unexperienced users, the produced tool should be accessible to people who never studied Process Mining but have some process to keep track of.

This study aims then to create a prototype tool which anybody with basis of statistic and graphs can use, to generate some useful results out of process data, leading to efficient application of Intelligent Automation. Ideally this should also stimulate Process Mining awareness and usage, and push for a general improvement in efficiency and automation. This document will describe the tool created, as well as some examples of results obtained, and an evaluation of the results based on a survey with potential users of the system.