Measure automation savings without double counting
Count distinct work, active human effort, exceptions and maintenance, then separate existing savings from a proposed scenario.
Library / AI & automation
Can you automate it before you hire for it? Use the sequence to inspect work, test a bounded change and keep the remaining human responsibilities visible.
Stop work that no longer earns its place.
Make the work repeatable enough to measure.
Hand the repeatable part to a tested workflow, with human review where the error cost is real.
Add people for the judgment, coverage and relationships that remain.
Count distinct work, active human effort, exceptions and maintenance, then separate existing savings from a proposed scenario.
Test the repeatable work before opening a requisition, without confusing saved effort with judgment, coverage or a smaller payroll.
Compare repeatable workflows by input quality, error cost and review burden before testing one small candidate.
Use AI for summaries and drafts with explicit review points, protected inputs and a correction-rate record that includes rejected output.
Set prompt-data boundaries, check the exact account and tool documentation, and give staff an approved-use note with an owner and a stop route.
Review the access, integrations, alerts and recovery paths around your RMM, PSA and documentation systems, with a usable evidence sheet.
Keep renewals, licence checks, lifecycle dates and roadmap decisions in one owned calendar, while leaving approvals and relationship work with people.
Turn a small authorized evidence pack into a checked client-review brief, with permission tests and an honest effort comparison.
Design an authenticated knowledge agent that answers from a small approved procedure library and refuses unsupported or unauthorized requests.
Build a dry-run request-to-approval workflow with verified organization context, duplicate controls and a separately gated write stage.
Compare two fictional procedure revisions in a private, bounded draft workflow and produce a source-checked change note without rewriting policy automatically.
Produce an evidence-linked handoff from fictional ticket notes while preserving failed fixes, unresolved status and human authority over replies and changes.
Turn a discovered script or policy suggestion into a reviewed provenance record, a bounded lab plan and an evidence-based accept or reject decision.
For Owner, Tech lead, Automation & AI
For Automation & AI, Tech lead, Service manager, Service desk & technicians
For Service manager, Automation & AI, Service desk & technicians
For Account management, Service desk & technicians, Service manager, Cybersecurity
For Service desk & technicians, Automation & AI, Tech lead, Cybersecurity
For Automation & AI, Service manager, Tech lead, Service desk & technicians
For Tech lead, Service desk & technicians, Service manager, Automation & AI
For Service desk & technicians, Service manager, Automation & AI
For Service desk & technicians, Tech lead, Cybersecurity, Automation & AI
Compare current workload with an automation scenario. Separate existing from proposed savings, include exceptions and maintenance, and record an owned next step.
For Owner, Service manager, Automation & AI, Tech lead
Contents & limits →A broad MSP reference covering operations, roles and AI; useful as an orientation map before specific vendor research.
Markdown index available; check factual claims against primary docs.
Vendor recipes for reporting and triage across MSP systems; useful for inspecting workflow inputs and permission boundaries.
Commercial product documentation, not independent savings evidence.
Primary language and module documentation for understanding scripts before adapting them.
Test in an authorized environment; examples are not permission to run changes.
Documentation for the Microsoft 365 administration tool; useful when checking supported operations and deployment assumptions.
An administration tool needs scoped access and a reviewed operating process.