Introduction

Unassisted Task Mining is an actionability discovery service. It collects employee desktop data comprising of the screenshot and log data upon each user action (mouse click, keystroke), then runs a machine learning model to analyze the data and suggest a list of tasks with high automation potential.

Use cases

Unassisted Task Mining allows you to record the actions of selected users, analyze them together, and export the results to:

• Identify automation opportunities, tasks that have been repeated frequently in the user action data.
• Understand the frequent path and variances for the candidate tasks to possibly standardize and agree on the process before automating.
• Document the details of a candidate process to accelerate the development of automation.

Benefits

• RPA CoE leaders: efficiently discover automation opportunities and effectively engage the business teams by demonstrating an objective view of the opportunities - All at a fraction of the time and cost versus a traditional consulting-led approach.
• Business Analysts: avoid the time-consuming projects to interview or observe employees' work activities and then identify the repetitive tasks with high automation potential. Easily view and analyze the detailed process metrics with the automation candidates. Reduce the time spent on documenting tasks.
• Employees: low touch process for the employees to set up and record. No impact on the day to day work. Preserves privacy by avoiding a human observer.
• RPA developers: reduce the time spent on understanding the process before building automation.