Pedal Me > Disrupting urban logistics – the Pedal Me approach

Disrupting urban logistics – the Pedal Me approach

Making the economics of cargo bike logistics work

In a previous post, we wrote about the advantages of cargo bikes for last mile deliveries. We analysed the data from our fleet of e-cargo bikes over a month, and showed they operate significantly more efficiently than vans and cars in dense urban areas: They can move past stationary traffic, benefit from shorter routes thanks to e.g. bus- and bike lanes, while also avoiding wasted time on finding parking space. In a second part, we described the deep impact replacing vans with cargo bikes can have on making our cities kinder and healthier. They directly decongest the city, clean up the air, prevent CO2 emissions, make our streets safer and encourage active travel infrastructure.

This article focuses more on the economics of cargo bike logistics. We give an overview of the disruptive approach taken by Pedal Me for operating large scale urban logistics and lay out its advantages and strong potential as the business scales up. Unlike any other mobility business, Pedal Me chooses to approach the broadest part of the logistics and mobility market. By leveraging the adaptive nature of e-cargo bikes, the Pedal Me fleet is developing what we name an Agile Urban Mobility network. As this network grows denser, network effects start to appear to create quicker and cheaper services for partners and clients while also removing logistical costs for the operator.

1. Traditional approaches to logistics & mobility

a. Last mile logistics and home deliveries πŸ“¦

Traditionally, last mile logistics consist in dispatching deliveries from a depot using large vehicles (i.e. vans) and assigning them an efficient sequence of drops. The optimisation problem faced by these kinds of operations lies in minimising the total number of kilometers travelled while respecting the time constraints of drivers (e.g. a driver may only be able to do 8 hours in a day). Due to the complexity of optimising the routes, these are often planned a day in advance. One of the unavoidable costs of these operations is the return to the depot, or dead miles, where the vehicle is empty. Dead miles are particularly burdensome for the operator, and often a forgotten cost of running logistics.

Beyond the unavoidable burden of dead miles for this model of logistics, we’ve also discussed in our previous article the inefficiency of vans due to congestion and the difficulty of parking, along with their severe negative impact on the health of cities.

b.Transport, food and courier deliveries 🍲

Separately, in the world of urban mobility, classical courier companies or taxi services operate on a short time notice, and instead of picking up from a depot, pick up directly from a point in the city and deliver to another one. Because of the difference in nature of these two logistical problems (planning a day ahead from depot vs last minute pick ups), these are rarely dealt with by the same companies and tend to rely on different kinds of vehicles (vans vs motorbikes or bicycles). Efficiency in the latter lies in having available resources near the pick up points readily available.

The crux of the problem lies in predicting as accurately as possible where and when orders may come in. A major cost in these operations comes from 1) having idle drivers waiting for jobs and 2) the “dead” miles between jobs. These services have been recently taken on by companies that pay “workers” (rather than employees) by the drop (e.g. Uber, UberEats, CitySprint, Deliveroo, Addison Lee etc) and simply opt to not consider these associated costs (despite the well known social implications for workers). The smaller capacity of vehicles used for point-to-point logistics (mopeds and standard bikes) also means they need to treat each order separately when larger capacity vehicles could potentially stack orders going in similar directions, and thus significantly reduce the logistical costs (a concept similar to car-pooling).

2. The Pedal Me approach: constructing Agile Urban Mobility networks

a. The Pedal Me bikes – at the crux of adaptive logistics

A core part of the Pedal Me philosophy lies in using cargo bikes to their full potential. The Pedal Me bikes are designed to be both fast and extremely adaptive in terms of what loads they can carry. The two-wheeled front loading design gives them the benefits of standard bicycles when bypassing traffic, while carrying loads of up to 150kg – a skill only possible with the professional training provided to riders.

To the novice eye, a Pedal Me bike may look a lot like any of these below, or even like they are able carry less:

 

Yet, despite their simplicity, the Pedal Me bikes are the only vehicles that can carry :

  • two adults and a small dog
  • 480L of essential products and food
  • 150kg of liquors and beers
  • 50 hot meals
  • a cement mixer
  • a fridge

back to back in the same day while moving at an average speed of 15km/h in Central London.

At the moment, the Pedal Me fleet covers over 25,000km each month doing exactly that.

b. Agile Urban Mobility Networks

Unlike other logistics companies, Pedal Me tackles the broadest part of the urban logistics market. This includes pre-planned multi-drops coming from a depot or from pick up locations across the city as well as point-to-point deliveries, with both last minute orders and passenger journeys.

In this section we explain why the Pedal Me model can overcome the limits of classical approaches to urban logistics discussed in the previous section. This includes (in no particular order): dead miles, idle time, geographical uncertainty in demand patterns and unfair employment conditions.

Approaching multiple markets at the same time also means the company can be more adaptive and resilient in the face of unexpected changes. During the first lockdown, Pedal Me was able to adapt to the sudden loss of all office deliveries by quickly switching over to offering safer travel options for vulnerable patients and delivering over 10,000 care packages to assist residents in Lambeth.

In our previous article, we explained how the smaller capacity of cargo bikes can lead to fewer total kilometers travelled. We review the example of the Water House Project (WHP) restaurant in East London, consisting of 9 drops spread across the city. Traditionally, these would be delivered by a van for a run of 54km. A cargo bike is only able to carry 6 of these boxes, as they are quite voluminous. Splitting the job onto three bikes results in a total distance of 48km, brushing off more than 10% of the total. A further benefit is that the deliveries can be done within a much shorter time window.

as the crow flies routes for three cargo bikes (total distance 48km)


as the crow flies route for a single van for all 9 drops (total distance 54km)

If this single job was isolated, the cargo bikes would have to return to the depot and the total count of dead miles across the three bikes would be larger than that of a single van. However, by tackling multiple markets at the same time, Pedal Me riders are available to cover for a wide range of jobs once they are finished with a run. Indeed, the WHP job is placed in a network of dozens of other jobs happening in similar time windows. Rather than returning to the depot, they can directly go to the nearest job needing service.

This adaptive approach to logistics,Β coupled with the more reliable times of cargo bikes in traffic, also means that unexpected events (e.g. delays or mechanicals) are much less likely to disrupt the planning for the day.

c. The Power of Network effects

We have seen that cargo bikes imply shorter delivery runs due to their capacity constraints. Shorter runs also means that vehicles are empty more frequently, and at different locations in the city. At the same time, the adaptive nature of the Pedal Me bikes in conjunction with the strategy of tackling multiple markets at the same time means more jobs across the city available to them.

These two factors combined together create a network of empty vehicles and jobs needing to be picked up throughout the day.

In this section, we study how, the density of this network affects the expected “dead” miles between jobs. To model this, we pick locations for empty riders (blue) and available jobs (orange) at random.

We then pair each free rider to their closest job. Each segment here represents the dead miles between a rider’s last job and the next one. With few riders and few jobs, we see that the distances are 1) quite unpredictable and 2) can be quite long.

We now look at the network as it grows denser, with more riders and jobs available. We find that on average the dead mile distances are significantly reduced.

 

This becomes clearer as the density further increase.

Finally, we plot the expected dead mile distance for a job against the density of the network (i.e. the number of jobs and riders available).

Due to the nature of network effects, we find an exponential relationship between the reduction in dead miles and network density. If one thing, the Covid-19 pandemic has taught us is the devastating power of exponentials. In this case, as the network grows denser, riders have shorter distances to their next pick up and less time to wait. This means 1) faster service for partners and customers, 2) fewer dead miles and idle time, 3) broad coverage over the city (more resilient to geographical uncertainty) 4) cheaper logistics for the operator.

Beyond the drastic cut in dead miles, a denser network of jobs also means more opportunity for stacking jobs together, which can lead to better prices for clients and a more profitable business.

Conclusion

In this article, we’ve presented the two dominating models for running last-mile logistics in dense urban areas. We highlighted the heavy burden of dead miles when operating from a depot (e.g. next day delivery), and the waiting time and dead miles that come with on-demand delivery (e.g. taxi or food deliveries), along with the unsustainability of the gig-economy. The adaptive nature of the Pedal Me cargo bikes, their speed and efficiency, paired with our philosophy of approaching mutiple mobility markets at the same time introduces a new paradigm for urban logistics. As Pedal Me continues to grow, our network of riders across the city will continue to provide quicker and cheaper services for partners and clients.


Written by Nicolas Collignon

Data science & rider @ Pedal Me.