Internal Marketplace & Expert Match Workflow

Purpose

This workflow helps teams find and consume internal expertise quickly while preventing expert overload and knowledge hoarding. It describes an end‑to‑end pattern: intake → triage → match → micro‑consult → reconcile → learn. Use it to turn ad‑hoc help into a dependable, measurable capability that improves over time.

Who should use this

• Team leads needing timely subject matter help
• Knowledge managers and librarians who curate expertise
• Individual experts and their managers who want fair, predictable demand
• Operations and people functions designing governance and incentives

Core outcomes (Hungers)

• Make expert time discoverable, requestable, and consumable on demand
• Reduce duplicated work and speed problem resolution
• Capture answers so knowledge becomes reusable organizational capability
• Protect experts from burnout via fair routing, SLAs, and credits

High‑level flow

1. Intake: Requester submits a short structured request (problem, desired outcome, urgency, attachments, budget/credits).
2. Triage: Automated or librarian review applies simple rules to route, escalate, or reject; sometimes the request is answered by a curated FAQ or knowledge artifact.
3. Match: Assign an expert, office hour slot, or micro‑consult; send calendar invite and pre‑work if needed.
4. Micro‑consult: Time‑boxed interaction (15–60 minutes) with a clear agenda and agreed deliverables.
5. Reconcile: Record time/credit usage, update expert availability, and mark request closed.
6. Feedback & capture: Collect requester feedback and save an indexed answer or artifact to the knowledge index.
7. Governance & metrics: Review utilization, fairness, wait times, satisfaction, and expert load; adjust rules and incentives.

Roles and responsibilities

• Requester: Provides a concise problem statement, desired outcome, urgency, and context.
• Marketplace Triage (librarian or automated rules): Validates requests, suggests self‑serve resources, routes or assigns priority.
• Matched Expert: Accepts or declines within SLA, prepares pre‑work, and conducts the micro‑consult to agreed scope.
• Manager/Owner: Oversees fairness, approves credit budgets, and reviews dashboards for capacity issues.

Intake form template (fields to capture)

Keep the intake form short. These fields work well as a simple interactive form:

• Request title (one line)
• Describe the problem and desired outcome (3–5 sentences)
• Why now? Business impact or deadline
• Estimated preferred session length (15 / 30 / 60 minutes)
• Attachments or links to artifacts
• Preferred times / timezone
• Requester contact and team
• Cost center or credit bucket (if applicable)
• Is this confidential or compliance‑sensitive? (yes/no)

Tip: Implement this as an interactive form so responses are stored, searchable, and linked to dashboards.

Simple triage rules (examples)

• If a knowledge article or FAQ score > threshold, return self‑serve suggestion and close.
• If request is urgent (blocker for work) and expert pool has available on‑call capacity, escalate to on‑call for same‑day slot.
• If request is routine (repeatable), route to a curated template or playbook contributor.
• If request is high cost or sensitive, require manager approval before matching.

Micro‑consult agenda & templates

Structure keeps short meetings productive. Share this agenda with both parties before the session:

1. Context recap and objective (5 minutes)
2. Data/artifacts review (5–10 minutes)
3. Options, recommended approach, tradeoffs (5–20 minutes)
4. Decide next steps, owner, and deadline (5 minutes)

After the session, the expert or requester should capture a 1–3 sentence answer and any artifacts to the knowledge index.

Credit / time reconciliation

Keep accounting simple so the marketplace scales. Example models:

• Time‑bank: Experts contribute X hours/month to the pool; consuming teams use credits tied to budget lines.
• Chargeback credits: Requesters spend department credits; experts record minutes and the system deducts credits.
• Sticker points: For informal communities, track consult counts and provide non‑monetary recognition.

Template record to store after each session: request ID, expert, date/time, duration, credits charged, deliverable link.

Feedback and knowledge capture

Immediately after a consult, ask the requester to answer two quick questions (one‑click/scale):

• Was this helpful? (yes/no or 1–5 scale)
• Do we need to convert this answer into a knowledge article? (yes/no)

If yes, route to the librarian or the expert to create a short indexed artifact (problem, solution, links, tags).

Simple SLAs and guardrails

• Initial acknowledgement: within X business hours (e.g., 4 hours)
• First match or suggested self‑serve: within Y business days (e.g., 2 business days)
• Maximum monthly consults per expert before manager review (to avoid overload)
• Confidential requests require explicit handling rules and limited indexing

Key metrics / sample dashboard

Track these to measure value and fairness:

• Volume: requests per week
• Median time to first response
• Median time to match
• Average consult duration and credits consumed
• Requester satisfaction (1–5)
• Expert utilization and number of requests per expert
• Knowledge capture rate (percent of consults converted to indexed artifacts)

Governance checklist

• Define expert eligibility and curate the expert directory
• Set capacity rules and require manager opt‑in for overcommitment
• Decide credit or cost model and how approvals work
• Privacy and sensitivity rules for indexed content
• Regular review cadence (monthly) to rebalance capacity and priorities

Common pitfalls and how to avoid them

• Hidden hoarding: make expertise discoverable and require listing of office hours/availability
• Overload: enforce per‑expert caps and monitor utilization dashboards
• Lost answers: require a short capture after each consult and index it
• Unclear expectations: use short micro‑consult agendas and explicit deliverables

Quick implementation roadmap

1. Stand up a simple intake form and triage rules (minimum viable form)
2. Curate initial expert roster and publish availability/office hours
3. Run pilot with one team for 4–8 weeks and capture baseline metrics
4. Iterate triage rules, SLAs and credit model based on usage and feedback
5. Scale by packaging the workflow as a toolkit for other teams (templates, forms, dashboards)

Templates & sample text (copy & adapt)

Short intake prompt

"In 2–3 sentences describe the problem, the desired outcome, and why you need help now."

Micro‑consult confirmation

"Agenda: 1) Quick context (5m) 2) Review artifacts (10m) 3) Advice & next steps (10m). Outcome: owner, decision, and deliverables. Please add links/info before the session."

Post‑consult capture

"Answer (1–3 sentences): [solution summary]. Link to artifacts: [link]. Tag(s): [tags]."

Next steps & capability opportunities

Turn the intake and post‑consult capture into interactive forms so requests and outcomes are stored and searchable. Connect the stored submissions to a dashboard that shows wait times, utilization, and knowledge capture rates. Package the intake form, triage rules, metrics dashboard, and templates as an Adaptive Ownable Domain or toolkit that teams can copy and tailor.

References & suggested extensions

• Create a searchable expert directory with tags and availability
• Offer scheduled office hours for frequent requests to reduce 1:1 matches
• Use lightweight peer review for knowledge artifacts before publishing to the index
• Consider a pilot credit model with one sponsoring department to test reconciliation