PURPOSE-DRIVEN ADAPTABLERESILIENT

Manufacturing

The pandemic has hastened the automotive industry’s shift towards connected and autonomous vehicles

A CASE for Acceleration

The rise of digital technologies such as the cloud, internet of things, artificial intelligence, machine learning, analytics and intelligent automation has revolutionized automotive products. Smart, highly connected vehicles enable a new way to be mobile by offering an increasing level of autonomy for the user. The COVID-19 pandemic has made such connected and autonomous vehicles (CAV) much sought-after.

Lockdowns and policy restrictions across the world have placed an enormous strain on mobility, global supply chains, local transport, and distribution of medical supplies and food and other essentials. Enabling CAV capabilities provides an

extraordinary opportunity in reducing contact, allowing for social distancing and halting the spread of the disease. This paper explores how companies in the automotive ecosystem need to adopt a neural mindset to leapfrog their product innovation and transformation programs in CAV and build differentiating competencies to drive competitive advantage in the digital era.

Abstract

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Technology is the lynchpin for manufacturing firms to become resilient to unprecedented events like COVID-19. It will play a key role in defining the future of business, customer experiences, and product or service behaviors of the agile automotive enterprise. TCS terms this future as Neural Automotive, inspired from biological neural systems. It comprises an intensely networked set of partners aligned to a common purpose, where the value chains are responsive, adaptive, and personalized, with intelligence built on the 'edge' of the networks. Embracing this mindset will be crucial not only as an integral part of providing products and services, but also during the product development cycles.

Neural Automotive

The transportation industry has been evolving constantly and is now moving towards mass-scale connected, autonomous, shared, and electric (CASE) systems, where the new business models are supported by artificial intelligence (AI), machine learning (ML), 5G, cloud computing, and big data. These technologies will help agile automotive enterprises take advantage of neural capabilities and adapt their businesses to the evolving CASE trends to cater to the post-pandemic customer.A combination of these technologies can also realize new ways of living and travel; some indications of what the post-pandemic market will look like are already clear, such as the development of smart cities and the variety of travel options made available through the introduction of CAVs.

The evolution of CASE

Figure 1: The evolution of CASE

Horse & Carriage

Combustion Engine

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Automobile

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Tesla Autopilot

Waymo and Uber Founded

Machine Learning/Deep Learning

Connected Car

Cruise Control Motor Buses

Steam Engine

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High SpeedRail

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Evolution of CASE

The health, social, and economic crisis triggered by the pandemic has led to the following seven emerging trends for the

automotive sector globally.

COVID-19 impact on CASE

AVs in Geo-Fenced Areas Shared Mobility

Drop in Oil Prices Utilization of Partnerships Mixed Messages on Investment

E-commerce and Supply Chain

Increased Time Spent in Vehicles

Figure 2: Global impact of COVID-19 on the CASE ecosystem

AVs in geo-fenced areas

Rise in demand for contactless deliveries and services, mandated by government policies as well as public fear of contagion, is set to increase the demand for CAVs.

Fall in oil prices

The various travel restrictions imposed across and within countries have caused a sharp drop in oil prices, which is encouraging personal vehicle use. It might also impact automotive electrification programs in the short and medium term.

Shared mobility

Shared mobility is the most affected, as people continue to avoid public transport, ride-hailing services, and taxis for good hygiene and social distancing reasons.

R&D spend

Automotive original equipment manufacturers (OEMs) and their suppliers need to look at balancing their budgets by optimizing capital expenditure and research and development (R&D) spend by exploring partnerships.

E-commerce and supply chain

Strict government-imposed processes and rules have exposed the weaknesses of and dependence on manual operators.

Increased time spent in vehicles

People will increasingly prefer to drive longer distances rather than take short-haul flights due to social distancing needs.

Investments in CASE

As the overall demand for automotive products slows due to job losses and a weakening economy, leading to falling revenues and profits for automakers, this could stress investments in CASE programs. However, with OEMs and start-ups announcing new funding and ventures in CAVs, the industry is indicating that strategic projects remain a priority.

The outlook for CASEThe short–term view

As lockdowns continue sporadically, vehicle usage will reduce, which will lead to fewer new sales. This would be partly offset by a steep increase in the number of second-hand purchases as people increasingly seek private means of mobility despite funds crunch.

An automotive enterprise would display connectedness in its products and services. For example, a shared mobility service that needs to increase customer confidence should have connected features such as contact tracing in its vehicles. This will assure the user of the cleanliness and hygiene of the vehicle and might even make it possible to track down the affected and stop the spread of the disease.

Additionally, to continue to prioritize CAV programs, automotive OEMs are increasingly collaborating with partners and solution providers to optimize their R&D spend, as the full financial implications of COVID-19 are realized.

The medium–term view

An agile automotive enterprise will need to work towards leveraging an ecosystem of partners to speed up implementation, improve its balance sheet, and optimize costs. Creating consortiums and ecosystems will help accelerate the development of CASE solutions to create personalized customer-centric products and services.

With demand rising, this is an appropriate time to adopt an AV rollout strategy to prioritize geo-fenced areas and alternate use cases that are relevant and quick to deploy, as the operating conditions can be tightly controlled to ensure the desired functionalities and safety of the vehicles.

Simulation would become key to validating autonomous vehicles as physical testing is not possible during lockdowns. Intelligently identifying test cases and simulation at scale enables automotive firms to remote test AVs flexibly, without the need for expensive hardware and infrastructure.

The long–term view

Connected experiences will continue to grow as the personal vehicle becomes the focal point for long-distance travel. Companies will need to invest in optimizing in-vehicle customer experience as this will be a key differentiator among the competition. Investment in CAVs is set to increase, particularly in the commercial market as players realize the importance of moving away from manual operations. CAVs will become the key segment to enable and operate a smart supply chain that can withstand the stress of another crisis.Figure 3: Post-pandemic outlook for CASE

Reduced new vehicle sales, higher number of used car purchases

Introduction of contact tracing in shared mobility

Moving from CAPEX to OPEX models

Leverage partners to expedite CASE solutions

Form consortiums to mitigate the risks and costs of development

Simulation will become key to validating autonomous driving systems

Personal vehicles to be used for more medium to long-distance drives

In-vehicle experience to become a key differentiator among competition

CAVs to enable smart supply chain operations

Short Term

Medium Term

Long Term

The key challenge in delivering autonomous capabilities lies in the sheer scale of the petabytes of data to be

managed through the data value chain, the complex algorithms that need to be developed and validated, and the

huge storage and processing capacity needed to support the development of AI in vision recognition,

path-planning, and decision-making models. Gleaning huge amounts of customer data for insights is key to

enhancing customer experience and providing highly personalized connected services to drivers, passengers, and

operators. The evolution of the automotive industry amply illustrates how a vehicle is much more software-centric

today than in the past when it was simply an engineering product.

Manufacturers and technology players can overcome these challenges in data management and validation by

bringing together multiple technologies including AI/ML, cloud, analytics, vision recognition, and simulation

capabilities to fashion a highly robust data management and visualization framework essential to delivering on the

CAV promise to transform the world of mobility.

In the post-pandemic world, businesses need to adopt a neural mindset by embracing technology to become

resilient to the unprecedented changes. Utilizing a partner ecosystem aligned to a common purpose, looking

beyond traditional and legacy business models, being purpose-driven, and developing a blueprint for their

transformation journey will help automotive firms adapt, survive, and grow as the world of mobility transforms

around them.

Revisit the fundamental business model as well as organizational culture and make it resilient enough to

withstand short-term shocks and responsive enough to quickly launch new offerings or capabilities and target

new markets without yielding on customer experience.

Switch over to an agile mindset, utilize the latest technologies, and embrace new business and potential

partnership opportunities that disruption in this industry provides.

The adoption of CASE in the post-pandemic era

By embracing neural automotive, an agile automotive enterprise can use technologies to develop intelligent, connected, and

automated processes in their value chain operations. Some key themes that reflect the neural thinking are as follows:

1. Accelerate automated driving system validation through AI-enhanced simulation validation and reduce dependence on

physical testing and public shadow testing.

2. Evaluate AV use cases that are quick to deploy by building robust business cases and address immediate social problems; for

example, parcel and grocery delivery and commercial supply chain use cases.

3. Optimize CAV infrastructure through enhanced AI/ML operations services.

4. Accelerate the development of AV capabilities through a robust data management solution.

5. Improve in-vehicle customer experience, evaluate new business models to engage with customers, and generate new

revenue opportunities using customer data analytics.

While OEMs and players in the CASE ecosystem must address the impact of this pandemic on their balance sheets in the short,

medium, and long term, enterprises will witness a significant upswing in the demand for CAVs. For instance, there will be

increased need for vehicles to conduct deliveries. A report by The World Economic Forum states that the rising demand for

e-commerce will result in 36% more delivery vehicles in inner cities by 2030¹. Besides, the increased incidence of long-distance

driving will trigger demand for connected services in personal cars as well as enhanced advanced driver-assistance systems or

autonomous driving (ADAS/AD) capabilities to make driving a pleasure.

Automotive enterprises with a high-growth mindset can capitalize on these opportunities. By being adaptable, purpose-driven,

and resilient, they can use the pandemic to grow and transform their businesses.

Key CAV transformational themes for the future

1 World Economic Forum; The Future of the Last-Mile Ecosystem; January 10, 2020; https://www.weforum.org/reports/the-future-of-the-last-mile-ecosystem

About the Authors

Vignesh Amur

Vignesh is an Automotive Domain Consultant from the Connected and Autonomous Vehicle Business Group in the Manufacturing Business Unit at TCS.He is involved in advancing solutions in the area of autonomous vehicle development and validation with a special focus on simulation-based testing.He previously worked at a global auto OEM, one of TCS’ customers, on validation and verification-related projects. Vignesh holds a master’s degree in automotive engineering.

Laksh Parthasarathy

Laksh is Managing Partner and Global Business Head for Connected and Autonomous Vehicle Development and Validation Services in the Manufacturing Business Unit at TCS. With over 20 years of experience as a thought leader in the automotive industry, he primarily focuses on developing solutions to address challenges faced by the connected and autonomous vehicle industry.

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