乌鸦传媒 Japan /jp-jp/ 乌鸦传媒 Tue, 11 Feb 2025 08:59:52 +0000 jp-JP hourly 1 https://wordpress.org/?v=6.7.2 /jp-jp/wp-content/uploads/sites/22/2021/07/cropped-favicon.png?w=32 乌鸦传媒 Japan /jp-jp/ 32 32 190432445 適切なアプローチでSAP S/4HANA変革を導きましょう。(※英語でのご案内) /jp-jp/insights/expert-perspectives/shape-your-sap-s-4hana-transformation-journey-with-the-right-approach/ /jp-jp/insights/expert-perspectives/shape-your-sap-s-4hana-transformation-journey-with-the-right-approach/#respond Thu, 14 Nov 2024 08:20:31 +0000 /jp-jp/?p=522180&preview=true&preview_id=522180 The post 適切なアプローチでSAP S/4HANA変革を導きましょう。(※英語でのご案内) appeared first on 乌鸦传媒 Japan.

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適切なアプローチでSAP S/4HANA変革を導きましょう。

David Lowson
22 Feb 2024

In today’s fast-paced world, there is often a tendency to rush into things without taking the time to carefully plan and strategize. This is no different when it comes to embarking on a transformation journey, especially when it involves configuring a complex system like SAP. 

It may be tempting to return to the past and immediately start configuring SAP, hoping for quick results. However, this is a mistake that can have long-term consequences.

When it comes to implementing a new system like SAP, it is crucial to invest the necessary time and energy upfront. This means taking the time to carefully plan and strategize before diving headfirst into configuration. By doing so, you are setting yourself up for long-term success. Rushing into configuration without proper planning can lead to costly mistakes and inefficiencies down the line. Starting out slowly and investing the necessary time and energy upfront may seem counterintuitive when you are eager to see quick results. However, taking this approach can actually expedite your transformation journey in the long run. By carefully planning and strategizing, you are ensuring that you have a solid foundation in place before beginning configuration. This will help you avoid costly rework and delays later on.

If you are looking to make a change that is not just temporary but also sustainable and value-creating, you must shape your transformation program. One of the key outcomes mandated by Stage 1 of our ‘SAP S/4HANA Large-Scale Transformation Program’ is to comprehend the forces driving change and to ensure that the transformation ambition is precisely defined, accepted by executives, and clearly communicated to and understood by the various business stakeholders.

How then do we achieve this clearly defined transformation target, also known as the Business Case for Change or the Why Change?

We use the following five steps to guide the Stage 1 – Shape Program activities that result in achieving the required Stage 1 outcomes.

The following are the five steps and their main objectives (although this is not a complete list of the tasks required to accomplish the stage results):

  1. Identify the goals of the business and the value levers needed to achieve these goals. To do this, we interview a number of CxO-level and senior business stakeholders to learn about their pain points, goals, and priorities. We also try to comprehend the business’s capabilities and operational models, and we submit that information, along with the compiled and analysed interview notes, for evaluation in step 2.
  2. Next, we move on to step 2: Value Stream Mapping. Wave 1. Value Stream Mapping is the method we use to comprehend the real, end-to-end business value streams and the business scenarios to which they are applicable. Understanding these supports the understanding of the current and target maturity for each capability change (the value lever) necessary for the transformation to take place in addition to helping us define the LTP boundary conditions, which are outputs from step 1.
  3. Once we have a clear picture of ambitions and benchmark of current state against target, we can finalize the high-level scope of changes and target Enterprise Architecture models.
  4. We’ve reached the fourth and final step, where we can use all the data gathered to model the business case scenarios, giving us a range of targets (from low to stretch) to choose from as we move on to the next LTP Stage. Determining the business engagement strategy is a crucial parallel task that must be completed now (and even earlier in the process), as it will determine whether or not one of any program’s most challenging aspects, and especially one of a large-scale transformation, will be successful. We must make sure that every stakeholder is involved in the process from the beginning and that they are not just spectators but active participants. When a transformation succeeds, everyone succeeds, and when it fails, everyone fails.
  5. Once the business engagement strategy is in place and a target transformation has been determined, it is time to present the Business Case for Change to senior leadership to make sure they are all pulling in the same direction and committed to not only sponsoring but also inspiring the transformation.

The goal of these 5 steps is to reach the 6 mandatory Stage 1 outcomes, which make sure that solid foundations have been laid and can be built upon in the next stage of the transformation journey.

These 6 imperative results are:

  1. The preliminary evaluation of the business case
  2. The initial roadmap for the transformation, which includes program resources
  3. Agreement on Business Engagement Strategy
  4. A target for the initial enterprise architecture
  5. Agreement on program governance, tooling, and the following Stage plan
  6. Executive agreement and approval

And even though all of this may seem overwhelming and be viewed as unnecessary by organisations, particularly if they have already made the decision to simply replace their system, Stage 1 must be completed in order to truly transform and deliver sustainable business change that adds value. It must be done well and is not an option.

This blog was by David Lowson on July 10, 2023

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今年の「Microsoft Ignite」が楽しみな理由 /jp-jp/insights/expert-perspectives/why-i-am-excited-about-this-years-microsoft-ignite/ /jp-jp/insights/expert-perspectives/why-i-am-excited-about-this-years-microsoft-ignite/#respond Tue, 12 Nov 2024 09:42:10 +0000 /jp-jp/?p=522662&preview=true&preview_id=522662 The post 今年の「Microsoft Ignite」が楽しみな理由 appeared first on 乌鸦传媒 Japan.

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今年の「Microsoft Ignite」が楽しみな理由

Jerry Lacasia
12 Nov 2024

Microsoft Ignite is just around the corner and we are putting our all behind it.

I couldn’t be more thrilled – I’ve spent over a decade working alongside some of the biggest names in technology, and now I have the privilege of leading 颁补辫驳别尘颈苍颈’蝉 partnership with Microsoft. For me, this event marks a unique opportunity to connect with our customers face-to-face, discuss industry challenges and explore the advanced AI solutions that 乌鸦传媒 and Microsoft bring to the table.

With over 2,000 existing Microsoft clients and more than 100,000 乌鸦传媒 practitioners certified in Microsoft’s solutions, we’re more than ready to bring our clients the insights and tools they need to stay ahead. Ignite is a golden opportunity for us to dive into the future with our clients, hear about their goals and work out how we can achieve them together. Here’s what I’m most looking forward to at Microsoft Ignite.

  1. Celebrating our partnership with Microsoft
    颁补辫驳别尘颈苍颈’蝉 partnership with Microsoft is one of our strongest, longest-standing and most impactful collaborations. We’re a top-five Microsoft partner globally, and a top sponsor at Microsoft Ignite. The conference gives us the chance to show how, together with Microsoft, we’re helping businesses across the world modernize, secure and scale their operations. It’s always inspiring to see the tangible difference our joint expertise can make.
  2. Building deeper connections
    One of the things I love about Ignite is the focus on meaningful connections – a theme that Microsoft has captured beautifully. Ignite offers a space for us to listen, learn and make these connections, while exploring our client’s needs, challenges and ambitions. For me and the entire 乌鸦传媒 team attending the event, these one-on-one discussions are where the real value lies, and we are looking forward to many of them
  3. Exploring Agentic AI together
    I’m especially looking forward this year to talking about our work in agentic AI architectures. Think of Agentic AI as a collection of AI-driven agents – small, autonomous functionalities that work together to accomplish larger tasks. This approach lets organizations deploy AI with flexibility and scalability, so they can get more done with fewer limitations. 乌鸦传媒 is pushing the boundaries here, and I’m excited for me and the team to share how this can bring clients a new level of intelligence.
  4. Scaling AI safely and reliably
    Innovation is one thing, but scaling it securely? That’s the real challenge. As an executive track sponsor, we will be showcasing solutions such as our RAISE platform, which is designed to deploy AI solutions at scale without compromising on security – something that’s now absolutely essential. This platform means our clients can confidently embrace AI across their operations, knowing they’re protected at all times.
  5. Cross-partnerships that bring unmatched value
    We also work with leaders like Databricks, Nvidia, Mistral.AI, SAP and Unity, meaning we’re able to create unique, three-way value propositions for our clients. These collaborations allow us to bring more flexible and integrated solutions to the table. I’m looking forward to talking about how these partnerships can open up new possibilities and make their transformations even more impactful.
  6. 颁补辫驳别尘颈苍颈’蝉 panel discussion
    Finally, one of the highlights for me this year is our client panel. We will have our North America COE leader Betsy Pridmore moderate the panel with some of our existing clients who will share their experience working with us, including real-world examples and illustrating the latest advancements in AI and digital transformation. It’s a chance to see 颁补辫驳别尘颈苍颈’蝉 vision in action and hear directly from the people who are making it happen.

Ready to ignite your transformation?

Every year, Microsoft Ignite brings us together to explore the latest advancements in technology, to connect and to inspire each other to think bigger. I can’t wait to connect with clients here, answer their questions and hopefully spark new ideas that they can take back to their teams.

If you’re at Ignite, come find us – let’s discuss how 乌鸦传媒 and Microsoft can make a real difference to your journey. And if you’d like to learn more in the meantime, send me a message on LinkedIn.

Learn more about our partnership with Microsoft

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础滨活用によりサプライヤーリスク軽减し、レジリエンスを构筑する /jp-jp/insights/expert-perspectives/building-resilience-with-ai-powered-supplier-risk-mitigation/ /jp-jp/insights/expert-perspectives/building-resilience-with-ai-powered-supplier-risk-mitigation/#respond Mon, 11 Nov 2024 09:52:00 +0000 /jp-jp/?p=522666&preview=true&preview_id=522666 The post 础滨活用によりサプライヤーリスク軽减し、レジリエンスを构筑する appeared first on 乌鸦传媒 Japan.

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础滨活用によりサプライヤーリスク軽减し、レジリエンスを构筑する

Laurence No?l
Nov 6, 2024

What’s the true value of AI in the automotive supply chain?

颁补辫驳别尘颈苍颈’蝉 Head of Automotive Laurence No?l describes the exciting results of a recent collaboration between 乌鸦传媒 and supply chain risk management specialist?Prewave.

Supply chain challenges for the global automotive industry seem to keep arriving in a never-ending stream, one of the latest examples being . Market volatility is currently further increased by geopolitical tensions and by evolving EV incentives. In such an environment, it’s hard for automotive manufacturers with a global supplier base to achieve the level of supply chain resilience they want or to confidently manage their supply chain risk.

Auto companies face an additional, and related, challenge: their risk management doesn’t yet extend far enough along the supply chain. The lack of visibility of more remote tiers affects not only their ability to minimize the impact of supply chain disruption but also their compliance with increasingly stringent regulations about ESG accountability, such as the German Supply Chain Act.

AI looks promising – but how can the promise be realized?

Most automotive companies suspect that – as we argued in a recent blog article – new advances in AI could help them overcome these challenges. Possible benefits of AI include getting ahead of crises through improved supply chain resilience, better identification and management of risk (including supplier-centred risk), and visibility of more tiers of the supply chain, which could help companies meet sustainability goals.

AI looks promising in part because of its ability to instantly process large volumes of data, create data models, and use learned patterns to predict the future. Given the rapid progress in this field, the possibilities are expanding almost by the day.

However, until now, making that happen has looked like an offputtingly large and complex task. Automakers are often too busy, and in too much of a hurry, to spend a lot of time experimenting with “bleeding edge” technology – or even to seek out the innovative startups who are known to be ahead in AI. They also want AI to be integrated into a total supply chain solution rather than implemented as a point solution, with all the issues that can cause.

In addition, the application of AI to supply chain problems holds significant inherent complexity. For example, to build a rounded picture of the current and future supply chain situation – and to build and evaluate remediation scenarios – it’s necessary to pull together data from multiple sources. Internal data might relate to projects, products, sustainability KPIs, and risk assessments. External data might include publicly available company certifications, news, and annual reports, as well as specialist third-party data about everything from financial scores to carbon footprints. This data can be in more than 150 languages and any number of formats, with much of it unstructured.

Demonstrating the power – and accessibility – of AI-enabled supply chain intelligence

乌鸦传媒 knew that these complexities could be overcome and has been working to do so on behalf of our automotive clients. In a recent collaboration with supply chain risk management specialist Prewave, we’ve built an AI- and web-based solution to tackle current supply chain issues. We were thrilled to demonstrate the result at the recent Paris Motor Show and gained great feedback from our clients and stakeholders.

The results of this collaboration show that an AI-powered solution can ingest all that multilingual, multi-source, unstructured data and use it to inform supply chain risk management. As a result, we’re confident that we can efficiently embed Prewave-powered solutions within client systems, providing features such as:

  • Supplier mapping – giving the automaker visibility of most tiers of their supply chain
  • Risk and sustainability scoring – informing supplier selection decisions and enabling share-of-business refinements
  • Real-time risk monitoring – telling the automaker exactly what’s going on in their supply chain at a given moment

“Especially in the automotive industry, which is very dependent on supply chains, we help to identify risks early and take action. The goal is not to offboard suppliers, but to improve them. Prewave leverages 13 years of AI research to offer an end-to-end approach to supply chain risk management, integrating risk, sustainability, and compliance into a single platform. Our AI maps 1.3 million global suppliers, analyzing 150+ risk categories and 400+ languages, delivering real-time insights and empowering businesses to take direct, preventative actions, proposed and evaluated by the solution.”

Harald Nitschinger, Co-founder and CEO, Prewave

As a result, we know AI can be used to create flexible, easy-to-use risk intelligence that supports the company’s strategic vision—including its supply chain sustainability goals—as well as its day-to-day management of supply chain issues. Entities such as transportation hubs, raw material markets, and suppliers can be monitored to maximize supply chain visibility and enable comprehensive supply chain management.

We’ve also shown that AI can help predict the automotive supply chain’s future, including when disruption will occur and what impact it will have on both upstream and downstream activities. In addition, AI-powered predictive methods can be used to assist with supply chain mapping, although complete penetration can never be guaranteed.  These methods can also help to evaluate and rank alternative scenarios as an aid to decision-making.

Could AI-powered supply chain intelligence help your organization?

Would you like to see our solution in action, or find out how AI-enabled intelligence can tackle supply chain challenges in the automotive industry so that you achieve both day-to-day and strategic supply chain goals? Please contact our supply chain team today via the form on our automotive supply chain page.

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生成础滨で自动车ディーラーや贩売店が顾客体験を向上させる5つの手法 /jp-jp/insights/expert-perspectives/five-ways-generative-ai-can-help-retailers-improve-the-automotive-customer-experience/ /jp-jp/insights/expert-perspectives/five-ways-generative-ai-can-help-retailers-improve-the-automotive-customer-experience/#respond Fri, 04 Oct 2024 09:56:53 +0000 /jp-jp/?p=522670&preview=true&preview_id=522670 The post 生成础滨で自动车ディーラーや贩売店が顾客体験を向上させる5つの手法 appeared first on 乌鸦传媒 Japan.

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生成础滨で自动车ディーラーや贩売店が顾客体験を向上させる5つの手法

Mat Desmond
Oct 4, 2024

Generative AI can help retailers improve customer and vehicle knowledge to boost sales and service

Customers in today’s digitally enabled world expect seamless, convenient, and personalized retail experiences. It’s no different when it comes to buying a vehicle. To compete, automotive dealerships must provide customers with the right offer, vehicle, and service at the right time. Throughout this end-to-end journey, retailers need to access data from various systems that provide information on vehicle sales, finance, and customer service. This is especially important as data can change at any time in the fast-paced environment of automotive retail. This creates complexity and can impact the customer experience.

The dizzying pace of change in sales, including pricing updates, marketing campaigns, and sales incentives, is one reason many automotive original equipment manufacturers in North America are beginning to use generative AI (Gen AI). Gen AI is a game-changing technology characterized by its ability to learn, adapt, and collaborate in ways once reserved for human intelligence.

Gen AI can help automotive original equipment manufacturer (OEM) sales and marketing teams and retailers improve the customer experience by providing information faster and more accurately. The power of Gen AI can help to assemble responses to important questions about the sales process and enable staff to spend more time with customers, building relationships and understanding their needs.

Applying Gen AI can also help with parts, service, and, of course, customer interactions. With the right application of the technology, automotive sales, marketing, and retail teams win, and customers will receive the right answers to questions more quickly than with humans alone.

The fast pace of automotive retail presents challenges

There is a massive amount of data to consult and understand in context to deliver on customer expectations. Managing this data to personalize recommendations, align vehicles in stock with customer preferences, and maximize sales and service opportunities is a challenge most often requiring years of experience with the product and the business. Gen AI can help address these challenges and improve the customer experience even for the most seasoned automotive retail team member.

Here are five use cases which illustrate how Gen AI can improve core processes in automotive retail, including customer shopping, customer service, OEM manufacturing, marketing and vehicle delivery.

1. Order

Gen AI can provide important data points in the ordering process for OEMs and dealers. It can be trained on inventory and sales history data to provide market intelligence that would otherwise be very time-consuming to obtain and analyze. This information can improve vehicle order management decision-making for the OEM and the dealer to ensure the right vehicle is available at the right time for the customer.

2. Sales

Recommending the best vehicle for a customer requires OEMs and dealers to understand numerous data points, including customer purchase history and preferences, available inventory, inventory on order, sales incentives, recent OEM and insurance offerings, and telematics. Gen AI can help OEM teams and retailers track all this. For instance, a busy parent with a history of buying minivans might be interested in a new model with a bigger trunk and new safety features, based on preferences, available inventory, and the best deals available. The offer can be enhanced with a tailored sales incentive or easy add-ons like insurance to meet the customer’s expectations based on their profile.

3. Finance

Gen AI can accelerate and streamline the cumbersome process of gathering information from various applications for finance. Traditionally, salespeople juggle multiple logins and interfaces to obtain a customer’s credit score, current loan rates, and available deals. Gen AI can gather finance data from disparate sources in real time, saving time for salespeople and placing the most up-to-date information in their hands to share with customers quickly.

Furthermore, Gen AI has the analytical advantage of answering complex customer questions quickly. For instance, if a customer wants to know how much a trade-in will reduce monthly payments, Gen AI can instantly access the trade-in value, calculate the adjusted loan amount, and present a revised payment schedule within parameters set by the dealer. Similarly, Gen AI can offer personalized recommendations for finance options that align with customer input (e.g., a target monthly payment and term).

4. Insurance

Gen AI can recommend the right insurance for each customer by analyzing data on driving habits, demographics, and local insurance trends. Outside of basic coverage options, Gen AI takes personalization to a new level by considering factors like vehicle usage (highway vs. city driving), climate, and even typical road conditions to identify potential risks and tailor coverage accordingly.

Gen AI can also highlight benefits relevant to the customer’s needs. A weekend traveler who works from home may want a policy with lower daily coverage limits but better features like roadside assistance or rental car coverage. Improved personalization and speed of providing options can increase customer satisfaction and boost sales of more relevant insurance products.

5. Service

Finally, Gen AI has the power to revolutionize customer service inquiries and internal dealer aftersales service processes. If a customer has car trouble, Gen AI can suggest potential diagnostics and service options based on data about the vehicle’s history and past repairs and available remedies, including software patch updates. Additionally, Gen AI can flag any open recalls or missing vehicle software, saving the customer time when deciding the next steps for service.

When a vehicle is ready for repair, Gen AI can improve service efficiency by optimizing scheduling. Equipped with data on technician availability and parts inventory, Gen AI can share expected service completion times help service departments set expectations and automatically notify customers if there are changes impacting completion.

With Gen AI, aftersales service will continue to move faster as vehicles become increasingly software-based. In the future, Gen AI technology will be trained to identify the parts needed, place the order, notify the customer, and create an appointment proactively with the customer’s consent. This can improve customer satisfaction, streamline operations, and help keep the wrenches turning in the service bays.

Revving up your Gen AI engine

OEMs have a unique opportunity to decide how they can use Gen AI capabilities to improve core processes as the technology is applied to all aspects of automotive retail. Exciting tools are reaching the market every day and expanding the pool of use cases. Now is not the time to hit the brakes on AI adoption; it’s time to accelerate progress toward using this technology to elevate customer experiences in a new era for automotive.

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行动データと础滨主导のパーソナライゼーションで顾客を支援 /jp-jp/insights/expert-perspectives/empowering-customers-with-behavioral-data-and-ai-driven-personalization/ /jp-jp/insights/expert-perspectives/empowering-customers-with-behavioral-data-and-ai-driven-personalization/#respond Fri, 03 May 2024 09:00:00 +0000 /jp-jp/?p=518902&preview=true&preview_id=518902 Generative AI is a key tool that has emerged to drive personalization.

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行动データと础滨主导のパーソナライゼーションで顾客を支援

Alok Benjwal
3 May 2024

In today’s competitive banking landscape, customers demand personalized experiences tailored to individual needs and preferences. However, the current generic interactions and misalignment with financial goals leads to dissatisfaction with the current state of customization offered by banks. A  by Blend found that 65% of consumers wanted banks to make it easier to shop and find tailored products, and 72% felt product offers to be more valuable when tailored to their personal needs. This illustrates the gap between customer expectations for personalized services and the reality of banking experiences.

Generative AI is a key tool that has emerged to drive personalization. Customers love it, with the 乌鸦传媒 Research Institute’s 2023 revealing that 73% of 8500+ consumers trusted content written by it and 53% have faith in generative AI-assisted financial advice. With the scramble to develop such solutions for enhanced business outcomes, business leaders should know how this technology can drive personalization for their businesses.

Content creation at scale

Generative AI revolutionizes media creation, infusing personalization into every aspect from text to images. This approach ensures that tailored content resonates uniquely with each consumer, be it product descriptions, blogs, or video scripts. Replacing labor-intensive manual efforts, generative AI streamlines the process, delivering messaging and visuals based on individual preferences, demographics, and past behaviors.

AI algorithms swiftly analyze real-time consumer interactions and transactions, ensuring content remains relevant and effective across platforms. In contact centers, Generative AI addresses common queries, reducing agent costs and resolution times, elevating overall customer experience.

CRI’s survey highlights this approach’s significance, with 29% of executives extensively leveraging generative AI for content creation and another 26% embracing it to some extent. , a US all-digital bank, used generative AI to reduce marketers’ production time by up to 2-3 weeks, achieving average time savings of 34% with prompt accuracy of 81% (indicating users generally received relevant content output).

Hyper-personalized recommendations

Generative AI utilizes customer data to analyze past interactions, transactions, and preferences, generating tailored product and service recommendations. This fosters trust, and contributes to loyalty, retention, and revenue growth through repeat purchases and brand advocacy.

Detailed customer profiles enable targeted recommendations, such as credit cards and insurance, based on individual preferences. Real-time analysis suggests agent responses and identifies cross-selling opportunities, catering to specific consumer needs.

According to , 60% of executives use generative AI extensively for customized customer experiences, and 57% for creating personalized customer and brand avatars. Mastercard’s Dynamic Yield developed , leveraging colloquial language to deliver customized product recommendations and predict shopping intents based on the past purchase data and behavior, enhancing shoppers’ discovery experience.

Dynamic and engaging interactions

Generative AI chatbots mimic human responses, providing round-the-clock support, engaging in natural conversations, and adapting to user mood or intent. This enhances service perception, offering personalized advice and support, ultimately boosting engagement and loyalty.

In a 乌鸦传媒 survey, 83% of organizations deemed chatbots relevant for automating customer service and improving knowledge management. Wells Fargo’s chatbot, , manages 20 million interactions, offering banking services and financial advice via voice and text, powered by the Tachyon AI platform.

Tailored marketing and advertising

Generative AI transforms marketing with targeted campaigns, replacing generic ads with personalized content across different media formats. Historical data informs tailored messaging, optimizing clickthrough and conversion rates. Financial institutions leverage generative AI for personalized content, driving loyalty and engagement with instant cross-selling and up-selling offers.

Consumers embrace generative AI, with 62% comfortable with its use in marketing, per 乌鸦传媒 Research Institute survey. For , Square integrates this technology into its business software, streamlining email marketing with personalized content and supporting blog copywriting for SEO improvement and resource savings.

Towards individualization

Marketing strategies have used technology to shift from broad-based campaigns to targeted approaches using group-level data. With generative AI, we move to individualization, where AI platforms craft unique experiences tailored to each user’s specific needs and preferences. This can incorporate factors like real-time behavior, mood, preferences, goals, and health metrics. To illustrate, while personalization involves targeting segments with credit card campaigns based on transaction history, individualization takes it further. It allows credit card companies to monitor each customer’s financial actions, adjusting credit limits dynamically based on their creditworthiness and current financial situation using AI/ML. This ensures personalized, responsible credit management.

Deploying sophisticated generative AI operationalizes, at scale, the insights generated from AI/ML algorithms. This optimizes resource allocation, improves customer engagement, and growth and efficiency strategies. According to 乌鸦传媒, 58% of organizations integrate generative AI into marketing, and 50% of financial services firms allocate budget to it . How does this technology enhance business and customer outcomes for financial institutions?

Generative AI’s technological prowess and operational capabilities will lead to a paradigm shift in how businesses can be ran efficiently. To extract the maximum value out of generative AI applications, a leader must understand the technology and how it can enhance existing business processes, along with clarity on the outcomes it can create. Banks and financial institutions will need to rapidly adopt these technologies in a volatile, competitive environment to ensure that customers’ demands for greater personalization and convenience are met quickly and effectively.

Please contact our experts

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    ソフトウェアがイノベーションを加速させ、安全なモビリティを実现するカギとなるワケ /jp-jp/insights/expert-perspectives/why-software-is-the-key-to-speedy-innovation-and-secure-mobility/ /jp-jp/insights/expert-perspectives/why-software-is-the-key-to-speedy-innovation-and-secure-mobility/#respond Thu, 11 Jan 2024 09:06:13 +0000 /jp-jp/?p=516443&preview=true&preview_id=516443 Innovation, Mobility

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    The key to speedy innovation and satisfying, safe, secure mobility?

    Alexandre Audoin
    Jan 5, 2024

    The race to provide autonomous mobility and compelling customer experiences is hotting up, but automakers need to balance their need for speed and innovation with a ‘no compromise’ approach to safety and cybersecurity.

    Competition in the automotive industry is intensifying and brands are competing on more fronts than at any time in history. Of course, price, performance, brand, and residual values continue to be important. But as the industry gravitates toward electrification and software-defined vehicles, customers are looking at what else their vehicles can do for them. How well do they integrate with their lives and their digital ecosystems? Can and will the car evolve over time to add more value to daily life? And, for manufacturers, how do you build supply chain resilience and competitiveness to address these evolving demands, while ensuring availability and affordability? 

    Automakers – especially at the luxury and premium end of the market – are also intensifying their focus on providing assisted and autonomous driving capabilities and new ways to add value with digital experiences, inside and outside the vehicle. In the face of increased competition, the speed with which automakers are able to innovate and the extent to which they can engage and satisfy their customers in new ways will be crucial to future success or failure.

    Autonomous mobility at the crossroads

    For years, tech and innovation events like CES have been dominated by autonomous vehicles of all shapes and sizes. The technology is always impressive … at the shows. But, in the real world, progress has been slower than expected. For every success, it seems like there’s been at least one story of a scaled-back or canceled investment, an unfulfilled promise, or a serious safety scare.

    The pursuit of autonomous mobility is a double-edged sword. The cost of adding sensors for 20+ detection zones around the car is significant. And the volumes of data, the sophistication of algorithms, and the amount of computing power required to develop, test, and validate systems are eye-watering. And yet, the ability to offer customers safe and stress-free ways to travel; to give back quality time while getting from A to B, is a once-in-a-lifetime opportunity to build trust and open the door to a whole new world of services and revenue streams. It’s no wonder the pursuit of the various certification levels is so intense and why so many companies are taking different routes – from in-house development with tech partners to major alliances with tier-1 suppliers, and even acquisitions. Some companies are making more progress than others, but the race is still wide open.

    The in-car experience is evolving

    The transition to electric and the pursuit of autonomous-driving capabilities have major implications for the automotive customer experience, especially the in-car digital experience. With electric vehicles, we know that recharging away from home will involve idle time. And – though it may still be a way off – autonomous mobility will allow us to focus less on driving the car and leave us more time to do other things. Today, our first thought might be to reach for our smartphones or tablets, but this is a lost opportunity for vehicle manufacturers.

    Event

    CES 2024

    Join us at the 乌鸦传媒 Executive Lounge, January 9 – 12, 2024 | Las Vegas

    And so the question becomes: How can your car keep you entertained and engaged while it charges or self-drives?

    The answers are emerging in the form of expansive screens, adaptive interfaces, the addition of extra screens for passengers, an increasing emphasis on in-car gaming, content consumption, subscription services, and almost unlimited ways to pass the time productively, recreationally, or relaxingly in a vehicle.

    And then there’s the potential to have an AI-powered assistant, or companion, that connects all the different services and is capable of providing pretty much any information you need about your journey, your agenda, upcoming commitments, highlights from your inbox or social media feed, and much more.

    All of these features represent potential points of differentiation, and many of them are revenue-generating opportunities (e.g. subscription-based services). Beyond direct revenue and new levels of customer intimacy, in-car digital interactions also create opportunities to generate new data and insights, which can (with the right levels of consent and anonymity, of course) be used to shape new products and services – inside and outside the vehicle – and new monetization opportunities.

    Speed and satisfaction – why they matter more than ever

    You could argue that the evolutions I’ve explored above are technology trends, much like many others. However, these trends are different in that if you can achieve the combination of safe autonomous or highly assisted mobility and engage customers with compelling in-car experiences, you can gain a level of trust, and access – and even companionship – that is unprecedented in the history of OEM-customer relationships. This brings with it the opportunity to develop deeper, longer, and more lucrative relationships.

    But the race for the hearts and minds of customers is intense, with a raft of new players (many from China) to compete against, new demographics, and rapidly evolving customer expectations. In this climate of increased competition, it is imperative that automotive companies intensify their innovation efforts in a bid to deliver the integrated and connected customer experience that will soon be taken for granted. And if your brand isn’t able to provide it, you can assume that another one will. 

    Balancing the need for speed and satisfaction with a ‘zero compromise’ approach to safety and security

    Against this backdrop of ultra-intense competition and a relentless focus on innovation, OEMs must remain vigilant and understand that speed to market can never take priority over safety and security.

    Assisted and autonomous mobility can offer comfortable, convenient, and stress-free travel. But they also mean taking a significant degree of responsibility for the safety of vehicle occupants. In short, ADAS and autonomous driving systems cannot fail. Failures will result in more than a few lost sales – they could lead to loss of life, high-profile court cases, and a complete loss of confidence in your brand.

    And though it’s less likely to be a life-or-death matter, automotive brands need to be vigilant about ensuring the cybersecurity of their vehicles and data ecosystems. Digital assistance or companionship, subscriptions, services, integrated payment solutions and ecosystem services (e.g. via wearable health devices, smartphones, etc.) will typically require some degree of data sharing. This opens the door for personalization and seamlessly convenient experiences, but it’s not without its risks. No brand wants to be the next one to appear in a high-profile data leak story and risk losing the hard-earned trust of its customers.

    Software is the key to safe, secure, and satisfying experiences

    So what’s the key to accelerating innovation cycles and customer satisfaction without compromising on safety and data security?

    The answer lies in your software strategy. After all, software is at the heart of assisted and autonomous driving systems, it drives immersive and engaging digital experiences through infotainment systems and more, and it can be the key to ensuring the security of personal data and the identification and elimination of sophisticated cybersecurity threats. The right software strategy and architecture (i.e. a simplified one) can also provide you with greater flexibility during times of supply chain instability, meaning you can maintain product availability while your competition potentially suffers. As many of us learned during the pandemic, simply making sure your cars are available to potential buyers can be the biggest advantage of all.

    乌鸦传媒 Research Institute: The Art of Software

    But the stakes are too high with software and the task of transforming into a software company is too big to go it alone. Here are three ways automotive companies can get their transformation right.

    1. Partner up to boost software capabilities

    Software-driven transformation is a broad and deep-reaching process, which can encompass upskilling your existing team, building new capabilities, and finding the right balance between maintaining your existing digital products and developing new ones. This is a huge undertaking, and so it makes sense to partner up with automotive software specialists and engineers who can share and instill industry best practices, build dedicated software factories for you, or support you in maintaining existing products or developing new ones.

    2. Use cloud, virtualization, and AI to achieve more

    Cloud and AI can be used to process and analyze the high volumes of data produced during autonomous driving system development and testing, to virtualize ECUs, and to support data spaces and service ecosystems. These technologies, combined with the suite of automotive-specific accelerators being built by hyperscalers today, can supercharge your innovation and product development cycles, enabling you to get to market faster with new products and services, while keeping your – and your customers’ – valuable data secure. 

    3. Look for external inspiration

    Automotive companies can’t be everything to everybody. It’s difficult (impossible?) to develop an infotainment UX that rivals that of smartphone makers like Apple and Google if it’s not your core business. Likewise, you won’t suddenly create ‘killer’ content and entertainment options if you’re just starting out. Instead, partner up with startups and niche players in differentiating domains and focus on the bigger picture.

    The road ahead is filled with complexity and exciting developments. And yet, for all the focus on new technology, there are still large groups of customers who care little for new tech, and who continue to value practicality, build quality, and affordability above all else. How organizations address these oft-divergent customer desires within their product portfolio will be a challenge for many ‘traditional’ OEMs.

    What we can say with confidence is that mobility experiences of the future – whether they’re autonomous or human-driven – must be satisfying, safe, and secure. Automotive companies must be quick to give their customers what they want. Check out our perspective on software in automotive to learn more. 

    Author

    Alexandre Audoin

    EVP, Head of Global Automotive Industry, 乌鸦传媒
    Alexandre Audoin is 乌鸦传媒 Group’s global leader for the automotive industry and head of automotive within 乌鸦传媒 Engineering (formerly Altran). Alexandre maintains a special focus on the creation of Intelligent Industry, helping clients master the end-to-end software-driven transformation and do business in a new way through technologies like 5G, edge computing, artificial intelligence (AI), and the internet of things (IoT).

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      新兴自动车公司の成功を左右する、顾客管理システム(颁搁惭) /jp-jp/insights/expert-perspectives/the-success-of-young-automotive-companies-stands-and-falls-with-the-use-of-the-crm-system/ /jp-jp/insights/expert-perspectives/the-success-of-young-automotive-companies-stands-and-falls-with-the-use-of-the-crm-system/#respond Thu, 11 Jan 2024 08:50:53 +0000 /jp-jp/?p=516345&preview=true&preview_id=516345 CRM is crucial for young automotive companies on their way to becoming global players. Set clear standards, remain customer-focused and maintain agility.

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      新兴自动车公司の成功を左右する、顾客管理システム(颁搁惭)

      CRM
      Alican Sahan
      Dec 13, 2023
      capgemini-invent

      CRM is crucial for young automotive companies on their way to become global players. For sustainable growth, the following is important: set clear standards, remain customer-focused and maintain agility.

      In last years, the shift to e-mobility opened the door for the automotive industry to new market players from all over the world. By then, the industry was considered untouchable in the hands of the established automotive OEMs. Some automotive start-ups have managed to penetrate the market and stand up to the traditional companies, led by Tesla. The successful market entries in the automotive market are partly because, unlike established OEMs, young companies did not have to undergo a transformation in the direction of electrification and digitalization. But the rapid growth of young companies brings also new challenges. The fact that priorities in the (first) years of growth are very much focused on brand building, market share as well as delivery, there is a risk that the cross-functional, consistent customer focus gets lost.

      If the CRM system is used by Marketing, Sales and Service in isolation, it will be difficult to keep the recently won customers in the long term

      We observe that the customer relationship management (CRM) system is not used efficiently and in a scalable way in young automotive companies. If, in addition, there is a drop in growth rates – which is to be expected in times of high inflation and the threat of recession – the advantage in terms of customer relations compared with the established automotive OEMs can shrink and even become a problem that jeopardizes the company’s existence. This is because, unlike the traditional companies, the new players do not yet have the same level of customer loyalty, which sometimes makes customers overlook poor experiences in marketing, sales and service. Weaknesses in the CRM system and poor customer experiences therefore have an even greater impact.

      Based on our market observations and experience, we have identified the following barriers that hinder sustainable growth:

      Lack of company-wide standards for CRM core functionalities

      Long-term planning on the right CRM usage is a major challenge for growing automotive companies and can be seen among various players:

      1. Joint Ventures often build on the existing CRM systems of the parent companies. However, the potential advantage that exists at first glance is often associated with system-related legacy issues.
      2. Start-ups with a newly built CRM often had too little capacity to focus on the optimal set-up of the CRM system due to the initial focus on sales.

      Instead of achieving a cross-functional further development of CRM and using synergies, ad hoc adjustments are usually made where it seems most necessary. However, these are often not compatible with the requirements of other departments. To prevent this, it is crucial to define company-wide standards and to align the CRM system with these standards in the long term right from the start.

      Fragmented view of the customer

      Most young companies repeat the mistakes of their predecessors and replace their early agility with typical silos in marketing, sales, and service. The result: fragmented customer experiences and an incoherent view of the customer due to inconsistent data flow. So why not leverage the agile strengths that a young company brings?

      Unclear responsibilities in lead management

      When it comes to realizing lead management, not only established OEMs are disappointing but also almost all young automotive companies. The question of who is responsible for lead management (marketing vs. sales vs. customer service vs. after-sales) should not be a “binary decision”. This way of thinking fosters silo-building so that many opportunities in lead conversion get lost or remain untapped. Instead, lead management should be the responsibility of all parties, with a clear definition of who is responsible for lead generation and lead processing. In addition, it must be clarified under which criteria a lead is handed over within the organization. This is how lead management can be optimized and the basis for effective revenue growth can be established.

      When and how should the CRM be optimized?

      • When: The clear answer is “NOW”. System landscapes are still lean and the spread of customer data is limited to a few systems. The growth of companies seems to be slower at the moment. This allows young automotive companies to focus on optimizing CRM.
      • How: To serve customers to their best satisfaction, it is essential to offer them individual care, personalized communication across all channels, and a superior level of convenience throughout the entire customer journey. From the customer’s point of view, it is irrelevant with which internal department they are in contact. They look at the brand and the customer experience as a whole. It is therefore even more important that a unified view of the customer is achieved throughout the company.

      Several CRM providers, such as Salesforce or Microsoft, offer software solutions that make it possible to achieve this target picture by using a modern, future-oriented platform. These solutions have the advantage that young automotive companies can access proven best practices and new functionalities right from the start. In addition, they can configure the CRM system specifically to individual needs.

      CRM from a business perspective means: Giving more than taking!

      The customer experience can be influenced by just a few CRM functionalities. For example, in addition to the customer, the respective vehicle with its details and features can also be stored in the CRM system. This provides valuable insights that help to create tailored service offers and improve customer communication. This can even be extended to household members’ vehicles to provide personalized service at the household level. In addition, fully integrated data-driven solutions can be used to generate “next best actions”, such as when is the best time to send a message to the customer regarding a potential new purchase. Salesforce provides these valuable capabilities with its Automotive Cloud, demonstrating how a variety of smart mobility solutions specifically for the automotive industry can be combined on one platform.

      Finally, it should be noted that the correct use of the CRM system alone is not enough to be successful in the long term. In addition to process optimization and the introduction of the latest features, organizational processes must also be future-oriented. In this case “process-follows-system”! For young automotive companies, this means retaining the agility from their “early days” and aligning CRM with a uniform view of the customer throughout the company.

      Together, we can put the customer back at the center, align CRM with the future, and thus ensure sustainable growth.

      Get the future you want!

      If you are a young automotive company and want to set up your CRM system in a scalable way or if you are an established company and want to benefit from our automotive-specific Salesforce experience, please contact us for more information.

      Many thanks to the co-authors and .

      Author

      CRM

      Alican Sahan

      Senior Manager, CRM for Automotive at 乌鸦传媒 Invent
      Alican is a Senior Manager at 乌鸦传媒 Invent and leads CRM projects at leading global automotive companies. His expertise includes the use of Salesforce in the areas of Marketing, Sales, Service and Customer Care in the automotive industry.

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        自动车业界で女性がキャリアを筑く絶好のチャンス(※英语でのご案内) /jp-jp/insights/expert-perspectives/theres-never-been-a-better-time-to-be-a-woman-in-automotive/ /jp-jp/insights/expert-perspectives/theres-never-been-a-better-time-to-be-a-woman-in-automotive/#respond Thu, 11 Jan 2024 08:47:57 +0000 /jp-jp/?p=516343&preview=true&preview_id=516343 Mobility, People experience

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        There’s never been a better time to be a woman in automotive

        Marie-Fleur Revel
        Dec 18, 2023

        I’ve spent most of my career working at the intersection of automotive and IT. It hasn’t always been easy but I’m convinced that there’s never been a better time to be a woman in automotive than right now.

        The world is changing and a combination of increased open mindedness and market forces is working to create more and more opportunities for women. Is everything perfect and can we say that IT and automotive are completely gender balanced? No, and my recent experiences of attending and speaking at events tell me that my situation is still somewhat of an exception – not many women have enjoyed the kind of support and opportunities I have. But we are on the right track.

        Here are 5 reasons why …

        1. Talent shortage prompts transformative action

        It’s well documented that the automotive industry – like many others – is suffering from a shortage of the right tech talent. As automotive companies pursue digital transformation and as the industry focuses ever more intently on software and digitalization, it is clear that talent needs are changing. The focus is no longer predominately on mechanical engineers  – data scientists, business analysts, SAP experts, programmers … they’re all in high demand, and often departments within the same organization are competing for this same talent. For example, cloud and SAP expertise are as important to procurement and HR as they are to production and logistics.

        The problem for the automotive industry is that it is not alone in feeling this need. Almost all industries are going through a similar transformation and require the same skills. This means that the automotive industry needs to step up and it needs to actively change its culture in order to appeal to potential candidates who might not traditionally consider it as a place to forge a career, i.e. women.

        We definitely shouldn’t see this as a situation where more women are hired and promoted just because there is a shortage of talent – far from it. Instead, there is a shortage of top tech and multi-disciplined talent. It is this shortage that represents a fantastic opportunity for everyone who fits the bill – men and women – to take a strong first step into a career in automotive.

        Every company is looking to add tech and IT talent – XL2 is Audi and 颁补辫驳别尘颈苍颈’蝉 joint approach to building IT expertise for the automotive industry.
        Every company is looking to add tech and IT talent – is Audi and 颁补辫驳别尘颈苍颈’蝉 joint approach to building IT expertise for the automotive industry

        2. Diverse teams perform better

        As the industry becomes more competitive, automotive organizations need to reflect on how they can maximize their performance. Technology can be a great enabler, but performance starts with your people, who they work with, and how they work together. Over the course of my career – which includes project and program management, capability building across geographic locations, and building and growing an entirely new business on behalf of Audi and 乌鸦传媒 – I’ve observed that diverse teams perform better. What do I mean by “diverse” in this context? I mean people of different nationalities, ethnicities, professional backgrounds, cognitive profiles, age groups, and, yes, also a mix of genders.

        And it’s not just my personal observation. There is a lot of research to back up this opinion.

        “Gender-diverse and inclusive teams tend to outperform gender-homogeneous teams, often by as much as 50%.”

        Gartner, , 2019

        How does diversity help drive performance? On a project or task level, it’s about bringing multiple perspectives to the table and harnessing the best of all worlds to find the right solution to a problem. The same can be true on an organizational and team level – being able to tap into a variety of perspectives, experiences, ways of thinking, and skill sets makes you collectively stronger. Based on my own personal experience, this kind of diversity also contributes to a healthier, more satisfying place to work, which undoubtedly makes a big difference to how people and the organization perform.

        Organizations are waking up to this and, thankfully, there’s a greater emphasis on diversity – especially gender diversity – in the hiring and promotion practices of companies, which means many more opportunities for women. An added benefit of this is that diversity tends to breed diversity so, once you’re on the right track, progress can be fast.

        3. Mobility megatrends are not all male-dominated

        The automotive industry is going through the largest transformation in its history. Electrification, digitalization, the rise of the software-defined vehicle, and the race to deliver autonomous mobility … are just some of the imperatives driving transformation. In addition, there’s stronger competition (Nǐ hǎo China!) than ever before and a strong need for established OEMs to streamline and strengthen their businesses. And if all that weren’t enough, there’s the growing need to stabilize supply chains and meet sustainability targets.

        This isn’t the automotive industry your father worked in, where the main emphasis was on mechanical engineering. Today, there are so many ways for talented individuals to contribute. We need scientists to develop future generations of EV batteries. We need AI experts and data scientists to help anticipate supply chain turbulence and take remedial action. We need UX and UI designers and software developers to design and deliver new functions and features to cars. We need environmentally conscious thinkers to design products and services with circularity and sustainability in mind. We need creative thinkers and partnership builders to devise new ways to build and extend relationships between customers and their cars. The list goes on.

        The key message here is that today’s automotive industry requires a far broader range of skills, profiles, and perspectives than it did just 10 or 15 years ago. And, as you see from the examples above, these aren’t all domains that are traditionally dominated by men. There’s also an argument that, as products and services become more complex, it’s increasingly important to have an inter- or multi-disciplinary skill set. In my experience, this is an area where women tend to shine (anyone for the joke about men and multitasking?).  

        In short, as the automotive industry transforms, opportunities will abound for ambitious females looking to make their mark.

        The automotive industry is undergoing disruptive changes and needs different and diverse talent to meet today’s challenges and customer expectations.

        4. Post-pandemic appreciation for work-life balance

        The pandemic caused us many difficulties and challenges. However, on reflection, many would agree that it brought about positive change in their approach to work. These days, most of us work from home for at least a few days a week. Many of us work from locations other than home or the office while travelling. It’s okay to say we can’t make a call or meeting because we have to pick up our kids. In many organizations, it’s acceptable to take a call while walking the dog. And, for most people, it’s fine to say you have a lot going on at home and could do with a little breathing space at work. These are all positive developments, many of which are a result of the constraints and difficulties we all experienced during the pandemic.

        Acceptance of the need to balance our personal lives with work is definitely a good thing, but it hasn’t always been this way. Many mothers have held back from returning to work after kids or have not progressed as fast in companies due to their inability or unwillingness to ‘give’ as much of themselves at work as their male colleagues (try getting in early or staying late when you are the primary carer of young children). Now, as more of society appreciates the benefits of work-life balance and there’s more empathy in the workplace, many of the obstacles that might have kept women out of work – or from progressing – have been openly acknowledged as being challenges for both men and women. This is sparking discussion and progress toward greater equality, which is opening the door for many more women to resume or progress more quickly in their careers.

        Life is work and work is life – this means that my kids will occasionally join my workshops. Could you imagine this 10 years ago?

        5. Role models and support networks

        When I began my career in the world of automotive tech, there were precious few female role models that I could look up to, admire, and seek to follow. Yes, there were women who were successful in their professional careers, but leaders? Role models? I’m not so sure. Today, the situation is much better. No, there aren’t many female CEOs (yet) but many of the established European and North American OEM brands all have women on their senior management teams. Sure, they may still be outnumbered, but many of these women are active in championing the cause of women leaders. Most importantly, though, they demonstrate that women can reach the top in a male-dominated industry.

        And while we don’t all have a direct line to the leaders at the top, we do now have solid community platforms in the form of the

         and where we can meet and hear from women of all levels from all kinds of backgrounds and domains. At 乌鸦传媒, there is a Women in Engineering network and the 乌鸦传媒 Invent Female Expert Network, as well as many other local or practice-based groups for women to join and contribute to.

        Having attended and spoken at several events in the last year, I’ve been taken aback by how much I have gained in terms of inspiration and advice and also how much positive feedback I’ve heard about my own story. Whereas in the past, we may have felt neglected by the lack of support structure, today, I think we can consider ourselves blessed by the networks, communities, and channels we have access to.

        Answering personal and business-related questions after my keynote presentation at the Woman Automotive Network Summit in Stuttgart, in September 2023

        So, what can you do?

        It may seem like now is a perfect time to be a woman in automotive. It’s not. There’s still much work to be done but the situation is improving all the time and we can all play a role in helping it to improve faster. We can connect, we can contribute to existing networks or create our own local communities. We can share our stories, we can look around for those who need a helping hand, we can provide advice to one another, and – if we’re leaders – we can make sure we are active in creating and nurturing workplace cultures and communities that support women. There is literally something that every one of us can do to pave the way for female success in the world of automotive. And, as Madeleine Albright used to say “There is a special place in hell for women who don’t help other women.”

        Note: This blog post is based on the keynote presentation I gave at the on 20 September 2023.

        Author

        Marie-Fleur Revel

        Co-Managing Director of @XL2 by Audi and 乌鸦传媒
        Marie-Fleur is a perfect blend of specialized startup spirit with corporate capabilities to accelerate the digital transformation of manufacturing, production, and logistics for Audi and other VW brands. At XL2, she leverages her background in computer science, IT, project management, and business building to nurture a new generation of automotive talent and build a workplace that celebrates diversity, equality, and inclusion.

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          Microsoft fabricでデータを活用した未来のビジネスを推進? /jp-jp/insights/expert-perspectives/embracing-data-powered-future-business-with-microsoft-fabric/ /jp-jp/insights/expert-perspectives/embracing-data-powered-future-business-with-microsoft-fabric/#respond Thu, 16 Nov 2023 09:04:00 +0000 /jp-jp/?p=518906&preview=true&preview_id=518906 The post Microsoft fabricでデータを活用した未来のビジネスを推進? appeared first on 乌鸦传媒 Japan.

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          Microsoft fabricでデータを活用した未来のビジネスを推進?

          Elayaraja Eswaran
          16th November 2023

          In a world driven by the data economy, organizations that are able to leverage data as a strategic asset while making the most of AI, including generative AI and analytics, will thrive.

          By collaborating with Microsoft on Fabric, we aim to help our clients address the fast-changing technology and competitive landscape to achieve their business goals with solid foundations and robust data and AI capabilities.

          乌鸦传媒 Fabric Journey is the result of a strong joint-commitment from our respective leadership, and our participation in the early adoption program. Being involved in the private and public preview programs provided our teams with a great opportunity to learn, test the product, and provide feedback to Microsoft. While we were involved in the Cloud Early Adopter programs and Azure Advisory Council, we have also been launch partners for strategic initiatives such as Microsoft Purview, Sustainability Manager, Fabric, and Data Explorer. Last year, we were the first system integrator (SI) to achieve all the three Specialization Status on Azure Data & AI, and we are also in the top five Global System Integrators worldwide in terms of Azure Data Service Consumption.

          Empowering our sales team

          In parallel with our upskilling efforts, we have prioritized enabling our Global Sales team to effectively communicate the value of Microsoft Fabric to our clients. Dedicated Sales Enablement sessions have equipped our sales force to articulate the tangible impact of this partnership. Leaders such as Arun Ulag, Corporate Vice President, Azure Data, Microsoft, and Niraj Parihar, 乌鸦传媒 & Data CEO at 乌鸦传媒, have provided invaluable insights into how data is driving transformation for our clients.

          “Through our relationship and the transformative capabilities of Microsoft Fabric, we are accelerating data value creation for our customers. 乌鸦传媒’s investment in scaling Fabric competency, paving the way for excellence through our Fabric-specific assessment and certification via 乌鸦传媒’s OCEANS Tool, provides enterprises with the opportunity to unleash unified data and drive their organizations forward” – Niraj Parihar, 乌鸦传媒 & Data CEO, 乌鸦传媒

          “Microsoft Fabric is a game-changer for data analytics and AI. It enables organizations to harness the power of data from any source, at any scale, and with any tool. 乌鸦传媒  has been relentlessly focused on readiness of resources for delivery of Microsoft Fabric to our customers. Together, we can help businesses transform with data and AI, and create a data-powered future.” – Arun Ulag, Corporate Vice President, Engineering – Azure Data, at Microsoft.

          Trailblazing tomorrow’s data business with our key offerings

          Our 乌鸦传媒 key offerings with Microsoft Fabric are delivering business value across industries and domains through four components:

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            生成础滨と合成データを通じてデータ领域を変革 /jp-jp/insights/expert-perspectives/transforming-the-data-terrain-through-generative-ai-and-synthetic-data/ /jp-jp/insights/expert-perspectives/transforming-the-data-terrain-through-generative-ai-and-synthetic-data/#respond Wed, 18 Oct 2023 09:09:00 +0000 /jp-jp/?p=518909&preview=true&preview_id=518909 The post 生成础滨と合成データを通じてデータ领域を変革 appeared first on 乌鸦传媒 Japan.

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            生成础滨と合成データを通じてデータ领域を変革

            Aruna Pattam
            18th October 2023

            Welcome to the brave new world of data, a world that is not just evolving but also actively being reshaped by remarkable technologies. It is a realm where our traditional understanding of data is continuously being challenged and transformed, paving the way for revolutionary methodologies and innovative tools.

            Among these cutting-edge technologies, two stand out for their potential to dramatically redefine our data-driven future: generative AI and synthetic data.

            In this article, we will delve deeper into these fascinating concepts.

            We will explore what generative AI and synthetic data are, how they interact, and, most importantly, how they are changing the data landscape.

            So, strap in and get ready for a tour into the future of data!

            Understanding generative AI and synthetic data

            Generative AI refers to a subset of artificial intelligence, particularly machine learning, that uses algorithms like generative adversarial networks (GANs) to create new content. It’s “generative” because it can generate something new and unique from random noise or existing data inputs, whether that be an image, a piece of text, data, or even music.

            GANs are powerful algorithms that comprise two neural networks — the generator, which produces new data instances, and the discriminator, which evaluates them for authenticity. Over time, the generator learns to create more realistic outputs.

            Today, the capabilities of generative AI have evolved significantly, with models like OpenAI’s GPT-4 showcasing a staggering potential to create human-like text. The technology is being refined and optimized continuously, making the outputs increasingly indistinguishable from real-world data.

            Synthetic data refers to artificially created information that mimics the characteristics of real-world data but does not directly correspond to real-world events. It is generated via algorithms or simulations, effectively bypassing the need for traditional data collection methods.

            In our increasingly data-driven world, the demand for high-quality, diverse, and privacy-compliant data is soaring.

            Current challenges with real data

            Across industries, companies are grappling with data-related challenges that prevent them from unlocking the full potential of artificial intelligence (AI) solutions.

            These hurdles can be traced to various factors, including regulatory constraints, sensitivity of data, financial implications, and data scarcity.

            1. Regulations:

            Data regulations have placed strict rules on data usage, demanding transparency in data processing. These regulations are in place to protect the privacy of individuals, but they can significantly limit the types and quantities of data available for developing AI systems.

            • Sensitive data:

            Moreover, many AI applications involve customer data, which is inherently sensitive. The use of production data poses significant privacy risks and requires careful anonymization, which can be a complex and costly process.

            • Financial implications:

            Financial implications add another layer of complexity. Non-compliance with regulations can lead to severe penalties.

            • Data availability:

            Furthermore, AI models typically require vast amounts of high-quality, historical data for training. However, such data is often hard to come by, posing a challenge in developing robust AI models.

            This is where synthetic data comes in.

            Synthetic data can be used to generate rich, diverse datasets that resemble real-world data but do not contain any personal information, thus mitigating any compliance risks. Additionally, synthetic data can be created on-demand, solving the problem of data scarcity and allowing for more robust AI model training.

            By leveraging synthetic data, companies can navigate the data-related challenges and unlock the full potential of AI.

            What is synthetic data?

            Synthetic data refers to data that’s artificially generated rather than collected from real-world events. It’s a product of advanced deep learning models, which can create a wide range of data types, from images and text to complex tabular data.

            Synthetic data aims to mimic the characteristics and relationships inherent in real data, but without any direct linkage to actual events or individuals.

            A synthetic data generating solution can be a game-changer for complex AI models, which typically require massive volumes of data for training. These models can be “fed” with synthetically generated data, thereby accelerating their development process and enhancing their performance.

            One of the key features of synthetic data is its inherent anonymization.

            Because it’s not derived from real individuals or events, it doesn’t contain any personally identifiable information (PII). This makes it a powerful tool for data-related tasks where privacy and confidentiality are paramount.

            As such, it can help companies navigate stringent data protection regulations, such as GDPR, by providing a rich, diverse, and compliant data source for various purposes.

            In essence, synthetic data can be seen as a powerful catalyst for advanced AI model development, offering a privacy-friendly, versatile, and abundant alternative to traditional data.

            Its generation and use have the potential to redefine the data landscape across industries.

            Synthetic data use cases:

            Synthetic data finds significant utility across various industries due to its ability to replicate real-world data characteristics while maintaining privacy.

            Here are a few key use cases.

            Testing and development:

            In testing and development, synthetic data can generate production-like data for testing purposes. This enables developers to validate applications under conditions that closely mimic real-world operations.

            Furthermore, synthetic data can be used to create testing datasets for machine learning models, accelerating the quality assurance process by providing diverse and scalable data without any privacy concerns.

            Healthcare:

            The health sector also reaps benefits from synthetic data. For instance, synthetic medical records or claims can be generated for research purposes, boosting AI capabilities without violating patient confidentiality.

            Similarly, synthetic CT/MRI scans can be created to train and refine machine learning models, ultimately improving diagnostic accuracy.

            Financial services:

            Financial services can utilize synthetic data to anonymize sensitive client data, allowing for secure development and testing.

            Moreover, synthetic data can be used to enhance scarce fraud detection datasets, improving the performance of detection algorithms.

            Insurance:

            In insurance, synthetic data can be used to generate artificial claims data. This can help in modeling various risk scenarios and aid in creating more accurate and fair policies, while keeping the actual claimant’s data private.

            These use cases are just the tip of the iceberg, demonstrating the transformative potential of synthetic data across industries.

            Conclusion

            In conclusion, the dynamic duo of generative AI and synthetic data is set to transform the data landscape as we know it.

            As we’ve seen, these technologies address critical issues, ranging from data scarcity and privacy concerns to regulatory compliance, thereby unlocking new potential for AI development.

            The future of synthetic data is promising, with an ever-expanding range of applications across industries. Its ability to provide an abundant, diverse, and privacy-compliant data source could be the key to unlocking revolutionary AI solutions and propelling us toward a more data-driven future.

            As we continue to explore the depths of these transformative technologies, we encourage you to delve deeper and stay informed about the latest advancements.

            Remember, understanding and embracing these changes today will equip us for the data-driven challenges and opportunities of tomorrow.

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