The Introduction to Results Virtual Classroom is designed for users who are looking to automate their Exceptions Remediation Process. This Virtual Classroom will cover the basics of using Analytics together with Results to automate remediation workflows and present results to key stakeholders through visualisations and storyboards.
Introduction to Results Virtual Classroom
Set up Results
- Understand the data container hierarchy in Results
- Identify the process of sharing data to Results
- Identify exceptions using ACL Analytics by examining General Ledger Backdated Transactions
- Determine levels of access for relevant parties so they can view and participate in the workflow
- Identify when to leverage the most appropriate Results feature whilst designing the remediation workflow. e.g. Questionnaires, Triggers, Metrics
Automate your issue remediation
- Identify the remediation status that will remove the records from the list of open issues
- Recognise when to leverage the most appropriate features for remediation
- Understand the benefits of designing a process workflow to then it through triggers and questionnaires
Report your results with visualisations
- Recognise the functions within a Results Visualisation page
- Identify outliers and trends within in visualisation
- Briefly examine the capabilities of storyboards
The Virtual Classroom is designed to be interactive and practical.
It will be a facilitator led training conducted over the internet using Zoom as a learning platform.
A pre-session checklist, Learner and Activity Guide and Datafiles relevant to this topic will be sent prior to the date. A preliminary zoom invite will be sent to you to ensure that you are all set up for this classroom.
Requirements: Internet Access, Desktop ACL Analytics (Analytics Version 14 or later), Dual monitors and a headset.
Prerequisites: Completion of an ACL 101 course is strongly recommended or at least 6 months previous experience using Analytics for data analysis.
Date and Time
Completion of an ACL 101 course is strongly recommended or at least 6 months previous experience using ACL Analytics for data analysis.