How Trucks Are Becoming A Solution, Not A Product
Daimler was the world's first automobile manufacturer to design, develop and sell a "commercial truck" in 1896 and, ever since, trucks from all vehicle manufacturers, in all parts of the world, were built and sold as products.
The simple governing theory in the global commercial industry was to build vehicles that could support specific vocations and duty cycles in the most cost-effective, safe and predictable manner. Then the manufacturer would sell these vehicles in as many markets as possible. Hence, the OEM (original equipment, or vehicle manufacturers) business models were governed by a simple question – "How do I build the best products and sell these to the widest cross-section of demand base?"
The customers, in turn, were governed by a different theory. It manifested in the form of a simple question they would ask themselves after they would purchase their trucks – "How do I use this truck to generate revenue for my business?"
The doors of perception separated OEMs and customers from each other, and this resulted in OEMs continuing to center around Truck-as-a-Product business model. The doors of perception remained shut.
And now it is: truck-as-a-service
For the 100 years that followed the rollout of the first truck in 1896, the doors of perception prevented the OEMs from creating trucks that would truly serve the needs of the businesses that would be using them. Then from around mid-1990s, with the rise of connected vehicle technologies, such as telematics, it started to become possible to get data from the vehicles. Data related to a vehicle's location, performance of its key component systems and modules, driver behavior, and many other parameters were captured by telematics systems. This array of data, in turn, was relayed to a wide range of stakeholders, such as fleet managers, maintenance managers, telematics solution providers, and OEMs, among others.
As a result, OEMs started leveraging data to develop better vehicles. Meanwhile, telematics solution providers and OEMs (as well as Tier-1 parts suppliers) began offering diagnostics and prognostics solutions, and disparate stakeholders started collaborating to improve vehicle, driver and cargo safety, reduce downtime and maximize vehicle uptime.
If you have been paying attention to advertisements that commercial vehicle OEMs have been running for past 10 years, you must have noticed three letters that stand out in most ads – TCO (Total Cost of Ownership/Operation).
Almost every truck OEM now wants to prove to its end-users that its vehicles offer the lowest cost of ownership/operation. Some do that by leveraging powertrain efficiency data, others highlight the superior safety features of their vehicles, and the remainder focus on the trucks' reliability and uptime.
All of these differentiators can be used to prove TCO reduction that became possible through the analysis of data streams emerging from the truck. This ability to analyze data and apply insights was bundled with the product (truck) to make it a service. And just like that, the doors of perception started to open slowly but surely, and in came powerful data that started causing business model transformation across all corners of the global commercial vehicle industry.
Final frontier: truck-as-a-solution
The flow and analysis of data, derived from trucks and their related services, started gaining rapid traction. We now have reached a stage where approximately 60 to 70 percent of all commercial vehicles sold each year – and approximately 40 percent of all heavy-trucks in operation on our highways – are now "connected vehicles."
This has coincided with the advancements and infrastructure in big data and cloud-based analytics, as well as the advent of high-speed cellular networks. It started stoking a large-scale digital transformation of the commercial vehicle industry, attracting the biggest names in tech. An industry that was product-centric for the past several decades now features participants such as Alphabet Inc (NASDAQ: GOOG), Tesla Inc (NASDAQ: TSLA), Amazon.com, Inc. (NASDAQ: AMZN) and Uber Technologies Inc (NYSE: UBER) as key influencers.
More and more industry participants leverage big-data analytics platforms, such as CONNVEX, and dashboards such as FreightWaves' SONAR. These tools help them make business decisions that are based on actionable insights and build solutions that not only help truck-buying and truck-owning businesses save money, but also make money.
These powerful and customized data analytics are enabling a fleet manager to gain both panoramic and granular insights over all areas of the fleet's business. Vehicle data, married with freight flow and shipper-carrier transaction data, is enabling solution providers to predict freight haulage demand in advance.
Hours of Service data, along with other data sources, is meshed to help create industry's first freight futures index. Data from vehicle systems and duty cycle patterns is used by vehicle system suppliers and OEMs to remotely program key vehicle systems and optimize them for application to any given duty cycle/vocation. These are just a few examples of how the digital transformation of trucking is enabling the creation of solutions that address the businesses challenges of fleet-owners and owner-operators.
The OEMs are the net benefactors of this change, because it now makes it possible for them to position their trucks not as products or services, but as solutions. This is the beauty of data flow and the insights it brings – it opens the doors of perception.
The OEMs no longer see vehicle buyers and users as customers, but as clients. This is the most fundamental change that the commercial vehicle industry has experienced. The OEMs are finally realizing that it was never about a truck anyway; it was always about the end-users and solving their problems. The Truck-as-a-Solution business model is making it happen.
In coming weeks, I will deep-dive into various commercial vehicle systems from bumper to bumper and into various commercial vehicle markets to provide descriptive, predictive and prescriptive analysis of key trends that are shaping this industry.
Image Sourced From Pixabay