My Surprising Visit to a Washing Machine Factory

Listen to an AI recording of this post.

I just returned from an exciting trip to Qingdao, China. In addition to eating brains and snails, I saw something that blew my mind when I visited a Haier washing machine factory. To the common observer, the process to create the appliances simply looks like parts coming together. But upon taking a closer look, I realized it was a view into the future of all industries.

Watch a video recording of this newsletter. ?

Beyond Just-in-Time?

At first, I didn’t realize what I was looking at. There were parts descending from the ceiling on elevator shafts, and robots lifting, shaping, and welding the parts as they dropped from the shafts down the line.

Representatives with Haier – the largest appliance manufacturer in the world, owner of GE Appliances and others – had been telling me about the model they have been using. To be honest, before my visit, it sounded like just-in-time (JIT) manufacturing advanced by robots, automation, cameras, sound sensors, and other technologies from the Internet of Things (IoT) era. Cutting-edge, but still JIT – a 70-year-old concept introduced by Toyota engineer Taiichi Ohno in the 1950s and popularized in the 1980s. The idea is to get the parts where they are needed, only when they are needed, and not before.

But then, I looked down at a giant dashboard tracking the process and saw something unexpected. Line by line, there were orders with order numbers, configurations, customer names, and customer locations. These orders were not for GE Appliances or Best Buy; they were for actual individual people – like James Smith in Irving, Texas. The factory was not producing washers and dryers in batches for businesses. They were producing them individually for specific humans.

Their AI-automated system was figuring out the configuration of components, like LEGO instructions, matching each part in the right order, and assembling them – personalization at the unit of one.

And these were not projected or anticipated orders. This was not Amazon using its patented "anticipatory package shipping" to get products closer to where they are likely to be needed. These orders were actually in hand – the easiest to predict because no prediction is needed.

These two concepts – personalizing for individual customers and making products after receiving the order – may not seem radical on the surface. But for 200 years, they have been nearly impossible to achieve at scale. They are two out of four strategic shifts that are transforming industries and value propositions, which Rob Wolcott and I discuss in our latest book, Proximity .

These shifts are part of a few trends to pay attention to:

• The shift from physical customers to digital customers
• The ability to personalize at scale
• The move from search to creation
• The emergence of suppliers and employees as the new customers

Let’s briefly tackle each of these.

Shifting from Physical to Digital Customers?

First, your customers are becoming digital customers, and if they’re not, you should do something about it. Amazon’s, Google’s, and Netflix's dominance in their areas is due significantly to their ability to turn physical customers into digital customers. Mohan Subramaniam, IMD professor, shared this on our Outthinkers Podcast .

If you go to a Barnes & Noble, shop for an hour, and buy a book, they get one piece of information about you. If you go to Amazon, shop for an hour for a book, and buy nothing, they still gather tons of information about you.

Buy a washing machine from a traditional producer, and they know what you bought and when. There’s a 10% chance that you will complete the warranty registration card, and then they might also know your name and address.

But when you buy a Haier washing machine, the machine interacts with you through an app which enables you to control personalized programs and connects with other appliances in your home. Let’s say you’re at the grocery store. You check the app to see if you still have milk in your fridge. Your refrigerator's infrared cameras show that you only have a little bit left, so you throw a gallon in your cart. Then you get a notice that the load of laundry you have in your washer is done. Since you won’t be home for a while, the app suggests turning on the air circulation function to avoid mold.

Through the app, Haier connects its customers to designers to personalize the product experience post-purchase; identify what improvements they can make to the product; and get real-time data to come up with entirely new products.

Here are some of the improvements Haier has made so far:

• They’ve made it easy to switch the door of their front-loading washing machines to open on the right- or left-hand side. Now, it’s done by just the turn of a screwdriver, which can drastically save on after-sales costs for the user.
• They found that Americans tend to do laundry on the weekends because it could take up to five or six hours. Last year, they released a washer-dryer combo that reduces drying time from two hours to 40 minutes. Now, because the time is compressed, users can do their wash on weekdays.

The point is that Haier has an ongoing, infinite, continuous interaction with its customers, which enables the second aspect of this model – personalization at scale.

Personalization at Scale?

Thanks to advances in automation, Haier can produce more of these products economically in smaller quantities. Changing one line of a washing machine plan used to take two to three hours; now it can be done in 20 minutes. The factory can produce 400 different models of washing machines. Robotics, modules, and AI help the factory assemble the “LEGO pieces” more rapidly in the desired configuration.

They run a digital twin platform that provides a simulation of the entire factory, allowing them to rapidly think through reconfigurations. For example, if they switch from producing one size washer to another, they know they need to turn on a specific machine, shift a robot’s program, and feed in this metal instead of that one.

A typical car manufacturer can produce 35 cars per hour on a single line. Tesla can famously produce one car per minute . However, another company, Chery, using Haier’s technology, can produce 60 cars per hour – one per minute. That’s slightly slower than Tesla, but Tesla can only produce one type of car on that line. Haier’s technology enables Chery?to produce six different types of cars. And I’m not just talking about different colors; they produce electric vehicles, hybrids, gas-powered vehicles, and a variety of types like SUVs and sedans.

From Search to Creation

These two abilities – shifting from physical to digital customers and personalization at scale – allow us to move from search to creation. Google dominated by delivering better search – when you want some information, Google helps you find it faster. Amazon dominated by doing this in the physical world – you want a product, and they help you find it and get it faster. But both of these models are still about "search." You’re searching for what is already out there, already created – the blog already written, the chair already produced.

What we are talking about here is fundamentally different because the things you are searching for do not yet exist. Your input triggers their creation. This is more like Etsy than Amazon, more like esports than movies. You don’t just passively get what’s already made; you get to influence the plot and storyline.

From the provider's point of view, producing at the moment of demand has several advantages. There is much less risk because you don’t make your product until someone orders it (London Business School Professor John Mullins in his book The Customer-Funded Business explains that this is how most great entrepreneurs start).

It also reduces waste. Thirty percent of apparel produced globally is never sold – it’s thrown away. If you only produce what people order, that waste would be zero.

The third advantage is that people will pay more. If a product is personalized rather than off-the-shelf, it is more precisely what they want, and they will naturally pay more for it.

The impact of these shifts multiplies with the final strategic shift: from customer to supplier.

The Shift from Customer to Supplier

Many of us have been trained to listen to customers and that the customer is always right. In some ways, that’s still true, but we are seeing a historic rebalancing from a focus on customers to a focus that also includes employees and suppliers. Felix Oberholzer-Gee , Harvard Business School professor, laid out in our podcast that companies need to think about increasing both their customers' willingness to pay and their suppliers' and employees' willingness to sell. Stephan Meier from Columbia Business School commented that "the employee is the new customer."

I propose also that the supplier is the new customer. We mostly think about digitization at the front end. What we need to do – and what Haier is doing – is also apply digital transformation on the back end. Suppliers are plugged into this "interconnected intelligent engine," as Haier calls it. When customer orders come in, the supplier can jump into gear and start producing the parts needed ... on demand. Logistic partners can start positioning to move the parts to the factory. It’s as if Haier is not selling washing machines but rather selling orders for washing machine parts to their network of thousands of suppliers.

Information flows from customers to Haier in three types of feedback:

1. Information on a new customer order coming in
2. Information to improve existing products. For example, if customers are having issues with the noise of a dryer, suppliers can spontaneously start working on a quieter mechanism.
3. Information to invent entirely new products. For example, Haier got feedback from customers that they didn’t want to bend down to get items from their refrigerator, so they invented a taller one that doesn’t require users to stoop down as much.

Economic factors are driving us to rethink our model for industries and value creation. Think Personalization Premiums and Cost of Customization:

• Personalization Premiums: People are increasingly willing to pay for customized options. Hard customers, especially next-generation customers, put more value on getting personalized experiences.
• Cost of Customization: Thanks to all the technological advances I’ve already discussed, the Cost of Customization is coming down.

Final Thoughts

Where are we headed? The linear industry value chain model that Michael Porter popularized in the 1980s has been the dominant paradigm for businesspeople and economists. Now, we are reshaping it into something that looks more like an infinite loop.

When you have connected customers searching, purchasing, receiving, and interacting with their products, feeding back into a supplier network that’s receiving orders, feedback, and improvements, building parts, and shipping, it becomes a back-and-forth interaction. It’s intelligent and reacts to actual demand, not projected demand. It delivers customization and sees suppliers and employees as just as important as customers.

I'm excited to continue exploring these models. The future of industries is unfolding before our eyes, and it's more personalized, efficient, and interconnected than ever before.

Join the Outthinker Accelerators Network

For innovators poised to lead the future, consider becoming a founding member of our soon-to-be-launched global community of accelerators. Click here for more information?and to apply to join .

?