Transportation & Logistics · Sourcing intelligence
We implemented an intelligent sourcing solution for a leading North American fueling network, combining cost optimization, demand forecasting, and automated recommendations to improve procurement decisions
At a glance
- Client
- Leading North American fueling network
- Industry
- Energy and fuel distribution
- Solution
- Intelligent fuel sourcing and cost optimization
- Capabilities
- Demand forecasting, scenario simulation, automated sourcing recommendations
- Users
- Fuel procurement, supply planning, and operations teams
The challenge
Procurement decisions focused on terminal prices without fully accounting for transportation costs, contractual terms, and anticipated demand, often making seemingly cheaper options more expensive.
Limited visibility into supply constraints and overall sourcing economics increased operational risks and made it difficult to select the most cost-effective and reliable fuel suppliers.
The data foundation
Optimizing fuel procurement required a broader understanding of cost, demand, and supply conditions beyond terminal pricing alone
Fuel prices
Unit costs across available supply terminals.
Transportation
Distance and delivery requirements influencing landed costs.
Contract terms
Commercial agreements and sourcing obligations.
Terminal reliability
Historical disruptions and supply availability.
Demand forecasts
Anticipated fuel requirements across the network.
What we built
An intelligent optimization system that evaluates available supply options and recommends sourcing decisions based on total cost, anticipated demand, and operational reliability
- 01
Forecast
Predictive models estimate future fuel demand, giving procurement teams a clearer understanding of supply requirements before making purchasing decisions.
- 02
Optimize
An automated decision engine evaluates terminal prices, transportation costs, contract terms, and supply reliability to recommend sourcing options based on true delivered cost rather than unit price alone.
- 03
Simulate
Real-time scenario modeling allows teams to assess price changes, contract adjustments, and potential terminal outages before committing to a sourcing decision.
The solution gives procurement teams evidence-backed recommendations while keeping purchasing decisions under their control.
The outcome
The fueling network moved from price-led sourcing toward a more comprehensive approach that considers the full economics and risks of every supply decision.
Procurement teams can now identify sourcing options that reduce overall fuel spend rather than selecting terminals based on unit prices alone.
Incorporating terminal reliability and disruption history also strengthens supply planning, helping teams evaluate risk before it affects operations.
Automated recommendations shorten decision cycles, while scenario simulations allow planners to test alternative sourcing strategies and approach supplier negotiations with stronger commercial insight.
The result is a more responsive procurement operation where purchasing decisions are informed by cost, demand, contractual obligations, and supply reliability rather than isolated price comparisons.
Discover how ShyftLabs uses data, predictive intelligence, and automation to improve enterprise operations and commercial performance
