Logistics and Carrier Performance
Your logistics team just finished a carrier performance review. Evri, which handles 30% of your London-to-Manchester volume, has an on-time delivery rate of 83.4% — down from 89.2% last quarter. Damage rate has doubled. The carrier is cheap: £1.45 per kg versus DPD at £1.84.
Your logistics manager says: keep Evri for the cost saving, ask them to improve.
Before agreeing, check one more number: 14% of your total logistics spend is on expedited shipments — same-day and next-day premium delivery — primarily from one business unit. Your logistics team has been asked to source more premium capacity to cover the shortfall.
This lesson teaches you to read both situations correctly. The Evri problem is a carrier performance problem — the scorecard makes the decision obvious. The expedited freight problem is not a logistics problem at all. Buying more premium capacity solves nothing. The answer is somewhere upstream.
The Four Dimensions of Logistics Optimisation
Most organisations treat logistics as a fixed cost, renegotiated at contract renewal and largely ignored between reviews. The result is that route assignments made 18 months ago — when carrier performance, fuel surcharges, and demand patterns were different — are still running today, accumulating avoidable cost with every shipment.
Samir Saci's published work in AI-driven supply chain optimisation demonstrates that analytical exercises which previously required weeks of consulting engagement can now be run continuously and conversationally. The /logistics-brief skill brings this capability to your Cowork session.
Dimension 1: Route Efficiency
For any origin-destination pair in your network: what is the cost, transit time, carbon footprint, and reliability profile of every available route and mode combination? When did you last verify that your current arrangement is still optimal?
Route efficiency analysis answers these questions at the lane level — not the network level. Network-level design is Dimension 3 and requires its own workflow (Lesson 9).
Dimension 2: Carrier Performance
Which of your approved carriers is performing best right now? The carrier scorecard tracks four metrics:
| Metric | What It Measures | Threshold |
|---|---|---|
| OTD rate | % of shipments delivered on or before promised date | OTD ≥ 95%: excellent; <90%: FLAG |
| Damage rate | % of shipments with reported damage or claim | <0.2%: excellent; >0.5%: FLAG |
| Cost per kg | Normalised freight cost (not per shipment — normalises for size) | Benchmark against market rate |
| Track-and-trace reliability | % of shipments with real-time tracking events | ≥ 98%: excellent; <95%: FLAG |
Carrier performance is not static. A carrier performing at 94% OTD at contract signing can deteriorate to 83% twelve months later as they over-expand their network or face operational problems. The scorecard catches this.
Dimension 3: Network Design
Where are your warehouses, distribution centres, and cross-docking points positioned relative to your current demand patterns? Network design is the strategic dimension — reviewing whether your physical infrastructure is optimally located relative to your supply origins and customer destinations. This dimension is covered in depth in Lesson 9.
Dimension 4: Sustainability
What is the carbon footprint of your current logistics network? This was once an optional reporting exercise. It is increasingly a compliance requirement: Scope 3 emissions reporting mandates are expanding across jurisdictions, and major customers are requesting logistics carbon data as part of their own supply chain due diligence. Approximate emissions by transport mode:
| Mode | Approximate gCO2e per tonne-km |
|---|---|
| Air freight | 500–600 |
| Road (HGV) | 60–80 |
| Rail (electric) | 20–30 |
| Sea (container) | 10–15 |
Mode shift from road to rail on high-volume lanes can reduce emissions by 60-75% per tonne-km — often with minimal transit time impact on appropriate routes.
The /logistics-brief Workflow
The skill handles all four logistics analysis types. Each is invoked with a type: parameter.
Carrier performance review:
/logistics-brief
> Agent: What logistics analysis do you need?
> User: Quarterly carrier performance review.
We use 4 carriers for UK domestic distribution:
DPD, Evri, Royal Mail Business, and our own fleet.
Provide a performance comparison and routing recommendations
for our top 3 distribution lanes.
Sample output — carrier scorecard:
CARRIER PERFORMANCE BRIEF — Q1 2026
════════════════════════════════════════════════════════════
Analysis period: Jan–Mar 2026 | Source: TMS + ERP data
CARRIER COMPARISON (all UK domestic lanes)
OTD% Damage% Cost/kg Track% Score
DPD 94.2% 0.3% £1.84 99.1% 🟢 4.2/5
Royal Mail Biz 91.1% 0.2% £2.10 97.3% 🟡 3.8/5
Own Fleet 96.8% 0.1% £2.45 N/A 🟢 4.5/5 (premium cost)
Evri 83.4% 0.8% £1.45 91.2% 🔴 2.9/5
KEY FINDINGS:
1. Evri performance has degraded significantly vs. Q4 2025
(was 89.2% OTD; now 83.4%). Damage rate doubled. Recommend:
→ Immediately reroute any B2B shipments off Evri
→ Retain Evri only for low-value B2C where cost is primary driver
→ Initiate performance review conversation with Evri account manager
→ If no improvement by end Q2: consider contract termination
2. Own fleet significantly outperforms on service but costs 33% more
than DPD (£2.45 vs. £1.84/kg). Currently used for:
→ Same-day/next-day critical deliveries: justified
→ Standard B2B deliveries: over-engineered; shift to DPD
3. DPD remains best price-performance for standard lanes.
Opportunity: consolidate volume from Evri to DPD to negotiate
improved rate at higher volume tier.
TOP 3 LANE ANALYSIS:
Lane 1: London → Manchester (daily; avg 340 shipments/week)
Current: 60% DPD / 30% Evri / 10% own fleet
Optimal: 85% DPD / 0% Evri / 15% own fleet (critical only)
Savings: £2,840/month (Evri removal + DPD volume rate)
Lane 2: Midlands Hub → Yorkshire (daily; avg 180 shipments/week)
Current: 50% own fleet / 50% Royal Mail Business
Optimal: 30% own fleet (priority) / 70% DPD (standard)
Savings: £1,920/month (own fleet reduction on standard shipments)
Lane 3: London → Scotland (3×/week; avg 85 shipments/week)
Current: 100% Royal Mail Business
Optimal: 100% DPD (better OTD + lower cost on this lane)
Savings: £640/month
TOTAL IDENTIFIED SAVINGS: £5,400/month (£64,800/year)
════════════════════════════════════════════════════════════
The scorecard makes the Evri decision clear. The overall score of 2.9/5 — driven by the below-threshold OTD and elevated damage rate — is not a marginal call. The £0.39/kg cost saving over DPD is more than offset by the downstream cost of 17% late deliveries (customer service, compensation, redelivery) and the reputational risk of B2B customers receiving damaged goods.
Expedited Freight: Logistics Symptom, Upstream Problem
If your expedited freight spend exceeds 10% of your total logistics budget, the logistics brief will flag it. But the diagnosis requires you to look upstream, not at carriers.
The five root cause categories:
| Category | Cause | Correct Intervention |
|---|---|---|
| Late supplier delivery | Supplier missed their delivery, forcing expedited onward shipment | Supplier corrective action (procurement problem, not logistics) |
| Demand forecast error | Demand was higher than forecast; inventory depleted early | Improve forecasting or safety stock levels (planning problem) |
| Inventory positioning error | Stock was in the wrong location relative to demand | Review distribution network and stock positioning |
| Customer emergency | Customer had an unexpected urgent requirement | Valid commercial reason — this is acceptable expedited spend |
| Production planning error | Internal scheduling created late production completion | Operations management problem |
For the example data above: 73% of expedited orders originate from one business unit, and the root cause analysis points to inventory positioning — the business unit is running with insufficient safety stock relative to demand volatility. The correct intervention is reviewing safety stock levels at that site, not sourcing more premium freight capacity. Buying more expedited capacity would solve nothing and would cost £24,000+ per year to maintain.
Expedited freight is expensive. The instinct is to manage it as a logistics cost — negotiate better premium rates, qualify more premium carriers, manage the budget. This is treating the symptom. If expedited freight exceeds 10% of your total logistics spend, the logistics team is funding an upstream process failure. Find the root cause in procurement, planning, or operations — and fix it there.
Lane and Carbon Analysis
For specific lane optimisation:
/logistics-brief type:"lane-optimisation"
lane:"[Origin] → [Destination]"
current:"[carrier, mode, cost, transit time]"
alternatives:"[list available carriers and modes]"
For carbon assessment:
/logistics-brief type:"carbon-assessment"
data:"[logistics data]"
scope3-reporting:"required/not required"
The carbon assessment identifies your highest-emission routes and evaluates mode-shift options — for example, moving a high-volume London-to-Edinburgh lane from road to rail would reduce emissions significantly at minimal transit time increase on that corridor.
The Logistics Intelligence Agent
The logistics-intelligence-agent automates continuous carrier performance monitoring, flagging performance deterioration between quarterly reviews. Configure it with:
- Carrier performance thresholds (OTD and damage rate triggers)
- Lane monitoring: which lanes to track continuously
- Alert routing: who receives performance alerts and at what threshold
- Reporting frequency: weekly or monthly performance digest
The agent's value is catching a carrier like Evri before the quarterly review. A 6-percentage-point OTD decline over a quarter can be caught at the 2-point mark if monitoring is continuous — giving you time to renegotiate or reroute before customer impact accumulates.
Exercise: Logistics Optimisation Analysis (Exercise 4)
Type: Operational Analysis
Time: 60 minutes
Plugin commands: /logistics-brief, /spend-analysis
Goal: Identify and quantify the top 3 logistics cost reduction opportunities
Step 1 — Data Collection
Pull from your TMS or logistics records for the last 90 days:
- Shipment volume and spend by carrier
- On-time delivery rate by carrier
- Cost per unit shipped by carrier and lane
- Expedited shipment volume and cost (premium freight total)
- Fuel surcharge amounts paid versus contracted rates
Step 2 — Carrier Performance Analysis
/logistics-brief type:"carrier-performance"
period:"Q1 2026"
data:"[paste or connect via MCP]"
For each carrier, compare actual OTD against contracted SLA, actual cost against contracted rate (identifying any rate creep or fuel surcharge over-application), and damage and claim rate. Classify each carrier: Outperforming / Compliant / Underperforming / Review-required.
Step 3 — Lane Optimisation
For your top 5 highest-volume lanes:
/logistics-brief type:"lane-optimisation"
lane:"[Origin] → [Destination]"
current:"[carrier, mode, cost, transit time]"
alternatives:"[list available carriers and modes]"
For each lane: is the current carrier and mode the best available option? When was this last evaluated? Have carrier performance or market conditions changed?
Step 4 — Expedited Freight Analysis
If your expedited freight cost is more than 10% of total logistics spend:
- Which business units generate the most expedited shipments?
- What events trigger expedited shipments? (Late supplier delivery, forecast error, inventory positioning error, customer emergency, production planning error?)
- Quantify: if you reduced expedited freight by 50%, what is the annual saving? What would need to change upstream to achieve it?
Step 5 — Carbon Footprint Assessment
/logistics-brief type:"carbon-assessment"
data:"[logistics data]"
scope3-reporting:"required/not required"
For each lane and mode, identify approximate carbon emissions. Flag the highest-emission routes and whether lower-emission alternatives exist at acceptable cost and service level trade-offs.
Deliverable: Carrier performance scorecard with classifications, lane optimisation analysis for top 5 lanes, expedited freight root cause analysis, carbon assessment, and ranked savings opportunity register with total annual saving identified.
Try With AI
Reproduce: Apply what you just learned to a simple case.
I manage logistics for a UK manufacturing business. We use three
carriers for outbound distribution:
ParcelForce: OTD 88.2%, damage 0.6%, cost £1.95/kg, track 96.1%
DHL: OTD 96.1%, damage 0.2%, cost £2.12/kg, track 99.4%
Yodel: OTD 82.7%, damage 1.1%, cost £1.38/kg, track 89.3%
Our top lane (Birmingham → London, 420 shipments/week) is currently
50% ParcelForce / 30% Yodel / 20% DHL.
1. Score each carrier using the scorecard framework.
2. Classify each as Outperforming, Compliant, Underperforming,
or Review-required.
3. Recommend the optimal lane routing and estimate the annual saving.
What you are learning: The carrier scorecard converts four metrics into an actionable classification. The lane routing recommendation is the output — but the scorecard is the input that makes it defensible.
Adapt: Modify the scenario to match your organisation.
For your own logistics network (or a hypothetical one in your
industry), answer:
1. What carriers do you currently use and for which lanes?
2. When was the last time you ran a formal carrier performance review?
3. What is your expedited freight spend as a percentage of total
logistics budget?
4. Do you know the root cause breakdown of your expedited orders?
Then identify one specific action — carrier rerouting, expedited
freight reduction, or mode shift — that you believe would deliver
the highest savings. What data would you need to confirm it?
What you are learning: The gap between what you know about your own logistics costs and what a data-driven review would reveal is where savings live. Identifying the question is the first step.
Apply: Extend to a new situation the lesson didn't cover directly.
Your finance director has asked the supply chain team to reduce
logistics Scope 3 carbon emissions by 20% within 18 months as
part of the company's ESG commitments.
Your current network is 95% road freight (HGV).
1. Which lanes are the best candidates for mode shift to rail?
What criteria would you use to identify them?
2. What would a 20% reduction require in terms of volume
shifted from road to rail?
3. What are the service level and cost trade-offs of the shift?
4. How would you report Scope 3 logistics emissions accurately —
what carrier data do you need, and what methodology would you use?
What you are learning: Carbon reduction targets require the same analytical rigour as cost reduction targets. Lane selection, mode availability, and service trade-offs are procurement and logistics decisions — not just sustainability team decisions.
Flashcards Study Aid
Continue to Lesson 9: Supply Network Design Scenarios →