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Inevitable futures – manufacturing

I recently finished Kevin Kelly’s “The Inevitable” – it’s good, positive, often revealing. But I want to work through some of the ideas and see what scenarios they might open up. First up – manufacturing.

When I left university in the late 1980s, I worked for a small multinational manufacturing conglomerate, and I saw a fair few factories on the inside. They were dirty, noisy places, with humans and machines interacting to transform one thing into another – aggregate, lime and cement into concrete, wood, laminate and hardware into kitchens, etc. The factories were large, and housed multiple specialized machines, storage areas for raw materials, intermediate products and finished goods. Human beings both controlled the process and did the work machines could not – from driving forklift trucks to cleaning the machines, or fixing them when they broke. Controlling the process was a big deal – most of the factories I worked in had roughly the same number of “administrative” staff as shop floor workers. Even though the factories made similar or even identical products every day, there were regular crises – machines breaking down, suppliers delivering late, customers changing their orders at the last minute.

Recently, I was lucky enough to visit the Rolls Royce Motor Car factory in the Sussex countryside. The contrast was amazing – it’s quiet, clean, controlled. Even though every car they produce is different, the process was almost serene. Far less of the factory was dedicated to “storing stuff”, and there were far fewer dedicated machines.

Of course, that’s because Rolls Royce mostly assemble and finish cars in their factory – most of the components that go into the car are made somewhere else. At Goodwood, they are put together, painted, polished, and generally glammed up with leather, wood, and all the other items that make a luxury car.

Now, I also got to have a look inside the engine plant of a motorcycle manufacturer a few years ago. I was expecting much more industrial grit – after all, engines are big, complicated things, made out of metal. Surely there would be lots of noise, and flashing lights and…well, no. Turns out that building an engine is also mostly assembling components delivered by suppliers.

I’m pretty sure it’s turtles all the way down.

The modern factory is possible only because we can process and exchange data across the globe, instantaneously. In the late 80s, we would fax or phone through orders to our suppliers; I spent a few months in the “planning” department, working out different ways to sequence customer orders to optimize production efficiency by shuffling index cards on a big felt board. We would then feed those plans into our manufacturing resource planning software, which in turn would spit out purchase orders (which we’d fax or phone through to our suppliers). We had lots of people throughout the factory collecting data (usually with a clipboard), and then feeding that into the computer.

Today, of course, most companies communicate orders directly, and factories gather their own data; the computer is much better at optimizing production capacity than a human could ever be, and as a result, the role of the human is increasingly about doing the things machines can’t do (yet).

I’m also pretty sure that this is just the beginning.

Once we have robots that can do tasks only humans can do today, self-driving lorries, 3D printing and nano manufacturing it’s easy to imagine lots of different scenarios. I’d like to consider one.

The local manufactury.

Right now, the cost of labour determines where we make most things – and as that’s cheap in China, Vietnam, Mexico, etc. our global economy takes raw materials, sends them (usually over great distances) to those cheap labour places where they get transformed into products we want to buy, and then ship them halfway around the world again for consumption in the West.

What happens once robots can replace that cheap labour?

Of course the other reason to have a “car factory” or a “shoe factory” or a “phone factory” is to have a store of knowledge and skills. Some of those skills are directly related to the product – welding, sewing, assembling small electrical components. Many of those skills are organisational – “how do we do things around here?”. Some relate to design – the development of new products.

It’s not ridiculous to imagine that much of this knowledge – especially the skills and organisational skills – can migrate into computers.

If these trends continue, maybe the cost of shipping things around the world becomes critical. Maybe every neighbourhood gets a local manufactury – a building with pluripotent robots, 3D printers and nano-bots, managed by a scheduling AI, integrated into a supply network. Customers choose a product – from an “off-the-shelf” design, or by customizing a design, or by commissioning a design from a specialist, and send the order to the manufactury. The manufactury looks at the bill of materials, and places orders with its supply network; self-driving vehicles deliver the materials, and the manufactury schedules the robots to build the finished product, which – of course – is then delivered to the customer using a self-driving delivery van. Or a drone.

To create a shirt, the manufactury would order cotton, buttons, etc. – either in bulk (if the purchasing algorithm decides that keeping a stock of cotton makes sense) or “just enough”. The nanobots would create dies to colour the cotton, and a robot would follow the pattern to cut the cotton into the components for a shirt, and stitch it together.

You could easily imagine such a manufactury making clothes, furniture, electrical components, household goods etc.

The economics would be interesting – but I imagine that the price of an object would be driven partly by the cost of the design and raw materials, and partly by the time the customer is prepared to wait. The economies of scale don’t go away – clearly making dozens, hundreds or thousands of the same product would be much cheaper than one-offs. You could imagine clever scheduling algorithms, aggregating demand from multiple neighbourhoods, so that when the threshold is reached for a particular product, one of the manufacturies configures itself to satisfy that demand. Of course, this could apply to finished goods and to intermediate products – manufacturies converting raw cotton to thread, thread to cloth etc. You can also imagine how specialized equipment – weaving looms, injection moulding presses etc. – would continue to offer significant cost advantages.

When? How?

This is just speculation. There are many leaps of faith – I’m pretty sure I made up “pluripotent robot” as a phrase, and while 3D printing and nano-materials are not purely speculation, they’re also not yet ubiquitous. Lights-out factories are still not mainstream, let alone factories that can re-configure themselves every day.

But ecommerce and digitisation means we’re all spending less time on the high street, and becoming more accustomed to ordering stuff on the internet and have it turn up. Amazon especially is innovating logistics and supply chains – I can order coffee beans and printer ink on my phone, and they will deliver it within 2 hours.

So, if this happens, I’d bet it would be a company like Amazon who leads the way – they already have highly automated distribution centers, so the jump to manufacture isn’t quite such a big one. They have the computing power, and the customer insight.

Europe.

I feel European. If I shared any of cousin Dirk‘s talents, I’d qualify to play football for 3 countries. I grew up speaking English at home, Dutch at school, and Frisian with my friends in the playground (though I never got the hang of Sneekers). Growing up, school and music trips went to France, Belgium and Germany; I can read a news paper in French, German, Italian and Spanish. I have friends and colleagues from around half the 27 remaining Eurozone countries.

I love classical music from the continent – Bach, Mozart, Vivaldi, de Falla, Lully, Beethoven, Sweelinck. I love continental food. I love continental cities. I love continental European comics – Franquin, Hergé, Toonder.

I’ve chosen to live in the UK for the last 30 years – I love the UK too. London is an amazing city. Many of my favourite authors – Martin Amis, William Boyd, David Mitchel – are British. The BBC is amazing. Even the food is getting better.

But now, after the vote to leave the EU, it feels like I have to chose. It’s not clear what the UK’s relationship with Europe will be – but I fear the worst.

Project management job number one: land the f****ing plane

I’ve been making software for a few decades now, and worked on all sorts of projects – small, large, complex, simple, fun, and not-so-fun. One of the biggest problems with software is the amount of information a developer needs to keep in his head (I believe Dijkstra once wrote that software developers were unique in having to be able to understand, simultaneously, 7 levels of abstraction). The same is true for those who manage developers.

On a large project I was involved with recently, I noticed that the project management team was working really hard, but not making much progress. I looked at all the streams of activity, and I noticed that the project had lots of outstanding decisions. When will we do the training? Who will manage QA? What day will we have the management call? Which version of the API should we use?

It reminded me of an iPhone game I’d played for a bit – I think it was called “Air traffic control” – in which you have an airfield, and planes arrive on the screen; the job is to land the airplanes. As the game goes on, it throws more airplanes at you, and eventually you’re overwhelmed by the number of aircraft, they crash, and the game ends.

It’s mildly diverting, and a good way to while away the tube journey.

It occurred to me that our project management team wasn’t landing enough planes – and the more planes are circling the runway, the more likely it is they’ll crash. Most people I know can keep a handful of things in their brain at one time (there’s some scientific research to confirm this), and the whole “Getting things done” system is designed around this.

The issue with project management, of course, is dependencies. One pending decision can block 4 other decisions, and before you know it, you end up looking like that guy from Airplane! , trying to keep the whole thing spinning, and dedicating all your energy to stopping the planes from crashing into each other, rather than to landing the planes.

And this, of course, affects everyone. The developers find that they can’t work on something because we’re waiting for a decision. The number of items that aren’t “done” grows every day – and when a decision is made, updating all the dependent items grows. The project sponsor sees an ever-longer list of open topics, none of which make much progress, and eventually everyone forgets what they were about. Risks that could have been avoided with a small amount of effort earlier suddenly erupt into craziness.

So, project management job number one: land the plane.

 

 

My kids don’t watch TV. How will you sell them anything?

Disclaimer – views entirely my own, nothing to do with my employer.

Familiarity ≠best

Advertising seeks to persuade human beings to make one choice over another. A big part of this has been taking advantage of our tendency to substitute hard questions (“which can of beans would be the rationally best choice?”) for easier questions – very often substituting “best” for “most familiar”. Daniel Kahneman’s book Thinking, Fast and Slow includes a chapter on this.

Much of the effectiveness of advertising depends on this principle – instead of evaluating the price, quality, nutritional benefits of a can of beans, the advertisers hope we’ll remember “Beans means Heinz”.

That strategy works – especially for products where we don’t expect a big upside from expending the effort to make a “better” choice (will that other can of beans really be so much better?), or where the downside of a wrong choice is (perceived as) high – I’ve never heard of car brand x, it’s safer to stay with a brand I’ve heard of.

But there are some powerful forces eroding the magic bullet of familiarity.

Howling into the void

Becoming “familiar” was never easy – you’d need a memorable message, you’d need a big budget to put it in front of your target audience, and you’d have to hammer home the message over many years. Today, I don’t think it’s even possible any more – no matter how much advertising spend you have, becoming “familiar” just through advertising would be unthinkable (if you’re aiming at a mainstream audience).

People are actively avoiding advertising if they can; if they can’t they ignore it. The decline of print audiences, and the fragmentation of linear TV means the “old” channels are becoming much less effective (even ignoring the fact that linear TV as a medium doesn’t look like it has a great future – nobody I know watches “TV” – it’s all streaming, on-demand, box-set and event-based viewing).

The big business success stories of the last decade – Facebook, Google, Amazon, Uber, AirBnB etc. – don’t advertise much. They use word-of-mouth and built-in mechanics like referral schemes – but most of all, they have a great, useful product.

From information scarcity to abundance

The “familiarity” model is based on information scarcity. If I have to chose a product in a super market, and I have no other information to hand,  instead of reading the label and making a comparison with similar products, it’s tempting to go for “which product have I heard of”.

And it’s not all that long ago that consumers didn’t have access to much other information. Before the Internet, you might know a few friends’ and family members’ opinion on something; you might read a magazine or a book; you might, for an important purchase, order a report from a consumers’ organisation.

Today, you can find out instantly what all your friends and family think about a product by asking on a social channel. You can find out what strangers think on review sites. You can find out every aspect of the product or service by running a quick search. And as we are all consuming more “information” every day, the chances of having no other information available are declining.

So, to become “familiar” is harder, more expensive, and less effective.

The end of the “Friday afternoon car”

In the 1980s, a friend bought a brand new car; it was an MG Metro. She owned the car for about 2 months before it broke down, so she took it back to the garage for a repair. 3 weeks later, it broke down again; after 6 months, the car had been back for 4 repairs. The mechanic at the garage introduced me to the phrase “Friday afternoon car” – the idea was that the factory workers wanted to get home for the weekend, so cars built on a Friday afternoon would be rushed, and suffer from problems.

It’s now pretty much impossible to buy a Friday afternoon car – even the cheapest, least prestigious car manufacturer is delivering a high-quality product that will do exactly what you expect, and will easily outlast its warranty period.

The same is true of most consumer goods (financial services are a notorious exception) – supermarket own-brand beans may taste different to the brand names, but they aren’t “worse”. Clothes from a discount store will last just as long as those from a high-street chain. You can watch NetFlix on a discount laptop just as well as on an Apple.

The value of “brand” and “familiarity” in customer decision making is declining – now that you cannot buy a “bad” product any more, the safety of going with the familiar brand is declining in importance.

 

The tragedy of the mega-pixel

A few years ago, I met an executive from a large camera company. Before digital photography came along, this company’s marketing (and manufacturing) emphasis had been on the quality of their lenses. This is  subjective field – you can use focal length and aperture as a proximate measure, but no serious photographer would equate a “no-name” lense with the same metrix with a lense from a well-known manufacturer.

And you know what? It was broadly right – a good lens meant a better photo.

Then the digital camera came along – and now people buy cameras based on one simple metric: the number of megapixels. This is not really correlated to image quality for most people (unless you want to print a photo to cover a bus shelter). But it allows consumers to compare products using a nice, simple metric – camera x has 12 megapixels for $200, camera y has 15 megapixels for $200 – camera y is the best deal”.

The camera executive called this phenomenon “the tragedy of the mega-pixel” – he said his company culture had changed. The focus on lens quality was still there – but it wasn’t commercially meaningful in the short term. When it came to dollars, it was better to invest in mega pixels than glass.

Restaurant review: Provender, Wanstead

Last week, we went for a sunday lunch at Provender, on Wanstead High Street, in North East London.

It’s a small French restaurant, and pretty much every table was taken, including the small area outside (we’d booked in advance). The interior is bright, and tasteful, without being pretentious.

We had the big starter platter – Hors d’oeuvre “Royale” – which was frankly amazing. Charcuterie, a very nice rilette, and a celeriac remoulade that I will have to experiment with. The other side of the platter was fish – smoked salmon, salmon mousse, and small sections of what looked like sword fish (I don’t eat fish). The charcuterie was spectacular – two sliced dried sausage varieties that were subtle, but each had a distinctive flavour I can still taste 2 days later…

My main was the steak tartare. I love tartare – it’s hard to find in the UK. The Provender tartare was minced by hand, and it makes a difference – the texture was much more interesting. The flavour was robust – the seasoning was just the right side of aggressive, and the meat was clearly from a good butcher.

My lunch partner had the coquilles St Jacques, served with saffron risotto. She smiled beatifically, and reported a state of bliss.

For desert, I had the blackcurrant sorbet – rich with a cassis liqueur, and very fruity. My lunch partner chose the chocolate tart, which may well be the most chocolatey thing I have ever tasted.

We had a nice bottle of wine; the total bill came to just over £100. Excellent value for money.
Thoroughly recommended.

What does “good” look like?

In traditional “waterfall” software development, “good” software meets the written requirements. No matter how bad the requirements – “good” software meets the requirements.

In agile software development, “good” software meets the quality goals set by the team, and delivers the features defined by the product owner. No matter how deluded the product owner.

Both models seem unsatisfactory.

 

Is web design work drying up?

I was listening to the Tim Ferris podcast where he interview Seth Godin. Seth publishes a new post every day. I’m going to try to write more.

I stumbled across a post on Hacker News called “The Elephant in the Room: Web design work is drying up (sazzy.co.uk)“. The conversation got pretty heated.

The original article is about life as a web design freelancer – which is a fair way from my life as an employee of a large digital agency, working in technology. But the basic trends are probably the same.

I think it boils down to three trends.

Anyone who needs a website probably already has one. And many businesses have decided (for better or worse) to stick with a social media presence, and not to put too much effort into their website.

Secondly – companies that do need a website almost certainly need more than just a nice static web presence. They may need a complex ecommerce site, or a dynamic web application, or – well, whatever. These projects typically need specialist skills, rather than a generalist.

Thirdly – for the simpler web sites, the “off the shelf” tools are getting better. A WordPress site, with a custom theme and a few nice plug-ins delivers the same business value as a custom-developed website did 5 years ago.

 

Food Gangnam Style – bibimbad. Yum.

Korean bibimbad

Bibimbad

I’ve decided to try and be less predictable in my eating – it’s too easy to fall back on habit, and experiments over the winter have reminded me how much I enjoy new tastes.

So, for lunch today, I got a bibimbad from the Food Gangnam Style stall on Leather Lane. For £5, you get a decent size bowl with rice, a variety of vegetables and salad, a fried egg, a choice of meat (I had the spicy chicken) and hot chili sauce.

First things first – it’s good. The mix of flavours is interesting – sourness from some of the pickled veg, fire from the chili sauce,  a fair bit of sweetness from the chicken. With oriental dishes, it’s often as much about the textures as about the flavours – and again, the bibimbad has a lot to offer. Crunch from the salad, a pleasantly fluffy rice, goo from the egg yolk – it’s all there.

The chili sauce is certainly noticable – I like spicy food, but it may be too much for some.

The service was quick (though it was a quiet time, so there was little queuing), the ingredients were fresh, and the portion size was perfect for me.

I’d recommend these guys.

Wintery pasta

Now that it’s getting distinctly autumnal, I’ve been trying to recreate a pasta sauce I had in an Italian restaurant in Berlin a few years ago. No idea if it’s authentic Italian – it has a central European flavour – but it’s easy to make, and very tasty.

Ingredients

500 g diced beef – stewing beef or similar

1 onion, finely chopped

2 medium carrots, finely chopped

1 leek, finely chopped

3 celery sticks, finely chopped

3 – 5 cloves of garlic, finely chopped

1 tsp fennel seeds

1 tsp smoked paprika

1 tsp fresh basil, finely chopped

1 tsp fresh rosemary, finely chopped

2 tins of chopped tomatoes

a knob of butter

a tsp of olive oil

salt & pepper

Pasta – I prefer penne or spirali.

Method

Bring the beef to room temperature. Season with salt & pepper.

Heat the oil in a heavy casserole pan on a high-ish heat; once it’s hot, add the butter, and wait for the butter to melt. Then fry the diced beef until it has a bit of colour. Remove from pan and set aside.

Reduce the heat a little. Add the onion to the fat, and fry for a minute, then add garlic, leek, celery and carrots. Reduce the heat a little, and cook over a low-medium heat until they take on a little colour.

Add meat back to the pan, add paprika, fennel seeds and rosemary; stir together so the meat and veg are coated. Cook over medium heat for around 10 minutes.

Add the chopped tomatoes. Reduce the heat to low-ish, and simmer for at least 20 minutes. Stir occasionally. The lower the heat, the longer you should cook; the longer you cook, the better the flavour.

Boil some salted water, cook the pasta, and mix with the pasta sauce. Serve with grated or shaved parmesan.