Digital Transformation Initiatives

McKinsey & Company 𝗯𝗹𝘂𝗲𝗽𝗿𝗶𝗻𝘁 𝗳𝗼𝗿 𝗵𝗼𝘄 𝗯𝗮𝗻𝗸𝘀 𝗰𝗮𝗻 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗲𝘅𝘁𝗿𝗮𝗰𝘁 𝗿𝗲𝗮𝗹 𝘃𝗮𝗹𝘂𝗲 𝗳𝗿𝗼𝗺 𝗔𝗜: ⬇️ This is a full-stack, enterprise-grade architecture — built on agents, orchestration, and rewired workflows. The AI bank stack consists out of 4 key layers: ⬇️ 𝟭. 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗟𝗮𝘆𝗲𝗿 This is the user layer — customers and employees. McKinsey calls for fully reimagined, intelligent, personalized experiences across all channels. → Multimodal chat (text, voice, image) → Omnichannel UX across mobile, contact center, branch → Digital twins for customer simulation and workforce training It’s all about a UI refresh and UX overhaul grounded in real AI. 𝟮. 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴 This is the brain of the AI-first bank. And it’s not just predictive models anymore — it’s orchestrated agent ecosystems. → AI Orchestrators: Plan, reason, delegate across workflows → Domain Agents: Specialize in credit policy, fraud, risk, legal → Copilots: Embedded in workflows to guide users and automate decisions McKinsey reports 20–60% productivity gains in decision-making with this approach. 𝟯. 𝗖𝗼𝗿𝗲 𝗧𝗲𝗰𝗵 & 𝗗𝗮𝘁𝗮 The foundation layer most banks underestimate — until GenAI models stall in production. → Vector databases → LLM orchestration and FinOps → Search and retrieval engines → ML pipelines → Secure data architecture → API infrastructure The goal: make data accessible, tools reusable, and infra invisible to the business. Without this, nothing scales. 𝟰. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 This is where the transformation wins or fails. Without rewiring the org, the tech doesn’t matter. → AI control towers to track value and set guardrails → Cross-functional teams across business, tech, and AI → Platform operating model for speed and alignment → Enterprise-wide reuse of AI capabilities If you're building isolated projects without shared assets or central coordination, you’re not transforming — you’re experimenting. 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗮𝗹𝗹 𝗮𝗱𝗱𝘀 𝘂𝗽 𝘁𝗼? The banks that win won’t be the ones with the most pilots. They’ll be the ones that industrialize agents, orchestration, and rewired workflows, with full-stack coordination. Full McKinsey article: https://lnkd.in/dPaJzVK4 𝗜 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲𝘀𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁𝘀 — 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 — 𝗶𝗻 𝗺𝘆 𝘄𝗲𝗲𝗸𝗹𝘆 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. 𝗬𝗼𝘂 𝗰𝗮𝗻 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 𝗵𝗲𝗿𝗲 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲: https://lnkd.in/dbf74Y9E

🗺️ AirBnB Customer Journey Blueprint, a wonderful practical example of how to visualize the entire customer experience for 2 personas, across 8 touch points, with user policies, UI screens and all interactions with the customer service — all on one single page. AirBnB Customer Journey (Google Drive): https://lnkd.in/eKsTjrp4 Spotify Customer Journey (High-res): https://lnkd.in/eX3NBWbJ Now, unlike AirBnB, your product might not need a mapping against user policies. However, it might need other lanes that would be more relevant for your team. E.g. include relevant findings and recommendations from UX research. List key actions needed for next stage. Add relevant UX metrics and unsuccessful touchpoints. That last bit is often missing. Yet customer journeys are often non-linear, with unpredictable entry points, and integrations way beyond the final stage of a customer journey map. It’s in those moments when things leave a perfect path that a product’s UX is actually stress tested. So consider mapping unsuccessful touchpoints as well — failures, error messages, conflicts, incompatibilities, warnings, connectivity issues, eventual lock-outs and frequent log-outs, authentication issues, outages and urgent support inquiries. Even further than that: each team could be able to zoom into specific touch points and attach links to quotes, photos, videos, prototypes, design system docs and Figma files. Perhaps even highlight the desired future state. Technical challenges and pain points. Those unsuccessful states. Now, that would be a remarkable reference to use in the beginning of every design sprint. Such mappings are often overlooked, but they can be very impactful. Not only is it a very tangible way to visualize UX, but it’s also easy to understand, remember and relate to daily — potentially for all teams in the entire organization. And that's something only few artefacts can do. Useful resources: Free Template: Customer Journey Mapping, by Taras Bakusevych https://lnkd.in/e-emkh5A Free Template: End-To-End User Experience Map (Figma), by Justin Tan https://lnkd.in/eir9jg7J Customer Journey Map Template (Figma), by Ed Biden https://lnkd.in/evaUP4kz Free Figma/Miro User Journey Maps Templates https://lnkd.in/etSB7VqB User Journey Maps vs. Service Blueprints (+ Templates) https://lnkd.in/e-JSYtwW UX Mapping Methods (+ Miro/Figma Templates) https://lnkd.in/en3Vje4t #ux #design

During the ascent of #fintech as a disruption driver in #finance, digital banks have been the first and most impactful use case. Let’s take a look at their playbook. The term itself – alternatives include challenger banks or neobanks – characterizes players (usually new entrants) challenging the traditional banking model with a #technology-first approach that involves flexible, branchless, digital-native (mobile) banking, often focusing on or starting from niche segments and customers. An increasingly digital arena, a shift in consumer behaviour and a gap in product and customer focus by incumbents have enabled these new players to challenge the status quo. Their success and proliferation around the globe is a clear sign of agile, digital-first, product-niche strategies prevailing over traditional, monolithic, vertical banking #business models. Whereas different patterns can be identified in their evolutionary path, the successful models can be aggregated to two broad categories: — Greenfield players starting completely from scratch by means of identifying a niche market or segment, often neglected by incumbents, and focusing on seamless customer experience, attractive design, competitive pricing and a digital or mobile only set-up. In terms of strategy two elements clearly stand-out: 1) hyper-growth and scale as the core - sometimes only - metrics (which explains why so many have been unprofitable) 2) an ecosystem play, driven by horizontal partnerships (vs the vertical traditional model). N26, Revolut and Nubank are typical examples of this model. — Large, closed-loop ecosystem players with a non-finance business geared on technology and an anchor in #ecommerce launching (digital) #banking spin-offs as a means of converting (and monetizing) their existing client-base. Most (or almost all) of the examples here come from Asia (i.e. Webank, Kakaobank), mainly due to the set-up of the #economy (lacking a robust, finance architecture and, in effect, benefiting private, BigTech players covering the gap). Webank, for example, is owned by Tencent, China’s largest social-media BigTech company (owner of WeChat, China’s equivalent of Facebook). It has managed to reach a value of $33 billion and a base of more than 320 million active users by focusing on building a modern IT stack (as a competitive edge to traditional banks) and leveraging on the data generated by the Tencent ecosystem (i.e. retail lending credit scoring built on Tencent data, resulted in a non-performing loan ratio of just 1.2%, about half (or less) of the industry average for such non-secured loans). Irrespective of their origins, both models have been (fast) converging to what has become the new holy grail of modern finance: platform #economics and ecosystem plays. These are the concepts that will be defining the boundaries in an increasingly network and technology driven field. Opinions: my own, Graphic source: Momentum Works, Decoding digital banks

About a year ago, I created a comprehensive graphic comparing the major cloud providers. As I revisit it now, I'm struck by the rapid evolution of the cloud landscape. While each provider's core competencies remain largely unchanged, there have been some significant developments and emerging trends. Let's dive in! 1. 𝗧𝗵𝗲 𝗥𝗶𝘀𝗲 𝗼𝗳 𝗠𝘂𝗹𝘁𝗶-𝗖𝗹𝗼𝘂𝗱: Increasingly, businesses are adopting a multi-cloud approach, cherry-picking services from different providers to optimize costs, avoid vendor lock-in, and take advantage of each platform's unique offerings. This shift towards a more diverse and flexible cloud strategy is a testament to the growing maturity of the market. 2. 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗧𝗮𝗸𝗲𝘀 𝗖𝗲𝗻𝘁𝗲𝗿 𝗦𝘁𝗮𝗴𝗲: In response to the pressing need for environmental action, the big three cloud providers have all stepped up their sustainability efforts. From renewable energy initiatives to tools that help customers monitor and reduce their carbon footprint, the cloud is becoming greener. 3. 𝗧𝗵𝗲 𝗔𝗜/𝗠𝗟 𝗕𝗼𝗼𝗺: Artificial intelligence and machine learning have seen explosive growth, with each provider offering an expanding array of AI/ML services. These tools are becoming more user-friendly and accessible, democratizing AI and enabling businesses of all sizes to harness its power.     4. 𝗧𝗵𝗲 𝗘𝗱𝗴𝗲 𝗘𝘅𝗽𝗮𝗻𝗱𝘀: Edge computing has come into its own, with Azure Arc, AWS Outposts, and Google Anthos all seeing significant enhancements. This development is crucial for IoT, real-time data processing, and low-latency applications. As the intelligent edge continues to evolve, it's opening up exciting new possibilities. 🚀 5. S𝗲𝗿𝘃𝗲𝗿𝗹𝗲𝘀𝘀 𝗦𝗶𝗺𝗽𝗹𝗶𝗰𝗶𝘁𝘆: Serverless computing has been a game-changer, abstracting away infrastructure management and enabling developers to focus on writing code. Over the past year, serverless offerings have continued to mature, with improved tooling, easier integration, and more robust functionalities. As always, the "best" cloud provider is the one that aligns with your unique requirements, existing infrastructure, and long-term objectives. It's crucial to periodically reassess your cloud strategy to ensure it remains optimized for your evolving needs. I'm curious to hear your thoughts! What notable changes or trends have you observed in the cloud ecosystem recently?

Ever heard of the Lippitt-Knoster Model for Managing Complex Change? It's a classic in the change management world, laying out the essential pieces needed to navigate big transformations. Taking a cue from that, I've adapted it to fit the world of digital transformation. There are seven key elements you can't afford to miss: Vision, Strategy, Objectives, Capabilities, Architecture, Roadmap, and Projects & Programs. Skip any one of these, and you're asking for trouble. Here’s why each one matters: • 𝐕𝐢𝐬𝐢𝐨𝐧: This is the 'what' of your transformation. A clear vision gives everyone a target to aim for, aligning all efforts and keeping the team focused. • 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: Think of this as the 'why' and 'how.' A solid strategy explains the logic behind your vision, showing how you plan to get there and why it's the best route. It’s designed to guide everyone in the company on how to make decisions that support the vision, aligning all efforts and keeping the team focused. • 𝐎𝐛𝐣𝐞𝐜𝐭𝐢𝐯𝐞𝐬: These are your milestones. Clear, specific objectives make it easy to measure success and ensure everyone knows what's important. Without them, you can easily veer off course and waste resources. • 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: These are what your company will now be able to do that it wasn't able to before in order to achieve the objectives. These can be organizational capabilities (like improved decision-making), technical capabilities (such as real-time operational visibility), or other types like enhanced customer engagement or streamlined processes. • 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞: A robust architecture ensures all your tech works together smoothly, preventing inefficiencies and costly headaches. This includes various types of architecture such as data architecture, IT infrastructure architecture, enterprise architecture, and functional architecture. Effective architecture is central to reducing technical debt and aligning software with broader business transformation goals. • 𝐑𝐨𝐚𝐝𝐦𝐚𝐩: Your roadmap is the game plan. It lays out the sequence of actions, helping you avoid uncertainty and missteps. It's your guide to getting things done right. • 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 & 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬: These are where the rubber meets the road. Actionable projects and programs turn your strategy into reality, making sure your plans lead to real, tangible outcomes. From my experience, I think '𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬' and '𝐑𝐨𝐚𝐝𝐦𝐚𝐩' are the two most overlooked. What do you think? ******************************************* • Follow #JeffWinterInsights to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

In countries like the Netherlands, trash doesn’t just disappear — it goes underground. How is it organized in your city? Amsterdam, Rotterdam and Utrecht use underground waste containers and smart collection systems where bins are connected to large subterranean units, keeping streets visually clean, reducing odour, and cutting unnecessary truck movements. But this isn’t just a Dutch story. It’s a global shift powered by technology. 📊 How leading cities are transforming waste management: 🇳🇱 Netherlands • Underground containers reduce surface bin clutter by up to 70–80% in dense neighbourhoods • IoT sensors monitor fill levels, enabling 30–40% fewer collection trips 🇰🇷 Songdo, South Korea • Fully pneumatic waste system • Trash travels through underground vacuum tubes at 70 km/h • Eliminated traditional garbage trucks in residential zones • Reduced waste handling costs by up to 50% 🇳🇴 Bergen, Norway • Pneumatic underground network beneath historic districts • Cut CO₂ emissions from waste collection vehicles by up to 35% • Reduced noise pollution in heritage zones 🇸🇬 Singapore • Smart bins + centralised waste chutes in HDBs • Waste-to-energy plants process over 90% of Singapore’s waste, shrinking landfill dependency • Semakau Landfill projected lifespan extended from 2045 to beyond 2035 through tech & efficiency gains 🚀 Technology making this possible: • IoT sensors for real-time bin monitoring • AI-powered route optimisation reducing fuel use • Pneumatic vacuum tube networks • Automated robotics for waste sorting • Waste-to-energy conversion systems ✅ The impact: • Cleaner cities • Fewer pests and odours • Reduced emissions • Lower operating costs • Better citizen experience The future of urban living isn’t just about shiny skyscrapers — it’s about invisible infrastructure working intelligently beneath our feet. Smart cities aren’t just built. They’re engineered to stay clean. #SmartCities #UrbanInnovation #Sustainability #CircularEconomy #CleanTech

In a recent discussion with Priscilla Ng, Prudential plc’s Group Chief Customer and Marketing Officer, we delved into Prudential’s shift towards customer-centricity. This conversation underscored the seamless integration of digital innovation and the essential human touch in the insurance sector.   Here are five key insights from our discussion applicable across industries:   🔹Strategic Integration of AI and Human Insight: Prudential is not just using AI to streamline processes; they are using it to significantly enhance personalization and customer service. From simplifying underwriting to transforming service at customer touchpoints like call centers, AI is proving to be transformative. How can other industries use AI not merely for efficiency but as a catalyst for customer connection?   🔹Empowering Employees: In the journey of digital transformation, the role of technology is as crucial as the people behind it. Priscilla emphasized the importance of equipping over 15,000 employees with the necessary mindset, skills, and tools to excel in a digitally evolving landscape. What strategies can companies implement to ensure their teams thrive amidst technological change?   🔹Balanced Approach to Digital and Human Interaction: Despite extensive technological integration, the human element remains critical at Prudential. Their approach ensures that digital enhancements support rather than replace human interactions, thereby strengthening customer relationships. How can businesses maintain this balance to enhance, not undermine, human connections?   🔹Navigating Challenges in Transformation: Adapting to digital transformation comes with challenges, from aligning large teams with new strategies to continuously adapting to emerging technologies. Priscilla shared that a steadfast focus on customer-centricity is essential for navigating these challenges. How can other organizations keep their focus on customer needs while managing transformation complexities?   🔹Continuous Learning and Adaptation: A crucial aspect of Prudential’s transformation is fostering an environment of continuous learning and adaptation. This involves training in new technologies and developing a deeper understanding of customer needs and behaviors. How can continuous learning be structured to keep pace with rapid technological advancements and evolving customer expectations?   This dialogue is part of McKinsey’s ongoing series exploring how leaders steer their companies through transformations. Stay tuned for more insights shaping today’s business landscape. Full interview: https://lnkd.in/gtjphW2s   #Leadership #DigitalTransformation #CustomerCentricity #InsuranceIndustry #AI

Emerging Departments: How AI is Transforming Organizations Transformation in light of AI isn't just about digital change—it's strategic, cultural, and organizational. Early results of organizational optimization with AI reveal that traditional structures are evolving into new, combined departments that break down silos and enhance collaboration. Here are some emerging trends: 1. Human Experience Department (Led by the CXO) Combines marketing, HR, and customer service to create a unified experience approach. Focuses on customer and employee experience as a seamless continuum. Example: Airbnb and Starbucks blending internal and external engagement for holistic experience design. 2. The Intelligence Function (Led by Chief Data & Intelligence Officer (CDIO)) Merges IT, data analytics, and AI strategy into a unified intelligence function. Enhances decision-making with data-driven insights and technology integration. Example: Microsoft and Amazon use intelligence functions to support strategy and innovation. 3. Integrated Growth Department (Led by the CGO) Combines Marketing, Sales, and Customer Success to create cohesive client journeys. Prioritizes growth by aligning customer interactions across all touchpoints. Example: HubSpot and Salesforce driving client experience continuity. 4. Strategic Innovation & Transformation Office (Led by Chief Strategy Officer or Chief Transformation Officer) Combines strategy, innovation, and transformation initiatives for continuous evolution. Fosters agility by integrating foresight and innovation into long-term strategy. Example: Tesla blending innovation with strategic growth planning. 5. Technology and Digital Transformation Department (Led by the Chief Technology & Transformation Officer) Integrates IT, digital transformation, and cybersecurity under one strategic role. Embeds technology into workflows while ensuring security and compliance. Example: Cisco and IBM streamlining their digital transformation efforts. 6. Resilience and Continuity Department (Led by the Chief Risk Officer) Oversees Risk Management, Business Continuity, and Strategic Foresight. Ensures organizational resilience in an increasingly FLUX world. Example: JP Morgan building resilience to mitigate risks and ensure continuity. 7. Ethics and Responsible AI Office (Led by the CEAO) Ensures ethical AI use and compliance with regulatory standards. Maintains trust and integrity as AI becomes central to business strategy. Example: Microsoft and IBM proactively building ethics frameworks for responsible AI. In sum, AI is driving fundamental shifts in how we structure our organizations. To thrive, leaders must think beyond digital transformation and focus on strategic, cultural, and organizational evolution. The companies that succeed will be those that break down silos, integrate their functions, and embrace transformation as a continuous journey.

🗞️ A must-read for anyone interested in European AI governance right now: this study, drafted for the Committee on Industry, Research and Energy (ITRE) of the European Parliament by the Policy Department for Transformation, Innovation & Health 👉🏼Analyses how the AI Act adopted mid-2024 is articulated with other key EU digital regulations 🔎 Examines interactions with: • GDPR • Data Act (DA) • Data Governance Act (DGA) • Digital Services Act (DSA) • Digital Markets Act (DMA) • Cyber Resilience Act (CRA) • NIS2 Directive, the New Legislative Framework (NLF) and product-safety / digital-elements rules 📖 A timely document as the #EU faces the demanding task of building digital rules that the world still lacks, balancing innovation, transparency and fundamental rights. ➡️ creating a broad legal ecosystem connecting data, algorithms and human values. 🎯 3 goals • Ensure trustworthy #AI in Europe — safe, transparent, respectful of rights and EU values. • Foster innovation and competitiveness • Provide legal certainty through a proportionate, risk-based approach. 🗺️ The study maps the interplay among current acts: 🔹with GDPR – Encourage joint guidance between data-protection and AI authorities to simplify impact assessments and ensure consistent supervision across Member States. 🔹with Data Act -Streamline obligations on data quality and access so that compliance supports, rather than slows, AI innovation. -Coordinate governance to prevent duplication and promote data flows for trustworthy AI. 🔹with Data Governance Act -Build bridges between data-sharing frameworks & AI requirements through interoperable standards and clear responsibilities for data use. 🔹with DSA / DMA -Use platform transparency & risk-assessment mechanisms to reinforce, not duplicate, AI Act duties -promote a coherent, innovation-friendly environment for general-purpose models 🔹with CRA / NIS2 / NLF -Align product-safety, cybersecurity & AI conformity processes to create 1 coherent certification pathway for digital products. 👉🏼an #AI Act as integrated regulatory ecosystem covering data, algorithms, products, platforms and rights = smart coordination turning compliance into trust and competitiveness. Future model proposed : • Principle-based horizontal rules with sectoral modules • Clear layering — data → algorithms → systems → services • Aligned definitions & conformity regimes • Simplified compliance for SMEs, rigorous oversight for high-risk systems 🧭 Practical steps forward ▶️Short term: joint guidelines (AI Act / GDPR), shared sandboxes, harmonised templates. ⏩️Medium term: clarify mandates, connect conformity procedures. ⏭️Long term: build a unified digital framework linking data, AI and platform rules, strengthen international standardisation& partnerships. ➡️ AI for good, trustworthy by design, aligned with rights and values. 🙏🏻 Authors Hans Graux Krzysztof G. Nayana Murali Jonathan Cave Maarten Botterman

Transformation thrives when people are empowered to make the most of technology. 🚀 My recent visit to the Bosch production facility for automotive and eBike drives in Miskolc, Hungary, showcased this perfectly. I was deeply impressed to see firsthand how their progress in digitalization and the implementation of the Bosch Manufacturing and Logistics Platform (BMLP) is reshaping their manufacturing operations. BMLP is a globally standardized, open IT platform that connects all stages of production and logistics. During an insightful plant tour, I observed a successful example of how the platform leads to significant improvements in efficiency, quality, and data transparency across the plant. What stood out most was seeing the passionate and enthusiastic team at Miskolc leverage this technology in action and achieving great results towards operational excellence. Here are three key areas where BMLP is contributing to the plant’s digital transformation success, powered by our NEXEED IAS: 1️⃣ Enhanced Efficiency & Reduced Downtime: The module Shopfloor Management enables a closed PDCA cycle in production by consequent integration of all relevant information in one system. This leads to quick reaction in case of deviations to minimize downtimes and safeguard the daily performance targets.   2️⃣ Improved Product Quality: Continuous monitoring throughout production stages helps the team identify issues early, ensuring top-tier quality while driving process improvements.   3️⃣ Change Management: Change management plays a crucial role in digital transformation within a plant. As seen in Miskolc, effectively managing change ensures that the workforce is engaged, and equipped to embrace new technologies, driving sustainable success. In Miskolc we have seen solutions using gamification that help to involve all associates, making the transition both engaging and effective.   I was also excited to see AI in action with a live demo of 8D Analysis using GenAI, cutting failure analysis time by half. By automating the root cause analysis process, engineers are now spending less time on administrative tasks and more on proactive problem-solving – a great example of how technology empowers people. Beyond the production lines, the most rewarding part of the visit was engaging with the team. Their passion for digitalization, commitment to upskilling, and their drive for innovation truly brought home the message: technology is only as strong as the people behind it. A special thank you to the entire Miskolc team for the inspiring discussions and warm welcome – along with Volker Schilling, Klaus Maeder, Joerg Klingler, Volker Schiek, Norbert Jung, Stephan Brand, Aemen Bouafif, and everyone who joined us on this great trip. I’m excited to see what’s next on this incredible digitalization journey!