Accenture - Data Led Automation combining Task Mining & Process Mining
One stop shop for visibility into the potential automatable areas by combining both the action and process logs
Accenture's Data Led Automation combining Task Mining & Process Mining app helps uncover potentially every automation opportunity existing in the process by tracking the click-level details of an agent. Provides clear visibility of issues preventing invoice approvals & payments, enabling quicker resolutions & allowing a greater chance to approve and pay invoices on time.
This is where Accenture and Celonis combine their Strengths:
Centralized allocation of agents to the invoices and auto allocation of the same to buyers in case of exceptions.
Identification of upstream process inefficiencies.
Identification of automation opportunities (Eg: Auto 3-way match, Auto sorting, and assignment of POCs).
Reduced Invoice processing time, Improved process efficiency, Improved productivity of agents and Reduced idle time.
Features & Capabilities
The dashboard is the management view which provides a cockpit view of trends of invoice creation, cycle time, # agents who have worked, exceptions, and the overall status of the invoices pertaining to respective stages of invoice processing.
The process explorer with filter allows the user to view and track each acitivity step performed in different system. In the combined view, the activity steps are colour coded based on the type of source system.
AIDT Dashboard provides the details of the number of activities ( as % and count ) performed by an agent in each source system.
The dashboards offers granular visibility into the agent who has addressed an invoices and the associated vendor for the same. Further slice and dice of the data with respect to the region, country code and approver details.
This Dashboard shows us the various stages the invoice is in. It also brings a view to show the invoices rejected and resolved in the period. It further helps in arriving at the root causes and top drivers behind the deviations.
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