The GTA Economy at the Wrong Door
A street observation on technology, shared capacity and the economics of last mile delivery
Andrain Scott, PMP®, CMILT
I came home to find somebody else’s prescription on my porch.
A prescription has a purpose at its destination. On my doorstep, it had become a problem for somebody to resolve.
My elderly neighbour’s frozen groceries and Amazon parcels also find their way to my address. Each time, I find myself looking past the package and mentally following its journey: the order, the allocation, the loading, the dispatch, the route and the final handover. Somewhere along that journey, the intended address became the wrong doorstep.
That is the habit my work in third party logistics has given me. I cannot help following how something gets to its intended location, on time, within budget and in the condition the customer expected. My PMP training draws my attention to dependencies and responsibility. Business development makes me follow the outcome further, into the customer’s response and the next order.
The carrier arrangements and the reasons for these errors remain unknown. I use the incidents here as observations through which to examine a larger economic relationship: how the GTA turns logistics technology, working time and shared infrastructure into a service that businesses and households can use.
The region’s economy becomes tangible in that movement. A purchase made on a screen becomes a physical commitment. Stock, labour, vehicles, roads and customer availability must meet at a particular place and time. A misplaced parcel leaves the final part of that commitment unresolved.
Cross-docking makes those dependencies especially visible. Goods moving from an inbound trailer towards an outbound departure carry a deadline through the building. Door allocation, load preparation, handling capacity and dispatch timing must work together. Moving inside the facility is valuable, but the customer receives the benefit through the performance of the whole journey.
Research accessed through CILT’s member knowledge resources gives this observation a useful foundation. Buijs, Danhof and Wortmann studied a Dutch grocery retailer using operational data and discrete event simulation. Their findings show how improvements in internal handling distance can have limited effects on overall flow unless decisions within the cross-dock and the surrounding network are coordinated (2016, pp. 226–227).
I recognise that relationship in the way I think about 3PL operations. A goods movement can be well executed within one department and still leave the next department with a problem. The warehouse’s departure time becomes the carrier’s starting condition. The carrier’s arrival becomes the customer’s receiving condition. Each handover carries the consequences of earlier decisions.
Technology strengthens that chain when the information travels with the goods. An address, access instruction, service window or exception must mean the same thing to the people who act on it. A route can be efficiently calculated and still depend on a detail known by a dispatcher, driver or customer.
CILTNA’s September 2026 presentation by Vijoe Raj on decision intelligence places this relationship at the centre of logistics practice: combine trustworthy operational context, forecasting and optimisation with human expertise and accountability (slides 3–5). I value that professional contribution because it connects technology to the decisions and responsibilities that give it economic purpose.
On GTA’s streets, the next dependency is shared capacity. The delivery vehicle travels among commuters, tradespeople, service vehicles and other freight. Its schedule draws on road space that many activities need at once. Congestion uses up time that was available for handling goods, serving another stop or dealing with an exception.
CANCEA’s commissioned 2024 study estimated the Greater Toronto and Hamilton Area’s congestion burden at C$44.7 billion. It combined C$10.1 billion in annualised economic impacts with C$34.6 billion in effects on wellbeing expressed as income equivalents. These are modelled estimates against a reduced-congestion counterfactual, covering the broader GTHA. The total includes substantial non-market effects; it cannot be read as a freight bill (CANCEA, 2024, pp. 35–37).
That distinction matters on my street. A business can account for a driver’s additional paid hour. A household can lose an hour waiting, searching or rearranging its day without that loss appearing on a carrier’s invoice. Regional economic performance and residents’ wellbeing are connected through transport, while being measured in different ways.
Peer-reviewed GTHA research makes interdependence clearer. Chowdhury and colleagues modelled off-peak freight deliveries using a network calibrated to 2016 road counts. One scenario shifted 30% of truck trips in participating retail, grocery wholesale, and accommodation and food-service industries, producing a net daily saving of 5,530 vehicle-hours, including additional passenger demand. This is a scenario result, rather than a saving observed across today’s network (2022, pp. 418–423).
Their model also shows additional passenger trips absorbing some daytime benefits. That is the regional connection I see: a carrier schedules its work within a network used by other firms and households. Freed capacity has other users.
Residential delivery has a further constraint. The time that works for the vehicle also must work for the recipient, the building and the product. Frozen groceries, a prescription and a commercial replenishment order place different demands on the handover. Scheduling joins the seller’s promise to the practical circumstances of the person receiving it.
This is where I see the distinction between a company’s saving and an improvement in economic productivity. Productivity concerns what useful service is achieved with the resources committed. A lower delivery rate can improve the buyer’s accounts. If completing the order then requires additional calls, another journey or unpaid help, some of the resource requirements have merely moved.
The neighbour who carries groceries to the intended house contributes time outside the original commercial agreement. Pigou’s treatment of uncompensated effects on third parties provides a theoretical basis for understanding that external cost (1932, Part II, chapter IX, section 10). The customer’s own recovery work belongs to the service experience they purchased. Both matter economically, even when neither produces a separate invoice.
The same task can also impose a different burden on different people. Walking to the next house may be straightforward for one recipient and difficult for an elderly person with limited mobility. Home delivery has been bought partly to remove that task. When it returns to the household, part of the convenience has been lost.
From this perspective, an avoidable correction consumes resources that could have supported another delivery, another customer or another use of household time. My porch does not establish the scale of those losses across the GTA. It makes their mechanism visible: the work required to finish a sale can extend beyond the businesses paid to fulfil it.
Coordination has an economic value of its own. Williamson’s transaction cost economics directs attention to how commercial relationships organise adaptation and responsibility (2010, pp. 679–681). Applied to delivery, that lens draws me towards the practical knowledge carried between people: who understands the route, who receives changed instructions and who takes responsibility when the plan meets an exception.
On recurring routes, familiarity can become part of that knowledge. A driver may learn a difficult entrance or a receiving routine. A dispatcher may understand why one customer’s window cannot move. That knowledge becomes more useful when it is shared and available to the next person who needs it. I see it as part of the coordination behind dependable service.
The economic value also reaches the demand side. Lu and colleagues’ 2026 Management Science paper examined home delivery versus collection at Cainiao pickup stations in China. Their quasi-experimental analysis found increased orders and spending on Taobao among customers receiving home delivery (pp. 5–9). The findings are specific to that setting; its magnitude cannot be transferred to GTA clients.
For my business development perspective, the implication is that delivery belongs within the value of the offer. Customers choose a product together with the practical arrangements for receiving it. A dependable recurring service gives a business something meaningful to sell: a commitment the customer can plan around.
My PMP perspective keeps me attentive to that wider outcome. PMI’s 2025 Pulse of the Profession connects project performance with business value beyond scope, schedule and budget (pp. 14–16). I carry that discipline into my understanding of recurring operations: the plan has dependencies, the work has owners, and completion must satisfy the people relying on it.
Even when everything has gone well, I cannot help following the goods all the way through. I want to understand how they reached the intended location on time and within budget, how the handovers protected their condition, and how the customer experienced the result. Customer praise interests me because it describes what worked from the receiving end. Repeat and recurring business interests me because the relationship continues beyond one successful movement.
In my work as Business Development Manager at ClearPath Distribution, that is how I read a delivery requirement. I see the customer’s operating rhythm, the responsibilities between parties and the service promise that must survive the journey. The commercial relationship begins to make sense when the capacity offered fits the work the customer needs done.
That is also the economic observation I take from my porch. Across the GTA, logistics connects digital purchases to physical life through individual handovers. When those handovers work, technology, infrastructure and professional judgement become useful service. The prescription on my porch brought that relationship back to one intended recipient. The economy had reached my doorstep; its promise still had another address.
About the author
Andrain Scott, PMP®, CMILT, is Business Development Manager at ClearPath Distribution Ltd. His business development focus is recurring cargo van delivery in the GTA. This article is a practitioner’s research-informed observation, drawing on his 3PL experience, project management training and published research. He acknowledges CILTNA’s professional programme and the CILT member knowledge resources used to access journal literature.
References
Buijs, P., Danhof, H. W., & Wortmann, J. C. (2016). Just-in-Time Retail Distribution: A Systems Perspective on Cross-Docking. Journal of Business Logistics, 37(3), 213–230. https://doi.org/10.1111/jbl.12135 Source
Canadian Centre for Economic Analysis [CANCEA]. (2024). Impact of Congestion in the GTHA and Ontario: Economic and Social Risks. Commissioned by the Residential and Civil Construction Alliance of Ontario and the Ontario Road Builders’ Association. Source
Chowdhury, T., Vaughan, J., Saleh, M., Mousavi, K., Hatzopoulou, M., & Roorda, M. J. (2022). Modeling the Impacts of Off-Peak Delivery in the Greater Toronto and Hamilton Area. Transportation Research Record, 2676(10), 413–425. https://doi.org/10.1177/03611981221089552 Source
Lu, Z., Cui, R., Sun, T., & Wu, L. (2026). The Value of Last-Mile Delivery in Online Retail. Management Science, Articles in Advance, 1–21. Published online June 8. https://doi.org/10.1287/mnsc.2023.03991 Source
Pigou, A. C. (1932). The Economics of Welfare (4th ed.). Part II, chapter IX, section 10. Macmillan. Online text hosted by the Library of Economics and Liberty. Source
Project Management Institute [PMI]. (2025). Pulse of the Profession® 2025. Sections 2.2 and 6. Source
Raj, V. (2026, September 15). Decision Intelligence in Logistics: Combining Generative AI, Optimization, and Human Expertise. CILTNA webinar presentation slides 3–5. Professional presentation. Source
Williamson, O. E. (2010). Transaction Cost Economics: The Natural Progression. American Economic Review, 100(3), 673–690. https://doi.org/10.1257/aer.100.3.673 Source