Tag: Business Models

The depth of critical thinking

A picture of a Charles Rennie Mackintoch chair by Chris 73 / Wikimedia Commons, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=857489

I made a bad joke at work recently. This isn’t necessarily unusual. The reaction to this bad joke made me think a bit more than normal though.

While reviewing some research on business models I observed that most of the models were predicated on the need to increase trust between businesses and their customers.

I wondered out loud if trust was in danger of becoming the next big over-used word and idly mused that we should get ahead of the game, joking that we should think about post-trust business models.

Unfortunately I was both believed and misheard. I was believed because sometimes I sound convincing — well, I am a middle-aged white man with a beard and a convincing poker face…—I was misheard because someone thought I said post-truth business models and, without me realising it, started researching that topic.

“Post-truth” was last year’s word of the year. It even has its own wikipedia page. The Oxford dictionary describes it as:

an adjective defined as ‘relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief’.

We often talk about post-truth at the Open Data Institute. We work with data after all. People ask our opinions on it. Some people tell us that better data and more facts is the answer to the challenge of “post-truth politics”. They ask us to imagine a world where someone reading a newspaper story can click on a fact to find out who produced it. And then click on the name of the fact producer to find out who funds them. And then click on the funder of the fact producer to understand their motives. This will soon cut down on those pesky emotions and bring facts back to their position of influence.

Unfortunately, there are problems with that vision.

Why and how will people click on a fact and what will they do next? We need to make it interesting for people to want to know more, to want to dive down beneath the story into the world beneath it. We need to make sure that the world beneath the story is present and linked together. We need to give people the critical thinking skills to navigate that world.

But even that risks not being enough. If you don’t believe me ask any philosophy student. One of their early courses will be on epistomology, the study of knowledge. They might be asked whether they can prove that the chair that they are sitting on is actually a chair. The students will quickly learn that for centuries, if not millenia, philosophers have been playing around with this and similar propositions.

A brain in a vat By made by Alexander Wivel [1]. — knol article, CC BY 3.0, https://commons.wikimedia.org/w/index.php?curid=8719730

The student will be asked to prove that they can actually sense the world and experience the chair rather than it being a trick being played on them by a Cartesian demon, some controlling their brain in a vat, or — heaven forbid — someone about to be tortured by Roko’s basilisk for failing to bring about the AI singularity.

The students will soon realise that the concept of a chair can mean different things to different people and get taught that many languages and cultures don’t differentiate between blue and green. They will put up countless facts about chairs and a good philosophy lecturer will knock them all down. Minds get blown in epistomology courses.

At the end of a bewildering course the philosophy lecturer might ask their students to vote on whether they have managed to prove that their chair is a chair. Some hands will go up for no, some for yes, others might waver a bit. When my own epistomology course got to that point the lecturer held a vote and then started laughing. “Does it matter?”, he said, “is it a comfortable chair and does it stop your bum from hitting the ground? Yes? Then it’s a flipping chair.”

You see the world is already complex enough and humans can decide to make it even more complex by diving into all the facts to try to empirically prove everything. Some of us love to do that and there are times when it is both fun and important to lose ourselves in a sea of facts and data to see what we learn. There are great things out there waiting to be discovered.

But in our daily lives we often need to dive just deep enough. To not submerge ourselves in the full sea but instead to simply go to a reasonable level and form an idea that we can test. We can then hold that conclusion up to scrutiny. Perhaps by sharing it with a range of other people so that we can learn from their responses or by doing a simple experiment (did bum hit ground? No? Probably chair).

This can need some fearlessness, we have to be open to being wrong, but forming and testing ideas can often be a quicker path to a decent truth than all of the facts and data in the world. It might help stop some myths and falsehoods lasting for longer than they need to too.

Oh, and the person researching post-truth business models? They came up to me a few hours later to share what they’d learnt. I shamefully admitted my bad joke, profusely apologised for their wasted time and praised them for testing their ideas sooner rather than later…

Will bike sharing benefit from learning some data lessons from other parts of transport?

This morning’s news that bike sharing firm Mobike was launching in the UK caught my eye.

Bicycles by Vivera Siregar, CC-BY-2.0

The story was full of excitement about the convenience and how cycling can help people becoming more active and improve air quality by reducing the number of car journeys. But the story also featured challenges: piles of bicycles on pavements and congested cycling lanes in cities not expecting an increase in traffic. Transport authorities seemed to be caught between the desire to seize the opportunities and head off the complaints.

But one thing that was missing from the story was how familiar the challenges are and how cities are already tackling them in other areas. At the Open Data Institute, where I work, we like to talk about design patterns for policies that use data to create impact. Some of the patterns needed to make bike sharing better are already in use elsewhere. Bike sharing companies and cities can learn some lessons from cars, buses and other cycling apps to tackle the challenges a bit faster and grab the opportunities a bit sooner.

What is bike sharing

Mobike is one of a number of firms offering bike sharing services. The service is simple. You download a smartphone app, request a bike, go to the location shown on the app, get the bike, cycle to where you want, leave the bike somewhere convenient and pay your fee.

The bike sharing operator will need to process orders and payments, maintain a fleet of bikes and predict demand so that they can move unused bikes to where they are likely to be needed.

The local transport authority has a different task. They need to maintain transport infrastructure to suit the different modes of transport (walking, cycling, cars, buses) that meet the needs of different groups of users (able-bodied people, people with disabilities, tourists, residents, business travellers) at different times of the day. It’s great that cities are welcoming trials of another option in this already complex system.

Some of bike sharing’s challenges can be helped by better use of data

Some of the challenges posed by bike sharing are already being helped by data. Better use of data can tackle them more easily.

Neither cyclists or bike sharing companies want congested cycling lanes. It will make it hard for people to get where they want and risks increasing accidents. That will reduce the number of people who cycle, and reduce the profits that bike sharing companies might make. Giving transport authorities access to data about where people cycle and where accidents occur will help them meet demand and create safer roads. Giving cyclists data about congested cycling routes will help them make better decisions about where to cycle and when.

The bike sharing companies don’t want piles of unused bikes on pavements. They make money when the bikes are used. Bike sharing companies won’t have data on how congested a pavement is because of other traffic: for example bicycles belonging to a competing bike sharing company or because of pedestrians trying to get to lunch. But that congestion can damage their reputation. Giving bike sharing companies access to this data will help them make better decisions about when to move bikes. Giving transport authorities access to this data will help them understand the impact of bike sharing on other types of transport.

Data isn’t a magic bullet. You can give better information to cyclists, bike sharing companies and transport authorities but there is no guarantee that they will use it or that they can even use it quickly. But it can help. We’ve seen it already. The transport sector still has lots to do to improve data but it is a sector which is ahead of most.

Learning the lessons

Many transport authorities already publish open data about congestion, accidents and road closures. Google, Uber and Strava are starting to publish aggregated open data about usage of their platforms for car and bicycle transport through the Mobility, Movement and Metro programmes. By making this data openly available then everyone can improve the service that is provided to car drivers, taxi passengers and cyclists. Openness is essential. It means that cyclists and taxi drivers can use a whole range of services to decide on a route while transport authorities can easily combine the data to give advice or decide where to build new capacity.

Pedestrians can report congested pavements using services like MySociety’s FixMyStreet. The reports are published openly so could be used by the bike sharing companies and transport authorities. If the bike sharing companies all publish aggregated data about where their bikes are left then the decision making can be further improved.

The challenge of bad data business models

Ah, I hear some readers say, but surely there’s a problem? If the bike sharing companies openly publish data about where their cycles are and the routes that people take then won’t that mean that other companies will use that data to compete with them?

Well yes, obviously. But good competitors will know already. It is fairly cheap to get a few people, or a camera or another form of sensor, hanging around major destinations to take pictures of bicycles that can be counted by machines.

Ah, I hear other readers say, but surely the bike sharing companies will be planning to sell the data as part of the data monetisation strategy that everyone is recommending nowadays?

Well yes, they may think they can sell it. But data monetisation is not a very clever strategy for these companies. That isn’t only because their users might prefer the data to be used to benefit their community but also because their users are carrying the smartphones that they used to get the bike. Google, Apple, and the telecoms operators have similar same trip data. It has negligible value.

In a world where data is abundant then data monetisation will work when you can add value to data. For example, it will work for data aggregators, like TransportAPI and ITOWorld, but only occasionally for data publishers. Instead bike sharing companies should open up the data to improve the service.

Data is not oil but it is infrastructure

In the 21st century when it is so cheap to get and use data, business models based on the scarcity of data are generally going to fail. That is one of the many reasons why “data is oil” is an utterly utterly terrible analogy. The smart bike sharing companies will open up aggregate data about usage and the locations of bicycles. They will compete on the quality of services. That competition and focus on services can benefit their users and the wider transport network.

But what happens if bike sharing companies aren’t smart? If they choose to impair the service they give to their users because of a lack of understanding of data and bad business models?

Well, that’s the final data lesson for this post. Data is a new form of infrastructure. Governments are realising that this infrastructure needs to be as open as possible, while respecting privacy, so that businesses can be built and services improved.

The UK government and local authorities tried, and failed, to persuade bus companies to open up data so are now legislating to force it to happen. That legislation will improve services for bus passengers by making it easier for services like Google Maps, Apple Maps and CityMapper to help people decide on their journey.

If the bike sharing companies don’t decide to be smart then I suspect the genuinely “smart cities” will make the decision for them. Bike sharing companies will be welcomed, but only the companies that decide to provide better services by opening up their data. Smart companies will learn the lessons and get ahead of that particular game.

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