Academic venture case · team project

MCY Logistics

Product thesis

Constrain the service until its customer value, reliability and economics can be tested together.

The model links a defined B2B customer hypothesis, bounded capacity, pilot gates and staged capital commitment. It was designed for decision-making; it was not executed.

My contribution: Operations lead within a two-person team
Venture: Sustainable B2B last-mile logistics
Planning model: 4 leased EV vans · illustrative ~100 km radius
Status: Academic concept · not launched

Case summary

Decision: Deliberately constrain the venture — four leased EV vans, an illustrative 100 km service radius and one narrow B2B customer profile — then earn expansion with evidence.
Decision criteria: Customer urgency, parcel and route fit, service reliability, utilisation and route-level economics.
Evidence & assumptions: The team defined a customer-profile filter, a proof-of-concept plan with service-level gates, and a break-even target for the constrained model.
My contribution: Within a two-person team, I led the academic operations workstream covering fleet, last-mile operations, optimisation and quality.
Decision artefact: A bounded operating model with explicit assumptions, validation gates and expansion criteria.
Evidence boundary: Coursework, not a launched business. Fleet, radius, systems, investment and break-even are model inputs or targets; no customer, revenue or realised outcome is claimed.

Documented: Research, decisions and outputs contained in the coursework.
Modelled: Assumptions, scenarios and targets — not observed results.
Proposed: Future validation and decision gates — not completed work.

Contribution and evidence boundary

My documented contribution

Operations workstream in a two-person team

My contribution covered fleet, last-mile operations, optimisation and quality within the academic venture model.

Team output

One integrated venture plan

Our team produced the opportunity framing, customer prioritisation, operating model, proof-of-concept path, service-level gates and investment plan documented below.

01 · Opportunity

Frame the customer problem as a falsifiable hypothesis

Desk research suggested a B2B opportunity around recurring, light-parcel urban delivery. No primary discovery was conducted, so customer urgency and willingness to switch remained hypotheses for interview and pilot testing.

Context

Urban last mile

Congestion and environmental restrictions challenge conventional delivery models.

Audience

B2B customers

E-commerce businesses and sustainability-oriented brands in Barcelona and Madrid.

Demand pattern

Recurring light parcels

A service concept focused on repeatable work suited to a compact electric fleet.

Discovery base

Desk research

Opportunity framing, competitor review, ideal customer profile (ICP) definition and an initial target-account shortlist.

Team output · opportunity brief

A bounded proposition

Problem space: More sustainable urban last-mile delivery.
Initial market: B2B e-commerce and sustainability-oriented brands.
Service focus: Light, recurring parcels within a limited operating area.
Evidence still needed: Direct customer and operating validation.

Can a constrained electric-delivery model create enough customer and operational value to justify a controlled PoC?

01
Customer urgency
Target accounts experience the problem often enough to consider changing provider.
02
Route density
Recurring light-parcel work can support reliable use of a four-van fleet.
03
Service quality
A deliberately narrow operating area can support consistent delivery and exception recovery.
04
Route economics
Observed contribution can cover fleet, hub, systems and exception costs.

Evidence boundary. These are model hypotheses, not findings from customers or live operations.

02 · Operating model

Design for control before expansion

The academic model deliberately limited physical capacity and geography. Each element below is a planning assumption, not a deployed capability.

Planned fleet

4 leased EV vans

Light parcels
Recurring routes
Leased capacity
Electric delivery

~100 km Illustrative service radius

Planned enablement

Microhub + WMS/TMS

Local coordination
Warehouse planning
Transport planning
Operating visibility

Model choice 01

Constrain the launch area

Choice: An illustrative operating radius of approximately 100 km.
Expected trade-off: Lower operating variation, but a smaller reachable market.
What to test: Real route density and service consistency.

Model choice 02

Lease the initial fleet

Choice: Four leased electric vans.
Expected trade-off: Lower initial capital commitment, with live availability and cost still uncertain.
What to test: Utilisation and cost per route.

Model choice 03

Connect physical and information flow

Choice: A microhub with planned WMS/TMS support.
Expected trade-off: Greater visibility, with additional operating and systems complexity.
What to test: The minimum viable information flow before adding system depth.

03 · Customer profile and prioritisation

Choose customers the model can serve well

The team translated a broad market into a practical ideal customer profile and an initial shortlist of five prospect accounts. Prioritisation centred on fit with the proposed operating model, not market size alone.

01
Strategic fit
Prioritise B2B e-commerce and brands whose sustainability positioning aligns with the proposition.
02
Operating fit
Look for recurring, light-parcel demand compatible with the planned fleet and radius.
03
PoC fit
Select a bounded opportunity where service and operating assumptions can be tested clearly.
04
Commercial fit
Keep opportunities only where the model could support a credible path to sustainable economics.

Prioritise

Recurring light parcels

Demand patterns suited to the intended urban electric-delivery model.

Exclude

Bulky or hazardous freight

Work outside the proposed fleet and service profile.

Exclude

Low-margin opportunities

Demand that weakens the model without creating sufficient strategic value.

Qualification rule. An account enters the proposed pilot backlog only if strategic fit, recurring light-parcel demand, geographic fit and a credible commercial path are all present.

04 · PoC-to-SLA delivery path

Earn the service commitment with evidence

The plan proposed moving from a bounded proof of concept to a service-level agreement (SLA). This was a delivery design only; neither stage was executed.

Qualify

Confirm customer, parcel and geographic fit before committing operating capacity.

Run a bounded PoC

Test the service pattern, handoffs, exceptions and evidence needed for a decision.

Decide on an SLA

Agree commitments only if customer, operating and economic assumptions hold.

Proposed PoC gates

Evidence required before an SLA

01
Customer gate
A qualified account agrees to a scoped test and confirms the problem being solved.
Decision evidence
02
Operating gate
Capture route completion, utilisation, handoffs and exceptions.
Decision evidence
03
Quality gate
Review service consistency and recovery from exceptions.
Decision evidence
04
Economic gate
Calculate route-level cost and contribution from observed pilot inputs.
Decision evidence

05 · Economics and roadmap

Treat the forecast as a decision model

The €200,000 investment and month-18 break-even target describe the scale of the coursework hypothesis. A product decision would stage commitment: first validate demand, then operations, then the economics required to justify further capital.

Team output · planning model

Inputs and targets, not results

Planned investment: €200,000
Fleet input: 4 leased electric vans
Initial operating input: Approximately 100 km radius
Break-even target: Before month 18

What evidence would justify committing capital — and what result would stop or reshape the plan?

Validate demand

Test the problem, ICP and willingness to run a bounded PoC.

Validate operations

Use PoC evidence to revise fleet, radius, microhub and systems assumptions.

Commit selectively

Move toward an SLA and expansion only when the evidence supports the economics.

06 · Evidence and next validation

Separate what was designed from what remains to prove

Documented

What the academic work established

Collaborative venture simulation
Operations workstream within a two-person team
B2B ICP and five-account shortlist
Constrained fleet, radius and systems model
PoC-to-SLA plan and financial target

Not yet evidenced

What the venture would still need to prove

Validated customer demand
Live operating performance
Commercial viability
Customer adoption or retention
Launch, revenue or realised break-even

Next validation plan

Questions for the next decision cycle

Problem

Do the intended B2B customers recognise the last-mile problem as urgent?

Proposition

Which part of the sustainable-delivery offer creates enough value to test?

Operations

Can the proposed fleet, radius and microhub model support the target demand pattern?

Economics

What evidence on routes, utilisation and cost would change the investment case?

Decision

Should the team proceed, narrow the model, redesign it or stop?

Proceed to SLA

Customer, operational, quality and route-level economic gates are all met.

Iterate

Customer value is supported, but one correctable operating assumption fails.

Stop

Customer urgency is weak or the delivery pattern cannot support defensible economics.

The value of an early venture model is not that it predicts success. It makes the next decisions explicit and testable.

Evidence base: collaborative UOC International Trade coursework, 2025–2026. Fleet, radius, investment and break-even values are planning assumptions or targets — not operating results.

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