What you need
Data sources
- TMS database — Historical shipment records with lane (origin-destination), volume (shipments and weight), dates, and carrier allocation
- Warehouse management system — Outbound volume, dock utilization, and staging capacity by facility
- Carrier capacity data — Contracted capacity by lane, available spot capacity, and rate trends
Knowledge spaces
- Demand calendar — Planned promotions, seasonal peaks, product launches, and known volume spikes
- Capacity planning guidelines — Target utilization rates, buffer capacity rules, and lead times for securing incremental capacity
| Component | Name | Definition |
|---|---|---|
| Object | Lane | Maps to the TMS lane master. Represents an origin-destination pair with its historical volume and carrier assignments |
| Object | Facility | Maps to the warehouse master. Represents a distribution center with its throughput capacity and current utilization |
| Metric | CapacityUtilization | Actual volume divided by contracted or available capacity, expressed as a percentage per lane or facility |
| Metric | ForecastedVolume | Predicted shipment volume for a future period based on historical trends and known demand events |
| Dimension | PlanningHorizon | Time-based categorization: next week, next month, next quarter |
Agent setup
Create the agent
Go to Agent Space → New agent.
| Field | Value |
|---|---|
| Name | Capacity Planner |
| Role | Network capacity and volume forecasting specialist |
| Goal | Ensure sufficient capacity across lanes and facilities to meet demand without overspending |
Set the description
You forecast shipment volume and identify capacity constraints across the logistics network. When presenting forecasts, always show the methodology: historical baseline, trend adjustment, and known demand events factored in. Present capacity utilization as a percentage with a clear indicator of headroom or shortfall. Use precise numbers — shipment counts, weight, and percentage utilization. When recommending capacity actions, include the lead time required and the estimated cost of securing incremental capacity.
Scope data access
Grant access to:
- TMS database (historical shipments, lanes, carriers)
- Warehouse management system (outbound volume, dock utilization)
- Carrier capacity data (contracted capacity, spot rates)
- Demand calendar knowledge space
- Capacity planning guidelines knowledge space
Lane,Facilityobjects andCapacityUtilization,ForecastedVolumemetrics
Add skills
Forecast volume by lane
Forecast volume by lane
Trigger: User asks about upcoming volume or quarterly planning
- Pull historical shipment volume by lane for the past 12 months.
- Identify the baseline trend: is volume growing, stable, or declining on each lane?
- Check the demand calendar for known events in the forecast period (promotions, seasonal peaks, new customer onboarding).
- Adjust the baseline forecast for each known event based on the expected volume impact.
- Calculate the forecasted volume for each lane for the requested horizon (week, month, or quarter).
- Compare forecasted volume against contracted carrier capacity on each lane.
- Flag any lane where forecasted volume exceeds 85% of contracted capacity as “capacity at risk.”
Identify capacity constraints
Identify capacity constraints
Trigger: User asks about capacity risks or monthly planning review
- Run the volume forecast for all lanes and facilities for the next 30 days.
- Calculate capacity utilization for each lane (forecasted volume versus contracted capacity) and each facility (forecasted outbound versus throughput capacity).
- Identify constraints: lanes or facilities where utilization exceeds 85%.
- For each constraint, calculate the gap in units (shipments or pallets) and estimate the cost of securing spot capacity to cover the shortfall.
- Present a prioritized list of constraints ranked by gap size and cost impact, with recommended actions: secure spot capacity, shift volume to alternate lanes, or negotiate temporary capacity increases.
Automation
Playbook: Quarterly capacity forecast
Set the trigger
Schedule: First business day of each quarter at 9:00 AM (runs for Q2 planning on April 1, Q3 on July 1, etc.).
Build the workflow
- Query the TMS for historical shipment volume by lane for the past 12 months.
- Query the demand calendar for all known events in the upcoming quarter.
- Query carrier capacity data for contracted capacity by lane.
- Run Python analysis to:
- Fit a trend line to each lane’s historical volume using linear regression.
- Apply seasonal adjustment factors derived from the prior year’s quarterly patterns.
- Add event-driven volume spikes from the demand calendar.
- Compute the forecasted weekly volume for each lane across the quarter.
- Calculate capacity utilization percentage: forecasted volume versus contracted capacity.
- Identify weeks and lanes where utilization exceeds 85%.
- Condition: If more than 20% of lanes are projected to hit capacity constraints during the quarter, flag the report as “action required” and recommend a capacity procurement review.
- Aggregate into a formatted forecast report: network-level summary, lane-level detail with weekly projections, constraint heatmap, and recommended actions.
The volume forecasting step uses a Python code block to run linear regression on historical data, apply seasonal adjustment factors, and project weekly volumes. You can customize the regression lookback window, seasonal adjustment methodology, and the capacity utilization threshold.
Configure delivery
Send an email to the VP of Logistics and the capacity planning team with the subject line: “Quarterly capacity forecast — [Quarter Year]”. Attach the full forecast report. Post a summary of the top 5 constrained lanes to the
#capacity-planning Slack channel.What’s next
Route efficiency analysis
Optimize the routes within your network to make the most of the capacity you have.
All logistics use cases
See the full list.