The Internet of Things (IoT) and its derivative the Industrial Internet of Things (IIoT) are often heralded as harbingers of Industry 4.0, a new (3rd?, 4th?) industrial revolution based on smart factories and technology driven reconfiguration of value chains for high efficiency.



4 Industrial revolutions

Industrial Revolutions


It seems however that something even more profound is taking place. Just as steam power enabled mechanization which in turn facilitated the transition from crafts to manufacturing, so it seems technology today is driving a wholesale shift to services.

Factory systems replaced craft modes of production as firms learned how to rationalize product designs as well as production work itself. In the 18th and 19th centuries in Britain, Europe and the United States, initially with products such as textiles, guns, agricultural machinery, and sewing machines, managers raised worker productivity and lowered unit costs by standardizing and then integrating production processes in large, centralized facilities. They developed interchangeable parts and closely coordinated the flow of each process; They divided and specialized labor and mechanized or automated tasks. Now, as described in previous articles*, robots, 3D printing, and IIoT applications, including data analytics, are pushing the dual capacity / efficiency envelope significantly further with tremendous implications for productivity. Not only can robots now safely operate alongside humans in many applications or execute tasks better at a few dollars an hour, but soon they will also be able to pass on the knowledge and experience instantaneously (for all practical purposes) to other robots in different settings, so that production processes can be set up and replicated in a fraction of the time needed now. Not only can 3D printing make parts with properties not possible through conventional manufacturing, it also cuts out complex, cumbersome processes from the supply chain and economizes resources. The IIoT means ability to better synchronize supply chains and granular knowledge of situations. The associated data masses mean robust correlations can be uncovered that were not visible before, therefore new insights can be gained, predictions made and actions taken. So what does this mean for products? Over the next few years, products will become better in terms of quality, they will be made in increasing varieties, and, importantly, they will be made with less resources, be these labor hours or materials, and so will become cheaper.

Products will also become smarter through massive sensing capacity, connectivity and algorithms that will enable them to sense and adapt to their environment, connect to humans or other machines and carry out instructions and tasks (much like robots). Connectivity is important here. The first thing connectivity did already in the early days of the internet is to disintermediate the storefront and the middle-man and the world went from book stores to Amazon, from travel agents to Expedia and many shops to Ebay. Connectivity was enhanced further with the mobile phone, which in turn was transformed by the adding of the capability to run algorithms -the smartphone. The smartphone enabled not only connections, but also processing, both locally and remotely. This enabled applications (Apps), some of which were designed as service enablers -the most famous being car-sharing (ZipCar) or ride-hailing (Uber). Whether one drives alone or with a driver, both Apps succeeded because of their economics: They put to use idle (vehicle, driver) capacity and reduce “deadweight” costs. Precisely because the capacity was previously idle the use price can be low (needed only to cover marginal cost to effectively break-even). Usage of the Apps therefore spread and is increasing explosively with many millions of users around the world today. The passenger vehicle has been servitized and the effects are profound. For example GDP is altered as previously private (non-commercial) trips are transformed into commercial services; Income is shifted away from professional taxi drivers in favor of a “gig economy“; Some local public transport systems lose passengers and might need higher subsidies from tax payers. Surprisingly for some, car accidents have declined. In a very recent study researchers in the US had this to say:

The advent of smart-phone based, ride-sharing applications has revolutionized the vehicle for hire market. Advocates point to the ease of use and lower wait times compared to hailing a taxi or pre-arranging limousine service. Others argue that proper government oversight is necessary to protect ride-share passengers from driver error or vehicle part failure and violence from unlicensed strangers. Using a unique panel of over 150 cities and counties from 2010 through 2013, we investigate whether the introduction of the ride-sharing service, Uber, is associated with changes in fatal vehicle crashes and crime. We find that Uber’s entry lowers the rate of DUIs and fatal accidents. For most specifications, we also find declines in arrests for assault and disorderly conduct. Conversely, we observe an increase in vehicle thefts.

And further:

Overall, this suggests that the introduction of Uber increases the safety of citizens. We also witness little to no change in liquor law violations, fraud, or embezzlement. This suggests that our findings are not simply due to overall declines in crime rates.

If these findings hold up, they have significant social as well as economic implications.

However the servitization of vehicles has also profound effects on the vehicle (product) manufacturers, who were originally not involved in the development of the concept.  As vehicles-as-a-service increases, vehicle utilization increases in turn and demand for new vehicle capacity reduces. Eventually this means less cars sold, eventhough the number of cars active on the roads goes up (the number of parked cars goes down). This means less car ownership and a shift of demand from consumers to service providers. Will service providers buy the same cars as consumers? That is doubtful.

It doesn’t stop there. While car sales have been growing due to pent up demand following the Great Recession, manufacturers have seen the highest growth in emerging markets and mainly in China. But car sharing / ride hailing mobility services are exploding in China, possibly an indication that these services are leapfrogging car ownership, just as mobile phones leapfrogged fixed line telephony in most emerging markets.

According to the New York Times:

The scale of ride-hailing as a phenomenon is encapsulated in China. Uber operates in more than 30 Chinese cities with plans to expand to 100 by the end of the year. Didi (a local rival) is in well over 300 cities and towns throughout the country.

Last June, Uber said it had approximately 20,000 regular drivers in the Chinese city of Chengdu alone, on par with the approximately 22,000 drivers in San Francisco and 26,000 in New York at the time.

Uber’s recent financing round, which included a (controversial) US $3.5 billion investment from Saudi Arabia’s sovereign wealth fund brings the company’s valuation to $68 billion, $20 billion more than General Motors, within six years of its founding. Lyft, its closest US competitor, which is four years old, is valued at $5.5 billion. Such valuations mean that market power is also shifting from producers to service providers, as they serve as aggregators  of and channels for consumer demand, which also changes and becomes more adhoc and utilitarian, driven by different needs than in the past.

For car manufacturers there is a very real and imminent risk of product commoditization enhanced by the expected arrival of autonomous (driverless) cars, which in addition shifts a vehicle’s differentiators to software, areas where Google and Apple or other digitally native companies such as Tesla, have clear advantages. So how are car manufacturers responding? Here are some examples:

GM invested $500 million in Lyft (Jan 2016). GM President Dan Ammann, who joined Lyft’s board as part of the deal, expects the automotive industry to “change more in the next five years than it has in the last 50 and we obviously want to make sure we’re at the forefront of that change.” GM also acquired self-driving vehicle technology startup Cruise Automation and continued a push to equip new vehicles with high-speed mobile internet connections. As reported by Reuters in an interview in China last March, Ammann said that as result of the Lyft and Cruise deals, GM is now “pretty well positioned” to pursue a strategy of expanding its presence in ride sharing and ride hailing, and in the long term, develop services that use autonomous vehicles to provide customers with transportation.

In an equivalent step Toyota invested in Uber, and also signed a deal to offer leases to Uber drivers, who’ll be able to cover their payments with what they earn ferrying around the app’s users. “Ride-sharing has huge potential in terms of shaping the future of mobility,” Shigeki Tomoyama, senior managing officer of Toyota, said in a statement about partnering with Uber; “We would like to explore new ways of delivering secure, convenient and attractive mobility services to customers”. Meanwhile Volkswagen invested $300 million in GETT, another ride hailing company. Manfred Müller, VW’s CEO said: “Ride hailing will be at the center of our new ‘mobility on-demand’ business, which we are building up as the second pillar alongside the classic automobile business”. Furthermore Ford, BMW and others are experimenting with their own car-sharing / ride-hailing formats.

However whether car manufacturers can be successful service providers is far from certain. Such a change in the business model requires radical changes in the ways they operate. The investment required and the complexity of car manufacturing has hereto erected barriers around that business. But a business based on infrastructural technology (software) does not provide that kind of protection. Furthermore a service business depends on constant engagement with customers, ability to manage ecosystems and crunching large quantities of data. If car manufacturers do succeed it will be quite unprecedented.

In addition success depends on positioning. If the vehicle gets commoditized, vehicle margins will decline. In addition some capacity may become idle (as demand for new cars declines). In that case a huge underutilized manufacturing operation and the ability to supply vehicles becomes a liability rather than an asset. Service companies unencumbered by huge manufacturing assets might make the running, for example managing a service platform and an ecosystem that integrates cars, buses, trams, trains, bicycles and anything else available and supplied by third parties at low cost.

To compound the difficulty car makers may also face a competitive attack on the self-driving front by companies like Google or Apple (Apple made a $1 billion investment in the Chinese ride hailing platform Didi, perhaps to eventually supply vehicle platforms) as well as Tesla. Google’s self driving cars have now over 1.5 million miles (2.4 million km) of testing. Tesla however may be even further ahead. The company introduced new sensors into its vehicles in 2014. At that point Tesla began using data streaming from cars with those sensors and in-built internet connection and information on their locations to start testing autonomous driving features. Since introducing this hardware 18 months ago, Tesla has accrued 780 million miles of data, which  it can use to look at how people are using the cars and how to  improve. Every 10 hours Tesla gets another million miles worth of data. Furthermore Tesla then introduces the improvements through over-the-air upgrades and again watches as they are activated and used by drivers in a continuous ultra-fast virtuous cycle. In contrast conventional car manufacturers, while working on self-driving technology, have not embraced the idea of internet connectivity in the same way, have to take care of huge legacy fleets and are far behind in the race.

Servitization of vehicles was made possible by technology and as technology evolves, new business models and approaches will become possible. Digitally native, pure play service providers, unencumbered by manufacturing legacies possibly have an advantage, nevertheless companies tightly integrating car manufacturing with services on the basis of multiple service platforms (e.g. Tesla’s EV charging platform is another service provided to customers in addition to its autonomous driving platform and others may follow as vehicle critical mass is established) may offer robust competition.

The impact of technology enabled servitization business models on economies and societies at large is probably at least on par with its impact on supply chains. In fact it allows the servitization of supply chains themselves in ways not possible before.

In further articles we’ll explore servitization in other industries within the sharing economy and other contexts.


*Industry, services and the Sharing Economy

Digitization: A challenge not well understood by non digital natives 

Digitization: How to know whether an industry is being disrupted

3D Printing will disrupt the spare parts market


Titos Anastassacos is Managing Partner at Si2 Partners, a consultancy helping clients leverage services to win in industrial markets

Further articles on this and other topics can be found in the Si2 Partners Resources Page and the Si2 Knowledge Center


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