Building a food delivery fleet of hundreds of robots is like teaching math to third graders. Their ability to learn and interact with their surroundings emotionally is a work in progress, but the sky is the limit. If carried out well, growth and success are very likely.
Since starting in 2017, we’ve been scaling robotic technology to create smart cities while demonstrating to the general public and investors the extraordinary potential of the latest technological advances.
Not only was company culture and automation important, but setting boundaries and acknowledging the difficulties of the competitive tech space are key to success.
Most importantly, some of the most progressive companies deliberately take on employees with track records reflecting both failure and success as failing is an essential part of growth.
So if your fintech launch doesn’t go to plan or SaaS doesn’t gain traction, however painful it may be to let go and move on, you’re not alone. Almost 60% of startups pivot by changing their business plan.
With plans to grow tenfold next year and expand our team, this is what I’ve learned about scaling operations.
Assess Your Company’s Capability to Take on Large Projects
There are key performance indicators (KPIs) and quantitative metrics to measure a company´s success and help calculate the mid to long-term predictions to achieve profitability. I call them complex or compounded metrics – they are formed by input variables and governed by cost and time.
For example, at Kiwibot, we look at how much it costs to operate our robots per kilometer. Any journey in a pilot program that costs over $2 per km is not considered a progression from regular delivery fees. The project would need far more testing to be able to scale up.
What robotic delivery fleets are doing is similar to what Amazon did when eCommerce was less prevalent a few years ago: Exploring uncharted territory and working their way into the spotlight.
There were plenty of attempts to set up eCommerce sites and sidewalk robotic delivery services but only those that leverage existing technological capabilities, and apply them in new ways, can succeed.
Amazon didn’t invent anything new, they just leveraged the infrastructure and technology that already existed to take shipping speed to the next level.
Human capital is a vital aspect of your company’s capability to scale too – and culture is an indicator of this. Employees must show flexibility, persistence, resilience, and be prepared for challenges.
Startups are the kings of ambiguity, and the people you want by your side when times get tough are those that have equal levels of passion and persistence, otherwise known as grit.
Search for individuals who have survived failure and have irreplaceable knowledge from overcoming hardships. Most importantly, fail as fast as possible.
According to Jeff Bezos, the defining attribute of Amazon is its appreciation of failure: “Most large organizations embrace the idea of invention, but are not willing to suffer the string of failed experiments necessary to get there.”
And as soon as you see something that doesn't work, say goodbye. It doesn’t matter how attached you felt to an idea or innovation, there’s just no point going over old territory.
Start Small to Control the Risk of Growing Too Fast
Startups must be optimistic, but they often tend to overshoot with overly hopeful objections. Always make sure to underpromise and overdeliver.
Take calculated risks as you assess opportunities, start with small operations, and set up shop in one major city, allowing you to sprawl.
This is what would be referred to as a “cluster” – where concentrations of interconnected companies and institutions from a specific field are situated – a generic concept used by Michael Porter many years ago that still serves today.
As a company scales, it must cluster around points of interest and use cases that deliver traction. It’s vital to partner with organizations in a chosen region and improve relationships with city authorities.
Once you have one client signed or a city in the bag, there will be proof of your product gaining customers, and the company will grow swiftly.
For example, university campuses or cities like Los Angeles and Miami are significant markets for food delivery, so that’s where Kiwibot has active operations.
We have the capacity as a company to expand to Scotland and Wales, for example, but would that be good for business? Probably not. My advice would be: Always choose those “second cities,” know your limits, and set boundaries.
Pushbacks: Why It’s Harder to Scale Tech Companies
Scaling a tech company is notoriously difficult because of ongoing public antitrust sentiment and the sheer cost.
Andy Grove, one of Intel’s founders, once warned that it can be difficult for smaller US tech companies to expand while competing with giant rivals, and this can mean missed opportunities.
Delivery robots are part of the green revolution and have a set speed governed by laws in cities across the US. Indeed, technology needs regulation, but with that comes added taxes or licenses which can impact tech companies’ budgets.
However, these taxes could help generate revenue for city authorities and cover the costs associated with robotic delivery service operations. Tax implications are what transport technology companies should watch out for – it’s a repetition of the Uber and Lyft stories all over again.
Now, consider this example. Buildings have not been designed for robots, but there is a high demand for delivery robots to have self-autonomy indoors.
Imagine getting your food order delivered to your desk or a dress from Bloomingdales brought to your apartment before a date. In theory, it’s an incredible invention.
Still, it involves APIs to facilitate communication between robots and elevators, the merging of technologies, and a lift company to actually have the appropriate software.
It poses a costly venture which can be a blocker to innovation. Malls have the potential to drastically innovate with robots – like Westfield or Halfords – as they search for a leading edge. But will they take that leap?
This challenge is similar to what Google struggled with twenty years ago – the development of the cloud, servers, mapping data, as well as physical infrastructure. All the foundations had to be laid before the infrastructure could be built.
Over time, robotic technology will become cheaper as demand skyrockets. Think about Yelp’s algorithm, for example, which allows you to find a restaurant that has a view or allows pets – something that is now viewed as indispensable.
That opportunity came from mapping technology, and billions were spent on that by Google who now own about 80 percent of the market.
Learning to Manage a Lack of Resources
US Cities are now busy planning to revive the economy and help local businesses grow post-pandemic. One initiative that was introduced was food ordering apps in restaurants.
But when 80% of deliveries are made by cars powered by gas, cities are searching for green opportunities for local businesses. Diverging demand to delivery robots could be the answer, but there aren’t sufficient resources.
Covid-19 exposed the lack of tech infrastructure at a local level. From a technology standpoint, there are several major obstacles for robotic fleets to work with local businesses: The cost, legal issues, logistical aspects, and the fact that each has a different app. The solution is to integrate with their apps and offer an alternative tool for delivery.
It is vital that technology providers work together to offer free IT support and advice to those local businesses who need it, in an effort to protect jobs and the wider economy. When more and more tasks are becoming digitized or automated, but workers do not possess the skills that the technology requires, the outcome will be greater inequality.
Overall, it’s vital for tech companies wanting to scale to do market research, spend time creating demand for their product, assess their qualitative and quantitative metrics, and strive for continuous growth. The best way to move forward is by searching for innovative solutions to stop a lack of resources or high costs from being a barrier to innovation.