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In this blog, we recap our webinar, “Bridging ALM and MBSE: Strategies for Seamless Integration” – Click HERE to watch it in its entirety.

Integrate Jama Connect® and Sparx Systems’ Enterprise Architect (EA) using LemonTree.Connect to align business and engineering objectives.

Join our experts Philipp Kalenda, Head of Consulting & Training at LieberLieber and Cary Bryczek, Director of Solution Architecture at Jama Software ® to discover how this powerful collaboration eliminates the gap between requirements engineering, system architecture, design, and product management.

You will gain a thorough understanding of these topics and more:

  • How Jama Connect®’s Live Traceability™ capabilities allow for seamless integration across best-of-breed tools.
  • How leveraging Jama Connect Traceable MBSE™ can act as a starting point for your MBSE efforts.
  • How to create a workflow for deriving systems architecture based on requirements from Jama Connect.
  • How LemonTree.Connect enables standard engineering domain practices for configuration management.
  • How to facilitate streamlined evidence that proves your architecture is satisfying requirements.

Below is a preview of our webinar. Click HERE to watch it in its entirety.

The following is an abbreviated transcript of our webinar.

Bridging ALM and MBSE: Strategies for Seamless Integration

Cary Bryczek: My name is Cary Bryczek. I’m the Director of Aerospace & Defense Solutions here at Jama Software. I’m really looking forward to speaking with you today on this particular topic and looking forward to Philipp’s presentation as well. So to kick things off, we are going to set … I just want to set the stage with some trends across the A&D industry that we’re seeing. I’ll talk about how those trends are creating challenges for chief engineers and describe what’s keeping them up at night. Then I’ll set the stage for Philipp’s presentation by showing you what Jama Connect’s Traceable MBSE™ looks like and how that’s designed to solve some of those challenges, and Philipp’s going to definitely take you on a deeper dive to show you how system models in Jama Connect interoperate.

In the aerospace and defense industry, developing a new system has a complexity that far exceeds commercial product development. For example, the FAA’s program to develop the unmanned aircraft traffic management system involves not just the pilot and his drone but is designed to enable autonomous and semi-autonomous operation of multiple aerial systems, including passenger and cargo delivery in a tightly integrated civil aerospace. The elements in blue that you see are all distinct systems of their own, and the new traffic management system needs to be able to integrate communications and data across all of those systems to provide this new capability.

In the highly constrained environment of outer space, NASA’s Cislunar and the Artemis program, for example, are focusing on the operation and survivability of autonomous systems. To develop a space system, NASA does not do this alone but has many contracts with companies to deliver parts of the system. For example, Blue Origin, they have two programs like the Friction Stir Additive Manufacturing Program and the Metallic Thermal Protection System are two examples of just parts of the system.

RELATED: Buyer’s Guide: Selecting a Requirements Management and Traceability Solution for Aerospace

Bryczek: Canopy Aerospace, they’re developing a low-cost reusable thermal protection system. Roccor AKA Redwire in Erie, Colorado, they’re developing a characterization of high aspect ratio booms for these large apertures and so many more. This ecosystem of partners and contributing to a whole brings its own challenges to the pool when trying to collaborate, share data, and execute common systems engineering processes. Like the NASA’s Cislunar and Artemis initiatives for space exploration, they’re focusing on operation and survivability.

In the defense domain, we’re seeing all sorts of cases in unmanned aerial systems as well to aid tactical situations and help with strategic planning. The underlying theme of these large systems is the integration and the collaborative approaches to developing these different weapon systems and aerospace systems in very constrained environments.

So from a strategy perspective, what are these agencies trying to really do? Government agencies and aerospace and defense companies are always evolving their strategies to be able to deal with this complexity and to help streamline their engineering processes. For example, the Department of Defense (DOD) has published a new adaptive acquisition framework. This pathway is intended for large-scale traditional hardware acquisitions to facilitate rapid and iterative development and delivery of software capability to the user.

RELATED: Traceable Agile™ – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

Bryczek: In 2018, the Digital Engineering strategy outlines a vision to modernize how the department designs, develops, delivers, and operates, as well as sustains systems securely and safely. Their vision is to connect people, processes, data, and capabilities across an end-to-end digital enterprise. The International Council on Systems Engineering (INCOSE) published its recent Vision 2035 document, and it is intended to inspire and guide the strategic direction of systems engineering, the practice of systems engineering for the global systems community.

MOSA, the Modular Open Systems Approach, it uses a system architecture that allows major subsystem components at the appropriate level to be incrementally added, removed, and replaced throughout the lifecycle of the major system. The DOD’s systems engineering and architecture group is focusing on modernizing the systems engineering practice. They’re leveraging capabilities from CERC. They’re using MOSA to build systems that can be upgraded and to incorporate new technology faster to respond to emerging threats.

When we look at this in a little bit larger view with this new modernization of the systems engineering approach, the DOD has moved away from visualizing its process using a V model in favor of what truly takes place from a process standpoint, which is that modern systems engineering is highly cyclic. You can see the outermost ring is as close to that old V model, where a concept definition is in the upper right, it moves the system definition through architecture and design and over to V & V and back-to-start around on the next cycle.

What’s important is that there’s a strong emphasis on measuring not just the system being built, but the process that’s building the system, your system’s engineering process and that data and models are at the heart of it all. To the fullest extent, models should be used in favor of documents and data should inform decision-making.

What is the industry saying? There’s a challenge to using data-driven approaches and models. The DOD has highlighted there’s a lack of an integrated approach to the implementation of these systems engineering focus areas, and it’s creating a delay in the full implementation of the digital transformation, which is necessary to ensure relevant guidance and skills.

RELATED: Leading Ground-to-Air Communications Systems Developer Indra Park Air Takes Off with Jama Connect®

Bryczek: Continuing to use legacy tools and approaches is what is making integrated approaches not possible. What is necessary is to take a federated approach to data across the tool ecosystem and to use tools with more robust APIs, and modern architectures that are standards-based. An MBSE approach requires an integrated approach to connect the system models, architecture, and requirements to the program teams the software teams, and the hardware teams. It doesn’t mean to use a siloed system modeling tool and expect those teams to be able to consume and understand that model.

What we hear quite often is, “How do I achieve the benefits of MBSE when no other engineers can access model parameters that they need for downstream decision-making?” Those with technical oversight, chief engineers who have technical oversight and responsibility for program success, executing MBSE, or even just traditional systems engineering commonly raise the following questions, “How do I know if the architecture and system requirements are satisfying all the needs? How do I know if a change in the architecture will impact testing? How do I know if a change in the architecture will impact downstream hardware or software teams? How do I detect unallocated systems architecture and requirements?”

So the question of, “How do I achieve the benefits of MBSE when no other engineers can access model parameters?” can be answered by using traceable MBSE. Now, the reality at most companies is that the end-to-end systems development process is fragmented into domain-specific tools and spreadsheets that have no built-in collaboration. Now, this leads to fragmented requirements traceability and requires significant manual effort through emails and meetings and sometimes luck to try and prevent delays rework, or cost overruns.

Most companies have come to accept the situation as an unchangeable reality given the lack of a single platform to enable this entire process, nor a method to integrate spreadsheets and desktop tools. Using Traceable MBSE, the system model in the modeling tool is joined with the Jama Connect model. Jama Connect is continually calculating traceability and coverage and provides scores that can be used to identify high-risk areas that can be drilled into to determine corrective actions. The system model can detect those changes and the modeling engineers can take the corrective actions.

Bridging ALM and MBSE: Strategies for Seamless Integration

Jama Software is always looking for news that will benefit and inform our industry partners. As such, we’ve curated a series of customer and industry spotlight articles that we found insightful. In this blog post, we share an article, sourced from PBC Today, titled “Integrating AI in AEC/O to Enhance Efficiency.” – originally published on June 4, 2024.

Integrating AI in AEC/O to Enhance Efficiency

AI’s use in the AEC/O industry has the potential to increase sustainability, efficiency, and decision-making, says Nemetschek Group.

From ChatGPT to the realm of robotics, AI appears to be everywhere.

In the time-honored tradition that follows the introduction of any new major technological leap – from the printing press back in the 15th century, right up to the democratization of the internet – conversations on the topic swing from the benefits AI will deliver to concerns over the risks that it poses.

As we have also seen in the past, once the dust has settled, AI will find its niche, whether it’s noticeable at the front end or hidden away at the back end of the services and technologies that we use in the future.

There’s no doubt that bad actors will use AI to their advantage, but events like the AI Safety Summit hosted in the UK last November will unite governments and the technology industry in a joint mission to create guardrails to ensure that, where possible, AI is used to benefit society, rather than compromise it.

Opportunities for AI in the AEC/O industry

Even at this early stage of AI’s evolution, there’s no doubt that the AEC/O industry should be excited about the opportunities that AI presents.

The technology has a role to play in helping the industry cut its carbon emissions and raw material waste through the implement of better ways of designing and constructing buildings.

The good news is that AI – tailored for the construction sector – already exists, although its usage remains somewhat discreet.

While it is less tangible and visible than in architecture or interior design, AI nonetheless represents a significant innovation for the construction industry; and, as the technology evolves and finds more applications where it can add value to our profession, it will become an invaluable part of our essential toolkit.

It is important that we are receptive to AI, despite any initial reservations or concerns we may have. Solutions supplemented with AI will emerge as formidable allies in addressing the crucial challenges the industry faces.

They will be essential in redefining our standards of efficiency, especially in meeting the challenges of ecological transition, precision, and profitability throughout project lifecycles.

Those are all commendable ambitions, and AI can help the industry meet them.

RELATED: Buyer’s Guide: Selecting a Requirements Management and Traceability Solution

Planning and design: Navigating fluidly through complex data to facilitate decision-making while boosting productivity

Although the industry is still in the midst of a digital transition, data already plays an essential role. In fact, data processing – automated through AI-integrated tools – can revolutionize the planning and design phases of construction projects.

Aggregating information from multiple sources and stakeholders (architects, urban planners, project managers, etc) – which is always complex and prone to error or confusion – becomes smoother when supplemented with AI.

Furthermore, the digital model derived from Building Information Modelling (BIM) becomes more precise and detailed, reducing reliance on numerous – and sometimes very specific – third-party solutions.

AI also intervenes to provide more accuracy by analyzing data history heterogeneously and in real-time, thus avoiding manual inaccuracies. As a result, AI ensures the integrity of initial design models while establishing a mechanism for continuous improvement.

Such an approach significantly reduces the costly and time-consuming risks associated with human error.

Another major asset for the sector is the contextual analysis that AI can provide professionals. It leads to the overall design of a building, considering environmental factors such as local climate models. Those insights guide professionals in making proactive decisions when anticipating future challenges.

Construction and renovation: Enhancing quality and tackling logistics

AI facilitates real-time monitoring of construction progress by measuring it against the planned schedule. This approach immediately identifies programming issues or potential delays, enabling offsite managers to make informed decisions to meet deadlines.

During renovation and modernization processes, AI offers intelligent simulations, reducing the time and costs associated with these projects, even for older buildings.

While traditional buildings may lack complete historical data, AI has the capability to leverage 3D scanning and panoramic technologies to create new BIM models. This digitization process modernizes older structures to align with current design and sustainability standards.

RELATED: Traceable Agile™ – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

Operations: Advancing data-driven management and sustainable practices through AI

AI will become an essential complement to the digital twin. It can already predict maintenance needs and automate malfunction detection through IoT sensors. This enables remote inspections and lifecycle analyses, increasing a building’s efficiency while reducing operating costs.

Perhaps more importantly, AI’s use in digital twins is pertinent in an era where sustainability is paramount, as AI algorithms can analyze real-time data from IoT sensors to identify inefficiencies in energy use.

It can also facilitate the smart search of structured and unstructured data. Therefore, AI-enhanced digital twins can also optimize other operational aspects – like space utilization and occupant comfort – by analyzing patterns and environmental variables to create an optimal work environment.

In this context, AI transforms the renovation and retrofitting process by enabling intelligent simulations that generate multiple design possibilities in seconds.

Whether the objective is sustainability or optimized lighting, AI-based models can visualize various scenarios, reducing both the time and cost associated with these projects.

The rapid advancements in AI are undeniably catalyzing a transformative shift across the AEC/O industry.

When used in conjunction with digital twins, AI is a powerful tool that enhances capabilities across planning, design, construction, and operations.

By way of practical example, a user can take a photo of a part of a building or an asset and search across the whole dataset for information relevant to the area they are interested in.

Building the future with AI

AI has quickly become a powerful tool for enhancing planning, design, construction, and operation capabilities.

It becomes the cornerstone of intelligent data-driven decision-making, which is essential for an industry aiming for innovation, sustainability, and operational excellence.

With so much focus on the environment – from governments, corporations, and consumers alike – and the AEC/O industry under immense pressure to address the damage it does to the environment, it’s imperative that it embraces technology like AI to become an even more responsible corporate citizen.

Understanding IATF 16949: A Quick Guide to Automotive Quality Management

In the ever-evolving landscape of the automotive industry, ensuring product quality and safety is paramount. One key standard that plays a crucial role in this pursuit is IATF 16949. In this article, we will delve into the intricacies of IATF 16949, exploring its significance, key elements, and benefits.

What is IATF 16949? IATF 16949, or the International Automotive Task Force 16949, is a globally recognized quality management standard specifically designed for the automotive sector. This standard is based on ISO 9001 and incorporates additional requirements tailored to the automotive industry. IATF 16949 was developed by the International Automotive Task Force (IATF) to promote quality, consistency, and continual improvement throughout the automotive supply chain.

This image portrays some of the automotive elements involved in the IATF 16949 regulation.

Key Elements of IATF 16949:

  • Customer Focus: IATF 16949 places a strong emphasis on meeting and exceeding customer requirements. This includes understanding customer needs, providing defect-free products, and consistently delivering high-quality services.
  • Process Approach: The standard adopts a process-oriented approach to quality management. Organizations are encouraged to identify, manage, and optimize key processes to enhance efficiency and effectiveness in meeting objectives.
  • Risk Management: IATF 16949 requires organizations to identify and address potential risks within their processes. This proactive approach helps in preventing issues, ensuring product safety, and maintaining a robust quality management system.
  • Supplier Quality Management: Recognizing the interconnected nature of the automotive supply chain, IATF 16949 places a significant focus on supplier quality management. Companies must work closely with their suppliers to ensure that quality standards are consistently met throughout the supply chain.
  • Continuous Improvement: The standard promotes a culture of continual improvement, urging organizations to regularly assess and enhance their processes. This commitment to ongoing refinement helps companies stay ahead in a competitive market.

Benefits of Implementing IATF 16949:

  • Global Recognition: Achieving IATF 16949 certification provides organizations with global recognition, enhancing their credibility and opening doors to new business opportunities.
  • Improved Efficiency: By adopting the standard’s process-oriented approach, organizations can streamline their operations, reduce waste, and enhance overall efficiency.
  • Enhanced Customer Satisfaction: Meeting IATF 16949 requirements ensures that products and services consistently meet or exceed customer expectations, leading to higher satisfaction levels.
  • Risk Mitigation: The focus on risk management helps organizations identify potential issues before they escalate, reducing the likelihood of defects and recalls.
  • Competitive Advantage: IATF 16949 certification provides a competitive edge in the automotive industry. Many OEMs (Original Equipment Manufacturers) prefer working with suppliers who adhere to this globally recognized standard – and many companies are required to comply.

RELATED: Buyer’s Guide: Selecting a Requirements Management and Traceability Solution for Automotive

Who is required to comply with IATF 16949?

Companies that are part of the automotive supply chain, including manufacturers, suppliers, and service providers, may be required to comply with IATF 16949. This includes organizations involved in the production of automotive parts, components, and assemblies.

Key stakeholders in the automotive industry, such as original equipment manufacturers (OEMs) and their suppliers, often seek IATF 16949 certification to demonstrate their commitment to quality and compliance with industry standards. Certification to this standard is often a prerequisite for becoming a supplier to major automotive companies.

It’s important for organizations in the automotive sector to assess their specific contractual requirements and the expectations of their customers to determine whether compliance with IATF 16949 is necessary for their business. Certification to IATF 16949 is typically achieved through a third-party audit process conducted by accredited certification bodies.

What is a Quality Management System?

A Quality Management System (QMS) is a comprehensive framework of policies, processes, procedures, and records that an organization establishes and maintains to ensure its products or services consistently meet or exceed customer expectations. The primary goal of a QMS is to enhance customer satisfaction by consistently delivering high-quality products or services while also meeting regulatory requirements. It encompasses various elements such as quality planning, control, assurance, and improvement. A well-implemented QMS helps organizations identify and document their processes, set quality objectives, and monitor performance against these objectives. It often involves the use of standardized methodologies, documentation, and quality tools to foster a systematic approach to quality management, ensuring that every stage of the product or service lifecycle is controlled, measured, and continually improved upon. Certification to internationally recognized QMS standards, such as IATF 16946 and ISO 9001, provides external validation of an organization’s commitment to quality and can enhance its credibility in the marketplace.

RELATED: Traceable Agile™ – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

How can Jama Connect® help?

Jama Connect® is a powerful tool that plays a pivotal role in assisting teams in meeting the requirements of a QMS within various industries, particularly those with stringent regulatory standards.

Here are several ways in which Jama Connect facilitates compliance with QMS requirements:

  • Documenting and Managing Requirements: Jama Connect provides a centralized platform for documenting and managing requirements throughout the product development lifecycle. It allows teams to create, review, and collaborate on requirements, ensuring clarity and consistency. This centralized approach enhances communication among team members, reducing the risk of misunderstandings and improving overall requirement management efficiency.
  • Enabling Risk-Based Thinking: The platform supports risk-based thinking by providing tools to identify, assess, and mitigate risks associated with product development. Teams can systematically evaluate potential risks, assign risk levels, and implement mitigation strategies. This proactive approach aligns with the risk management requirements of QMS standards, contributing to safer and more reliable product development.
  • Assisting with Change Management Processes: Change management is a critical aspect of QMS, and Jama Connect streamlines this process. Teams can efficiently capture and evaluate proposed changes, assess their impact on requirements and other project elements, and implement changes in a controlled manner. This ensures that changes are documented, reviewed, and tracked, promoting transparency and accountability in the change management process.
  • Enabling Traceability of Processes and Products: Jama Connect offers robust traceability features, allowing teams to establish and visualize relationships between requirements, tests, and other project artifacts. This traceability is crucial for demonstrating compliance with QMS standards, as it provides a clear linkage between various stages of the development process, from initial requirements to final product validation.
  • Easy Documentation for Evidence for Audits: Jama Connect simplifies the documentation process required for audits. The platform enables teams to generate comprehensive reports, traceability matrices, and documentation trails that serve as evidence of compliance with QMS standards. This facilitates smoother and more successful audits, as auditors can easily review and verify the necessary documentation.
  • Supporting a Continuous Improvement Process: Continuous improvement is a fundamental principle of QMS, and Jama Connect supports this by providing analytics and insights into project performance. Teams can analyze data on requirements, testing, and other project metrics to identify areas for improvement. This data-driven approach fosters a culture of continuous improvement, aligning with the principles of QMS standards.
  • Supporting a Customer Focus with Traceability to Customer Needs: Jama Connect helps maintain a strong customer focus by establishing clear traceability from requirements to customer needs. This ensures that the final product aligns with customer expectations and requirements. The platform’s traceability features provide a visual representation of how each requirement contributes to meeting customer needs, strengthening the customer-centric approach advocated by QMS standards.

IATF 16949 is a critical standard for the automotive industry, emphasizing quality management, risk mitigation, and continuous improvement. Organizations that invest in achieving and maintaining IATF 16949 certification position themselves as reliable partners in a highly competitive and demanding market, ensuring the production of high-quality automotive products.

Note: This article was drafted with the aid of AI. Additional content, edits for accuracy, and industry expertise by Matt Mickle and McKenzie Jonsson.

This image displays the title of this blog, focused on Secure by Design for medical device.

Secure by Design: A Crucial Imperative for Medical Device Teams

In today’s healthcare landscape, technology plays a crucial role in patient care. Medical devices have become essential for monitoring vital signs and administering treatments. However, as these devices become more connected and complex, ensuring their security is now more important than ever. This is where the concept of “Secure by Design” comes in, serving as a fundamental principle for medical device teams to navigate the intricate world of healthcare technology. Which begs the question, with the rise in security concerns, do regulations now need to consider whether each device is safe, effective, and secure?

Understanding the Landscape

Medical devices have advanced beyond being simple, independent systems. With the rise of the Internet of Things (IoT), devices are now interconnected, allowing for the exchange of data. While this connectivity has many advantages, it also opens vulnerabilities that could be exploited by malicious entities.

Cybersecurity threats not only put patient data at risk, but also the health of those who rely on these devices. It’s also a costly and time-consuming process for medical device companies to manage, and resolve. According to IBM Security analysis of research data compiled by Ponemon Institute, 83% of organizations have had more than one security breach, and the average cost of each breach averaged $4.3 million globally. That number more than doubles for the average cost of a security breach in the United States – $9.44 million – the highest in the world.

RELATED: Traceable Agile™ – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

The Essence of Secure by Design

Secure by Design is a proactive approach that prioritizes security in the development process. Rather than treating security as an afterthought, it is integrated into the design and development phases. For medical device teams, this means implementing security measures from the start of a project, considering potential threats and vulnerabilities, and implementing safeguards to reduce risks.

Key Principles of Secure by Design:

  • Risk Assessment: Before beginning development, medical device teams must conduct a thorough risk assessment. This involves identifying potential threats, understanding vulnerabilities, and evaluating the potential impact of security breaches on patients and healthcare providers.
  • Data Encryption: Due to the sensitive nature of healthcare data, encryption is a crucial aspect of secure design. Implementing strong encryption protocols ensures that patient information remains confidential and secure during transmission and storage.
  • Access Control: Limiting access to medical devices is crucial. Secure by Design stresses the importance of implementing strict access controls, ensuring that only authorized personnel can interact with the device. This prevents unauthorized users from tampering with critical settings or accessing sensitive patient data.
  • Regular Software Updates: Vulnerabilities in software can leave devices vulnerable to cyber threats. It is essential for medical device teams to prioritize regular software updates and patches to address potential security risks. This ensures that devices can withstand evolving cyber threats.
  • User Education: Even the most secure devices can be compromised if users are not vigilant. Secure by Design also includes educating end-users on cybersecurity best practices. This ensures that individuals using medical devices are aware of potential risks and take necessary precautions.

Regulatory Landscape and Compliance

The healthcare industry must comply with strict regulations to protect the well-being of patients. Regulatory agencies, such as the Food and Drug Administration (FDA), acknowledge the significance of cybersecurity in medical devices. Following regulatory guidelines is not only a legal obligation, but also a dedication to ensuring the utmost safety and security for patients.

Challenges and Solutions

Implementing Secure by Design in the development of medical devices can be challenging. Balancing the need for innovation with strict security measures is complex. Additionally, the ever-changing landscape of cybersecurity threats requires constant attention.


  • Collaboration and Training: It is crucial to foster collaboration between cybersecurity experts and medical device developers. Ongoing training for the development team ensures they are informed about the latest security threats and mitigation strategies.
  • Third-Party Security Assessment: Engaging third-party security experts to regularly assess medical devices can provide an unbiased perspective on their security. This external validation can uncover blind spots that internal teams may miss.
  • Incident Response Planning: Despite preventative measures, security incidents can still occur. A robust incident response plan allows medical device teams to promptly and effectively address breaches, minimizing their impact on patients and healthcare providers.

RELATED: The Complete Guide to ISO 13485 for Medical Devices

The Future of Medical Device Security

As technology continues to advance, the healthcare industry is constantly evolving. Medical device teams must be proactive in anticipating and addressing potential security challenges to stay ahead of the curve. Secure by Design is not a one-time effort, but an ongoing commitment to the safety and well-being of patients.

It is not just best practice, but a moral imperative for medical device teams to integrate security into the DNA of their development process. By doing so, they contribute to a safer and more resilient healthcare ecosystem. The future of healthcare relies on innovation, connectivity, and security, and it is the responsibility of medical device teams to ensure that these pillars remain strong.

Jama Connect® for Medical Device Development

Jama Connect for Medical Device Development helps medical device teams reduce the effort required to achieve regulatory compliance throughout the development process. With this solution, medical device teams can manage design controls for device requirements and related risks, simplifying regulatory submissions and audit preparations while accelerating time to market. Learn more: Solution Overview: Jama Connect Solution for Medical Device Development

Note: This article was drafted with the aid of AI. Additional content, edits for accuracy, and industry expertise by [Vincent Balgos, McKenzie Jonsson, and Decoteau Wilkerson].

This image portrays an article about manufacturing technology predictions in 2024.

Jama Software is always looking for news that would benefit and inform our industry partners. As such, we’ve curated a series of customer and industry spotlight articles that we found insightful. In this blog post, we share an article, sourced from IndustryWeek, titled “AI, XR and Data: Manufacturing Technology Predictions for 2024” – written by Dennis Scimeca and originally published on January 3, 2024.

AI, XR and Data: Manufacturing Technology Predictions for 2024

If we’re finished with the hype cycle, we’re probably talking about a technology that’s here to stay. So, when IndustryWeek asks manufacturers and analysts for their predictions about manufacturing technology in the coming year, we’re looking for the most mature technologies with the widest adoption rates.

This year’s answers demonstrate the point yet again. Of the dozen technologies we asked about, artificial intelligence (AI), augmented/virtual/mixed reality (XR for short) and the use of data and analytics garnered the most response. Manufacturers next year really should keep their eyes on these three technologies in 2024.

AI’s 2024 Prospects

Artificial intelligence took center stage in 2023 with the arrival of generative AI, specifically ChatGPT and Microsoft’s Bing AI, sparking a slew of marketing campaigns and enthusiastic op-eds about what gen AI would do for manufacturers and the world.

Listening to our audiences (and IndustryWeek’s own analyses) the hype bubble for gen AI burst rather quickly but the topic of AI generally still holds great relevance for the manufacturing world.

“The current market zeitgeist around AI has bled significantly into manufacturing markets, but its deployment will be held back by a staunch lack of trust amongst operators and calls for comprehensive and provable use cases. This is particularly the case for functionality associated with quality management processes and QMS software, due to an entrenched resistance to change and concern around giving up control of processes,” says ABI research industry analyst James Prestwood.

“QMS software vendors are and will continue to take a slower approach to developing AI functionality for solutions, engaging in strong and consistent dialogue with key customers to ensure that the technology is meeting real plant floor challenges. … However, even as solutions are released, adoption will be slow, if in 2024 at all, and will most likely be focused on manufacturer’s lighthouse facilities, rather than being deployed organization wide,” Prestwood adds.

Paul Miller, vice president and principal analyst at Forrester, was a bit more blunt in his assessment.

“Generative AI will not transform the business of manufacturing in 2024,” Miller says. “There are clear opportunities to add ChatGPT-like interfaces in front of complex sets of product documentation and operational data, lending a helping hand to experienced engineers. The human remains in charge, and they must still be responsible for the actions that they take: We’re not yet in a position where these generative AI tools can be relied upon to support inexperienced users in situations where mistakes can be both costly and dangerous.”

RELATED: 2024 Predictions for Product and Engineering Teams

Tim Gaus, smart manufacturing leader and principal at Deloitte, is more optimistic in the long term, but sees few applications right now.

“GenAI holds the potential to create closed-loop manufacturing systems that can automatically make real-time adjustments and self-optimize based on data. This can bring new levels of efficiency to the industry – but as the capabilities of GenAI continue to be explored and mature, organizations will be best served to start testing the technology in areas like maintenance and repair.” .

Of the technology leaders and experts we interviewed, Anu Khare , senior vice president and chief information officer at Oshkosh Corp., sounded the most optimistic about AI’s potential.

“We are entering into the most exciting period of technological evolution since the advent of the Internet. The most impactful and broadest application of technology will be AI (artificial intelligence). Every aspect of business will be infused with and augmented by various AI tools,” Khare says.

According to Khare, predictive insight, task automation, human machine engagement and content generation are the four areas that will most benefit from new AI technology.

“All these technological advances and adoption will create a new relationship between humans and AI, where AI becomes an augmentation tool, just like we use industrial tools in our manufacturing plants,” Khare adds.


XR technology, initially pitched as the next, best thing in gaming instead found its home within the manufacturing world. That’s not to say no one uses VR for entertainment, but we cannot deny the utility of manufacturers blowing up product designs in augmented reality to allow operators to see how their parts fit into the final product, or virtually training operators on dangerous equipment to increase safety or collaborating with colleagues across continents.

Somehow this morphed into discussions of the metaverse, a term borrowed from Neal Stephenson’s 1992 dystopian science fiction novel Snow Crash, but according to our experts XR discussion came down to earth again quickly.

“We see a bit of a resurgence of interest in AR and VR in 2024, as everyone moves away from talking about the industrial metaverse. … . Both AR and VR got caught up in broader hype around the metaverse, and they and other enabling technologies like digital twin and even IoT now risk losing credibility (and project funding) as part of the backlash against that deflating hype bubble. Forrester predicts that over 75% of industrial metaverse projects will rebrand to survive the metaverse winter: project teams will go back to talking about the enabling technologies – and the very real problems they address – and quietly hope that everyone forgets any association with the metaverse,” says Miller.

ABI Research director Eric Abbruzzese expects 2024 will be an important year for the AR/VR/MR market because Apple releases its Vision Pro hardware, the company’s first truly new device in a long time. He there expects an influx of mixed reality content to hit the market next year, both for the Pro and its competitors.

“While mixed reality may have a strong 2024, smart glasses will not. OEMs continue to struggle to create a full smart glasses package that delivers quality of experience alongside acceptable design, form factor, and price. Devices have either been too niche and focused—such as glasses specifically targeting cyclists—or too expensive and bulky for broad use (e.g. Magic Leap),” said Abbruzzese.

“Even if smart glasses from major tech names like Samsung and Meta hit the market in 2024 (which is possible, but releases have traditionally been delayed), these will be first generation smart glass devices mostly targeting developers and early adopters,” he adds.

Dale Tutt, vice president of industry strategy at Siemens Digital Industries Software, adds, “The computing and visualization graphics power that are available makes augmented and virtual reality much more accessible and I think in 2024 there is going to be even greater use of AR/VR.” .

“When I think back to the transition from 2-dimensional drawings on the shop floor to when we started printing 3D pictures with colors to help the technicians install equipment, that had a massive impact and reduced the learning curve. AR/VR provides an even more intuitive environment, so the more that companies can present in virtual and augmented reality, the more effective they are going to make technicians and engineers,” Tutt says.

RELATED: Traceable Agile™ – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

Data and Digitization

Of all the technologies highlighting this year’s predictions, data digitization and analysis represent the most mature of the trio. Plant-wide lattices of IIoT devices can capture information on vibration, temperature, humidity, quality check results, cycle times, just about anything you can register and quantify with a sensor.

Even the simplest IIoT system, that only tracks products passing in front of photoeyes or logs when and why machines go down can have profound results in increasing OEE and productivity. At the other end of the spectrum, dense IIoT meshes feeding rich data into AI algorithms enable prediction, process tracking and simulation. That’s also a much more complicated proposition.

“In 2024, we’ll continue to see industrial data management evolve and become a priority for organizations if it is not already at the top of the list. Most manufacturers continue to cite industrial data as one of the biggest challenges to innovation due to complexity and accessibility issues,” says Gaus.

Miller adds, “Industrial IoT software platforms do important work, connecting to, managing and extracting data from large fleets of connected devices in production environments. But that’s only part of the picture. Manufacturers need analytics to make sense of the data. They need AI and machine learning to build models and predictions based on the data. They need job scheduling systems and work order management systems, tasking field service engineers to repair machines when machine learning models trained on IoT data spot a problem ahead.”

“IoT platforms are very good at managing and extracting insight from connected devices, but it may not make sense continuing to extend IoT software much further beyond that. Instead, we should be working to effectively surface IoT data inside these more comprehensive enterprise systems,” Miller adds.

Sean Spees, CPG market segment leader for Bosch Rexroth, says in 2024, the emphasis will be “data retrieval and remote assistance. How the data is used and finding a partner with expertise in the digital space to evaluate it to help with predictive maintenance and line conditioning to move towards a lights out factory will be critical.”

Jama Software is always looking for news that would benefit and inform our industry partners. As such, we’ve curated a series of customer and industry spotlight articles that we found insightful. In this blog post, we share an article, sourced from Innovation News Network, titled “Expanding EV infrastructure in the US: Both on- and off-road” – originally published on November 20, 2023.

Expanding EV Infrastructure in the US: Both On- and Off-Road

The expansion of electric vehicle infrastructure in the US has been challenged by various issues, from governance to location. Here, we explore the issues and how they can be combated.

The evolution and expansion of electric vehicle (EV) infrastructure, encompassing both on-road charging stations and off-highway electrification, is a burgeoning topic in the United States. This issue has been characterized by significant regional disparities, with varying levels of availability across different parts of the country.

Furthermore, it is marked by distinct challenges that arise in urban versus rural settings as well as on- and off-road contexts. The role of government support and policy direction also comes into play in shaping this landscape.

As interest in electric vehicles continues to surge, understanding the intricacies behind their supporting infrastructure becomes increasingly crucial. Off-highway electric vehicles have their own unique set of requirements when it comes to charging infrastructure, presenting numerous design and manufacturing challenges.

Looking ahead, predicting future trends within this area is challenging due to its rapidly evolving nature but nonetheless vital for planning and strategizing growth trajectories within this realm.

Availability of EV infrastructure in the US

The uneven distribution of electric vehicle charging stations across the United States underscores a significant disparity, with coastal areas generally boasting greater availability than their counterparts in the Midwest and rural regions.

This can be attributed to several factors, including regional disparities in both population density and average income level, which directly influence infrastructure cost and consumer adoption rates of EV technology.

For instance, densely populated urban centers, particularly those along the coasts such as New York City or San Francisco, tend to have higher per capita incomes. These areas are more likely to invest in expensive EV technology and support the infrastructure costs associated with establishing charging stations.

The increased presence of these facilities subsequently encourages more consumers within these regions to adopt electric vehicles due to decreased concerns over charging time.

In contrast, regions characterized by lower population densities or average income levels –such as many Midwestern states and rural areas – are typically less equipped with EV charging infrastructure. This results from a combination of factors: reduced consumer demand for EV technology due to financial constraints; longer distances between destinations that increase concern over charging times; and higher per-unit infrastructure costs arising from the need for more extensive grid enhancements in less developed areas.

As such, despite growing national interest in reducing carbon emissions through transitioning towards electric vehicles, these challenges contribute significantly towards regional disparities in the availability of EV charging stations across America.

Thus, it is imperative that future efforts aimed at expanding this crucial segment of green transportation infrastructure consider these distinctive geographical characteristics and obstacles.

RELATED: Traceable Agile™ – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

The challenges of expanding EV charging infrastructure

Significant stumbling blocks surface when scrutinizing the surge in electric vehicle utilization, particularly pertaining to potential power supply problems, prohibitive price points of charging stations, and a paucity of policies promoting progress. These issues include:

Infrastructure costs

The establishment of an extensive network of charging stations necessitates substantial capital outlay from both public and private sectors. The latter’s involvement is critical since government funding alone may not suffice.

Technological limitations

Current technology restricts rapid mass-charging capabilities, potentially leading to power grid stress during peak demand periods. This limitation necessitates additional investments in technology development and grid reinforcements.

Public awareness

Despite growing interest in electric vehicles, many potential users remain uninformed about their benefits or how to utilize existing EV infrastructure effectively.

Sustainability concerns

While electric vehicles significantly reduce greenhouse gas emissions compared to conventional fuel cars, the production process itself can have a substantial environmental footprint, largely due to battery manufacturing processes.

The availability of EV infrastructure in rural and urban areas

Differences in the accessibility and utilization of EV charging stations between rural and urban areas present a nuanced challenge in promoting wider adoption of this sustainable mode of transportation. Rural EV adoption faces obstacles such as a lack of public charging infrastructure due to less population density and greater travel distances.

Moreover, financial considerations play into these disparities as well; the high cost associated with the installation and maintenance of charging stations may not be justified by the potential low usage in rural settings. This situation leads to EV accessibility being heavily skewed towards urban regions where there is higher demand.

On the other hand, urban planning challenges also arise in expanding EV infrastructure within cities. The densely populated nature of urban environments results in space constraints for installing new charging stations. Available funding also becomes a critical factor – adequate EV infrastructure funding is necessary for both the construction and operation of sufficient charging facilities to meet growing demands.

Additionally, differences between these two types of geographies are reflected not only on human mobility but also have an impact on the environment.

While increased use of electric vehicles can significantly reduce greenhouse gas emissions in densely populated cities, achieving similar outcomes in rural areas can prove much more difficult due to their unique characteristics.

Government support

In light of these challenges, it is noteworthy to mention the initiatives taken by American governmental bodies to bolster the proliferation and accessibility of charging amenities for electric vehicles. The US Government has employed a mixture of methods to support this development:

Federal incentives

At the federal level, several incentives have been introduced over recent years to encourage EV adoption. For instance, the Electric Drive Vehicle Battery and Component Manufacturing Initiative provided $2bn in grants for manufacturing of advanced batteries and electric drive components.

Private partnerships

On top of direct funding, the US government also fosters private partnerships aiming at enhancing electric vehicle infrastructure. An example would be the ‘EV Everywhere Grand Challenge’, launched by the Department of Energy (DOE), which works with national laboratories, universities, private industries, and other governmental agencies to increase availability of high-speed charging stations across country.

Infrastructure financing

Additionally, there are efforts directed at infusing capital into public charging infrastructure through financing programs like the Clean Cities Alternative Fuel Vehicle Deployment Initiatives which allocated millions towards building EV charging stations nationwide.

Technological advancements and environmental impact

Given that environmental impact is a key driver behind the shift towards electric vehicles, governmental policies are expanding physical infrastructure but also investing in research & development for technological advancements that could reduce emissions further while improving EV range and battery life.

Developing off-highway EV charging infrastructure

The development of charging facilities for electric vehicles designed for non-highway use represents a unique and complex challenge, necessitating innovative solutions and strategies. Off-highway adaptations require not only the installation of charging stations in remote or less accessible areas but also the incorporation of infrastructure financing to support their construction and maintenance.

Technological advancements have been pivotal in addressing these challenges, making it feasible to develop energy-efficient charging systems that can withstand harsh environmental conditions while providing reliable service. These advancements range from solar-powered charging stations to smart grid technologies that optimize electricity usage during off-peak hours.

Investing in this type of infrastructure is critical for promoting sustainable solutions within the transportation sector, particularly in industries such as mining, agriculture, and construction where off-road vehicles are prevalent. The integration of renewable energy sources with charging infrastructure offers dual benefits: reducing greenhouse gas emissions associated with traditional fossil fuel-based power generation and extending the reach of EV technology into areas beyond urban centers.

Furthermore, public-private partnerships offer potential avenues for securing necessary funding without placing undue financial burden on local communities or individual businesses.

As such, developing an efficient and resilient off-road EV charging network requires a holistic approach incorporating technological innovation, targeted investment strategies, and sustainability considerations.

RELATED: Jama Connect® for Automotive

The challenges of designing and manufacturing off-highway EVs

Designing and manufacturing electric off-highway vehicles presents unique challenges, with research indicating that a significant one is ensuring these machines can withstand the rigors of heavy-duty applications, an issue reported by 60% of manufacturers. Battery longevity is a critical concern in this regard since off-road vehicles often operate in extreme conditions that could quickly diminish battery life.

Similarly, terrain adaptability is another challenge. Electric vehicles must be designed to handle diverse terrains, from rocky landscapes to sandy dunes, without compromising on performance or energy efficiency.

Material sourcing poses yet another problem due to the need for lightweight but highly durable materials for construction. This brings us to durability concerns which are paramount because, unlike regular city electric cars, off-highway EVs have to endure harsher operational conditions requiring them to be more robust and longer-lasting.

Finally, cost efficiency continues to be an obstacle as developing high-performance, yet affordable electric off-highway vehicles remains a struggle for many manufacturers, due to the high costs associated with batteries and other essential components.

The future of EV infrastructure both on- and off-road

Transitioning from the challenges of designing and manufacturing electric off-highway vehicles, it is pivotal to envision what the future holds for EV infrastructure. This includes both on- and off-road contexts, as each comes with its unique set of considerations pertaining to infrastructure financing, renewable energy integration, vehicle-to-grid technology, and battery disposal methods.

The future landscape of EV infrastructure will likely be shaped by a variety of factors. The pace at which this change occurs may largely hinge upon infrastructure financing – securing sufficient funds to create an expansive network of charging stations that facilitate higher EV adoption rates. As more consumers opt for electric vehicles, there will be an increased demand for reliable and accessible charging facilities.

Therefore, investment in this sector is crucial not only for supporting current users but also promoting further uptake.

Simultaneously, the integration of renewable energy sources into these infrastructures represents a crucial aspect. By harnessing power from sustainable resources such as solar or wind energy, the environmental impact can be further mitigated while optimizing energy usage overall.

Moreover, vehicle-to-grid technology presents another promising avenue where electric cars do not just draw power but can feed surplus back into the grid during peak demand hours – thereby acting as mobile energy storage units. This could revolutionize how electricity grids operate while offering additional revenue streams for EV owners.

Lastly are considerations regarding battery disposal methods. With growing numbers of electric vehicles on- and off-road comes increased volumes of spent batteries which necessitate effective recycling or disposal strategies to minimize environmental harm and potential resource losses.

Thus, these aspects collectively indicate a multifaceted future wherein technological advancements must go together with strategic planning and responsible practices.

The US Government’s solutions offer hope

In conclusion, the path to an electrified future, both on- and off-road, resembles a vast and uncharted road. Despite challenges such as regional disparities in charging station availability, hurdles in infrastructure expansion, and manufacturing complexities for off-highway vehicles, progress is being made.

The US Government’s support, alongside innovative solutions, offers hope that these obstacles can be overcome. As the dawn breaks on this new era of transportation, one cannot help but feel a sense of anticipation for what lies ahead – a highway illuminated by the promise of sustainable mobility.





This image portrays product and engineering predictions for teams in 2024.

2024 Predictions for Product and Engineering Teams

As Product and Engineering Teams move into 2024, we aim to gain a deeper insight into the factors driving transformation in the development of products, systems, and software and explore how teams within this industry are adapting to meet the challenges posed by these evolving complexities.

In the final part of this six-part series, we asked our own industry experts Josh Turpen – Chief Product Officer, and Preston Mitchell – Vice President, Global Solutions, to weigh in on the product development and engineering trends they’re anticipating in the coming year in the coming year and beyond.

We like to stay on top of trends in other industries as well. Read our predictions for Automotive predictions HERE, Aerospace & Defense HERE, Industrial & Consumer Electronics (ICE) HERE, Medical Device & Life Sciences HERE, and SoftTech HERE.

Design Trends – What are the biggest trends you’re seeing in your industry right now? How will they impact product & engineering teams through product, systems, and software development?

Josh Turpen: Software continues to eat hardware. This trend is accelerating in the complex product space, particularly in automotive. This is driving companies to be “agile” but at the cost of quality.

Preston Mitchell: The big trend will be how to focus using the emergent Artificial Intelligence (AI)/ Large Language Models (LLM) solutions so they actually help the team be more efficient or profitable. Plenty of emerging tech in the AI space but remains to be seen how “useful” it will be. There is a huge opportunity to leverage this in ways that are beneficial for teams with the right focus. For example, we’re just starting down this path at Jama Software® with Jama Connect Advisor™, which helps train business analysts/product managers / engineers on how to write their requirements in more concise fashion with less ambiguity.

Biggest Challenges – What are some of the biggest challenges you think product & engineering teams will be working to overcome in 2024?

Turpen: Quality at scale and speed will continue to be a problem. This is exacerbated by the increasing complexity in software.

Opportunities – What are some of the biggest opportunities you think product & engineering teams should be considering in 2024?

Mitchell: Automation. Consider where automation can reduce the complexity and time needed to deliver large scale products. I’ve worked with hundreds of companies that build very complex products and I’m still amazed at how many of their internal processes are manual. AI will certainly be the 2024 buzzword – but currently most AI tools are still beta and rely on a human to prompt for an answer – not exactly automating a repeatable process. When I mean automation opportunity I’m talking about the low-hanging fruit of manual business processes – for example, automating task links between multiple engineering tools.

RELATED: How to Plan for Large Language Model (LLM) Adoption Within Your Engineering Organization

Regulations – What changing regulatory guidelines do you anticipate having an impact on companies in 2024?

Turpen: Companies that seek to identify risks (not just in products, but in process) will come out on top. Anti-fragile product development pipelines are the logistical super-power for the next phase of product development.

Tool Innovation – From a product & engineering toolset perspective, what are some of the processes you think forward-thinking organizations will be working to leverage or incorporate into their process and why?

Turpen: Moving from the individual engineer to the team/product pipeline will give management the opportunity to intervene early to reduce risk. Products that are focused on a best-of-breed world will give companies a leg up on legacy vendors and their suite approaches.

Mitchell: Forward-thinking orgs will adopt data-driven assessment of the product development lifecycle. Today there are no generally accepted measurements of Research and Development (R&D) efficiency. It’s hard for organizations to predict if a product will be delivered on time and without defects. Launch delays and regressions are common and almost generally accepted. Organizations commonly measure a product’s performance after it is launched (revenue, profit, adoption.) Why don’t we measure what happens before it is launched? Why don’t we measure the R&D lifecycle? Forward thinking orgs will adopt ways to measure their development lifecycle to they can better predict success or failure…and some may not like what they find.

Cybersecurity – What role will cybersecurity play in product & engineering development in the coming year and beyond?

Turpen: Cybersecurity will be baked into requirements and, therefore, products for everything from thermostats to ADAS.

Survival Factors – In your opinion, what are the biggest differences between product & engineering companies that will survive to see 2030, and ones that don’t?

Turpen: Agility tempered with quality will be the common trait of survivors. We’re already seeing companies get slapped with criminal charges based on their inability to see and manage risk.

Mitchell: With the hot economy and low interest rates before recent inflation there was a lot of investment in new startups and emerging technologies — think self-driving cars and AI. The economy is still doing well, but tempered with higher interest rates, so the investors of years past are looking for a return on their prior investment and will be more tempered with any new bets they place. The companies that survive to see 2030 will be the ones that find clear use cases that people are willing to pay for in these emerging technologies. New products and tech just “because it’s cool!” will not survive without a commercialization path.

RELATED: Traceable Agile – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

Advice – What advice would you give to new product & engineering teams entering the market?

Turpen: Move fast and KNOW what you’re going to break.

Mitchell: Ask questions and seek advice from your peers or mentors who have built something before in your industry. Determine who your ideal “first customer” would be and work hard to speak with them, show them your early prototypes, and validate your assumptions about what they need.

Emerging Topics – What topic(s) do you wish companies were paying more attention to?

Turpen: Management of the engineering process.

Mitchell: Solving very easy efficiency problems in the engineering process like automating flow of data between disparate systems. I just spoke with a customer whose testers were redundantly logging defects in two different systems! Come on! Set aside some time to automate that process!

Identifying Mistakes – What is the biggest mistake you see product and engineering teams making right now?

Turpen: Throwing money at hard problems with little understanding of success and no management of the outcome.

Mitchell: Assuming a tool will solve their problems. Process first, then tool.

Innovation – What is the most innovative thing you’ve seen with product and engineering teams this year that you anticipate other companies following suit in coming years?

Turpen: Moving away from the “big meeting” to an asynchronous, stateful collaboration process.

Predictions – What do you think will remain the same in your industry throughout 2024?

Turpen: Companies who think the answer to their engineering process problems is a monolithic tool will continue to lose ground and engineers to their competitors.

Do you think there will be any major disruptors for product & engineering teams in the coming year? How do you think it will impact the industry?

Turpen: We’ll see the first set of major Intellectual Property (IP) lawsuits based on uncontrolled LLM. This will force companies to think about security and IP protections in their own AI development.

Mitchell: This will not happen in one year, but I foresee AI solutions replacing the need for traditional learning assets like static help guides, training videos, and maybe even support sites. Users don’t need to read a help guide, watch a tutorial, or submit a support ticket if an AI assistant is guiding them in the process and available for quick questions. Effort to build those types of traditional learning assets will be redirected to investments in AI assisted “on the job” learning while using the product.

What do you predict for product & engineering regulations in 2024?

Turpen: A continued increase in the importance of security/safety regulations in the automotive/medical industries with more penalties for poor performance.

Will those trends still be prevalent 5 years from now? 10 years?

Turpen: Yes, this is an area that will only grow in complexity and impact.

2024 Predictions or Soft-Tech Product, Systems, and Software Development

2024 Predictions for Soft-Tech Product, Systems, and Software Development

As the SoftTech sector moves into 2024, we aim to gain a deeper insight into the factors driving transformation in the development of products, systems, and software and explore how teams within this industry are adapting to meet the challenges posed by these evolving complexities.

In part five of this six-part series, we asked our own industry experts Patrick Garman – Principal Solutions Consultant, and Steven Meadows – Principal Solutions Lead, to weigh in on the SoftTech trends they’re anticipating in the coming year and beyond.

We like to stay on top of trends in other industries as well. Read our Automotive predictions HERE, Aerospace & Defense HERE, Industrial & Consumer Electronics (ICE) HERE, Medical Device & Life Sciences HERE, and Product & Engineering Teams HERE.

Design Trends – What are the biggest trends you’re seeing in your industry right now? How will they impact SoftTech development?

Patrick Garman: With the increased awareness and popularity of tools like ChatGPT, Generative AI and its potential applications in product development and requirements management has come up often in conversations with customers. Common questions include: can AI suggest ‘missing’ requirements, suggest relationship links for existing requirements, or even generate a full set of requirements based on similar products or projects? These are interesting questions, and I can certainly see the potential value that AI could add, but softtech companies should be wary of automating too much of their requirements management and product development processes. Generative AI might be able to provide suggestions or at least a starting point for requirements, but it cannot and should not replace human review and insights.

Steven Meadows: Artificial Intelligence (AI) is evolving at an unprecedented rate and the continuation of the application of AI in software development is no exception. More tools and libraries are being built to help support the automation of development tasks, including coding and test automation. Developers are now able to create more intelligent and user-centric systems, which ultimately improves the stakeholder experience. Over the next few years, I anticipate that we’ll start to see more AI-based applications that will help teams debug code and fix bugs in real-time.

In terms of requirements management in the software world, we’re seeing AI and machine learning assist with tasks such as requirement generation. This will continue to help shape better-quality systems with fewer issues for users. Models in this area are still being improved, but we are already seeing the benefits of AI bringing better-quality systems to market.

Regulations – What changing regulatory guidelines do you anticipate having an impact on companies in 2024?

Garman: Data privacy still looms large in SoftTech and is top of mind for consumers. A 2020 Pew Research study indicated that half of U.S. consumers have not used a product because of privacy concerns. While the European Union acted several years ago by introducing GDRP, the United States has shied away from federal regulation – focusing on specific classes of data (health and financial) and users (children). Traction for data privacy regulation at the state level is gaining speed, though. California introduced the California Privacy Rights Act in 2019, laws are being enacted in Virginia, Colorado, Utah, and Connecticut this year, and eight more states have signed data privacy legislation, with another six currently debating the issue. With the continued growth of connected devices and cloud services, and the emergence of advanced AI, I predict even more attention will be directed to how tech companies collect and use consumer data. To prepare, forward-looking tech companies will take a cue from companies like Apple and take a more proactive ‘self-regulating’ approach to data privacy in their product design.

Meadows: Keeping with the theme of AI, I anticipate that there will be new regulations coming out affecting the application and use of AI in software. Governments and state entities have made it clear that further regulation of AI is coming, so it’s only a matter of time.

It’s clear to see that there have been instances of biased results being produced by AI systems. For example, credit card algorithms that discriminate based on sex and other factors. Algorithms have also been developed that target people based on race, religion, and gender.

It’s unclear if there will be mandates on the particular use of training data as part of a model’s learning phase or whether limitations will be placed on the types of models used. One thing is for certain though – further regulation of AI in software is coming!

Tool Innovation – From a SoftTech industry engineering toolset perspective, what are some of the processes you think forward-thinking firms will be working to leverage or incorporate into their process, and why?

Garman: While it might seem like a step back for some, I think there is a strong movement in software development to find a better balance between planning and implementation activities. Many companies take Agile to mean ‘just go do’ — start writing code as quickly as possible, release to customers early and often, learn lessons on the fly, and incorporate feedback rapidly. That’s certainly part of Agile and a great ideal to strive for, but in practice, it is very difficult to incorporate customer feedback into iterative releases quickly enough. In other words, it’s easy to ‘fail fast’ but very hard to ‘course correct fast.’ That’s not the fault of software teams; there is a lot of pressure to deliver an ever-growing backlog of features and stories, and prioritization is difficult to manage when business objectives and market demands can change overnight! Applying more diligence to the planning activities – defining and getting agreement on requirements before ‘just going and doing’ – goes a long way towards improving software teams’ ability to actively prioritize their backlogs, feel confident that what they are doing is the right thing to be doing, and reduces the amount of rework or technical debt that must be addressed post-release. Adopting a requirements management tool that supports an agile approach will add tremendous value in SoftTech development.

Meadows: Software companies continue to adopt, and rightly so, an Agile work culture and methodology. Forward-thinking Agile teams must be prepared to adapt to challenges that can hinder quality development for their customers. Task management tools like Jira and Azure DevOps (ADO) have become standard ways to manage work including the prioritization of activities, project management, and resource allocation. One aspect of development that is very much neglected is requirements management. Development teams need to be able to effectively communicate with business analysts, product owners, architects, and their own customers, as well as understand whether requirements have been satisfied in real time.

Without a dedicated and purpose-built requirements management system, silos are created in terms of data and teams, leading to systems produced with more defects and lower quality. Forward-thinking- teams should be adopting a requirements tool tightly coupled with their task management applications for effective end-to-end visibility throughout the development cycle, catching issues and mitigating risk earlier in the development lifecycle.

RELATED: Buyer’s Guide: Selecting a Requirements Management and Traceability Solution for Software Development

What role will cybersecurity play in soft-tech industry development in the coming year and beyond?

Garman: Cybersecurity is perhaps the most important consideration for product development in SoftTech. The convenience of connected devices will continue to drive consumer demand – even my dishwasher connects to the internet! However, this convenience comes with the risk of data breaches and network vulnerabilities. Encrypting data during transmission and storage is just table stakes now. SoftTech companies must be ready to move much faster than in the past to push software and firmware updates in response to new vulnerabilities. The ability to quickly generate impact analyses and trace- identified risks and vulnerabilities to the mitigating requirements is more important than ever in taking a proactive stance toward cybersecurity.

In your opinion, what are the biggest differences between SoftTech companies that will survive to see 2030, and ones that don’t?

Garman: Technical debt is becoming a much larger liability for SoftTech companies as the rate of innovation continues to accelerate – the more technical debt a SoftTech company builds, the harder it will become to quickly respond to emerging trends and innovations. We see it more and more often – once the better mouse trap is available, it becomes the expectation, not the nice to have. Of course, decisions must be made to address near-term or immediate needs and there will always be trade-offs to consider to optimize ROI. SoftTech companies that design and develop their products to not only to fulfill the near-term needs while maintaining the architectural flexibility to adopt future trends will be the ones to keep pace with consumer expectations and win in the long term.

What advice would you give to new companies entering the SoftTech industry?

Garman: Embrace design thinking and avoid jumping too quickly to a solution. This applies if you are a new company or an established company entering a new market. SoftTech products can become commodities very quickly – it’s easier than ever to just copy/paste an existing solution – but that will ultimately only drive prices down as more options are available to consumers. Design thinking is a great framework for requirements management. Start by really defining the problem or needs that your product intends to resolve and also defining the user needs for your target market. User needs are the foundation for good requirements, and good requirements are the foundation for successful products.

What topic(s) do you wish companies were paying more attention to?

Garman: Refocus on user experience. MVP is commonly defined as “Minimum Viable Product,” but I strongly prefer “Minimum Valuable Product”– in other words, instead of designing through the lens of ‘what is the least we can deliver so that a user can accomplish this task or goal,’ adopt a mindset of ‘what is the least we can deliver so that a user has a good experience in accomplishing this task or goal.’ Designing for good user experience does not limit the return on investment (ROI) – in fact, it leads to higher lifetime value through customer loyalty and goodwill.

What is the biggest mistake you see companies in the soft-tech industry making right now?

Garman: I mentioned earlier that I see the trend of software teams re-prioritizing requirements management and planning activities in advance of development activities, and that is in direct response to the issues and pain points that SoftTech companies have experienced as they adopt a ‘just go do’ approach to product development. One of my grad school professors claimed that an 80/20 ratio of planning to doing was the ideal. Every company will need to find its own balance, but the data is clear – companies that apply diligence in requirements management are faster to market, expend less time and resources in the actual development phase, and experience fewer defects after release.

RELATED: Traceable Agile – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

Do you think there will be any major disruptors in the SoftTech industry in the coming year? How do you think it will impact the industry?

Garman: At the risk of sounding like a broken record, advancements in artificial intelligence. The potential applications are tremendous! I’ve mentioned the potential for using AI to develop products. In the short term, we’ll likely see more soft-tech companies employing generative AI for product support and predictive process automation. Conversational AI will also change the way we interact with software and connected devices. The market for voice assistants has a projected CAGR of nearly 27% over the next eight years and hands-free devices are projected to have a 7% CAGR over the next five years – and that is based on the current task-based commands that are supported. As consumers continue to adopt smart home devices, the expectations for hands-free control will only increase.

What do you predict for regulation in the SoftTech industry in 2024?

Will those trends still be prevalent five years from now? 10 years?

Garman: I’ve already discussed data privacy regulation, and I do think that the federal regulations will be expanded in the United States in the coming years. Regulation for AI – specifically generative AI – is likely next, but what will be enacted and how is still an open question. The two topics are linked in that generative AI produces content based on existing inputs, generally user data and public-facing IP. AI and advanced machine learning have tremendous potential, but aside from data privacy concerns, AI also introduces safety risks. We are already seeing the implementation of functional safety standards in robotics, and as autonomous robots continue to advance, we will likely see increased regulatory oversight. No one wants the rise of Skynet!

2024 Predictions for Medical Device & Life Sciences Product, Systems, and Software Development

2024 Predictions for Medical Device & Life Sciences Product, Systems, and Software Development

As the medical device & life sciences industry transitions into 2024, we aim to gain a deeper insight into the factors driving transformation in the development of products, systems, and software and explore how teams within this sector are adapting to meet the challenges posed by these evolving complexities.

In part four of this six-part series, we asked the following industry experts to weigh in on the medical device & life sciences product, systems, and software trends they are anticipating in the coming year:

We like to stay on top of trends in other industries as well. Read our Automotive predictions HERE, Aerospace & Defense HERE, Industrial & Consumer Electronics (ICE) HERE, SoftTech HERE, and Product & Engineering Teams HERE.

2024 Predictions for Medical Device & Life Sciences Development

Design Trends – What are the biggest trends you’re seeing in your industry right now? How will they impact medical device & life sciences development?

Shawnnah Monterrey: We are seeing a significant increase in healthcare innovations, especially with in-vitro diagnostics, and clinical decision support software.

The ability to connect medical devices to share medical device data through emergence, evolution of cloud computing, and the increase in data storage capability has led to the derivation of new clinical insights, in diagnostics, and clinical decision support. Artificial Intelligence (AI) and Machine Learning (ML) are being applied to clinical and patient data in unique and novel ways, such as in-vitro fertilization, cancer treatment recommendations, and the automation of status-quo manual clinical processes.

The increase in research allocated to understanding our DNA, and its relationship on our health, has led to the rapid adoption of DNA-based clinical tools utilizing next-generation sequencing and other DNA detection technologies such as DNA nanotechnology tools, chip-based digital Polymerase Chain Reaction (PCR) detection, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) diagnostic technology, etc. to aid in the diagnosis and treatment of complex diseases such as cancer, neurodegenerative diseases and dementia and even behavioral, and psychiatric disorders.

Vincent Balgos: As we’re seeing in other industries, a common trend in the medical industry is that organizations are refreshing their internal processes to scale, integrate, and increase efficiency. With extrinsic pressures (market, financial, and regulatory), there is continual effort to optimize organization activities, specifically around product development processes, and leverage previous work as much as possible.

Biggest Challenges – What are some of the biggest challenges you think medical device & life sciences companies will be working to overcome in 2024?

Monterrey: A few of the biggest challenges companies will face in 2024 include but are not limited to:

  • Being competitive and innovative in a highly regulated environment
  • Understanding regulatory requirements in new or less mature regulated areas
  • Obtaining funding to support regulatory and development efforts

Companies who are focused on aligning their product roadmap with a sound regulatory strategy will not only unlock funding but obtain revenue faster, which will allow them to leap ahead of the competition.

Regulations – What changing regulatory guidelines do you anticipate having an impact on companies in 2024?

Monterrey: U.S. Food & Drug Administration (FDA) is not known to be fast, but within recent years, the FDA has released a record number of guidances and have even changed the medical device regulation in a few areas. While the industry is playing catchup on hundreds of new guidances in areas such as:

  • Software as a Medical Device (SaMD)
  • Cybersecurity
  • Clinical Decision Support Software
  • Mobile Applications

The FDA is working on furthering the regulation and guidance around many areas including, 510(k) Third Party Review Program, In Vitro Diagnostics (IVDs), AI/ML, and the use of real-world and simulated data in pre-market submissions.

It would be wise for companies to start understanding and applying new draft guidances that are relevant to their products in advance of the final draft. Once a final version is issued it could drastically interrupt your product development and launch plans.

Balgos: There are a few regulations that will start or continue to have an impact on the industry:

  • FDA’s Final Guidance on Cybersecurity for Medical Devices – Continuing the focus on Software (SW) in previous years, this new final guidance will require ongoing discussions on the new security requirements (ex: Software Bill of Materials (SBOM)), activities, and expected documentation.
  • FDA’s proposed ruling on Laboratory Developed Tests (LDT) – In the latest turn of events in this long running topic, this new proposed rule to transition away from Enforcement Discretionary (ED) to more explicit LDT oversight by FDA will have significant impact to the laboratory industry. Industry feedback has been active and complex, so will be interested to see if there will be a resurgence of the previous VALID Act or will the new proposed ruling stand as is.
  • Based on FDA’s proposed 2024 list of prioritized guidances, there will be additional information around AI/ MLin context of lifecycle management, pre-submissions, and change management considerations.
  • In the EU, both the Medical Device Regulation (MDR) and In-Vitro Dianostics Regulation (IVDR) will continue to impact companies as they transition to these new rulesets. Even with the time extension on MDR, companies are continuing to struggle in converting their processes to comply with the new regulations as 2024 rolls out.

Romer De Los Santos: The FDA just released the final guidance on cybersecurity in medical devices that includes additional tasks and deliverables that medical device manufacturers must start to implement. Design and development procedures for software that is part of or is a medical device itself will need to be updated with this new guidance in mind. Software Bill of Materials (SOBM), security risk assessments, threat modeling, and consideration of the entire lifecycle for security risks and mitigations are just some of the things that are required in today’s interconnected world.

RELATED: Understanding Integrated Risk Management for Medical Devices

Tool Innovation – From a medical device & life sciences engineering toolset perspective, what are some of the processes you think forward-thinking firms will be working to leverage or incorporate into their process and why?

Monterrey: Product development costs, regulatory complexity, and time-to-market are all increasingly trending topics in the medical device industry. Companies that are thinking ahead of these trends are focusing on their competitive advantage, which includes their innovation or core Intellectual Property (IP) and leveraging the support of industry experts and built–for–purpose tools.

This includes:

  • Investing in existing regulatory and quality management frameworks, including software, built-in processes, and training
  • Hiring regulatory and quality experts who understand the regulatory landscape and have domain expertise related to their products
  • Integrating medical/clinical grade or complaint platform software, components, and development tools

De Los Santos: Firms will need to leverage tools like Jama Connect to start to track security risks, SBOM, and the documentation for a multitude of software variants, upgrades, and patches. While the tools enable compliance with regulatory requirements, medical device manufacturers need to create a robust and lightweight design and development process that leverages the capabilities of their tools. For many firms, this means looking at the total development lifecycle holistically instead of tacking on quick fixes to their procedures to meet current regulatory requirements.

What role will cybersecurity play in medical device & life sciences development in the coming year and beyond?

Monterrey: Per the current FDA guidance, obtaining per-market approval/clearance for a medical device with firmware or software, connected, or not connected all require some level of cybersecurity compliance, especially around risk management. This has put an extra strain on medical device manufacturers because the guidance is very technical and rigorous and currently does not provide guidance around the level of application based on the risk of the device. I hope to see a future revision that accommodates lower risk devices, but for now it’s worth investing in cybersecurity experts who can help you certify your device and associated processes.

Balgos: As noted in a recent FDA webinar around cybersecurity, there is continual discussion in how to regulate this topic, and the expected deliverables to the agency. One area is SBOM and how to properly document all the elements of software for a medical device.

De Los Santos: Cybersecurity will play a starring role as manufacturers start to revise their design and development processes to include it.

In your opinion, what are the biggest differences between medical device & life sciences companies that will survive to see 2030, and ones that don’t?

Monterrey: Those who survive to see 2030 will respect the regulatory landscape and put in place proper attention and investment, instead of those trying to delay, resist, or evade the inevitable. Although it might not feel like it, the changes being put in place are to our benefit, with the intent of providing the industry with a clearer pathway for new innovations. It will just take a while for the regulations to harmonize and for the industry to adopt to the new ways of thinking by leveraging data, tools, and expertise to rapidly innovate.

De Los Santos: Companies that are adaptable and innovative with not only their products, but their design and development process will survive to see 2030.

What advice would you give to new companies entering the medical device & life sciences industry?

Monterrey: Build your product for the industry – align your product development efforts with your business model and regulatory strategy and do not try to obtain premarket approval for your device without the support of experts in the industry unless you have done so successfully before.

De Los Santos: Keep it simple.

What topic(s) do you wish companies were paying more attention to?

Monterrey: I wish more companies would focus on defining their regulatory strategy early in the development lifecycle and not wait until they have only six months or less to start thinking about getting their device approved or cleared. Depending on the complexity of your device, regulatory compliance efforts could take 12-36 months, with most of the efforts around verification and validation. Six months prior is often too late and could be detrimental to your business launch plans that do not meet your stakeholder expectations.

De Los Santos: I wish companies would focus on fixing their process problems instead of patching them. A little more front-end work will save future teams lots of time.

RELATED: Jama Connect® for Medical Device & Life Sciences Development Datasheet

What is the biggest mistake you see companies in medical device & life sciences making right now?

Monterrey: Two biggest mistakes I see are:

  • Trying to make a medical device not a medical device, even though it is a medical device
  • Not narrowing down a product’s intended use for the first launch

Balgos: Cutting corners for short-term gain, but in reality, these cuts will actually cause long-term consequences exponentially. Example: Documentation. Time and time again, our technical customers (and from my own personal experience) are being pressured to get products out the door and do the documentation later. There are several issues with that: 1) technical documentation and files are required for regulatory submissions for market clearance, 2) this generally conflicts with most good Engineering and Quality practices as they will need time for review/approval, and 3) it’s much harder to document something long after it’s happened. These issues culminate in taking much longer to complete the documentation, and thus impacts the long term.

De Los Santos: Companies should not make their procedures more complex than they need to be.

What is the most innovative thing you’ve seen in medical device & life sciences this year that you anticipate other companies following suit in coming years?

Monterrey: The most innovative things I have seen is the creative use of simulated and real-world data to support pre-market approval and the novel application of AI, which uses data from multiple unrelated devices to diagnose, treat, or support various diseases and medical conditions. I am seeing more products provide a technology platform for multiple intended uses. Companies that are successful, understand the long game and focus on the easiest-to-launch intended use first, generate revenue, and then focus on further product applications, including innovations that require a more rigorous regulatory pathway.

Predictions –

What do you think will remain the same in your industry throughout 2024?

Monterrey: I think 2024 will be a very innovative year meaning there are more changes to come, and we will continue to see new and novel clinical innovations continue to disrupt the industry. 2024 is going to be an exciting and unprecedented year!

Do you think there will be any major disruptors in medical device & life sciences in the coming year? How do you think it will impact the industry?

Monterrey: Major disruptors will come from those focusing on diseases and conditions that have previously been ignored or neglected. One area I would like to see advance is the use of software as a therapeutic as opposed to prescription pharmaceuticals, devices, or surgery. Because of limitations in reimbursement and the non-traditional use of software as a therapeutic device, this area has experienced challenges which has delayed its adoption.

Balgos: The emergence of AI/ML has the potential to become an industry disruptor, dependent on its application or intended use. We can see its impact already in non-medical software, so it is only a matter of time before its influence is felt in the medical industry. Hence, there are continual discussions from FDA, industry bodies and experts, in how to regulate, develop and manage AI/ML for medical devices.

What do you predict for regulation in the medical device & life sciences industry in 2024?

Will those trends still be prevalent five years from now? 10 years?

Monterrey: As I stated last year, I still see progress around the harmonization of guidances and standards, which will eventually allow for a more standard way to approach pre-market approval — but I stated previously, this will be messy and complex before it clears itself out. I primarily see the increased use of simulated and real-world data as a new way to validate devices. Animal and in-human use will decrease, and publicly available and validated datasets will become available to quickly assess new medical devices for safety and efficacy.

2024 Predictions for Aerospace & Defense Product, Systems, and Software Development

As the aerospace & defense industry advances into 2024, we aim to gain a deeper insight into the factors propelling transformation in the development of products, systems, and software, and explore how teams within this sector are adapting to meet the challenges posed by evolving complexities.

Jama Software® asked selected thought leaders — both internal Jama Software employees and our external partners — across various industries for the trends and events they foresee unfolding over the next year and beyond.

In part two of this six-part series, we asked the following industry experts to weigh in on the aerospace & defense product, systems, and software trends they are anticipating in the coming year:

We like to stay on top of trends in other industries as well. Read our Automotive predictions HERE, Industrial & Consumer Electronics (ICE) HERE, Medical Device & Life Sciences HERE, SoftTech HERE, and Product & Engineering Teams HERE.

Design Trends – What are the biggest trends you’re seeing in your industry right now? How will they impact aerospace & defense product, systems, and software development?

Francois Couadau: There is a lot of attention, both in academia and within the industry, around Artificial Intelligence (AI) / Machine Learning (ML.). These technologies promise many exciting applications, such as single-pilot operations for cargo and commercial flights or supercharged Intelligence, Surveillance, and Reconnaissance (ISR) capabilities for the defense sector. They have a long way to go before they’re certified for flight, but experiments are everywhere.

Aside from this, trends from past years are still going strong: Model-Based Systems Engineering (MBSE) and the use of a Digital Thread throughout programs allows teams to tame the ever-growing complexity.

Guilherme Goretkin: Big trends towards more modular and loosely coupled architectures with open systems approaches like Modular Open Systems Approach (MOSA) and PYRAMID Reference Systems (PRA) utilizing open publicly available interoperability standards like Future Airborne Capabilities Environment (FACE) and ARINC 661 with the goals of reducing program risk, more software interoperability, reuse, and better sustainability.

Cary Bryczek: The biggest design trend is figuring out ways to incorporate AI into systems and products in a safe way.

Karl Mulcahy: I’m also seeing a need to work together as a consortium to deliver a product for an end customer. It’s fascinating to see how companies are approaching this, and working together across different networks, countries, and even industries.

RELATED: Buyer’s Guide: Selecting a Requirements Management and Traceability Solution for Aerospace

Biggest Challenges – What are some of the biggest challenges you think aerospace & defense companies will be working to overcome in 2024?

Couadau: In the avionics projects domain, growing complexity and ever-shorter timelines go hand in hand and are the main challenge.

Bryczek: The biggest challenges are protecting against intellectual property (IP) loss and preventing security incidents from adversaries. Both the United States and European countries defense organization have set forth mission statements to protect technology advantage and counter unwanted technology transfer to ensure warfighter dominance through assured, secure, and resilient systems and a healthy, viable innovation base.

Mulcahy: On top of IP protection like Cary mentions, I believe there is a desire to modernize ways of working to help drive efficiencies in existing operations, but also to attract / retain new and emerging talent. By having best–of-breed tools, it can help attract best-of-breed talent and facilitate an easier way to realize innovation.

Regulations – What changing regulatory guidelines do you anticipate having an impact on companies in 2024?

Couadau: In keeping with the trends, AI/ML is currently not certifiable due to lack of specialized standards. Standardization efforts are ongoing, and we should see the first documents emerge soon.

Unstable global geopolitics may also play a part. Sanctions and embargoes may change the shape of markets.

Goretkin: Cybersecurity. “DoD [Departement of Defense] policy generally requires all acquisitions containing mission-critical or mission-critical IT systems to have a cybersecurity strategy” – GAO-23-106059 Weapon Systems Annual Assessment June 2023

Bryczek: In the US the Department of Defense will continue providing more guidance on its 2023 DoD Cyber Strategy. In 2024 you will see more guidelines provided to Defense Components as well as instructions in contracts to encourage the increase of collective cyber resilience by building the cyber capability of allies and partners. Lessons learned from the war in Russia-Ukraine has sparked commentary from Assistant Secretary of Defense for Space Policy John Plumb to say. “It has driven home the need to work closely with our allies, partners, and industry to make sure we have the right cyber capabilities, cyber security, and cyber resilience to help deter conflict, and to fight and win if deterrence fails.”

Mulcahy: With sustainability a renewed global focus, especially with recent initiatives such as the 28th meeting of the Conference of the Parties (COP28), more focus will be turned to sustainability, efficiency, and developments in greener technology such as electronic / hydrogen / hybrid airborne travel. It’s exciting to see many start-ups in this domain.

Maybe we’ll see something around unmanned aerial systems regulations come to fruition – again with the increase of use cases in civilian / defense markets for these unmanned aerial vehicles (UAVs.)

Tool Innovation – From an aerospace & defense engineering toolset perspective, what are some of the processes you think forward-thinking firms will be working to leverage or incorporate into their process and why?

Couadau: Model-Based System Engineering tools and methods are continuing to mature and are a key pillar for complex aerospace projects. Generative AI, applied at key spots during design, is also a key design accelerator.

Bryczek: Forward-thinking organizations will be focusing their processes and supporting tools around these areas of systems engineering: Digital Engineering, Modular Open Systems Approach (MOSA), Agile DevSecOps Development, and Mission Engineering (ME). Each of these areas touch aspects of systems engineering lifecycle management and require tools to support the newer techniques. Data integration across disparate tools such as software code version control, enterprise architecture modeling tools, requirements tools, mission simulation tools, and a variety of specialized analysis tools are some of the keys to success. Open standards such as the newest version of SysML 2.0 is driving new tool innovation from both long-standing tool vendors and companies that are new to the marketplace. Processes such as mission simulation will take place much earlier in the lifecycle and will reduce the cost of some of the Verification & Validation (V&V) efforts from traditional approaches.

Mulcahy: With digitization a big focus to start / advance with in 2024, we anticipate more discussions around MBSE (in line with SysML 2.0), but also Digital Engineering** – to connect with other tools in house and work towards a Digital Twin.

**CIMdata: Digital Thread in Aerospace and Defense

Not only could this include tools that help develop software, manage parts / simulations / detailed design aspects, but also ones that ensure validation and verification are undertaken sufficiently, proving out compliance to various industry mandates — especially when it comes to safety critical systems.

With many mergers and acquisitions continuing to be a part of this industry, re-use, collaboration, and auditability will increasingly become important. Knowing who changed things, why they were changed, and a record of the associated discussion will be invaluable as new products are designed — whether they have been designed from scratch or using existing IP. Not only would this save time understanding the complexities, but also help capture that knowledge to be able to transfer it to other organizations or teams who may not have been involved in original projects.

What role will cybersecurity play in aerospace & defense development in the coming year and beyond?

Bryczek: Cybersecurity is being prioritized nearly above all else in developing every type of system, from vehicles, to satellites, to commercial and military aircraft, and the systems that perform command and control. Any system that is connected to a network or connects to other computer systems via a removable cable, whether it is operating in an air-gapped environment, embedded within an aircraft, or touching the public internet are equally scrutinized for known vulnerabilities and are being required to adhere to security policies during development. DevSecOps strategies are putting security at the forefront during all stages of the lifecycle now instead of just being a post development process. In addition, we’re seeing organizations, more often now than ever, providing human-centric training to employees around good cybersecurity practices.

In your opinion, what are the biggest differences between aerospace & defense companies that will survive to see 2030, and ones that don’t?

Couadau: Adaptability is the name of the game. In addition to the market pressures, we are used to, the aviation industry is tasked with ambitious carbon reduction goals. International Air Transport Association (IATA) predicts that 1.8 gigatons of carbon will need to be abated yearly by 2050**. Companies that embrace this change now are bound to find success in a low-carbon future.

** IATA: Net-Zero Carbon Emissions by 2050

Bryczek: The aerospace and defense companies that retain top talent, spend design dollars wisely, and make winning partnership decisions will help companies survive to 2030.

Mulcahy: Embracing modern ways of working to enhance competitive advantage by delivering projects on time / to scope.

What advice would you give to new companies entering the aerospace & defense industry?

Bryczek: New start-ups need to embrace design-thinking principles right from the outset. Early collaboration involving the target end users such as military personnel together with the engineers, designers, and data scientists will lead to faster validation of the design’s requirements and ensure that the new capability is solving the needs of the users. Companies will also need to embrace new technologies like AI, machine learning, 3D printing, and multi-scale and multi-physics simulation.

Mulcahy: With ever-changing regulations, work with experts to help your company adhere to them. Embrace help and guidance from industry experts to allow you to focus on your new innovation to the market and not re-invent the wheel.

RELATED: Certification and the Role It Plays in the eVTOL Aircraft Market

Furthermore, working with best-of-breed tools will allow you to attract new talent and help achieve innovation quicker.

What topic(s) do you wish companies were paying more attention to?

Bryczek: As systems become more software-centric, security regulations, especially those related to cybersecurity become increasingly more relevant and unavoidable. The updates to security frameworks such as the National Institute of Standards and Technology (NIST) – and Network and Information Systems (NIS) in EMEA — as well as cybersecurity frameworks such as Cybersecurity Maturity Model Certification (CMCC) are no longer applicable only to government organizations but now extend to any contractor that is performing work for governments as well. As challenging and expensive as it might be to implement security practices and design security into applications throughout development and operations, not doing so from the beginning will cost more in the long run and in some cases might prevent going to market.

What is the biggest mistake you see companies in aerospace & defense making right now?

Bryczek: The biggest mistake I see companies make is assuming their legacy tools are good enough for today’s design and development environments. They simply aren’t. Legacy tools were built around document-based processes and not model-based or simulation techniques used in modern development environments. In the long run it costs more in man hours and license costs than the switch to more modern tooling.

Mulcahy: Agree here with Cary. Legacy tools prohibit companies from real collaboration and are often customized to outdated ways of working where support can no longer be given.

With more tools now available today, and in the future – the need to be open for integrations is more crucial than ever as we aspire towards the digital world

What is the most innovative thing you’ve seen in aerospace & defense this year that you anticipate other companies following suit in coming years?

Couadau: Many of the experienced players have already embraced Digital Engineering and are using it to come up with automated frameworks that alleviate certification activities. I expect that the industry will align around these practices. The entry ticket is expensive but the shortened time to market is worth it.

Bryczek: The most innovative thing I personally saw was a large aerospace company making use of internal generative AI to assist with developing specifications and planning documentation. Heavy documentation which previously took four months to author, review and approve, took only a couple of weeks. AI is spreading into many other areas of the business including training and simulation. It is most certainly being used today by warfighters in Gaza and Ukraine to create realistic training simulations to predict outcomes of various defense strategies and enhance preparedness.

Mulcahy: For an industry that is very security conscious, I’m seeing more companies embrace the cloud to get better total cost of ownership, scalability, and performance from their engineering tools. Furthermore, an increase in consortium working together to break boundaries and define new ways of working together (often across time zones and cultures) I think will become more of the norm. In addition, we see organizations utilizing companies / partners to provide strength in specific and unique areas of expertise to develop groundbreaking technology.

Do you think there will be any major disruptors in aerospace & defense in the coming year? How do you think it will impact the industry?

Couadau: We have discussed many influencing factors already: emerging technologies, environmental goals, and a changing geopolitical context are all strong forces that can challenge the status quo.

RELATED: Traceable Agile – Speed AND Quality Are Possible for Software Factories in Safety-critical Industries

What do you predict for regulation in the aerospace & defense industry in 2024?

Will those trends still be prevalent five years from now? 10 years?

Couadau: We should see the first standards emerge around AI and Machine Learning. On our end, we happen to be contributing to SAE ARP6983. We expect these standards to lay a solid foundation for safe, observable, and certifiable AI in aeronautics for the coming decades.

Bryczek: The aerospace and defense industry will continue to be challenged with environmental decarbonization initiatives such as the Paris Agreements. More to come here.

Mulcahy: Many of our customers are working on new systems in the Aerospace Industry. Whether that’s for UAV’s, Electric Vertical Take-Off and Landing (eVTOL), AirTaxis, etc, there will need to be more regulations developed here for the development of UAVs for example, but also to govern usage of the products in the sky. Furthermore, as these start to become more of the norm, regulation will need to be established for the surrounding infrastructure, usage, and purchase of these for the consumer market.

As more companies near release dates, more will be developed regarding these regulations, with of course current regulations also enhanced to better serve today’s needs.

With more global conflict at the forefront of our lives, and with other tensions continuing to escalate, I expect defense spending to be increased in anticipation of future conflicts, with new products being developed to gain advantage.

Linking with the above, I see Space being an area of further exploration in the defense sense, but also commercialization — whether it’s advancing the space race or decluttering space (as an example). I anticipate more startups in this sub-industry.