黑料不打烊

Workforce & HR

Staff to the real workload and run HR services efficiently

Staff ahead of each office鈥檚 peak workload, and resolve routine employee requests.

Built for CHRO 路 CFO

Why workforce planning is hard to run today

1. Workload lives nowhere

Cases, tickets, and transactions sit in each office鈥檚 own tools.

HR systemPositions and peopleexport
Budget systemFunded linesemail
Case and ticket toolsThe actual workre-key
SpreadsheetsOvertime and temps

2. Peaks swamp the same offices every year

The calendar predicts them, but staffing reacts after the backlog forms.

SpringAdmissions
SummerFinancial aid
AugustRegistrar and bursar
All yearHR questions by email

3. Departures are predictable, and found in a resignation letter

Pay against market, workload, and leave signal it months ahead.

Months beforeWorkload and pay signals
Weeks beforeDisengagement
ResignationThe letter arrives
Months afterA search, and lost capacity

2 路 The ontology we build

The workforce model

We bring your systems, outside data, and policies together, model the domain, and compute what it runs on.

Workforce ontology: offices, work queues, positions, requests, postings, candidates, employees, leave, and job classeshandlessubmitsrequestssits inposted asapplies toclassified asfillstakessubmitslands inOfficedivisionenumservice_hoursstring茠capacity_gaphoursPosition requestreasonenumrequested_ondatefunding_sourceenum茠approval_routelist茠prefilled_sharepercentApprove positionWork queuekindenumweekly_volumeintegerminutes_per_itemdecimalpeak_volumeintegerPositiontitlestringgradeenumftedecimal茠days_vacantintegerJob postingopened_ondateapplicantsinteger茠time_to_fillintegerCandidatestageenumapplied_ondateEmployee requestkindenumopened_ondatestatusenumResolve requestEmployeehired_ondateftedecimalsalarymoneydeparture_riskpercent茠pay_vs_marketpercentLeavekindenumstarts_ondateends_ondateJob classfamilyenumgrade_rangestringmarket_ratemoney茠Expression 路 Officecapacity_gapsum(work_queues.peak_volume  脳 minutes_per_item)  鈭� staffed hours after leave茠Expression 路 Position requestapproval_routeoffice.budget_owner  鈫� HR classification  鈫� provost when facultyML model 路 Employeedeparture_riskChance this employee leaves in thenext six months.From position, office, and pay againstmarket and leave historyRefit quarterlyYour systemsOutside dataPolicies and memoryHR information systemPayroll and timeRecruiting systemOffice queues and ticketsBLS wage dataIPEDS staffingHR policies and handbookPosition descriptionsPast requests and approvals

A slice of the full model: the labeled objects are the ones this work runs on most.

Object

Office

A unit of the institution, the work it handles, and the people who do it.

Properties and logic
division
enum
service_hours
string
茠capacity_gap
sum(work_queues.peak_volume 脳 minutes_per_item) 鈭� staffed hours after leave
Relationships
  • handlesWork queuemany
  • submitsPosition requestmany
  • includesPositionmany
Fed by
HR information systemIPEDS staffing

What it enables

3 路 What we deploy on top

Applications, agents, and workflows on the model

Each one reads the model and changes it only through governed actions.

App

Workforce HQ

For HR and division leaders: workload against capacity by office, open positions, time to fill, and departure risk.

Reads
Acts through
Approve position

Approve position: Dean or vice president for new lines

Agent

Employee services agent

Answers leave, tax form, and benefits questions from policy and the employee鈥檚 record, and resolves routine requests within policy.

Reads
Acts through
Resolve request

Resolve request: HR reviews leave and pay changes

Workflows

HR operations

Prefills position requests from source data, routes them for approval, and opens the posting once approved.

Reads
Acts through
Approve position

Approve position: Dean or vice president for new lines

4 路 Outcomes

What the workforce model lets you do

1. Staff ahead of peak workload

Staff move before overtime hits

HR and department heads
What the model sees

Each office鈥檚 workload against its capacity, month by month

2. Prefill and route position requests

Requests arrive complete, with a committee briefing

Approval committee
What the model sees

The source data behind every request field

3. Handle routine employee requests

An agent resolves them and routes the rest

HR
What the model sees

Leave, tax forms, and benefits questions

4. Fill vacancies faster

Positions post before the vacancy opens

HR
What the model sees

Each office鈥檚 turnover patterns

5. Shift routine work to agents

Staff hours are redeployed to higher-value work

Department heads
What the model sees

Work agents can absorb, like payment-plan calls

How we measure it

Projected value when a change goes live, and realized value against a holdout, a matched group, or the prior cycle, reported separately.

Overtime hours avoided

Employee questions resolved on first contact

Position requests decided with full evidence

Start with Workforce & HR

We scope the first domain with your team and agree on the outcomes to measure.