In a world where retention and graduation rates remain stagnant, and the demographic cliff looms, universities need to implement data governance in order to effectively leverage the vast amounts of data at their disposal.
Governance can be tough - marshaling political will, finding consensus, implementing processes and systems can dissuade even the most committed institution. AI can help instantiate governance.
Here are some examples of AI working in support of communications governance.
AI can introspect messages queued to be sent for:
- logistics optimization - best day, time, channel - to ensure messages are read and any appropriate action taken
- content - does message content match the desired sentiment? Instead of common content, maybe match content to student-specific data from the SIS system
- duplication and conflict - students receive messages about the same subject, often with conflicting information and instructions
AI can introspect sent messages to determine:
- logistics optimization that derives data to inform/drive outbound message management
- student action/inaction to surface ineffective content
- duplication and conflicts
Lack of communications governance looks like this to a student:
- · Overwhelming - multiple emails and texts about the same subject
- · Confusing – collisions when different messages contain conflicting information
- · Tone deaf – messages are one-size-fits-all with zero student specific recognition
- · Barraged – emails and texts slam inboxes and mobile devices simultaneously.
Ultimately, governance drives student success. AI can drive governance if properly conceived, implemented and managed.
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Hendrix Bodden
CEO/Founder
xSIGNAL, Inc.
Chicago
312.661.6931
https://xsignal.inc/------------------------------
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