Operations planning for swappable battery micromobility

Zoba
Zoba
Apr 16 · 5 min read

Zoba provides demand forecasting and optimization tools to shared mobility companies, from micromobility to car shares and beyond.

This post is by Dan Brennan, cofounder of Zoba.

As more micromobility operators transition from non-swappable to swappable battery fleets, they must navigate an increasingly complex set of operational decisions in the pursuit of positive unit economics. Managed correctly, swappable fleets are more operationally efficient than non-swappable fleets and will have an outsized impact on the sustainability of the micromobility industry. When they are managed poorly, however, swappable fleets increase both operational complexity and costs.

The best operational teams go through a mindset shift when switching from non-swappable to swappable vehicles. The minimum interventions related to batteries, maintenance, and regulatory or city complaints are not sufficient to achieve positive unit economics. In non-swappable fleets, vehicles are moved in and out of the market for charging, which means that effective deployment strategies can match supply with demand. In swappable fleets, vehicles stay on the ground longer, meaning that markets need to execute additional, elective but mission-critical interventions in order to achieve high performance. The vehicles won’t tell market managers when they should be moved. Managers must decide when to move vehicles, how many to move, which to pick up, and where to drop them off, then allocate the necessary resources to do so.

Market interventions for swappable fleets can roughly be broken down into two categories: required and voluntary interventions.

  • Required interventions keep the market operating at a certain supply level. These include: swapping batteries, conducting maintenance, and adhering to local regulations. These interventions are necessary for maintaining fleet size, equity zone allocations, and vehicle availability. These costs increase with utilization.
  • Voluntary interventions are additional tasks meant to improve market performance and include rebalancing and dynamic pricing. Given these are entirely voluntary, selecting and executing these tasks incorrectly may lead to both an increase in cost and a decrease in performance.

Choosing to forego voluntary interventions in a market entirely will lead to a degradation of performance, as my colleague Evan Fields described in a previous post about supply and demand imbalances. Luckily, the right combination of voluntary and required interventions will result in profitability at the market level. For the rest of this post, I will focus on how to manage voluntary rebalance task interventions.

Strategy 1: Combining all voluntary interventions with required interventions

Fleet managers may choose to combine all voluntary tasks with required interventions. In practice, a manager might only rebalance vehicles that require a battery swap or have a regulatory complaint. If the team only moves vehicles with a required task assigned, they can minimize their total number of vehicle visits and their costs. While they avoid significant additional costs, market performance will degrade significantly and hurt profitability. Over time, users will cause a supply and demand imbalance as there will be fewer opportunities to rebalance vehicles in a poor position.

In this scenario, the pool of potential rebalances only include low battery vehicles. Additionally, the market team will likely rebalance vehicles that were in a high demand area when they were swapped, actively hurting market performance. Low battery vehicles usually get that way because they are in high circulation and many will be a good location when they run low.

Strategy 2: Separating voluntary and required interventions

A second common approach is to separate voluntary and required interventions entirely. For example, the overnight shift might execute rebalances, then run another route in the morning to swap all batteries. Splitting shifts means that the team completes all tasks, but at a high operational cost. The motivation for this approach is usually that it decreases the operational complexity of combining swap tasks with rebalancing tasks and therefore, reduces work for the local team. Many of the vehicles rebalanced overnight might have needed a swap. Additionally, visiting the same locations twice a day at different times greatly increases vehicle miles traveled (VMT) and the amount of labor required to maintain a fleet. In this approach, the market will receive more ridership but costs will dilute those gains significantly.

Strategy 3: Opportunistically combing required and voluntary interventions

The final, Zoba-recommended approach is to selectively combine voluntary and required interventions to minimize vehicle touches and vehicle miles traveled while maximizing operational efficiency. Here is how that would look:

  1. Determine the volume of rebalances required to maximize profit in a market (Zoba has a tool to support this. Contact us to discuss your rebalancing ROI).
  2. Determine areas that require rebalancing pickups and subselect vehicles in that area for rebalance that are below a specific battery threshold or must be visited for other reasons.
  3. Combine, route, and batch van trips to opportunistically overlap voluntary and required interventions using a methodology similar to the one described by my colleague, Nick.

Using this approach, a market will execute all required interventions as well as the necessary level of voluntary interventions to maximize fleet performance, simultaneously reducing operational costs. If required interventions are treated like sunk costs, then this methodology can reduce the cost of rebalancing by +30% depending on the level of fleet utilization and swaps required in a market.

This method gives markets flexibility in execution. By selecting the best vehicles on which to combine tasks, a market can either execute all interventions using one van/trip or can make a combination rebalancing and swap run while a follow-on swap run is executed to finish off any swap tasks that were not combined with rebalance tasks on the first run.

Zoba’s operational decision automation platform eliminates the work required to intelligently combine voluntary and required interventions for mobility fleets, allowing market managers to focus on higher-leverage tasks like forming relationships with city stakeholders and managing their teams.

If you’re interested in improving your fleet or operational efficiency we’d love to hear from you! You can learn more about our work and reach out at our website www.zoba.com.

Zoba Blog

Zoba increases the profitability of mobility operators through decision automation.

Zoba Blog

Zoba uses demand forecasting and optimization to improve the performance of shared mobility services. On this blog, Zoba operations leaders, data scientists, and engineers write about the problems we solve for shared mobility operators and tools we use to solve those problems.

Zoba

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Zoba

Zoba increases the profitability of mobility operators through decision automation.

Zoba Blog

Zoba uses demand forecasting and optimization to improve the performance of shared mobility services. On this blog, Zoba operations leaders, data scientists, and engineers write about the problems we solve for shared mobility operators and tools we use to solve those problems.