A food distributor approached Marketways because product availability, waste, cold-chain exposure and transport cost were being managed through separate decisions. A kilometre-saving route could still destroy value if milk or fresh food lost saleable life. We connected demand, inventory, product-specific decay, vehicle conditions and customer promises in one route-to-market system.
The engagement objective
Through the initial discovery, Marketways defined the objective: connect demand, inventory, product decay, cold-chain capacity and route decisions.
How Marketways translated the problem
We began with a practical question: What should each location hold, and how should uncertainty change the decision? The first analysis used sku-location sales, inventory, lead time, waste, events, weather and promotions.
That evidence could not be read in isolation. Forecast error has different costs for long-life, seasonal and perishable items. Milk, fresh food, frozen goods and furniture cannot share one generic routing objective; time and temperature create product-specific decay.
The route with the fewest kilometres was not necessarily the route that preserved the most value. Product decay, temperature exposure and remaining saleable life changed the objective the optimisation had to solve.
We did not judge each component by its isolated KPI. We examined how people, assets, decisions and constraints affected one another, then used the evidence to test whether an apparent improvement would strengthen the complete system or merely move cost, pressure or risk elsewhere.
How the engagement developed
The initial work on demand, replenishment and waste forecast exposed dependencies with perishable cold-chain and route optimisation, store and service execution audit, market entry and demand definition. Treating them as separate recommendations would have left the operating trade-offs unresolved.
- Demand, replenishment and waste forecast: Improve availability while reducing excess stock and waste.
- Perishable cold-chain and route optimisation: Protect product quality while controlling fleet and waste cost.
- Store and service execution audit: Make branch-level improvement specific and measurable.
- Market entry and demand definition: Define a credible route to market before scaling investment.
Evidence we examined
- SKU-location sales, inventory, lead time, waste, events, weather and promotions.
- Orders, product decay tests, temperature, routes, service windows, vehicle and outlet constraints.
- Mystery visits, customer feedback, operations, staffing and branch characteristics.
- Customer research, category sales, channels, competition, price and cost.
Industry conditions we accounted for
- Forecast error has different costs for long-life, seasonal and perishable items.
- Milk, fresh food, frozen goods and furniture cannot share one generic routing objective; time and temperature create product-specific decay.
- Customer experience varies by time, staffing, queue, stock, compliance and local demand.
- Interest in a concept does not prove repeat purchase, distribution access or unit economics.
How our engagement contributed to business impact
We connected every method to a decision and a business measure. The organisation could assess the engagement through operating results as well as model performance.
- Demand, replenishment and waste forecast
- Method: Forecasting, Risk & Optimisation, Machine Learning & Predictive Analytics.
- Evidence: SKU-location sales, inventory, lead time, waste, events, weather and promotions.
- Decision supported: Improve availability while reducing excess stock and waste.
- Impact measure: Availability, waste, markdown and working capital.
- Perishable cold-chain and route optimisation
- Method: Forecasting, Risk & Optimisation, Statistics & Econometrics.
- Evidence: Orders, product decay tests, temperature, routes, service windows, vehicle and outlet constraints.
- Decision supported: Protect product quality while controlling fleet and waste cost.
- Impact measure: Remaining shelf life, spoilage, on-time delivery, distance and cooling cost.
- Store and service execution audit
- Method: Research & Evidence Collection, Statistics & Econometrics.
- Evidence: Mystery visits, customer feedback, operations, staffing and branch characteristics.
- Decision supported: Make branch-level improvement specific and measurable.
- Impact measure: Compliance, waiting, resolution, conversion and sustained improvement.
- Market entry and demand definition
- Method: Research & Evidence Collection, Market, Customer & Behavioural Analytics.
- Evidence: Customer research, category sales, channels, competition, price and cost.
- Decision supported: Define a credible route to market before scaling investment.
- Impact measure: Trial, repeat, distribution, margin and demand confidence.
Implementation
The engagement was structured as pilot by product and depot, then network scale-up. We connected the analysis to the decisions, operating constraints and measures that the organisation would continue to use.
How success was assessed
The overall assessment considered freshness, availability, waste, service and delivered cost. The supporting measures included:
- Availability, waste, markdown and working capital.
- Remaining shelf life, spoilage, on-time delivery, distance and cooling cost.
- Compliance, waiting, resolution, conversion and sustained improvement.
- Trial, repeat, distribution, margin and demand confidence.
Services and methods used
Services: Sales Forecasting & Demand Planning, Risk & Uncertainty Modelling, Fleet & Logistics Optimisation, Predictive Maintenance & Reliability, Mystery Shopping & Service Quality Audit, Operational Performance Diagnostic, Market Research & Demand Assessment, Market Entry Strategy.
Methods: Forecasting, Risk & Optimisation, Machine Learning & Predictive Analytics, Statistics & Econometrics, Research & Evidence Collection, Market, Customer & Behavioural Analytics.