Transforming Aftermarket Experiences: The Power of Service Lifecycle Management
The significance of providing exceptional aftermarket services cannot be overstated in today’s times as organizations strive to meet the dynamic expectations of their customers and stay competitive. Service Lifecycle Management (SLM) emerges as a powerful solution, seamlessly integrating various aspects of post-sales support to create a connected and customer-centric experience. In this blog post, we’ll delve into the multifaceted features of SLM, exploring how it revolutionizes field service, warranty management, service contracts, service parts management, customer service, supplier recovery, service intelligence, recalls, auditing, and service quality. Additionally, we’ll shed light on how Artificial Intelligence (AI) and Advanced Analytics are playing a pivotal role in powering SLM. Customer Service: SLM enhances customer service by providing a 360-degree view of customer interactions and service history. AI-driven chatbots and virtual assistants enable quick issue resolution, while predictive analytics anticipates customer needs, ensuring a proactive approach to service delivery. Warranty Management: SLM enables efficient warranty management by automating claims processing, tracking warranty periods, and ensuring compliance. AI algorithms can predict potential warranty issues, allowing organizations to take preventive actions before problems escalate, ultimately saving costs and improving customer trust. Service Intelligence: Harnessing the power of AI and Advanced Analytics, SLM provides actionable insights into service performance. Predictive analytics identifies trends and areas for improvement, empowering organizations to make data-driven decisions and continuously enhance service quality. Field Service: SLM streamlines field service operations by optimizing technician scheduling, route planning, and real-time communication. AI-driven predictive maintenance ensures proactive service, reducing downtime and enhancing overall customer satisfaction. This feature is particularly beneficial for industries relying heavily on equipment maintenance, such as manufacturing and healthcare. Service Parts Management: Effective inventory management is crucial in providing timely service. SLM optimizes service parts logistics, minimizing stockouts and excess inventory. AI algorithms predict demand patterns, ensuring that the right parts are available when needed, reducing lead times and costs. Service Contracts: The management of service contracts becomes seamless with SLM, providing a unified platform to create, manage, and renew service agreements. AI-powered analytics can identify upsell opportunities and recommend personalized contract options based on historical data and usage patterns. Recalls and Auditing: SLM ensures a rapid response to product recalls by efficiently tracking affected units and managing the entire recall process. Advanced analytics aids in auditing, ensuring compliance with industry regulations and providing a comprehensive overview of service processes. Supplier Recovery: SLM facilitates collaboration with suppliers by streamlining communication, order processing, and performance tracking. AI analyzes supplier data to identify potential risks, enabling organizations to proactively address issues and maintain a reliable supply chain. Service Quality: Continuous improvement is at the core of SLM, as it enables organizations to monitor and enhance service quality. AI-driven analytics identify patterns in customer feedback, allowing companies to address issues promptly and refine their service offerings. Final Thoughts Service Lifecycle Management is a game-changer in the aftermarket services landscape, fostering seamless and connected experiences for both businesses and customers. The integration of AI and Advanced Analytics adds an extra layer of intelligence, enabling organizations to not only meet but exceed customer expectations. As industries evolve, embracing SLM becomes imperative for those aiming to stay ahead in the competitive market, delivering unparalleled post-sales support and solidifying customer loyalty. Tavant SLM solution is a comprehensive solution suite comprising of products and services designed to empower manufacturing ecosystem by simplifying and streamlining service lifecycle management processes.
Embracing the Service Life Cycle Management Opportunity and the Challenges It Presents
More digital technology in more machines, increased capacity to transmit data, expanded data storage and faster data processing in the cloud, and the emergence of sophisticated artificial intelligence (AI) and machine learning (ML) have invigorated manufacturers’ interest and activity in service life cycle management (SLM). The ability to access and analyze so much information has presented the manufacturing ecosystem with an interesting opportunity to alter its business model to focus as much or more on servicing equipment after it is sold as on actual production. Service life cycle management is historically more profitable and enables producers to cultivate the long-term relationships that customers prefer over one-time purchases.
Service Contracts in Manufacturing: A Blueprint for Revenue Growth and Customer Loyalty
In today’s competitive manufacturing landscape, the imperative to stay ahead transcends the realm of producing high-quality products. Service contracts have evolved into a strategic cornerstone for manufacturers, providing an additional revenue stream, fostering customer loyalty, and delivering crucial insights into customer expectations. The symbiotic relationship between service contracts and manufacturer success hinges on the ability to consistently exceed customer expectations while capitalizing on the wealth of data generated through service interactions. Let’s explore the various advantages of Service Contracts in Manufacturing below: Diversifying Revenue Streams Service contracts offer manufacturers a dependable additional revenue source, extending far beyond the initial product sale. Ongoing services such as maintenance, repairs, and upgrades create a steady income throughout the product’s lifecycle. This predictable revenue ensures financial stability and facilitates better planning and investments in research and development. As manufacturers bolster their ability to innovate, they gain a competitive edge, positioning themselves as dynamic entities capable of adapting to the market’s ever-changing demands. Building Long-Term Customer Loyalty The significance of service contracts goes beyond monetary gains; they play a pivotal role in nurturing enduring customer relationships. Offering comprehensive service packages leads to increased customer loyalty. Timely resolution of issues, proactive preventive maintenance, and efficient support contribute to positive customer experiences. These positive experiences foster loyalty and potentially translate into repeat business and positive word-of-mouth referrals, further solidifying a manufacturer’s market position. Insights from Service Interactions Every service interaction allows manufacturers to gather valuable data about their products and customer needs. The nuanced analysis of service contract data yields insights into common issues, usage patterns, and emerging trends. This treasure trove of information becomes a potent tool for continuous improvement. Manufacturers can enhance product design, identify areas for innovation, and proactively address customer concerns, ultimately ensuring their offerings remain in sync with evolving market dynamics. Tailoring Products to Customer Needs Armed with a profound understanding of customer expectations, manufacturers can tailor products and services to better align with those needs. Whether introducing new features, optimizing existing functionalities, or addressing pain points highlighted by service interactions, manufacturers can continually refine their offerings to resonate with customer preferences. This not only boosts customer satisfaction but also positions the manufacturer as a customer-centric entity capable of adapting swiftly to evolving market demands. Proactive Maintenance and Risk Mitigation Service contracts empower manufacturers to adopt a proactive approach to maintenance, substantially reducing the likelihood of product failures and downtime. Predictive analytics derived from service data allow manufacturers to identify potential issues before they escalate. This proactive stance facilitates timely interventions, minimizing disruptions for customers and enhancing the overall product experience. Furthermore, it instills confidence in customers regarding the manufacturer’s commitment to delivering reliable products. Strategic Expansion Opportunities Beyond the immediate benefits, service contracts open avenues for strategic expansion. Manufacturers can explore additional service offerings, creating new revenue streams and diversifying their portfolio. This strategic expansion reinforces financial stability and positions manufacturers as comprehensive solution providers capable of addressing a spectrum of customer needs. Final Thoughts In conclusion, service contracts represent a multifaceted strategy for manufacturers to secure additional revenue, build customer loyalty, and gain invaluable insights into customer expectations. To unlock these benefits, manufacturers must prioritize meeting and exceeding customer expectations in their service offerings. By leveraging the data generated through service interactions, manufacturers can address immediate concerns and position themselves as dynamic entities capable of adapting to the ever-changing landscape of customer needs and preferences. As the manufacturing industry evolves, service contracts emerge as a vital tool for those seeking to survive and thrive in a customer-driven marketplace.
From Warehouse to Customer: The Strategic Journey of Service Parts in Service Lifecycle Management
Within the aftermarket world, service parts management assumes a pivotal role in upholding customer satisfaction and operational excellence. This blog explores the role of service parts management, its far-reaching influence on various stakeholders, and the nuanced challenges it presents alongside strategic solutions. The Significance of Service Parts in Service Lifecycle Management (SLM) Aftersales service transcends mere technical support; it is a commitment to upholding customer satisfaction and brand integrity. Service parts help in product longevity and performance, facilitating timely repairs, maintenance, and upgrades. Service Parts Management (SPM) is not just a logistical function; it is the backbone that reinforces trust, loyalty, and an enriched customer experience, solidifying a brand’s reputation for reliability and support. By harnessing the synergies across interconnected SLM modules, organizations can attain greater agility, visibility, and control over their spare parts operations. This, in turn, leads to the maximization of service parts availability, minimization of costs, and the facilitation of sustainable growth. Customer & Field Service – The seamless orchestration of service parts ensures that orders are initiated promptly when service requests or work orders are raised. Real-time visibility into service activities enables proactive planning and inventory management to meet the dynamic demands of the service domain. SPM acts as the linchpin, aligning service parts orders with contractual obligations and minimizing errors and disputes. This not only improves customer satisfaction but also maintains compliance with contractual commitments. Warranty Management – An often overlooked facet of SPM is its role in warranty management. It allows for the automatic identification of warranty-eligible parts, streamlining the process of identifying, ordering, and replacing parts covered under warranty. Enhanced visibility into warranty claims and coverage aids in optimizing service parts inventory, ensuring that organizations are well-equipped to fulfill their warranty commitments. Service Campaign Management – SPM facilitates proactive identification of parts subject to recalls or service campaigns. This proactive stance ensures the timely fulfillment of replacement parts, mitigating risks associated with non-compliance or safety issues. The interconnected nature of SPM within the broader SLM framework ensures that organizations are not only responsive but also preventative in their approach to potential issues. Supplier Recovery – A crucial aspect of SPM is the improved visibility into supplier recovery processes. This transparency helps in tracking returns, processing refunds or replacements, and optimizing inventory levels to minimize financial losses. Synchronized efforts between organizations and suppliers foster a mutually beneficial relationship, contributing to streamlined supply chains and shared growth. Service Quality Management – SPM goes beyond logistics; it enables organizations to monitor and analyze parts performance metrics and quality. Key indicators such as fill rates, lead times, and order accuracy are closely tracked, providing insights into the effectiveness of service operations. This data-driven approach empowers organizations to continuously enhance service quality. Service Contracts For organizations operating within contractual frameworks, SPM ensures that service parts orders align with contractual obligations and service level agreements (SLAs). This meticulous alignment minimizes errors and disputes, thereby improving customer satisfaction and maintaining compliance with contractual commitments. Service Parts Management At the heart of it all lies the centralization of service parts management within an integrated SLM solution. This not only streamlines end-to-end service parts lifecycle processes but also provides data-driven insights. These insights, derived from integrated modules, enable predictive analytics and optimization algorithms to anticipate service parts demand. This, in turn, optimizes stocking strategies and ensures the timely availability of critical parts. Connecting Stakeholders: OEMs, Suppliers, Dealers, and Customers Service parts management serves as the nexus connecting a myriad of stakeholders within the aftersales ecosystem. This interconnected network collaborates harmoniously to ensure that the right part is at the right place at the right time, delivering superior service experiences and driving operational excellence. Suppliers – Effective communication, shared data, and synchronized efforts between suppliers and organizations contribute to streamlined supply chains and mutual growth. SPM acts as a bridge, facilitating this collaboration and ensuring that suppliers play a pivotal role in supplying high-quality components on time. OEMs – For Original Equipment Manufacturers, the efficient supply and management of service parts are not merely logistical puzzles but strategic imperatives. It contributes to brand integrity, customer satisfaction, revenue growth, and the ability to uphold warranty commitments. Additionally, it plays a pivotal role in fostering customer loyalty and repeat business. Dealerships – Dealerships serve as frontline ambassadors, providing expert guidance and support to customers seeking service parts and aftersales services. Their role in the aftersales ecosystem is critical, and SPM ensures that they have the necessary tools and information to serve as trusted service partners. Customers – For customers, service parts become the lifeline for maintaining and repairing their cherished products. The availability of the right service parts at the right time directly influences the customer experience, shaping perceptions of brand reliability and customer care. Challenges in Service Parts Management: Solutions for Success Understanding challenges in service parts management and implementing strategic solutions is crucial for unlocking untapped potential and ensuring operational excellence. Demand Forecasting and Inventory Optimization Inaccurate demand forecasting and suboptimal inventory levels can lead to stockouts or excess inventory, impacting customer satisfaction and operational costs. The solution lies in implementing advanced analytics and forecasting models that leverage historical data, customer trends, and market insights to predict demand accurately. Additionally, employing inventory optimization techniques such as ABC analysis and just-in-time inventory helps optimize stocking levels and minimize carrying costs. Parts Obsolescence and Shelf-Life Management Managing parts obsolescence and shelf-life expiration poses a significant challenge, particularly for components with limited usage or those susceptible to degradation over time. Excess and obsolete inventory tie up valuable resources and can result in significant financial losses. The solution involves regularly reviewing service parts inventory and implementing proactive strategies such as phase-out plans and shelf-life management protocols. Prioritizing the use of First-In-First-Out (FIFO) or First-Expired-First-Out (FEFO) methods helps mitigate the risk of expired inventory. Supply Chain Disruptions and Lead Time Variability Supply chain disruptions and lead time variability can result in delayed service parts delivery and customer dissatisfaction. The solution lies in diversifying the supplier
Driving Innovation in Warranty and After Sales: The Role of Generative AI in the Manufacturing Industry
Generative AI has gained significant prominence worldwide in 2023, transforming the way researchers, enthusiasts, and software developers tackle machine learning and artificial intelligence challenges. Generative AI is an artificial intelligence subfield that can create content in the form of text, images, music, and code. A massive amount of text data is used to train these models. Let us examine some use cases of these models in the manufacturing industry. Text Generation and Summarization: Large language models can generate text in a conversational and human-friendly manner. These models support several languages and aid in use cases such as producing content for marketing and sales departments, supporting developers with code documentation, and assisting developers in understanding the code written. Long-format papers can be summarized using Generative AI models to deliver precise, context-relevant information. Summarization can be tailored to the user’s preferences. Semantic Search Systems: These models can be used to build search and knowledge-based systems that can recognize the context in user queries and return relevant information, enhancing user acceptability and search experience over traditional keyword-based search systems. Question and Answering Systems: The generative models may also answer user queries by recognizing the context of the query and generating answers utilizing knowledge learned from massive amounts of data relevant to the user inquiry. Synthetic Data Generation: Generative models, with their vast knowledge base comprising massive amounts of data, may generate synthetic data for experiments and training machine learning models in situations where real-world data is unavailable. Image Generation: Generative models can create images with various artistic styles, settings, and colors. These are useful in generating synthetic images to aid users in machine learning modeling. Applications in Manufacturing – Warranty and After Sales Claim Process Optimization: Warranty dealers and claim processors can use Generative AI models to revolutionize question-answering systems by answering queries with interpretable and appropriate reasoning by understanding the context and semantics of queries using a large number of documents. The systems shorten the procedure and optimize it. Customer service and support: Using generative language models such as GPT3.5 and GPT4, personal assistants and chatbots can be constructed to aid customer support teams in addressing client inquiries and issues relating to warranty, claim procedures, and troubleshooting steps. These models can also help with faster claim processing and provide a better client experience. Warranty Claim Validation: Claims processors can use Generative models to analyze and validate dealer claims. These models use warranty information, product specifications, and claim information to identify patterns of fraudulent claims and make decisions to automate the validation process, prevent fraud, and speed up claim settlement. Recommendations: Using usage patterns and historical data, large language models can provide individualized recommendations to clients and dealers regarding warranty coverage and upgrades. Text Sentiment Analytics: Customer evaluations and feedback can assist warranty providers and dealers in improving their service, identifying and resolving reoccurring issues, and enhancing the overall customer experience. Without the need for training, generative models can assist in determining the sentiment of the text. These models extract textual patterns and provide reasoning for sentiment prediction. Intelligent Search System: Generative AI models can aid in the creation of a centralized knowledge base that dealers, technicians, claim processors, and warranty providers can use to find and obtain relevant information on claims, warranties, troubleshooting common issues, service manuals, and FAQs. It lets you quickly discover root causes, potential part replacements, SLAs, and applicable resolution actions. It can return relevant search results and citations, as well as supporting content related to the context of the query. Quality Control and Defect Detection: Generative AI algorithms can analyze a large amount of manufacturing data, including sensor readings and images, and process this information to detect defects and patterns identified in the data. Tavant is actively exploring and integrating these cutting-edge features into the highly advanced Tavant Manufacturing Analytics Platform (TMAP). This strategic initiative aims to empower customers with a distinct competitive edge by utilizing advanced Generative AI models. In our initial forays into this dynamic field, we have successfully developed compelling POCs in the domains of chatbots, personalized assistants, and smart-search systems. Leveraging warranty after-sales data, these pioneering POCs deliver unparalleled value to dealers and claim processors. Some of the modules in TMAP where we are exploring Generative AI models are: Warranty – Automate claims processing, identify suspicious information, improve dealer performance, reduce warranty spend, enhance the quality of the claim, and identify anomalies in the image. Price – Recommend optimal parts price, completive pricing analysis, evaluate the performance of pricing strategies, monitor and alert price changes, and segment customers based on their price sensitivity. Quality – Identify product quality issues, failure rates, and areas for improvement by analyzing claims, returns, and repairs. Field – Optimize services using AI Smart search, service & parts demand to forecast, and real-time insights enabling you to improve service quality and enhance customer satisfaction. Contract – Enhance contract performance, improve profitability, mitigate risks, and strengthen customer relationships through personalized contract offerings and optimized prices. Final Thoughts By utilizing the various text content available, such as installation and warranty manuals, service guides, and safety guidelines, Generative AI can transform the manufacturing industry by enabling technicians, dealers, and manufacturers with personalized assistants, chatbots, intelligent search systems, and recommendations. This can assist dealers in providing excellent customer care, as well as business users in identifying potential issues and improving the product and after-sales services.
From Cost Center To A Competitive Advantage: Warranty Management In Manufacturing Today
We have all experienced that moment… staring at a dysfunctional product and wondering what the repairs will cost us. And more importantly… is the product still under warranty? As a customer, it seems like a solid and straightforward customer service process, yet the warranty management process is viewed as a manually intensive administrative task that’s not exactly the most productive or efficient. Warranty management is a critical set of processes and activities within service life-cycle management. While manufacturers may have viewed the warranty management process to be a drain on resources and revenue, technology has changed the game. Technology: The pill to warranty management headaches In an increasingly competitive world, manufacturers are beginning to recognize the opportunity technology offers. Not only in terms of minimizing costs but also in enhancing customer experience through optimization of the warranty management process. By optimizing warranty processes, manufacturers can reap financial and operational benefits and positively impact their entire service life-cycle: increased asset reliability, better production, and improved supplier relationship management. Studies show that the market for warranty management systems is valued at $2.87 billion in 2019 and is expected to reach $6.24 billion over the next five years, growing at a CAGR of 13.8%. Let’s look at some of the issues that warranty management solutions can resolve: Problem: Multiple Stakeholders The warranty process runs across multiple partners, which can be both internal and external, to the manufacturer. It’s easy to lose sight of metrics within this network of dealers, partners, and OEMs. As a result, product performance, usage, and ultimately, the customer experience gets affected. Technology Solution: Warranty Management Systems Software solutions can radically improve connectivity across the service life-cycle. Warranty management solutions can help reduce claims processing by 70%, by bringing all stakeholders together into a seamless system. Warranty Management Systems can positively impact collaboration with suppliers, channel partners, and customers by enabling manufacturers to focus on functionality that provides visibility into a product’s warranty life-cycle. Problem: Information Siloes The lack of transparency has many manufacturers struggling to gain visibility into their customer or product usage. This is especially true in industries where products are sold through dealers, retailers, distributors, resellers such as automotive or other equipment and machinery. With so many stakeholders involved, it is apparent that information is disconnected, leading to inefficiencies, delays in new product introduction, and ultimately dissatisfied customers.> Technology Solution: IoTs and Closed Loop Collaboration The ability for warranty operations and other service processes to leverage connected product data hinges on the number of connected assets. While the data is available, legacy systems often prevent visibility across relevant teams. By connecting smart devices and sensors and the data generated by machine networks, manufacturers can access a new level of insight needed to intelligently update the warranty claims processes. Problem: Time-Consuming and Fraudulent Claims One of the reasons warranty management is considered to be a costly affair is due to the amount of time and resources needed to investigate warranty claims. Time to process a warranty claim often requires customers to wait without their functioning product leading to increased frustration. Where the processing is still manual, errors and fraud can further derail the warranty management process. Technology Solution: AI & Machine Learning AI-driven real-time analysis of warranty claims helps understand behavior based on environment and recommend efficient product usage. This technology can help improve performance, reduce failure rates, and enhance productivity. Additionally, as more data is fed into the system through IoTs, machine-learning can enable automated warranty processes to make recommendations at a much faster pace than ever before. Problem: Duplication of Efforts Redundancies in data can cause a lot of problems in warranty management processes. It is estimated that more time and money is spent that more time is spent on administrative tasks such as updated customer information than on resolving the problem. This duplication of data inadequacy can often result in errors and more siloes within the service life-cycle process. Technology Solution: Automation Automated warranty claims systems can enhance process efficiency by reducing or eliminating manual efforts in claim submissions such as parts return and payments, turnaround time, and increasing productivity. Data accuracy will also be improved human error can be circumvented, reducing errors and redundancies. The future indicates that with the increasing use of smart devices, wearables, and smart home units, adopting a warranty management solution will likely enable an unparallel customer experience. Technology partners that offer warranty and service contract management expertise, which leverage AI and ML, will provide a distinguished advantage to the manufacturers. And manufacturers that quickly move towards a system to take advantage of these capabilities can secure their business competitiveness through increased customer satisfaction and enhanced product quality. SOURCES: https://www.mordorintelligence.com/industry-reports/warranty-management-system-market
Electric Vehicles and their Impact on Automotive Warranty Management
The falling costs of the lithium-ion battery pack, coupled with the rising concern of climate change, in addition to policy incentives, rising incomes, and technological advancements have pushed the adoption and sales of electric vehicles (EV) this last decade. The Growth of the EV Segment Bloomberg NEF’s Electric Vehicle Outlook study forecasts that EVs will hit 10% of global passenger vehicle sales by 2025, growing to nearly 28% in 2030 and 58% in 2040. In the US alone, the number of brands offering EV options will grow from 16 now to at least 40 in 2025, with electric vehicles offering consumers a wide range of segments and price points. In addition to climatic awareness, governments are also driving change. US President Biden began his term with an order to electrify the federal fleet of about 650,000 vehicles, investing in over 550,000 public charging points, and taking initiatives to bolster the domestic supply chain for critical technologies and raw materials. The Impact of EVs on the Automotive Industry All of this indicates that the next decade will see a major shakeup in the automotive industry. One example is an estimation by Ford, which believes that the simplification in the assembly of EVs could lead to a 50% reduction in capital investments and a 30% reduction in labor hours, as opposed to internal combustion engine (ICE) manufacturing. Similarly, as the number of electric vehicle consumers grows, other aspects of the automotive industry including automotive design, supply chains and production processes will undergo a transformation as well. As vehicles become more computer-dependent and less combustion engine related, learning gaps are expanding for technicians and even drivers, as they learn to handle what is essentially a new operational vehicle. EV Trends and Future of Warranty Management The automotive industry is already bracing for a shake-up when it comes to repair and parts management. With the surge in Electric Vehicles across the world, we can expect the OEMs to face an increase in the volume of technical warranty requests from their dealers. And because every vehicle is different, there will be a significant shift in how to handle these claims initially. The service and maintenance of an electric vehicle are likely to be highly different from a typical combustion engine, to which the industry has so far been geared. Not only do EVs have fewer mechanical parts, but some components also (such as plugs and sockets, inverters and powerpack coolers), aren’t part of the existing automotive warranty service. How Connected EVs Change the Repair Game There are also several different types of EVs, such as hybrid and connected vehicles, which could further add more complexity to the issue of long-term service and maintenance. IoT devices are also enabling vehicles to stay connected and detect vehicle failures even before they physically reach the service center. That means connected EVs ​will offer vehicle owners the ability to self-service and distinguish between actual car failure and driver solvable issues. This will impact automotive servicing to a greater extent as manufacturers may need to include ability to educate the driver if vehicles are brought in with no actual failure. There are also likely to be more auto repairs in the field, as the parts get smaller and more computer-like. This could have a significant cost and operational impact on manufacturer warranties as mechanics (with computerized knowledge) travel to the customer rather than the other way around. Smarter Cars, Smarter Warranty Management To manage this transition, OEMs will need to become smarter about their warranty management processes. By using technology to examine warranty claims, OEMs can bring increased efficiency and transparency into a complex process. This will, in turn, enable OEMs to offer superior customer-centric service. The next generation warranty management software solution leverages artificial intelligence and machine learning capabilities in order to identify and understand patterns in warranty claims. Additionally, software solutions such as end-to-end warranty lifecycle management can help OEMs reduce costs in warranty management, increase supplier recovery, and improve aftermarket sales support. Warranty management solutions can also be used to handle increased volumes in claims processing easily. Through machine learning and image recognition, the system can be trained to recognize parts and models automatically, or even detect fraud claims, saving manufacturers a tremendous amount of time and money. Shifting Gears to Stay Ahead The transition to smarter electric vehicles and the potential phasing out of combustion engines is likely to be a game-changer for many. Automotive manufacturers and suppliers are making key investment and technology decisions about the next generation of vehicle and components manufacturing, already. Forward-thinking OEMs will need to tackle their challenges by using technology solutions to enable transparent cooperation with partners to offer sourcing, supply, and maintenance benefits and future proof their business. SOURCES: The future of cars is electric – but how soon is this future? The Auto Industry and EVs: Where We Are and What’s Coming Next, After Years of Crying Wolf? Plugging Into The Future: The Electric Vehicle Market Outlook