Emotional intelligence (EI) is the ability to recognize, understand, and regulate people’s emotions. There is increasing recognition within the workforce of the appetite for EI, and of the need for organizations to satisfy this demand.

In this blog, we look at the business arguments for change, key factors in its execution, and routes organizations can take towards a more emotionally intelligent workforce.

Business benefits

The subject is topical because of a recent report on the subject that has been published by the Capgemini Research Institute. The report pointed out that it wasn’t only teams and individuals who benefit from developing a greater capacity for emotional intelligence. Research conducted for the report found that, on average, 60% of the surveyed organizations realized significant benefits by having employees who display high EI.

The report aimed to quantify these benefits. Taking a conservative approach, it assumed that 10% of benefits from the survey results would translate into an actual return for organizations, leading to an incremental gain of $6.7 million. This, the report said, would amount to a return of up to 2.2 times the investment made, i.e., an annualized return of up to 29%.

A more optimistic assessment would assume that 20% of benefits from the survey results would translate into an actual return, leading to an incremental gain of $13.3 million. This would amount to a return of up to 4.3 times the investment made, i.e., an annualized return of up to 62%.

The Capgemini Research Institute maintains that there are four key areas on which organizations should focus to build a more emotionally intelligent workforce:

• Customize existing learning programs to integrate EI – emotional intelligence may be a skill that people possess innately and to differing degrees, but that doesn’t mean it can’t be taught or enhanced. Organizations should:
• Identify the key EI skills that are important for their workforce – requirements may vary from one enterprise to another – because, for instance, of the market in which they operate
• Identify and develop targeted training by career levels and functions – one size does not fit all. While EI training is important in leadership roles, there is also a need to focus on mid-management and on more junior levels. Some organizations go further, and identify particular groups and individuals where benefits may be greatest
• Assess EI skills within the organization – to do this, businesses should first establish a continuous EI assessment framework, examples of which are discussed in the report.

• Modify recruitment processes to include the evaluation of EI – the report declared that an evaluation of EI should be an integral part of every good hiring decision, and that therefore organizations need to think more creatively. They need to determine the recruiting channels where they could also look for candidates for high EI, and attract a more diversified talent pool. They also need to think about building EI into their hiring practices, starting with effective assessment tools.

• Use an EI lens when promoting and rewarding talent – the Capgemini Research Institute report found that more than two-thirds (69%) of employees would be willing to invest in their EI skills if they are provided feedback on it. Employees were also asked about what would motivate them to learn new EI skills. The top three responses, in order, were:
• Monetary benefit (e.g., higher raises in wages/salary)
• Organizational sponsorship for EI training and value addition to their CV and profile to move jobs/roles
• Opportunity to safeguard their job against increasing automation/AI.

We see clearly here that there is a greater need for organizations to incorporate EI assessment and evaluation into promotion, performance management and reward practices.

• Use technology for building a high EI workforce – technology should be used to measure EI in the workforce and also to deploy programs for training employees in EI. This, the report tells us, is still an area in which organizations are yet to invest significantly.

A commitment worth making

Planning for, and investing in, emotional intelligence may require a foray into what is new territory for some organizations, but it’s worth the effort. The benefits that were quantified earlier in this post are enumerated in the Capgemini Research Institute report as enhanced productivity, high employee satisfaction, increased market share, and reduced attrition.

Nurturing emotional intelligence is the right thing to do, not just for senior people, but for all teams and individuals. It’s beneficial not only to employees, but to customers, to suppliers, and hence to the business as a whole. It is, in short, an investment that can deliver dividends for everyone.

Read the Capgemini Research Institute’s full report entitled “Emotional Intelligence – the essential skillset for the age of AI” – that investigates the increasing importance and growing relevance of emotional intelligence in the age of automation and AI.

To find out more about how Capgemini’s Digital Employee Operations can transform your HR function and employee satisfaction, contact: aarti.srivastava@capgemini.com

The last two years have taken their toll on the working environment. Sure, people have grown accustomed to working from home and to meetings online, but our natural instinct is to be together. There’s no substitute for being in the same room, for sensing and responding to mood, to tone of voice, and to body language. It’s something we do instinctively.

This human facility is sometime called emotional intelligence. It’s a term that describes the ability to recognize and understand the emotions of oneself and of others, and to regulate one’s own.

We may feel that some people are more gifted at this sort of thing than others, but emotional intelligence is something we can all do better, and at Capgemini, we’re actively training our staff.

The need for human understanding

Why? Because in the modern business climate, where so much is conducted online, where remote working has increased the physical distance between people, and where transaction volumes make automation unavoidable, the need for human understanding is greater than ever.

We need to arm ourselves with a different toolkit to navigate in these new environments but still achieve our desired outcomes which is why emotional intelligence is even more crucial to success. In the changing circumstances we’ve all experienced, we need to focus on building cohesion between people, on feeling part of a high performing team, and creating and sustaining a sense of belonging.

What is emotional intelligence?

There are four main elements to emotional intelligence:

• Self-awareness – understanding your own emotions and how they affect your performance
• Self-management – controlling your emotions effectively, and taking positive initiatives
• Social awareness – accurately gauging situations and people around you, for example, via empathy and organizational awareness
• Relationship management – managing interactions with others to help them feel understood, for instance, via coaching, teamwork, conflict management, and inspirational leadership.

In short, the better people can be at empathizing, listening, collaborating, innovating, adapting, and trust-building, the better the workplace will be, the better the business’s external relationships will be, and the happier and more fulfilled those people will themselves be.

In a range of workshops, classes, and expert talks over a three-month course, our emotional intelligence training program uses a range of approaches to develop a more emotionally intelligent workforce. We’ve customized existing learning programs, and we’ve made technology and data available to help people grow in insight and understanding.

In addition, we use emotional intelligence as a foundation principle for promoting and rewarding talent, and we are also modifying our recruitment processes to include its evaluation.

Commercial and personal benefits

There are business benefits to emotional intelligence. For example, according to our own Capgemini Research Institute, it can improve team performance by at least 20%.

But there are other advantages. The emotional and mental wellbeing of employees is noticeably – and indeed, measurably – better. Fears of job loss are reduced. Openness to change is increased.

Customers benefit, too, not just from engaging with a happier and more motivated workforce, but because they, too, are now dealing with more emotionally intelligent people, who are taking the time to understand them better, and to make a connection.

This is a workplace evolution that we believe ought to be an essential element of the digital transformation for which so many businesses today are striving.  The changing world has shown that we need a different type of focus, and new skillsets. We need to be the glue between different parties, and to do that we need fresh perspectives, particularly in the new ways of working.

It’s true that actionable data, and streamlined processes, and automated online functions are all necessary in a fast-moving, high-volume world, and we hear these points made regularly. But the point remains that we lose sight of the human element at our peril.

Cloud has helped accelerate and – some might argue – lay the groundwork for digital transformation. Key transformation drivers for organizations included enhanced customer experience through innovation – and business agility to achieve business growth. Some of the immediate benefits of moving to the Cloud were scalability, reliability, cost efficiency, and faster time to market. Cloud computing is now becoming a foundation for digital business – and therefore CTOs and CXOs are now mandating moving to Cloud as a major part of their IT strategies.

Custom(er) Cloud journeys – are you building Cloud-native applications?

The odyssey of moving to Cloud is now at a stage where most organizations have already built – or are in the process of building or migrating – strategic business applications that support topline growth into Cloud. Crafting these business capabilities requires a big shift in the application development and management lifecycle – where design thinking, product-based development, DevOps, and cultural transformation are just a few of the key ingredients for success.

Development of Cloud-native applications utilizing Cloud computing architectures, microservices, containerization, API management stacks, and integrated continuous delivery with DevOps are core technology trends here. And harnessing these trends to craft your own custom Cloud strategy for your application landscape – and business as a whole – is critical in continuing to offer the unique experiences your customers desire.

For example, Capgemini’s Digital Cloud Platform for Restaurants business is hosted on Amazon Web Services and provides a comprehensive collection of Cloud-native, built-in accelerators for crafting an end-to-end restaurant experience.

What challenges can you expect in moving your core applications to Cloud?

As enterprise adoption of Cloud rises, core business applications are an essential focus area – but migrating them to Cloud has many challenges. Over the years, the demand for customization, the duplication of business processes across departments, changing regulations, evolving IT strategies, and the creation of complex integration points have all added complexity.

Successfully migrating these applications to Cloud requires a clear strategy that outlines your motivations, proper business case justifications, and desired business outcomes. Cloud Modernization with ADMnext ensures your application landscape is geared to support and enables you to harness the full power of Cloud for comprehensive IT, digital, and data-driven business transformation. Together with Capgemini’s eAPM (economic Application Portfolio Management), Cloud Modernization with ADMnext can help you reach your Cloud migration ambitions. eAPM offers you a comprehensive Cloud assessment and an AI-based, data-driven decision-making framework that delivers a solid foundation that you can base your Cloud strategy upon.

New Cloud adoption models to integrate into your Cloud strategy: Hybrid, container, multi-Cloud, and Edge

Some of the most common risks associated with moving to Cloud are found around data security, compliance, vendor lock-in, and low latency for connected devices (IoT). Here are a few models that can help you mitigate risk:

Hybrid Cloud environment: To reduce risks surrounding data security, organizations are adopting hybrid Cloud environments where non-sensitive data is hosted in a public Cloud, while a private Cloud provides the necessary capabilities to protect sensitive data.

Container technology: These are self-contained technology boxes with software products and applications that are packaged with all the needed infrastructure elements, which can be deployed, scaled, and updated across any Cloud vendor.    

Multi-Cloud strategy: Organizations are adopting multi-Cloud strategies to adhere to regulatory requirements, offer unique services, and get the best of Cloud services across application workloads. Adopting architecture principles such as loosely coupled, application portability that uses open standards and a clear exit strategy will help to avoid vendor lock-in. Cloud vendors are also making provisions to run applications across the entire Cloud platform.

Edge computing: With growing demand for connected devices that require local processing with low latency, Edge computing is becoming more and more relevant in solving core business challenges.      

To learn more about these models, check out Capgemini’s TechnoVision 2022 for tech implementation guidance with route maps around emerging trends and innovations.  

Are you geared up to build your next-gen ADM services?

Going forward, managing your application portfolio will require the right skills, right collaboration tools, and new communication channels, as technology will continue to evolve rapidly with increased adoption by organizations. Use of automation and machine augmented services are already on the rise in supporting this complex Cloud environment. And Cloud Modernization with ADMnext can help you meet all your Cloud strategy goals – from cost reductions to a fully future-ready applications portfolio.

In our next post, we’ll dive deeper into strategies for better supporting your applications by moving from and on-premises hosting to Cloud.

In the meantime, to learn more about Cloud Modernization with ADMnext, Capgemini’s overall ADMnext offering, and how you can ensure that your Cloud strategy is a success, contact me here.

This blog is authored by Darshan Bhatkar, Enterprise Integration Architect at Capgemini

The case for automation is clear: it will increase efficiency, lower the total cost of ownership – the list goes on. Telcos know that they need to move towards an automated and efficient network if they want to support agile service innovation and delivery on a competitive level. But at present, automation has only reached varying levels of maturity across the network span. For many telcos, RAN automation is still limited to discrete trials with small groups of vendors; it’s mostly experimental, and its scalability remains unproven.

Even a few years ago, the complexity of trying to link multiple software systems would have been unthinkable. Today disaggregated RAN is not only possible – it provides a very real competitive edge. The problem is, Open RAN requires a level of intelligent automation that is difficult to build completely in-house¹. Let’s look at the specific challenges to automating Open RAN, and then see what solutions are available.

No one said Open RAN would be simple…

Radio networks are inherently complex. Add to that business requirements that mandate compatibility between new, next-gen networks and legacy technologies, and that complexity multiplies. Operators find themselves facing two options: automation that’s fairly easy to implement, but limited in scope, or automation that links entire networks, but must be custom built, which typically requires some help from outside software experts. Add to that the steadily increasing number of sites², plus the need to keep software expenditures and OPEX in check, and that complexity becomes a serious obstacle.

5G generates a flood of data that – for all the reasons listed above – creates some very real challenges for operators. This data needs to be classified and prioritized for effective network control and management to be possible. The solution? Classic automation is not enough. Open RAN depends on intelligent automation.

Abstracted architecture, concrete benefits

Capgemini solves the issue of multi-vendor CNF diversity through layered, abstracted architecture. In plain English, abstracted means that the architecture is not tied to any specific vendors’ software, but can be quickly tailored to incorporate multiple combinations. It’s the difference between a recipe for a cake, which needs to be followed precisely, and only works for one set of ingredients, and the skill of barbequing. A good grill master can swap out any number of meats or vegetables and adjust the technique slightly, without the need to find (or create) a new recipe each time. In the same way, an abstracted architecture makes it possible to automate a network end-to-end, without the difficulty and cost of a fully unique solution. That goes a long way to managing time, costs and complexity. But the most interesting piece is yet to come.

The spark of intelligence

The heart of Capgemini’s OpenRAN Operations Automation solution lies in a set of RAN applications driven by our NetAnticipate AI-Model platform. To address the issues of automation in real time – when millions of impulses are streaming through networks and each one must be routed correctly and immediately – something more than standard automation is required. The innovative solution we’ve created uses the near Real-Time RIC (nRT-RIC) model. This is based on the extendible, abstracted architecture described above, that enables easy integration of multi-vendor xAPPs on nRT-RIC. So whatever vendors an operator is working with, the same powerful AI is able to handle the traffic. RAN-specific AI models that learn with no supervision, make O-RAN NonRealTime RIC implementation possible. The result is a complex network that essentially runs on autopilot³.

The challenges of Open RAN – the complexity, the constraining brownfield environment, the risk of cost overruns – these all come down to the need to intelligently manage information flow. By doing so, our OpenRAN Operations Automation solution opens the door to a range of benefits.

The benefits of automated Open RAN

Intelligent automation turns Open RAN from a resource-intensive challenge into a source of value. Some of the benefits include:

• The ability to deploy in multi-vendor RAN environments consisting of complex multi-technology networks where the automation platform can create the greatest operational impact.
• Lower operational costs thanks to the automation of network deployment and network operation, leveraging new automation rApps and xApps deployed over O-RAN SMO.
• The ease of harnessing proven operational models of legacy RAN application by modernizing to cloud-native service on nRT and NRT RIC platform.
• The ability to deploy RAN automation across multi-technology networks, using design patterns in alignment with the O-RAN Alliance, and providing future-proof flexible automation across varying technology and vendors. The level of automation can also be adjusted in the network’s constituent layers to varying degrees – for example a high level of automation on RAN compute and connectivity infra, and a medium level in radio resource management.

Looking forward

Solving the riddle of efficient Open RAN automation is only the beginning. With reliable RAN, telcos can create new innovative services like end-to-end network slicing and open and closed loop service assurance, thanks to Capgemini’s RAN automation solution portfolio. With the same underlying infrastructure, telcos can start to capitalize on new business opportunities as service providers for 5G consumer and enterprise services, as well as for mission-critical communications providers. With the right partner and the right solutions, the benefits are just around the corner. Contact me below to learn more.

TelcoInsights is a series of posts about the latest trends and opportunities in the telecommunications industry – powered by a community of global industry experts and thought leaders.

¹ Such automation depends on specialized, real-time cloud network functions (CNF) software management and deployment automation

² Due to network densifications and real-time sensitive Radio Network traffic, which makes it very difficult for any third-party generic automation master controller to seamlessly schedule and operate cloud network functions (CNF), virtual network functions (VNF), or physical network functions (PNF) without a large degree of customization.

³ It’s worth noting that the nRT-RIC does not have a clearly-defined open interface to xApps, so to enable developers from different expertise background to be able to create xAPPs in an Application Builder environment, Cagpemini has introduced a SDK (xAPP SDK) and plugin template approach to xAPP development.  This can easily be integrated over the underlying nRT-RIC.

If you want to know who’s driving the explosion of tech innovation, follow the money. Global venture funding increased 83% year over year from $392B to $718B in 2021, and it’s the tech giants and venture capital firms who are the main sources of this investment.

Their role is not limited to being a source of funds. They are having a major influence on the culture and direction of innovations. Indeed, Big Techs positively encourage the creation of startups to develop new products and services that enhance their vast product ecosystems; being one example among thousands, Salesforce has recently acquired the business communication platform Slack in order to integrate it into their own offering. But, for now, let’s focus on how Big Techs are deploying their capital to enable young startups to grow.

The deep pockets of Big Tech

It’s no surprise that the tech giants are at the forefront of startup investment and acquisition. The world’s biggest tech companies – Facebook, Amazon, Google, Microsoft, Intel, and Apple – were startups themselves not long ago, and they have grown rapidly on the back of innovation and disrupting the marketplace. In many ways, they still think like startups and have an understanding of startup culture that traditional investors cannot match.

These are also the companies that have done well coming out of the pandemic and have capital to burn for M&A and investment activity. Alphabet, Amazon, Apple, Facebook, and Microsoft had a combined total of $472B in cash in May 2020. Big Tech is hungrily eyeing the next innovative business models, and they are in the driver’s seat as startup valuations are exploding again across the board.

So, which startups are catching their eye and their investment? The answers provide strong insight into where Big Tech sees growth coming over the next decade.

1. Automotive. While traditional auto manufacturers struggled during the pandemic, Amazon, Intel, and Google invested heavily in startups developing the new software-driven mobility ecosystem: notably, electric, autonomous, and shared vehicles as well as mapping, augmented displays, EVTOL, and system integration.
2. Developer tools. Google, Microsoft, and Amazon are investing in crowdsourcing platforms, code marketplaces, data training and modelling, automated testing, and database tech to empower developers.
3. Data. Google, Intel, and Apple are all buying into AI/ML and big data analytics startups in areas such as automated monitoring platforms, AI/ML, predictive analytics, NLP and voice tech, and data governance and visualization.
4. Computing technologies. Intel, Google, and Microsoft lead in powerful computing technologies, including quantum, cloud, edge, AI chips, and semiconductors.

A global phenomenon

US-based companies are not the only players in town. Big Tech players in China and India are also flexing their financial muscles, making the scramble for startup investment a global phenomenon. Chinese companies such as Alibaba, Tencent, Xiaomi, Huawei, Baidu, and ByteDance are on the acquisition trail and are rapidly gaining ground in new markets, especially in South Asia. They are not the only ones expanding in this region. For example, India’s local ecommerce giant, Flipkart, backed in early stages by Microsoft, among others, was finally acquired by Walmart, and Google has announced a $10B India Digitization Fund to provide their own funding for Indian startups[SP2] . Africa too has its own emerging startup culture, and in October 2021 Google announced its Africa Investment Fund, with plans to invest up to $50 million in African early- and growth-stage startups.

The venture capital boom

VCs have been an equally vital pillar of the innovation economy, and VC money is flowing at unprecedented levels – in 2021, they invested a total of $718B (+83% YoY), making for a record year. There were more than 1,556 mega deals (defined as deals of more than $100M, +147% YoY), accounting for $414B in investment, and there are now no fewer than 959 unicorns (privately owned startups with a value of over $1 billion, +69% YoY)[SP3] . If we’re following the money, the path leads directly to VCs.

VC investment is flowing into startups in two different ways – from the traditional venture capital firms who invest their capital in exchange for equity for a return on investment, and from corporate venture capital (CVC) funds, which are set up specifically to give big corporates access to promising startups. Most big corporates today, including Capgemini, have created a CVC or are in the process of doing so. Today, there are more than 1000 CVCs in operation, and in 2020 they were involved in over 3,000 deals valued at a total of $120B.

VCs as a primary source of innovation intelligence

As we have seen, VCs are much more than just investors; they bring their own unique perspectives to the collaboration paradigm and are a valuable source of qualified market intelligence of emerging trends. They can analyze the market differently, bringing an outside-in perspective with the ability to take risky bets. This gives them unique expertise in identifying the most promising young companies. It’s worth remembering that without the belief that VCs displayed in emerging payments trends, the fintech and payments revolution might not have happened at the speed that it did – large VCs like Andreessen Horowitz and Sequoia Capital invested early in firms such as Stripe and Klarna.

Capgemini as part of the open innovation ecosystem

If startups are providing the disruptive innovation and corporates are offering the go-to-market opportunities and augmenting delivery capabilities, Big Tech’s and VC’s financial firepower are key enablers in the new model. They help drive the innovation economy by supporting high-potential startups, spotting trends early, and giving startups the freedom to experiment, innovate, and disrupt while staying afloat.

At Capgemini, we closely track the changing dynamics of the open ecosystem, giving our clients unique access to startup innovation and disruptive technologies. We are a growth partner for promising startups in the B2B space, providing them with access and penetration into markets and clients, insights and data, and our army of practitioners, experts, and thought leaders. With our ISAI Cap Ventures fund, in partnership with ISAI, Capgemini Ventures can on the one hand leverage rich sources of market intelligence and generate co-investment opportunities, and on the other hand can help shape partnerships between selected startups and Capgemini for joint market opportunities. For more information on how to incorporate startup solutions into your innovation model, look out for forthcoming blogs and vlogs in this series. Meanwhile, you can catch up on the previous blogs in the series.

What is containerization? What is a container?

Containerization is a software-deployment technology and approach that enables software products and applications (the code, as well as components like libraries, frameworks and other dependencies) to be packaged into self-contained components that are easy to deploy, scale, and update.

Software and services are thus packaged into containers. Like real-world, physical containers (i.e., the metal boxes used to send cargo from one location to another), they are (relatively) lightweight and portable, and can be deployed or moved across a variety of different infrastructure platforms. In the context of software, this means that containerized applications are not dependent on the infrastructure platform (e.g., public cloud, private cloud, or your proprietary data center) and do not require their own copy of a specific operating system.

Prior to the mainstream adoption of containerization, the most popular way to deploy applications was by using virtualization or virtual machines. Virtualization was a key enabler to cloud adoption, but containerization provides the means to accelerate the journey and reap greater benefits.

The differences between containerization and virtualization

The key differences between containers and virtual machines are:

• Abstraction. Virtual machines are abstractions of physical servers (hardware). The hypervisor enables multiple virtual machines to run on one physical server. Containers serve as the app (software) layer that packages code and dependencies together.
• Operating system. Multiple containers can work on one virtual machine and share the same OS kernel, despite running in isolation. Every virtual machine requires a full copy of the operating system.
• Complexity. Containers run in isolation, with everything they need packaged inside the container. Apps on virtual machines are typically dependent on libraries and/or scripts, which means they typically require more work to deploy, test, and operate.
• Size. Containers are normally measured in tens of megabytes. Virtual machines typically take up tens of gigabytes. Size, plus dependencies, can make virtual machines slow to boot and means they often require more support and maintenance.

Although both technologies and approaches have a key role to play in business IT, containerization provides advantages in that it enables quicker and easier deployment and migration, and can help reduce the number of operating systems and virtual machines required by a business. As a result, a well-executed adoption, scale up, and operation of a containerization platform can enable a business to accelerate its cloud-native development and innovation, optimize costs (e.g., reduce spend on energy, cloud, and virtual machines, and divert it toward innovation), and reduce the carbon footprint of its IT (e.g., through better utilization of existing resources and reduced energy bills from IT). 

What are the key use cases for containerization?

In addition to the cost, carbon footprint, and innovation benefits, container adoption can help you accelerate and improve your success in several key business and IT areas:

Cloud adoption. Containerization can help you move workloads to the cloud and across various cloud types and providers, and a well implemented, properly operated containerization platform can provide a standardized way to develop, deploy, secure, and operate workloads. Containerization also enables organizations to develop services centrally and then push them to edge locations for maximum benefit.

IT transformation. Containers are key to enabling application modernization, and to FinOps, sustainable IT, and overall IT modernization efforts. In this regard, containerization contributes to faster delivery, lower support costs, and better use of existing resources (e.g., physical servers and procured cloud infrastructure).

Industry 4.0 (what we like to call Intelligent Industry). Success in the fourth industrial revolution will require effective deployment and use of IoT, artificial intelligence, machine learning, data analytics, and more. It will also require the ability to simulate various scenarios using digital twins, connect microservices quickly and effectively using APIs, and accelerate the development, testing, and deployment of MVPs and new services. Containerization is a key enabler for all of these technologies and ambitions.

Business innovation. Technologies and approaches like microservices, digital twins, data science, machine learning, and cloud-native application development have key roles to play in the pursuit of business innovation. Containerization provides the technology to develop and operate microservices at scale. It also enables computing power to be accessed and scaled on demand to support data science, machine learning, and digital twins. What’s more, containers are an efficient and quick-to-deploy way of hosting, deploying, scaling, and operating cloud-native products and applications.   

Key concepts and terms around containerization

When talking about containerization, there are some key terms to be aware of. Among the most popular are:

• Container orchestration (Kubernetes) is the automated management, deployment, scheduling, and networking of containers. Kubernetes is the industry standard container orchestrator.
• DevSecOps tooling is a collective term for the development, security, and operations tools needed to build and operate containers. DevSecOps tooling facilitates increased delivery velocity using automation.
• Container platform (DevSecOps platform and cloud-native development platform)combines DevSecOps tooling and Kubernetes to provide all the platform-level capabilities to develop, run, and operate container-based products and applications. Red Hat OpenShift^® is the best example of a fully integrated and supported containerization platform.
• Cloud native is a term that covers both application and platform development. In the context of platform development, it means to use as much of the cloud provider native services as possible. In the context of application development, it means to build software that is designed to work natively with the cloud.

Containerization is an important technology that is relevant to businesses of all shapes and sizes, as well as to a broad range of strategic and operational ambitions. To learn more about how you can use containerization to accelerate your progress against your business objectives, check out Capgemini’s Containerization Service with Red Hat.

Bernard Drost

VP and Global CTO Cloud and Infrastructure Services

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During 2021, a total of 66.7 million cars were sold across the globe. The above statistics show that roughly 2.6 million of those cars are running as you’re reading this article. But what if the cars’ utilization percentage increased?

Imagine we had been able to double car utilization from 4% to 8%. In theory, only half the number of cars would then have been sold during 2021. In practice, this would probably not be the case, but increased utilization would definitely affect the amount of cars produced and sold worldwide.

Airbnb: sharing economy in action

Increasing asset utilization is not a new idea. One of the most famous examples is Airbnb. As of December 2021, Airbnb had 12.7 million listings in its database; 356.9 million bookings were made during 2021. Across all Airbnb listings, the average Airbnb occupancy rate globally in 2021 was 17.4%, up from 11.5% in 2020.

This area of the sharing economy has been growing for many years, and the trend shows no signs of slowing down. Would we have built more houses/hotels if we hadn’t been sharing them with each other? The answer is probably yes, though we don’t know how many more.

An Airbnb for cars

So, how about creating an Airbnb for cars? It’s already been done. In 2018, a new member of the Zhejiang Geely Holding Group, Lynk & Co, was launched. The very same year, the new brand sold more than 120,000 cars, all in China, making this the fastest-selling new car in history.

Gaining confidence from this success, Lynk & Co decided to launch in Europe, but this launch was to be different from the Chinese one. One of the key messages and selling points was car sharing: being able to lend your car to people in the Lynk & Co community when you are not using it yourself.

Let’s take Jenny as an example. Jenny lives in the countryside but works for a company in the inner city. Every day, she commutes to work with her Lynk & Co 01, which she parks down the street, normally from 8am to 5pm. Using the Lynk & Co mobile app, she can make her car available to the community, set a rental fee, and state where people can park the car at the end of the rental period.

Secure sharing powered by digitalization

The Lynk & Co experience shows that an Airbnb model can be applied to vehicles. But, you may ask, how does it deal with the risks of renting your car out to someone else – for example, the risk of theft? What are the implications in terms of insurance? And what about cleaning?

Lynk & Co addresses these concerns in several ways. First, to be a member of its community, you need to register with your personal ID, driver’s license, and insurance details. Second, Lynk & Co cars are equipped with advanced telematics and connectivity, making the rental process more secure for the owner. And last but not least, all community members get a star rating of between one and five from vehicle owners based on their behavior. In other words, people who misuse cars will have a harder time renting one in the future. The same goes for those renting out their cars. If a car isn’t clean, they will get a lower ranking from renters, and therefore have a harder time earning money from that car.

This disruptive and experimental concept was launched in Europe during 2021 and is still in its infancy. However, one thing is certain: The idea is challenging the whole industry around car ownership and usage.

It’s exciting to consider how this new business model could develop. Will we see collaboration between different OEMs so that a driver can rent multiple car brands and benefit from the same telematics and connectivity-enabled security for all of them?

Accounting for 7.1% of total greenhouse emissions

Now, let’s consider sharing from a sustainability point of view. Globally, human activity generates around 50 billion tonnes of greenhouse gases each year. In 2020, 11.9% of total emissions came from road transport. Of those, 60% result from passenger travel and the remaining 40% from road freight. This means that 7.1% of global emissions arise from passenger transport vehicles.

To put that into perspective, 7.1% is more than 3.7 times as high as the aviation industry’s CO₂ emissions, which represent 1.9% of the total. If we factor in the additional carbon emissions from producing the 66.7 million cars made in 2021, you can see that the total impact is massive.

So, how do we reduce those emissions levels? Let’s return to our example. By sharing her car, Jenny might be able to increase its utilization from the average of 4% to, say, 10%, which in the long run will reduce the need for new car production. In addition, her Lynk & Co 01 car is a hybrid electric vehicle (EV) – which makes it much more eco-friendly than non-hybrid internal combustion engine (ICE) vehicles.

Electric vehicles are on the rise

Out of the 66.7 million cars sold worldwide during 2021, 6.5 million – around 9.7% – were EVs (including both fully electric and plug-in hybrid passenger cars). That’s an increase of 109% compared with 2020.

Different automotive markets have significantly different EV adoption rates. The world’s largest automotive market by far – almost double the size of the next largest, the US – is mainland China. There, 3.2 million EVs were sold in 2021, accounting for 15% of all the new cars sold. Europe had 2.3 million EV sales: 19% of the total. However, in the US only 535,000 EVs were sold, representing just 4% of new car sales.

With today’s shortages of materials – semiconductors in particular – it’s hard to predict what the adoption curve will look like across different regions in the future. In addition, while EVs will have a positive impact on greenhouse gas emission levels, we need to keep in mind their downside. First, they require rare metals (especially lithium), and second, producing an EV car results in 60–90% more CO₂ emissions than making an ICE car.

Digitalization is leading the way

That said, what would be the optimal solution from a sustainability point of view? The combination of EV cars and higher utilization rates holds great promise since, as we have seen, higher utilization of cars can reduce production-related CO₂ emissions while transitioning to EVs reduces emissions from transportation.

From a holistic perspective, disruptive and innovative digitalization will be the key enabler of this type of transformation, just as it enabled the rise of Airbnb a decade ago. The icing on the digitalization cake is that as autonomous driving gradually becomes a reality, we can increase the utilization percentage even more and take a further step toward an eco-friendlier industry.

Sharing is caring… for the environment

In conclusion, with the help of digitalization and sharing, we can reduce the need for newly produced cars and increase car sharing bookings to get closer to Airbnb’s 356.9 million. This approach could bring about a substantial reduction in the passenger vehicle industry’s 7.1% share of global emissions.

At an individual level, it’s now time for all of us car owners to think about whether we can be like Jenny, and make sure that our next car is not standing still 96% of the time.

AUTHOR

John Sparrefors
Global Account Executive in Automotive Sector

And then of course, there is the global transition to a data economy, where new business models, new products and services are now powered by data sharing and data ecosystems.

But not every Data & AI business has shifted their own positioning accordingly, reshaping themselves with the aim to deliver clients tangible business value, not just technology capabilities.

At Capgemini, that’s exactly what we have been doing. For over 3 years, we have been building up a differentiated Data & AI portfolio to better fit the needs of organizations today, to empower CXOs with data & AI end-to-end solutions, and to help clients transform into a business of the future.

I’m incredibly proud that these efforts have been recognized. Recently, Capgemini were announced as a ‘Leader’ in the 2022 Gartner Magic Quadrant for Data and Analytics Service Providers for the sixth consecutive year, and a ‘leader’ and ‘star performer’ in the Everest Artificial Intelligence (AI) services PEAK MATRIX® Assessment 2022, for the second time consecutively.

These ongoing recognitions are a testament to our people, particularly our incredible Data, AI and Analytics community.

I’d also like to take this opportunity to share some examples of why I believe we have been able to achieve and maintain our position as an industry leader.

1.   Put your customers at the center

This might sound overly simple – putting your end customer first is something that is taken for granted in most organizations.

But true data driven organizations – data masters – know that optimizing customer acquisition and retention, and delivering a customer experience based on respectful personalization and intelligent customer services, is where they can differentiate themselves to drive tangible results.

This is what sits at the heart of our Data Driven Customer Experience offering, a foundation for businesses to deliver this stellar customer experience but also continuously reinvent their business.

As an example, we are helping a leading global consumer brand to achieve €30M per year of efficiencies and to become best-in-class in marketing.

In this case, we built a smart engine based on a powerful global analytics platform that translates the customers’ digital footprint into deep insights of their behaviors and preferences. These insights are then leveraged by business units across the entire organizations, such as for, product development, product launches, marketing campaigns or sales.

2.   The future of industry is intelligence powered by Data & AI

By leveraging Data & AI across every dimension of what they do and how they do it – from R&D, supply chains, factories to networks – organizations can unleash innovation and new revenue models by creating Intelligent products, operations or services.

For a year now, we have been working on transforming the R&D function of a global pharma company. Not only is this helping to accelerate clinical studies and time-to-market of new drugs, but it helps also improve diagnostics and predict responses to therapy.

The measurable impact? The probability of success for drug development is improving up to 30%.

3.   Our commitment to solving problems through data-powered innovation

Data, analytics, and AI are critical to creating innovative solutions to today’s biggest challenges – both for businesses and society.

This is something that is reflected in the work that we do with our clients, with Data for Net Zero and Sustainable AI being a key part of our portfolio. This means two things: helping clients to achieve their sustainability targets and reduce their greenhouse gas emissions with innovative data & AI capabilities, and implementing resource efficient solutions that ensure data platforms and AI use cases does not undo its own great work on climate action.

Our commitment to building a positive, inclusive and sustainable future is also echoed within our organization, through initiatives like our Global Data Science Challenge, a company-wide hackathon, focusing this year on using AI to help eliminate river blindness, a tropical disease which has currently infected more than 20 million people, and our support to the Girls in AI Global Hackathon, aiming to empower young people using AI in their projects to tackle the UN Sustainable Development Goals, through dedicated mentorship.

As another example, in the latest edition of our Data-powered Innovation Review, we present an app using AI as a powerful tool helping people suffering from dyslexia with reading and writing. 15 articles explore the fresh, innovative technologies that are enabling us to be the change we want to see in the world – Make sure you check it out!

Data is the key to getting the future we want 

For all of us in the Data & AI community, there has never been a more exciting time.

Data, which has long been our lifeblood, is now the lifeblood for organizations everywhere – driving impactful and meaning transformations and driving exciting new opportunities for both businesses and society. With Data, AI can finally be impactful at scale, for organizations, people and planet.

It’s an incredible privilege to work alongside passionate colleagues, clients and partners in this rich and innovative space! I can’t wait to achieve even more successful outcomes together.

As we gained an understanding of what was actually possible and felt the benefits of digital collaboration, the movement towards reinventing how we work was accelerated. Now, organizations find themselves trying to combine these two ways of working in a hybrid work model. But when reinventing how we work, questions arise: what is our New Working Paradigm? And how does it add value to organizations? In this blog we will dive deeper into this concept and explain why the New Working Paradigm is here to stay in a post-pandemic world. To provide you with the opportunity to assess where your organization is currently at regarding the New Working Paradigm, we developed a 10-minute version of our hybrid work assessment: A quick scan.

What is the New Working Paradigm?

Before diving in, let’s define what we mean by the New Working Paradigm. It is an analytical approach to design your future way of working that is tailored to your organization. Despite the truly relevant discussions focused on creating the physical and digital workplace for hybrid work, the New Working Paradigm takes a broader perspective. It is about determining why your organization wants to work differently and what the impact of such a decision is for your organization, where one potential outcome is to combine physical, virtual and hybrid ways of working while maintaining a supportive organizational work environment. The New Working Paradigm is a way to match your organizational processes and redefine the relationship between employers and employees. Overall, the New Working Paradigm sets your organization up to become more resilient, purpose-driven and connected.

Why is the New Working Paradigm important/relevant?

Taking the example of hybrid work, employers and employees encounter several challenges. Employers want to their organizations to be an attractive place to work for their (future) employees, thereby ensuring they have the right people with the right skills. A more flexible way of working is often considered as a requirement by current employees and candidates on the labor market. Besides that, the flexibility that is associated with a hybrid work model makes it easier for employers to attract skilled employees from a wider geographical range.

Second, working flexibly regarding location and time enables organizations to work in a more efficient and effective way. This is because employees have more autonomy over when and where they can best do their work, resulting in higher employee satisfaction, productivity, and performance. Hence, this contributes to an engaged and empowered workforce.

How does the New Working Paradigm (not) work?             

Back to the start: The urgency of the pandemic forced companies to focus on setting up the digital workplace in a noticeably short time. Understandably, this often meant that there was no or little time to think about the organizational and people processes. While many organizations have made big leaps in designing their digital workplace, they often lack in matching the other aspects of the new working paradigm. Thus, they face a discrepancy between what they should do to make the New Working Paradigm successful and sustainable and what they were able to do so far. While with good intentions, the lack of alignment between the different aspects of the New Working Paradigm has burdened organizations with a productive but disengaged workforce, new digital solutions but a lack of digital skills to reap the benefits, and old offices that do not match the renewed employees’ way of working.

The New Working Paradigm is more than the decision of what the best digital collaboration tools are and how to furnish an office matching its new role. It’s also about empowering people to make conscious choices about how to leverage the given tools and locations. This requires aligning the new work model with an organization’s culture, engaging leadership with their New Working Paradigm and training people in the necessary skills – so that everyone is comfortable and able to make conscious choices about when, where, how and with whom to work.

At Capgemini we are here to help you out

We support your organization in developing a vision for the hybrid work model that fits the organization’s strategy, mission, goals, and market. A clear vision is the cornerstone of the transformation towards a new working paradigm because it provides the framework to mobilize the workforce, enable decision-making on each of the elements and communication. A vision entails having a clear idea of why you would like to implement hybrid work, knows what the expected benefits and challenges of a hybrid work model are; communicate this vision to employees and stakeholders, and have a plan of action to implement hybrid work across people, digital, and physical aspects. Your vision guides how the New Working Paradigm is shaped based on 4 critical elements:

1. Organizational Design (primary focus): The new working paradigm has an impact on the target operating model. This needs to be redefined in terms of the hybrid workplace for teams. To support the delivery of the new target operating model, it is essential to identify the needed adaptations and the new rituals.
2. Digital Leadership & Talent (primary focus): The hybrid model will impact the way leaders think and lead and the way work are conducted. Organizations enter in a new social contract supplying the right balance between performance, autonomy, benefits, and flexibility. The focus is on accelerating the needed new employee experience.
3. Digital Workplace (supporting focus): In the new working paradigm, organizations need a digital workplace that enables seamless collaboration across locations. To achieve this, we combine three elements: virtual collaboration, augmented employee and connected office.
4. Real Estate (supporting focus): In the new working paradigm, organizations redefine their real estate strategy and determine how different physical locations best support their employees in achieving their goals. The new trend will be reflected through new sites concepts based on digital evolution, lower density, and activity-based usages to support the increased temporary use.

When helping our clients in shaping the New Working paradigm, we tailor the vision and four elements to the unique characteristics of the organization that we are facing: strategy, mission, goals, market, and culture, thereby defining a starting point and a future state. For this, we take a co-creation approach and, for example, conduct a vision workshop, create a roadmap based on the vision and discuss the internal processes and client processes. It all comes together in the new working paradigm covering the whole breadth of the organization.

Where can I start?

It may be clear that in today’s challenging professional environments, making bold decisions to design your new working paradigm for your organization is more important than ever. We have set up a quick scan to determine what is your starting point regarding the new working paradigm and how your journey towards a strong new working paradigm will look like (find the abbreviated version here). In case you would like to gain more insights into the new working paradigm and what it can mean for your people and organization explicitly, do not hesitate to reach out to one of our Capgemini colleagues mentioned below the blog.

Author

Freek Visser
Consultant Organization, Purpose and Strategy, Capgemini Invent
Freek focuses as consultant Organization, Purpose and Strategy on projects related to personnel and organizational changes in the public sector. He helps organizations prepare, design and implement transformations and enjoys working together with the client to make an impact together. This also applies to Hybrid Work, as organizations recognize the need to respond to the new way of working and that a transformation to a Hybrid Work model is inevitable.

Judith Groenewoud
Consultant Organization, Purpose and Strategy, Capgemini Invent
As a consultant Organization, Purpose and Strategy, Judith helps organizations in private and public sectors to make the translation from strategy and objectives to a sound organizational structure and collaboration. Judith enjoys finding new ways to work smarter, more efficient, and innovative. This all comes together in her contribution to the new working paradigm, where she helps organizations to reach their full potential.

Dr. Julia Schlegelmilch
Managing Consultant Organization, Purpose and Strategy, Capgemini Invent Julia is a hybrid work expert, providing evidence-based advice. She dares her clients to think further and inspires organizations, their leaders, and people to make conscious choices to effectively collaborate in a hybrid way. As a managing consultant Julia focuses on assignments related to hybrid work, organizational design, and leadership. Her PhD research about hybrid work (VU Amsterdam, 2020) and knowledge about organizational change and psychology complement her consultancy work at Capgemini Invent.