IntelliProSight

IntelliProSight

As digital transformation interventions enhances customer experience, unidentified process
inefficiencies can disrupt the process leading to frictions in the customer journey. Traditional process monitoring tools fail to identify anomalous behaviours in process flows proactively to highlight potential delays. Also alerts generated are not intelligent enough and do not take into account historic process trends into account. 

By leveraging advanced analytics and machine learning, ProSight exploits your business process data to highlight inefficiencies and recommend actions to avoid delays and customer experience.

Key Features

Proactive alerts for delayed processing

Overview of process level statistics such as total processes in progress, delayed, erroneous

Ability to track every process with features such as time bound flow, delayed/on time status, estimated time of completion

Multiple graphical representation of process performance with respect to standard expected outcome

Resource level logging of data to derive insights including tracking of active time, processes worked on, delayed processes

Ability to create/edit master process or create new process with simple drag and drop interface

Ability to notify respective point of contact in case of delay setting triggered

Authority based login access to dashboard and features

Live/near real time tracking of processes

What benefit will it provide?

Finding out tasks/activities or resources negatively impacting the process turnaround time in real
time before completing the entire process.

Why is it required?

Processes consisting multiple automated or manual tasks which needs to be completed in given
time can find it hard to locate where is the actual bottlenecking is happening in entire process.

What does it do?

It shows various of insights at process and activity level where one can track each entity going
through the process, and task consistently causing delay can be pointed out, also processes which
can get delayed according to current state can be predicted.