Clinical development is changing fast. To make an impact, it is crucial to stay ahead of the curve. This is why we are thrilled that ISG has named Capgemini a leader in the field.

Leveraging our expertise across strategy, emerging technology, data, AI, and operations, Capgemini supports clients in accelerating and evolving their clinical research and development programs.

Clinical development is a fast-evolving area where we are witnessing a rapid transformation. This is thanks to the ongoing integration of cutting-edge technologies and digital tools, along with innovative methods in study design, study execution, study reporting, and data re-use for purposes going beyond the primary objectives.

The 2024 ISG Provider Lens™ report explores the role of leading organizations such as Capgemini in advancing clinical research and development and life sciences as a whole. The report looks at how innovators are shaping the future; from creating the next generation of clinical operating models to maximizing value from data and smart devices. 

Read on for highlights from the report, to understand Capgemini’s role in tomorrow’s life sciences, and discover three key shifts in the evolution of clinical development.

Partnerships take us further

The ISG Provider Lens™ report showcases Capgemini’s ability to offer outstanding clinical development consulting – delivering tech-driven business outcomes using emerging technology, innovative methods of collaboration, and commercial models.

In the report, ISG note that we are enabling efficient execution of clinical trial transformation initiatives by “proactively monitoring operations, streamlining post-trial data analysis, and providing robust data foundations for protocol design and synthetic trials.”

“Capgemini pioneers transformative solutions in clinical development, advancing trial methodologies.”

Rohan Sinha, Lead Author, ISG Provider Lens™

Discover the ISG report

ISG (Information Services Group) is a leading global technology research and advisory firm. Its annual Provider Lens™ reports play an influential role in evaluating independent vendors and providers across a range of capabilities by topic and region. The positioning is based on a neutral and independent research and evaluation process.

As organizations increasingly adopt cloud services to power their digital transformation, FinOps has become crucial to deliver insight as well as optimizing and controlling cloud costs. FinOps within organizations also support the alignment of cloud strategy with sustainability goals, optimizing both cost efficiency and environmental impact.

An ever-growing cloud

Cloud computing has revolutionized the way businesses operate and the adoption of cloud is growing significantly. Predications are that developments such as Gen AI will continue the growth for years to come. Gen AI offers scalability, flexibility, and cost-effectiveness, allowing companies to focus on innovation rather than infrastructure management. However, rapid adoption comes with challenges and consequences, both from a cost perspective as well as a sustainability standpoint as cloud data centers consume significant amounts of energy and water and contribute to carbon emissions.

Back to the beginning

As organizations started adopting FinOps, the first phase of adoption was “inform.” This helped to identify data sources for cloud cost, usage, and efficiency data. This information could then be allocated, analyzed, and reported. This is also the first step in aligning your FinOps and GreenOps approach. The good news here is that much of the pre-work of the FinOps function can be recycled as there is a significant overlap in data sources and reporting structure. However, it is key to align further with the sustainability function to define the additional needs and potentially new stakeholders that need to be serviced by the GreenOps function. As before, this is the basis to start building KPI’s for benchmarking and developing metrics that will reveal the business goals to achieve a responsible usage of cloud computing.

The balancing act

Obviously, there are easy wins, such as rightsizing and eliminating waste, that will immediately deliver both savings and sustainability benefits. However, optimizing cloud usage has always been a balancing act. You can’t just look at costs as a decision factor; you want to achieve the right costs while balancing these against other factors, such as performance and security. GreenOps is adding a new dimension to the mix, and a structure is needed to make the right decisions for the organization. Adopting the Well-Architected Framework (WAF) is a highly recommended step for organizations to look at all these factors when defining the right architecture and configuration of the infrastructure needs of a workload. The WAF covers six pillars that need to be balanced:

1. Operational excellence
2. Security
3. Reliability
4. Performance efficiency
5. Cost optimization
6. Sustainability

Incorporating this approach will help to optimize cloud usage and establish a culture of accountability within the organization enabling a long-term roadmap of transformation and continuous improvement across all areas.

Keep it going

“Going green” should not be an exercise to get from sustainability report to sustainability report. It needs to be embedded in your way of working, so it requires implementation and organizational change to operationalize GreenOps using the data and capabilities that the organization has developed, building on the foundations that have been laid by the FinOps practice.

Align the stakeholders within the organization and engage with your public cloud providers to ensure transparency and to drive further improvements in sustainability.

Measure success by defining sustainability metrics that are relevant and enable continuous reporting through unified dashboarding combining financial, performance, environmental, and other KPI’s in a single dashboard. Encourage responsible cloud usage, empowering individuals by developing training programs, team guidelines, and automation policies aligned with organizational objectives.

A more sustainable cloud

The convergence of FinOps and GreenOps is essential for organizations seeking to align their cloud strategy with their sustainability goals. By leveraging the investments into FinOps, organizations can quickly deliver on their sustainability objectives. By enabling a culture of ownership and monitoring clear KPI’s, organizations can build a greener, more cost-efficient cloud ecosystem. Capgemini supports organizations to execute this by combining our knowledge of FinOps, Sustainability, and Organizational change into a joint and practical step-by-step approach. The journey toward more sustainable cloud operations is ongoing; a commitment to responsible practices will drive positive change.

Looking to go deeper into Sustainable FinOps? Check out our Sustainable FinOps Page and the Point of View on – A leaner , greener future in the Cloud.

Sources:

AWS Well-Architected – Build secure, efficient cloud applications (amazon.com)

Please reach out to me through LinkedIn if you have any queries relating to FinOps and Sustainable FinOps. Happy to help!

The future of IT is inextricably linked to cloud computing, and within that landscape, two key concepts are gaining traction: FinOps and GreenOps. These emerging practices hold the potential to revolutionize how we manage and optimize usage of cloud resources, not just for cost savings and environmental sustainability but also for optimizing business value in the cloud.

As companies gear up to meet the Corporate Sustainability Reporting Directive (CSRD), the stakes now are higher than ever, with funding risks looming for those falling short. Furthermore, the GenAI revolution intensifies the reliance on the cloud, demanding a dual focus on cost and carbon efficiency. In today’s fast-paced digital landscape, the convergence of FinOps and GreenOps has thus emerged as a strategic necessity.

The imperative for a sustainable cloud revolution: The unified framework

Sustainable FinOps – the fusion of FinOps and GreenOps – perfectly provides the imperative framework to address the urgent need for organizations to become both cost and carbon-efficient. This powerful end-to-end service leverages a unique blend of capabilities, best practices, and a cultural shift that not only empowers organizations to control dynamic cloud service expenses but also helps them meet their sustainability commitments, all under the same umbrella.

Figure 1: Complementary end-to-end service to control the continuously increasing expenses of dynamical cloud services and achieve sustainability targets simultaneously.

Combining FinOps and GreenOps into a single management framework eliminates the need for separate teams and processes, streamlining operations, and reducing overhead. This integrated view enables you to improve synergy between the two domains, identify and address potential issues more effectively, make data-driven decisions collaboratively, and lead to more informed and strategic outcomes.

Environmental, social, and governance (ESG) factors are increasingly important to stakeholders. By consolidating FinOps and GreenOps, you provide greater transparency to stakeholders, enable them to make informed decisions, and hold the organization accountable for its cloud usage. Thereby, you demonstrate a solid commitment to sustainability and align your cloud strategy with the broader corporate ESG goals.

Building the foundation of Sustainable FinOps

It is worth mentioning that the successful enablement of capabilities in Sustainable FinOps requires a well-defined strategy, a well-architected governance structure, an effective tooling and automation mechanism as well as a powerful cultural change management. In other words, if you do not pay attention to such essential building blocks, the implementation of Sustainable FinOps capabilities cannot be executed smoothly and therefore the realization of identified cost and carbon savings cannot be achieved at the desired level.

Figure 2: Our Sustainable FinOps-as-a-Service embeds dynamic and continuous sustainability and cost management capabilities into your daily IT operations.

Ready to propel towards a greener, more efficient tomorrow?

The convergence of FinOps and GreenOps in Sustainable FinOps is where the magic happens. While the concept is simple, the practice isn’t easy. Waste creeps in from multiple corners, and it takes a combination of skill and experience to keep systems running optimally. Therefore, I strongly recommend my customers consider not a one-time Sustainable FinOps engagement, but Sustainable FinOps-as-a-Service.

Figure 3: Sustainable FinOps-as-a-Service for continuous cloud efficiency and waste management.

After a one-time Sustainable FinOps engagement, waste will come back over time and therefore your organization cannot reach the optimal cloud usage curve. However, with Sustainable FinOps-as-a-Service – which provides continuous cloud efficiency management of overall cloud cost and carbon emissions – your company will tend toward optimal cloud consumption not only for the current cloud environment but also for upcoming workload migrations. It is thus an accelerator for cloud best practices adoption.

This holistic Sustainable FinOps-as-a-service approach also offers key corporate reputation benefits. While embracing Sustainable FinOps showcases your commitment to environmental stewardship, attracting talent, and fostering a culture of business, organizations can attract eco-conscious customers and investors by aligning with financial and sustainability goals.

Unleashing Sustainable FinOps values: Empower a sustainable future and generate integral value from your cloud computing investments

The future of IT belongs to organizations that encompass both FinOps and GreenOps principles. By implementing sustainable cloud strategies, businesses can optimize costs, enhance their brand image, and contribute to a greener future. This approach is not just about cost-cutting, but about building long-term resilience and achieving sustainable success in the ever-evolving digital landscape with:

• Seamlessly integrating to cloud operations
• Defining objectives, KPIs, and clear accountability for efficient governance
• Maximizing the realization of cost savings and CO₂ footprint reduction
• Increasing organizational awareness and anticipation of economic and ecological impacts of new innovative cloud services
• Improving corporate sustainability and complying with environmental regulations
• Minimizing wasted cloud resources and aligning with investments that are revenue-driven            
• Improving financial oversight, delivering immediate TCO benefits, and reducing brand risk
• Driving ownership across IT, Engineering, and businesses
• Adapting to evolving business needs while producing business value from the cloud at the lowest possible cost and carbon impact

Unlocking tomorrow, today: The endless journey of Sustainable FinOps

Remember, the journey towards sustainable IT is continuous, and embracing Sustainable FinOps is not just a strategic choice – by constantly learning, adapting, and scaling – it’s a commitment to unlocking unparalleled business value, fostering innovation, and maximizing the potential of your cloud investments, to get the future you want.

Do you have any specific aspects of this topic you’d like to explore further? I’m happy to delve deeper into any of the above-mentioned areas or even discuss specific challenges and opportunities businesses face in implementing sustainable cloud strategies. Here you can find my previous article Future IT: FinOps, GreenOps and sustainable cloud strategies where you can get more background knowledge about the synergy between FinOps and GreenOps. Looking to go deeper into FinOps? Check out our FinOps Services

Sustainable IT starts with public cloud…

Driven largely by the Paris Agreement of 2015, businesses of all sizes are increasingly committed to sustainability. From reducing carbon emissions to implementing eco-friendly practices, there is a growing push towards sustainable business operations.

This comes at a time when rapid growth of the digital economy is significantly increasing energy consumption and carbon emissions. The rise of computing has led to concerns about its environmental impact. As companies strive to become more environmentally conscious, a green concept for future IT has become a critical component of sustainable business operations.

The role of public cloud will be central to sustainable IT. However, when managed haphazardly, public cloud can rapidly lead to waste and inefficiency – virtually bottomless and out of sight, public cloud tempts employees to shoot first and ask questions later. On the other hand, properly managed public cloud provides consistent energy savings in comparison to traditional on-premises data center solutions. This comes down to a conscious choice that each organization faces.

…and continues with FinOps

Leveraging energy-efficient technologies, optimizing resource usage, promoting remote work, developing green computing practices, and enabling collaboration among users and organizations, public cloud has the potential to significantly reduce carbon emissions compared to traditional on-premises IT infrastructure (by up to 95%).

Therefore, when I work with organizations to help them reduce their carbon footprints, one of my first recommendations is migrating their workloads to public cloud (if an organization hasn’t made that move yet). However, the cloud sustainability journey doesn’t finish with an eco-friendly public cloud environment; this is where it begins. Once the workloads are landed in the public cloud, it is important to run them with a sustainable cloud operation approach. That’s where FinOps comes in.         

The role of FinOps in cloud sustainability

FinOps (short for financial operations) is a cloud financial management discipline and cultural practice that focuses on tracking and optimizing cloud spending. It does so by bringing together IT, finance, engineering, and business teams, and providing a cultural mechanism for teams to manage their cloud costs, where everyone takes accountability of their cloud usage.

FinOps – when applied correctly – ensures the optimal usage of cloud resources, which in turn promotes not only cost efficiency but also energy savings and carbon emissions reductions. In other words, if you do not build such a cost-usage-control framework in your public cloud environment – where resource deployment is unlimited due to a pay-as-you-go cloud consumption model – this suboptimal cloud usage leads to underutilization and waste in the form of excess energy consumption and carbon emissions. Therefore, FinOps is sustainable by design.

FinOps helps organizations achieve their sustainability goals in the cloud by implementing cloud cost optimization techniques like:

• Establishing FinOps governance and policies
• Rightsizing and autoscaling of elastic resources
• Shifting workloads to containers
• Automated scheduling of compute services
• Decommissioning of idle and unused resources
• Reducing log ingestion
• Optimizing storage tier and redundancy
• Refactoring and mutualizing of applications by cloud native architectures (e.g., plarform as a service)
• Budgeting, forecasting, and overspending alerts
• Managing anomalies
• Establishing FinOps culture and accountability
• Switching usage-based pricing to new consumption models (reservations, saving plans, spot instances, etc.) for more efficient resource usage 

Brothers-in-arms – how FinOps supports GreenOps

FinOps and GreenOps are two distinct methodologies that – when used together – form a powerful strategy for organizations looking to optimize their cloud usage and reduce their environmental impact.

While FinOps is focused on managing cloud consumption, GreenOps is focused on implementing sustainable practices within an organization’s operations. It involves developing strategies that prioritize environmental sustainability while still achieving business objectives like reducing waste, promoting renewable energy sources, using eco-friendly materials and processes, and promoting a culture of sustainability and environmental responsibility. By identifying and mitigating carbon emissions, organizations can reduce their impact on the environment and contribute to a more sustainable future.

There is a bit more to it though. GreenOps encompasses everything an organization does to reduce the carbon footprint of their cloud program. This might include relocating resources to companies or regions where sustainable energy is used or using code that requires less energy to run. But the greatest contribution by far is usually – in my experience – made by FinOps.

The most obvious way is through optimization of cloud resource consumption, which naturally reduces energy consumption. FinOps can also help companies choose the most environmentally friendly cloud service providers. Best of all, the gains made by FinOps allow for continuous improvement and ensure that a company remains on track to achieve its sustainability targets.

FinOps and GreenOps can create common work areas with unified dashboards, enabling teams to make joint decisions. A great example of how FinOps and GreenOps can work together is through the optimization of supply chains. Together, teams can identify areas where supply chain inefficiencies are leading to unnecessary energy consumption so that organizations can reduce their carbon emissions and save money. FinOps can be used to identify supply chain inefficiencies, while GreenOps can be used to implement sustainable supply chain solutions.

Future IT: Sustainable and cost-effective cloud operations

Sustainability is a natural benefit of FinOps – one of many. In fact, FinOps can be an essential framework for organizations looking to reduce their environmental impact while saving money. Moreover, when combined, FinOps and GreenOps can create a more holistic approach for companies to manage their cloud resources in a sustainable and cost-effective way while also maximizing the business value of public cloud.

Incorporating FinOps recommendations into cloud operations can help drive both sustainability and cost-effectiveness. Creating a vision for end-to-end cloud operations and decarbonizing procurement are essential first steps that enable teams to identify and optimize savings opportunities. Continuous improvement and automation, empowering teams to take action, and promoting a culture of green accountability is crucial for long-term success. By adopting these measures, businesses can achieve their financial goals while also contributing to a more sustainable future.

Looking to go deeper into FinOps? Check out our FinOps services & download the whitepaper developed by IDC and commissioned by Capgemini to explore the full potential of FinOps and the value it brings to every stage of the cloud journey.

Knowledge is power

In the era of digital transformation, the phrase “knowledge is power” takes on a new dimension. The power of knowledge is no longer confined to the possession of information, but extends to the ability to use this information effectively for strategic decision-making. This is where predictive analytics comes into play. It not only helps businesses navigate the data deluge, but also transforms raw data into actionable insights.

Predictive analytics enables businesses to leverage their data to anticipate customer needs, optimize operations, and drive strategic decision-making. It empowers organizations to move from reactive to proactive operations, thereby gaining a competitive edge in the market.

Moreover, predictive analytics democratizes data, making it accessible and understandable by all stakeholders in an organization. This fosters a data-driven culture where every decision is backed by data, reducing biases and improving overall business outcomes.

In the ever-evolving realm of contemporary business, a multitude of systems and solutions has emerged, tailored to address the diverse and complex requirements of organizations.

However, this abundance of systems often leads to the generation of massive volumes of data. The sheer magnitude of information produced is overwhelming for businesses, posing challenges in terms of analysis and the extraction of meaningful insights. Knowledge is a vital asset in today’s world, but it needs to be built on reliable information extracted from data and IT systems. A decision-making process supported by data has become the digital holy grail.

Currently, 402.74 million terabytes of data are created every day (“created” includes data that is newly generated, captured, copied and consumed).[1] Not all IT enterprise data needs to be managed with the same frequency or picked up for analysis.

The information overload may lead to decreased productivity, and an increased likelihood of overlooking genuinely important alerts. To foster a more efficient and focused work environment, businesses need to implement intelligent filtering mechanisms and prioritize notifications, ensuring that employees receive only the pertinent information necessary for decision-making and problem resolution.

Operational costs of out-of-control data management

Building an entire team of specialists to sift through data can significantly escalate operational costs for a business. According to the Komprise 2023 State of Unstructured Data Management Report, the majority of enterprise IT organizations are spending over 30% of their budget on data storage, backups, and disaster recovery.[The recruitment, onboarding, and continuous training of data experts requires substantial financial investment. Moreover, maintaining a specialized workforce demands ongoing salaries, benefits, and infrastructure, further adding to the financial burden.

In the context of data analysis, operational costs extend beyond the obvious financial expenditures. They also encompass the time and resources invested in data management. As businesses grapple with increasingly complex data ecosystems, the operational costs associated with data analysis can skyrocket.

One significant cost factor is the continuous evolution of data technologies. Keeping up with these advancements requires ongoing training and upskilling of the data team. Furthermore, as data volumes grow, so does the need for robust and scalable infrastructure. This not only includes the physical hardware, but also the software solutions for data storage, processing, and analysis.

Another often overlooked cost is the opportunity cost. When specialists spend their time sifting through data, they are diverted from other strategic tasks that could potentially bring more value to the business. Different studies estimate that HR teams using manual data handling spend between 15% and 50% of their time managing information by hand.[3] This is where predictive analytics can make a significant difference. By automating the data analysis process, predictive analytics frees up specialists to focus on strategic decision-making and innovation.

Lastly, there’s the cost of errors. Manual data analysis is prone to them, which can lead to misguided decisions and strategies. These mistakes can be costly for businesses, both financially and in terms of reputation. Errors in data processing can cost organizations an average of $12.9 million each year.[4] Predictive analytics, with its automated and accurate analysis, can significantly reduce the risk of such errors.

In conclusion, while the operational costs of data analysis are multifaceted and substantial, the adoption of predictive analytics can help businesses optimize these costs effectively. By automating data analysis, reducing errors, and freeing up specialists for strategic tasks, predictive analytics can transform the cost center of data analysis into a strategic asset for the business.

Sustainability versus manual data handling

Manual systems can quickly become outdated, requiring periodic upgrades or replacements that generate electronic waste and further resource consumption.

Major companies often mass produce single-use data that is generated and discarded quickly in manual processes, which impacts a company’s sustainability by increasing waste and resource consumption.

Single-use data refers to data that is collected and used for a single purpose or event, often without being stored, analyzed, or reused for other purposes. This practice can have significant implications for a company’s sustainability. It leads to higher paper usage, greater energy consumption for data entry and storage, and an increased environmental footprint due to the frequent disposal and replacement of outdated materials.

Without a strategy for reusing data, companies may find themselves repeatedly collecting similar data for different purposes, leading to inefficiencies and increased costs.

By addressing these inefficiencies and missed opportunities associated with single-use data, companies can enhance their sustainability efforts, reduce their environmental impact, and gain a competitive advantage in their industry.

A case for predictive analytics for your IT

From a predictive analytics standpoint, implementing such a system provides tangible benefits for businesses, including a significant reduction in the impact on operations by proactively addressing potential issues before they escalate. By leveraging insights from connections between performance alerts, including monitoring and observability system data such as:

• Metric data stream
• Events
• Logs

As well as service management data, including configuration management system data such as

• CI asset/relationships
• Topology information
• Resolver group information

Service management system data such as change tickets and knowledge management information for known issues the predictive analytics platform empowers the delivery team to address technical issues proactively, minimizing downtime and enhancing overall service health. 

For example, warning alerts coming from multiple infrastructure nodes would typically result in tickets for the different resolver teams responsible for each technology. But by referencing a service management CMDB (Configuration Management Database) and service topology trees, predictive analytics can quickly correlate multiple alerts to create a probable root cause ticket for the relevant resolver team, reducing time for service restoration or preventing service interruption altogether.

Conversely, time series alert data, including system resource utilization thresholds such as CPU utilization, may be analyzed for recurring breach patterns. Such cyclical alerts can be correlated with service management information such as a planned maintenance window for nightly backups, which could prevent false positive tickets and decrease work for resolvers.

Predictive analytics can effectively reduce the number of Priority 1 (P1) tickets by analyzing historical data, patterns, and trends to identify potential issues before they escalate to critical levels. By employing machine learning algorithms and statistical models, predictive analytics anticipates potential incidents based on past occurrences, enabling proactive intervention.

In essence, predictive analytics acts as a preemptive tool, helping organizations stay ahead of critical incidents and maintain a more stable and efficient IT environment.

From our experience, for clients struggling with conducting root cause analysis, reactive instead of proactive problem identification, and a low success rate in detecting patterns in problem analysis, we were able to provide tangible outcomes by implementing predictive intelligence (PI).

Based on a survey conducted on the problem management teams of certain projects, we can point out:

• 100% of users implementing the PI solution
• 20% time saved comparing to manual work
• For 80% of the users, the PI dashboard enhanced the analysis process, improving overall problem handling.

Other benefits include:

• Identification of patterns that evade manual detection, enabling valuable insights to enhance the operational efficiency of the problem management process
• Enhanced ability to identify major incidents in advance, avoiding potential disruptions
• Enabled data-driven decisions for proactive problem identification
• Reduced manual efforts, saving valuable time and resources for higher-value tasks.
  

Summary

Harnessing the power of data is crucial for strategic decision-making. Predictive analytics elevates this capability by transforming vast amounts of raw data into actionable insights. It enables businesses to anticipate customer needs, optimize operations, and proactively address potential issues. This shift from reactive to proactive operations provides a significant competitive advantage.

Predictive analytics not only democratizes data access, making it understandable for all stakeholders, but also fosters a culture of informed decision-making. This reduces biases and enhances overall business outcomes. By automating data analysis, predictive analytics lowers operational costs, minimizes errors, and frees up specialists for strategic initiatives. It supports sustainability by reducing reliance on manual data handling, leading to lower operational costs and waste.

Furthermore, predictive analytics enhances IT operations by proactively addressing potential issues, correlating alerts, and preventing disruptions. This transformation turns data analysis from a cost center into a strategic asset, driving efficiency, accuracy, and sustainability in modern business environments.

Feel free to contact us if you’d like to get familiar with predictive analytics solutions for your business.

[1] https://explodingtopics.com/blog/data-generated-per-day

[2] https://www.komprise.com/glossary_terms/data-storage-costs
[3] https://www.peoplexcd.com/insights/cost-and-likelihood-of-inaccuracy-in-manual-data-handling/
[4] https://www.cloverdx.com/blog/is-manual-data-processing-making-your-organization-error-prone

Capgemini’s Chief Innovation Officer Pascal Brier shares his insights on how academia and industry come together to transform ideas into solutions, empower future talent, and accelerate innovation.

Rewriting the Future: Shaping the Next Through Academic Collaboration

At Capgemini, we have always believed that the synergy between academia and business is a powerful driver of innovation. Academia contributes cutting-edge research and fresh perspectives, while technology and business organizations provide the foundation to turn ideas into scalable solutions. By merging theoretical knowledge with practical implementation, Capgemini shapes the next, optimizes operations, and drives sustainable growth, making them a preferred transformation partner for our clients across the globe.

At the recent Paris Motor Show 2024, along with Anne-Laure Cadene, Head, Industry Partnerships, we discussed how academia brings top-tier talent and a sharp focus on advancing the frontiers of research, while industry builds practical applications and the ability to scale innovations quickly. I firmly believe that one of the most challenging aspects of innovation is ensuring a seamless transition from leadership and great ideas to scalable development, and with the surge of disruptive technologies across all scientific domains, no company can master everything alone, making it crucial to build an ecosystem of partners for rapid progress, especially in fields like autonomous systems and robotics.

Innovation to Impact: How Capgemini’s Strategic Academic Partnerships Drive Innovation and Real-World Solutions

We’ve observed that one of the major challenges in innovation today is ensuring a seamless transition from visionary ideas to scalable, practical applications. Organizations constantly face a surge of disruptive technologies across various scientific fields, making it challenging to master every innovation independently.

The solution? At Capgemini, we believe in fostering strategic academic partnerships that bridge the gap between vision and practical application. Our collaborations with prestigious universities like Oxford, MIT, and Berkeley accelerate research on critical topics such as trusted autonomous systems, sustainability, and engineering advancements.

This approach ensures our clients benefit from reliable, scalable technologies. Our commitment to applied research and impactful innovation bridges the gap between groundbreaking science and practical, client-focused results, driving forward-thinking solutions that meet today’s challenges and anticipate tomorrow’s needs. I am excited by the tangible impact of our collaboration and the limitless possibilities it unlocks. Let’s rewrite the future together!

Visit our Innovation Ecosystem to discover how we’re shaping the future of innovation!

How will digitalization accelerate transformation in welfare services throughout 2025?

According to an OECD report, 50% of employment agencies are already utilizing artificial intelligence (AI). However, despite significant strides towards digitalization, welfare organizations are not fully realizing the potential of AI to improve user-centricity, foster innovation through collaboration, and speed up accessibility advancements. They have also yet to make the best use of increasingly sophisticated AI—or what’s known as agentic AI. A focus on these areas underpins the key trends for welfare services in 2025. 

While the use of AI may have contributed to what the Journal of Social Policy describes as a 50% increase in the delivery of social benefits, the fact remains that there is huge untapped potential for digital tools to help create a more inclusive, sustainable and effective welfare system for future generations.  Our work with welfare agencies worldwide has enabled us both to identify the trends shaping welfare services this year and to help organizations seize the opportunities these trends present, notably in advancing the use of AI.

2025 – a year of maturity or uncertainty?

Will 2025 be the year of maturity for agentic AI in social welfare? Being a crucial touchpoint for public sector interactions, welfare organizations stand to benefit immensely from the potential of AI. However, the journey towards maturity involves strong executive support, robust technological infrastructure, a solid data foundation, a trained workforce, and a clear AI strategy.

Even with all of these building blocks in place, welfare organizations must also acknowledge—and address—the associated challenges of AI. These include ethical considerations such as the potential for algorithmic bias, which might lead to unfair treatment of certain groups. Data protection is also vitally important: Clear governance and transparency are needed for all tools handling sensitive personal information. And organizations must consider how greater usage of AI can be compatible with their commitments on sustainability: A prompt on ChatGPT consumes 100 times more energy than a Google search.  

Finally, while agentic and other forms of AI can contribute much to the transformation of welfare services, they should not be regarded as the only solution for digitalization within the welfare sector. Our work with Chief Digital Officers in welfare organizations often reveals a need to prioritize other pressing issues – for example outdated legacy systems, and gaps in the mobile friendliness of some public sector websites. All of these have their place in an ongoing story of digital transformation, and all can contribute in different ways to helping agencies deliver more for less.

Not long ago, using virtual reality to train aerospace technicians or augmented reality to assist in maintenance felt like science fiction. Today, immersive technologies are soon to become essential.

The aerospace and defense industry is under pressure. Airlines are struggling to meet surging travel demand, supply chain disruptions are delaying production, and a retiring workforce is creating a skills gap. At the same time, sustainability mandates are pushing manufacturers to improve efficiency while reducing waste.

Simply hiring more workers or relying on traditional methods won’t be enough. To train faster, streamline production, and enhance collaboration, companies need new solutions—and immersive technologies are filling the gap. Augmented reality (AR), virtual reality (VR), and extended reality (XR) are already transforming how teams learn, work, and innovate.

Once considered experimental, these tools are now enterprise-ready and scalable. Companies that embrace them today will lead the next era of aviation.

What is immersive technology and why does it matter?

Immersive technologies—augmented reality (AR), virtual reality (VR), and extended reality (XR)—merge digital and physical worlds, transforming how aerospace companies train employees, design aircraft, and collaborate. Once seen as experimental, these tools are now scalable and practical, solving some of the industry’s biggest challenges.

• Augmented Reality (AR) overlays digital information onto the real world, helping technicians see schematics, step-by-step assembly instructions, or system diagnostics in real-time.
• Virtual Reality (VR) creates fully simulated environments where pilots, engineers, and technicians can train or test designs without physical aircraft.
• Extended Reality (XR) is an umbrella term covering both AR and VR, along with mixed-reality applications that blend real and digital elements.

Aerospace is under growing pressure to produce more, train faster, and operate with greater precision. A retiring workforce is creating a knowledge gap just as aircraft systems become more complex, making traditional training and manufacturing methods harder to sustain. At the same time, rising production demands leave little room for inefficiencies or delays. Immersive technologies are becoming essential tools in this environment, allowing companies to modernize training, refine manufacturing processes, and improve collaboration across global teams. As these tools become more advanced and widely adopted, they are shaping the future of how aircraft are built, maintained, and operated.

Misconceptions about immersive technologies

There’s a common assumption that immersive technology is about replacing human expertise with automation. In reality, it’s about enhancing collaboration, efficiency, and safety by putting better tools in the hands of experts.

• It doesn’t replace human intuition—it augments it. Pilots, engineers, and technicians still rely on expertise, but immersive tools provide deeper, faster, and more effective training than traditional methods.
• It’s not just for training: While often associated with workforce development, immersive technology also improves design visualization, remote troubleshooting, and real-time collaboration across supply chains.
• It’s already proving its value: Early adopters are seeing real cost reductions from shorter learning curves, fewer errors, and faster approvals in manufacturing and sales.

Immersive technology is no longer something aerospace companies can afford to wait on—it’s a strategic advantage that will define the industry’s next era.

How immersive technology makes A&D training more effective

For decades, aerospace training has relied on a combination of classroom instruction, hands-on mentorship, and access to real aircraft. But as fleets grow more complex and skilled technicians become harder to find, traditional methods are proving too slow, too expensive, and too difficult to scale. The industry needs a faster way to train the next generation of workers—without grounding aircraft or pulling seasoned experts away from critical operations.

Immersive technologies are stepping in to fill this gap. AR, VR, and XR are transforming training by creating realistic, repeatable learning environments that accelerate skill development while reducing costs. A trainee can now enter a fully simulated cockpit, interact with controls, and practice emergency procedures long before stepping into a real aircraft. Maintenance crews can rehearse engine repairs in a virtual hangar, diagnosing system failures without needing access to physical components.

For technicians, the ability to train in virtual environments means they no longer have to wait for a grounded aircraft to practice troubleshooting. Instead, they can work through real-time system failures in a digital twin of a cockpit, repeating complex repairs as many times as needed before applying them in the field. Meanwhile, AR overlays are changing on-the-job training by projecting live system data onto real aircraft, guiding workers through intricate maintenance tasks step by step.

The impact of these technologies is already visible. Companies using immersive training are seeing shorter onboarding times, fewer errors, and a workforce that adapts faster to new aircraft systems. As aerospace companies race to fill skill gaps and scale training efficiently, immersive learning is shifting from an experimental tool to an operational necessity.

A new era of speed and precision in aerospace production

Bringing an aircraft from concept to reality is an intricate, high-stakes process. Every component must fit together with absolute precision, and even minor errors can cause costly delays. Yet, many aerospace manufacturers still rely on 2D blueprints, static models, and siloed workflows, making it difficult for teams to spot issues early or adapt quickly when problems arise. As demand for faster production grows, so does the need for smarter, more connected manufacturing processes—and immersive technologies are making that possible.

By AR, VR, and digital twins into production workflows, manufacturers can detect and resolve issues before they disrupt the assembly line

• Engineers no longer have to rely on paper schematics. Instead, they can step inside a virtual aircraft, interacting with a full-scale digital twin to test how components fit together before manufacturing begins. This prevents costly design flaws from making their way onto the factory floor.
• On the production line, AR overlays provide real-time visual guidance to technicians. Workers assembling complex components can see precisely where parts should be placed, ensuring accuracy while reducing rework and waste. Maintenance teams can also use AR to overlay live system data onto real aircraft, helping them diagnose issues faster.
• VR simulations allow production teams to refine workflows before making physical changes. Instead of shutting down a line to test new processes, teams can rehearse different assembly techniques in a fully simulated factory environment, identifying bottlenecks and optimizing efficiency without disrupting operations.

Some manufacturers are already adopting enterprise-scale digital twins to integrate immersive tools more effectively. For example, Capgemini’s partnership with Unity is expanding real-time 3D visualization capabilities in aerospace, allowing companies to create highly detailed, interactive models of aircraft that improve both design validation and production efficiency.

These immersive technologies are reducing errors, accelerating production, and cutting waste. Catching design flaws early prevents costly rework, while improved accuracy keeps assembly moving efficiently. With greater visibility across operations, manufacturers can scale to meet demand without compromising quality.

Customers now expect immersive buying experiences

Passenger expectations for comfort, customization, and cutting-edge design are higher than ever, and airlines and private jet operators must respond. Cabin configurations, materials, and layouts are no longer just engineering decisions—they are central to the customer experience. Yet, traditional design methods often rely on static renderings and physical mockups, making it difficult for buyers to fully grasp what their aircraft will look and feel like.

Immersive technologies are changing that. AR and VR allow buyers—whether airlines configuring new fleets or private customers designing bespoke interiors—to step inside a fully realized virtual cabin. They can walk through different seating arrangements, test lighting schemes, and see how materials look in various conditions, all before making final decisions. This level of interaction helps ensure expectations align with reality, reducing costly revisions later in production.

For aircraft manufacturers and interior designers, this shift streamlines the sales and customization process. When customers can explore their options in a virtual environment, decisions happen faster, back-and-forth revisions decrease, and confidence in the final product increases. In a competitive market where differentiation is key, offering an immersive buying experience is quickly becoming an industry standard.

Collaboration without boundaries

Aerospace production and maintenance require expertise from specialists spread across different locations, making collaboration a persistent challenge. Immersive technologies are transforming how teams work together by allowing engineers, technicians, and designers to interact in real time, no matter where they are.

For maintenance teams, AR-powered remote troubleshooting enables technicians in the field to connect with experts across the world, receiving step-by-step repair guidance without needing an on-site visit. Engineers and production teams can conduct virtual design reviews, stepping inside a shared 3D model of an aircraft to inspect components, evaluate potential issues, and refine designs before production begins. Even training programs benefit, as high-risk tasks can be practiced in controlled virtual environments, allowing workers to gain hands-on experience without real-world consequences.

By eliminating geographical barriers and enabling real-time collaboration, immersive technologies are making aerospace operations more efficient, reducing downtime, and ensuring that expertise is always within reach—no matter where a team is located.

The costs—and savings—of immersive technologies

Immersive technologies require upfront investment, but for aerospace companies, the long-term savings and efficiency gains far outweigh the costs. As hardware prices drop and digital tools improve, companies that adopt now are seeing faster training, fewer manufacturing errors, and reduced operational waste.

Costs of adoption

• Hardware & software – AR headsets, VR systems, and simulation tools require an initial investment, but costs have fallen significantly.
• Digitization efforts – Older aircraft models may lack digital twins, requiring companies to build virtual replicas before immersive tools can be fully utilized.
• Integration with legacy systems – Many aerospace companies still rely on outdated IT infrastructures, slowing large-scale adoption.

Return on investment

• Faster workforce training – Virtual training environments allow new hires to upskill quickly, reducing onboarding time and labor shortages.
• Improved manufacturing Accuracy – Real-time 3D visualization helps catch design flaws early, minimizing rework and material waste.
• Reduced downtime & travel costs – AR-assisted remote troubleshooting means technicians can receive expert guidance instantly, instead of waiting for specialists to be on-site.

Despite the challenges, immersive technologies are proving to be a cost-cutting tool rather than an expense. As adoption grows, their impact on efficiency, precision, and production timelines will only increase.

The leadership imperative

Aerospace has always been defined by innovation. From the first powered flight to the rise of commercial aviation, the industry has evolved by embracing new technologies that push the limits of what’s possible. Today, immersive technologies represent the next major shift—one that is already transforming how aircraft are designed, built, and maintained. But tools alone don’t drive change. Leadership does.

Early adopters are already seeing the impact—faster training, more precise manufacturing, and seamless collaboration across global teams. Yet, these technologies can’t be implemented in isolation. For immersive solutions to reach their full potential, aerospace leaders must take an active role in driving digital transformation. This means investing in the right digital infrastructure, fostering a culture of innovation, and aligning teams around a shared vision.

Companies that wait too long risk falling behind as competitors streamline operations and reduce costs with immersive solutions. The opportunity is here now—but the industry’s next leap forward depends on the decisions made today.

Learn more:

Digital Continuity in Aerospace

Digital Twins in Aerospace and Defense

Intelligent Supply Chain for the Aerospace and Defense Industry

TechnoVision 2024: Aerospace and Defense

The aerospace industry is set for a decade of rapid expansion, but behind the surge in demand lies a growing challenge—keeping up with the maintenance needs of a swelling global fleet. The International Civil Aviation Organization (ICAO) forecasts the demand for air traffic will increase by an average of 4.3% per annum over the next 20 years fueling the need for new aircraft.

As airlines push for greater efficiency amid growing backlog, maintenance, repair, and overhaul operations are under pressure to scale. However, supply chain disruptions, engine durability issues, and delayed retirements are straining the system, demanding urgent innovation in MRO strategies to sustain this growth.

Evolving MRO strategies: Key trends, investments, and challenges

Maintenance, Repair, and Overhaul (MRO) operations are the backbone of aviation, ensuring aircraft remain airworthy, safe, and available for service. But as global fleets expand and aircraft lifespans extend, the MRO sector is under mounting pressure to scale efficiently while navigating increasingly complex challenges.

MRO is often associated with heavy maintenance cycles, which require aircraft to be taken out of service for months at a time. These checks—conducted every 60, 90, or 120 months, depending on usage and OEM recommendations—can involve a complete overhaul. A D-check, for example, requires stripping the aircraft down to its core: engines, landing gear, interior panels, and even lavatories are removed for inspection and restoration. Similarly, engine MRO providers spend three months restoring engines to full performance. In a typical MRO process, incoming inspections are also often performed before the disassembly of modules and assembly begins.

The financial stakes are massive. Air transport MRO spending is expected to reach $124 billion by 2034, growing at a CAGR of 4.88% from 2025. Engine maintenance alone accounts for 45% of this spend, making it the largest cost driver, followed by component maintenance (21%), line maintenance (19%), and airframe overhauls ($6 billion).

But ramping up MRO operations is not simply a matter of scaling capacity. Several key challenges are slowing the industry’s ability to keep pace with demand:

Skilled Workforce: The industry faces a brain drain of experienced engineers and technicians, with 690,000 new MRO technicians needed over the next 20 years to sustain global operations.

Availability of parts: A shortage of critical components—such as castings, engine assemblies, and repair shop capacity—is straining MRO service providers, leading to extended turnaround times (TAT) and making it increasingly difficult to meet operational targets.

Licensing and compliance issues: MRO service providers must adhere to strict safety standards and keep thorough documentation required for airworthiness verification by regulatory agencies. Intense FAA/EASA audits of MRO provider’s documents, processes, stores, AME licensing, stock referring and parts issued or fitted in the aircraft, etc., which are lengthy and logistically cumbersome processes.

Capacity and infrastructure constraints: As more aircraft remain in service longer, MRO facilities are struggling to keep up with demand, requiring significant investment in new hangars, tooling, and workforce expansion.

Shifting markets and emerging players

The commercial aircraft MRO market remains highly fragmented, with numerous providers offering specialized services at both global and regional levels.

Leading players such as GE Aviation, AAR CORP, Safran SA, RTX Corporation, and Lufthansa Technik AG have traditionally dominated the industry, particularly in North America and Europe. However, the market is undergoing a significant geographic shift, with Asia-Pacific emerging as a key growth hub.

Driven by rising air travel demand and fleet expansion, the Asia-Pacific region is projected to see the highest MRO growth between 2025 and 2030. The region currently operates one-third of the global commercial aircraft fleet, and the fleet in the area is expected to reach over 13,000 aircraft by 2031, with China’s airline fleet accounting for over 45% of the region’s total.

Additionally, the extension of airline lease contracts in Asia-Pacific has increased the average aircraft age to between 18 and 24 years. This trend has increased the number of in-service aircraft while reducing overall retirements, driving greater demand for MRO services to support fleet longevity and maintenance needs in the region.

The limitations of traditional MRO solutions

MRO operations rely heavily on labor-intensive paperwork, making it difficult to maintain agility and responsiveness.

Traditionally, resource planning and scheduling in MRO operations have been manual processes, carried out in silos with limited data integration and minimal cross-functional collaboration between engineering, procurement, logistics, and accounting divisions. Time and cost estimation, capacity planning, and workload assessments still rely heavily on the experience and maturity level of individual technicians, making the process inconsistent and difficult to optimize.

The lack of accurate workload estimation significantly impacts costs and Turnaround Time (TAT). Since an exact assessment of time and effort is only possible after disassembling a system or component, the true scope of work—and the necessary equipment and expertise—remains unknown until the teardown process begins. Ordering spare parts only after disassembly adds further delays, as lead times for procurement, receipt, and acceptance extend the overall TAT.

Beyond scheduled maintenance, unplanned aircraft visits to MRO facilities introduce even greater complexity. With most processes still manual, predictive maintenance remains a challenge due to limited access to historical data, making decision-making more reactive than proactive. Additionally, the lack of structured knowledge retention is hampering workforce development, slowing technician autonomy, and making it harder for organizations to build a skilled and efficient MRO workforce.

Technology adoption & embracing digital transformation

An integrated, enterprise-wide IT solution for engine MRO Service providers can introduce a high level of intelligent automation, integrating people, processes, and data at a single platform. This transformation enables MRO organizations to achieve key objectives, including:

• Reduced TAT and cost optimization
• Integrating people, process and capacity
• Collaboration with all the stakeholders/ process owners across the lifecycle
• Real time monitoring and analysis of operational efficiencies

MRO organizations are investing in artificial intelligence, robotics, drones, big data, and blockchain technologies to improve operational efficiency of MRO activities and achieve the above goals.

With huge amounts of historical data available with MRO service providers,coupled with matured Machine Learning Models and advancements in Artificial Intelligence, it is possible to make accurate predictions about when a repair job could come in next, which spare parts are most likely to be on demand and what the associated costs and risks of any unanticipated event, taking predictive maintenance to much efficient level and optimized inventory management.

The adoption of drones, robotics, and vision systems has also accelerated inspection and anomaly detection, making them faster and more precise. Meanwhile, Robotic Process Automation (RPA) is helping MRO service providers automate backend processes, enhancing overall operational efficiency and reducing manual workload.

Conclusion

The MRO industry is set for continued growth, driven by a focus on efficiency and high productivity. To balance TAT and execution costs while delivering cost-effective solutions, MRO service providers are increasingly investing in intelligent enterprise software. These advanced systems streamline and automate critical operations, including contract planning, maintenance execution, performance reporting, and invoicing, ensuring greater precision, efficiency, and scalability.

Capgemini is actively working with customers in the MRO space to turn around digital and intelligent services in the space enabling our customers to optimize operations and enable a more proactive and predictive approach to MRO operations.

Meet with us at AeroIndia 2025 (Hall H, Booth, 1.7) to discuss the transformative power of digital technology to transform MRO. Click here to learn more about our presence and follow Capgemini A&D on LinkedIn for updates from my colleagues.

Learn more:

Digital Continuity in the Aerospace Industry

Digital Twins in Aerospace and Defense

Intelligent Supply Chain for the Aerospace and Defense Industry

TechnoVision 2024: Aerospace and Defense