How OEMs respond to high-tech talent shortage?

In the context of emerging technologies, competition among high-tech companies is increasingly fierce, both to be first to market with innovative solutions and to find the talent to design and develop those solutions.

According to a recent report from Gartner “Technology executives think that talent shortage is the biggest barrier to the adoption of 64% of new technologies.

Causes behind the tech workers crisis

The Covid-19 pandemic sparked an unprecedented wave of technology adoption. The move toward remote working across all industries, and the acceleration of recruitment by companies not only in their region but around the world have intensified the shortage of tech talent, particularly for sourcing the skills that power cloud and edge, automation and continuous delivery.

It becomes more and more challenging for companies like OEMs to have in-house staff with all the necessary technical skills. More complex services are increasingly being outsourced as OEMs gain confidence in the capabilities of their Engineering Services Outsourcing (ESO) providers. Advances in sensor technology, distributed computing, wireless communications, and big-data capabilities have enabled the Internet of Things (IoT) to rapidly transform the technology topography. OEMs across a variety of industries have quickly begun to leverage these technical capabilities and outsource complex tasks such as driver assistance, connected homes, remote and continuous health monitoring, engineering information management and more.

The “new investment cycle”

The COVID-19 pandemic has accelerated companies' efforts to digitize their operations to meet the "new normal" of hybrid and flexible work arrangements.

This situation has led organizations to initially create a significant need for IT infrastructure that can support a fully virtual workforce, and then to increase their investments in emerging technologies in 2021 to drive innovation.

Companies know that they need to make customer experience a priority in 2022, starting with investing in the right technology stack and empowering their teams to create the products of the future.

Developments in emerging technology and improving critical IT infrastructure are top priorities

To enable the smooth flow of information between physical and virtual sites, OEMs are prioritizing and investing in building a solid and secure hybrid cloud base, supported by multi-cloud technologies. It is difficult for a company to have in-house staff with all the necessary technical skills. They must therefore find strong partners in order to stay competitive.

Tech talent crisis is definitely leading to increased outsourcing needs

Most of the changes caused by the pandemic will not fade with the decline in infection rates, which means that companies will need to continue to invest in technology and modernized work practices to survive.

Is Nearshore Software Development  the ideal solution?

Nearshore software development involves working with partners who will help you increase your overall development and get you to market faster, providing added value and allowing you to benefit from the latest technologies.

Whether you require access to talent with specific skills to accelerate development, or to strengthen your internal team for a special project, engineering outsourcing may be the ideal solution.

At Orthogone, we have built a product and solution development group composed of resources specialized in complex challenges. Our unique business model addresses these issues. We are responding to a critical problem of staff shortages, but more importantly we are increasing the level of innovation and functionality of our customers' products.

Learn more about the benefits of partnering with a leading software development company.

What is engineering outsourcing for high-tech product development?

As products and technology become more complex, the expertise needed to update and develop new versions increases. It’s difficult, if not impossible, for a company to have in-house staff with all the technical skills needed.

A Harvard Business Review article says, “The days are long gone when a single vertically-integrated manufacturer like Ford or General Motors could design and manufacture all or most of the subassemblies and components it needs to make a finished product. Technology is just too complicated, and it is impossible to possess all the skills that are necessary in just one place.”

More and more companies are choosing to keep their in-house staff focused on their primary business, so they engage an outsourced engineering team to provide technical expertise. According to a report from Grand View Research, “The global engineering services outsourcing market… is expected to expand at a compound annual growth rate (CAGR) of 22.9% from 2021 to 2028. The increasing collaboration between Engineering Service Providers (ESPs) and Original Equipment Manufacturers (OEMs) is expected to emerge as one of the primary factors contributing to the growth in the adoption of engineering services outsourcing (ESO).”

The need for specialized skills often drives OEMs to partner with our team at Orthogone. For example, a medical device manufacturer with industry-leading image detection needed FPGA expertise to take their products to the next level. They partnered with our team to develop the latest version of their product.

Read the case study about our FPGA design for a highly programmable image processing engine.

In addition to needing specialized skills, companies also need to get their products to market quickly. They can’t wait for a time-consuming talent recruitment process and ramp-up delay for new hires.  Companies that are developing industry-leading innovations work with us to speed development time. For example, we partnered with an optical detection and ranging technology company to design the electronics for an automotive LiDAR solution. Through the partnership, we met an extremely tight schedule to meet a product introduction deadline.

Learn more about our solid-state 3D LiDAR with 180 field of view project.

Crucial differences between outsourced engineering services and other outsourced services

Many companies have taken advantage of the cost savings associated with using an offshore team for services such as IT. However, the IT outsourcing business model doesn’t exactly translate to engineering outsourcing. Working with an engineering firm or engineering team can be done on a project basis. This arrangement allows companies to scale up their teams as needed to meet peak requirements.

Also, the focus on cost savings as the primary factor in deciding to outsource and selecting a partner has shifted. Finding people that have the necessary technical skills along with essential communication and project management skills can make all the difference in the success of a project. Engineering services are extremely specialized. Building a team that has knowledge and experience takes years and requires investing in continuous education. Innovative product development demands creative thinking in an environment that supports collaboration and nurtures continuous learning. Every team member at Orthogone benefits from the company’s investment in research and development.

Learn more about how strategic partnerships drive innovative software product development.

Meeting your product development needs with 3 flexible engineering outsourcing options

There is no one-size-fits-all model for engineering outsourcing. Every company, team, and project will have its own unique needs. However, there are 3 categories that engineering outsourcing services generally fall into:

1 - Augmenting your in-house staff

With this option, the outsourced team members work side-by-side with your in-house team, either in person at your offices or remotely with frequent meetings. The augmenting model works well for OEMs that have a large engineering team in-house and require specific expertise for a project. By augmenting your in-house team with an engineering services partner, your team members will benefit from knowledge transfer and learn more about the new technology from experienced developers.

Find answers to frequently asked questions in our Custom Engineering Services FAQs

2 – Assigning a portion of product development to the outsourcing team.

With this option, the outsourcing partner typically provides more input into the project management and design of the product, while taking on responsibility to complete a significant portion of development. This model is used by both OEMs and startups. For OEMS, this option can speed development significantly, while leaving their in-house staff available to focus on other priority tasks. For startups that have some staff, but need help with certain portions of product development, this option can be used at any point in the product development life cycle, for example, to show proof of concept or develop a working prototype.

Learn more about increasing the capacity of your technical team.

3 – Opting for turnkey product development.

For some projects, having an outsourcing partner take on the entire project from idea to manufacturing makes the most sense. This can happen for a variety of reasons, such as when a startup has a great idea with a time-sensitive market opportunity, but doesn’t have the bandwidth to take on the project. For OEMs, sometimes a project is outside the boundaries of the company’s normal operations, so it makes more sense to outsource it completely. Another reason for turnkey product development is when the idea presents seemingly impossible engineering challenges that need experienced developers to manage.

Development is still done as a collaborative process, with open communication and input from your company’s experts, but the majority of the development work is done by the outsourcing partner.

Discover answers to frequently asked questions about Turnkey Product Development.

 

How engineering outsourcing pricing works

An experienced outsourcing partner can provide a pricing model that meets your needs. Typical options include time and materials, and fixed price contracts. The suitability of these options will depend on the size and scope of the project.

Sometimes, both models will be used. For example, if you want to use fixed price terms, but don’t have an RFP or specifications, an experienced developer can use the time and materials model to help you to define the requirements and specifications for your project. Then you can use those requirements as the basis for a fixed price contract.

 

What is the best engineering outsourcing option for you?

Whether you need to access people with specific skills, speed development, or scale up your internal team for a special project, engineering outsourcing can be the ideal solution. Our successful work with clients develops into long-term partnerships where we collaborate on multiple projects.

Learn more about the benefits of partnering with a leading software development company.

 

The Role Played by Vehicle Perception Sensing in ADAS Applications

As the automotive industry increasingly moves towards autonomous driving (AD), the role of embedded vision in advanced driver assistance systems (ADAS) is evolving. Original equipment manufacturers (OEMs) need to prepare for the move from assisted to automated systems.That presents technical challenges for engineers in developing ADAS and AD solutions.

 

In this article, we’ll look at how vehicle perception sensors are driving automation.

We'll also consider some of the challenges that lie ahead.

How Sensors and Embedded Systems Enable ADAS

Ongoing advances in sensor technology are integral to the goal of increasing road safety. How? ADAS features are built on data from sensors. They use it to warn drivers of safety risks as well as intervene to prevent accidents. Some vehicles combine ADAS with the infotainment system to provide drivers with a view of their surroundings.

ADAS relies on embedded systems throughout the vehicle. Cameras, radio detection and ranging (RADAR), light detection and ranging (LiDAR), and ultrasonic transducers all have roles in gathering the data. Global Navigation System Satellite (GNSS) and Inertial Measurement Units (IMUs) provide additional inputs. The challenge is to interpret the data in real-time from embedded vision to enable the system to intervene.

To that end, modern ADAS needs higher computing power and memory to process the multiple data streams. New technologies have developed in the past year to advance state-of-the-art vehicle perception. These systems use GPU, FPGA or custom ASIC within the electronic control units (ECUs) to efficiently manipulate computer graphics and image processing and handle large volumes of data in real time.

ECUs are the brain controlling automotive sensor fusion. In what way? The ADAS controller fuses data from the different sensors to make decisions. Information-based systems use different cameras to alert the driver to hazards with blind-spot, lane departure, and collision warnings, while radar and other sensors at different levels help map the environment and take action.

The Evolution of Sensors in ADAS

The Society of Automotive Engineers (SAE) standards document, SAE J3016, is a good reference that defines the levels of driving automation systems for on-road motor vehicles. The levels of driving automation are defined based on the specific role played by each of the three main performance actors: the user (human), the driving automation system, and other vehicle systems and components. Levels 1, 2 and 3 require the presence of a human driver. At these levels, the human driver and the car's automation system are expected to work hand in hand while driving. Levels 4 and 5 refer to true self-driving cars with artificial intelligence (AI) and no human assistance required while driving.

The latest generation of vehicles is moving beyond Level 0-2 autonomy that provides driver support, including warnings and brief assistance like blind spot warning, automatic emergency braking as well as lane centering and adaptive cruise control.

Levels 3-4 advance to automated driving features, which can take control of the vehicle under specific conditions. ECUs use embedded vision to enable vehicles to make safety decisions instantly. How? Input from sensors, maps, and real-time traffic data allows ECUs to anticipate road issues ahead.

With more sensors built into the vehicle, the system can combine historical and real-time data about road conditions. This allows it to not only inform the driver but to act. Deep learning computer vision algorithms are used to train neural network models. These models are trained and refined continually using road scenes and simulators. Real-time inference uses these models in real-time to detect, classify and track objects like bikes and pedestrians in the vehicle's field of view. The system then has enough information about the driver and its surroundings to take control, whether to avoid a hazard or simply provide automatic parking.

As vehicles already benefit from a wide variety of 4G-enabled services for the driver and passengers, driver assistance systems can also be seen as a gateway to fully autonomous driving with the implementation of 5G and real-time connectivity to complement advanced on-board sensors (RADAR, LIDAR, cameras).

There is still work to be done to achieve full autonomy and the implementation of a Level 5 self-driving car. Changes in sensor positioning and integration will be incremental as these technologies advance and costs decrease.

The Challenges of Combining Sensors and Technologies in Vehicle Development

The vehicles we can buy today are becoming smarter and safer and are equipped with the three main types of sensors - cameras, RADAR or LiDAR. With these sensors coupled with a powerful computer system, the vehicle can map, understand, and navigate the environment around it safely. Every sensor has their pros and cons. What are the fundamental differences between these three types of sensors? Let's take a look.

Cameras

Although the cameras detect Red Green Blue (RGB) information and offer extremely high resolution, they lack depth information, speed perception and can be blinded by sunlight. They also require significantly more computing power and must be combined with radar and lidar sensors as a complementary technology to optimize the analysis of all data.

RADAR

Commonly also associated with cameras, RADAR can help reduce the number of video frames needed for the vehicle to detect the hazard and respond. It offers advantages in speed and object detection, as well as perception around objects and the ability to operate in bad weather. But it does not have enough precision to identify whether an object is a pedestrian, car, or another object.

LiDAR

Placed throughout the vehicle, LiDAR complements the cameras and radar to provide 360˚ coverage and the ability to achieve very fine and accurate detection of objects in space. But LiDAR does not have resolution comparable to that of a 2D camera, and has limitations in poor weather conditions. In addition, it does not detect colors or interpret text to identify, for example, traffic lights or signs. Cost is also an issue for the integration of LiDAR solutions to advanced driver assistance systems. The emergence of efficient and innovative solutions recently has paved the way for affordable solutions to bring high resolution 3D imaging to the automotive industry.

Fundamental differences between LIDAR, RADAR and VISION

 

GNSS

Beyond cameras, RADAR, and LiDAR, other systems play an important role that can help address the ADAS safety development challenges. A fully autonomous vehicle must have an accurate localization solution. Ground data, mobile mapping, and accurate real-time positioning are essential. High-precision GNSS technology, provides the accuracy, availability, and reliability, that a vehicle requires to be self-driving.

The combination of technology such as: RADAR, LiDAR and cameras with GNSS solutions are certainly the best way to deliver the positioning performance required by Level 4 and 5 autonomous vehicles.

The Future of Embedded Systems in ADAS.

Most vehicles produced in the world are equipped with some level of driving automation and ADAS is one of the fastest growing segments of automotive electronics. To remain competitive, development teams must have the experience to deliver high-quality solutions with minimal risk, while understanding sensor technologies so that the vehicle can fully respond to its environment and provide an enhanced user experience.

At Orthogone we have the expertise that can help to develop a safe and smart vehicle.

We partner with automotive manufacturers and suppliers to design high-performance systems and we understand the growing challenge around the use of embedded systems in ADAS.

Contact us today to learn how you can partner with Orthogone for your automotive embedded systems project.