Connect. Optimize. Transform.

Building resilient and intelligent supply chains for Canada.

The SFU Digital Supply Chain Lab brings together government, industry, and academia to turn trusted data into better decisions, stronger infrastructure, and more resilient supply chains.

Start a Collaboration Explore the Lab
SFU Digital Supply Chain Lab infographic showing a connected global supply chain network
Mission

Canada needs sovereign digital supply chain intelligence.

Canada’s geography, inter-provincial trade corridors, ports, resource economy, northern and remote communities, and global market exposure create supply chain challenges that are national in scale. DSCL will help Canada move from fragmented visibility to coordinated, data-driven resilience.

Hosted within SFU’s Big Data Hub, the lab is designed as a practical interface between academic expertise and external partners. Its focus is applied: secure data collaboration, AI-enabled analytics, decision-support tools, and measurable economic impact.

What We Do

From data sharing to operational impact

01

Supply Chain Data Infrastructure

Integrate data from transportation, ports, logistics, inventory, procurement, geospatial systems, climate risks, and economic indicators.

02

AI, Simulation, and Forecasting

Develop models for bottleneck detection, disruption forecasting, scenario analysis, anomaly detection, and operational optimization.

03

Trusted Multi-Party Collaboration

Enable partners to share sensitive data responsibly using secure access controls, anonymization, aggregation, and privacy-preserving methods.

04

Training and Talent Development

Train students, researchers, public servants, and industry professionals in digital supply chain analytics and responsible AI.

Project Model

How successful DSCL projects are run

  1. Define the problem.Clarify the decision, partner needs, users, constraints, data requirements, and expected impact.
  2. Review data and governance.Assess data ownership, sensitivity, quality, privacy, security, and sharing conditions.
  3. Build the prototype.Create a dashboard, model, simulation, data pipeline, risk score, or optimization tool with rapid partner feedback.
  4. Validate and stress test.Evaluate against historical data, domain expertise, operational constraints, and disruption scenarios.
  5. Deploy and transfer knowledge.Provide documentation, training, technical handoff, research outputs, and implementation support.
  6. Measure impact.Track benefits such as faster response, lower delay, improved forecasts, reduced waste, and better coordination.

Privacy · Security · Governance

Trust is the operating model.

Supply chain data can include commercially sensitive, operationally sensitive, and regulated information. DSCL applies privacy-by-design and security-by-design principles from the start of every project.

  • Purpose limitation: data are used only for approved project purposes.
  • Minimum necessary access: partners and researchers access only what they need.
  • Transparent governance: ownership, use, retention, publication, and commercialization terms are explicit.
  • Secure analytics: support for controlled access, audit logs, encryption, secure enclaves, aggregation, and federated analysis.
  • Responsible AI: models are tested for reliability, bias, explainability, and operational suitability.

Shared Benefit

Better supply chain data benefits everyone

Government

Improved infrastructure planning, emergency preparedness, inter-provincial coordination, trade policy, and economic resilience.

Industry

Better forecasting, reduced uncertainty, lower costs, stronger supplier coordination, and improved competitiveness.

Academia

High-impact research, student training, reproducible methods, and applied innovation tested on real-world problems.

Canada

Fewer disruptions, stronger domestic capacity, improved productivity, and global leadership in trusted supply chain intelligence.

Principal Sector Advisor

Andrew Hamilton

Andrew Hamilton will serve as Principal Sector Advisor for the SFU Digital Supply Chain Lab, bringing senior industry perspective and sector knowledge to the lab’s applied research, partnership development, and supply chain innovation activities. Based in Vancouver, Andrew is associated with Phrone Consulting and has professional ties to SFU’s Beedie School of Business, positioning him well to help connect academic expertise, industry needs, and practical implementation pathways.

As Principal Sector Advisor, Andrew helps guide the lab’s engagement with supply chain stakeholders, ensuring that projects address real operational challenges, industry priorities, and opportunities for economic impact. His contribution are especially important in shaping sector partnerships, validating project relevance, and supporting the lab’s goal of strengthening Canada’s supply chain resilience, competitiveness, and data-driven decision-making capacity.

Lab Director

Stephen Makonin, PhD, PEng

Stephen Makonin is an SFU data science and AI leader with extensive experience across academia and industry. He has led multidisciplinary research initiatives, secured more than $2 million in research funding, published 60+ peer-reviewed articles, and built partnerships that translate advanced analytics into practical outcomes. His background spans software engineering, machine learning, data governance, stakeholder management, computational sustainability, and industry-facing research through SFU’s Big Data Hub.

As Lab Director, Stephen guides DSCL’s project execution, partner engagement, technical development, privacy-aware data practices, and knowledge translation.

Partner with DSCL

Bring your supply chain challenge to the lab.

DSCL is seeking collaborations with public agencies, industry partners, researchers, and community stakeholders interested in secure, data-driven supply chain innovation.

Contact Stephen Makonin