In our last post we described why critical thinking is a necessary and valuable skill that can help to improve decision making and unlock bigger topline growth opportunities. In this post we turn theory into practice.
This is the scene.
It’s the summer of 2017. We are a fly-on-the-wall in the office of an Automotive executive. He is trying to establish his brand in a fast-growing Mobility as a Service (MaaS) ecosystem, and particularly within urban mobility.
He is open to doing this via acquisition or by building it in-house, and has begun to evaluate a few of the emerging solutions and business models in the market; we are able to spot a coffee stained business model canvas, saddled between an Islay Single Malt and Elon Musk’s biography on a side table in the corner of the office.
But he has a nagging feeling that he hasn’t actively, persistently or carefully considered the data he has gathered, the hypotheses he has formed or the assumptions he has made. Becoming aware of this he reaches for a checklist he spotted on LinkedIn a few weeks ago, and proceeds to look through the questions.
He takes out his Mont Blanc and begins to scribble with a rare level of lucidity…
Urban areas are choking with congestion: road and public rail networks are nearing capacity, the average cost per mile of travel is rising and particulate air pollution is posing a public health risk. The status quo is economically, socially and environmentally unsustainable – and this situation will only be compounded as the percentage of people living in urban areas increases from 55% today to a forecast of 68% by 2050. This means we need to better utilise the increasingly constrained physical space in cities for the purposes of travel, whilst controlling the cost per mile of mobility and finding cleaner alternatives.
An analysis of passenger journey’s across a representative sample of users – from the commuter travelling to work from the suburbs to the retiree reliant on public transport networks – indicate that we are most underserved during their first and last mile of travel. These are the journey’s we make from our front door to a transport hub that connects us to the next part of our journey. These journeys are often done on foot (which is slow), by bus (which is faster, but not the most direct way of getting from A to B) or on a personally owned push bike (which requires us to lock it up and return to it at the end of the day, plus an initial investment cost). Although these journeys comprise short physical distances, they still represent a significant amount of total travel time (up to 50% of an end to end journey), especially in areas underserved by public transport networks.
Making these journeys using existing modes of road transport personal vehicles, taxis and buses are taking longer and longer as vehicle traffic speeds in many of those city centers are now averaging as little as 15 kilometers an hour (9 miles per hour).2 A fascinating big data analysis conducted by Strava, a platform that allows athletes to track their sports activities and connect with other athletes, calculated that running to work in London is now faster than travelling by road.3
Source: STRAVA and TFL ; * Central London
This becomes even more interesting when we overlay data that shows the average distance people are travelling is skewing towards short distances — below 15 miles (24km), most probably due to increasing urbanisation. This analysis of US car journeys estimates the volume of journeys and spotlights the potential value pool:
Source: Medium, Oliver Bruce
These datasets have helped the exec establish that micro-mobility (the industry term for short distance transport) could serve an unmet consumer need in a very big market ( journeys under 9.5 km). This has helped him to narrow his focus, but he is aware that he is still missing fresh insights and a strong point of view.
A large number of urban passengers now use some form of journey planning or mobility aggregator like Google Maps, CityMapper, Moovit to get from A to B. These services provide the passenger with a shortlist of options mixing transport modes and travel distances. The majority of passengers decide which one to take based on travel time, cost, accessibility and weather. The solution our exec invests in needs to win based on these decision-making parameters and hierarchy of needs.
But it also needs to seamlessly fit into a multi-modal world. Every signal in the market – from Uber’s Google maps integration to Daimlers move into building an urban mobility operating system – suggest accessibility and integration is no longer a differentiator, but a hygiene factor. This allows him to establish the following design principles:
At this point it could be tempting to start generating ideas, but we know we are still short of a fresh consumer insight. The decision-making pyramid helps us to understand how passengers decide between options, but we still don’t have a read on their intrinsic motivation.
We therefore need to develop a set of hypotheses that we can test to establish which motivation is most common, most of the time. This will help us to develop a first mile / last mile proposition that captures the greatest possible share of passenger journeys.
As well as knowing what motivates consumers, we need to understand how our organisation fits into a fast-evolving mobility value chain. Why? Because this allows us to evaluate where new value is being created, and figure out where and how we could win.
The exec calls in a gifted young analyst and asks them to build a few schematic Excel models…
After being talked through these excel models the OEM exec establishes that the last mile business model and unit economics are significantly different from manufacturing cars or even leasing them. He establishes that in the last mile world four levers make or break the viability of a business:
This exercise has helped him to understand: how much he can afford to spend on acquiring a customer, how often he needs them to use his service, for how long, and how many times an asset needs to serve them. An example of what a good output looks like is here.
The exec picks up the phone to his head of logistics, who assumes nothing and plans for every eventuality…
When it comes to building a new service there are many things we wish to be true. The nature of innovation means we need to make assumptions about the future to break new ground. However we need to go in with our eyes open – a failure to identify these assumptions at the start of the process could trip us up down the line.
Here are a few relevant examples that real businesses have failed to flag:
Hint: tree diagrams are a great way of capturing and linking a growing list of assumptions. These can help to priortise the ‘big and important’ assumptions and build further supporting assumptions around a core thing we ‘need to be true’ for our business to fly.
Have we critically evaluated the different options available to us?After all this thinking, doing nothing is still an option. If we believe that we have gathered enough insight and data to begin developing a new solution (i.e. we have met Jeff Bezos’ 70% rule), then a new set of options and decisions await us:
At this stage in the critical thinking process it is worth pausing to consider a wider spectrum of options and evaluating which ones best suit our strategic goal. To support this endeavor the OEM exec reaches for that Single Malt you might have spotted earlier. The question that now arises, is which cigar to pair it with?
1. UN data hub – [accessed July 2019] – https://www.un.org/development/desa/en/news/ population/2018-revision-of-world-urbanization-prospects.html
2. McKinsey, Micromobiity’s 15,000-mile checkup, 2019
3. Forbes, [accessed July 2019] – https://www.forbes.com/sites/carltonreid/2018/12/08/ running-to-work-quicker-than-driving-shows-strava-data-from-british-cities/#65514dbdbe01