Capgemini https://www.capgemini.com/ Capgemini Tue, 15 Aug 2023 10:23:22 +0000 en-US hourly 1 https://wordpress.org/?v=6.1.3 https://prod.ucwe.capgemini.com/wp-content/uploads/2021/06/cropped-favicon.png?w=32 Capgemini https://www.capgemini.com/ 32 32 Unleashing the data mesh revolution: empowering business with cutting-edge data products https://www.capgemini.com/insights/expert-perspectives/unleashing-the-data-mesh-revolution-empowering-business-with-cutting-edge-data-products/ Wed, 09 Aug 2023 05:06:40 +0000 https://www.capgemini.com/?p=943076 The post Unleashing the data mesh revolution: empowering business with cutting-edge data products appeared first on Capgemini.

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UNLEASHING THE DATA MESH REVOLUTION: EMPOWERING BUSINESS WITH CUTTING-EDGE DATA PRODUCTS

Dan O’Riordan
9th August 2023

The principles of data mesh have moved beyond being just theoretical concepts for data architects and forward-thinking executives. It’s time to start delivering on data mesh’s promise of exceptional data products. Data mesh principles can help us uncover the valuable insights that businesses need.

Feedback Fusion: The power of continuous iteration for product success

When building a product, it’s crucial to understand the utility of the product and how any changes to the product will impact its utility over time.

If we consider building a mobile phone or any other product, the cost of building a phone that is unusable will be significant. Therefore, conducting thorough research in the beginning to understand what the market wants is critical before beginning the product-development process.

Once we have built and distributed a phone, we need to continually consider feedback from different channels, including social media and online reviewers, to continuously iterate and improve the phone.

This feedback loop is also imperative for data, however in the past data developers have typically waited for feedback from data consumers and then reacted. This has introduced time delays and ultimately frustration for data consumers.

With product thinking this approach is turned on its head, data product developers are continuously monitoring both quantitative and qualitative feedback from consumers.

This feedback allows data product teams to proactively evolve the data product to ensure that as data consumers need new capabilities, they are being built into the data product, thus avoiding delays and frustration, and enabling better outcomes for the organization.

Data mesh dilemma: Embracing innovation amidst fear and uncertainty

Data mesh principles, which focus on the notion of first-class data products and other factors, have gained an unprecedented amount of interest in the past eighteen months. The conversation in the data mesh community has largely focused on the principles data mesh and what they mean for each organization. Most organizations have invested heavily in cloud but are still struggling to keep up to the pace that the business requires. “Why does it take me three to six months to get a new or modified dataset? Who’s responsible for the data governance? How can I trust that the dataset can be trusted?” and the list of questions goes on.

What we discovered during these conversations with clients is there is an overall acceptance that data mesh and its principles make good sense, but there is the fear factor on the pain an organization needs to go through to get to the promised land of a truly federated data estate of quality, secured, discoverable data products. So, most organizations have kicked the can down the road.

Start small, think big, and design for industrialization

Here are useful guidelines to help reduce this fear of failure.

1. To effectively build data products, it’s crucial to identify the problem you’re trying to solve and determine why a data product is the appropriate solution from the beginning of the process. Taking the time to clarify the reasons behind your approach will ultimately save you a great deal of time, money, and effort. This fundamental step is applicable to any product-development process, and it’s no different when building data products.

A simple data product canvas together with the business and domain experts need to be committed to this phase. Note: Forget about all technology during this phase.

2. Many organizations have not changed their approach to data management in the last 30 years. It is commonly believed that all data must be centralized into a data warehouse or data lake before it can be analyzed, which is both difficult and costly in terms of human resources and technology. Today decision makers wait for data to be made available before it can be used. This means waiting for data pipelines to be specified and built, however this is typically done in the absence of the complete knowledge of the value of the data to a particular use case. This unnecessarily elongated process is fragile and has a negative impact on an organization’s ability to compete using data.

Fortunately, solutions like Starburst/Trino offer intelligent connectors and a highly optimized federated MPP SQL engine that enables the creation of data products by analysts in the lines of business (domains) with no need for intimate knowledge of the source technology. Lines of business can quickly access data and determine its applicability to a use case without having to rely on central data teams.

If we consider this in the context of cloud-data migrations, solutions like Starburst/Trino enable these data products to be created, managed, and retired while the underlying data platforms are migrated. The system administrators only need to update the connector to ensure uninterrupted service for business users. With Starburst we want to give the data-product teams the option to decide on what works best for them to deliver the best data product that will satisfy the requirements as outlined by the data product canvas.

3. Finally, to ensure that the quality of data products is maintained over time as business needs change, a continuous monitoring and feedback loop is key. Data-product producers need to understand who, how, and for what purpose their data product is being used, so they can proactively manage the data product. This management requires technology capabilities to provide this insight as well as an agile approach to streamline the pipeline from ideation to production and constantly improve efficiency. We look at this as the building of a factory like model for data products.

Data mesh in action

At online fashion retailer Zalando, various lines of business independently utilize Amazon S3 for storing and managing datasets, eliminating the need for a central data team. A central data “enabling team” oversees data-governance standards and identifies reuse opportunities, while a dedicated platform team supplies compute services including a distributed SQL Engine (Starburst) for analytics. This clear division of responsibilities – lines of business managing data, the enabling team governing it, and the platform team providing technology – prevents bottlenecks and centralization, fostering agility in leveraging data to maintain a competitive edge.

A prominent French state organization has been devising its data-estate roadmap for 2025 over the past year. Its current extensive data platform comprises batch processing, streaming processing, AI, and use cases, with concerns about cloud readiness. With a complex data estate plagued by performance and monitoring issues, its goal is to streamline operations using a new data platform based on Starburst and Apache Iceberg. The primary objective is simplification and reduced complexity, achieved by focusing on business outcomes and scaling with data-mesh principles.

“Start small, think big and design for industrialization.”

Dawn of a new era

The rise of data mesh and its principles plus the technical offerings from Starburst marks the dawn of a new era for data products. As businesses embrace the principles of data mesh, it’s essential to address the fear factor associated with adopting this approach. By following the guidelines outlined in this article – focusing on identifying the problem to be solved, leveraging modern solutions like Starburst/Trino for data management, and implementing continuous monitoring and feedback loops – organizations can confidently embark on their journey towards a truly federated data estate. Success stories like Zalando and the large French state organization demonstrate the transformative power of data mesh in improving efficiency, agility, and competitiveness. As we move forward, it’s crucial for businesses to embrace the promise of data mesh, shifting from theoretical discussions to real-world implementation. Only then will they be able to harness the full potential of exceptional data products and uncover the valuable insights needed for sustained success in an increasingly data-powered world.

INNOVATION TAKEAWAYS

OVERCOMING ADOPTION HURDLES IN A FEDERATED DATA ESTATE

Data mesh principles enhance data-product creation, driving valuable insights and competitiveness, but adoption is slowed by perceived challenges in achieving a federated data estate.

THE THREE PILLARS OF EFFECTIVE DATA MESH IMPLEMENTATION

Implementing data mesh effectively involves problem identification, utilizing modern data-management solutions, and establishing continuous monitoring and feedback loops.

DATA MESH IN ACTION

Success stories like Zalando and a large French state organization showcase the benefits of data mesh, including improved efficiency, agility, and competitiveness.

BRIDGING THE GAP, PRACTICAL STEPS TO DATA MESH SUCCESS

Moving from theory to practice in data-mesh implementation allows organizations to better harness data-product power and succeed in a data-powered world.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 6 features 19 such fascinating articles, crafted by leading experts from Capgemini, and key technology partners like Google,  Starburst,  MicrosoftSnowflake and Databricks. Learn about generative AI, collaborative data ecosystems, and an exploration of how data an AI can enable the biodiversity of urban forests. Find all previous Waves here.

Dan O’Riordan

VP AI & Data Engineering, Capgemini
A visionary with the architectural skills, experience, and insight to transform any application, computing platform infrastructure or data operation to the cloud. He works regularly with the CxO’s of large enterprises across different industries as they embark on a digital transformation journey. A key part of digital transformation requires an organization to be data centric. Organizations are on their journey to using Cloud and have started to migrate applications but also are looking at how to migrate their data operations and how to then build & deliver data services using the latest AI & ML services from the Cloud Service Providers. 

Andy Mott

Partner Solution Architect, Starburst
With more than 20 years of experience in data analytics, Andy Mott is skilled at optimizing the utility of analytics within organizations. When determining how to generate value or fortifying existing revenue through technologies, Andy considers the alignment of an organization’s culture, structure and business processes. He ensures that the strategic direction of the organization will ultimately enable organizations to out compete their respective markets with data. Andy Mott is currently EMEA head of partner solutions architecture and a Data Mesh lead at Starburst, and lives in the United Kingdom.

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    Software-defined vehicles: the answer to truck driver shortages? https://www.capgemini.com/insights/expert-perspectives/software-defined-vehicles-answer-to-truck-driver-shortages/ Wed, 02 Aug 2023 10:49:45 +0000 https://www.capgemini.com/?p=943238 The post Software-defined vehicles: the answer to truck driver shortages? appeared first on Capgemini.

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    Software-defined vehicles (SDV): the answer to truck driver shortages?

    Fredrik Almhöjd
    Aug 2, 2023

    Although most truck OEMs acknowledge software-defined vehicles as a new norm for the commercial vehicle industry, they still need to convince their customers that these vehicles will add value to their businesses – especially around the top three objectives of improved uptime, productivity, and fuel efficiency.

    SDVs have a major role to play in helping fleet operators overcome the international shortage of truck drivers, explain Fredrik Almhöjd and Jean-Marie Lapeyre, Chief Technology & Innovation Officer, Global Automotive Industry at Capgemini. That’s because SDVs can transform the driver experience, potentially attracting younger people and women who currently don’t see truck-driving as a career option.

    “Without action to make the driver profession more accessible and attractive, Europe could lack over two million drivers by 2026, impacting half of all freight movements and millions of passenger journeys.” That is the stark prediction of the International Road Transport Union (IRU), commenting on a study it conducted in 2022. The outlook isn’t any more reassuring in other regions.

    So what are transportation companies to do, and how can truck OEMs help? In this article, we’ll argue that software-defined vehicles (SDVs) could be a big part of the answer. We’ll be building on ideas from earlier blogs.

    In the passenger car market, the concept of SDVs is often promoted on the basis that it will create a better customer experience for the driver. For commercial vehicle fleet operators, by contrast, the main focus has always been, and will continue to be, on TCO. Until recently, efforts to improve life for the driver, while important, have received less attention.

    However, with driver shortages becoming critical, truck-driving needs to be made more attractive to jobseekers. The IRU suggests that attracting more women and young people is an important part of the solution – but current working conditions make that difficult.

    SDVs can help with the challenge of recruiting and retaining staff.

    SDV features can make drivers’ lives better

    So what SDV features might improve driver experience? Truck drivers will enjoy many of the same benefits as car drivers, such as customized infotainment – though obviously, this must not distract them from the job.

    Consumer-oriented SDV features can be tailored for trucks. For example, a framework for companion apps on smartphones could be adapted to support the needs of HGV drivers in finding places to stop, eat, and sleep, avoiding illegal and dangerous use of phones while driving. In addition, although software can’t improve the quality of facilities available to drivers, it can help direct them to the most satisfactory ones based on a driver’s personal preferences and ratings by other users.

    With all the functionality they need integrated and automated (and configured for personal habits and preferences that they have already stored), the job can be done safely, easily, and legally. Similar technology could be used to help last-mile delivery drivers navigate between stops.

    Integrate drivers’ digital lives

    Many people, especially younger ones, now expect their digital lives to be streamlined and integrated across work and leisure. To appeal to these individuals, SDVs could be equipped to remember drivers’ preferences regarding infotainment modes and transfer them across trucks. Their preferred smartphone apps, or similar ones, could also be made available via the truck’s console.

    By integrating various aspects of working life, we can make the driver’s job easier, as well as more pleasant. A common complaint from truck drivers is that they have to unload cargo themselves because there is nobody else to do it. An SDV can contact the destination to communicate the arrival time and nature of the cargo, increasing the chances of the relevant staff being on hand with the right equipment.

    When a truck is an SDV, ADAS features can easily be added. Some of these features can help to make truck-driving more attractive to younger people and women by allowing multiple tasks to be performed simultaneously. Stress levels for the driver are reduced significantly if they can organize their working day – including route optimization and scheduling of pickups and deliveries – while they’re on the road. This can be achieved through partial automation of driving tasks, whether via assistant systems or fully autonomous driving (say up to level 4), paired with services that help with routing and scheduling.

    Overcome negative perceptions of truck-driving careers

    For women in particular, personal safety issues can be a deterrent to working as a truck driver. Connected vehicle software can help here too. For example, AI-enabled services can monitor sensor data and warn when someone is approaching a stationary truck, and biometrics can control who has access to the cabin. Predictive maintenance can reduce or eliminate the risk of breaking down in a lonely spot. (And with SDVs, we can go beyond preventive maintenance via telematics and alerts to their natural successor, self-diagnosis by the vehicle.)

    Thanks to SDV connectedness, despatchers can more easily monitor drivers’ safety and send help if needed. The same communications facilities could streamline interaction between communities of drivers who can look out for one another, reducing any sense of isolation.

    Long hours away from home are another turn-off for many potential drivers. SDVs’ communications technologies can improve their work-life balance, with social media style software, in-vehicle display screens, and cameras keeping the driver in touch with family or friends during stops.

    Work-life balance can be further improved by advanced route optimization techniques. An SDV route can be automatically optimized to accommodate a driver’s personal preferences and constraints, as well as requirements such as refueling and rest stops. It can then be continuously adjusted to reflect the current circumstances such as weather and traffic conditions, helping drivers to finish work on schedule.

    Deliver better driver experience and financial benefits for fleet operators

    Despite their urgent need to recruit more drivers, at the end of the day truck buyers are still likely to focus on the more tangible benefits of SDVs. The good news is that many of the features that give drivers a better experience simultaneously increase productivity, uptime, or fuel efficiency – for example, predictive maintenance and real-time route optimization, both mentioned above.

    The same is true of services that address electric vehicles’ range limitations and shortages of charging stations (as discussed in our recent e-mobility blog). Suppose the truck’s battery is getting flat, and the nearest charging station has a long wait time. An SDV can save energy in various ways: for example by modifying engine parameters or environmental settings such as aircon, or by advising changes in driving behavior. With these adjustments, the driver can continue to a charging station with an acceptable wait time, improving productivity and likely reducing frustration too.

    Safer driving is yet another example of an SDV capability that benefits both employer and driver. Examples here include the use of sensors to detect when vehicles get too close to one another, or when drivers are tired and need a break. For example, a truck could raise an alert when its driver is blinking more frequently than is normal for them, indicating exhaustion.

    Make driver appeal part of the business case for SDVs

    For truck OEMs and tier 1s, the case for SDVs is clear. They can enhance revenue flows via a shift from one-off purchases to full lifecycle engagement, and improve automotive sustainability performance, for example by reducing waste in R&D processes. Ultimately, SDVs can help to make the brand central to customers’ businesses. In addition, selling SDVs makes sense as part of the journey to autonomous driving and in the context of companies’ overall digital transformation.

    Software-defined vehicles as passenger cars

    SDVs are already proving their worth in the passenger car market, where improved driver experience is a more obvious selling point. (Read our “point of view” report on software-driven transformation for more.)

    An excerpt from a recent Connected Mobility infographic – please download the full version here

    The question is how to demonstrate the value of SDVs to truck customers such as fleet operators. Industry concepts such as software-driven transformation are not always much help here. Instead, OEMs can point to the business benefits that result from SDV adoption. And right now, improved driver experience could be among the most important of those benefits because of its ability to help overcome driver shortages.

    For more information, visit the commercial vehicles area of Capgemini’s website, and read the earlier articles in this blog series.

    About Author

    Fredrik Almhöjd

    Director, Capgemini Invent
    Fredrik Almhöjd is Capgemini’s Go-to-Market Lead for Commercial Vehicles in the Nordics, with 25+ years of sector experience plus extensive knowhow in Sales & Marketing and Customer Services transformation.

    Jean-Marie Lapeyre

    Chief Technology & Innovation Officer, Global Automotive Industry, Capgemini
    Jean-Marie Lapeyre works with automotive clients to develop and launch actionable technology strategies to help them succeed in a data- and software-driven world.

      The post Software-defined vehicles: the answer to truck driver shortages? appeared first on Capgemini.

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      The art of creating customer-centric mobility experiences https://www.capgemini.com/insights/expert-perspectives/customer-centric-mobility-experiences/ Tue, 01 Aug 2023 06:27:07 +0000 https://www.capgemini.com/?p=942663 The post The art of creating customer-centric mobility experiences appeared first on Capgemini.

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      The art of creating customer-centric mobility experiences

      Dr. Rainer Mehl
      Aug 1, 2023

      Transforming and connecting the touchpoints that matter in the digital age

      The faster-than-expected transition to electric mobility and the ongoing digitalization of our daily lives has caused massive disruption in the automotive industry.

      In many ways, the playing field has been levelled and new doors have been opened. Tesla has emerged as a market leader, relative newcomers like Kia and Hyundai have strengthened their position against ‘higher-shelf’ brands, and a whole wave of digital-first Chinese newcomers are winning market share at home and gearing up to take on the European automotive market and potentially others. How can legacy automotive brands respond to this disruption?

      Against this backdrop of change and disruption, brand heritage, local presence, and familiarity still count. But arguably, for less than before. Amid the pandemic and subsequent supply chain squeeze, long wait times pushed many consumers toward brands they might not have considered before. But with the pandemic (hopefully) behind us and the supply chain situation easing, the deciding factor for many car buyers today is customer experience.

      What do we mean by customer experience in automotive?

      Customer experience is the sum of all interactions a customer has with a brand over time.

      Capgemini Invent: Time to level up

      In the automotive industry, this means everything from the moment you start thinking about buying or leasing a car, through your test drive and selection process, delivery or collection, driving time, and service visits, right up to the moment you return the car or decide to sell it.

      Our understanding of the automotive customer experience is very different to what it was just a few years ago and the opportunities to influence it are growing dramatically as several trends converge:

      • The transition to electric mobility and software-defined vehicles
      • The rise of new sales and business models, and ways to own or enjoy a car
      • Increased comfort with e-commerce, even with ‘big ticket’ purchases
      • Digitalization or ‘apple-ization’ and its growing role in our personal lives and in business

      With more opportunities and touchpoints than ever before and with the car being the third-most-frequented place by most people (after home and work), it is imperative that carmakers invest in and improve their approach to customer-centric mobility experiences.

      This isn’t just about getting the sale – it’s about becoming an integral part of the customer’s digital universe and building the type of trust and loyalty that people today have toward the Apple ecosystem. We need to look no further than Tesla for an example of a brand that has led with tech and reaped the benefits in terms of customer loyalty. And then there’s NIO, which proactively invites prospective customers into the NIO ecosystem and seeks feedback, even before they become NIO owners. The result so far? Seventeen times as many NIO app users as NIO car owners – proof that digital creates huge opportunities to attract and engage customers earlier in the sales process than ever before.

      So how can automotive brands use digital to transform their customer experiences and reap the benefits?

      The digital transformation of the automotive customer experience

      Let’s look at some of the key touchpoints that could be transformed or enabled with the power of digital and how they could contribute to longer and stronger relationships with customers.

      From dealer networks to agency sales and e-commerce

      A current focus topic in the automotive industry is the transition to Direct-to-Consumer sales (D2C) with many carmakers transforming their sales model towards agency or direct sales to drive omnichannel experiences with seamless channel integration – online and offline. Although many prestige brands still rely heavily on the showroom experience (the human touch should not be underestimated), consumers are increasingly comfortable with online channels, even for big-ticket items like cars.

      In a not-too-distant future, where dealers become agents, carmakers will have direct access to customers via their online channels. This should result in more-sophisticated and connected online experiences. Many brands have already invested in slick 3D configurators but these rarely allow for more than one-off configurations and perhaps an option to ‘request a call’, which often leads to fragmented or inconsistent experiences.

      Brands like Skoda are dipping their toes into the metaverse, and – while it all feels a little experimental for now – it will be interesting to see what role this emerging space plays in the consideration phase of the sales process and beyond. 

      Look out for more simplification and integration, and less friction when buying or leasing a car in the future – leading brands are working towards enabling car purchases in just a few clicks with financing options available with just a few more.

      Carmakers looking to keep lead times short and inventory levels lean should be able to provide real-time access to available cars – new or used – that match or closely match customer configurations. This will give each customer the choice of ordering their perfect car and waiting for its production, or picking up a close match immediately. The technology already exists to make this vision a reality – a well-configured CRM and real-time access to a database of available cars – so we should see this become standard for most brands in the near future.

      Apps that add value

      Customers today aren’t just looking at the car – its performance, comfort, features, and price. More than ever, they’re also considering the mobile application that accompanies it and evaluating if and how it fits and complements their personal digital ecosystem. Compatibility with Apple CarPlay and Android Auto have become table stakes but it’s with carmakers’ own apps where they can really make a difference.

      Will the app enable you to unlock a car so you can leave your keys at home? Does it serve as an integrated way to pay for fuel or charge? Does it allow you to remotely check the status of your car and prepare it for use? And, perhaps most importantly, is the app reliable and enjoyable to use? This is one of the areas where Tesla has led the way and it’s clear that the Tesla mobile app is an important contributor to the brand’s loyal following.

      The car and smartphone are key companions in daily life. If they work together well, customers are happy.

      Continuous evolution with ‘over the air’ updates

      Not many car owners enjoy visiting dealers for service and maintenance visits. If a dealer manages this experience well, they might call or notify a car owner of the need for a visit and proactively suggest available slots. But this doesn’t change the fact that such visits are generally a hassle – one that takes precious time out of an already-packed schedule and delivers little tangible value beyond peace of mind.

      With electric and software-defined cars, such visits can be reduced and many checks, updates, and enhancements can be executed ‘over the air’ using software and an internet connection. This is what we expect with our smartphones and it’s increasingly what customers expect with their cars. Yes, this might result in fewer physical touchpoints between customers and car brands (or dealers), but the potential to improve customer satisfaction with convenience and by making a car better and more useful over time outweighs any potential drawbacks.

      In this regard, software is a true game changer – one that can help strengthen and extend the relationship between brand and customer.

      Simplified and satisfying charging experiences

      The filling station experience has never been much of a concern for automotive brands. After all, with abundant infrastructure, experiences lasting just a few minutes, and customers free to make their own choices, there was little carmakers could do to influence the experience.

      With electric mobility, the situation is altogether different. Today, carmakers have much to consider – what charging speeds to enable, whether to enable vehicle-to-appliance/home/grid charging, which infrastructure to enable compatibility with, whether to partner up or build proprietary infrastructure, and whether to get involved in providing payment solutions or not (e.g., via the car’s mobile app). These are questions that require deep consideration and, in some cases, the acquisition of new capabilities and assets.

      Today, we see a variety of approaches to charging. Ionity is a European example of a joint-venture approach to providing charging infrastructure, VW Group has the Electrify America company for the US market and Tesla has its proprietary global network, which – having established itself as best in class for reliability and availability – is now opening up to partners like GM and Ford in the US. In line with its premium-brand credentials, Audi has piloted charging hubs as convenient stops within an aspirational lifestyle.

      One thing is clear – providing access to seamless and convenient charging experiences is a key success factor for excellent customer experience with electric mobility.

      Autonomous driving and ways to pass the time

      Among the glittering array of new products and technologies on show at this year’s CES event in January, autonomous vehicles attracted far less attention than in previous years. The hype machine may have cooled, but assisted and autonomous driving remain firmly on the agenda of every major car company. Of course, the need for proven safety means there is no room for error. Yet the prize for being among the first to reach the recognized autonomous driving levels is potentially huge – an unprecedented level of customer trust and the opportunity to engage passengers and drivers with new services while the car looks after the task of driving.

      Indeed Audi, in designing its ‘sphere’ concept cars, talks about them being “a third living space”, alluding to the amount of time customers will spend there and the opportunity to fill it with revenue-generating options. CARIAD already announced its intention to bring an app store to VW Group vehicles, hinting at the development of a proprietary ecosystem as an alternative to the Apple and Android offerings.

      Gaming, a popular pastime for much of today’s car-buying demographic, could be an area to watch. With Audi investing in the mixed-reality Holoride solution, BMW partnering with AirConsole, and the latest-generation higher-end Teslas offering Steam integration, is it possible that gaming options will play a part in buyers’ decisions? Could we see carmakers seek to differentiate through user experience or exclusivity on titles in the way Nintendo and Sega did in the 90s?

      With gaming platforms these days typically requiring connectivity and subscriptions, this could soon be a highly valuable source of revenue and data for carmakers. The decision by Honda and Sony to team up and form the Afeela brand certainly suggests that combining mobility and top-class in-car entertainment could be a huge opportunity to stand out in a crowded market.

      Development of autonomous driving levels per OEM over the next 5 years -
      Source: Capgemini Invent: Time to Level Up – How to Win the Race for Customers with Superior Experiences.

      Personalized in-car experiences (and companionship?)

      Today, we expect to be able to personalize many of the products and services we buy, and the in-car experience is going in the same direction. Most automakers have been offering driver profiles (saved seating and steering-wheel positions) and changeable ambient lighting in their cars for years now, but some of the new electric offerings – particularly those from China – are taking personalization to a new level.

      We’re increasingly seeing cameras inside cars, and these are used for a variety of functions – to recognize the driver and adjust to their preferences (seating and temperature), to detect tiredness, driver mood, and then tailor services (e.g., playlists) and actions accordingly. What could the future hold in this area?

      BMW showed us its vision of the car as a digital companion with its bold DEE concept, with the promise of deeply immersive experiences and an AI assistant that learns from you, and to be more in tune with your tastes. What’s presented as a vision by BMW is already on offer elsewhere. NIO’s Nomi assistant brings in a remarkable and fast learning experience that feels lightyears ahead of what many people are accustomed to today.

      And while for some, it might feel a bit much, it’s easy to imagine car ownership turning into companionship and a subsequent increase in customer loyalty. Think about it … would you find it easy to say ‘goodbye’ to a companion that had learned about your preferences and who had helped and accompanied you on thousands of daily commutes and road trips? The presence and role of the digital assistant is a whole new dimension that will be fascinating to observe in the future.

      Reaching our destination: an ecosystem that we can trust

      With all the excitement around how to enhance the car buying/leasing and ownership experience and the current pace of change in the industry, it’s easy to lose focus on what needs to happen at the end of the ownership or lease period.

      If you’re an iPhone user, you know how much of a wrench it would be to leave the Apple ecosystem. This is at least partly because we’ve become heavily accustomed (reliant even) on a specific UX and we’re generally happy to keep our data stored in an ecosystem that we trust in exchange for the many conveniences we enjoy every day.

      As the provider of the ‘third living space’ and being at least somewhat responsible for ensuring safe and satisfying transport in our daily lives, automotive companies are in enviable positions. They can truly make their cars and brands integral parts of their customers’ lives in ways that few other companies can. By embracing the challenge and using the power of digital to transform existing touch points and create new ones, there is no limit to how long the customer experience can last.

      Data as the key to unlocking value

      When we consider all the touchpoints above, the common denominator is the presence of and reliance on data. With a Direct to Consumer (D2C) model, automotive companies understand who their customers are from day one and can start building the relationship.

      By using the data generated by every interaction with an app, every journey, every acceleration, every service accessed and every charge, brands can propose additional services, create new services, subtly adjust existing functions to better suit driver needs and preferences, and much more. In short, they can get closer to customers than ever before and continuously improve the relationship.

      But are incumbent automotive brands set up to work like this today? In most cases, the answer is ‘no’. Data often sits in siloes, owned by specific areas of the business that perhaps don’t see how it can add richness to the big picture of the carmaker-customer relationship. Organizationally, the area of customer experience is typically limited to sales and service visits.

      There is a strong argument for the creation of a dedicated customer experience domain that has access to data from right across the car-and-customer relationship (CRM, telematics, subscriptions, Finance, Insurance), and has the goal of bringing it all together to understand, strengthen, and extend the experience, wherever possible.

      This is no small step and it goes against the way many players in the industry have operated for decades. It requires organizational and technological transformation. However, the benefits – increased revenue, greater loyalty, and the potential for stronger and longer relationships and an integral place within the customer’s digital universe – are worth the effort.

      To learn more about how automotive brands can enhance the automotive customer experience, I encourage you to check out Capgemini Invent’s Point of View “Time to Level Up – How to Win the Race for Customers with Superior Experiences.”

      Capgemini at IAA Mobility 2023

      The world’s largest mobility event is coming soon

      Explore more:

      About author

      Dr. Rainer Mehl

      EVP and Managing Director Strategic Account Intelligent Industry
      A leader who serves: leadership in the digital age is Rainer’s passion allowing him to successfully lead transformations both at clients and in service organisations. He supports companies in their digital transformation with a focus on customer centricity, agile organization and new business models

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        ​How a system-based modular approach minimizes risk and accelerates SaMD go-to-market​ https://www.capgemini.com/insights/expert-perspectives/how-a-system-based-modular-approach-minimizes-risk-and-accelerates-samd-go-to-market/ Wed, 26 Jul 2023 14:08:44 +0000 https://www.capgemini.com/?p=940858

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        How a system-based modular approach minimizes risk and accelerates SaMD go-to-market​

        Capgemini
        27 Jul 2023

        In the field of healthcare systems compliance, the difference between 99% and 100% is a chasm.  ​ 

        “Software defect.” “False upstream alarms.” “Firmware error.” “Login error.” “Software bug.” “Sensor failure.” “Cybersecurity vulnerability.” The FDA list of software-related recalls is sobering reading. We see the story behind each event – the teams that worked overtime designing and building a new device, quality assurance professionals checking each and every vulnerability, last-minute adjustments, the elation of a seemingly successful release… And all the while a tiny flaw lay hidden from sight, with the power to derail everything compromising safety and exposing liabilities. ​

        As a legal manufacturer, we specialize in safety and compliance for Software as a Medical Device (SaMD). It’s a fast-growing field, with risks hiding in every nook and cranny. How do we make sure we catch and neutralize every risk? How do we ensure safety and compliance, without sacrificing speed? Let’s dive in. ​

        Compliance and agility by design​

        There’s a common fear that safety and compliance slow down go to market. A justified concern? Yes and no. Of course, extra steps take extra time. That’s why, wherever possible, we work to engrain safety and compliance considerations into every process. For example, a remote patient monitoring system that records patient data needs to do many things, some are basic functions; others cross over into the “safety” category. Safety and compliance are mandatory and are integrated into the development process. Pharma and MedTech companies will speed development and improve quality if they adopt two changes: agile processes combined with modularity by design. To see how modularity adds value, let’s look closer at the challenges SaMD teams face.​

        Challenges of connected systems ​

        With today’s more connected and complex systems, the boundaries of what constitutes “Software as a Medical Device” are often blurred. For example, when the system is distributed, with parts of an application running on a wearable, mobile phone, or in the cloud, and  a combination of medical and non-medical functions, is the whole system SaMD? How do we manage a combination of safety and non-safety, administrative and other functions that all need to work together to fulfill a medical purpose? If the system is developed as monolithic, this increases effort to get regulatory approval and places additional compliance effort to modify, improve or add functions after the system has received initial market authorization. What’s the solution?​

        The benefits of modularization for connected health ​

        A pragmatic approach to accelerate SaMD development, manage safety and regulatory complexity, and maintain flexibility, is modularization. We segregate SaMD products by function and by risk category (high, medium and low risk). This makes it possible to apply the appropriate level of risk control and testing measures in each case. Using pre-built, ready-to-use SaMD modules developed under certified processes and qualified tools, assures reliable, fast and compliant software. ​

        Modularization reduces regulatory complexity and – together with agile development models – speeds up the time to market, while providing the flexibility we need to continuously adapt functions. Most critically, it reduces risk. The “hidden flaw” we talked about earlier – in a modular system there’s no place to hide, and agile development makes it possible to and correct flaws early in the development cycles.​

        Reducing risk and regulatory complexity​

        We believe that risk is best managed when technical and regulatory responsibility go hand-in-hand. The closer a development team is to the consequences of success or failure – the more skin they have in the game – the more we count on them to scrupulously manage risk. We’d been working in the SaMD field from the start, at the intersection of software, life sciences and regulatory, so taking regulatory responsibility for our work was a natural step. How to manage regulatory compliance is an important question for every innovator – a far-reaching question with many dimensions. For us, most crucial is the link between technical and regulatory responsibility.​
        ​You can find more about our offer and our Legal Manufacturer capabilities on our webpage, and we’re also available to consult on any aspect of risk and compliance.

        When your innovations hit the market, dozens of factors affect their success. Avoidable mistakes should not be one of them. Let’s make your products flawless.  

        Meet our experts

        Andrew Koubatis

        Intelligent Medical Products and Systems Lead, Capgemini Engineering
        Providing Pharma and MedTech with service offers to accelerate and de-risk product development. “Intelligent products and systems allow us to break the traditional boundaries of the healthcare ecosystem, providing greater patient insights through data, more effective, reliable and personalized treatments, driving better outcomes and supporting value-based care with connected and interoperable technologies.”

        Frédéric Burger Ph.D.

        CTO Life Sciences and Regulatory Affairs, Global Life Sciences Center of Excellence Leader, Capgemini Engineering
        Leading the global life sciences portfolio and solutions in Pharma and Medical Devices “This is undoubtedly a new stage in the use of data in the life sciences industry. With the combination of Regulatory Sciences and a clear strategy on Digital implementation, the data is now at the core of any new journey. We support our clients with expertise, strong assets and methodologies for accelerating their transformation”.

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          Sharing without showing: data clean rooms allow for unprecedented collaboration https://www.capgemini.com/insights/expert-perspectives/sharing-without-showing-data-clean-rooms-allow-for-unprecedented-collaboration/ Wed, 26 Jul 2023 04:41:14 +0000 https://www.capgemini.com/?p=939350 The post Sharing without showing: data clean rooms allow for unprecedented collaboration appeared first on Capgemini.

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          SHARING WITHOUT SHOWING: DATA CLEAN ROOMS ALLOW FOR UNPRECEDENTED COLLABORATION

          Jennifer Belissent
          26 July 2023

          Imagine the potential for secure data collaboration. With the boundaries between different companies, organizations, and entire industries blurring, the use cases are endless. Organizations can perform joint data analysis and train machine-learning (ML) models while ensuring that confidential information will stay protected from their sharing partners. It’s all happening in the world of data clean rooms.

          Pharmaceutical companies can identify the best hospitals for clinical trials with a look-alike analysis against patient records. Insurance companies can collaborate to identify fraudulent claims. Media outlets can offer premium placement to advertisers to ensure targeted messaging. Loyalty programs can deliver truly personalized services across hotels, airlines, and other services. Telecom operators can collaborate with location data to enrich those personalized services. Emergency and social services can collaborate to help those in need.

          Yet in many cases, the relevant data is personal information, and protected by privacy laws and bonds of trust. How can that data be shared?

          The use cases for secure collaboration with data clean rooms are endless

          Imagine the following scenario.

          A crowd of spectators is watching a big game and the teams are tied. The tension mounts. The fans grow restless. He shoots. He scores! The roar of the crowd can be heard all the way down the neighborhood street. And all the consumer brands want to know who is watching and how to reach these audiences. Yet, these sports fans are watching the game in the privacy of their homes, and the network they’re watching on must legally protect their data.

          How can these media outlets share their viewer data – or the insights from it – without violating data protection laws and the trust of their subscribers?

          It turns out that a similar question was posed by an academic in the early 1980s. Professor Andrew Yao introduced the problem: Alice and Bob, both millionaires, want to know which of them is richer but neither wants to reveal his or her exact wealth. Through complex mathematical proofs, Yao’s Millionaires’ problem was solved, proving it is possible to share insights without showing the underlying data. Fortunately, modern methods do not require arduous manual calculations.

          “Sharing without showing? You bet!”

          Increased demand for data sharing

          For potential advertisers or anyone who wants to collaborate with data, that’s great news. Data sharing and collaboration deliver business value. A recent Capgemini study, Data sharing masters, found that companies with collaborative data ecosystems reported better business outcomes including new revenues, reduced costs, increased productivity, and greater customer satisfaction. And that promise has spurred new data ecosystem initiatives.

          Companies have long used their own data to better understand their customers or to improve operations. Increasingly, data teams turn to external data sources to enrich their internal data and enhance analytics. Budgets for external data are significant and growing. In a recent survey conducted by external data platform Explorium, 22 percent of respondents said they were spending more than $500,000 on external data, with 13 percent saying they spent more than $1 million (up from 7 percent from a similar survey in 2021).

          Customer data was the number one type of data acquisition: 52 percent purchased data on companies, followed by 44 percent purchasing demographic data. And the number of sources has grown as well: 44 percent of firms acquire external data from five or more providers. That’s up from only 9 percent the previous year. However, procuring external data is not without challenges, with regulatory constraints often topping the list. Concerns about GDPR or other privacy regulations loom large, and for good reason.

          Introducing modern data clean rooms

          Not long ago, data sharing meant copying and sending files to a partner. That practice certainly complicated data governance. Short of a manual audit, knowing who accessed the data and for what purpose was impossible. Now, using the principles demonstrated by Yao’s millionaires, two or more parties can derive insights from data without revealing the underlying information.

          With a Snowflake Global Data Clean Room, each party controls its own data, allowing governed, controlled analytics by other parties. That is to say, each party specifies who can access the data and for what purpose. Let’s take a look at how it would work with Yao’s two millionaires, Alice and Bob.

          First, each party creates a table with the data to be shared. Then one party, let’s say Bob, creates a table to store allowed statements. This is where the queries that Bob will allow another party to run against his data will be maintained. He then creates an access policy granting use of these statements and applies this access policy to his data table.

          Next, Bob defines the exact statement or query he will allow, and inserts it into his “allowed statements” table. The statement includes the comparison of their wealth and the answers that will be returned in each case: “Bob is richer,” “Alice is richer,” or “Neither is richer.” Finally, he grants Alice permission to access and use his data for only this specific purpose. Alice then asks the question in the form of the specified query and receives the response: Bob is richer. Sorry, Alice.

          Now imagine a more realistic business scenario where two companies want to know which customers they have in common – an overlap analysis. They would put the data in tables, establish the statements to compare their customer lists, and specify the information to be returned. Or one company might be interested in finding new prospects among a partner’s customers and would perform a look-alike analysis comparing customer attributes.

          Data clean rooms transform the ad world

          In a real use case, commonly seen in media and advertising these days, brands want to optimize their ad spend through better targeting to specific customers or personas – like the fans watching that exciting game. Media outlets want to offer premium placements by knowing exactly which programming the brand’s customers are watching. Comparing customers is a win-win. However, neither wants to show the underlying data. The clean room allows them to share without showing. In this case, as illustrated in the diagram, the returned information would include a customer count for each of the media outlet’s programs, but not specific customer data, in order to ensure compliance with privacy regulations. All queries of the data would be monitored and logged for audit purposes.

          In the past, this scenario required data to be copied and moved across the AdTech value chain from enrichment to activation to attribution. Not only were there the aforementioned governance concerns, but that data was also immediately stale. With Snowflake, live, near real-time data can be shared where it resides – no copies necessary. Data governance capabilities allow all parties to assign access and use policies that limit both who can query the data and exactly which queries are allowed. Additional capabilities add further security to the clean room. Data can be encrypted, anonymized, tokenized, or pseudonymized with built-in hashing functions, or obfuscated with data masking or by injecting differential privacy.

          With today’s technology, data clean rooms allow parties across teams, companies, government agencies, and international organizations to collaborate and securely share sensitive or regulated data. As Thomas Edison said, “The value of an idea lies in the use of it.” The more data is used, the more value is created. Secure data collaboration accelerates value creation.

          INNOVATION TAKEAWAYS

          CROSS – INDUSTRY COLLABORATION AND DATA SHARING

          A growing trend that’s here to stay.

          DATA CLEAN ROOMS FACILITATE JOINT DATA ANALYSIS AND ML

          While ensuring that confidential information will stay protected

          from sharing partners.

          DATA ECOSYSTEMS AND SECURE DATA COLLABORATION

          They accelerate value creation.

          Interesting read?

          Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 6 features 19 such fascinating articles, crafted by leading experts from Capgemini, and key technology partners like Google,  Starburst,  MicrosoftSnowflake and Databricks. Learn about generative AI, collaborative data ecosystems, and an exploration of how data an AI can enable the biodiversity of urban forests. Find all previous Waves here.

          Jennifer Belissent

          Ph.D., Principal Data Strategist, Snowflake
          Jennifer Belissent joined Snowflake as Principal Data Strategist in 2021. Prior to joining Snowflake Jennifer spent 12 years at Forrester Research as an internationally recognized expert in data sharing and the data economy, data leadership and literacy, and best practices in building world-class data organizations. At Snowflake, Jennifer helps customers develop Data Cloud strategies that facilitate data access and deliver business value. Jennifer earned a Ph.D. and an M.A. in political science from Stanford University and a B.A. in econometrics from the University of Virginia.

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            Closing the generational life insurance gap with education https://www.capgemini.com/insights/expert-perspectives/closing-the-generational-life-insurance-gap-with-education/ Tue, 25 Jul 2023 10:11:04 +0000 https://www.capgemini.com/?p=939913 American adults continue to put short-term priorities ahead of saving for retirement or planning for a catastrophe.

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            Closing the Generational Life Insurance Gap with Education

            Samantha Chow
            26 July 2023

            The percentage of Americans covered by life insurance has been steadily decreasing since the 1970s.

            My family is no exception.

            Traditionally, newborn life insurance policies protected against the financial burden of death. My great-grandmother purchased a $1,500 life insurance policy for my grandmother when she was born. When my mother was born, her grandmother bought one for her. Even my brother, only ten years older than me, has been insured since birth. As a child of the ‘70s, though, I was the first in generations not to be insured in childhood.

            Significant advances in healthcare, changes in the socioeconomic and demographic characteristics of the population and lower war casualty rates have led many to experience mortality resistance. Despite the recent pandemic, the threat of death feels less imminent than it once did and today, we are more likely to be able to cover the costs of a funeral. Therefore, the urgency to insure the lives of our loved ones — and especially youngsters — has subsided.

            Ultimately, this change has led to a startling reality: Less than 60% of Americans are currently covered by life insurance — a number that has declined steadily since 1971, with a 13% reduction in the last decade alone.

            Mortality resilience and the growing generational wealth gap

            American adults continue to put short-term priorities ahead of saving for retirement or planning for a catastrophe. They prioritize vacations (29%), recreational activities (23%), and paying monthly bills (49-60%). Along with believing life insurance coverage is “too expensive,” many say they have “other financial priorities”  beyond saving for what’s next. As a result, less than half of Millennials and Gen Zers currently have a life insurance policy.

            And yet, global mortality resilience, a measurement of how resilient we are to death, is low, at just 43%, and the global mortality protection gap hit a record $406 billion last year. Both are key indicators that households are more vulnerable than ever to the loss of a breadwinner.

            At the same time, the majority of seniors today have life insurance coverage. And with the payout of their policies, we are about to experience the greatest wealth transfer the world has ever seen. The result is record-breaking distribution rates of death benefits, with approximately $89 million in 2022, compared to $76 million paid out in 2019.

            The question is: Will the beneficiaries of these policies — often Millennials and Gen Xers —reinvest in securing their futures, and the future of those after them, with proper life insurance coverage?

            Meeting the needs of the next generations

            Meeting the needs of the next generation will require education and innovation.

            For one, it is our responsibility to teach Millennials, Gen Xers (and younger generations) that the true value of a life insurance policy is not only realized after one’s death but can also serve as income replacement, an investment vehicle, cover long term care — and more.

            We also need to build a library of policies that match the lifestyle choices of Millennials and Gen Xers to help bridge the gap. If Gen X wants to save, pay their bills and retire early, then maybe carriers need to reconsider offering a Return of Premium Term, for example, that returns the policy premium if the insured outlives the term.

            Here are examples of how two life insurance companies are already bridging the life insurance gap with education and product — across the generational and financial divide:

            • Kemper Life Insurance : With a focus on low-income communities, Kemper’s engagement approach is very personal. They provide door-to-door sales and premium collection services, establishing face-to-face relationships with their customers. While many are not in the financial position to purchase large life insurance policies, Kemper’s goal is to help customers make the right financial decisions for their security whether it be life, accident and health or contents coverage.
            • Prudential Financial : Prudential’s Stages for Retirement education program is designed to help younger generations prepare for retirement at every stage by providing personalized projections on how much they will need for retirement, which products will help them meet these projections over time and advice on how to reach savings goals throughout their lives.

            To move forward, we need to take a step back and reeducate everyone on the value of income replacement, debt payment, and cash value opportunities within life insurance policies, and to provide products that fit today’s needs. The true value of life insurance has not changed; it’s been forgotten. It’s our job to help everyone remember.

            Author

            Samantha Chow

            Global Head, Life Insurance, Annuities, and Benefits Leader, Capgemini Financial Services
            Samantha has over 20 years of experience in the L&A and A&H industries working for carriers in positions across the value chain, evaluating technology and consulting as an industry analyst, and leading the technology roadmap for policy administration systems.

              Related research and insights

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              Data and tech: The future of commerce is connected https://www.capgemini.com/data-and-tech-the-future-of-commerce-is-connected/ Tue, 25 Jul 2023 09:27:11 +0000 https://www.capgemini.com/?p=939880 The post Data and tech: The future of commerce is connected appeared first on Capgemini.

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              Data and Tech: The future of commerce is connected

              Kees Jacobs
              Jul 25, 2023

              Part 3: Embed data within the business

              Welcome to the third part of this initial blog series on the future of commerce and the role of data and technology. In the earlier parts, we discussed the impact of channel-less commerce, the need for connected capabilities, the significance of data-driven competencies and value, and the importance of managing data foundations, data collaboration and composable technology architectures. In this final part, we will focus more on data cultures and business-transformational data journeys at scale.

              Data-driven competencies: From data adhocracy to data democracy

              Data and technology are critical for executing end-to-end connected commerce capabilities and navigating the evolving consumer goods and retail landscapes. Companies need to develop next-level data and technology competencies, ensuring that (real-time) intelligence is embedded in every business decision, operational action, and consumer touchpoint. From experiences with our clients, I know that most companies have made progress in this area through omnichannel initiatives, and often have some strong ‘pockets of excellence’, but there is still a need to further democratize data capabilities across the whole organization. Successful data masters have both the foundational data infrastructure to make data and insights accessible and the right data behaviors to leverage data for business impact at scale.

              Data culture: The hearts and minds

              Ultimately, while data and technology professionals play a crucial role, I clearly see that the responsibility of data ownership and value creation should be more prominently extended to business users. A data-driven culture shift is necessary for success in a data-driven era. This requires addressing the hearts and minds of employees across various functions, such as category managers, supply chain operators, store staff, and B2B sales teams. Integration of data within business processes, breaking down silos, transparency in efficiency and effectiveness measures, and fostering open innovation are all essential elements of a data culture. Investing in new skills, both technical and soft, is crucial for driving business outcomes and working in multidisciplinary teams.

              The transformational data journey: Towards the end-to-end game

              To embark on a successful data-driven connected commerce journey, I see three pillars to be most critical: intelligence activation within the business, orchestration for scale across the organisation, and appropriate data and technology enablement. Intelligence activation involves embedding data, AI, and analytics at the heart of business operations and decision-making, demonstrating concrete business value. Orchestration for scale requires a balanced approach that combines centralized and local capabilities, as well as skilled talent and automation. Data enablement ensures the proper management of data platforms, data quality, governance, and collaboration.

              The approach: Think big, start small, scale fast

              Achieving maturity on these three dimensions simultaneously is essential for unlocking the full potential of data-driven commerce. We have good experiences by integrating all 3 dimensions in so-called ‘hothouses’, bringing together the data and tech capability with business processes and cultural change to help embed analytics into core processes and your people’s work. Multi-disciplinary teams (with T-shaped profiles) are focused on demonstrating real business value (with rapid learning cycles from proven benefits) while building the blue-print for accelerated scaling and enabling the fit-for-purpose data and technology tooling.

              Where is your company on this journey? A few questions to ask yourself:

              1. Do you see measurable value from data across your end-to-end business?
              2. Are you managing your underlying data foundations accordingly?
              3. Are you effectively scaling up, taking advantage of new innovations – and do you run your data and analytics engine efficiently?

              The future of commerce belongs to those who can harness the power of data and technology. Embracing channel-less commerce, leveraging connected capabilities, and cultivating a data-driven culture are crucial steps for success.

              By tapping into various data sources, collaborating within ecosystems, and leveraging advanced analytics, companies can gain valuable insights and deliver personalized experiences to consumers. Investing in data foundations, adopting composable tech architectures, and focusing on the hearts and minds of employees will further accelerate the transformation towards a data-driven era of commerce. It’s time for companies to embrace the opportunities presented by data and technology and position themselves at the forefront of the evolving consumer goods and retail landscape.

              This was the last part of this blog series. We will further elaborate on the various topics mentioned in subsequent blog series – stay tuned for those.

              The bottom line: The future of commerce is connected, and it’s essential for companies to embrace it!

              Meet the author

              Kees Jacobs

              Consumer Products & Retail Global Insights & Data Lead, Capgemini
              Kees is Capgemini’s overall Global Consumer Products and Retail sector thought leader. He has more than 25 years’ experience in this industry, with a track record in a range of strategic digital and data-related B2C and B2B initiatives at leading retailers and manufacturers. Kees is also responsible for Capgemini’s strategic relationship with The Consumer Goods Forum and a co-author of many thought leadership reports, including Reducing Consumer Food Waste in the Digital Era.

                Explore more

                Reimagine the future of consumer products

                Redefining success in the new era of connected commerce

                What matters to today’s consumer 2023?

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                Why realizing a circular economy requires a holistic approach: 5 key factors to successful circularity https://www.capgemini.com/insights/expert-perspectives/why-realizing-a-circular-economy-requires-a-holistic-approach-5-key-factors-to-successful-circularity/ Mon, 24 Jul 2023 14:00:00 +0000 https://www.capgemini.com/?p=937159 The post Why realizing a circular economy requires a holistic approach: 5 key factors to successful circularity appeared first on Capgemini.

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                Why realizing a circular economy requires a holistic approach: 5 key factors to successful circularity

                Clément Chenut
                17 Jul 2023

                Achieving a circular economy requires complex and iterative transformation initiatives, but the ambition is worth pursuing

                Circularity: From a theoretical concept to an industrial reality

                While it still only represents 7.2% of the global economy in 2023[i], the circular economy is experiencing exceptional momentum. Circular goes well beyond recycling. In fact, the most untapped value lies between product end-of-use and its recycling, opening up new business models such as product-as-a-service, product life extension, sharing platforms, sell and buy-back, repair and maintenance services, as well as second-hand platforms. The ultimate objective is to create environmental and business value by minimizing the use of raw materials and resources and, therefore, production of waste. This involves creating new industrial value chains, embracing business models based on long-term value, and eco-systemic solutions to help tackle global challenges such as climate change, biodiversity loss, waste, or pollution.

                Beyond the trend, why is the circular economy gaining more traction?

                Several factors are at a play in accelerating the adoption of circular economy principles and initiatives by some companies, and even in a few organizations a more holistic transformation. On one hand, several risks are prompting organizations to adopt circular economies – to remain competitive in the long term.

                These include environmental risks (eg increased GHG emissions, scarcity of resources), but also systemic risks linked to geopolitical and economic events disrupting supply chains and the sourcing of materials (eg war in Ukraine, Covid-19 crisis, Suez Canal blockage) Circular business models can therefore help organizations become more resilient and better address such risks.

                Social pressures are also at play: more than 65% of buyers consider sustainability when making a purchase. In addition, regulation on the matter is tightening, in particular in Europe (Circular Economy Action Plan, AGEC law). These environmental, social, and legal factors are pressuring organizations to change.

                While companies need to respond to these external factors, the circular economy can, at the same time, bring a lot of benefits. As an alternative to traditional business models, it could yield up to $4.5 trillion by 2030. Beyond the economic value, deploying circularity at scale could help reduce GHG emissions by 39% and ease pressure on virgin materials by 28%. A circular economy also brings social value by creating employment opportunities in the field, attracting new clients, and improving brand image. A circular economy therefore brings long-term value to businesses by helping them become more resilient and competitive, as well as making their offerings more desirable to their consumers.

                How to move towards a circular economy?

                Given these challenges and opportunities, the transition to a circular economy would seem to be an inevitable path. But having the right components is key for businesses to drive their circularity transformation successfully across all stages of their value chains (from sourcing to end-of-life). To do so, companies need to deploy a holistic approach across these five main factors:

                • Economic scarcity is essential in defining a company’s strategy. Businesses must rethink their strategy to bridge the gap between increasing customer demand on one hand and limited supply in a world with finite resources on the other hand. Business performance is no longer a matter of being competitive in the short term, but of being resilient in the long term – to face potential supply risks, while being mindful of planetary boundaries. For example, Northvolt launched a joint venture with Volkswagen to create a gigafactory of electrical batteries, the first one to be established in Europe. In 2021, the Group produced its first fully recycled battery cell with an ambition to equip 3 million electric cars by 2030. This well illustrates the importance of integrating a circular economy early on at the strategic level, with the objective of supporting an economy of value rather than volume.
                • Product design is the cornerstone of the circular economy. We tend to consider economic circularity at the end of the value chain, synonymous with recycling or repairing (think about mobile phones as an example). But did you know that over 70% of a product’s lifecycle impact is determined during its design phase? Design is a critical stage for businesses to define their circular models. For instance, IKEA designs furniture to be easy to assemble and disassemble, taking into account the diverse lifecycles of its furniture. This can include not only purchasing but also rental, buying back old products that the brand will resell in “second life spaces,” and donating to associations. Product design is key to developing feedback loops between the different stages of a lifecycle and to adapting with agility to an increased variety of consumer behaviors by leveraging product functionality, modularity, and connectivity.
                • The greatest source of value lies between a product’s end of use and recycling. There are many unexplored upcycling opportunities involving reusing, repairing, and “remanufacturing” products. Depending on a product’s level of complexity, recovering components or certain parts can represent sources of supply delivered upstream within the production chain. In a circular economy, the product is analyzed as a whole: some parts may be sufficient to upgrade a product that will no longer be considered as waste. This involves in-depth reflection on reverse logistics, mobilizing supply chains dedicated to the reverse flow of products and materials; this can involve maintenance, repair, remanufacturing, etc. The “Re-Factory”, Renault’s circular economy factory, located in Flins in France, is part of this approach. The manufacturer extends the life of its vehicles and components (such as gearboxes or turbochargers) by offering advanced remanufacturing services based on a unique ecosystem of partners.
                • Achieving scalability requires the transformation of the entire ecosystem. Deploying a circular economy marks the transition from the concept of the extended enterprise, based on the exchange of information between a company and its partners (suppliers, service providers, etc.), to the establishment of something bigger – ecosystems. To enable this step change, new value chains need to be created by partnering with:
                  • Competitors (horizontal partnerships): Illycaffè has, for instance, proposed to its competitors to agree on a unified recycling standard for all their coffee capsules. The idea is to pool all the capsules and, by extension, the recycling process.
                  • Actors from other sectors (vertical partnership): Citeo is financed by companies to support the end-of-life of household packaging and paper, including their recycling. Citeo has developed eco-design, collection, sorting, and recycling services, thanks to the pooled action of its customers behind the creation of these solutions, and in partnership with local authorities and professionals.

                    These examples demonstrate how collective sharing of information with an ecosystem of diverse actors is key to driving systemic change and defining innovative models. Collective sharing of data will be another important enabler in accelerating the circular economy transition.
                • Technological innovation is the transformation catalyst. Two major innovations will fuel further disruptions:
                  • The emergence of biomaterials and synthetic biology will provide economically viable alternatives to the scarcity of certain key resources (eg bio-based materials, insect-based proteins), and high planet-impact processes (eg chemical recycling, precious metal recovery). For example, Ynsect and Innovafeed have developed innovative protein flours made of insects that are much less energy intensive and produce less water than traditional proteins.
                  • The development of reusability solutions in product design and operations (eg product digital passports, materials traceability, exchange platforms, decision-making tools, or design and simulation capabilities) will become increasingly important. For instance, digital twins can help develop next-gen supply chains by creating virtual replicas of physical products, systems, or processes. These replicas monitor, control, and optimize all aspects of a physical twin. This is a technological breakthrough that can accelerate implementation of the circular economy at the scale of an entire sector.

                What should be done next?

                The five factors outlined above are we believe good entry points for businesses to build their own solutions to achieve circularity, identifying and developing the interdependencies existing between the different stages of their value chains. Businesses will have to be creative and agile, relying on their human, physical, and technological assets to shift towards circular models and deliver economic and environmental value.

                Just reducing carbon emissions is insufficient for achieving net-zero trajectories. Organizations need to start thinking in terms of planetary boundaries and resource scarcity when developing their business models. By doing so, they will become more economically resilient in the long term and will better protect our planet.

                Achieving a circular economy requires complex and iterative transformation initiatives, but the ambition is worth pursuing. Organizations following this path will be more profitable in the long term by capturing new market shares, delivering tangible value, and setting new industry standards. Our next articles will deep-dive into some of the tools organizations should start implementing to start transitioning.  

                Thanks to additional contributions from Alice Blanchard and Stanislas Ancel

                For further information, we have a wealth of Capgemini Research Institute Reports and research:

                And other reports and points of views:

                [i] https://www.circularity-gap.world/2023

                Author

                Clément Chenut

                Circular Economy Services Leader
                Part of Capgemini’s Sustainability Accelerator, set up to increase awareness of sustainability issues and develop practical solutions for clients, my focus is to promote and accelerate the adoption of circular economy business models. With Capgemini colleagues, we’ve developed a suite of CE services from strategy to digital/engineering solutions. These services guide clients from a linear economy that can destroy value, to a circular economy that preserves value – by minimizing the use of raw materials and resources, and reducing the production of waste. I’ve also led digital transformation programs, mainly in banking and transport, and was part of the Capgemini’s 5G Lab team, set up to help clients strategize, build and monetize the advantages of 5G.

                  The post Why realizing a circular economy requires a holistic approach: 5 key factors to successful circularity appeared first on Capgemini.

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                  We elevate your possible with Generative AI https://www.capgemini.com/insights/expert-perspectives/we-elevate-your-possible-with-generative-ai/ Thu, 20 Jul 2023 20:05:08 +0000 https://www.capgemini.com/?p=938433 The post We elevate your possible with Generative AI appeared first on Capgemini.

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                  We elevate your possible with Generative AI

                  Mark Oost
                  20 Jul 2023

                  While there is a huge adoption of Generative AI across organizations and industries – our research reveals that over 95% of executives are engaged in Generative AI discussions in their boardrooms – we can observe clearly a shift in the way people perceive AI now.

                  I have been working in the field since many years, and the unprecedent enthusiasm around Gen AI is impressive – 74% of executives believe the benefits of generative AI outweigh the associated risks. Beyond the positive feedback around it, there is a massive need for information, education and guidance. Especially for organizations to successfully and responsibly implement Generative AI across their data value chain, considering ethics, privacy and security from the start.

                  However, when you leverage Generative AI in a secured and trusted environment the opportunities are immense. From tasks and workflow optimization, to content production, product innovation and R&D, it is revolutionizing the way we create, interact and collaborate, completely shifting the way organizations operate. What if you could as a CXOs leverage Gen AI, across your organization, in a safe, secured and controlled manner, to fit your business reality?

                  Creative and Generative AI

                  Why consumers love generative AI, we explore the potential of generative AI, its reception by consumers and their hopes for the technology

                  Building on your unique skills and knowledge

                  By combining your company’s unique knowledge with foundational models to create tailored Gen AI solutions, you can deliver reliable outcomes at scale while addressing your specific business needs. Together, we can unlock this full potential and rewrite the boundaries of what’s achievable with our new offer Custom Generative AI for Enterprise.

                  We help you elevate and focus on your excellence to unleash new possibilities. This is what our Custom Generative AI for Enterprise is all about: building on the unique skills and knowledge that make you, you. And it’s because we are tailoring from your data, business knowledge and context that results will create maximum impact and benefit your organization.

                  Rather than sharing clients examples, I prefer to illustrate this with our partnership with Dinara Kasko, an extraordinary creative talent and architect-designer. At the intersection of GenAI and 3D printing, she is building on her skills to create unique art pieces in the shape of patisserie, unleashing her creative process with the power of technology.

                  We are collaborating with her with a bespoke solution to elevate her possible with Generative AI. Stay tuned for exciting updates!

                  And if you are curious about the new possibilities of Generative AI and the rapid pace of its technological advancements, connect with me!

                  Author

                  Mark Oost

                  Global Offer Leader, AI Analytics & Data Science
                  Prior to joining Capgemini, Mark was the CTO of AI and Analytics at Sogeti Global, where he developed the AI portfolio and strategy. Before that, he worked as a Practice Lead for Data Science and AI at Sogeti Netherlands, where he started the Data Science team, and as a Lead Data Scientist at Teradata and Experian. Throughout his career, Mark has had the opportunity to work with clients from various markets around the world and has used AI, deep learning, and machine learning technologies to solve complex problems.

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                    Write a prescription for improved patient journeys https://www.capgemini.com/insights/expert-perspectives/write-a-prescription-for-improved-patient-journeys/ Thu, 20 Jul 2023 10:31:36 +0000 https://www.capgemini.com/?p=937042 First Name *First Name is not valid.Last Name *Last Name is not valid.Company *Company is not valid.Email *Email 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 […]

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                    Write a prescription for improved patient journeys

                    Thorsten Rall
                    20 July 2023

                    Capgemini’s Data-driven CX provides life sciences companies with better understanding of how their customers use their products.

                    When talking about excellent customer experiences, likely the first thing to come to mind is shopping at a store or online for a consumer product – perhaps a shirt, a book, or a new phone. But every organization, in every sector, has customers – and can benefit from providing them with the best possible experiences.

                    For companies in the life sciences sector, the customers are primarily patients and healthcare professionals. And those customers form opinions about products and about the companies which create them.

                    Capgemini’s Thorsten Rall, Global Industry Lead Life Sciences, and Naresh Khanduri, Vice President, Digital Customer Experience, help clients leverage data to provide patients, healthcare professionals, and others in the sector with excellent customer experiences. Here, they discuss some of the unique experience challenges faced by life sciences companies, and how manufacturers benefit from using data and insights to gain a better understanding of customer journeys.

                    Why is it important for companies in the life sciences sector to create excellent customer experiences?

                    Naresh Khanduri: The key to improving patient outcomes is to understand the patient journey. For example, a pharmaceutical manufacturer wants to understand how a patient is using a drug it produces. Is the patient getting the information they need in order to take this drug correctly? Are they aware of potential side effects or conflicts with other drugs? Is the patient actually following those directions? Answering those types of questions is important if the company wants to improve the patient’s health outcomes.

                    How does creating excellent customer experiences help with that?

                    Thorsten Rall: As Naresh noted, patients don’t always follow the directions. When a life sciences company creates a new product, it typically conducts clinical trials. Patients in the trials are closely monitored to ensure they’re participating in the trial correctly. But there’s a huge difference between the experience a patient has in a trial and how they actually interact with a company’s product in real life. This is one of the fundamental challenges in the sector because there’s this notion that somehow a patient’s life has to circle around their health but the reality is, most people actually don’t want their life to circle around their health: they just want to live their life. Imagine a person who has to take a drug twice a day, but this person isn’t a morning person and frequently forgets to take their medicine before they leave the house. So, some days they take it as prescribed, and other days they take it only in the evening. That’s not ideal. By understanding their journey with the drug, the manufacturer can determine whether, for example, a different dose, delivery mechanism, or activation trigger would improve that person’s health outcomes.

                    Naresh Khanduri: For that reason, many life sciences companies would like to offer individuals a curated experience – one that understands the patient’s experience and then uses that information to better serve them. To expand on Thorsten’s example, the manufacturer might offer that patient who is not a morning person an app to remind them to take the drug. They might also offer other useful content, such as dietary advice to prevent possible negative interactions. It’s about more than the pill. It’s providing the pill plus personalized information, at the right time and in the right context, to improve the patient’s life. This creates trust, which is extremely important in healthcare. For one thing, building that trust can encourage the patient to share their experiences with taking the drug, which in turn can help the manufacturer improve it.

                    Most patients aren’t medical professionals, so what sort of useful feedback could they provide?

                    Thorsten Rall: There are many examples. And some of them can be simple. A good example for this relates to the leaflet that must be included inside every medicine package. This provides important information about the drug, its use, precautions and warnings, dietary restrictions, possible reactions with other medicines, and so on. But for space reasons, these are usually printed in extremely small fonts – and that can present problems. For example, elderly patients may not be able to read the leaflet or may have difficulty remembering the information. If they’ve had positive customer experiences with the manufacturer in the past, they’re more likely to share this feedback – which gives the manufacturer an opportunity to improve how this important information is presented for this group of patients. Moreover, a positive customer experience related to the leaflet may encourage the patient to share other, more personal information – such as symptoms related to the therapy – which can be vital data for the drug manufacturer.

                    So far, we’ve discussed examples of life sciences companies dealing directly with the patient. But most health matters are mediated through a healthcare system. What role do healthcare professionals play in this?

                    Thorsten Rall: In addition to understanding the patient journey, life sciences companies must also understand the experience of healthcare professionals. On the one hand, these professionals are under increasing pressure to treat more patients, so their time to learn about new products is severely limited. Meanwhile, the amount of information and innovation in the sector is accelerating. Doctors and other decision-makers are bombarded with information – new discoveries, therapies, insights into real-world outcomes, etc. – and they are expected to absorb this and make potentially life-changing decisions for their patients. But how do they get this information? Currently, they have to go to conferences, or have meetings with representatives from life sciences companies, or read through thick journals, or endure massive slide presentations. It’s generally not very user friendly, and definitely not something that’s easy to work into an already fully packed day. So there’s a huge need for a better customer experience for healthcare professionals. And that starts with understanding their journeys, too. For example, how frequently and via what channels do they want to receive this type of information? How does that vary by product and by context? And how do their needs evolve over time?

                    Naresh Khanduri: In addition, the customer experience for patients will be different than that for healthcare professionals, and life sciences companies need to accommodate that. For example, as a patient, my first engagement with the manufacturer may be in search of information about a drug I’m taking. The next time I interact with the manufacturer, I may be looking for recommendations on diet or other lifestyle changes that may improve my outcomes with this drug. To gain accurate information, I may have to share very personal, very identifiable information related to me, my health, and my lifestyle. Obviously, that information must be protected – for example, it must comply with privacy legislation and laws governing healthcare administration in the jurisdiction in which I live. But that data is also valuable to healthcare providers. For example, a pharmaceutical company could share useful data about a cohort – a group of patients with common characteristics such as age, gender, diet, lifestyle, and so on – to help doctors determine when and how to prescribe a particular drug.

                    Doing this correctly and gaining the greatest benefit requires the ability to collect and manage huge amounts of sensitive data and draw insights from it. How ready are life sciences companies to face this challenge?

                    Thorsten Rall: Almost every company in this sector has made this a priority and most of them have identified use cases or launched a project. Where they often struggle is in coping with vast amounts of information dispersed across many discrete sources. As noted in the 2022 Health & AI: Now and Next report from Capgemini Invent and AI for Health, life sciences organizations are still working on more robust data foundations, including improvements to data quality and data availability across their ecosystems. These challenges are not only complex but must be dealt with while complying with the stringent regulatory and legal frameworks that govern healthcare. For this reason, I’d argue a proper audit trail framework is far more important in life sciences than in most other sectors.

                    How does Capgemini address these challenges?

                    Naresh Khanduri: Capgemini created our Data-driven CX solution expressly to help enterprises take full advantage of insights from their data to build trust, transparency, and long-term customer relationships. Data-driven CX uses a unique framework to help Capgemini clients stitch together customer identities from across domains to provide a personalized, contextualized experience. It then uses AI to provide insights into how to customize engagements based on the customer’s historical actions and how they’re currently interacting with the enterprise. The result is better customer experiences – for example, by using Data-driven CX to predict what the customer’s next need will be, based on where they are on their journey. We have also developed several accelerators that reduce the time required for our clients to start seeing results.

                    Thorsten Rall: Hand in hand with this, we work with our clients to develop their customer-experience strategy so we can improve their business outcomes – so they don’t spend a lot of time and money on solving problems that don’t have a significant impact. What’s quite interesting about the sector is that even though life sciences is by its nature a very people-centric business – after all, it’s about treating and helping patients – historically the industry has been more product-centric than experience-focused. So, helping our clients identify and address the main pain points in their customers’ journeys is key. That will lead to not only improved business outcomes, but better relationships with healthcare professionals – and improved health and quality of life for patients.

                    Thorsten Rall

                    Global Industry Lead Life Sciences, EVP
                    Thorsten is a global Life Science Industry Leader who oversees strategy, offers, market positioning, strategic partnerships and G2M for Capgemini in Life Sciences.

                    Naresh Khanduri

                    VP | Leader Data-driven CX Offer | Global DCX | Capgemini
                    Naresh has been with group for more than 6 years now and has played multiple roles. In his current role as “Strategic Initiatives & Growth Lead – DCX” he is responsible for envisioning, designing and building strategic initiatives to help Capgemini differentiate and win in market place.
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