Tiredness

As working in the gig economy is often a side-job from other forms of employment, working for Uber, UberEATS or Deliveroo can make a long day’s work even longer. A recent Financial Times article is very revealing on the impact of tiredness (many of their articles are paywalled so I will do my best to summarise). The article tells the story of Sami, who works an eight-hour shift at the supermarket Tesco and then works for Uber afterwards for additional money. He says that he’s often falling asleep behind the wheel and that fellow Uber drivers can often work 14 or 15 hours a day.

Uber currently doesn’t limit the number of hours someone can work for but sends messages when someone has been driving for a ‘prolonged’ period. However, Sami point out that Uber doesn’t know if the driver has been working somewhere else beforehand and so can’t easily calculate recommended working times. Either way, tiredness can be a real issue and pose a danger not just to the driver and passenger but other road users if an accident occurs.

Isolation

Working in the gig economy is a lonely job. For ride-hailing drivers, there’s possible interaction with the passenger but if it’s forced or unwanted by the passenger, their rating may go down. For food delivery riders, beyond a ‘hello’ and ‘enjoy your meal’, interaction with customers or other people is essentially zero. If people are working long hours, upwards of four for food delivery and up to 15 for ride-hailing, this can easily lead to a day spent with incredibly low social interaction. Coupled with a lack of control over orders, insecure income and low pay, long-term mental health issues are likely to develop.

Whilst in the past I’ve described how interaction with others is limited in the process of delivering i.e. from collecting an order to handing it over. The Financial Times article details important research by Kevin Daniels and others that shows communication and engagement with a line manager is important in ensuring the health and safety of ‘remote workers’. I’ve only contacted the head office once or twice and my issue was resolved relatively quickly and easily but feel essentially alone and separate from the overall company or platform. A lack of engagement with the head office reiterates this isolation and minimal interaction experienced.

Acid Attacks

Riders are also at risk of having acid thrown at them so their bicycle or moped can be stolen. This came to light after a spate of attacks in London this July where five individuals were attacked with acid, two of which were riders in the gig economy. This also links to more general physical and verbal abuse directed towards riders which has led some riders to avoid work in particular areas of London. I personally haven’t experienced anything like this but that’s probably due to the zone I work in having a high proportion of office buildings rather than residential areas. Hearing from other areas though, it does appear common.

It is welcoming though to see Deliveroo introducing increased safety measures for riders. These include a feature in the app that allows safety concerns to be raised, and the trialling of helmet cameras to collect evidence. As well as this, Deliveroo riders have been encouraged to meet with Air Ambulance and police representatives to discuss their concerns. What is of concern though, is the lack of support provided by other platforms like UberEATS and Jinn.

Pay Structure

There is also an increased safety risk due to the nature of pay in the gig economy, that encourages quick deliveries to earn more. As a ‘fee per drop’ pay structure appears to have become the most common, how much they earn is bound with how many deliveries they do. This is likely to increase assertive behaviour on a bike or moped, particularly during busy times, and thereby increase the risk of injury. Additionally, it’s not clear what variables affect how orders are assigned to riders. If average delivery time is a major factor, this encourages the incentive to deliver quicker.

Solutions Needed

Overall, it’s clear there are multiple health and safety concerns with the gig economy. Whether these outweigh the benefits is likely to be down to the individual. As a student, I’m only in the gig economy for a small amount of my week so these negatives are less pronounced. For others, these costs are likely to accumulate over time and worsen the situation. However, it’s clear that changes need to be made to improve the physical and mental wellbeing of those working in the gig economy, particularly those for prolonged periods of time.

As the title suggests, the article considers the flexibility of work in the gig economy, allowing students to balance studying, socialising and working. This is a central tenet of debates over the gig economy, a dividing line between supporters and those who oppose.

Whilst the article focuses on Uber, this flexibility is widespread for other platforms. Food delivery through platforms like UberEATS are arguably even more flexible than Uber. To work for Uber, you need a car, to work for UberEATS, you need a bicycle or moped. The entrance costs of the latter are far lower. In London, you can purchase a good budget bicycle for £300, but a car and the associated MOT and insurance is likely to be far more expensive. For cash-strapped students, this is a big factor. You can log in and out whenever you like for both platforms, but getting started in UberEATS is far easier.

The article raises another interesting point, about the role of self-driving cars. If there is widespread uptake of this technology, as many suggest, then Uber drivers may be forced out by another ‘disruption’. As I’ve said in the past, interaction in the ride-hailing gig economy can be significant. However, the spread of driverless cars could undermine this interaction for better or worse. Personally, I enjoy talking to the driver when in an Uber, but there’s no shortage of stories of silence during a journey.

I’m far more sceptical, however, of the potential for self-driving cars to disrupt the food delivery gig economy any time soon. Dominoes has recently been testing this in Michigan, USA. However, the use of a car is a major limitation. Unlike mopeds or bicycles, cars cannot weave in and out of traffic to reach their destination quicker. In slow-moving traffic in central London, this difference is likely to be significant. Whilst driverless mopeds could be a possibility, weaving through traffic may be beyond current technology. However, it may not be driverless cars that overtake bicycles and mopeds, but drones instead. Overall then, those working in the gig economy appear in for a bumpy ride, more than they’ve experienced in recent months.

The post, in The San Diego Union-Tribune, makes the argument that pay in the San Diego gig economy, regardless of platform, is ‘pretty low’. I’ll leave you to read and think about what the article suggests, but will draw out two things to expand on.

Drawing from a JPMorgan Chase & Co. Institute 2016 report, less than 1% of the San Diego workforce made money from some form of online platform. This number is likely to be greater in London, however, with a rise of 72% (2010-2016) of people working in the gig economy. This number is likely to vary even more when considering other cities in other countries, showing the varied importance of the gig economy to the local economy. This sector currently receives a considerable amount of attention, in part due to continued strikes and legal disputes. However, it should be recognised that in some cities the relative importance of the gig economy is rather small. As a result, people interested in social justice who might look to improve the conditions of the gig economy in their city, might better focus on other areas of urban inequality.

Secondly, the article doesn’t count the costs inherent to working in the gig economy. Whilst I can’t speak for platforms like TaskRabbit and Airbnb, the costs of working for companies like UberEATS, Quipup and Jinn are noticeable. Firstly, it’s necessary to purchase the relevant equipment, including a bike or moped, delivery backpack and uniform. It is then necessary to ensure the equipment is in good condition and seek out repairs if necessary. Personally, I’ve spent more on bike repairs than I did on the actual bike.

In addition, I remember speaking to one rider about his bike, where the frame was literally broken in half on the section in-between his legs and the seat. For moped riders, petrol is a major component and without it, they’re not going far. Whilst for some companies, fuel is reimbursed to drivers, I’ve heard that distance travelled is calculated as a straight line. Obviously moped drivers don’t drive this way in reality, so they’re not being fully reimbursed for the petrol used.

Whilst these costs might not appear much, the ‘pretty low’ pay means that they’re high in comparison to what many earn. There’s more information about pay in the gig economy in past posts here and here.

Give the article a read and let me know what you think in the comments section below!

Walking around London you’re bound to see delivery riders, but you often don’t know where they’re going and where they’ve been. Whilst I worked, I had the app Strava running in the background to record my location and speed throughout the night. This post is all about that shift, with a visual element too.

Before we delve into where I went, some basic shift stats are in order. It was a standard three-hour shift on a Saturday evening, where I delivered 7 orders. Saturday is usually quieter than Friday or Sunday. My average number of deliveries for a Saturday three-hour shift is 6.75 so slightly above average yesterday. However, I earned less under the ‘fee per drop’ system than if I’d been working under the ‘hourly’ pay structure (£26.25 vs. £28). No tips last night, either.

Here’s a quick video of the route I took over the entire shift, sped up 340x. Over the three-hours, I travelled 15.8 miles and climbed over 1,000 feet in elevation. My average speed was 9 miles per hour (mph), with the max reaching 21.7 mph. If I could consistently cycle at 22 mph that’d be some quick deliveries for customers and very quick money for me!

As the video shows, it’s very common to cycle through the centre of the zone repeatedly. This was particularly true last night, as I had no deliveries in the east of the zone around Clerkenwell. Normally a shift is more spread out, including deliveries around Euston, the Barbican and out to St Paul’s.

Interestingly, for a three hour shift, my total moving time was one hour 45 minutes. It’s not clear whether Strava counts walking through an apartment complex as moving or waiting. Therefore, yesterday I was cycling for 58% of the shift, with the other 42% comprised of waiting at the zone centre, at restaurants, and navigating flats and houses. There was a particularly long wait towards the end of my shift (beginning at 0:28 in the video). Normally, waiting for food at a restaurant takes one to three minutes so to be waiting for around 15 is rare.

The shift itself was somewhat different from a Saturday night shift. It wasn’t slow to the extent I thought of going home but it took longer for orders. I did find myself waiting at the zone centre, as you can see in the video at 0:17, 0:23 and 0:27. What was particularly interesting, however, was that no one else was waiting there. Usually, there’s at least three other riders waiting for an order. Demand for riders as shown on the app was considered ‘normal’ so the slight waiting is to be expected. However, riders received an email saying the Bank Holiday weekend should mean increased demand. Also, the Mayweather-McGregor boxing fight meant I expected more deliveries than there were.

I’d expect to cycle for longer and more widely in a normal shift. In the future, I’ll be sure to record where I’m going on a Friday or Sunday and then compare. Look out for that post in the future!

The main reason for the ban is due to security and safety concerns. Deliverers are considered “unauthorised visitors”, lacking the correct government checks. The head-teacher goes on to say “We have no idea who these delivery drivers are, so it is not appropriate for them to come to our school site and interact with other students”.

Restricting access and interaction with the school from any unknown individuals, gig economy aside, is of course necessary. However, it’s the idea that riders are interacting with others that I want to explore.

Interaction in a typical delivery

Minimal interaction with others is the norm for delivering in the gig economy, at all stages of the process.

When I enter the restaurant and give the order number, I stand quietly to the side, out of the way of ‘normal’ customers. Sometimes other drivers are also waiting and we might exchange words but we’re rarely there long enough for much more than simple shallow conversation. The only communication with staff at the restaurant is if they provide an update on when the food will be ready. They’re normally busy and there’s no time for anything else. Plus, I’m not wanting to hang around for too long, time is money in the gig economy.

Cycling to the destination is also rather solitary. I’ve seen other riders talk on the phone via headphones but for many, it’s the sound of the street or the music in their ears that makes up the largest portion of the ride. On the odd occasion the destination is difficult to find, it’s necessary to call the customer. This often entails some degree of confusion on both sides. In one instance, I told the customer I was outside the nearby post office, with them coming to the street to try and locate me. After he had not been able to, nor locate the post office, it turns out a fault with the address and the app had sent me five minutes in the wrong direction. It makes for light-humour, slight-annoyance.

Once I’ve arrived, I notify the customer via the app. For apartment complexes, it’s often necessary to call the customer via the intercom to be let in or via phone for them to come to reception. I hand them the food and/or drink, they say ‘thank you’, I say some small variation of ‘enjoy’ or ‘have a nice evening’, and then the door shuts. Delivery done and on to the next one.

Unique to the food gig economy?

Even other aspects of the gig economy provide more interaction than I experience. Although I rarely take an Uber for transport, when I do, I can interact with the driver and chat about anything. Working for a food delivery platform is often a frequent topic of conversation. Some Uber drivers also use their passengers as an audience for comedy or the subject of comedy told to others. However, with UberEATS, Deliveroo, Jinn, Quipup (or any delivery platform), at best a rider’s name is provided. Mostly, people just want to know how long the delivery is going to take. Although I have no experience with platforms like TaskRabbit, I’d expect interaction to be highly limited, perhaps only when receiving instructions and feedback (or criticism).

Good or bad?

For me, the minimal interaction is positive. It allows me to switch off, play music and enjoy cycling around London. It’s an enjoyable difference from university in the day-time where there’s far more interaction and communication.

I’m not alone on this, an interesting short documentary by the Guardian tells how Keran, who has autism with ADHD, found particular fulfilment and enjoyment from working with Deliveroo. He says he enjoys the freedom and being ‘away from people but being out and active’, showing how the more informal and less frequent interaction can be beneficial.

However, the fact I am studying in the day makes a large difference. If the main part of my day was to ride in the gig economy, then this would be far less enjoyable. To ride around the same streets all day, delivering food with no interaction beyond infrequent ‘hello’ and ‘thank you’ is far less fulfilling and enjoyable. It seems beneficial, then, that the gig economy emphasises multiple sources of employment. Otherwise, I’d expect many to get tired, mentally and physically, of doing the same task on repeat throughout the day with little opportunity for wage increases or interaction with others.

The algorithm uses machine learning to continually evaluate the most efficient way to assign orders to riders. It does this by considering a range of factors including meal preparation time, time of day, vehicle and distance. As a result, the average delivery time of Deliveroo orders has fallen by 20%. Quicker deliveries, in theory, also means more deliveries, letting riders earn more. This also has benefit in helping achieve a key recommendation of the UK Taylor Review.

The UK Taylor Review is a recent government review of modern working practices and what makes up ‘good work’. One of the central recommendations is to ensure that the average hourly pay of riders equals 1.2 times the UK minimum wage. With the introduction of this new algorithm, riders can earn more per hour and so be more likely to earn at this level. This is all whilst retaining the flexibility that is fundamental to the gig economy.

For the UK government, ‘Frank’ is beneficial in that it doesn’t contribute to undermining state regulations like the minimum wage, something many claim is at the root of the abusive gig economy. This helps to bring the modern, disruptive gig economy more in line with current labour standards, allowing them both to thrive without either being undermined. There are, of course, other issues such as a lack of sick pay and equipment costs that the government needs to consider. Nevertheless, ‘Frank’ is going some way in improving the situation for gig economy riders and improving their chances of earning the minimum wage whilst retaining work flexibility.

From a Deliveroo perspective, the introduction of ‘Frank’ shows they are at least trying to improve the pay situation in light of the Taylor Review. This is a wise decision given the UK government’s ‘serious consideration’ of the findings. Whilst the company might be more focused on the 20% reduction in delivery time, good for keeping customers happy, improving pay prospects for riders should always be at the forefront. Furthermore, with Jinn ‘pausing’ operations and no mention of any recent UberEATS developments (other than with McDonald’s) Deliveroo appears to be leading the way on improving rider pay and safety.

However, it is possible that ‘Frank’ will lead to greater waiting periods for riders. If the number of orders remains the same, and riders are completing them quicker, they’ll also be waiting longer for the next one. From personal experience, on some nights there is no shortage of orders and quicker deliveries to move onto the next one will be welcomed. However, Saturday and lunchtimes seem particularly quiet, with waiting prolonged periods of time not being uncommon. If Deliveroo can use the quicker delivery time to encourage new customers, then orders should increase and waiting periods be unaffected. Otherwise, the benefits of quicker delivery in terms of pay might be less than expected.

Also, no definitive list of what characteristics ‘Frank’ utilises is given. I’d personally be interested to know what variables go into the algorithm to determine who is given which order. Whilst some variables are of little control, such as the type of meal, others might enable riders to improve their prospects of being selected for an order.
When riders are free, we’re told to go to a central meet-up area that is claimed the best location for being assigned orders. However, if there are ten of us waiting and an equal chance of being assigned an order, would it be better to be more spread out, possibly closer to some restaurants in a popular area? Whilst a detailed breakdown isn’t necessary, a better understanding of what influences ‘Frank’ might go some way in reducing waiting times for particular individuals. Even if it’s of little use to riders, it puts Deliveroo in a better light if they are open about how their platform works.

‘Frank’ clearly has important ramifications in a number of ways; it could offer greater opportunity for a minimum wage whilst retaining the flexibility of the gig economy, even if waiting periods might increase. Hats off to Deliveroo for trying to improve the overall experience of the gig economy, Jinn, UberEATS and others appear almost silent on this front.

Just as I was finishing this post, Deliveroo have revealed new tech that should improve the restaurant experience of their platform. Expect a post on this soon! For more information on Deliveroo’s use of data in its operations, see this short article.

This is a much welcomed development, as some riders are actively avoiding particular areas. Whilst I personally haven’t experienced anything concerning, where I work in central London is well lit, busy and many customers are offices, unlike other areas of the city. It is also encouraging to see Deliveroo riders meeting with Air Ambulance representatives and the police to discuss the specific issues they face. It’s this kind of dialogue between groups that can help the gig economy continually improve.

However, safety in the gig economy is often secondary to other aspects such as pay. With the majority of riders being paid per delivery, as opposed to per hour, there’s greater emphasis on riding quicker to finish one order and begin another. I’ve also seen no information from companies on how deliveries are assigned to riders through the app, and whether average delivery time has any influence on this. If it does, there’s even greater pressure to be quick, which can mean rider safety is diminished.

Moped riders are also particularly vulnerable to unsafe situations, as their vehicle is often targeted, like in the recent acid attacks. A method of transport (bicycle or moped) is fundamental to working in the food gig economy and because no compensation is provided for equipment, riders have to fork out for anything new. This could then increase the pressure to work more, and quicker, to regain the lost wages and offset the cost of a new vehicle. This all accumulates to mean safety is always on the mind of riders. Additionally, a lack of sick pay means deliverers may return to work before they have fully recovered, putting their long-term health at risk.

Although not a direct purpose of using helmet cameras, they might have a secondary benefit in encouraging riders to wear helmets, something that seems uncommon for many riders and that companies have limited ability to enforce. Cameras might also encourage other road users to take more care in overtaking, as they are being filmed.

Delivering will never be completely safe, due to the nature of riding in a city and of the gig economy as a whole, but it’s good to see progress being made. Other platforms have been silent on this issue but, as one rider in the acid attack was working for UberEATS, hopefully they will follow Deliveroo’s suit.

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The company has decided to focus solely on London, halting operations in Edinburgh, Glasgow, Manchester, Birmingham and Leeds (as of the 25th of July). It doesn’t seem clear but the company also seems to have stopped in Spain (Barcelona and Madrid), too. Citing the search for profitability, a co-founder said that because over 90% of orders come from London, operations in other areas would be ‘paused’ until September. Interestingly, the option to apply for work in these others cities is still available on the website, even nearly one week after the announcement.

Whilst this development shows a lot about the competitiveness of operating in the gig economy, it also highlights the associated insecurity for workers of the gig economy. Whilst you could be fired in any career or workplace (as many in Jinn’s offices have reported), to have it done so bluntly as a text is particularly telling. Also, by reminding individuals that Jinn will return in September, it suggests the company believes they can easily fire and hire riders as and when they see fit. Whilst the gig economy is often depicted and advertised as flexible, you obviously cannot utilise this benefit if operations suddenly cease.

However, it is all too easy to paint this as representing the job insecurity of the gig economy and leave it there. This insecurity is mitigated by the presence of numerous other platforms that are always open for hiring. Riders that have been affected by this, will hopefully seize the opportunity to join a (hopefully) more ‘stable’ platform like UberEATS or Deliveroo. Whilst these companies aren’t perfect examples of a gig economy company (and what that represents is up for debate), they’re larger players in the scene and so shouldn’t be ‘pausing’ operations in cities any time soon. Some riders already adopt this tactic, and are registered for multiple platforms, sometimes working simultaneously. Therefore, this change might represent far less a disruption of riders’ lives than believed. If riders do flock from Jinn to other companies, this might make them reluctant to re-register when Jinn returns, punishing the company in September.

However, it’s still more than just an inconvenience for riders. If individuals are only registered to one platform (like I am), the process of registering and beginning can take time away from earning, time that isn’t a luxury for many. My entire onboarding process took around two weeks (see here and here for details), meaning riders could be left with without any pay for one-three weeks. This disruption could even be longer, because of being paid every two weeks. Again, this is sure to leave a bad taste in the mouth of former Jinn riders, making rehiring even more difficult.

It awaits to be seen whether this tactic by Jinn will be profitable for the business and what the reaction of riders is (for both solo- and multi-platform deliverers). We might never know the true effect; the gig economy moves at a quick pace and I’m sure there will be another disruptive development soon.

Called ‘The McDelivery Collection’, if you order from McDonald’s, through UberEATS, in one of ten countries, you’ll also be receiving a McDonald’s item for free. There’s a whole range of things on offer, but what is delivered is totally random.

With the gig economy going through substantial change (internally and externally), this wasn’t the most obvious development to expect. Whilst this is one a one-off event, there’s potential for items beyond food (like clothes and electronics) to become more regularly available for quick delivery through companies like UberEATS and Deliveroo. Whilst this is nothing new for others such as Jinn, the two largest players in the food gig economy (UberEATS and Deliveroo) are yet to make waves.

The emphasis on speed in delivery of any goods coupled with the quick pace of any gig economy platform does make for a pretty harmonious match. Whilst companies like Amazon Prime do offer same-day delivery for a whole range of items, you often have to wait at least two hours. In contrast, my average time from assignment to delivery is 20 minutes. Whilst riders are unlikely to have the capacity to deliver a full supermarket shop like a van would, items up to the size of a couple of shoe boxes would fit fine in a delivery backpack. There might be size limitations, but in terms of speed, nothing would be quicker than a UberEATS, Deliveroo or Jinn rider.

UberEATS and Deliveroo have the infrastructure largely ready to go, with the only major addition being connections with suppliers and shops. This does pose a particular challenge though, in terms of matching riders to suppliers. At the moment, each rider is given a specific area to work in, mine is ‘West Central’ i.e. around the Holborn, St Pancras and Barbican area of London. If someone living in Kensington wanted an item delivered that came from a shop near Holborn, would I collect it and then deliver it out of my zone, would it be someone from the Kensington area or would ‘rapid rider delivery’ only be available for shops in immediate proximity? Regardless of who collects and delivers, expanding the food gig economy to encompass other items would go someway to reducing the noticeable over-supply of labour.

With the gig economy associated with ‘disruption’, it seems a radical but possibly lucrative opportunity. Jinn and others have begun, but will UberEATS and Deliveroo follow? Whilst we’ll have to wait and see, today we can celebrate #McDelivery!

The blog has been quiet for a little too long now, whilst I went on holiday and moved flat. It’s back for good now, though, with more consistent posts. For anyone who read some of the previous posts, the blog was previously called ‘A Gig Economy Blog’. Realising this was perhaps the most unimaginative name possible, I’ve changed it to ‘The Delivery Gig’, coupled with a WordPress theme change as well. Exciting times!

In my last post, a major change to my contract was offered, and I can now talk a bit more about the possible change now that it’s gone ahead! I’d recommend going back and reading the post to recap, this is essentially ‘part 2’. As the title suggests, I’ve changed from an hourly rate pay structure to fee per delivery (often called fee per drop). Under this, I’m paid £3.75 per delivery (+ tips), and that’s that. As the last post suggested, this was essentially a trade-off between security and higher pay. £3.75 is less secure because I’m solely dependent on being assigned deliveries, but the pay is greater if I deliver over eight orders in three hours.

Although I’ve only worked three shifts since changing, some preliminary results!

My first shift was far from ideal. I delivered seven orders in a three hour shift, less than I would have earned under the hourly rate (£26.25 vs. £28, not counting tips). £1.75 might not seem a lot, especially when many deliveries take me past Goldman Sachs, law offices and some of the nicer hotels in the city. But, every pound counts when you earn around £10 an hour.

The following day, however, was far more lucrative, doing 10 deliveries. Perhaps it wasn’t fair to judge the first day of fee per delivery too much, and more a result of working on a Saturday, a day of the week noticeable quieter. My average deliveries on a Saturday is 6.7, whereas for Friday is 9.3 and Sunday 10.3. The difference is observable from both a pay and waiting perspective, as a picture I tweeted shows.

One of the supposed benefits of the fee per delivery structure is the greater flexibility given, because riders aren’t bound to shifts like before. Taking this into account, I decided to work Tuesday lunchtime, my first lunchtime shift. For one thing, cycling through central London in the middle of the day in the intense heat, dodging cars, lorries and other cyclists is far less enjoyable than the quieter evening shifts. All of the deliveries I did (only three in 1 hour 26), were to large well-known companies, including Facebook. Delivering around the back-exit, I wasn’t the only rider, with a mix of major companies represented. There seemed to be a constant stream of 1-2 people carrying food through the building to drop it off at a reception.

I was glad to have the flexibility of fee per delivery, I had a spare two hours and delivering was a valuable use of that. However, working for one and a half hours seemed almost futile, it just wasn’t enough time to get into it, nor earn anything substantial. There might be flexibility in when to log in, but not when to log out to make it worthwhile.