Leading the way is a new group of disruptive manufacturers; companies such as Tesla, Faraday Future and Local Motors, are attempting to redefine many of the key principles of the traditional supply chain. What can we learn from these businesses in terms of the future for supply chain management?
Tesla is a name that is synonymous with disruptive manufacturing. In just seven years, Elon Musk’s start-up has pioneered the design and manufacture of premium electric-powered vehicles, seeing its revenue grow from under $14.8m in 2008 to over $4bn in 2015.
Let’s take a look at Tesla’s business model for a second. What sets them apart from your traditional manufacturer, and the secret behind their rapid success, is a desire to take complete ownership of the supply chain from initial development to the end consumer experience. While other companies were busy outsourcing as many elements of their business as possible in order to reduce labour costs, Tesla knew that in order to control the value chain, it needed to be vertically integrated.
As a result, Tesla is a supply chain manager’s dream, with the entire process from design to assembly taking place in the U.S., with nothing outsourced. All components, including the battery plant, are produced in California. Even sales and servicing are retained as part of the Tesla network. The end result is 100 percent control and visibility over their supply chain from start to finish.
Tesla has used technology to gain a number of competitive advantages. Innovative digital technologies enable Tesla to provide product and firmware updates directly to the vehicles, rather than the traditional physical approach to upgrade during a routine service. The fact that they know that the product is plugged in every night means that they can reliably deliver new updates to existing customers, like GPS enhancement and performance tweaks, to help keep customer satisfaction high. Late last October, for example, Tesla Model S P85D and P90D customers who went to bed with a normal electric car found themselves in possession of a semi-autonomous one when they awoke. Cars constrained by the normal combustion engine and a 12V battery can only update software when the engine is running – and it is never a good idea to update software while you are driving the car!
Another car manufacturer that is hoping to become as well-known as Tesla is Faraday Future, who launched their futuristic concept car back at the CES technology show in January 2016.
Whilst in the same industry and a direct competitor to Tesla, California-based Faraday Future is taking a different approach to the future of automotive manufacturing. Supply chain optimisations are integrated into Faraday Future’s business model from the product up. Its research chief, Nick Sampson, formerly a rival engineer at Tesla, suggested the firm was able to move faster than others thanks to an adoption of “variable production architecture”.
The product’s modular design provides key enhancements to Faraday Future’s supply chain. The same basic structure will underlie all its vehicles, with the ability to adapt to include battery packs of various sizes, different types of wheelbases and anywhere from one to four motors. Fundamentally, this guarantees easier procurement management due to the significant reduction in the range of parts required for sourcing.
Another “new kid on the block” is Local Motors. It came to prominence in 2015 with the release of the Strati, the world’s first 3D printed car, with 75 percent of the vehicle being 3D printed. As their website states: “From the retail lobby, to the factory floor, to the open road, we're making everything simpler and smarter.”
Local Motors’ use of Additive Layer Manufacturing at an industrial scale (something often referred to as BAAM – Big Area Additive Manufacturing) means that it can produce cars much more sustainably than traditional manufacturers at small-footprint microfactories. This material is fully recyclable, which can be chopped and reprocessed to be used in printing another car. After the car is printed, the mechanical and electrical parts, such as battery, motors and suspension are manually assembled.
It also means that it is not constrained to traditional design constraints. On June 20, 2016, Local Motors unveiled Olli, a 3D-printed electric minibus capable of carrying 12 people and which is powered by IBM’s Watson’s Internet of Things (IoT) for Automotive. According to a press statement by Local Motors and IBM, by the end of 2016 Olli will be used on public roads in Washington DC, Miami-Dade County and Las Vegas.
The press statement says Olli will use cloud-based cognitive computing capability of IBM Watson IoT to analyse and learn from high volumes of transportation data, and is fitted with more than 30 sensors, which will collect this data. IBM stated that the inclusion of Watson enables Olli to engage in conversations with the passengers while travelling – they could ask why Olli is making specific driving decisions, or ask for recommendations on local destinations such as popular restaurants or historical sites.
The challenge for existing manufacturers
A central theme that links both disruptive manufacturer examples is prioritising control over their supply chains. With full visibility of your supply chain, you can identify bottlenecks well in advance, save money, and cut production times. This degree of agility allows them to fail fast and often, learning from these mistakes in order to continually innovate.
This can prove difficult for large, existing automotive manufacturers that are clearly constrained by their size, hierarchical structure and culture. The ghost of Kodak looms large over them. Their current asset base, previously a massive benefit through economies of scale, tends to restrict their ability to redesign their products from the ground up in order to do things such as develop a more modular design. Furthermore, converting a global supply chain to a more vertically integrated and localised approach would be expensive.
Another challenge for existing manufacturers is the ability to continue to attract the best talent to their companies, especially with the rise in autonomous vehicles.
So what lessons can existing companies take from these disruptive upstarts, and how can they be applied to their own supply chain processes?
In terms of product development, the automotive industry, in particular, has previously focused its efforts on mechanical, rather than digital, enhancements. However, recent research by McKinsey shows this is shifting, with the automobile slowly becoming a computer with wheels, rather than a car with a computer in it:
“In the United States, a squeeze is developing as content requirements of cars in emissions and safety continue to rise while consumers pay no more for these features than they did a decade ago”.
Therefore, manufacturers have to look to digital design methods and data simulations to stay ahead of their competitors. Integrating data sensors for component monitoring and supply and demand monitoring using online systems is paramount; Tesla, for example, collects 10 times more data per car than any other car manufacturer. This data is collected and consumed back at their headquarters and then uploaded to existing vehicles. This means that each car is not simply learning from the actions of its own driver – it is learning from every Tesla driver. Within days of the autonomous software upgrade, Tesla owners started reporting that their vehicles were becoming noticeably smarter. This is exponential machine-to-machine learning.
It is clear that well-performing business models in the modern manufacturing era will focus on a supply chain that is based on data, gathering ever greater insight that enables it to be continuously optimised and closer to the customer.
Source: Every Angle
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