Meetings
CIO
IT leaders know that the key to success in this digital age is data. It fuels the new economy of AI by providing the building block on which AI algorithms work. Data is part of every business decision around digital transformation, and is now widely recognized as arguably the most important strategic asset of an organization. According to McKinsey, companies that treat their data as a corporate asset grow revenue 5x faster than companies that do not.
To shift the perception of D&A from a mere support function to a strategic growth asset, organizations must innovate in alignment with the rapid pace of digital transformation. How do IT leaders quantify and prove the ROI of data initiatives in the context of business value? How can we drive change while bridging the gap between business and technology?
Furthermore, new tools like Generative AI have the power to change the way the workforce accomplishes goals, but it is imperative that leaders practice care when implementing these technologies. What are the major opportunities and challenges within this space?
Scaling and operationalizing AI and ML are critical to driving value and impacting how decisions within the business are made. It is vital to establish the technology trends, organizational requirements, skill development and talent required for successful deployment. How can we set ourselves up for success and develop a transformative vision for AI and data & analytics?
During this roundtable session we will discuss:
- How do you create frictionless collaboration within your data ecosystem - people, tools and data?
- We hear that data is the new oil. What do organizations need to do to become/cultivate a data driven culture?
- What are the key challenges in implementing data-driven strategies & AI to drive business outcomes and improve workforce efficiency?
- What emerging trends and technologies are expected to have a profound impact on workforce efficiency and business outcomes in the near future?
- What are the potential risks and ethical considerations associated with utilizing AI and analytics for workforce optimization?
- How can organizations ensure data security and privacy while harnessing the power of D&A and AI to drive workforce efficiency?
- How can CIOs collaborate with other departments to leverage the power of data, analytics, and AI?
- Implementing new tech like AI often requires new ways of operating, how can organizations rethink their operations from both a business and IT perspective?
- How can organizations ensure their teams and staff are equipped with the right skills?
- Strong AI outcomes require trust, data-fluency, and agility. Why is leveraging change management to create the right culture so important?
Date TBC by the steering committee (H2) 2024
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The rapid acceleration of digital business presents IT leaders with a distinct opportunity to enhance their influence and collaboration over business strategies, creating new value. Exploring this opportunity demands a new approach to building relationships and co-operating with business stakeholders.
Modernizing the digital core is essential for business transformation, and IT must be an enabler of this process, delivering an environment that is proactive, agile and uninterrupted. Digitization is also essential for achieving sustainability goals across business operations, as well as driving recruitment and attracting key talent. The key to success for the IT leader is arguably maintaining a close partnership and alignment with all business functions, as well as placing customers and employees at the heart of every digital transformation effort.
A desire for greater flexibility, efficiency, and reducing expenses is driving organizations to rethink their approach to technology delivery. However, as companies begin to adopt increasingly innovative technologies, like data analytics, hybrid cloud, and AI & automation, they are still faced with the challenge of siloed teams and processes, without the sustained support needed to be effective. Successful digital transformation comes not only from adopting technology, but adjusting the people, processes, and culture to support it.
So how do you create this intimate alignment in environments of complexity and unite tech with business?
During this roundtable session we will discuss:
- How can we evolve the business-IT relationship dynamic and leverage technology to better serve the business strategy?
- Successful digital modernization comes not only from adopting technology, but adjusting the people, processes, and culture to support it. Do you agree? What are the key challenges here?
- Shifting from reactive to proactive engagement with business stakeholders.
- Partnering with other areas of the business to drive recruitment and craft a desirable future IT culture.
- The areas IT leaders should focus on, from finance to culture, in order to attract key talent and drive change.
- How can we utilize digitization to meet sustainability goals across the business?
- In order to transform at scale, how can technical and non- technical teams work together?
- What do you do about leaders who do not want to collaborate?
- How do you accelerate delivery and deliver new capabilities to the market in a way that compliments or surrounds your technical debt, vs trying to eradicate it all?
- What are the key challenges that companies face on the path to modernizing the digital core? How do we enable speed and agility?
- How can IT leaders channel innovation and extract the value from modern technology, whilst also prioritizing cost savings? And how can IT become a business enabler, rather than a cost center?
Date TBC by the steering committee (H2) 2024
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In order to thrive in today's fast-paced and dynamic digital landscape, IT leaders need to understand the implications of the changing technology landscape on the business. Today's organizations are under huge pressure to keep up with the always-on, always-connected digital economy and its demand for constant innovation. As a consequence, IT ecosystems are undergoing a constant transformation, and IT leaders face an ever-growing challenge: making sense of technology complexity.
Key areas to consider in the tech landscape include the role of automation in streamlining tasks, optimizing cloud-based solutions, managing vast data volumes & understanding the intricate flow of data within organizations, designing robust IT architectures, and ensuring that disparate technologies work seamlessly to benefit the business; all while considering UX, CX, governance, and security.
Naturally, the more complex a company's technology and processing environment, the more difficult it is to make it resilient. As organizations add new layers to their tech stack, each layer comes with its own surface area to secure, requiring increased investments of time, technology, and talent.
A key ingredient in managing this complexity is to figure out how to measure the current state. However, very few organizations have a formalized approach to measuring the complexity of their application and data environment. If companies don't know where they are, they certainly don't know where they are headed.
So how can we measure, evaluate, and make sense of technology intricacy, in order to succeed on a digital transformation journey?
During this round table we will discuss:
- How can organizations ensure that disparate technologies work cohesively, keeping user experience, customer experience, governance, and security in focus?
- How can leaders design agile & scalable IT architectures that adapt to changing business needs?
- How should you decide to what extent new solutions/platforms should replace existing technologies, or be grafted onto previous layers? What challenges arise in managing legacy technology?
- The importance of IT observability & measurement. How can organizations evaluate whether a new change will increase or decrease their tech complexity?
- What does an alternative to complexity look like in an evolving tech stack? How can IT teams reimagine and simplify the ways in which they access their software and tools?
- What levels of talent and upskilling are required when it comes to adopting modern technology stacks? Is there a significant challenge here?
- What are the best practices and strategies for optimizing cloud solutions to accelerate transformation?
- How can we better understand the pathways data takes within the organization, and harness its potential for informed decision making?
- How can we optimize IT & business Ops with the use of automation?
- What's the best approach for breaking large digital transformation initiatives into manageable pieces that can deliver results in 6 months or less?
Date TBC by the steering committee (H2) 2024
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Data & Analytics
As artificial intelligence (AI) continues to advance, questions about ethics and privacy become more important. AI systems make decisions based on the data they are trained on, and it is crucial to ensure that these decisions are fair, unbiased, and aligned with ethical values. Additionally, privacy concerns arise as AI systems rely on vast amounts of personal data. Striking a balance between the benefits of AI and the ethical considerations is essential to ensure that AI technologies are used responsibly and for the greater good of society.
- How can organizations ensure ethical considerations are integrated into the development and deployment of AI systems, particularly with respect to privacy and data protection?
- What are the key challenges and risks associated with privacy in the context of AI, and how can these challenges be effectively addressed?
- How can organizations strike a balance between leveraging AI for innovation and maintaining privacy rights and data protection for individuals?
- What are some potential ethical dilemmas that arise in the use of AI, and how can organizations proactively address these dilemmas to ensure responsible AI deployment?
- What steps can organizations take to ensure that AI models and algorithms do not perpetuate bias or discriminate against certain individuals or groups, while still maintaining privacy and data protection?
- How can organizations establish robust mechanisms for obtaining informed consent and providing individuals with control over their personal data in the context of AI-driven applications and services?
Date TBC by the steering committee (H2) 2024
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A human-centric approach in data is a powerful tool that can empower innovation and drive meaningful outcomes. By placing humans at the centre of data-driven initiatives, organizations can gain valuable insights into human behaviour, needs, and preferences, leading to the development of products, services, and experiences that truly resonate with people.
- How does a human-centric approach to data transform the way organizations collect, analyse, and utilize data to drive innovation?
- In what ways can a human-centric approach ensure that data-driven insights are aligned with the needs, values, and preferences of the end-users or customers?
- What are the key considerations for organizations when integrating a human-centric approach into their data strategies and decision-making processes?
- How can organizations effectively gather and incorporate user feedback, experiences, and behaviour data to enhance the human-centricity of their data-driven initiatives?
- What ethical considerations should organizations keep in mind when applying a human-centric approach to data collection, analysis, and usage?
- What challenges or barriers might organizations encounter when adopting a human-centric approach to data, and how can these challenges be addressed?
- How can organizations balance the need for personalization and customization with user privacy and data protection when taking a human-centric approach to data-driven innovation?
Date TBC by the steering committee (H2) 2024
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Data has become the fuel that drives decision-making and innovation in various industries. With the constant disruptions happening around us, data plays a crucial role in identifying trends, predicting outcomes, and informing decision-making processes. The potential of data is immense, as it can uncover hidden insights, unlock new opportunities, and drive business growth. It is important for organizations to effectively harness and analyse their data to stay competitive in the rapidly changing landscape.
- What are the main challenges organizations face when it comes to effectively harnessing and analysing their data, and how can these challenges be overcome?
- In what ways can organizations leverage data to uncover hidden insights and unlock new opportunities for business growth?
- How can organizations ensure the quality and reliability of their data to make accurate and impactful decisions?
- What role does advanced analytics, such as machine learning and artificial intelligence, play in maximizing the value of data for organizations?
- How can organizations establish a data-driven culture and mindset throughout their workforce to encourage data utilization and decision-making at all levels?
- What emerging trends or technologies should organizations be aware of when it comes to data utilization and analytics, and how can they leverage these trends for competitive advantage?
Date TBC by the steering committee (H2) 2024
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Cyber Security
88% of security breaches have human error at their core, according to research from Stanford University. The human being in the attack chain is seen as an easy, low-hanging no-hack option, to infiltrate a network and carry out a destructive and often financially lucrative cyber-attack.
Increasingly, cybercriminals are turning to the 'human factor' to execute their cyber-attack. Therefore, cybersecurity is much more than a technology problem. Attacks focus on finding ways to exploit human behavior to then begin a chain of events that results in stolen credentials and other data, ransomware infection, DDoS attacks, and general IT chaos.
The challenge is to ensure that anyone who interacts with the digital realm understands how cybersecurity works. The problem stems from the 'plug-and-play' view of technology, instilled in human behavior as digital technology has evolved over the decades. Cybersecurity behavior is then seen as a 'blocker', something that adds an extra burden on the human user. Enter Cyberpsychology! The basis of the discipline is to develop human-oriented systems for a given type of technological area. Cyberpsychology applies to home, work and work from anywhere environments.
So how can security leaders and their teams become empowered and achieve "the human-centered approach to cybersecurity?" A socio-technical approach is crucial. A technical only approach can achieve quite a lot but will not result in seamless cyber-security where humans are part of the systems.
Join this panel discussion to dive into the symbiosis between people and the technology that they use, and how organizations can reduce the number of human errors that lead to cyber-attack success.
Date TBC by the steering committee (H2) 2024
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The concept of digital transformation has been with us for a decade now, and it has become the driving force behind the IT efforts of most enterprises and always involves multicloud deployments. In fact, 71% of respondents to a recent IBM survey agreed that it is "difficult to realize the full potential of a digital transformation" without a multicloud strategy. At the same time, 41% of the executives do not think their security initiatives have kept up with digital transformation.
One of the primary roadblocks to implementing a strong cloud security posture is the fact that each major public cloud platform uses a different approach and tools for protecting its infrastructure. For example, AWS, Azure and GCP do not handle basic security functions such as identity and access management (IAM), privileged access management and VPNs in the same way. There are nuances that must be considered for security measures to work properly. The professionals who understand these nuances are not easy to find. Is this where the talent crunch meets the budget crunch? There are few organizations that are not suffering from a lack of skilled security personnel, and the competition for talent is intense. Whilst corporations tighten their purse strings and talent is scarce how can cloud providers better collaborate with their customers during this challenging landscape?
Join this meeting to discuss the following points:
- How would you describe the current state of the skills shortage in cloud security? What are the specific challenges organizations face in finding and retaining skilled professionals?
- What are the key skills and expertise required to effectively manage cloud security? Are there any emerging areas or specialized roles that are becoming increasingly critical?
- What role can automation, artificial intelligence, and machine learning play in mitigating the skills shortage? How can these technologies enhance the capabilities of security teams and streamline cloud security operations?
- Looking to the future, what trends and technologies should organizations consider when developing their cloud security strategies? How can they prepare for the evolving threat landscape and the changing skill requirements?
- In the context of the skills shortage, how can organizations effectively balance outsourcing or partnering with third-party providers while maintaining control and ensuring the security of their cloud environments?
- Are there any regulatory or compliance considerations that must be considered when addressing the skills shortage in cloud security? How can organizations meet these requirements effectively?
- During a skills shortage shared responsibility has never been more prevalent, so how can cloud providers support businesses to navigate the complexities of cloud security, foster a proactive and cooperative approach to mitigate risks effectively?
Date TBC by the steering committee (H2) 2024
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- Hackers are leveraging artificial intelligence and machine learning to add an additional layer of sophistication to their attacks, which means organizations need to move beyond the traditional and into the extraordinary when it comes to defending themselves. This includes investing in technologies such as threat detection and response, encryption, and multifactor authentication. But the question is "How can artificial intelligence help cybersecurity strategy today?"
- How can organizations strike the right balance between AI automation and human expertise in cybersecurity operations? What are the key decision points for determining when human intervention is necessary?
Date TBC by the steering committee (H2) 2024
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Healthcare
Superior patient experience boosts the reputation of life sciences organizations among patients, positively influences clinical outcomes, and has an indirect yet critical impact on life sciences' bottom line. However, delivering a superior patient experience is anything but easy - it requires significant monetary and time investments, a patient-centric mindset, seamless coordination with care delivery teams, and the right digital means to enrich patient lives wherever possible (Indigene).
Additionally, IDC analysts predict that by 2025, 60% of life science firms will use health data platforms for physician engagement, along with patient journey processes. The connection of quality information that can be securely exchanged will support the patient and provider experience, and enable the growing demand for telemedicine and remote care.
Questions to answer in this roundtable discussion include:
- Digital is a key theme in improving the patient journey. But how do you balance the human and technology element to deliver better patient engagement and outcomes?
- How can we adapt and change technology as we learn more about patient need?
- What are some of the challenges that life sciences companies face when attempting to implement patient-centric processes, and how can these challenges be addressed?
- How does patient activation support better outcomes?
- How can life sciences organizations ensure they are providing meaningful digital assets?
- How can life sciences organizations ensure the patient voice is considered in the creation of products, decisions, and directions?
- How can patient feedback be effectively incorporated into the development of patient journey processes in life sciences?
- What is the future of patient engagement and journey processes in life sciences, and how can companies stay ahead of the curve in this rapidly evolving field?
Date TBC by the steering committee (H2) 2024
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Revolutionizing the patient and member experience is a critical aspect of providing high quality healthcare services as we move through the next decade. Healthcare providers are under immense pressure to improve patient outcomes, reduce costs and enhance individual experiences. Healthcare organizations that offer their patients and members a positive experience will be better positioned to attract and retain new ones. According to McKinsey - consumer-centric healthcare companies drive more than twice the revenue growth than those with lower patient satisfaction scores. More of a reason companies must integrate customer experience into their overall strategy and put patients at the heart of every decision to succeed. With technology at the heart of this transformation, we need to best leverage new strategies to communicate the right messages to costumers at the right time to best meet their needs. Did you know Telemedicine had a market valuation over $71.5 billion in 2023. Experts predict the global telemedicine market will exceed $244 billion by 2033.
Let us discuss:
- How you are redesigning your care pathways to create a hybrid approach now that virtual care is an integral part of the patient experience.
- When you think about care routing and care navigation when patients have both virtual and physical resources- how do you create continuity in their overall patient experience?
- For patients/ members with no access to the internet, technology can be a barrier to care. What does a personalized experience look like for that population as we head into 2024?
- For patients/ members with no access to the internet, technology can be a barrier to care. What does a personalized experience look like for that population as we head into 2024?
Date TBC by the steering committee (H2) 2024
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Utilizing data efficiently has become an essential strategy in enabling better health outcomes. AI and data analytics featured heavily in the healthcare industry's line of defence against COVID-19 and is now playing a critical role to help clear the backlogs caused by the pandemic. By collecting and analysing patient data, healthcare providers can identify trends, patterns, and potential risks to patient health. Data security and patient confidentiality is at the heart of the issues concerning transformation within in the industry. CyberMDX reports that hospitals account for 30% of all large data breaches. More than half [51%] of healthcare organizations reported an increase in data breaches since 2019. If healthcare organizations can marshal the right technologies and approaches, the opportunities are enormous: better demand forecasting reducing waste and saving costs; powerful insights into patient needs and preferences to reconnect them with the healthcare system; and the ability to deliver predictive, personalized, preventative care.
- How do we manage trust issues when working with such sensitive data? - What are the opportunities for using data to deliver better individual care that is predictive, personalized, and preventative?
- Data driven approach. Is that important to your group?
- What approaches did people discuss with regards to gaining greater visibility of your data?
- Do you see value in payers collaborating in the Medicaid space?
- What type of innovations do you foresee in the collaboration space?
- How should payers and providers be working together in this space? Is Patient Experience a Catalyst for Payer-Provider Collaboration?
- What avenues can be used between provider and payer to facilitate collaboration through better use of patient data to enable better patient/ member experiences and outcomes?
- The HIPPA Journal reported 4.2 million patients were impacted in the largest data breach in 2023 so far?
Date TBC by the steering committee (H2) 2024
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Manufacturing
Artificial intelligence is transforming the nature of work in nearly every field, from film production to legal writing. In the last year, new technologies have made AI dramatically more accessible for analyzing and generating text, images, and videos, and as a result adoption of AI tools in everyday work has surged.
The manufacturing sector was an early adopter of the previous generation of AI: machine learning technologies that could sift through images and structured data to find anomalies and spot trends. Machine learning-based tools are now widely used across the manufacturing world in areas like quality control, inventory management, and maintenance planning.
The latest advancements in generative AI appear to be focused on creative fields, but a deeper look reveals highly impactful applications for engineers and manufacturing managers. Generative AI technology can consolidate knowledge from both global resources and from internal experience, organize it, and make it available to front-line workers in plain language. In doing so, it can break down silos within organizations, spot trends that would otherwise go unnoticed, give engineers access to specialized knowledge, and help engineering teams approach problems quickly and creatively.
This roundtable will explore applications for the latest generation of AI in manufacturing, at every stage of the product development process from initial design through mass production.
Questions to answer in this roundtable include:
•>How can manufacturers leverage the latest generation of AI technology- commonly seen as applicable in only creative fields- to improve product design and manufacturing outcomes?
- What training and preparation is required for individual workers and for teams in order to make the most of new AI tools?
- What data is required in order to use AI tools in manufacturing organizations?
- Are there security risks associated with AI, and how can they be mitigated?
- How can AI technologies be integrated into the product development process, from the initial design phase to mass production? What benefits can this integration bring?
- How do you envision the future of AI in manufacturing, and what emerging trends or applications are you most excited about?
Date TBC by the steering committee (H2) 2024
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The manufacturing industry remains an essential part of the economy, but it's no secret that it's currently facing a considerable talent shortage. Companies are continually searching for skilled workers to fill vacant positions, facing numerous challenges that have hindered their recruiting efforts. Deloitte predicts that by 2030, 2.1 million manufacturing jobs could go unfilled, and a Workday survey found that nearly half of manufacturing leaders today are reporting worker turnover that's higher than the historical average.
Adding pressure to this talent crunch is that factories hit a 14-year production high point in September 2022, according to the Federal Reserve. Although business growth opportunities exist, 45% of manufacturers have had to turn down opportunities due to a lack of workers, according to Deloitte. In addition, manufacturing companies face tough competition for skilled workers from industries like healthcare, energy, and technology. Manufacturing workers are also the most likely to leave for higher pay or for a career change within another industry as they seek more flexibility in their work lives. (Workday).
The pandemic's effects on supply chains and labor underscored the need for increased innovation and digitalization in the manufacturing industry. While digitalization offers exciting opportunities, it also poses the risk of exacerbating skills gaps. Manufacturers need workers with experience in the industry and proficiency in physical tools like welding and machining, while also understanding transformative digital technologies such as AI, automation, analytics, and robotics. Upskilling is becoming increasingly crucial as a solution to both the industry's high turnover rate and the demands of the new advanced manufacturing age.
The workforce of tomorrow will look, learn and work differently, forcing organizations to reimagine their talent strategies to meet employees' evolving expectations around everything from hybrid working, L&D and upskilling, to better pay and greater flexibility. (Workday)
Questions to answer in this roundtable include:
- How can manufacturing companies attract and retain skilled workers in the face of competition from other industries?
- Workers in the manufacturing industry are more likely to leave for higher pay or career changes to seek better work-life flexibility. How can manufacturers address these factors and create a work environment that encourages employee loyalty and long-term commitment?
- How can manufacturing companies invest in upskilling and reskilling their existing workforce to meet changing industry demands?
- What role does L&D play in addressing the skills gap in manufacturing?
- How can diversity and inclusion initiatives in manufacturing help attract a broader range of talent and contribute to filling the skills gap?
- What role can automation and advanced manufacturing technologies play in both exacerbating and alleviating the skills gap in the industry?
Date TBC by the steering committee (H2) 2024
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Sustainability has emerged as a critical focus in the manufacturing industry, driven by the increasing awareness of the environmental and societal impacts of industrial activities. Manufacturers are now taking proactive measures to minimize their ecological footprint through various sustainable practices. These efforts encompass product lifecycle management, e-waste management, and the adoption of greener manufacturing techniques. (Powers)
Moreover, organizations are actively embracing renewable energy sources like solar, wind, and hydro-power to reduce their carbon emissions. This not only contributes to the preservation of the environment, but also brings long-term cost savings by lowering energy bills and mitigating exposure to fluctuating fossil fuel prices. Companies are also focusing on the reduction of pollution and incorporating recycling practices into their operations.
The fast-evolving environmental, social, and governance (ESG) landscape may also require close monitoring in the coming years for manufacturing organizations. Many organizations voluntarily comply with a complex network of reporting regulations, ratings, and disclosure frameworks, but regulators globally are also moving toward requiring more disclosures for nonfinancial metrics. Manufacturers are progressing toward their ESG commitments by making operational changes across their value chains. Efforts by manufacturers to become more sustainable not only safeguard the planet and society, but also foster goodwill among consumers who prioritize eco-friendly products and contribute to a brighter, greener future for all.
Questions to answer in this roundtable include:
- How can manufacturers strike a balance between adopting sustainable practices and maintaining their profitability and competitiveness in the market?
- How can manufacturers encourage consumer behavior to support sustainable products?
- How do varying regulatory environments impact manufacturers' sustainability efforts, and what are the implications for global supply chains?
- Collaboration and partnerships among manufacturers, suppliers, and other stakeholders are essential for a sustainable future. How can companies foster these collaborations and create a shared vision for sustainability?
- As technologies evolve, how can manufacturers leverage advancements like Industry 4.0, AI, and IoT to further enhance their sustainable practices and efficiency?
- Beyond environmental aspects, how can manufacturers incorporate social sustainability into their operations, such as fair labor practices, diversity and inclusion initiatives, and community engagement?
Date TBC by the steering committee (H2) 2024
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