State of Industry

The concept of low code was coined way back in the 1990s. During that time, Microsoft Office users were creating simple yet advanced automation using Visual Basic. And by now, most technology leaders have recognized the value of low-code development in this modern era. A 2021 Gartner study has predicted that over 75% of large enterprises will utilize at least four low-code development tools. Undeniably, the adoption of low-code platforms delivers a great business value. But despite this rapid growth, low-code strategies often face significant challenges that discourage many businesses from using low-code development platforms. A low-code development platform is not a silver bullet, and it can be detrimental to the effectiveness of an organization if the challenges are not addressed correctly. Let’s have a look at the most oft-cited challenges and the best ways to address them: This is the most common challenge for developers in low-code platforms. If you are following the path outlined by the platform, everything is smooth and easy. But if you try to bend the platform for your unique business requirements, it is difficult or almost impossible to achieve your goals in a standard development environment. Some platforms might provide limited customization options or access to the underlying code, but it comes with specific customization limits. The best solution to this problem is to choose an extensible platform powered by multiple open technologies like HTML, JavaScript, and Electron/Cordova. The flexible platform allows you to implement customizations with extensible tooling and meet future business requirements. You can also choose to develop a customized software solution and augment the application with required APIs, workflows, and business rules. It is difficult to debug the applications built on low-code platforms as the logging of the platform is not mature enough. Usually, these types of platforms overlook the effort to keep the design simple with drag-and-drop features and minimal configurations. When the coding and user interface are not simplified, it gets challenging to debug the front-end and back-end of the application. The best way to address this problem is to choose a low-code platform that provides testing and visual debugging capabilities. Another solution is to run the program locally using the popular debugger application. The database logging capabilities of debugger applications allow you to debug the front-end and back-end performance efficiently. While many enterprise applications could run in isolation, in today’s connected world, most of the applications must integrate with different systems. Growingly, the low-code platforms are also promising to enable you to build the required parts of APIs and integrate them into the application. However, there is a high complexity of managing APIs when you need to integrate with dozens of systems. Today, even the basic business functions like billing, accounting, and payments are routed through APIs, integrations have become a necessity. The most feasible solution to this problem is to choose a platform that allows you to use drag and drop connectors and logic constructs to create custom flows of integration and perform workflow automation. Another solution is to choose reusable integration templates that can help you speed up the integration process without any hassles. Low-code platforms are positioned as easy-to-use, agile, and efficient but this is mostly riddled with the increased user training requirements. The steep learning curve of low-code platforms may outweigh the benefits because it adds heavily to the business cost. The teams have to spend time learning the platform, keep themselves updated about the new features and versions, and a lot more. The best solution to this problem is to choose a platform with a familiar user interface and features. For example, it will take less time to learn the JavaScript framework as compared to an entirely new ecosystem. When the familiar framework is combined with powerful customization features, it can drastically reduce the learning curve of the platform. When building different features of the application, low-code platforms offer multiple components and templates that can be configured to meet specific business requirements. Even if the low-code platforms are equipped with fancy features, a drag-and-drop interface, and many out-of-the-box functions, they cannot accommodate a sudden rise in users or business expansion requirements. While seasoned developers spend years developing expertise to create scalability in the application, it is not possible to expect the same level of scalability in low-code platforms. It is recommended to ensure that the internal processes and architectural needs of the platform are aligned towards scalability. Also, the use of microservices architectural models is preferred over multiple architectural designs to reduce the time spent on managing the large application systems. Low-code platforms do not compromise the security of the data. Developers need to decide about various access controls, permissions, and configurations to ensure data security. But low-code platforms lack the process of data management as there are only a few platforms that offer precise controls like login scrutiny, time-based access, viewing, altering, and sharing the information. In addition, the business logic errors in the low-code platform can lead to data leakage. With an ever-increasing number of users on the The best way to ensure data security is to put restrictions on the utilization of data or a specific type of information being shared. It is recommended to choose a low-code platform that comes with fine-grained controls and a strong content access mechanism. Final words Although low-code platforms are not likely to replace software development, they will become more important across varied industries due to increased agility in the business environment. Today, digital transformation relies on agile software development and continuous improvement. In this case, low-code platforms provide that agility and empowerment to non-technical stakeholders aka Citizen Developers. It is useful to know the likely challenges with low-code platforms so that you can devise strategy to proactively manage those.

Digital transformation has the potential to transform an enterprise, provided it is strategically planned, aligned with business goals, and informed by a sound understanding of the market. COVID’s profound impact since Q1 2020 has fueled the rate of this transformation, as has been elucidated and affirmed via surveys by Statista, McKinsey, and IBM.  Naturally, such transformation has been welcomed by many organizations by setting a new digital agenda. To support this agenda, they are implementing cutting-edge technologies, such as AI, ML, NLP, RPA, and Big Data. Clearly, digital transformation is here to stay. But what about mobile-led digital transformation? Will more companies adopt this approach in the coming years? And will 2022 be the year when it really takes off? What is Mobile-first Digital Transformation? Just like digital-first digital transformation focuses on customer journeys, needs, and demands, mobile-first digital transformation is also about paying more attention to customers and creating better experiences for them via the mobile channel. Moreover, mobile-first means that organizations don’t see mobile as an “additional” or “peripheral” channel in their channel ecosystem. In fact, it’s a common myth that “mobile-first” equates to “mobile-only.” Nothing could be further from the truth. Rather, mobile-first means that companies exploit all available mobile technologies. Further, they consider mobile a strategic focus area that can enhance their digital presence, unlock new levels of innovation, and meet customers’ evolving demands and expectations. Why Mobile-first Matters In 2021, digital transformation is the #1 budget priority for 77% of Fortune 500 CIOs. In late 2020, 90% of companies also believed that if they don’t complete their digital transformation initiatives in the next 12 months, their revenues will be impacted. From these facts, it’s clear that organizations see the long-term value of digital transformation. And yet, not all of them are thinking about “mobile-first” digital transformation.  According to one survey, over 80% of the global population has access to a smart mobile device. That’s over 6 billion people –and potential customers – who use smartphones. In another survey, 86% of respondents said that they want access to multiple channels when talking to a brand.  In other words, most consumers are no longer happy with legacy call centers or email-based customer support. They also want companies to provide service via mobile SMS, social media, and messenger apps. One study even found that 68% of consumers had a positive experience interacting with chatbots, indicating their openness to this mobile-based channel as well. For all these reasons, companies should not only think about digital transformation but also about mobile-first digital transformation. By adopting this approach, organizations can: Mobile-first Digital Transformation Takes Off After COVID In 2018, 79% of consumers made a purchase through their mobile phones. Of course, this was the pre-COVID era. In the post-COVID age, mobile shopping has truly come into its own, with 75% of customers making purchases through mobile devices. That’s why organizations worldwide now use mobile channels to: Moreover, over a billion people already use their mobile phones for banking. By the end of 2021, mobile commerce sales will reach $3.56 trillion, while in 2023, the mobile wallet market will hit $3.5 trillion. Another U.S. study found that the pandemic has transformed cell phone usage, with 37% of respondents saying they’re texting more, while 23% are using shopping apps more.  These trends show that mobile is one of the most powerful channels for consumer-facing brands. That’s why a mobile-first digital transformation strategy should be on the radar of all such brands. Mobile-first Digital Transformation in 2022 and Beyond In 2022, more companies will shift their focus to mobile. They will redesign their digital strategies with a mobile-first approach by defining the type of mobile experiences they want to deliver. To support this strategy, they will create separate marketing budgets and increase their investments in mobile technologies. With mobile-first digital transformation, they will leverage mobile as the catalyst for all new products, applications, and services. Moreover, these applications and brand offerings will be customer-centric, hyper-personalized, and optimized for the relevant audience. The apps will also be highly responsive, feature fluid design, and offer tailored content. Customer satisfaction and personalized user experience will be the keystones of this strategy. In the long term, adopting such an approach will enable organizations to deliver enhanced customer experiences that will directly impact their economic gains, competitiveness, and brand value. That said, mobile-first digital transformation goes beyond just the channel or product. It also requires adopting a new mindset. It’s a fast-paced, iterative, low-friction workflow that enables experimentation and risk-taking. And it requires a mobile-first mindset. To achieve success in the post-COVID era, companies must approach mobile-first digital transformation with the right mindset, structure, and systems. Conclusion Organizations that adopt mobile-first digital transformation will be better prepared for the new challenges the future will bring. The strategy could open up a world of innovation and opportunities, which will enable them to deliver differentiated solutions that enhance customer experiences and provide an all-important competitive edge. Simply put, organizations that focus on mobile-first digital transformation will not only survive in the new world – but also thrive.

Imagine a car in a remote area. Due to poor lighting, the car collides and meets with an accident. Earlier, it took time for the police to identify the accident and send the rescue team to save the driver. However, things have changed now. In 2018, the EU legislation made it mandatory that all cars must have an in-built technology to alert the police officials in case of an accident. The GPS data helps the police to detect the car’s location and reach there quickly. Imagine a car in a remote area. Due to poor lighting, the car collides and meets with an accident. Earlier, it took time for the police to identify the accident and send the rescue team to save the driver. However, things have changed now. In 2018, the EU legislation made it mandatory that all cars must have an in-built technology to alert the police officials in case of an accident. The GPS data helps the police to detect the car’s location and reach there quickly. Similarly, the driver can use a smartphone app to start the engine and make the windows frost-free before getting into the car. From entertainment to driver’s safety and comfort, connected cars have re-imagined transportation. These cars are connected to the internet through wireless LAN. It allows the car to share data with devices inside and outside the car. This helps in vehicle management and ensures driver safety. Technologies such as data analytics and artificial intelligence (AI) make these cars smart. Let’s look at the role these technologies play. Role of AI And Analytics in Connected Cars Preventive Maintenance Like other cars, connected cars are also susceptible to wear and tear. However, the difference here is that it’s easy to detect the issues in advance and take preventive measures to fix them. Companies can leverage AI to monitor the vehicle’s lifecycle in real-time and alert the driver to fix it. Analytics can be used to accurately predict when the vehicle requires maintenance to avoid unexpected breakdowns. AI and analytics are also useful in car manufacturing. Companies can detect the defects in car parts at an early stage before they are even installed and ensure vehicle and driver’s safety. Accident Prevention A driver has to witness multiple hindrances on the road – from pedestrians, objects, bicycles, etc. while driving. There are other potential dangers too, such as foggy weather, snow, potholes, etc. Navigating such an unpredictable external environment can be cumbersome for drivers. Analytics collects data from a car’s sensors. It uses it to train AI to predict human behavior and other road challenges to ensure that it alerts the drivers on time to avoid object collisions and accidents. Nissan, for instance, uses sensors to alert the drivers and automatically lock the seat belts to prevent collisions. As the sensors collect more data, AI will be more effective in preventing accidents and ensuring driver safety. Improving driver’s experience Today’s customers want personalized and safe experiences. From offering infotainment services to informing about safety parameters and sharing the maintenance schedule in advance, car manufacturers like Mercedes, Toyota, and BMW have already started personalizing the driver’s experience. AI and analytics help in personalizing these experiences. It provides insights on different factors such as fuel efficiency, battery life, etc. that could help in improving the driver’s experience. Being data-driven helps car manufacturers to meet customers’ expectations and stay ahead in the competitive curve. Connected cars have in-built sensors, GPS, and cameras that help gather data and improve experiences. Transparency in supply-chain AI and analytics have been particularly useful in improving transparency in supply-chain management. Connected cars use well-integrated software and hardware. Hence, car manufacturers must have full visibility on the supply-chain operations. They need to deal with diverse data sets and also compare different price ranges and the quality of different components involved in building the car. Given the complexity, analytics can be useful to manufacturers. With the help of analytics, manufacturers can identify potential risks in the delivery and fix them to ensure seamless operations. Analytics also helps car manufacturers to understand the customer and market demands, how they interact with the company, and use those insights to predict customer needs better. Leverage OTA updates to improve the experience The ultimate goal of a connected car manufacturer is to identify defects on time and produce good-quality cars that meet the customer’s expectations. Considering that connected cars use embedded systems, the software requires continuous updates to deliver a good experience to customers. Whenever an over-the-air software or firmware upgrade happens, analytics can track its performance in real-time and improve it based on the data collected. Eventually, all this helps to improve the overall experience of the driver. Conclusion Connected cars have become a game-changer in the automotive industry. By 2025, over 14 million semi-autonomous vehicles will be seen on US roads. However, to build such cars, automotive companies must invest in embedded product design and development. This will ensure that the hardware and software used in the vehicles work cohesively to provide a seamless experience to drivers. To build such intelligent and complex systems, companies need resources with specialized skillsets. At Intellore, we have a team of engineers, designers, and developers who possess the skills to build connected systems for connected cars. We understand the complexities involved in the connected vehicle space and thus, combine our software and hardware expertise to build connected cars for tomorrow.

More than 95% of the vehicles would feature connectivity (ethernet, cybersecurity, real-time updates) by the end of 2030. More than 50% of such vehicles would be entirely electric, and more than 60% of the customers would prefer switching OEMs based on the feature-laden autonomy being facilitated.  The likelihood of such a tremendous shift reminds us of the time when wireless consumer electronics became the norm and gave wired devices a run for their money or the time when eCommerce snatched away the liberty of brick-and-mortar stores. But even these cannot come close to the influence that connected vehicle Industry 4.0 will have on the way we go about manufacturing, distribution, and maintenance of automobiles.  In fact, the shift is already happening with the human-machine interface (HMI) becoming the new front end and vehicle control moving to the cloud-based solutions. Considering the relatively acute market differentiation possibilities but equally vaster opportunities to thrive, how can Original Equipment Manufacturers (OEM) prepare for a data-driven era of connected vehicles? Let’s find out.  Software-first Ideology Software, as opposed to the standard design-first philosophy, will embark on its journey as the pivotal market differentiator, and rightly so. The intricate connectivity powered by IoT devices and facilitated by high-grade ethernet will make it essential for the OEMs to manufacture enhanced powertrains capable of striking a balance between the go-to driving philosophy and the changing market.  On the microscopic scale, the OEMs will have to adhere to the following: Burkacky et al., from McKinsey Center for Future Mobility, state that a vertical technology stack could very well be the answer to “customer-facing functions” and will present opportunities for “developers to focus on differentiation” and OEMs to “rely on best-in-class hardware implementations, such as chips for AD.” Integration-first Approach In 2018, Eric Taub, while writing for New York Times, expressed his concerns over the non-integration of carmakers and software giants. He argued that the in-dash navigation systems are not as adept as those on one’s smartphone. Although Taub’s views didn’t necessarily pertain to the case for connected vehicles, they certainly reflected the conundrum that (is and) could trouble the OEMs soon.  In the past, too, OEMs have had to move from their in-built applications to those from service providers. The integration of Apple CarPlay is one such example that demonstrates the vitality of moving forward with an all-inclusive approach.  Actually, there’s no reason why an OEM wouldn’t. Software product manufacturers and cloud giants like Google, Amazon, Microsoft, and Apple have already made their name for user-centric applications. Why not leverage them for good? In fact, their omnipresence is an opportunity to attract and sustain consumers by facilitating an exceptionally improved user experience. To that end, integration-first is a preparation for the OEMs to establish absolute control over the connected vehicles market.  Future-proofing Philosophy Although the OEMs are aware of the market disruption headed their way, they must remain loyal to their own strategy by being future-proof. In other words, OEMs must focus on incorporating better connectivity standards to be able to secure the cloud tokenization of vehicle control logic. Specifically, the OEMs will have to focus on: From the management perspective, OEMs must: Accelerate the design phase in order to make the product suitable for both legacy and new cars/vehicles similarly.  Enterprise-Consumer Balancing Approach OEMs would be wise to consider their readiness in the face of an enterprise-first approach. It would be easier for the OEMs to take the leap if they are already on the right path.  The enterprises’ concerns are different from those of consumers. For example, while consumers would like more power, businesses would want greater flexibility. While consumers would like predictive maintenance of their vehicles, companies would want to get more done with fewer resources.  Likewise, customers and businesses differ a bit in other aspects such as security, reliability, and governance. The data-driven era of connected vehicles will introduce points of convergence between the consumer and enterprise applications, and OEMs will have to be ready to expedite the same. For example:  The Road Ahead In a future-proof strategy for the connected vehicles market, OEMs will have to be cognizant of digital disruption on a global scale and move away from traditional business models. In their efforts towards that end, the car-makers must look at both the automotive industry and adjacent verticals as opportunities to breed stakeholder solutions and create long-lasting customer relationships.