Industry and Organizational Context

This case examines a logistics organization responsible for selecting carriers to move goods across domestic and international lanes. Carrier selection decisions authorize which carrier is assigned to a specific shipment or lane under defined constraints.

• Selections occur daily across spot moves, contracted lanes, and exception scenarios.

• Each decision commits capacity, service risk, and cost for a specific movement.

• Poor carrier selection discipline creates hidden fragility, delays, and recovery costs.

Leadership initially framed carrier selection as a rate optimization problem, but instability stemmed from inconsistent treatment of individual decisions.

How the Work Was Intended to Function 

On paper, carrier selection was intended to operate as follows:

• Available carriers are identified based on lane and equipment requirements.

• Rates, service history, and capacity are compared.

• A carrier is selected and tendered the shipment.

• The shipment is executed and monitored. 

Leadership believed this evaluation logic could be applied uniformly to all carrier selections.

What Was Actually Happening

In practice, carrier selection decisions behaved very differently:

• Low-impact spot moves consumed disproportionate negotiation effort.

• High-impact selections were sometimes made on rate alone.

• Teams disagreed on when to favor reliability over cost.

• Carrier fatigue and concentration risk accumulated unnoticed.

The failure mode was not missing data. The failure mode was misclassification of individual carrier selection decisions.

How FLOW Was Introduced

Leadership was not seeking a new TMS or bidding platform. They were seeking a way to interpret carrier selection risk consistently. Specifically, they wanted:

• A shared language to distinguish routine selections from consequential ones.

• A way to avoid over-optimizing low-impact moves.

• A lens to surface systemic risk created by a single carrier choice.

FLOW was introduced as a classification lens to evaluate each carrier selection before tendering.

Identifying the Unit of Effort

Rather than optimizing annual spend or carrier scorecards, the organization anchored on a single unit of work:

• Unit of Effort: one carrier selection decision for a specific shipment or lane movement.

• Each selection decision is evaluated independently.

• Portfolio metrics are tracked separately and are not used to classify the unit.

How Complexity Was Determined

Complexity was defined as the amount of judgment required to evaluate viable carrier options.

• Low complexity selections involve interchangeable carriers with predictable performance.

• Higher complexity selections involve limited capacity, special handling, or uncertain reliability.

• Higher complexity selections require tradeoffs across cost, service, and resilience.

This definition of complexity was applied consistently across all carrier selection decisions.

How Scale Was Determined

Scale was defined as the breadth of downstream impact created by assigning a specific carrier.

• Number of downstream orders or operations dependent on the movement.

• Degree of substitution available if the carrier fails.

• Visibility and coordination required to manage execution or recovery.

Freight rate and shipment value were tracked, but they were not used as the primary definition of scale.

Other Measures of Scale Considered

Several commonly used indicators were considered but not used for classification:

• Absolute freight cost.

• Lane volume history.

• Urgency language associated with delivery commitments.

These indicators informed execution, but they did not reliably predict impact breadth.

Applying FLOW to Carrier Selection Decisions

With complexity and scale definitions fixed, each carrier selection was classified before tendering:

• Determine complexity first (option viability).

• Determine scale second (impact breadth).

• Assign a single FLOW classification to the selection.

FLOW A — Local, Contained Requests

Example: selecting a contracted carrier for a low-volume, non-critical shipment.

• Complexity: low.

• Scale: low.

• Handling implication: rate-optimized selection using standard rules. 

FLOW B — Broader Operational Impact Carrier Selections

Example: selecting a carrier for a shipment feeding multiple customer orders.

• Complexity: low.

• Scale: moderate.

• Handling implication: balance cost and reliability with visibility.

FLOW C — Complex, Judgment-Driven Carrier Selections

Example: selecting a carrier under constrained capacity or special handling requirements.

• Complexity: high.

• Scale: low-to-moderate.

• Handling implication: deliberate evaluation before tendering. 

FLOW D — System-Level Impact from a Single Carrier Selection

Example: assigning a single carrier to a critical movement that gates a launch, restart, or contractual milestone.

• Complexity: may be low or high.

• Scale: high because many downstream commitments hinge on this single selection.

• Handling implication: governance and sequencing are required due to impact breadth, not shipment count.

FLOW S — Exceptional Carrier Selections

Example: emergency or security-driven selections outside normal contracting rules.

• Normal tendering rules are inappropriate.

• Explicit exception handling is required.

• Post-event review is critical.

What Changed After FLOW Classification 

Once carrier selections were classified consistently, execution improved:

• Routine selections moved faster with less debate.

• High-impact selections surfaced risk earlier.

• Hidden concentration risk became visible.

Organizational Implications 

FLOW classification reshaped how transportation teams balanced cost and resilience:

• Escalation aligned to impact breadth rather than rate variance.

• Decision ownership became clearer.

• Carrier strategy shifted from reactive to intentional.