Tag: Automobile Industry

The automobile industry is one of the largest sectors in the world. In just the U.S., the car & automobile manufacturing industry boasts a market size of $104.1 billion.

However, even an ecosystem as large as the automotive industry is not immune to the unprecedented challenges over the last few years. The coronavirus pandemic and subsequent semiconductor chip shortage forced manufacturers to cut 11.3 million vehicles from production in 2021.

In addition to supply chain challenges, automotive manufacturers have contended with labor shortages, shifts in consumer demand, and pressures to create a sustainable work environment.

But, like any resilient industry, the automotive sector has leaned into these new challenges and has begun to address them proactively. Let’s take a closer look at what these hurdles entail and, more importantly, how automotive businesses overcome them via technology’s strategic implementation.

Challenges and Trends Reshaping the Automotive Industry

While many challenges and trends prompt the automotive industry to evolve, three stand out above the rest. These roadblocks include:

1. Ongoing Worker Shortages

Like many other business verticals, the automotive industry has been plagued by worker shortages. Manufacturers need help to fill vacancies at every level of the organization, including line-level staff, decision-makers, and engineers.

This worker shortage has made it nearly impossible to rebuild supply and catch up to runaway consumer demand for new vehicles.

2. Supply Chain Disruptions

Various legs of the automotive supply chain have faced disruptions over the last few years. Of these, the shortfall of semiconductor chips had the most significant impact on production and vehicle inventory.

Unfortunately, many experts predict the shortage will continue well into 2023, if not beyond. It is too late for automakers to prepare for this extended chip shortage. All they can do now is adjust manufacturing strategies to align with consumer demand and cut back production on less popular vehicles.

3. The EV Revolution

Despite these other concerns, the electric vehicle (EV) market continues to grow. By Q4 of 2022, EV sales represented 5.6% of all auto transactions. This percentage doubled from the year prior when EV sales made up just 2.7% of the total auto market.

This statistic demonstrates that consumers are becoming more environmentally conscious and are interested in decreasing their impact on natural resources. Government incentives and tax credits are further contributing to the surging popularity of electric vehicles.

But what does all this have to do with the future of work in the automotive industry? It means that automakers will need to implement new and more sophisticated production processes and hire better talent if they hope to push the envelope in the EV space.

The New Industry Focus: Creating a Sustainable Work Environment 

One of the biggest drivers of change in the automotive industry is a global push toward creating a sustainable work environment.

Historically, the automotive sector has been anything but sustainable. Traditional assembly line-based production strategies focus on efficiency at the expense of almost anything else. These tactics result in the consumption of excessive amounts of power and often produce an unnecessary amount of resource waste.

However, the next-generation automotive industry will likely be unrecognizable to the pioneers of the last century. Modern manufacturers are reimagining every aspect of the supply chain, from material sourcing to assembly and distribution. Visionaries and thought leaders are also encouraging a shift away from old-school engineering and development processes in favor of AI-powered practices prioritizing efficiency.

Even the retail sales aspect of the automotive industry is changing. Many dealers are shifting toward online transactions, and some are transitioning increasingly to a made-to-order sales model. The end result is a more agile and less wasteful automotive supply chain.

Technologies that Can Fuel the Auto Sector’s Metamorphosis 

The future of work in the automotive industry will focus on sustainability, resilience, and agility while prioritizing efficiency. To realize their aspirations of a sustainable work environment,

industry executives, managers, and workers must embrace leading-edge technologies, including:

1. Predictive Analytics Software

Predictive analytics software will influence numerous aspects of the automotive industry. Organizations interested in forging sustainable work environments can use these analytics tools to identify production waste and increase operational efficiency. Additionally, they can leverage these solutions to create more energy-efficient vehicles that produce fewer greenhouse gasses.

Predictive analytics technologies will also assist with demand forecasting — organizational leaders can use these insights to prioritize in-demand vehicles as they contend with ongoing chip shortages.

2. Automation Tools

Automation tools will prove invaluable amid labor and talent shortages. Businesses in the automotive industry can use automation software to streamline redundant back-office processes and improve communication across the entire supply chain.

Manufacturers can also use automation tools to ramp up production while conserving energy and reducing waste.

3. Machine Learning and AI Solutions 

Machine learning and artificial intelligence technologies can transform every link in the automotive industry supply chain. Businesses can use these complementary technologies to optimize raw material sourcing, vehicle distribution, and production.

Because they allow for a more data-driven approach to manufacturing and sales, these technologies can reduce waste while simultaneously creating more agile and resilient supply chains. In turn, this will help keep the costs of vehicles manageable, thereby increasing accessibility to energy-efficient automobiles and EVs.

Read more: AI and ML for Faster and Accurate Project Cost Estimation

Accelerate Your Transformation with Fingent

When your business is in the automotive industry, creating a sustainable work environment should be one of your top priorities. Doing so will help you attract and retain top talent, meet consumer demand for more efficient vehicles, and align your business model with the latest regulations and compliance frameworks.

To achieve these goals, you will need access to purpose-built technologies designed for your business’s unique needs. That’s where Fingent top custom software development company, can help.

Our development experts can create dynamic software for your business. From customer-facing applications to internal solutions that empower your staff to be more productive, we build the software you need to thrive.

To learn more about our wide range of technology development services, connect with Fingent today.

How Machine Learning Edges Us Closer to Paperless Office?

Paper! Paper! Everywhere! Until recently you couldn’t imagine an office without paper. But today, Machine Learning allows you to print, sign, fill and scan digitally. It eliminates the hassle of handling multiple paper documents and helps organizations in converting to a paperless office.

In this blog, we will discuss how ML is influencing the modern workplace, the importance of paperless office and the industries which are seeing a tremendous impact through paperless technology.

The Role of ML in Achieving a Paperless Workplace

Machine Learning (ML) which is a subset of Artificial Intelligence (AI), is a science of software application where the program can learn to provide accurate outcomes without detailed coding. Through reinforcement signals, the software is able to “learn” the best possible approach to achieve the desired goal. Machine Learning algorithms are being trained to take on collaborative business processes and workflows for automation. This enables employees and the organization to go digital. 

Machine Learning replaces huge filing cabinets and the laborious process of searching for the right information. To find information easily, to collaborate and manage a business more effectively, ML uses powerful search and discovery tools. Since computers have the ability to process calculations, scan large amounts of data, and assess probabilities in a matter of seconds, Machine Language (ML) is proving to be an extraordinary innovation that will greatly impact the workplace. Let us consider some aspects of office organization and how ML is superior to the traditional paper workflow. 

Related Reading: AI and ML are revolutionizing software development. Here’s how!

• Efficient Document Organization

You save time in searching for documents. Information is readily accessible to all employees. Restricting access to confidential documents is made easier. You could access digital documents from anywhere which facilitates remote working. The origin of digital documents can also be traced easily.

• Enhanced Security 

Customers are often concerned about data protection. This requires that companies provide greater security beyond paper shredders and locked filing cabinets. The digital format offers greater document security. Since it is inexpensive to create backups, it is easier to retrieve lost or stolen data. 

• Lower Overhead Costs

Research estimates that an office worker makes more than 60 trips per week to the printer, fax machine, and copier. Digitizing documents eliminates those trips as well as the need to buy expensive equipment and pay for their maintenance. This has a direct impact on reducing operating costs. Digital documents could be sent across by electronic mail, saving postal costs. 

• Lesser Storage Space

A paperless office software frees up space. Companies now can archive everything on private company servers or in the cloud. Jonathan Velline, executive vice president for ATM banking and store strategy at Wells Fargo, talks about the benefits achieved by utilizing paperless document management tools and wireless devices: “It’s a very efficient use of space for us. In a 3,000 square-foot store, we would have an area for full-service banking and a separate area for self-service banking. Here we fit it all in one place.” Having a fully integrated paperless system, employees don’t have to have designated offices. Mini work areas inside the store are more than enough to digitally access customer information and any other details required. This way, Wells Fargo, reduced their office space to three times smaller than the average location.

Related Reading: You may also like to take a look at the top AI trends of the year!

How has Machine Learning Helped Industries to Go Paperless?

Machine Learning has found application in many industries and has helped them in going paperless. Let’s consider three such formerly paper-heavy sectors – legal firms, the automobile industry, and the insurance sector:

Legal firms

ML facilitates greater efficiency and productivity by allowing a lawyer to shift his focus from labor-intensive tasks to core functions like counseling, analysis, and advocacy. Since it is capable of eliminating the laborious process of managing and reviewing boilerplate documents within legal contracts, it allows time for attorneys to appear in court, advice their clients, and negotiate deals. ML can also generate alerts to provide advance notification regarding crucial dates in contracts, such as renewal dates. It can reduce the overall cost of litigation in many ways. It reduces the amount of time a lawyer spends on proofing a document and helps locate relevant information quickly. Use of computer algorithms also helps an attorney identify relevant information that is buried in electronic documents. ML is further equipped to provide a paper-free trial for legal firms. 

Automobile industries

Machine Learning enables machines and devices to replicate the way humans learn. This has enabled great strides in the automobile industry in terms of supporting a paperless office. Machine Learning is also capable of generating highly sensitive autonomous systems that can speed up the process of filing claims if an accident occurs, eliminating the time consuming and paper-heavy process of filling up elaborate forms.

With ML algorithms, the automotive industry is set to have various features like automatic braking, pedestrian, collision avoidance systems, and cyclists’ alerts. It also supports dealers and manufacturers by enabling a paperless update of the vehicle’s firmware. Through the cloud, a diagnostic system can communicate any problems by sending performance data directly to the manufacturer or schedule repairs. 

Insurance

Insurers are using Machine Learning to boost customer service, increase their operational efficiency, and even detect fraud.  ML can improve the process of insurance and automatically move claims through the system. With sophisticated rating algorithms, companies are able to fit in most risks as long as they find good pricing. ML can support agents in classifying risks and calculating accurate predictive pricing models. Tools powered by ML, help consolidate volumes of highly varied data such as membership and provider data, insurance claims data, benefits, and medical records without the use of paper. These solutions can process and structure data with insights leading to a higher quality of care, costs reduction, and fraud detection.

Insurers can draw insights from data about behaviors, individual preferences, lifestyle details, attitudes, and hobbies to create personalized products such as loyalty programs, policies, and recommendations. 

Machine Learning- Deciphering the most Disruptive Innovation : INFOGRAPHIC

Go Paperless Now!

The call to move to a paperless office is getting more urgent every day. To make this transition easy, we can help your organization reap the best benefits of Machine Learning.  Give us a call and let’s talk!