A glimpse of the future: rehearsing last-mile delivery services

How can strategic design help guide these decisions and explore new business opportunities?

Using autonomous, last-mile delivery service as a pedagogical example, this article will provide an example of what these practices can look like and why their use in early stage development could better support multidisciplinary teams by guiding their decision-making about new products and services.

You’re walking down the street of Bagarmossen, a small suburban neighborhood in Stockholm. A shiny little robot on wheels approaches you. It’s kind of wonky, it tilts to one side a bit, and it seems to huff and puff to get over obstacles. You hope it will safely make it to where it’s going. The robot rounds another pedestrian and stops at your local grocery store. A store clerk comes out and puts a grocery bag in its box. The robot soldiers on to deliver the groceries to one of your neighbors.

This little delivery drone is part of a fleet of wheeled robots roaming the streets. They constitute a new local delivery service shared among the several existing businesses already present in the city. This system aims to make better use of space and resources by sharing and reduce the number of vehicles while better servicing local businesses and neighborhoods.

The drones can pick up goods from logistic nodes: grocery stores, shops, and public services and deliver them to local residents. Customers can conveniently place and manage orders and deliveries via a mobile app. Peer-to-peer deliveries are also possible. People can book an available delivery-bot, define a starting point and destination, and send the package off to friends and grandparents. When it runs out of battery, the drone can return to its home base and get recharged. The fleet operations are largely autonomous and self-managed through the cellular network, though there is supervision by local fleet managers — usually kiosk owners and employees. Brand presence and customer experience of the different parties involved are ensured by digitally augmenting vehicles and by dynamically adjusting logos and brand identities according to the company or business partner enabling the service.

Needless to say, this service doesn’t exist yet. It’s a speculative concept we’ve imagined and mocked-up using a small cardboard box placed on a tiny radio-controlled car platform, with a few wireframe screens as props. This project is part of an ongoing internal initiative aimed at exploring how strategic design research can help us guide digital transformations and transition our existing infrastructures and services towards more responsive, adaptive, and people-centered systems. This design intervention lasted approximately five hours, with two weeks for preparation and roughly 200€ for materials.

Background

In San Francisco and Tallinn, short-distance delivery robots already roam the streets on an experimental basis. Considering the advantages in safety and efficiency that automation brings, it’s reasonable to think that autonomous fleets will be part of your life soon. This probable near-future presents an interesting opportunity to explore through design. How might all these drones change our city? Where should they ride and how should they behave? What types of services could such a system support?

We drew parallels to a recent, similar example: within a few years, electric scooters and micro-mobility companies sprang up in cities around the world. While many appreciate them as a quick way to get where you’re going they also sparked debate as some people found them obtrusive and unsafe. Although microbility services are probably the first successful shared mobility platforms, the way they were introduced into our cities — multiple companies competing on public ground — caused systemic issues from land use, environmental issues to market regulation. One thing was clear though: no one asked us, the citizens and consumers, and all problems had to be painfully fixed later on.

This triggered a question for us: Would the same issues arise with last-mile autonomous delivery field? Will we have to experience overcrowded streets and sidewalks or perhaps an accident? How can we use design to find the best way to fit new technologies into our lives, giving a voice to all those that will be affected by design decisions and possibly anticipating the consequences of our actions?

Beyond user-centeredness

When it comes to addressing last-mile distribution challenges, what seems to be missing is a more open, systemic and inclusive approach. When looking at recent developments, all major companies still pretty much view these technical innovations as incremental extensions as stand-alone new solutions. The focus is usually on product features and the user experience of digital touch points.

As strategic designers and researchers, we understand that the “experience” is broader than the look and feel of a mobile app, and requires an approach that goes beyond user-centeredness. The introduction of autonomous and interactive systems like delivery drones requires more awareness of potential systemic consequences and side effects.

Whether it’s a new car or a new mobility app, new innovations are often portrayed within friction-less worlds where cities are made of large sidewalks and upscale neighborhoods. But the world we live in is way messier than what we often see in corporate advertisements.

Regional economies, neighborhoods, culture, rules and attitude vary from place to place. Within this complexity, it’s difficult for new services, conceived in meeting rooms and developed through traditional design thinking, to serve people well from the beginning.

Towards community-centric design, a field approach

As a way to address these questions, we began exploring how to guide the introduction and assimilation of new technologies into their environments. Therefore, we took our props into the field — Bagarmossen, a small modernist and microtown-like neighborhood. We used our little delivery cardboard robot and a couple of wireframes of a possible mobile application to illustrate our concept and engage people in a conversation about automated last-mile service possibilities and challenges. Our field research happened in the afternoon, which allowed us to observe the changing dynamics as the neighborhood transitioned from day to evening.

We intentionally kept the prototype’s concept and aesthetics looking relatively sketchy and undefined. A reflective coating was added so the prototype would reflect the city around it and create a more relatable and familiar robotic look. Our intention in doing so was to get people to comment and engage with the
prototype.

By staging this possible future service in the field, we allowed our early concept to interact with its future users and context. Through this dialogue we constantly challenged the nature and potential of what our service could actually become — a shared platform or a privately-owned device, or what type of business could this little drone support, beyond moving goods? This approach, if employed in the early stage of the design process — when the focus is more on exploring and inquiring what ought to be designed rather than proving feasibility or usability of an already defined solution — can bring in many advantages to designers and their clients when it come to the modeling interactive systems and their services.

Check out the summary of our methodological learnings and key findings.

1. An open design practice

We drove the prototype around the neighborhood, simulating entering and exiting stores, kiosks, and buildings. No participant was recruited and nothing was a set priority, but the small robot made people naturally curious. In a few hours, we interacted with a variety of people of different professions, ages, sex and education: shop owners, parents with kids, and many other “experts of their environment”.

We discussed the possibilities and concerns around the drone delivery concept, asking what-if questions, such as “what if there wasn’t just one but many of these on the streets”? Through these open-ended conversations with potential future users, we received relevant feedback on how a potential delivery service could better serve local inhabitants and businesses.

From a service perspective, what we initially thought was a delivery service for parcels and groceries was suddenly much more. With a more community-centric perspective, we discovered more about the public utility dimension of such last-mile delivery services. For instance, we stopped in front of the community library and the pharmacy, and we saw elders carrying their food trolleys and kids coming back from school in the dark with their oversized backpacks. We spoke with local baker who thought that she could easily serve customers who haven’t had the chance to pass by the shop. All this information made us reflect on the possible scale and qualities our drone could have. We needed to further explore prototypes and learn how to open up our design process to a diversity of people, needs and interpretations.

2. The context strikes back

Exposing an early concept to its context not only provides insight into the service and possible business models. It also allows us to encounter unexpected situations that would otherwise be difficult to anticipate or predict by developing concepts in the studio.

The more our four-wheeled, cardboard friend was exposed to the real world, the more it challenged the way we were looking at it, as we became more aware of other factors that could interact with it. While driving around the neighborhood, we realized our machine would interact with actors that we hadn’t predicted. For instance, a group of dogs became truly excited at the sight of the drone, reminding us that animal-drone interactions would happen. In addition, we soon realized that our drone could encounter much more dangerous scenarios when we nearly crashed it into a kart driven by a municipality gardener.

But it’s not always only about people. The interaction between the drone, the built environment, and other technologies also provided relevant insights from an interaction and product design point of view. Automatic sliding doors wouldn’t open, as they couldn’t recognizing the drone; sidewalks curbs were challenging for the drone and its small wheels, while current road-uses and their partitions made us wonder whether our drone could or should drive. Our misadventures made us reflect on the drone’s behaviors and the etiquette it should follow when crossing paths with people and vehicles. In particular, it made us consider what its machine vision software should be taught to recognize and respond to.

This type of education and sensitivity should take place through a deep understanding of different contexts and their dynamics. We should anticipate the possible side effects of new technology, rather than fixing and patching mistakes afterwards.

3. The aesthetic of interactions

When it comes to human-drone interactions, it was interesting to observe how participants show emotional reactions towards the drone by carefully avoiding it or hoping that it doesn’t crash into something. This may be partially due to the drone’s slow speed and clumsy movements that made people think it was not so intelligent and required more attention.

These clunky qualities differ from the prevalent super-intelligent and efficient rhetoric around machine vision and robotics, but that somehow seems to work, and might be interesting to explore when discussing the introduction of this technology into everyday life. Despite our efforts to anonymize this delivery drone with undefined aesthetics, we were caught off-guard when a senior citizen told us that it resembled a traditional “sausage-box”, so he naturally expected food to be delivered in it. This highlighted that peoples’ expectations are intimately linked to their cultural background, which may influence perceptions and acceptance of this technology.

Design as a way of questioning

This experiment is only the beginning of an endeavor that would require a range of skills and professions that go far beyond strategic and industrial design. There’s undoubtedly other directions this experiment could have explored. What about the data and information these machines and their vision could collect, and how would they be used? What are the implication for privacy? What materials could we use to foster engagement, learning, and understanding of this complex subject, to foster more dialogue?

Nevertheless, the insights gained from our field exploration provided material for some ideas on how to work with “futures”, and how to refine and open up an idea for many interpretations. In particular — despite its sketchy, low-fi form — our exploration revealed new considerations for rethinking future services and infrastructures. We must develop new design methods to deal with the increasing complexity of society and its technical systems.

The process presented here is not about problem solving or validation of this specific design concept. Rather, it is about exploring what conversations emerge when something that doesn’t yet exist — and therefore invisible and hard to related to — is made tangible and present in an everyday context.

Staging our speculative concept in a typical neighborhood gave us an impression of the collective experience of a future last-mile delivery service. In a short time, we got a glimpse of a complexity of relationships and interactions taking place on multiple scales — product, service, policy and infrastructure — that would be otherwise difficult to sense. For a brief moment, our project opened up an opportunity for people to sense and question the future interactions and possible consequence of our concept in use.

Through this open and active dialogue between the subject, the context and us, participants were able to form ideas about these networks based on their particular individual interpretations. Through such a loop, new potential crossover points between an envisioned system and its context emerged, allowing us to critically question our ideas and to identify new design criteria at all levels: service and business model; touch points; possible new users, uses, forms and interactions.

These insights shows how prototypes don’t need to be functional and expensive to provide valuable information. Making sure the “right thing” is developed from start — before investing in engineering and implementation — will be much more valuable and cost-effective. Technology is, after all, merely an enabler. Including a diversity of participants and stakeholders, learning how to assimilate technology into their lives, and solving real problems for people is key. If the right question are addressed, meaning and usefulness are created — and business value will always follow.