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

Connect with us

First name *

First name is not valid.

Last name *

Last name is not valid.

Company email *

Company email is not valid.

Company *

Company is not valid.

Country

Country Afghanistan Aland Islands Albania Algeria American Samoa Andorra Angola Anguilla Antarctica Antigua And Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia And Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Congo, Democratic Republic Cook Islands Costa Rica Cote D'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands (Malvinas) Faroe Islands Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Gambia Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island & Mcdonald Islands Holy See (Vatican City State) Honduras Hong Kong Hungary Iceland India Indonesia Iran, Islamic Republic Of Iraq Ireland Isle Of Man Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Korea Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libyan Arab Jamahiriya Liechtenstein Lithuania Luxembourg Macao Macedonia Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Micronesia, Federated States Of Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island Northern Mariana Islands Norway Oman Pakistan Palau Palestinian Territory, Occupied Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Puerto Rico Qatar Reunion Romania Russian Federation Rwanda Saint Barthelemy Saint Helena Saint Kitts And Nevis Saint Lucia Saint Martin Saint Pierre And Miquelon Saint Vincent And Grenadines Samoa San Marino Sao Tome And Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia And Sandwich Isl. Spain Sri Lanka Sudan Suriname Svalbard And Jan Mayen Swaziland Sweden Switzerland Syrian Arab Republic Taiwan Tajikistan Tanzania Thailand Timor-Leste Togo Tokelau Tonga Trinidad And Tobago Tunisia Turkey Turkmenistan Turks And Caicos Islands Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States United States Outlying Islands Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgin Islands, British Virgin Islands, U.S. Wallis And Futuna Western Sahara Yemen Zambia Zimbabwe

Country is not valid.

Phone (optional)

Your message *

Your message is not valid.

I agree to Capgemini collecting and processing my personal data to allow me to receive information on Capgemini services. For further information, please see our Privacy Notice. .  

Page title

Expert title

Page URL

Slide to submit

Thank you for your submission. We will be in touch with you soon!

We are sorry, the form submission failed. Please try again.

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.

In our previous post, we delved into the importance of innovation in the ADM space – and the value that a collaborative idea incubation center can deliver across your operations. But now, we’re looking at something even more important than innovation. We’re talking about talent – the people who create ideas and bring new offerings to life with innovative technologies.

At the core of every successful modern business, you’ll always find two Ts – talent and technology. We need good talent to develop and make the best use of current and emerging technology that’s essential for starting, running, or transforming businesses. Making the best use of technology is just as important as creating or developing new technology – and for success with both – nurturing your talent is the key success factor.

Continuous change, new technologies and techniques, and new ways of working

In today’s chaotic world, certainty has almost entirely lost its meaning – and as innovators in the technology space, we must always be on our toes. This means adapting to continuous change to innovate, adopting new technologies and techniques to transform, and implementing new ways of working to meet business demands:

• Adapting to continuous change: business needs are changing faster than we can anticipate – be it effects stemming from the pandemic, tense geo-political situations, or climate change
• Adopting new technologies and techniques: these are essential in augmenting your ability to respond to change. You can see Moore’s Law in action every day with new surprises on the technology front – be it innovation in Cloud, Data with AI, ML and IoT, blockchain, transformation with data fabric, composable applications, MLOps, etc.
• Implementing new ways of working: this is essential to keep pace with changes in business priorities and technology innovation. Agile and DevOps are the new guidance systems in responding on time and making your business viable.

And as you may have guessed, the key to adapting to continuous change, adopting new technologies and techniques, implementing new ways of working – and ultimately succeeding in this new normal – lies within your ability to attract, develop, and retain talent. But how should you get started here?

From “I” to “Pi” – Taking a fresh look at skill management, involvement and ownership, and effective training

With maturity in Agile ways of working, it’s been observed that for successful execution of projects and service management, there’s a real need to develop a totally new mindset and take a fresh look at skill management.

The main objective of a team should always be the solving of business challenges – rather than the fulfilment of specific skills. In the technology space, a business challenge could be the creation of a new application or platform, the efficient and cost-effective running of an application landscape, or the transformation of a legacy environment. Time and again, we have seen that individuals with broader knowledge bases (in addition to specializations) are better equipped to handle complex problems and can quickly adapt to new environments.

There’s a real need to nurture your talent to meet the expectations of this new normal, which should include fostering speed, agility, and out-of-box thinking. To accomplish this, it’s critical to take a fresh look at the skill management of your people on their journeys to Agile maturity – from I to T to Pi-shaped skill sets.

Personal ownership and involvement of individuals within teams

Addressing and aligning with the career aspirations and life goals of individuals is crucial. Some people may thrive on the familiarity of an environment and take pride in maintaining the stability and efficiency of business as usual, while others may be more adventurous in terms of learning new skills and trying out different things to come up with innovative solutions. Nurturing both these types of individuals is essential for your teams.

Additionally, enabling individuals to choose their own mode of engagement is also essential – whether it be time-boxed (depending on at what point value gets delivered) or more fluid. While onboarding needs to show every individual the plan for the success of the team, project, and customer engagement, along with conveying how the team is going to achieve its goals – which in turn relates to how we are going to solve future business problems.

Training is critical – but effective training is the real challenge

Getting away from stereotyping or typecasting – a developer can learn the necessary skills to address business expectations appropriately, while a business analyst could be interested in learning the basics of microservices, to visualize the changes required in business function workflow.

Rather than long, rigorous learning regimes, breaking down information into small, bite-sized learning chunks that are relevant and interesting enough to prompt learners to try out things and attain a sense of achievement can play a huge role. While trainings designed to nurture T and Pi-shaped skill sets help teams address pressing business issues without any feelings of being forced by compliance measures or a need to add another certification.

On-the-job training can help develop prototypes for solutions to a variety of business issues, as team members actively learn the skills required to solve specific problems. For example, maintaining applications hosted in the Cloud versus on premise (data center) requires different collaboration, coordination, and networking skills, in addition to technical and functional skills.

Enabling your people with the right training and tools can help transform your applications development to innovate faster, work smarter, improve operational efficiency and TCO, meet specific business goals in less time, and enhance collaboration between business and IT. Within Application Development and Maintenance (ADM) space, Low code/No code with ADMnext can bring your people the right tools that will enable them to seamlessly create applications using a graphical interface, with virtually no programming experience required.

While overall, Capgemini’s ADMnext provides a comprehensive platform with tools and techniques necessary to adopt and effectively use technology to address business challenges. ADMnext empowers your people to step outside of a ticket-focused mentality and into a value-based mentality by developing heightened human and business connections – and adding direct value to customers.

In our next post of this series, we’ll look at Cloud within the ADM space and how the right Cloud modernization strategy can take your business to new heights.

In the meantime, to learn more about Low code/No code with ADMnext can help nourish your talent and the overall ADMnext offering as a whole, shoot me a message here.

Decarbonization is now firmly at the top of the C-suite agenda. Legislation is evolving fast, and civil society is increasingly sensitive to the carbon catastrophe we face. Citizens, customers, and the whole of society is demanding climate action, right now.

Consumers, investors, and employees expect organizations to be accountable and transparent about climate action. Greenwashing is a major issue, for example, with fossil fuels being marketed as carbon neutral [1], and 59% of sustainability claims by fashion brands having been found to be greenwashing [2].

Promises and platitudes are no longer enough. The carbon cost of every activity is scrutinized intensely, since reports on climate risks and social impacts are now expected to be disclosed in routine corporate accounting.

Finance and asset managers are using ESG performance as a decision-making criterion. During the height of the global pandemic in 2020, large funds with ESG criteria outperformed the broader market. In fact, the most carbon virtuous companies can expect positive impacts on corporate financials, enjoying more favorable financing terms and being seen as more resilient in times of crisis.

Increasingly, organizations face legal demands to act and even more importantly, to prove their actions. In May 2021, a ruling by the Dutch Supreme Court ordered Shell to reduce its carbon emissions by 45% by 2030 for failing to deliver formal proof that it was keeping its commitments. This legal thunderclap warns all companies that lip service is no longer enough. Action is everything.

We are entering a new era of carbon accounting, and carbon is our new currency. There is no doubt that enterprise needs to be fully equipped for carbon accounting, as it is for financial accounting now.

The critical role of data in reporting on ESG commitments

While many businesses and governments have set net-zero targets, data-powered intelligence is key to bridging the gap between net-zero ambition and action. The shift towards action – and proof of action – demands a super refined level of ESG data management.

Simple in theory, less so in real life. First, we make sure that all the data is complete, consistent, and compliant with the taxonomy and frameworks, cataloging to build a trusted foundation.

Next, we move from a one-off, batch collection logic to a recurring collection logic, or even continuous integration. This allows us to create a real data platform dedicated to the net zero program designed for analytics and optimizing its value using data science. Not forgetting, throughout the process, to implement the governance required to manage the project over the long term.

Net zero intelligence supercharges decarbonization

Evolving frameworks, regulations, and standards require that organizations make their emissions data transparent and visible. Not so long ago, this data was reported annually. Today environmental data is a new parameter that feeds into real time decision-making processes, enabling us to make the optimum compromise between cost, time, quality, and now carbon.

Data, AI and analytics are key levers to secure and execute the enterprise sustainability agenda.

Data is an essential lever to build resilience and reduce climate and business risks by addressing three main objectives:

• Measure to steer progress
• Improve to reduce impact
• Anticipate, adjust the climate action plan

 Data for Net Zero

Capgemini has developed a seminal net zero program, underpinned by an enviable track record in data analysis, governance, and the deployment of data solutions and products. These experiences have convinced us of the power of data to fuel the decarbonization process through the creation of Data for Net Zero.

We translate the carbon assessment into tangible insights to monitor and report your ESG commitments at scale through industrialized measurement, powered by our trusted data and AI platforms.

Data for Net Zero enables simulations and advanced analytics that provide centralized real time enhanced insights. These enable organizations to transform their ESG commitments into a pragmatic and viable action plan.

Create a data strategy for net zero

First, your data vision needs to be seamlessly integrated into your overall net zero trajectory. This means breaking down your net zero objectives into key data projects and indictors, then sharing them right across your business.

To anchor your data challenges, you’ll need to review the best calculation methodology for GHG emissions and define the optimum organizational model and parameters of governance. To achieve your data ambition, you’ll also need to select the right technologies and solutions. And finally, you’ll need to create and nurture the optimum data partner ecosystem, which means focusing on seamless data collaboration.

For example, a large American retailer asks its suppliers to formalize the improvements it has made, from one year to the next, on key environmental indicators, as a condition of their partnership. For large industrial companies, fulfilling this simple request would usually take months of work, collecting information and creating an appropriate response. A foundation of data collaboration focused on sustainability, activated across a data ecosystem, revolutionizes the process, quickly identifying those business needs and organizing data and systems accordingly.

Establish a sustainability data hub

It’s crucial that businesses set up a Data for Net Zero nerve center at the crossroads of their enterprise functions. Creating a Sustainability Data Hub will enable you to identify granular data to feed your data hub, from sources such as operational data, the operating system, and external sources, including the emission factor database and suppliers’ carbon data.

We’ll help you design and set up the optimum technological platform for sustainability related data, based on your current data estate. You’ll be able to measure data founded insights and report the environmental impacts of your activities, including scope 3. And you’ll soon be packaging data models to enhance advanced analytics and help business functions to simulate reduction paths to reduce their footprint powered by AI driven use cases.

In the automotive industry, one of our clients is applying this analytical platform to its inbound and outbound logistics activities. Until now, it reported its carbon footprint annually. Today, in its decision-making, sustainable development is on the same level as the safety of the vehicles it designs.

Activate ESG data performance

Your ESG data performance can be harnessed and put to work as a corporate asset. First, you’ll need to set up a cross-organizational ESG performance steering infrastructure and choose relevant the ESG reporting framework to meet mandatory disclosing process from SEC, EU, HKEX, TCRD, and ISSB to name of few. Then you’ll need to measure the ESG insights of all your activities, projects, and transactions, as well as those of third parties.

Once this is in place, you can industrialize and automate ESG reporting to comply with evolving regulations. And in the process, you’ll be able to extract a specific environmental dataset to meet and exceed the increasing expectations of investors, customers, and other stakeholders.

Cross-functional projects require cross-functional skills

It’s a fact net zero is a cross-function responsibility that needs a holistic approach. In addition to creating a solid data and AI foundation, it’s critical that senior managers in information systems management, data, and corporate social responsibility (CSR) are fully invested and committed to the cause. You’ll also need the full buy-in of decision makers right across the business, in operations, purchasing, supply chain, and sales, who need to track their respective sustainability performance.

Going forward, collaboration with an external partner, like Capgemini, with cross-functional expertise in strategy and operations transformation, industrial process engineering, data management and AI, ESG, and sustainability will transform your approach to put decarbonization in action and at scale. We’ll facilitate cross-functional exchanges, helping you to technically embrace sustainable performance and measurement in your data roadmap.

In truth, ESG is no longer an “optional extra” or a “nice to have.” Instead, it’s now a given that businesses will deliver clear and transparent ESG reporting. A business that doesn’t deliver a comprehensive ESG program is likely to experience poor investor satisfaction, as well as a negative impact on its financial results.

Wherever you are on your ESG journey, Capgemini is the perfect partner to help you reach the first stage of compliance maturity level, or to help you accelerate towards high value creation.

In short, we’ll ensure you maximize the full benefits of decarbonization, far beyond delivering basic annual carbon footprint statistics.

A transition that is seeing traditional ways of acting and thinking merge into a world of more dynamic and fluid interactions, inspired by the constantly evolving demands of consumers, governments, and regulators.

As with any change of this magnitude, innovation has a vital role to play.

In fact, ingenuity has a lot of hard lifting to accomplish as it empowers the shift from mass production mindsets to services-centric models. Where legacy systems and constraints give way to new approaches, and the rapid ideation enabled by software-driven transformation. Change that brings with it 3 broad challenges:

• Completing the move to a service-oriented and agile culture
• Building up the competencies needed to sustain this transformation
• Enabling change through the adaption of legacy production capabilities

Let’s quickly assess each of these in turn.

Challenge #1: moving to a service-oriented culture

The innovation remit in automotive is certainly broad. That’s because there is a lot to factor in, with new usage and ownership models demanding attention, alongside the all-consuming concept of sustainable mobility. Innovation therefore needs to be inclusive and extend from first design concepts to methods for end-of-life recycling, thereby helping the OEM:

• Bring to life the concept of digital continuity extending across the full lifecycle of a vehicle
• Act to enhance the appeal of their vehicles with unique services that help enrich the overall mobility experience
• Deliver a regular rhythm of new features and functions across a car’s full lifecycle – made available on demand – to create additional revenue opportunities

Delivering against these ambitions takes OEMs into the realm of end-to-end service provision. An environment of always-on connectivity and universal data flows that moves them beyond ‘fabricate and forget’ products, to cars as ‘service platforms’ – constantly adjusting to meet the needs of drivers and passengers.

Challenge #2 building up the competencies to succeed

One of the biggest tasks faced by OEMs today is to maintain the skills needed to thrive in a software-defined marketplace. To move beyond the traditional focus on cost and quality, toward an operating environment where engineering blends effortlessly with IT to create unified and seamless outputs.

That can of course be easier said then done. Building up the required technological competence involves more than opening up a new department.  Instead, fundamental change is called for to support:

• The different methodologies and expectations of software developers, who are used to highly creative and agile working practices
• Open and transparent end-to-end design thinking, not restricted by any vertical siloes within the OEM
• The championing of software as a means to extend hardware features, and placing this philosophy at the heart of every activity

In response, leading OEMs have been quick to act. Taking inspiration from other industries to adapt procedures, while also spinning off parts of their business to create centers of software excellence – or acquiring specialist consultancies.

Whether these are short-term measures designed to buy time for OEMs as they strengthen their own in-house training, or whether such trends continue we wait to see. But one things is certain: skills availability is proving a key differentiator – and a core enabler of future innovative prowess.

Challenge #3 enabling the transition

Legacy skill sets are not the only barrier to accelerated innovation. Legacy production processes also present sizeable obstacles, as they ensure software integration is relegated to a minor, final step prior to a vehicle’s completion.

Innovating at speed however means ensuring software acts as a key enabler throughout this end-to-end production phase, both inspiring and informing it. The end goal being a more flexible and modular approach that helps realize the full potential promised by Intelligent Industry, alongside the twin advantages of standardization and customization:

• Standardization of hardware: a vital trend as software-driven transformation calls for greater utility of components – from specialist to generalized capabilities – while also helping reduce the overall cost of production
• Customization of software: where this ‘foundational’, universal hardware can be used to quickly develop, refine, and re-purpose different on-demand services, made available from across an expanded automotive ecosystem

In summary

Sustaining and accelerating innovation in automotive is an endeavor that impacts every facet of an OEM’s end-to-end operation. The need to enable new service models while maintaining the necessary skill sets, are challenges that few organizations in the industry were ever fully prepared for. Yet overcoming them is a must for any OEM hoping to remain relevant.

Progress however can be surprisingly swift. Especially when based on a clear vision and backed up by the skills, methodologies, and production capabilities needed to succeed. To help inform this conversation, Capgemini has created its TechnoVision for Automotive 2022. A guide that details how end-to-end thinking leads to end-to-end innovation, while always ensuring that the customer sits at the heart of every transformation initiative.

AUTHOR

Alexandre Audoin
Group Industry Leader for Automotive at Capgemini

The disruption of traditional business models by the global pandemic, the necessity for more resilient operations, and the need to scale digital transformation initiatives is driving increased demand for intelligent automation solutions that combine digital tools to achieve results.

One of these digital tools is process mining – a set of data science and process management techniques that are often leveraged to support operational process analysis efforts based on event and case logs that many organizations already store in their IT systems. The objective is to turn business process data into tangible insights and actions that organizations can take forward to improve key areas of their business such as customer experience for example.

Achieve more scale and value – easily

It’s true that process mining helps you achieve more scale and greater value realization for your transformation initiatives – these six steps outlined below show you how: 

• Secure executive buy-in early – lack of executive sponsorship and stakeholder buy-in will undoubtedly lead to gaps in your organization’s vision and strategic focus. But avoiding this is crucial if you want your transformation efforts to catch on. This is why executive support must be achieved early in any transformation – as it helps direct the whole transformation journey from day one.
• Start with a simple project – selecting the right processes for process mining proof of concepts (POC) is critical as they demonstrate your vision, while also highlighting the potential this technology will have for you and your clients. It’s easier to start with a process that is structured, contains a limited number of steps, and requires low data preparation. Keeping things simple here will potentially lead to more success and grow business appetite for scaling-up.
• Ensure data better availability/quality – limited event logs data availability is key to scaling adoption correctly. This is why educating stakeholders about the benefits of logging business data through information systems is vital to ensuring you overcome your data issues quickly. To do this, focus on transforming data into the formats that work for you. Getting enterprise IT involved early-on will also lead to a better understanding of your application landscape – enabling you to address data privacy and availability concerns quickly.
• Set up a CoE – trying to scale process mining efforts with a siloed approach and a lack of proper governance will always be challenging. However, establishing a dedicated center of excellence (CoE) will help you clearly define what you want from your transformation. It will also provide a strong centralized structure and governance framework for developing a shared vision, transformation initiatives collaboration, and strategic alignment between key stakeholders.
• Identify and source relevant skills/expertise – process mining requires a multi-disciplinary team to be implemented successfully. However, skill shortages, difficulty in acquiring/retaining talent, and high training costs often impedes progress here. Consider leveraging your service providers’ expertise to fill the gaps. After all, collaborating with vendors or service providers to train employees, while helping them develop an analyst-based mindset will further accelerate your scaling efforts – with the added benefit of fast-tracking your own in-house skills.
• Focus on change management – resistance from individual employees to process mining adoption hinders scaling efforts. However, you can access to change agents your employees know and trust by simply aligning with, and educating frontline managers on the benefits of process mining.

Developing organizational culture that embraces innovation and builds a workforce excited by process mining reinforced through events, workshops, and active collaboration will help accelerate the adoption of this technology across your entire enterprise.

Begin your process mining journey today

Adopting process mining at scale offers huge potential for organizations to drive continuous improvement, accelerate their automation and transformation initiatives, and realize greater ROI and business value.

To learn more, download Capgemini and Everest’s joint whitepaper “Process mining – more than just process discovery.” To learn more about how Capgemini’s Intelligent Process Automation solution can help you implement process mining across your business, contact: marek.sowa@capgemini.com

Let’s imagine that providing efficient technical product support is like climbing Mount Everest, and delivering a meaningful customer experience is like undertaking this challenging climb while carrying another person on your back.

But anything is possible, even climbing Everest, if you set clear boundaries at the beginning of any undertaking and have someone to guide you along the way, right?

Overcoming these two seemingly insurmountable challenges requires a solution that provides modern, single point-of-contact services for your global product support that helps you manage your technical inquiries and incidents better. But where can you start?

The quickest way is with a holistic shift-left strategy that resolves more technical support transactions in lower-cost channels, as this is a proven path to accelerating savings when applied across thousands of transactions.

Implement a holistic shift-left strategy – quickly and easily

Any successful shift-left strategy has a number of steps to achieving efficient and holistic technical support that always puts the customer first. These steps include:

• Focusing on L1/L2 transactions to identify configuration and product issues
• Deflecting support tickets to a self-service portal to take pressure off call center agents and enable more customer-friendly, self-service transactions
• Delivering more proactive communications
• Implementing intelligent automation into a seamless resolution path
• Adopting rigorous root-cause analysis and corrective actions to stop problems before they occur
• Cross-skilling agents to accelerate career growth and optimize team performance.

All of this, ultimately, leads to improved call resolution times, greater agent job satisfaction, reduced ticket handling times, and increased end-user satisfaction.

Keep your focus on your customers

Keeping your customer preferences in mind is critical if you plan on leveraging automation as part of any new shift-left strategy. Most customers still prefer talking to a real person – as only one-third of them believe virtual agents deliver a better holistic, support experience.

To conquer this challenge you need to bridge the gap between higher efficiency and better customer experiences. You can do this by prioritizing contextual transaction management supported by intelligent automation capabilities, a modern and scalable technical support platform, and a team of experts used to working in a global environment.

All of this can help you develop and implement a technical product support solution based on three pillars:

• Make it easy – implement solutions that help customers to help themselves
• Make it intelligent – deploy automation capabilities that integrate the best AI, natural language processing, and machine learning technologies out there
• Make it efficient – reduce customer effort and seamlessly integrate digital and live-agent services.

Holistic and proven shift-left expertise

Capgemini’s approach is to leverage frictionless conversational AI solutions, backed by modern, scalable omnichannel routing to seamlessly handle a range of customer transactions and channels.

And leveraging a proper analytics and automation setup that keeps a live agent in the loop ensures the tech support you deliver is not only excellent, but also memorable.

This helps you stay focused on your most important asset – your customers.

Interested in learning more? To learn how Capgemini’s Intelligent Customer Operations for Technical Support solution can help you build a holistic shift-left strategy, contact: tim.szymanki@capgemini.com

Tim Szymanski focuses on orchestrating and streamlining customer experience operations to improve profitability, quality, efficiency, and brand loyalty for Capgemini’s clients.