The internal requests that cross three teams and stall in the middle of all of them.
Onboarding, access, equipment, approvals and leaving. Each is a sequence nobody owns end to end, which is why each one is slower than any individual step in it.
- Email and calendarRevoked
- PayrollRevoked
- TicketingRevoked
- Shared driveStill active
- Vendor portalStill active
The list of what to revoke is reconstructed each time.
Shape of an access list, illustrative. No system or count on this page is read off this drawing.
Four sequences that fail the same way.
These are coordination failures, not capability gaps.
A new starter waits on three teams in series
IT, facilities and the manager each act correctly and sequentially, so a two-day setup takes two weeks and nobody is at fault.
Access requests have no visible state
The requester cannot see where it is, so they chase, and the chasing is now a meaningful share of everyone's week.
Approvals live in inboxes
The approval exists as a message. When the approver is away, the process has no defined behaviour at all.
Leavers are handled from memory
Which is a security exposure rather than an inconvenience, because the list of what to revoke is reconstructed each time.
Three costs, and one of them is a security finding.
Every individual team is doing its part correctly, which is why buying a better tool for any one of them changes very little.
New people are unproductive while they wait
The salary is being paid from day one. The capability arrives later, and the gap is pure loss.
Chasing becomes a job nobody was hired for
Managers and requesters spend their time asking where things are, which is coordination work disguised as management.
Leavers keep access they should not have
Not through negligence but because the revocation list is rebuilt from memory each time. This is the item that appears in an audit.
Nobody can see where the time goes
Without state, there is no cycle time, so the process cannot be improved and its cost stays invisible.
The workflow afterwards.
Every block below is the same width. Only the starting point changes: strung end to end above, all starting together underneath. No width here is a duration.
Requests move team to team in series.
State is invisible, so people chase.
Approvals sit in an inbox.
Leaver revocation is remembered.
Cycle time is unknown.
Steps that do not depend on each other run at the same time.
The requester and the manager can see where it is without asking anyone.
Approvals have a defined route, a timeout and a stated fallback when someone is away.
It is a defined checklist derived from what was granted, with the closure recorded.
It is measured, so the slowest step is a fact rather than an opinion.
Most of this is not an AI problem, and it is worth saying so.
The category is sold as AI automation, but most of the recoverable time comes from sequencing and state, which are ordinary software. Knowing the difference keeps it small.
- Ordinary software
Steps running in series that need not
Ordinary workflow orchestration
The fix is the dependency graph, not intelligence. This is usually the biggest single win.
- Ordinary software
Requesters cannot see progress
A state model and a status view
Nothing needs interpreting. Something needs recording.
- Ordinary software
Approvals with no fallback
A rule, a timeout and a named deputy
This is a policy decision expressed in software, not a prediction.
- Benefits from AI
Requests arriving as free text in messages
This part benefits from AI
Classifying an unstructured request into a defined type is genuine interpretation.
- Benefits from AI
Answering the same policy questions
This part benefits from AI, over owned sources
Retrieval with provenance. See knowledge automation for the ownership prerequisite.
- A person, always
Deciding who should have access to what
The consequence of being wrong is a security incident, not a delay.
Roughly the first three rows are where most of the time is recovered, and none of them requires a model. A proposal that puts AI in every row is selling scope rather than solving the problem.
How the work runs, step by step
Time one real sequence end to end
Usually onboarding, because everyone recognises it. Measure elapsed time per step, not effort, since the waiting is the cost.
Separate dependency from habit
Which steps genuinely require an earlier one to finish, and which are sequential only because that is how the email chain grew.
Give the process a state model
Defined states, one owner per state, and a visible current position. This alone removes most of the chasing.
Automate the sequencing, then the interpretation
Orchestration first because it is where the recoverable time is. Classification and retrieval afterwards, where they earn a place.
Close the loop on leavers
Revocation derived from what was granted, with completion recorded. This is the part with an audit consequence.
What this connects to, and who builds it
Employee operations sits between several more specific services. Where one of these describes your blockage better, it is the better place to start.
- The orchestration itselfAI Workflow AutomationSequencing and handoffs across systems is AI workflow automation.
- A system to hold the processCustom Software DevelopmentWhere no existing tool can represent the workflow, that is custom software development.
- Policy answers for staffKnowledge AutomationRetrieval over owned sources, with the ownership prerequisite, is knowledge automation.
- Connecting HR and IT systemsAI IntegrationMaking existing systems exchange the right records is AI integration.
- Who is in the buildingWorkplace OperationsVisitors, contractors, desks and compliance records are workplace operations.
Where this work has been done
Answer quality, provenance and knowing when a system should decline are the substance of this work, and they are already how Viithiisys runs AI in production.
Vizitor, workplace operations at spread
In daily use across 500+ workplaces in 15+ countries.
Software for workplace operations that has to work the same way in many locations, which is the constraint this solution has. Multi-site consistency is the part that breaks first when a process grows by accretion rather than by design, and it is the part this work is built around.
Milo, a time-critical operational sequence
A driver-facing system where a coordination delay has immediate operational cost.
Relevant to sequencing work under time pressure, where the fix is almost always the order in which steps run rather than the speed of any single one.
Fitelo, controls in production
Evaluation and cost controls in place rather than added after an incident.
Questions we are actually asked
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Tell us how long onboarding actually takes.
Elapsed days, not effort. If most of it is waiting rather than working, this is the right page, and the first fix is usually sequencing rather than anything involving AI.