Data-Driven Intelligence for the Automotive SectorBy Alejandro Enríquez | Thu, 02/11/2021 - 06:00
Q: What is the role of data in the automotive supply chain?
A: Data is a 21st-century asset but companies have not yet focused on it. They are embracing automation but they are not transforming the generated information into a financial asset. The automotive sector faces the challenge of merging tech with autos to enable a comprehensive digital platform. Not so long ago, the largest companies in the world were from the automotive sector. Today, we have tech giants.
Q: What are the implications of creating data-driven business models?
A: In legal terms, companies need to define who is the owner of the information generated by components and devices. If a company is manufacturing sensors that are to be used in a smart system within the vehicle, who does that data belong to, the owner of the vehicle, the OEM, or the Tier 1 supplier? There will be an agreement throughout the supply chain to create an additional service that adds value to everyone involved.
Another major implication is how to create an added-value business based on the generated data. This will rely on what other data companies can interact with. For instance, regarding ADAS systems, we could study the correlation between performance and weather data. This is where OEMs can go beyond selling vehicles to offer added services. Another example is the “tires-as-a-service” model where users pay a fee and tire manufacturers to take care of all replacements. The data is out there; the great opportunity is to generate data-based business models.
Q: Who would be the potential customers of these new business models?
A: There are different customer profiles for these new business models. First, the final customer will be the priority. However, the ecosystem will enable different targets within the supply chain. For a company alone, it is extremely difficult to embrace Industry 4.0 practices when it is not part of an OEM’s strategy toward digitalization. Players within the supply chain will reach an agreement to, in addition to component manufacturing, integrate strategies to generate relevant data.
Other business models can be more disruptive. Some cities in Europe, for instance, are betting on free public transportation, taking a similar approach as Facebook or Instagram. No one pays for these platforms because people’s data is the real product. Public transportation could also become a new platform to generate data and provide additional services.
Q: What can help companies to be successful in their data strategy?
A: Businesses need to have an internal team to coordinate all data efforts. If an application programming interface (API) is used or developed without a proper strategy, it is futile. We hire young people due to their innovative ideas and we complement them with the years of experience of other professionals who can assess the financial impact that such a strategy could have. Many AI-related concepts have existed for several years but only now do we have the computing capacity to implement them. OEMs and Tier 1 must have two teams, one dedicated to data analytics and another to develop new data-based business models.
Mexico is at the forefront of engineering and data analytics implementation. We have many people interested in the subject and many capable engineers to develop these kinds of solutions. The missing puzzle piece is effective implementation. A key concept in data science is to be crystal clear about the problem we are trying to solve.
Q: What will be the impact of technology on the automotive value chain?
A: For the vehicle to be the digital platform, partnerships between tech giants and automakers should take place. Apple, Google, Microsoft, and other tech companies are investing in partnerships with different automakers and suppliers. The race is for who can transform the vehicle into the largest smart device for the user. As in any revolution, we need to be clear about the direction we are taking and adapt accordingly.
The industry should adapt fast to evaluate the impact this partnership will have on the country. Mexico is a low-cost manufacturing hub, which presented a challenge to advance Industry 4.0 operations as manual labor was actually cheaper than implementing comprehensive digitalization strategies. There is a great opportunity for companies to use technology to produce more with the same amount of resources. Betting on technology will bring great results to the country.
Q: What potential do sales and aftersales segments represent for new data-driven businesses?
A: Consumers are driving this technological revolution. We are living in a moment in which the end-consumer is purchasing a customized vehicle through the internet or an app. Advanced technology allows a great degree of personalized services and features that were not possible before. When it comes to aftersales service, an immersive digital experience will be essential. Moreover, new generations are also changing the paradigms of mobility as driving is not essential given additional services such as ride-hailing solutions. These are great opportunities as well.
Q: What are the challenges for Mexican companies to create a data-driven ecosystem?
A: The German government has different KPIs to evaluate the advancement of Industry 4.0 and its related ecosystem in a company. First, there are company strategies to embrace this trend. Second, there are smart factories and operations parameters, then, data-related services and finally, training and human capital. The very first step is strategy. All C-level executives should have a clear idea of where they are heading to. Once they have a clear strategy, training and finding the right people for the job is essential. Having that set, they can move on to smart manufacturing or other related processes.
In Mexico, this ecosystem has been delayed, largely due to our low-cost-manufacturing operations. However, strategies are emerging and are being accelerated due to the pandemic.
Q: What will be the role of ITEIN in this data-driven transformation?
A: ITEIN built a partnership with CLAUZ in the Puebla-Tlaxcala region. The first step we are taking is spreading the advantages of data analytics and AI while exploring data-driven business models. A few years ago, we spoke about digitalization and smart manufacturing. Now, we should ask ourselves how much income we are generating through digitalization and data. In Germany, the target is that 50 percent of the income of Tier 1 or OEM must come from car-related services, including data. ITEIN’s role is to create partnerships while helping companies to design their data strategy.
ITEIN is really involved in data literacy projects. Some of our applications imply a basic understanding of statistical concepts to use a predictive model that will need zero code. The essential aspect remains the interpretation. This is an optimal approach to accelerate data-driven decisions.
The Institute of Strategic Technologies for Business Intelligence (ITEIN) is a Mexican company focused on delivering data-driven solutions across different sectors, integrating data structures, and developing data-driven business divisions