• Ah, "Recherche de nouveaux marchés : un guide en 3 étapes". Parce que qui n'a jamais rêvé de plonger tête la première dans un océan de données, armé seulement d'un tableau Excel et d'un café trop fort ? Semrush, notre sauveur numérique, nous promet une méthode infaillible pour analyser un nouveau marché. En trois grandes étapes, évidemment, parce que deux, c'est trop simple et quatre, c'est pour les amateurs.

    Première étape : l'analyse. Oui, parce qu'il suffit de jeter un œil sur quelques graphiques colorés pour saisir les subtilités d'un marché complexe. Qui a besoin de comprendre le comportement des consommateurs quand on a un joli diagramme en camembert ? Cela dit, n'oubliez pas de mettre vos lunettes d'analyste, sinon vous risqueriez de confondre la courbe de croissance avec celle de votre compte en banque après une soirée un peu trop arrosée.

    Deuxième étape : la stratégie. C'est là que le vrai fun commence. Développer une stratégie basée sur des données ! Quelle idée brillante ! Mais attention, assurez-vous de ne pas vous laisser emporter par des concepts comme "besoins des clients" ou "concurrence". Ce serait trop ennuyeux. Pourquoi ne pas plutôt se concentrer sur les buzzwords à la mode pour impressionner vos collègues lors de la prochaine réunion ? "Synergie", "agilité", "disruption"… Les mots sont comme des épices : un peu trop et vous risquez de brûler le plat.

    Enfin, la troisième étape : l'exécution. Voilà, le moment tant attendu où vous pouvez enfin passer à l'action. Après avoir passé des heures à analyser et planifier, c'est maintenant que vous pouvez voir à quel point votre stratégie est brillante en théorie… et catastrophique en pratique. Qui aurait cru que le monde réel ne se plie pas toujours aux chiffres que vous avez triturés ? Mais ne vous inquiétez pas, vous pourrez toujours blâmer les "facteurs externes" ou la météo.

    En somme, ce guide de Semrush pour "rechercher de nouveaux marchés" est un incontournable pour quiconque cherche à se perdre dans un dédale de chiffres et de graphiques. Cela dit, je suis sûr que vos talents de détective de marché vous permettront de déchiffrer tout ce jargon. Alors, en avant pour l'aventure, n'oubliez pas votre sens de l'humour, vous en aurez besoin !

    #RechercheDeMarchés #AnalyseDeMarché #StratégieMarketing #Semrush #BusinessIntelligence
    Ah, "Recherche de nouveaux marchés : un guide en 3 étapes". Parce que qui n'a jamais rêvé de plonger tête la première dans un océan de données, armé seulement d'un tableau Excel et d'un café trop fort ? Semrush, notre sauveur numérique, nous promet une méthode infaillible pour analyser un nouveau marché. En trois grandes étapes, évidemment, parce que deux, c'est trop simple et quatre, c'est pour les amateurs. Première étape : l'analyse. Oui, parce qu'il suffit de jeter un œil sur quelques graphiques colorés pour saisir les subtilités d'un marché complexe. Qui a besoin de comprendre le comportement des consommateurs quand on a un joli diagramme en camembert ? Cela dit, n'oubliez pas de mettre vos lunettes d'analyste, sinon vous risqueriez de confondre la courbe de croissance avec celle de votre compte en banque après une soirée un peu trop arrosée. Deuxième étape : la stratégie. C'est là que le vrai fun commence. Développer une stratégie basée sur des données ! Quelle idée brillante ! Mais attention, assurez-vous de ne pas vous laisser emporter par des concepts comme "besoins des clients" ou "concurrence". Ce serait trop ennuyeux. Pourquoi ne pas plutôt se concentrer sur les buzzwords à la mode pour impressionner vos collègues lors de la prochaine réunion ? "Synergie", "agilité", "disruption"… Les mots sont comme des épices : un peu trop et vous risquez de brûler le plat. Enfin, la troisième étape : l'exécution. Voilà, le moment tant attendu où vous pouvez enfin passer à l'action. Après avoir passé des heures à analyser et planifier, c'est maintenant que vous pouvez voir à quel point votre stratégie est brillante en théorie… et catastrophique en pratique. Qui aurait cru que le monde réel ne se plie pas toujours aux chiffres que vous avez triturés ? Mais ne vous inquiétez pas, vous pourrez toujours blâmer les "facteurs externes" ou la météo. En somme, ce guide de Semrush pour "rechercher de nouveaux marchés" est un incontournable pour quiconque cherche à se perdre dans un dédale de chiffres et de graphiques. Cela dit, je suis sûr que vos talents de détective de marché vous permettront de déchiffrer tout ce jargon. Alors, en avant pour l'aventure, n'oubliez pas votre sens de l'humour, vous en aurez besoin ! #RechercheDeMarchés #AnalyseDeMarché #StratégieMarketing #Semrush #BusinessIntelligence
    Researching New Markets: A 3-Step Guide
    A comprehensive guide by Semrush helps to analyze a new market in three big steps. Based on best practices and functionalities of the Traffic & Market Toolkit.
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  • data analysis, dashboards, data visualization, business decisions, analytics mistakes, ineffective dashboards, data solutions, performance metrics, business intelligence

    ## Introduction

    Are you one of those professionals who spends countless hours crafting a visually stunning dashboard, only to discover that nobody gives a damn about it? Welcome to the harsh reality of data analysis! It's shocking how many analysts fall into this trap, pouring their creativity and skill into something that ult...
    data analysis, dashboards, data visualization, business decisions, analytics mistakes, ineffective dashboards, data solutions, performance metrics, business intelligence ## Introduction Are you one of those professionals who spends countless hours crafting a visually stunning dashboard, only to discover that nobody gives a damn about it? Welcome to the harsh reality of data analysis! It's shocking how many analysts fall into this trap, pouring their creativity and skill into something that ult...
    Dashboard: The Mistake That Ruins Your Data Analysis
    data analysis, dashboards, data visualization, business decisions, analytics mistakes, ineffective dashboards, data solutions, performance metrics, business intelligence ## Introduction Are you one of those professionals who spends countless hours crafting a visually stunning dashboard, only to discover that nobody gives a damn about it? Welcome to the harsh reality of data analysis! It's...
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  • Ankur Kothari Q&A: Customer Engagement Book Interview

    Reading Time: 9 minutes
    In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns.
    But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic.
    This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results.
    Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.

     
    Ankur Kothari Q&A Interview
    1. What types of customer engagement data are most valuable for making strategic business decisions?
    Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns.
    Second would be demographic information: age, location, income, and other relevant personal characteristics.
    Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews.
    Fourth would be the customer journey data.

    We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data.

    2. How do you distinguish between data that is actionable versus data that is just noise?
    First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance.
    Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in.

    You also want to make sure that there is consistency across sources.
    Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory.
    Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy.

    By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions.

    3. How can customer engagement data be used to identify and prioritize new business opportunities?
    First, it helps us to uncover unmet needs.

    By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points.

    Second would be identifying emerging needs.
    Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly.
    Third would be segmentation analysis.
    Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies.
    Last is to build competitive differentiation.

    Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions.

    4. Can you share an example of where data insights directly influenced a critical decision?
    I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings.
    We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms.
    That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs.

    That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial.

    5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time?
    When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences.
    We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments.
    Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content.

    With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns.

    6. How are you doing the 1:1 personalization?
    We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer.
    So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer.
    That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience.

    We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers.

    7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service?
    Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved.
    The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments.

    Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention.

    So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization.

    8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights?
    I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights.

    Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement.

    Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant.
    As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively.
    So there’s a lack of understanding of marketing and sales as domains.
    It’s a huge effort and can take a lot of investment.

    Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing.

    9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data?
    If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge.
    Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side.

    Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important.

    10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before?
    First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do.
    And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations.
    The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it.

    Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one.

    11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations?
    We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI.
    We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals.

    We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization.

    12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data?
    I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points.
    Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us.
    We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels.
    Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms.

    Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps.

    13. How do you ensure data quality and consistency across multiple channels to make these informed decisions?
    We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies.
    While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing.
    We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats.

    On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically.

    14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years?
    The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices.
    Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities.
    We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases.
    As the world is collecting more data, privacy concerns and regulations come into play.
    I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies.
    And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture.

    So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.

     
    This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die.
    Download the PDF or request a physical copy of the book here.
    The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage.
    #ankur #kothari #qampampa #customer #engagement
    Ankur Kothari Q&A: Customer Engagement Book Interview
    Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage. #ankur #kothari #qampampa #customer #engagement
    WWW.MOENGAGE.COM
    Ankur Kothari Q&A: Customer Engagement Book Interview
    Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question (and many others), we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage.
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  • IA : « Les robots peuvent-ils battre les loups de Wall Street ? »

    A la Bourse de New York, le 10 juin 2025. RICHARD DREW / AP En 1973, Burton Malkiel, un professeur à l’université Stanford, avait fait polémique en affirmant qu’un singe avec un bandeau sur les yeux lançant des fléchettes sur les pages d’un journal financier sélectionnerait un portefeuille d’actions « aussi bon » que celui soigneusement choisi par des experts. Le test a été tenté. Il s’avéra que M. Malkiel avait tort : les singes étaient meilleurs. Cinquante ans après, la question désormais est de savoir si les robots peuvent battre les loups de Wall Street. Lire aussi | Article réservé à nos abonnés Dans les banques, la marche à pas comptés vers l’IA générative Stanford a la réponse. Un article paru lundi 9 juin sur le site de l’université relate que des chercheurs ont entraîné sur des données de marchés allant de 1980 à 1990 un modèle prédictif d’investissement. Puis, ils lui ont demandé de recomposer les portefeuilles de 3 300 fonds communs de placement en actions américaines entre 1990 et 2020. Verdict : l’intelligence artificiellea écrasé 93 % des gérants, obtenant des performances en moyenne six fois supérieures. Pas étonnant que l’industrie de la gestion d’actifs mette les bouchées doubles sur la technologie. Selon Bloomberg, BlackRock a révélé, jeudi 12 juin, avoir bâti une « IA analyste » sur les actions, baptisée « Asimov », du nom de l’auteur de science-fiction fasciné par la relation entre l’humain et les robots. « Pendant que tout le monde dort la nuit, ces agents d’intelligence artificielle balayent les notes de recherche, les dépôts de documents des entreprises, les courriels », a expliqué Rob Goldstein, le responsable des opérations du premier gestionnaire d’actifs mondial. Il vous reste 41.24% de cet article à lire. La suite est réservée aux abonnés.
    #les #robots #peuventils #battre #loups
    IA : « Les robots peuvent-ils battre les loups de Wall Street ? »
    A la Bourse de New York, le 10 juin 2025. RICHARD DREW / AP En 1973, Burton Malkiel, un professeur à l’université Stanford, avait fait polémique en affirmant qu’un singe avec un bandeau sur les yeux lançant des fléchettes sur les pages d’un journal financier sélectionnerait un portefeuille d’actions « aussi bon » que celui soigneusement choisi par des experts. Le test a été tenté. Il s’avéra que M. Malkiel avait tort : les singes étaient meilleurs. Cinquante ans après, la question désormais est de savoir si les robots peuvent battre les loups de Wall Street. Lire aussi | Article réservé à nos abonnés Dans les banques, la marche à pas comptés vers l’IA générative Stanford a la réponse. Un article paru lundi 9 juin sur le site de l’université relate que des chercheurs ont entraîné sur des données de marchés allant de 1980 à 1990 un modèle prédictif d’investissement. Puis, ils lui ont demandé de recomposer les portefeuilles de 3 300 fonds communs de placement en actions américaines entre 1990 et 2020. Verdict : l’intelligence artificiellea écrasé 93 % des gérants, obtenant des performances en moyenne six fois supérieures. Pas étonnant que l’industrie de la gestion d’actifs mette les bouchées doubles sur la technologie. Selon Bloomberg, BlackRock a révélé, jeudi 12 juin, avoir bâti une « IA analyste » sur les actions, baptisée « Asimov », du nom de l’auteur de science-fiction fasciné par la relation entre l’humain et les robots. « Pendant que tout le monde dort la nuit, ces agents d’intelligence artificielle balayent les notes de recherche, les dépôts de documents des entreprises, les courriels », a expliqué Rob Goldstein, le responsable des opérations du premier gestionnaire d’actifs mondial. Il vous reste 41.24% de cet article à lire. La suite est réservée aux abonnés. #les #robots #peuventils #battre #loups
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    IA : « Les robots peuvent-ils battre les loups de Wall Street ? »
    A la Bourse de New York, le 10 juin 2025. RICHARD DREW / AP En 1973, Burton Malkiel, un professeur à l’université Stanford (Californie), avait fait polémique en affirmant qu’un singe avec un bandeau sur les yeux lançant des fléchettes sur les pages d’un journal financier sélectionnerait un portefeuille d’actions « aussi bon » que celui soigneusement choisi par des experts. Le test a été tenté. Il s’avéra que M. Malkiel avait tort : les singes étaient meilleurs. Cinquante ans après, la question désormais est de savoir si les robots peuvent battre les loups de Wall Street. Lire aussi | Article réservé à nos abonnés Dans les banques, la marche à pas comptés vers l’IA générative Stanford a la réponse. Un article paru lundi 9 juin sur le site de l’université relate que des chercheurs ont entraîné sur des données de marchés allant de 1980 à 1990 un modèle prédictif d’investissement. Puis, ils lui ont demandé de recomposer les portefeuilles de 3 300 fonds communs de placement en actions américaines entre 1990 et 2020. Verdict : l’intelligence artificielle (IA) a écrasé 93 % des gérants, obtenant des performances en moyenne six fois supérieures. Pas étonnant que l’industrie de la gestion d’actifs mette les bouchées doubles sur la technologie. Selon Bloomberg, BlackRock a révélé, jeudi 12 juin, avoir bâti une « IA analyste » sur les actions, baptisée « Asimov », du nom de l’auteur de science-fiction fasciné par la relation entre l’humain et les robots. « Pendant que tout le monde dort la nuit, ces agents d’intelligence artificielle balayent les notes de recherche, les dépôts de documents des entreprises, les courriels », a expliqué Rob Goldstein, le responsable des opérations du premier gestionnaire d’actifs mondial. Il vous reste 41.24% de cet article à lire. La suite est réservée aux abonnés.
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  • Apple WWDC 2025: News and analysis

    Apple’s Worldwide Developers Conference 2025 saw a range of announcements that offered a glimpse into the future of Apple’s software design and artificial intelligencestrategy, highlighted by a new design language called  Liquid Glass and by Apple Intelligence news.

    Liquid Glass is designed to add translucency and dynamic movement to Apple’s user interface across iPhones, iPads, Macs, Apple Watches, and Apple TVs. The overhaul aims to make interactions with elements like buttons and sidebars adapt contextually.

    However, the real news of WWDC could be what we didn’t see.  Analysts had high expectations for Apple’s AI strategy, and while Apple Intelligence was talked about, many market watchers reported that it lacked the innovation that have come from Google’s and Microsoft’s generative AIrollouts.

    The question of whether Apple is playing catch-up lingered at WWDC 2025, and comments from Apple execs about delays to a significant AI overhaul for Siri were apparently interpreted as a setback by investors, leading to a negative reaction and drop in stock price.

    Follow this page for Computerworld‘s coverage of WWDC25.

    WWDC25 news and analysis

    Apple’s AI Revolution: Insights from WWDC

    June 13, 2025: At Apple’s big developer event, developers were served a feast of AI-related updates, including APIs that let them use Apple Intelligence in their apps and ChatGPT-augmentation from within Xcode. As a development environment, Apple has secured its future, with Macs forming the most computationally performant systems you can affordably purchase for the job.

    For developers, Apple’s tools get a lot better for AI

    June 12, 2025: Apple announced one important AI update at WWDC this week, the introduction of support for third-party large language models such as ChatGPT from within Xcode. It’s a big step that should benefit developers, accelerating app development.

    WWDC 25: What’s new for Apple and the enterprise?

    June 11, 2025: Beyond its new Liquid Glass UI and other major improvements across its operating systems, Apple introduced a hoard of changes, tweaks, and enhancements for IT admins at WWDC 2025.

    What we know so far about Apple’s Liquid Glass UI

    June 10, 2025: What Apple has tried to achieve with Liquid Glass is to bring together the optical quality of glass and the fluidity of liquid to emphasize transparency and lighting when using your devices. 

    WWDC first look: How Apple is improving its ecosystem

    June 9, 2025: While the new user interface design Apple execs highlighted at this year’s Worldwide Developers Conferencemight have been a bit of an eye-candy distraction, Apple’s enterprise users were not forgotten.

    Apple infuses AI into the Vision Pro

    June 8, 2025: Sluggish sales of Apple’s Vision Pro mixed reality headset haven’t dampened the company’s enthusiasm for advancing the device’s 3D computing experience, which now incorporates AI to deliver richer context and experiences.

    WWDC: Apple is about to unlock international business

    June 4, 2025: One of the more exciting pre-WWDC rumors is that Apple is preparing to make language problems go away by implementing focused artificial intelligence in Messages, which will apparently be able to translate incoming and outgoing messages on the fly. 
    #apple #wwdc #news #analysis
    Apple WWDC 2025: News and analysis
    Apple’s Worldwide Developers Conference 2025 saw a range of announcements that offered a glimpse into the future of Apple’s software design and artificial intelligencestrategy, highlighted by a new design language called  Liquid Glass and by Apple Intelligence news. Liquid Glass is designed to add translucency and dynamic movement to Apple’s user interface across iPhones, iPads, Macs, Apple Watches, and Apple TVs. The overhaul aims to make interactions with elements like buttons and sidebars adapt contextually. However, the real news of WWDC could be what we didn’t see.  Analysts had high expectations for Apple’s AI strategy, and while Apple Intelligence was talked about, many market watchers reported that it lacked the innovation that have come from Google’s and Microsoft’s generative AIrollouts. The question of whether Apple is playing catch-up lingered at WWDC 2025, and comments from Apple execs about delays to a significant AI overhaul for Siri were apparently interpreted as a setback by investors, leading to a negative reaction and drop in stock price. Follow this page for Computerworld‘s coverage of WWDC25. WWDC25 news and analysis Apple’s AI Revolution: Insights from WWDC June 13, 2025: At Apple’s big developer event, developers were served a feast of AI-related updates, including APIs that let them use Apple Intelligence in their apps and ChatGPT-augmentation from within Xcode. As a development environment, Apple has secured its future, with Macs forming the most computationally performant systems you can affordably purchase for the job. For developers, Apple’s tools get a lot better for AI June 12, 2025: Apple announced one important AI update at WWDC this week, the introduction of support for third-party large language models such as ChatGPT from within Xcode. It’s a big step that should benefit developers, accelerating app development. WWDC 25: What’s new for Apple and the enterprise? June 11, 2025: Beyond its new Liquid Glass UI and other major improvements across its operating systems, Apple introduced a hoard of changes, tweaks, and enhancements for IT admins at WWDC 2025. What we know so far about Apple’s Liquid Glass UI June 10, 2025: What Apple has tried to achieve with Liquid Glass is to bring together the optical quality of glass and the fluidity of liquid to emphasize transparency and lighting when using your devices.  WWDC first look: How Apple is improving its ecosystem June 9, 2025: While the new user interface design Apple execs highlighted at this year’s Worldwide Developers Conferencemight have been a bit of an eye-candy distraction, Apple’s enterprise users were not forgotten. Apple infuses AI into the Vision Pro June 8, 2025: Sluggish sales of Apple’s Vision Pro mixed reality headset haven’t dampened the company’s enthusiasm for advancing the device’s 3D computing experience, which now incorporates AI to deliver richer context and experiences. WWDC: Apple is about to unlock international business June 4, 2025: One of the more exciting pre-WWDC rumors is that Apple is preparing to make language problems go away by implementing focused artificial intelligence in Messages, which will apparently be able to translate incoming and outgoing messages on the fly.  #apple #wwdc #news #analysis
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    Apple WWDC 2025: News and analysis
    Apple’s Worldwide Developers Conference 2025 saw a range of announcements that offered a glimpse into the future of Apple’s software design and artificial intelligence (AI) strategy, highlighted by a new design language called  Liquid Glass and by Apple Intelligence news. Liquid Glass is designed to add translucency and dynamic movement to Apple’s user interface across iPhones, iPads, Macs, Apple Watches, and Apple TVs. The overhaul aims to make interactions with elements like buttons and sidebars adapt contextually. However, the real news of WWDC could be what we didn’t see.  Analysts had high expectations for Apple’s AI strategy, and while Apple Intelligence was talked about, many market watchers reported that it lacked the innovation that have come from Google’s and Microsoft’s generative AI (genAI) rollouts. The question of whether Apple is playing catch-up lingered at WWDC 2025, and comments from Apple execs about delays to a significant AI overhaul for Siri were apparently interpreted as a setback by investors, leading to a negative reaction and drop in stock price. Follow this page for Computerworld‘s coverage of WWDC25. WWDC25 news and analysis Apple’s AI Revolution: Insights from WWDC June 13, 2025: At Apple’s big developer event, developers were served a feast of AI-related updates, including APIs that let them use Apple Intelligence in their apps and ChatGPT-augmentation from within Xcode. As a development environment, Apple has secured its future, with Macs forming the most computationally performant systems you can affordably purchase for the job. For developers, Apple’s tools get a lot better for AI June 12, 2025: Apple announced one important AI update at WWDC this week, the introduction of support for third-party large language models (LLM) such as ChatGPT from within Xcode. It’s a big step that should benefit developers, accelerating app development. WWDC 25: What’s new for Apple and the enterprise? June 11, 2025: Beyond its new Liquid Glass UI and other major improvements across its operating systems, Apple introduced a hoard of changes, tweaks, and enhancements for IT admins at WWDC 2025. What we know so far about Apple’s Liquid Glass UI June 10, 2025: What Apple has tried to achieve with Liquid Glass is to bring together the optical quality of glass and the fluidity of liquid to emphasize transparency and lighting when using your devices.  WWDC first look: How Apple is improving its ecosystem June 9, 2025: While the new user interface design Apple execs highlighted at this year’s Worldwide Developers Conference (WWDC) might have been a bit of an eye-candy distraction, Apple’s enterprise users were not forgotten. Apple infuses AI into the Vision Pro June 8, 2025: Sluggish sales of Apple’s Vision Pro mixed reality headset haven’t dampened the company’s enthusiasm for advancing the device’s 3D computing experience, which now incorporates AI to deliver richer context and experiences. WWDC: Apple is about to unlock international business June 4, 2025: One of the more exciting pre-WWDC rumors is that Apple is preparing to make language problems go away by implementing focused artificial intelligence in Messages, which will apparently be able to translate incoming and outgoing messages on the fly. 
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  • IBM Plans Large-Scale Fault-Tolerant Quantum Computer by 2029

    IBM Plans Large-Scale Fault-Tolerant Quantum Computer by 2029

    By John P. Mello Jr.
    June 11, 2025 5:00 AM PT

    IBM unveiled its plan to build IBM Quantum Starling, shown in this rendering. Starling is expected to be the first large-scale, fault-tolerant quantum system.ADVERTISEMENT
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    IBM revealed Tuesday its roadmap for bringing a large-scale, fault-tolerant quantum computer, IBM Quantum Starling, online by 2029, which is significantly earlier than many technologists thought possible.
    The company predicts that when its new Starling computer is up and running, it will be capable of performing 20,000 times more operations than today’s quantum computers — a computational state so vast it would require the memory of more than a quindecillionof the world’s most powerful supercomputers to represent.
    “IBM is charting the next frontier in quantum computing,” Big Blue CEO Arvind Krishna said in a statement. “Our expertise across mathematics, physics, and engineering is paving the way for a large-scale, fault-tolerant quantum computer — one that will solve real-world challenges and unlock immense possibilities for business.”
    IBM’s plan to deliver a fault-tolerant quantum system by 2029 is ambitious but not implausible, especially given the rapid pace of its quantum roadmap and past milestones, observed Ensar Seker, CISO at SOCRadar, a threat intelligence company in Newark, Del.
    “They’ve consistently met or exceeded their qubit scaling goals, and their emphasis on modularity and error correction indicates they’re tackling the right challenges,” he told TechNewsWorld. “However, moving from thousands to millions of physical qubits with sufficient fidelity remains a steep climb.”
    A qubit is the fundamental unit of information in quantum computing, capable of representing a zero, a one, or both simultaneously due to quantum superposition. In practice, fault-tolerant quantum computers use clusters of physical qubits working together to form a logical qubit — a more stable unit designed to store quantum information and correct errors in real time.
    Realistic Roadmap
    Luke Yang, an equity analyst with Morningstar Research Services in Chicago, believes IBM’s roadmap is realistic. “The exact scale and error correction performance might still change between now and 2029, but overall, the goal is reasonable,” he told TechNewsWorld.
    “Given its reliability and professionalism, IBM’s bold claim should be taken seriously,” said Enrique Solano, co-CEO and co-founder of Kipu Quantum, a quantum algorithm company with offices in Berlin and Karlsruhe, Germany.
    “Of course, it may also fail, especially when considering the unpredictability of hardware complexities involved,” he told TechNewsWorld, “but companies like IBM exist for such challenges, and we should all be positively impressed by its current achievements and promised technological roadmap.”
    Tim Hollebeek, vice president of industry standards at DigiCert, a global digital security company, added: “IBM is a leader in this area, and not normally a company that hypes their news. This is a fast-moving industry, and success is certainly possible.”
    “IBM is attempting to do something that no one has ever done before and will almost certainly run into challenges,” he told TechNewsWorld, “but at this point, it is largely an engineering scaling exercise, not a research project.”
    “IBM has demonstrated consistent progress, has committed billion over five years to quantum computing, and the timeline is within the realm of technical feasibility,” noted John Young, COO of Quantum eMotion, a developer of quantum random number generator technology, in Saint-Laurent, Quebec, Canada.
    “That said,” he told TechNewsWorld, “fault-tolerant in a practical, industrial sense is a very high bar.”
    Solving the Quantum Error Correction Puzzle
    To make a quantum computer fault-tolerant, errors need to be corrected so large workloads can be run without faults. In a quantum computer, errors are reduced by clustering physical qubits to form logical qubits, which have lower error rates than the underlying physical qubits.
    “Error correction is a challenge,” Young said. “Logical qubits require thousands of physical qubits to function reliably. That’s a massive scaling issue.”
    IBM explained in its announcement that creating increasing numbers of logical qubits capable of executing quantum circuits with as few physical qubits as possible is critical to quantum computing at scale. Until today, a clear path to building such a fault-tolerant system without unrealistic engineering overhead has not been published.

    Alternative and previous gold-standard, error-correcting codes present fundamental engineering challenges, IBM continued. To scale, they would require an unfeasible number of physical qubits to create enough logical qubits to perform complex operations — necessitating impractical amounts of infrastructure and control electronics. This renders them unlikely to be implemented beyond small-scale experiments and devices.
    In two research papers released with its roadmap, IBM detailed how it will overcome the challenges of building the large-scale, fault-tolerant architecture needed for a quantum computer.
    One paper outlines the use of quantum low-density parity checkcodes to reduce physical qubit overhead. The other describes methods for decoding errors in real time using conventional computing.
    According to IBM, a practical fault-tolerant quantum architecture must:

    Suppress enough errors for useful algorithms to succeed
    Prepare and measure logical qubits during computation
    Apply universal instructions to logical qubits
    Decode measurements from logical qubits in real time and guide subsequent operations
    Scale modularly across hundreds or thousands of logical qubits
    Be efficient enough to run meaningful algorithms using realistic energy and infrastructure resources

    Aside from the technological challenges that quantum computer makers are facing, there may also be some market challenges. “Locating suitable use cases for quantum computers could be the biggest challenge,” Morningstar’s Yang maintained.
    “Only certain computing workloads, such as random circuit sampling, can fully unleash the computing power of quantum computers and show their advantage over the traditional supercomputers we have now,” he said. “However, workloads like RCS are not very commercially useful, and we believe commercial relevance is one of the key factors that determine the total market size for quantum computers.”
    Q-Day Approaching Faster Than Expected
    For years now, organizations have been told they need to prepare for “Q-Day” — the day a quantum computer will be able to crack all the encryption they use to keep their data secure. This IBM announcement suggests the window for action to protect data may be closing faster than many anticipated.
    “This absolutely adds urgency and credibility to the security expert guidance on post-quantum encryption being factored into their planning now,” said Dave Krauthamer, field CTO of QuSecure, maker of quantum-safe security solutions, in San Mateo, Calif.
    “IBM’s move to create a large-scale fault-tolerant quantum computer by 2029 is indicative of the timeline collapsing,” he told TechNewsWorld. “A fault-tolerant quantum computer of this magnitude could be well on the path to crack asymmetric ciphers sooner than anyone thinks.”

    “Security leaders need to take everything connected to post-quantum encryption as a serious measure and work it into their security plans now — not later,” he said.
    Roger Grimes, a defense evangelist with KnowBe4, a security awareness training provider in Clearwater, Fla., pointed out that IBM is just the latest in a surge of quantum companies announcing quickly forthcoming computational breakthroughs within a few years.
    “It leads to the question of whether the U.S. government’s original PQCpreparation date of 2030 is still a safe date,” he told TechNewsWorld.
    “It’s starting to feel a lot more risky for any company to wait until 2030 to be prepared against quantum attacks. It also flies in the face of the latest cybersecurity EOthat relaxed PQC preparation rules as compared to Biden’s last EO PQC standard order, which told U.S. agencies to transition to PQC ASAP.”
    “Most US companies are doing zero to prepare for Q-Day attacks,” he declared. “The latest executive order seems to tell U.S. agencies — and indirectly, all U.S. businesses — that they have more time to prepare. It’s going to cause even more agencies and businesses to be less prepared during a time when it seems multiple quantum computing companies are making significant progress.”
    “It definitely feels that something is going to give soon,” he said, “and if I were a betting man, and I am, I would bet that most U.S. companies are going to be unprepared for Q-Day on the day Q-Day becomes a reality.”

    John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John.

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    More in Emerging Tech
    #ibm #plans #largescale #faulttolerant #quantum
    IBM Plans Large-Scale Fault-Tolerant Quantum Computer by 2029
    IBM Plans Large-Scale Fault-Tolerant Quantum Computer by 2029 By John P. Mello Jr. June 11, 2025 5:00 AM PT IBM unveiled its plan to build IBM Quantum Starling, shown in this rendering. Starling is expected to be the first large-scale, fault-tolerant quantum system.ADVERTISEMENT Enterprise IT Lead Generation Services Fuel Your Pipeline. Close More Deals. Our full-service marketing programs deliver sales-ready leads. 100% Satisfaction Guarantee! Learn more. IBM revealed Tuesday its roadmap for bringing a large-scale, fault-tolerant quantum computer, IBM Quantum Starling, online by 2029, which is significantly earlier than many technologists thought possible. The company predicts that when its new Starling computer is up and running, it will be capable of performing 20,000 times more operations than today’s quantum computers — a computational state so vast it would require the memory of more than a quindecillionof the world’s most powerful supercomputers to represent. “IBM is charting the next frontier in quantum computing,” Big Blue CEO Arvind Krishna said in a statement. “Our expertise across mathematics, physics, and engineering is paving the way for a large-scale, fault-tolerant quantum computer — one that will solve real-world challenges and unlock immense possibilities for business.” IBM’s plan to deliver a fault-tolerant quantum system by 2029 is ambitious but not implausible, especially given the rapid pace of its quantum roadmap and past milestones, observed Ensar Seker, CISO at SOCRadar, a threat intelligence company in Newark, Del. “They’ve consistently met or exceeded their qubit scaling goals, and their emphasis on modularity and error correction indicates they’re tackling the right challenges,” he told TechNewsWorld. “However, moving from thousands to millions of physical qubits with sufficient fidelity remains a steep climb.” A qubit is the fundamental unit of information in quantum computing, capable of representing a zero, a one, or both simultaneously due to quantum superposition. In practice, fault-tolerant quantum computers use clusters of physical qubits working together to form a logical qubit — a more stable unit designed to store quantum information and correct errors in real time. Realistic Roadmap Luke Yang, an equity analyst with Morningstar Research Services in Chicago, believes IBM’s roadmap is realistic. “The exact scale and error correction performance might still change between now and 2029, but overall, the goal is reasonable,” he told TechNewsWorld. “Given its reliability and professionalism, IBM’s bold claim should be taken seriously,” said Enrique Solano, co-CEO and co-founder of Kipu Quantum, a quantum algorithm company with offices in Berlin and Karlsruhe, Germany. “Of course, it may also fail, especially when considering the unpredictability of hardware complexities involved,” he told TechNewsWorld, “but companies like IBM exist for such challenges, and we should all be positively impressed by its current achievements and promised technological roadmap.” Tim Hollebeek, vice president of industry standards at DigiCert, a global digital security company, added: “IBM is a leader in this area, and not normally a company that hypes their news. This is a fast-moving industry, and success is certainly possible.” “IBM is attempting to do something that no one has ever done before and will almost certainly run into challenges,” he told TechNewsWorld, “but at this point, it is largely an engineering scaling exercise, not a research project.” “IBM has demonstrated consistent progress, has committed billion over five years to quantum computing, and the timeline is within the realm of technical feasibility,” noted John Young, COO of Quantum eMotion, a developer of quantum random number generator technology, in Saint-Laurent, Quebec, Canada. “That said,” he told TechNewsWorld, “fault-tolerant in a practical, industrial sense is a very high bar.” Solving the Quantum Error Correction Puzzle To make a quantum computer fault-tolerant, errors need to be corrected so large workloads can be run without faults. In a quantum computer, errors are reduced by clustering physical qubits to form logical qubits, which have lower error rates than the underlying physical qubits. “Error correction is a challenge,” Young said. “Logical qubits require thousands of physical qubits to function reliably. That’s a massive scaling issue.” IBM explained in its announcement that creating increasing numbers of logical qubits capable of executing quantum circuits with as few physical qubits as possible is critical to quantum computing at scale. Until today, a clear path to building such a fault-tolerant system without unrealistic engineering overhead has not been published. Alternative and previous gold-standard, error-correcting codes present fundamental engineering challenges, IBM continued. To scale, they would require an unfeasible number of physical qubits to create enough logical qubits to perform complex operations — necessitating impractical amounts of infrastructure and control electronics. This renders them unlikely to be implemented beyond small-scale experiments and devices. In two research papers released with its roadmap, IBM detailed how it will overcome the challenges of building the large-scale, fault-tolerant architecture needed for a quantum computer. One paper outlines the use of quantum low-density parity checkcodes to reduce physical qubit overhead. The other describes methods for decoding errors in real time using conventional computing. According to IBM, a practical fault-tolerant quantum architecture must: Suppress enough errors for useful algorithms to succeed Prepare and measure logical qubits during computation Apply universal instructions to logical qubits Decode measurements from logical qubits in real time and guide subsequent operations Scale modularly across hundreds or thousands of logical qubits Be efficient enough to run meaningful algorithms using realistic energy and infrastructure resources Aside from the technological challenges that quantum computer makers are facing, there may also be some market challenges. “Locating suitable use cases for quantum computers could be the biggest challenge,” Morningstar’s Yang maintained. “Only certain computing workloads, such as random circuit sampling, can fully unleash the computing power of quantum computers and show their advantage over the traditional supercomputers we have now,” he said. “However, workloads like RCS are not very commercially useful, and we believe commercial relevance is one of the key factors that determine the total market size for quantum computers.” Q-Day Approaching Faster Than Expected For years now, organizations have been told they need to prepare for “Q-Day” — the day a quantum computer will be able to crack all the encryption they use to keep their data secure. This IBM announcement suggests the window for action to protect data may be closing faster than many anticipated. “This absolutely adds urgency and credibility to the security expert guidance on post-quantum encryption being factored into their planning now,” said Dave Krauthamer, field CTO of QuSecure, maker of quantum-safe security solutions, in San Mateo, Calif. “IBM’s move to create a large-scale fault-tolerant quantum computer by 2029 is indicative of the timeline collapsing,” he told TechNewsWorld. “A fault-tolerant quantum computer of this magnitude could be well on the path to crack asymmetric ciphers sooner than anyone thinks.” “Security leaders need to take everything connected to post-quantum encryption as a serious measure and work it into their security plans now — not later,” he said. Roger Grimes, a defense evangelist with KnowBe4, a security awareness training provider in Clearwater, Fla., pointed out that IBM is just the latest in a surge of quantum companies announcing quickly forthcoming computational breakthroughs within a few years. “It leads to the question of whether the U.S. government’s original PQCpreparation date of 2030 is still a safe date,” he told TechNewsWorld. “It’s starting to feel a lot more risky for any company to wait until 2030 to be prepared against quantum attacks. It also flies in the face of the latest cybersecurity EOthat relaxed PQC preparation rules as compared to Biden’s last EO PQC standard order, which told U.S. agencies to transition to PQC ASAP.” “Most US companies are doing zero to prepare for Q-Day attacks,” he declared. “The latest executive order seems to tell U.S. agencies — and indirectly, all U.S. businesses — that they have more time to prepare. It’s going to cause even more agencies and businesses to be less prepared during a time when it seems multiple quantum computing companies are making significant progress.” “It definitely feels that something is going to give soon,” he said, “and if I were a betting man, and I am, I would bet that most U.S. companies are going to be unprepared for Q-Day on the day Q-Day becomes a reality.” John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John. Leave a Comment Click here to cancel reply. Please sign in to post or reply to a comment. New users create a free account. Related Stories More by John P. Mello Jr. view all More in Emerging Tech #ibm #plans #largescale #faulttolerant #quantum
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    IBM Plans Large-Scale Fault-Tolerant Quantum Computer by 2029
    IBM Plans Large-Scale Fault-Tolerant Quantum Computer by 2029 By John P. Mello Jr. June 11, 2025 5:00 AM PT IBM unveiled its plan to build IBM Quantum Starling, shown in this rendering. Starling is expected to be the first large-scale, fault-tolerant quantum system. (Image Credit: IBM) ADVERTISEMENT Enterprise IT Lead Generation Services Fuel Your Pipeline. Close More Deals. Our full-service marketing programs deliver sales-ready leads. 100% Satisfaction Guarantee! Learn more. IBM revealed Tuesday its roadmap for bringing a large-scale, fault-tolerant quantum computer, IBM Quantum Starling, online by 2029, which is significantly earlier than many technologists thought possible. The company predicts that when its new Starling computer is up and running, it will be capable of performing 20,000 times more operations than today’s quantum computers — a computational state so vast it would require the memory of more than a quindecillion (10⁴⁸) of the world’s most powerful supercomputers to represent. “IBM is charting the next frontier in quantum computing,” Big Blue CEO Arvind Krishna said in a statement. “Our expertise across mathematics, physics, and engineering is paving the way for a large-scale, fault-tolerant quantum computer — one that will solve real-world challenges and unlock immense possibilities for business.” IBM’s plan to deliver a fault-tolerant quantum system by 2029 is ambitious but not implausible, especially given the rapid pace of its quantum roadmap and past milestones, observed Ensar Seker, CISO at SOCRadar, a threat intelligence company in Newark, Del. “They’ve consistently met or exceeded their qubit scaling goals, and their emphasis on modularity and error correction indicates they’re tackling the right challenges,” he told TechNewsWorld. “However, moving from thousands to millions of physical qubits with sufficient fidelity remains a steep climb.” A qubit is the fundamental unit of information in quantum computing, capable of representing a zero, a one, or both simultaneously due to quantum superposition. In practice, fault-tolerant quantum computers use clusters of physical qubits working together to form a logical qubit — a more stable unit designed to store quantum information and correct errors in real time. Realistic Roadmap Luke Yang, an equity analyst with Morningstar Research Services in Chicago, believes IBM’s roadmap is realistic. “The exact scale and error correction performance might still change between now and 2029, but overall, the goal is reasonable,” he told TechNewsWorld. “Given its reliability and professionalism, IBM’s bold claim should be taken seriously,” said Enrique Solano, co-CEO and co-founder of Kipu Quantum, a quantum algorithm company with offices in Berlin and Karlsruhe, Germany. “Of course, it may also fail, especially when considering the unpredictability of hardware complexities involved,” he told TechNewsWorld, “but companies like IBM exist for such challenges, and we should all be positively impressed by its current achievements and promised technological roadmap.” Tim Hollebeek, vice president of industry standards at DigiCert, a global digital security company, added: “IBM is a leader in this area, and not normally a company that hypes their news. This is a fast-moving industry, and success is certainly possible.” “IBM is attempting to do something that no one has ever done before and will almost certainly run into challenges,” he told TechNewsWorld, “but at this point, it is largely an engineering scaling exercise, not a research project.” “IBM has demonstrated consistent progress, has committed $30 billion over five years to quantum computing, and the timeline is within the realm of technical feasibility,” noted John Young, COO of Quantum eMotion, a developer of quantum random number generator technology, in Saint-Laurent, Quebec, Canada. “That said,” he told TechNewsWorld, “fault-tolerant in a practical, industrial sense is a very high bar.” Solving the Quantum Error Correction Puzzle To make a quantum computer fault-tolerant, errors need to be corrected so large workloads can be run without faults. In a quantum computer, errors are reduced by clustering physical qubits to form logical qubits, which have lower error rates than the underlying physical qubits. “Error correction is a challenge,” Young said. “Logical qubits require thousands of physical qubits to function reliably. That’s a massive scaling issue.” IBM explained in its announcement that creating increasing numbers of logical qubits capable of executing quantum circuits with as few physical qubits as possible is critical to quantum computing at scale. Until today, a clear path to building such a fault-tolerant system without unrealistic engineering overhead has not been published. Alternative and previous gold-standard, error-correcting codes present fundamental engineering challenges, IBM continued. To scale, they would require an unfeasible number of physical qubits to create enough logical qubits to perform complex operations — necessitating impractical amounts of infrastructure and control electronics. This renders them unlikely to be implemented beyond small-scale experiments and devices. In two research papers released with its roadmap, IBM detailed how it will overcome the challenges of building the large-scale, fault-tolerant architecture needed for a quantum computer. One paper outlines the use of quantum low-density parity check (qLDPC) codes to reduce physical qubit overhead. The other describes methods for decoding errors in real time using conventional computing. According to IBM, a practical fault-tolerant quantum architecture must: Suppress enough errors for useful algorithms to succeed Prepare and measure logical qubits during computation Apply universal instructions to logical qubits Decode measurements from logical qubits in real time and guide subsequent operations Scale modularly across hundreds or thousands of logical qubits Be efficient enough to run meaningful algorithms using realistic energy and infrastructure resources Aside from the technological challenges that quantum computer makers are facing, there may also be some market challenges. “Locating suitable use cases for quantum computers could be the biggest challenge,” Morningstar’s Yang maintained. “Only certain computing workloads, such as random circuit sampling [RCS], can fully unleash the computing power of quantum computers and show their advantage over the traditional supercomputers we have now,” he said. “However, workloads like RCS are not very commercially useful, and we believe commercial relevance is one of the key factors that determine the total market size for quantum computers.” Q-Day Approaching Faster Than Expected For years now, organizations have been told they need to prepare for “Q-Day” — the day a quantum computer will be able to crack all the encryption they use to keep their data secure. This IBM announcement suggests the window for action to protect data may be closing faster than many anticipated. “This absolutely adds urgency and credibility to the security expert guidance on post-quantum encryption being factored into their planning now,” said Dave Krauthamer, field CTO of QuSecure, maker of quantum-safe security solutions, in San Mateo, Calif. “IBM’s move to create a large-scale fault-tolerant quantum computer by 2029 is indicative of the timeline collapsing,” he told TechNewsWorld. “A fault-tolerant quantum computer of this magnitude could be well on the path to crack asymmetric ciphers sooner than anyone thinks.” “Security leaders need to take everything connected to post-quantum encryption as a serious measure and work it into their security plans now — not later,” he said. Roger Grimes, a defense evangelist with KnowBe4, a security awareness training provider in Clearwater, Fla., pointed out that IBM is just the latest in a surge of quantum companies announcing quickly forthcoming computational breakthroughs within a few years. “It leads to the question of whether the U.S. government’s original PQC [post-quantum cryptography] preparation date of 2030 is still a safe date,” he told TechNewsWorld. “It’s starting to feel a lot more risky for any company to wait until 2030 to be prepared against quantum attacks. It also flies in the face of the latest cybersecurity EO [Executive Order] that relaxed PQC preparation rules as compared to Biden’s last EO PQC standard order, which told U.S. agencies to transition to PQC ASAP.” “Most US companies are doing zero to prepare for Q-Day attacks,” he declared. “The latest executive order seems to tell U.S. agencies — and indirectly, all U.S. businesses — that they have more time to prepare. It’s going to cause even more agencies and businesses to be less prepared during a time when it seems multiple quantum computing companies are making significant progress.” “It definitely feels that something is going to give soon,” he said, “and if I were a betting man, and I am, I would bet that most U.S. companies are going to be unprepared for Q-Day on the day Q-Day becomes a reality.” John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John. Leave a Comment Click here to cancel reply. Please sign in to post or reply to a comment. New users create a free account. Related Stories More by John P. Mello Jr. view all More in Emerging Tech
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  • A shortage of high-voltage power cables could stall the clean energy transition

    In a nutshell: As nations set ever more ambitious targets for renewable energy and electrification, the humble high-voltage cable has emerged as a linchpin – and a potential chokepoint – in the race to decarbonize the global economy. A Bloomberg interview with Claes Westerlind, CEO of NKT, a leading cable manufacturer based in Denmark, explains why.
    A global surge in demand for high-voltage electricity cables is threatening to stall the clean energy revolution, as the world's ability to build new wind farms, solar plants, and cross-border power links increasingly hinges on a supply chain bottleneck few outside the industry have considered. At the center of this challenge is the complex, capital-intensive process of manufacturing the giant cables that transport electricity across hundreds of miles, both over land and under the sea.
    Despite soaring demand, cable manufacturers remain cautious about expanding capacity, raising questions about whether the pace of electrification can keep up with climate ambitions, geopolitical tensions, and the practical realities of industrial investment.
    High-voltage cables are the arteries of modern power grids, carrying electrons from remote wind farms or hydroelectric dams to the cities and industries that need them. Unlike the thin wires that run through a home's walls, these cables are engineering marvels – sometimes as thick as a person's torso, armored to withstand the crushing pressure of the ocean floor, and designed to last for decades under extreme electrical and environmental stress.

    "If you look at the very high voltage direct current cable, able to carry roughly two gigawatts through two pairs of cables – that means that the equivalent of one nuclear power reactor is flowing through one cable," Westerlind told Bloomberg.
    The process of making these cables is as specialized as it is demanding. At the core is a conductor, typically made of copper or aluminum, twisted together like a rope for flexibility and strength. Around this, manufacturers apply multiple layers of insulation in towering vertical factories to ensure the cable remains perfectly round and can safely contain the immense voltages involved. Any impurity in the insulation, even something as small as an eyelash, can cause catastrophic failure, potentially knocking out power to entire cities.
    // Related Stories

    As the world rushes to harness new sources of renewable energy, the demand for high-voltage direct currentcables has skyrocketed. HVDC technology, initially pioneered by NKT in the 1950s, has become the backbone of long-distance power transmission, particularly for offshore wind farms and intercontinental links. In recent years, approximately 80 to 90 percent of new large-scale cable projects have utilized HVDC, reflecting its efficiency in transmitting electricity over vast distances with minimal losses.

    But this surge in demand has led to a critical bottleneck. Factories that produce these cables are booked out for years, Westerlind reports, and every project requires custom engineering to match the power needs, geography, and environmental conditions of its route. According to the International Energy Agency, meeting global clean energy goals will require building the equivalent of 80 million kilometersof new grid infrastructure by 2040 – essentially doubling what has been constructed over the past century, but in just 15 years.
    Despite the clear need, cable makers have been slow to add capacity due to reasons that are as much economic and political as technical. Building a new cable factory can cost upwards of a billion euros, and manufacturers are wary of making such investments without long-term commitments from utilities or governments. "For a company like us to do investments in the realm of €1 or 2 billion, it's a massive commitment... but it's also a massive amount of demand that is needed for this investment to actually make financial sense over the next not five years, not 10 years, but over the next 20 to 30 years," Westerlind said. The industry still bears scars from a decade ago, when anticipated demand failed to materialize and expensive new facilities sat underused.
    Some governments and transmission system operators are trying to break the logjam by making "anticipatory investments" – committing to buy cable capacity even before specific projects are finalized. This approach, backed by regulators, gives manufacturers the confidence to expand, but it remains the exception rather than the rule.
    Meanwhile, the industry's structure itself creates barriers to rapid expansion, according to Westerlind. The expertise, technology, and infrastructure required to make high-voltage cables are concentrated in a handful of companies, creating what analysts describe as a "deep moat" that is difficult for new entrants to cross.
    Geopolitical tensions add another layer of complexity. China has built more HVDC lines than any other country, although Western manufacturers, such as NKT, maintain a technical edge in the most advanced cable systems. Still, there is growing concern in Europe and the US about becoming dependent on foreign suppliers for such critical infrastructure, especially in light of recent global conflicts and trade disputes. "Strategic autonomy is very important when it comes to the core parts and the fundamental parts of your society, where the grid backbone is one," Westerlind noted.
    The stakes are high. Without a rapid and coordinated push to expand cable manufacturing, the world's clean energy transition could be slowed not by a lack of wind or sun but by a shortage of the cables needed to connect them to the grid. As Westerlind put it, "We all know it has to be done... These are large investments. They are very expensive investments. So also the governments have to have a part in enabling these anticipatory investments, and making it possible for the TSOs to actually carry forward with them."
    #shortage #highvoltage #power #cables #could
    A shortage of high-voltage power cables could stall the clean energy transition
    In a nutshell: As nations set ever more ambitious targets for renewable energy and electrification, the humble high-voltage cable has emerged as a linchpin – and a potential chokepoint – in the race to decarbonize the global economy. A Bloomberg interview with Claes Westerlind, CEO of NKT, a leading cable manufacturer based in Denmark, explains why. A global surge in demand for high-voltage electricity cables is threatening to stall the clean energy revolution, as the world's ability to build new wind farms, solar plants, and cross-border power links increasingly hinges on a supply chain bottleneck few outside the industry have considered. At the center of this challenge is the complex, capital-intensive process of manufacturing the giant cables that transport electricity across hundreds of miles, both over land and under the sea. Despite soaring demand, cable manufacturers remain cautious about expanding capacity, raising questions about whether the pace of electrification can keep up with climate ambitions, geopolitical tensions, and the practical realities of industrial investment. High-voltage cables are the arteries of modern power grids, carrying electrons from remote wind farms or hydroelectric dams to the cities and industries that need them. Unlike the thin wires that run through a home's walls, these cables are engineering marvels – sometimes as thick as a person's torso, armored to withstand the crushing pressure of the ocean floor, and designed to last for decades under extreme electrical and environmental stress. "If you look at the very high voltage direct current cable, able to carry roughly two gigawatts through two pairs of cables – that means that the equivalent of one nuclear power reactor is flowing through one cable," Westerlind told Bloomberg. The process of making these cables is as specialized as it is demanding. At the core is a conductor, typically made of copper or aluminum, twisted together like a rope for flexibility and strength. Around this, manufacturers apply multiple layers of insulation in towering vertical factories to ensure the cable remains perfectly round and can safely contain the immense voltages involved. Any impurity in the insulation, even something as small as an eyelash, can cause catastrophic failure, potentially knocking out power to entire cities. // Related Stories As the world rushes to harness new sources of renewable energy, the demand for high-voltage direct currentcables has skyrocketed. HVDC technology, initially pioneered by NKT in the 1950s, has become the backbone of long-distance power transmission, particularly for offshore wind farms and intercontinental links. In recent years, approximately 80 to 90 percent of new large-scale cable projects have utilized HVDC, reflecting its efficiency in transmitting electricity over vast distances with minimal losses. But this surge in demand has led to a critical bottleneck. Factories that produce these cables are booked out for years, Westerlind reports, and every project requires custom engineering to match the power needs, geography, and environmental conditions of its route. According to the International Energy Agency, meeting global clean energy goals will require building the equivalent of 80 million kilometersof new grid infrastructure by 2040 – essentially doubling what has been constructed over the past century, but in just 15 years. Despite the clear need, cable makers have been slow to add capacity due to reasons that are as much economic and political as technical. Building a new cable factory can cost upwards of a billion euros, and manufacturers are wary of making such investments without long-term commitments from utilities or governments. "For a company like us to do investments in the realm of €1 or 2 billion, it's a massive commitment... but it's also a massive amount of demand that is needed for this investment to actually make financial sense over the next not five years, not 10 years, but over the next 20 to 30 years," Westerlind said. The industry still bears scars from a decade ago, when anticipated demand failed to materialize and expensive new facilities sat underused. Some governments and transmission system operators are trying to break the logjam by making "anticipatory investments" – committing to buy cable capacity even before specific projects are finalized. This approach, backed by regulators, gives manufacturers the confidence to expand, but it remains the exception rather than the rule. Meanwhile, the industry's structure itself creates barriers to rapid expansion, according to Westerlind. The expertise, technology, and infrastructure required to make high-voltage cables are concentrated in a handful of companies, creating what analysts describe as a "deep moat" that is difficult for new entrants to cross. Geopolitical tensions add another layer of complexity. China has built more HVDC lines than any other country, although Western manufacturers, such as NKT, maintain a technical edge in the most advanced cable systems. Still, there is growing concern in Europe and the US about becoming dependent on foreign suppliers for such critical infrastructure, especially in light of recent global conflicts and trade disputes. "Strategic autonomy is very important when it comes to the core parts and the fundamental parts of your society, where the grid backbone is one," Westerlind noted. The stakes are high. Without a rapid and coordinated push to expand cable manufacturing, the world's clean energy transition could be slowed not by a lack of wind or sun but by a shortage of the cables needed to connect them to the grid. As Westerlind put it, "We all know it has to be done... These are large investments. They are very expensive investments. So also the governments have to have a part in enabling these anticipatory investments, and making it possible for the TSOs to actually carry forward with them." #shortage #highvoltage #power #cables #could
    WWW.TECHSPOT.COM
    A shortage of high-voltage power cables could stall the clean energy transition
    In a nutshell: As nations set ever more ambitious targets for renewable energy and electrification, the humble high-voltage cable has emerged as a linchpin – and a potential chokepoint – in the race to decarbonize the global economy. A Bloomberg interview with Claes Westerlind, CEO of NKT, a leading cable manufacturer based in Denmark, explains why. A global surge in demand for high-voltage electricity cables is threatening to stall the clean energy revolution, as the world's ability to build new wind farms, solar plants, and cross-border power links increasingly hinges on a supply chain bottleneck few outside the industry have considered. At the center of this challenge is the complex, capital-intensive process of manufacturing the giant cables that transport electricity across hundreds of miles, both over land and under the sea. Despite soaring demand, cable manufacturers remain cautious about expanding capacity, raising questions about whether the pace of electrification can keep up with climate ambitions, geopolitical tensions, and the practical realities of industrial investment. High-voltage cables are the arteries of modern power grids, carrying electrons from remote wind farms or hydroelectric dams to the cities and industries that need them. Unlike the thin wires that run through a home's walls, these cables are engineering marvels – sometimes as thick as a person's torso, armored to withstand the crushing pressure of the ocean floor, and designed to last for decades under extreme electrical and environmental stress. "If you look at the very high voltage direct current cable, able to carry roughly two gigawatts through two pairs of cables – that means that the equivalent of one nuclear power reactor is flowing through one cable," Westerlind told Bloomberg. The process of making these cables is as specialized as it is demanding. At the core is a conductor, typically made of copper or aluminum, twisted together like a rope for flexibility and strength. Around this, manufacturers apply multiple layers of insulation in towering vertical factories to ensure the cable remains perfectly round and can safely contain the immense voltages involved. Any impurity in the insulation, even something as small as an eyelash, can cause catastrophic failure, potentially knocking out power to entire cities. // Related Stories As the world rushes to harness new sources of renewable energy, the demand for high-voltage direct current (HVDC) cables has skyrocketed. HVDC technology, initially pioneered by NKT in the 1950s, has become the backbone of long-distance power transmission, particularly for offshore wind farms and intercontinental links. In recent years, approximately 80 to 90 percent of new large-scale cable projects have utilized HVDC, reflecting its efficiency in transmitting electricity over vast distances with minimal losses. But this surge in demand has led to a critical bottleneck. Factories that produce these cables are booked out for years, Westerlind reports, and every project requires custom engineering to match the power needs, geography, and environmental conditions of its route. According to the International Energy Agency, meeting global clean energy goals will require building the equivalent of 80 million kilometers (around 49.7 million miles) of new grid infrastructure by 2040 – essentially doubling what has been constructed over the past century, but in just 15 years. Despite the clear need, cable makers have been slow to add capacity due to reasons that are as much economic and political as technical. Building a new cable factory can cost upwards of a billion euros, and manufacturers are wary of making such investments without long-term commitments from utilities or governments. "For a company like us to do investments in the realm of €1 or 2 billion, it's a massive commitment... but it's also a massive amount of demand that is needed for this investment to actually make financial sense over the next not five years, not 10 years, but over the next 20 to 30 years," Westerlind said. The industry still bears scars from a decade ago, when anticipated demand failed to materialize and expensive new facilities sat underused. Some governments and transmission system operators are trying to break the logjam by making "anticipatory investments" – committing to buy cable capacity even before specific projects are finalized. This approach, backed by regulators, gives manufacturers the confidence to expand, but it remains the exception rather than the rule. Meanwhile, the industry's structure itself creates barriers to rapid expansion, according to Westerlind. The expertise, technology, and infrastructure required to make high-voltage cables are concentrated in a handful of companies, creating what analysts describe as a "deep moat" that is difficult for new entrants to cross. Geopolitical tensions add another layer of complexity. China has built more HVDC lines than any other country, although Western manufacturers, such as NKT, maintain a technical edge in the most advanced cable systems. Still, there is growing concern in Europe and the US about becoming dependent on foreign suppliers for such critical infrastructure, especially in light of recent global conflicts and trade disputes. "Strategic autonomy is very important when it comes to the core parts and the fundamental parts of your society, where the grid backbone is one," Westerlind noted. The stakes are high. Without a rapid and coordinated push to expand cable manufacturing, the world's clean energy transition could be slowed not by a lack of wind or sun but by a shortage of the cables needed to connect them to the grid. As Westerlind put it, "We all know it has to be done... These are large investments. They are very expensive investments. So also the governments have to have a part in enabling these anticipatory investments, and making it possible for the TSOs to actually carry forward with them."
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  • Five Climate Issues to Watch When Trump Goes to Canada

    June 13, 20255 min readFive Climate Issues to Watch When Trump Goes to CanadaPresident Trump will attend the G7 summit on Sunday in a nation he threatened to annex. He will also be an outlier on climate issuesBy Sara Schonhardt & E&E News Saul Loeb/AFP via Getty ImagesCLIMATEWIRE | The world’s richest nations are gathering Sunday in the Canadian Rockies for a summit that could reveal whether President Donald Trump's policies are shaking global climate efforts.The Group of Seven meeting comes at a challenging time for international climate policy. Trump’s tariff seesaw has cast a shade over the global economy, and his domestic policies have threatened billions of dollars in funding for clean energy programs. Those pressures are colliding with record-breaking temperatures worldwide and explosive demand for energy, driven by power-hungry data centers linked to artificial intelligence technologies.On top of that, Trump has threatened to annex the host of the meeting — Canada — and members of his Cabinet have taken swipes at Europe’s use of renewable energy. Rather than being aligned with much of the world's assertion that fossil fuels should be tempered, Trump embraces the opposite position — drill for more oil and gas and keep burning coal, while repealing environmental regulations on the biggest sources of U.S. carbon pollution.On supporting science journalismIf you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.Those moves illustrate his rejection of climate science and underscore his outlying positions on global warming in the G7.Here are five things to know about the summit.Who will be there?The group comprises Canada, France, Germany, Italy, Japan, the United Kingdom and the United States — plus the European Union. Together they account for more than 40 percent of gross domestic product globally and around a quarter of all energy-related carbon dioxide pollution, according to the International Energy Agency. The U.S. is the only one among them that is not trying to hit a carbon reduction goal.Some emerging economies have also been invited, including Mexico, India, South Africa and Brazil, the host of this year’s COP30 climate talks in November.Ahead of the meeting, the office of Canada's prime minister, Mark Carney, said he and Brazilian President Luiz Inácio Lula da Silva agreed to strengthen cooperation on energy security and critical minerals. White House press secretary Karoline Leavitt said Trump would be having "quite a few" bilateral meetings but that his schedule was in flux.The G7 first came together 50 years ago following the Arab oil embargo. Since then, its seven members have all joined the United Nations Framework Convention on Climate Change and the Paris Agreement. The U.S. is the only nation in the group that has withdrawn from the Paris Agreement, which counts almost every country in the world as a signatory.What’s on the table?Among Canada’s top priorities as host are strengthening energy security and fortifying critical mineral supply chains. Carney would also like to see some agreement on joint wildfire action.Expanding supply chains for critical minerals — and competing more aggressively with China over those resources — could be areas of common ground among the leaders. Climate change is expected to remain divisive. Looming over the discussions will be tariffs — which Trump has applied across the board — because they will have an impact on the clean energy transition.“I think probably the majority of the conversation will be less about climate per se, or certainly not using climate action as the frame, but more about energy transition and infrastructure as a way of kind of bridging the known gaps between most of the G7 and where the United States is right now,” said Dan Baer, director of the Europe program at the Carnegie Endowment for International Peace.What are the possible outcomes?The leaders could issue a communique at the end of their meeting, but those statements are based on consensus, something that would be difficult to reach without other G7 countries capitulating to Trump. Bloomberg reported Wednesday that nations won’t try to reach a joint agreement, in part because bridging gaps on climate change could be too hard.Instead, Carney could issue a chair’s summary or joint statements based on certain issues.The question is how far Canada will go to accommodate the U.S., which could try to roll back past statements on advancing clean energy, said Andrew Light, former assistant secretary of Energy for international affairs, who led ministerial-level negotiations for the G7.“They might say, rather than watering everything down that we accomplished in the last four years, we just do a chair's statement, which summarizes the debate,” Light said. “That will show you that you didn't get consensus, but you also didn't get capitulation.”What to watch forIf there is a communique, Light says he’ll be looking for whether there is tougher language on China and any signal of support for science and the Paris Agreement. During his first term, Trump refused to support the Paris accord in the G7 and G20 declarations.The statement could avoid climate and energy issues entirely. But if it backtracks on those issues, that could be a sign that countries made a deal by trading climate-related language for something else, Light said.Baer of Carnegie said a statement framed around energy security and infrastructure could be seen as a “pragmatic adaptation” to the U.S. administration, rather than an indication that other leaders aren’t concerned about climate change.Climate activists have lower expectations.“Realistically, we can expect very little, if any, mention of climate change,” said Caroline Brouillette, executive director of Climate Action Network Canada.“The message we should be expecting from those leaders is that climate action remains a priority for the rest of the G7 … whether it's on the transition away from fossil fuels and supporting developing countries through climate finance,” she said. “Especially now that the U.S. is stepping back, we need countries, including Canada, to be stepping up.”Best- and worst-case scenariosThe challenge for Carney will be preventing any further rupture with Trump, analysts said.In 2018, Trump made a hasty exit from the G7 summit, also in Canada that year, due largely to trade disagreements. He retracted his support for the joint statement.“The best,realistic case outcome is that things don't get worse,” said Baer.The worst-case scenario? Some kind of “highly personalized spat” that could add to the sense of disorder, he added.“I think the G7 on the one hand has the potential to be more important than ever, as fewer and fewer platforms for international cooperation seem to be able to take action,” Baer said. “So it's both very important and also I don't have super-high expectations.”Reprinted from E&E News with permission from POLITICO, LLC. Copyright 2025. E&E News provides essential news for energy and environment professionals.
    #five #climate #issues #watch #when
    Five Climate Issues to Watch When Trump Goes to Canada
    June 13, 20255 min readFive Climate Issues to Watch When Trump Goes to CanadaPresident Trump will attend the G7 summit on Sunday in a nation he threatened to annex. He will also be an outlier on climate issuesBy Sara Schonhardt & E&E News Saul Loeb/AFP via Getty ImagesCLIMATEWIRE | The world’s richest nations are gathering Sunday in the Canadian Rockies for a summit that could reveal whether President Donald Trump's policies are shaking global climate efforts.The Group of Seven meeting comes at a challenging time for international climate policy. Trump’s tariff seesaw has cast a shade over the global economy, and his domestic policies have threatened billions of dollars in funding for clean energy programs. Those pressures are colliding with record-breaking temperatures worldwide and explosive demand for energy, driven by power-hungry data centers linked to artificial intelligence technologies.On top of that, Trump has threatened to annex the host of the meeting — Canada — and members of his Cabinet have taken swipes at Europe’s use of renewable energy. Rather than being aligned with much of the world's assertion that fossil fuels should be tempered, Trump embraces the opposite position — drill for more oil and gas and keep burning coal, while repealing environmental regulations on the biggest sources of U.S. carbon pollution.On supporting science journalismIf you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.Those moves illustrate his rejection of climate science and underscore his outlying positions on global warming in the G7.Here are five things to know about the summit.Who will be there?The group comprises Canada, France, Germany, Italy, Japan, the United Kingdom and the United States — plus the European Union. Together they account for more than 40 percent of gross domestic product globally and around a quarter of all energy-related carbon dioxide pollution, according to the International Energy Agency. The U.S. is the only one among them that is not trying to hit a carbon reduction goal.Some emerging economies have also been invited, including Mexico, India, South Africa and Brazil, the host of this year’s COP30 climate talks in November.Ahead of the meeting, the office of Canada's prime minister, Mark Carney, said he and Brazilian President Luiz Inácio Lula da Silva agreed to strengthen cooperation on energy security and critical minerals. White House press secretary Karoline Leavitt said Trump would be having "quite a few" bilateral meetings but that his schedule was in flux.The G7 first came together 50 years ago following the Arab oil embargo. Since then, its seven members have all joined the United Nations Framework Convention on Climate Change and the Paris Agreement. The U.S. is the only nation in the group that has withdrawn from the Paris Agreement, which counts almost every country in the world as a signatory.What’s on the table?Among Canada’s top priorities as host are strengthening energy security and fortifying critical mineral supply chains. Carney would also like to see some agreement on joint wildfire action.Expanding supply chains for critical minerals — and competing more aggressively with China over those resources — could be areas of common ground among the leaders. Climate change is expected to remain divisive. Looming over the discussions will be tariffs — which Trump has applied across the board — because they will have an impact on the clean energy transition.“I think probably the majority of the conversation will be less about climate per se, or certainly not using climate action as the frame, but more about energy transition and infrastructure as a way of kind of bridging the known gaps between most of the G7 and where the United States is right now,” said Dan Baer, director of the Europe program at the Carnegie Endowment for International Peace.What are the possible outcomes?The leaders could issue a communique at the end of their meeting, but those statements are based on consensus, something that would be difficult to reach without other G7 countries capitulating to Trump. Bloomberg reported Wednesday that nations won’t try to reach a joint agreement, in part because bridging gaps on climate change could be too hard.Instead, Carney could issue a chair’s summary or joint statements based on certain issues.The question is how far Canada will go to accommodate the U.S., which could try to roll back past statements on advancing clean energy, said Andrew Light, former assistant secretary of Energy for international affairs, who led ministerial-level negotiations for the G7.“They might say, rather than watering everything down that we accomplished in the last four years, we just do a chair's statement, which summarizes the debate,” Light said. “That will show you that you didn't get consensus, but you also didn't get capitulation.”What to watch forIf there is a communique, Light says he’ll be looking for whether there is tougher language on China and any signal of support for science and the Paris Agreement. During his first term, Trump refused to support the Paris accord in the G7 and G20 declarations.The statement could avoid climate and energy issues entirely. But if it backtracks on those issues, that could be a sign that countries made a deal by trading climate-related language for something else, Light said.Baer of Carnegie said a statement framed around energy security and infrastructure could be seen as a “pragmatic adaptation” to the U.S. administration, rather than an indication that other leaders aren’t concerned about climate change.Climate activists have lower expectations.“Realistically, we can expect very little, if any, mention of climate change,” said Caroline Brouillette, executive director of Climate Action Network Canada.“The message we should be expecting from those leaders is that climate action remains a priority for the rest of the G7 … whether it's on the transition away from fossil fuels and supporting developing countries through climate finance,” she said. “Especially now that the U.S. is stepping back, we need countries, including Canada, to be stepping up.”Best- and worst-case scenariosThe challenge for Carney will be preventing any further rupture with Trump, analysts said.In 2018, Trump made a hasty exit from the G7 summit, also in Canada that year, due largely to trade disagreements. He retracted his support for the joint statement.“The best,realistic case outcome is that things don't get worse,” said Baer.The worst-case scenario? Some kind of “highly personalized spat” that could add to the sense of disorder, he added.“I think the G7 on the one hand has the potential to be more important than ever, as fewer and fewer platforms for international cooperation seem to be able to take action,” Baer said. “So it's both very important and also I don't have super-high expectations.”Reprinted from E&E News with permission from POLITICO, LLC. Copyright 2025. E&E News provides essential news for energy and environment professionals. #five #climate #issues #watch #when
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    Five Climate Issues to Watch When Trump Goes to Canada
    June 13, 20255 min readFive Climate Issues to Watch When Trump Goes to CanadaPresident Trump will attend the G7 summit on Sunday in a nation he threatened to annex. He will also be an outlier on climate issuesBy Sara Schonhardt & E&E News Saul Loeb/AFP via Getty ImagesCLIMATEWIRE | The world’s richest nations are gathering Sunday in the Canadian Rockies for a summit that could reveal whether President Donald Trump's policies are shaking global climate efforts.The Group of Seven meeting comes at a challenging time for international climate policy. Trump’s tariff seesaw has cast a shade over the global economy, and his domestic policies have threatened billions of dollars in funding for clean energy programs. Those pressures are colliding with record-breaking temperatures worldwide and explosive demand for energy, driven by power-hungry data centers linked to artificial intelligence technologies.On top of that, Trump has threatened to annex the host of the meeting — Canada — and members of his Cabinet have taken swipes at Europe’s use of renewable energy. Rather than being aligned with much of the world's assertion that fossil fuels should be tempered, Trump embraces the opposite position — drill for more oil and gas and keep burning coal, while repealing environmental regulations on the biggest sources of U.S. carbon pollution.On supporting science journalismIf you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.Those moves illustrate his rejection of climate science and underscore his outlying positions on global warming in the G7.Here are five things to know about the summit.Who will be there?The group comprises Canada, France, Germany, Italy, Japan, the United Kingdom and the United States — plus the European Union. Together they account for more than 40 percent of gross domestic product globally and around a quarter of all energy-related carbon dioxide pollution, according to the International Energy Agency. The U.S. is the only one among them that is not trying to hit a carbon reduction goal.Some emerging economies have also been invited, including Mexico, India, South Africa and Brazil, the host of this year’s COP30 climate talks in November.Ahead of the meeting, the office of Canada's prime minister, Mark Carney, said he and Brazilian President Luiz Inácio Lula da Silva agreed to strengthen cooperation on energy security and critical minerals. White House press secretary Karoline Leavitt said Trump would be having "quite a few" bilateral meetings but that his schedule was in flux.The G7 first came together 50 years ago following the Arab oil embargo. Since then, its seven members have all joined the United Nations Framework Convention on Climate Change and the Paris Agreement. The U.S. is the only nation in the group that has withdrawn from the Paris Agreement, which counts almost every country in the world as a signatory.What’s on the table?Among Canada’s top priorities as host are strengthening energy security and fortifying critical mineral supply chains. Carney would also like to see some agreement on joint wildfire action.Expanding supply chains for critical minerals — and competing more aggressively with China over those resources — could be areas of common ground among the leaders. Climate change is expected to remain divisive. Looming over the discussions will be tariffs — which Trump has applied across the board — because they will have an impact on the clean energy transition.“I think probably the majority of the conversation will be less about climate per se, or certainly not using climate action as the frame, but more about energy transition and infrastructure as a way of kind of bridging the known gaps between most of the G7 and where the United States is right now,” said Dan Baer, director of the Europe program at the Carnegie Endowment for International Peace.What are the possible outcomes?The leaders could issue a communique at the end of their meeting, but those statements are based on consensus, something that would be difficult to reach without other G7 countries capitulating to Trump. Bloomberg reported Wednesday that nations won’t try to reach a joint agreement, in part because bridging gaps on climate change could be too hard.Instead, Carney could issue a chair’s summary or joint statements based on certain issues.The question is how far Canada will go to accommodate the U.S., which could try to roll back past statements on advancing clean energy, said Andrew Light, former assistant secretary of Energy for international affairs, who led ministerial-level negotiations for the G7.“They might say, rather than watering everything down that we accomplished in the last four years, we just do a chair's statement, which summarizes the debate,” Light said. “That will show you that you didn't get consensus, but you also didn't get capitulation.”What to watch forIf there is a communique, Light says he’ll be looking for whether there is tougher language on China and any signal of support for science and the Paris Agreement. During his first term, Trump refused to support the Paris accord in the G7 and G20 declarations.The statement could avoid climate and energy issues entirely. But if it backtracks on those issues, that could be a sign that countries made a deal by trading climate-related language for something else, Light said.Baer of Carnegie said a statement framed around energy security and infrastructure could be seen as a “pragmatic adaptation” to the U.S. administration, rather than an indication that other leaders aren’t concerned about climate change.Climate activists have lower expectations.“Realistically, we can expect very little, if any, mention of climate change,” said Caroline Brouillette, executive director of Climate Action Network Canada.“The message we should be expecting from those leaders is that climate action remains a priority for the rest of the G7 … whether it's on the transition away from fossil fuels and supporting developing countries through climate finance,” she said. “Especially now that the U.S. is stepping back, we need countries, including Canada, to be stepping up.”Best- and worst-case scenariosThe challenge for Carney will be preventing any further rupture with Trump, analysts said.In 2018, Trump made a hasty exit from the G7 summit, also in Canada that year, due largely to trade disagreements. He retracted his support for the joint statement.“The best, [most] realistic case outcome is that things don't get worse,” said Baer.The worst-case scenario? Some kind of “highly personalized spat” that could add to the sense of disorder, he added.“I think the G7 on the one hand has the potential to be more important than ever, as fewer and fewer platforms for international cooperation seem to be able to take action,” Baer said. “So it's both very important and also I don't have super-high expectations.”Reprinted from E&E News with permission from POLITICO, LLC. Copyright 2025. E&E News provides essential news for energy and environment professionals.
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  • McDonald's in Trouble as Ozempic Takes Hold

    Image by Getty / FuturismRx/MedicinesBroken ice cream machines aren't the only thing bedeviling stalwart fast food chain McDonald's.Financial services firm Redburn Atlantic put the company's stock in the bear category, coinciding with a slumpy week in which it lost about three percent of its value — because analysts are betting that GLP-1 agonist weight loss drugs like Ozempic are going to disrupt the fast food business model, CBS News reports.The eyebrow-raising conclusion comes as the analysts reason that people with lower incomes who go on the drugs will tend to shun food outside the home. Meanwhile, people at a higher income level who take Ozempic and similar go back to their food spending habits after a year or so."Behaviour changes extend beyond the individual user — reshaping group dining, influencing household routines and softening habitual demand," wrote the analysts, as reported by CBS. "A 1 percent drag today could easily build to 10 percent or more over time, particularly for brands skewed toward lower income consumers or group occasions."This could have a huge impact on the bottom line of fast food chains like McDonald's, which could stand to lose as much as million annually as they see the disappearance of 28 million visits from formerly hungry customers.This is all complete speculation at this point, because only about six percent of American adults are currently taking these weight loss medications. And they're prohibitively expensive, prices starting at around per month, meaning that extremely few poor people are currently able to afford them.But there's a movement by some policymakers to lower the price of the drugs, which have been proven to not just help people lose weight, but they come with a rash of benefits from preventing certain cancers to treating addictions, among other positives.So if lawmakers force a reduction in price in the future, expect fast food chains like McDonald's to be left holding the bag.And maybe that's a good thing, because the kind of fried foods that McDonald's traffics in are just plain bad for your health.More on Ozempic: Doctors Concerned by Massive Uptick in Teens Taking OzempicShare This Article
    #mcdonald039s #trouble #ozempic #takes #hold
    McDonald's in Trouble as Ozempic Takes Hold
    Image by Getty / FuturismRx/MedicinesBroken ice cream machines aren't the only thing bedeviling stalwart fast food chain McDonald's.Financial services firm Redburn Atlantic put the company's stock in the bear category, coinciding with a slumpy week in which it lost about three percent of its value — because analysts are betting that GLP-1 agonist weight loss drugs like Ozempic are going to disrupt the fast food business model, CBS News reports.The eyebrow-raising conclusion comes as the analysts reason that people with lower incomes who go on the drugs will tend to shun food outside the home. Meanwhile, people at a higher income level who take Ozempic and similar go back to their food spending habits after a year or so."Behaviour changes extend beyond the individual user — reshaping group dining, influencing household routines and softening habitual demand," wrote the analysts, as reported by CBS. "A 1 percent drag today could easily build to 10 percent or more over time, particularly for brands skewed toward lower income consumers or group occasions."This could have a huge impact on the bottom line of fast food chains like McDonald's, which could stand to lose as much as million annually as they see the disappearance of 28 million visits from formerly hungry customers.This is all complete speculation at this point, because only about six percent of American adults are currently taking these weight loss medications. And they're prohibitively expensive, prices starting at around per month, meaning that extremely few poor people are currently able to afford them.But there's a movement by some policymakers to lower the price of the drugs, which have been proven to not just help people lose weight, but they come with a rash of benefits from preventing certain cancers to treating addictions, among other positives.So if lawmakers force a reduction in price in the future, expect fast food chains like McDonald's to be left holding the bag.And maybe that's a good thing, because the kind of fried foods that McDonald's traffics in are just plain bad for your health.More on Ozempic: Doctors Concerned by Massive Uptick in Teens Taking OzempicShare This Article #mcdonald039s #trouble #ozempic #takes #hold
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    McDonald's in Trouble as Ozempic Takes Hold
    Image by Getty / FuturismRx/MedicinesBroken ice cream machines aren't the only thing bedeviling stalwart fast food chain McDonald's.Financial services firm Redburn Atlantic put the company's stock in the bear category, coinciding with a slumpy week in which it lost about three percent of its value — because analysts are betting that GLP-1 agonist weight loss drugs like Ozempic are going to disrupt the fast food business model, CBS News reports.The eyebrow-raising conclusion comes as the analysts reason that people with lower incomes who go on the drugs will tend to shun food outside the home. Meanwhile, people at a higher income level who take Ozempic and similar go back to their food spending habits after a year or so."Behaviour changes extend beyond the individual user — reshaping group dining, influencing household routines and softening habitual demand," wrote the analysts, as reported by CBS. "A 1 percent drag today could easily build to 10 percent or more over time, particularly for brands skewed toward lower income consumers or group occasions."This could have a huge impact on the bottom line of fast food chains like McDonald's, which could stand to lose as much as $482 million annually as they see the disappearance of 28 million visits from formerly hungry customers.This is all complete speculation at this point, because only about six percent of American adults are currently taking these weight loss medications. And they're prohibitively expensive, prices starting at around $900 per month, meaning that extremely few poor people are currently able to afford them.But there's a movement by some policymakers to lower the price of the drugs, which have been proven to not just help people lose weight, but they come with a rash of benefits from preventing certain cancers to treating addictions, among other positives.So if lawmakers force a reduction in price in the future, expect fast food chains like McDonald's to be left holding the bag.And maybe that's a good thing, because the kind of fried foods that McDonald's traffics in are just plain bad for your health.More on Ozempic: Doctors Concerned by Massive Uptick in Teens Taking OzempicShare This Article
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