Continuing a series of posts on Uber's business model.  Much of this material also applies to Lyft and other similar operations. For previous posts, see https://rvsoapbox.blogspot.com/search/label/Uber

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Another thing about Uber is that it operates as a two-sided platform, matching passengers with drivers. Two-sided platforms can only operate successfully if there is sufficient demand on both sides - people looking for rides, drivers looking for work.

As I noted in an earlier post, Uber might initially have been able to recruit more drivers than it needed, in order to provide a high quality of service to its customers. Many people may have signed up as drivers based on unrealistic estimates of the likely earnings, costs and overheads, but obviously this is not sustainable for long.

So if Uber's pricing model can't pay the drivers enough to make the job worth doing, who would be surprised that Uber is now facing a shortage of drivers? While Uber customers experience increasing prices and worsening service levels.

So after years of what they regarded as unfair competition, traditional taxi services are now returning to popularity in large cities such as London (black) and New York (yellow).

But this has also resulted in an excess of demand over supply. In recent years, traditional cab driving has been hit by a triple whammy - competition from Uber et al, environmental regulations forcing older polluting vehicles off the road, and of course the COVID pandemic forcing many potential passengers to stay at home. So there is now a shortage of drivers and vehicles across the industry.

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Will Dunn, Why is there an Uber shortage? (New Statesman, 8 November 2021)

Caroline Tanner, Why yellow cabs are (again) your best bet in New York City (MSN, November 2021)

James Tapper, Black cabs roar back into favour as app firms put up their prices (Guardian, 30 October 2021)

In the early 1990s, I was on a research and development project called the Enterprise Computing Project, within an area that was then known as Open Distributed Processing (ODP) and subsequently evolved into Service Oriented Architecture (SOA). One of the concepts we introduced was that of Interaction Distance. This was explained in a couple of papers that Ian Macdonald and I wrote in 1994-5, and mentioned briefly in my 2001 book.

Interaction distance is not measured primarily in terms of physical distance, but in terms of such dimensions as cost, risk, speed and convenience. It is related to notions of commodity and availability.

Goods that are available to us enrich our lives and, if they are technologically available, they do so without imposing burdens on us. Something is available in this sense if it has been rendered instantaneous, ubiquitous, safe, and easy. Borgmann p 41

In our time, things are not even regarded as objects, because their only important quality has become their readiness for use. Today all things are being swept together into a vast network in which their only meaning lies in their being available to serve some end that will itself also be directed towards getting everything under control. Levitt

One of the key principles of ODP was distribution transparency - you can consume a service without knowing where anything is located. The service interface provides convenient access to something that might be physically located anywhere. Or even something that doesn't have a fixed existence, but is assembled dynamically from multiple sources to satisfy your request.

As we noted at the time, this affects the relational economy in several ways. It may introduce new intermediary roles into the ecosystem, or alternatively it may allow some previously dominant intermediaries to be bypassed. Meanwhile, new value-adding services may become viable. Over the past twenty years there have been various standardization initiatives of this kind, often prefixed by the word Open. For example, Open Banking.

The example we used in our 1995 paper was video on demand (VoD). At that time there were three main methods for watching films: cinema, scheduled television or cable broadcast, and video rental. Video rental generally involved borrowing (and then rewinding and returning) VHS cassettes. DVDs were not introduced until 1996, and Netflix was founded in 1997.

Our analysis of VoD identified a delivery subsystem and a control subsystem, and sketched how these roles might be taken by some kind of collaboration between existing players (cable companies, phone companies). We also noted the organizational and commercial difficulties of implementing such a collaboration. As we now know, in the VoD case these difficulties were bypassed by the emergence of streaming services that were able to combine control and delivery into a single platform, and the technical configuration we outlined now looks horribly complicated, but the organizational and commercial issues are still relevant for other potential collaborative innovations.

And our analysis of interaction distance in relation to this example is still valid. In particular, we showed how VoD (in whatever technological form this might take) could significantly reduce the interaction distance between the film distributor and the consumer.

People often talk about digital transformation, and want to use this label for all kinds of random innovations. As I see it, the digital transformation in the video industry was largely on the production side. While the switch from VHS to DVD brought some minor benefits for the consumer, the real difference for the consumer came from the switch from rental to streaming, reducing interaction distance and bringing availability closer in space and time to the consumer. So I think a more meaningful label for this kind of innovation is service transformation.

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Albert Borgmann, Technology and the Character of Contemporary Life (University of Chicago Press, 1984)

William Levitt's introduction to Heiddegger, The Question Concerning Technology

Christian Licoppe, ‘Connected’ Presence: The Emergence of a New Repertoire for Managing Social Relationships in a Changing Communication Technoscape (Environment and Planning D Society and Space, February 2004)

Ian G Macdonald and Richard Veryard, Modelling Business Relationships in a Non-Centralised Systems Environment. In A. Sölvberg et al. (eds.) Information Systems Development for Decentralized Organizations (Springer 1995)

Richard Veryard, Information Coordination (Prentice-Hall 1994) 

Richard Veryard, The Future of Distributed Services (December 2000)

Richard Veryard, Component-Based Business: Plug and Play (Springer 2001)

Richard Veryard and Ian G. Macdonald, EMM/ODP: A Methodology for Federated and Distributed Systems, in Verrijn-Stuart, A.A., and Olle, T.W. (eds) Methods and Associated Tools for the Information Systems Life Cycle (IFIP Transactions North-Holland 1994)

Wikipedia: ODP Reference Model

Let us suppose we can divide the world into those who trust service companies to treat their customers fairly, and those who assume that service companies will be looking to exploit any customer weakness or lapse of attention.

For example, some loyal customers renew without question, even though the cost creeps up from one year to the next. (This is known as price walking.) While other customers switch service providers frequently to chase the best deal. (This is known as churn. B2C businesses generally regard this as a Bad Thing when their own customers do it, not so bad when they can steal their competitors' customers.)

Price walking is a particular concern for the insurance business. The UK Financial Conduct Authority (FCA) has recently issued new measures to protect customers from price walking.

Duncan Minty, an insurance industry insider who blogs on Ethics and Insurance, believes that claims optimization (which he calls Settlement Walking) raises similar ethical issues. This is where the insurance company tries to get away with a lower claim settlement, especially with those customers who are most likely to accept and least likely to complain. He cites a Bank of England report on machine learning, which refers among other things to propensity modelling. In other words, adjusting how you treat a customer according to how you calculate they will respond.

My work on data-driven personalization includes ethics as well as practical considerations. However, there is always the potential for asymmetry between service providers and consumers. And as Tim Harford points out, this kind of exploitation long predates the emergence of algorithms and machine learning.

 

Update

In the few days since I posted this, I've seen a couple of news items about autorenewals. There seems to be a trend of increasing vigilance by various regulators in different countries to protect consumers.

Firstly, the UK's Competition and Markets Authority (CMA) has unveiled compliance principles to curb locally some of the sharper auto-renewal practices of antivirus software firms. (via The Register).

Secondly, new banking rules in India for repeating payments. Among other things, this creates challenges for free trials and introductory offers. (via Tech Crunch)

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Machine Learning in UK financial services (Bank of England / FCA, October 2019)

FCA confirms measures to protect customers from the loyalty penalty in home and motor insurance markets (FCA, 28 May 2021)

Tim Harford, Exploitative algorithms are using tricks as old as haggling at the bazaar (2 November 2018)

Joi Ito, Supposedly ‘Fair’ Algorithms Can Perpetuate Discrimination (Wired Magazine, 5 February 2019)

Duncan Minty, Is settlement walking now part of UK insurance? (18 March 2021), Why personalisation will erode the competitiveness of premiums (7 September 2021)

Manish Singh, Tech giants brace for impact in India as new payments rule goes into effect (TechCrunch, 1 October 2021)

Richard Speed, UK competition watchdog unveils principles to make a kinder antivirus business (The Register, 19 October 2021)

Related posts: The Support Economy (January 2005), The Price of Everything (May 2017), Insurance and the Veil of Ignorance (February 2019)

Related presentations: Boundaryless Customer Engagement (October 2015), Real-Time Personalization (December 2015)

As I have previously noted, drawing on research by Izabella Kaminski and others, there is something seriously problematic about the current business model of rideshare platforms such as Uber and Lyft. It seems that the only route to profitability is via some disruptive event in favour of their business. Although investors have poured eye-watering amounts of cash into these companies, this only makes sense as a bet on such an event occurring before the cash (or investor patience) runs out.

How does the magic of digital allow a centralized company with international overheads (Uber or Lyft) provide a service more cheaply and cost-effectively than a distributed network of local cab companies, many of which are run by one rather harassed guy in a small booth next to the train station? Well it doesn't. Even screwing the drivers can only go so far in stemming the losses.

So what is this disruptive event, that these companies and their investors are eagerly waiting for? One theory was that the rideshare platforms could only be profitable once they had eliminated all competition, by a combination of undercutting rivals and doing deals with local authorities - for example, offering to run other elements of the local transport network. Once a monopoly had been established, then they could start to push the prices up.

Obviously this strategem only works if the consumers accept the price rises, and the guy in the booth doesn't find a way to take back his business.

Another theory was that they were just waiting for self-driving cars. This would also explain why they weren't looking after their drivers properly, because they didn't expect to need them for the longer-term. However, not everyone was convinced by this. Aaron Benanav thought that they will have to wait rather longer than they originally reckoned, while Sameepa Shetty noted that Uber's ambitions in this regard were currently focused on small favourable pockets rather than being spread across the whole operation, and quoted an analyst who worried that investors were throwing good money after bad. 

At the end of 2020, we learned that Uber itself had come to the same conclusion, selling off the driverless car division to focus on profits.

So remind me, where are these profits coming from?

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Uber sells self-driving cars to focus on profits (BBC News, 7 December 2020)

Aaron Benanav, Why Uber's business model is doomed (Guardian, 24 August 2020)

Julia Kollewe, Uber ditches effort to develop own self-driving car (Guardian, 8 December 2020)

Elaine Moore and Dave Lee, Does Uber deserve its $91bn valuation? (FT, 17 October 2021)

Sameepa Shetty, Uber’s self-driving cars are a key to its path to profitability (CNBC, 28 January 2020)

Gwyn Topham, Peak hype: why the driverless car revolution has stalled (Guardian, 3 January 2021)

Related Posts Uber Mathematics (Nov 2016), Uber Mathematics 2 (December 2016), Uber Mathematics 3 (Dec 2016)

In some of my posts, I have used the terms vertical and horizontal in relation to Business Architecture. The purpose of this post is to analyse what these terms actually mean.

Firstly, the word vertical is often associated with value chain thinking. Typically, there is a process that spans from the raw materials to the finished product or service, and this process may either be divided between different actors or controlled by a single actor. Where a single organization controls the end-to-end process, this is known as vertical integration.

Large organizations typically have several versions of these processes, or even several entirely different processes. Bunding these into a single organization only makes economic sense if they can share resources and other stuff. For example, if procurement is done jointly, this may give the organization more buying power.

So there are typically a number of cross-cutting concerns, which may be referred to as horizontal. TOGAF 9 (released in 2009) identified "rich domain knowledge of both horizontal, cross-cutting concerns, such as human resources (HR), finance, and procurement alongside vertical, industry-specific concerns" as fundamental to Business-Led SOA.

So one version of horizontal integration involves establishing shared capabilities or services, which may support multiple value chains. Even when these value chains are distributed across different companies across different market sectors, one actor may seek to dominate the provision of these shared services, whether by merger and acquisition, technological superiority, or sheer market power.

In a 2005 discussion on Efficiency and Robustness, Stu Berman commented

The US economy is remarkably resilient to a wide variety of shocks (9/11 is a good example, as is Katrina) due to our horizontal integration rather than vertical. It is easy to look at history and see where colossal economic problems occurred - Soviet central planning, Nixonian gas price controls. via Chandler Howell

I have always argued that Business Architecture requires multiple Viewpoints. One reason for this is that the Activity or Value Stream viewpoint concentrates on the vertical dimension, while the Capability or Service viewpoint concentrates on the horizontal dimension. (Further viewpoints are required, because business architecture is not simply a two-dimensional problem.)

Note that the terms vertical and horizontal also appear in discussions of technology architecture, where they mean something rather different.

 

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Further discussion

Efficiency and Robustness: Central Planning (September 2005)

Business-Led SOA (February 2009)

Towards an Open Architecture for the Public Sector (May 2014)

 

See also

Philip Boxer, The Double Challenge (March 2006)

Richard Veryard, Six Viewpoints of Business Architecture (LeanPub, 2012)