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The most important part of the technology puzzle: People Eli Lilly and Company’s chief information and digital officer explains how a medicine company rewires itself to embrace technology—starting with the CEO. #executives #leadership #CEO #technology #digital #transformation #2019linkedintoprecruiter #mostsociallyengaged https://lnkd.in/gRh8PQG6

The most important part of the technology puzzle: People Eli Lilly and Company’s chief information and digital officer explains how a medicine company rewires itself to embrace technology—starting with the CEO. #executives #leadership #CEO #technology #digital #transformation #2019linkedintoprecruiter #mostsociallyengaged https://lnkd.in/g2-pjncg

As digital transformation accelerates, the potential of #DataSharing is becoming more evident. Pioneers like Walmart and Procter & Gamble have, over the years, reaped significant benefits from embracing data sharing, yet many organizations remain hesitant. In a new article published by Fortune, François Candelon, Riccarda Joas, Guillaume Sajust de Bergues, and Leonid Zhukov, explore how these technological advances are impacting the risk-reward calculus.

As the Tech Leader with leading organizations, I've been grappling with a critical question that many large organizations face: Q: Should we centralize our Data and AI teams or embed them within specific business units? After years of experience and careful analysis, I've come to realize that there's no one-size-fits-all answer. Both approaches have their merits and drawbacks, and the optimal solution often depends on your company's unique culture, goals, and structure. Some things that have worked for me and my team's in the past are - Centralization offers the advantages of standardized practices, economies of scale, and the ability to tackle large, cross-functional projects. However, it can lead to slower response times and a disconnect from business needs. On the flip side, embedding teams within business units ensures closer alignment with stakeholders and faster, more tailored solutions, but it can result in siloed knowledge and duplicated efforts. The key lies in finding the right balance – perhaps a hybrid model that combines the best of both worlds. What's your take on this? Have you found a solution that works particularly well in your organization? #DataStrategy #AIinEnterprise #TechLeadership #AILeaders

As digital transformation accelerates, the potential of #DataSharing is becoming more evident. Pioneers like Walmart and Procter & Gamble have, over the years, reaped significant benefits from embracing data sharing, yet many organizations remain hesitant. In a new article published by Fortune, François Candelon, Riccarda Joas, Guillaume Sajust de Bergues, and Leonid Zhukov, explore how these technological advances are impacting the risk-reward calculus.

Mention of being ‘future-ready’ often comes up in client conversations when we discuss technology investment or potential applications of #GenAI: but ‘doing tech right’ simply isn’t enough for long-term success.    To effectively manage complex decisions about cost structures, sustainability, and technological advancements in a competitive and uncertain market environment – all while retaining optimism and a clear vision for the future – leaders should nurture five critical traits to become future-ready.   A great read in Fortune from Hans-Paul Bürkner, Arindam Bhattacharya, and François Candelon.

You have described the classic Data Team structure dilemma. The federated structure is what I have seen work the best. Seattle Data Guy describes this in this article. https://lnkd.in/g72Ag3AX I have spent the most time on the 'business' side of the house (embedded within FP&A) and most of the time even the best centralized data teams cannot respond to changing business needs in a timely manner. Siloed knowledge and duplicated efforts are inevitable and often the centralized team may not even be aware of it as it may exist in their own tools (excel, custom reports in the ERP or EPM). In my opinion a small data team dedicated to the goals of the leader of each function is needed in order to enable fast decision making. These teams should dotted line to the central data team. The role of the centralized data team should be to bring these siloed metrics, KPIs, etc. to a standardized state over time and maintain the infrastructure and best practices across the company.

Technology has been advancing for decades, and many companies have worked to #digitize their processes and functions. Yet, #GenAI is different. In BCG’s recent research, roughly 65% of senior executives say it has the greatest disruptive potential of any #technology over the next five years. Read our complete insights to learn why leaders are so bullish: https://lnkd.in/eJZ6CkEC

Technology has been advancing for decades, and many companies have worked to #digitize their processes and functions. Yet, #GenAI is different. In BCG’s recent research, roughly 65% of senior executives say it has the greatest disruptive potential of any #technology over the next five years. Read our complete insights to learn why leaders are so bullish: https://lnkd.in/e9hHqh2u

Interesting day at the AI in Business & Digital Transformation Conference yesterday. There was a definite shift change from the last year where much of the conversation was dominated by fear & regulation concerns. Key takeaways ✅️ Business strategy - AI must be a driver, or at least part of, the business strategy as opposed to side vanity projects. ✅️ Talent - we need to be intentional about closing the talent gap in our teams & start to appoint leading roles. I was really impressed that GSK has created a new senior role for Riccardo Calliano to lead GenAI Commerical Investments ✅️ Make AI relatable - to get buy in & senior investment, we need to find the balance between the business value & excitement of tech ✅️ Get serious about change - we need to be set up for the business to embrace the change/ opportunity which will move at pace and continually evolve ✅️ Lay the foundations - siloed GenAI projects are fine & will deliver some benefit but we need to be thinking about laying the overall data, infrastructure, architecture foundations to really support transformational benefit In my opinion, we need to ensure that any GenAI investment does have a clear benefit to test against but also provides a clear link to your customer experience, employee productivity or both. This will ensure we focusing on something that will deliver end to end benefit for our customers. #GenAI #digitaltransformation #CX