Michael Porter, in his landmark 1996 Harvard Business Review article, “What Is Strategy?”, made a clear distinction: operational effectiveness is not strategy. While practices such as total quality management, benchmarking, and outsourcing can lead to significant improvements, they are easily replicated and do not constitute a sustainable competitive advantage.
For digital and technology leaders, a similar debate persists: operational effectiveness is not transformation. Many executives recognize this distinction and seek a dedicated transformation office to drive outcomes beyond efficiency gains and into the realm of true business model reinvention.
Porter distinguishes operational effectiveness—performing similar activities better than rivals—from strategic positioning, which entails performing different activities or performing similar activities in unique ways.
The same logic applies to transformation. Consider Amazon’s use of AI-driven demand forecasting and route optimization to reduce delivery times and inventory costs. While these improvements enhance efficiency, they are also easily adopted by competitors such as FedEx and UPS.
Now, compare that to Tesla’s over-the-air (OTA) software updates. Traditional automakers rely on dealerships and service centers for vehicle maintenance, recalls, and feature updates. Tesla fundamentally changed this model by enabling OTA updates, allowing it to fix issues, improve performance, and introduce new features remotely. This wasn’t just an efficiency play—it transformed the very nature of vehicle ownership, turning cars into continually evolving digital platforms. Rather than simply optimizing the existing automotive service model, Tesla redefined how customers interact with and experience their vehicles.
When organizations pursue transformation, they often jump straight from ideation to execution—focusing on refining existing systems and processes rather than redefining the activity itself. This approach can yield value but frequently results in a multi-million-dollar effort to do the same things faster rather than reimagining what is possible.
The “missing middle” is the set of strategic activities that occur between ideation and execution—steps that increase the likelihood of delivering truly transformative outcomes rather than just operational efficiencies. These activities include establishing a vision, reimagining experiences and processes, defining the holistic technical architecture, and devising a plan for managing delivery and change.
The magic of the “missing middle” is not derived from the activities themselves. None of them in isolation are novel; you are probably doing all of them in some form or fashion. Rather, the magic is derived from the order, rigor, and purview at which they are executed.
Take order, for example. A company that starts its transformation by designing systems and then tries to retrofit a vision based on the system changes they have proposed will likely overlook key aspects of the experience or opportunities to truly change how they go to market to serve a growing persona or channel in a differentiated fashion.
Similarly, a transformation that skips visioning to determine how success will be measured and how it ties to firm economics may suffer from an existential crisis, unable to articulate how its investment has moved the needle. Order matters, and it all needs to start with a measurable vision.
The rigor with which these activities are executed is another moment of truth. As the Chief Digital Officer of a Fortune 500 manufacturing client said, “Transformation is not a part-time job.”
Performing the missing middle correctly often requires a team of dedicated resources. Sometimes, this is simply a matter of capacity, and other times, it’s a matter of not having the proper skill set. Organizations that do this well dedicate full-time resources to establishing repeatable playbooks and executing the activities in the missing middle.
For example, a Fortune 500 manufacturing client recently enlisted 15 new full-time resources to stand up a transformation function and lead key transformation activities: strategy, experience, process and technical architecture, and change.
Despite their best efforts and intentions, a technical lead asked to design the future-state vision and experience off the side of their desk, while also leading architecture, will inevitably fall short. Cross-functional, cross-business-unit transformation initiatives that are intended to fundamentally change how a business operates or interacts with constituents deserve fully dedicated resources to execute the missing middle.
Last but surely not least is purview. For large, at-scale organizations, transformation efforts cannot succeed in a vacuum. It’s rare that something truly transformative won’t have its tentacles in various business units, functions, and other parallel transformative initiatives.
To effectively play the orchestra, there needs to be a centralized transformation function that defines “the music” that the various initiatives follow in conducting the activities in the missing middle. It should define the overarching guardrails for experience, business, and technical architecture for all of the initiatives in the portfolio. It should also have methods for maintaining ongoing dialogue with initiative teams so they can verify alignment with the guardrails and have visibility into execution to navigate portfolio-level issues, ensuring that the outcomes of one initiative complement, rather than conflict with, those of another.
The degree to which these capabilities are decentralized at the initiative or centralized at the portfolio level will vary based on the goals of the organization regarding consistency, governance, speed, and agility. Over time, most organizations settle in with a hybrid model.
If your transformation efforts feel more like an exercise in operational efficiency rather than a fundamental shift in how your business operates, it may be time to reconsider your approach. True transformation is not about doing the same things better—it is about redefining what is possible. A dedicated transformation office, equipped with the right order, rigor, and purview, can be the difference between incremental improvement and a true reinvention of your business model. By focusing on the missing middle and aligning strategic activities before execution, organizations can drive meaningful, sustainable change that extends beyond efficiency and into the realm of true competitive advantage.
At first glance, the shift toward product thinking may seem tailor-made for teams working on customer-facing digital products, like mobile apps or eCommerce experiences, where new features are envisioned in lockstep with business units that have P&L responsibility. But what about teams maintaining enterprise applications like SAP and Salesforce? Or those responsible for shared APIs, IT Ops, and core platforms, which serve multiple product teams rather than direct customers?
If these questions resonate, you’re not alone. Many organizations transitioning to a product operating model encounter a moment of reckoning, where technology professionals accustomed to a service-oriented approach begin questioning where they fit. The reality is that while the implementation of product thinking varies depending on the type of work, there are core principles that apply universally. Proactively addressing these nuances is key to ensuring adoption, mitigating resistance, and maximizing impact.
To successfully adopt a product operating model across the technology function, it’s critical to recognize that not all teams will work in the same way. The model applies broadly, but the composition of work, customer relationships, and team structure will vary based on the type of product being supported.
Product teams focus on customer-facing or business-aligned products—solutions designed for direct end-users, whether external customers, employees, or partners. These teams operate in close collaboration with business units, iterating on features that enhance experiences and drive revenue. Because they are continuously evolving their offerings, product teams typically allocate the highest proportion of their efforts to grow and transform work—building new capabilities, improving customer experiences, and responding to emerging market demands—while still maintaining the core functionality of their products.
Platform teams provide shared capabilities, APIs, and infrastructure that support multiple product teams. Their customers are often internal, ensuring that foundational technology services—such as data platforms, authentication systems, or integration layers—are scalable and reusable. The nature of their work is more evenly distributed across run, grow, and transform activities, as they must balance maintaining system stability with improving and expanding the services they offer to product teams.
Services teams maintain critical technology operations, supporting both internal users and other product teams. Unlike product teams that focus on innovation, services teams prioritize run activities—ensuring uptime, compliance, and operational efficiency—while still making measured improvements over time. Their primary responsibility is to keep core capabilities and infrastructure reliable while adapting to business needs and regulatory changes.
Beyond work allocation, these teams also differ in who they serve. Product teams work closest to revenue-generating customers, continuously improving their experience. Platform teams serve internal product teams, providing the foundational services that enable scalable innovation. Services teams support internal business users and the rest of the technology organization, ensuring critical enterprise functions run smoothly.
While the scope of work varies, all product-oriented teams share fundamental principles that drive alignment, agility, and accountability.
Every team operates against a proactive, long-term roadmap that ensures continuous improvement rather than reactive project execution. Whether delivering a customer-facing experience, maintaining a data platform, or supporting enterprise technology services, teams work with a strategic view of how their domain evolves.
Each team balances two complementary focuses: working on the business, which drives innovation and efficiency, and working in the business, which ensures the successful delivery of day-to-day operational needs. This ensures that even services teams, which spend more time on operational stability, are still evolving their capabilities rather than just maintaining them.
Regardless of the type of product a team supports, they all operate with common ways of working, typically inspired by agile methodologies. Structured sprints, iterative delivery, and continuous alignment with business stakeholders ensure that teams remain responsive and adaptable while maintaining consistency across the enterprise.
If you’re leading the shift to a product operating model, anticipating these nuances and addressing concerns early will be essential. A key first step is clarifying roles and responsibilities so that technology service teams understand their continued relevance and how their work aligns with the new model.
Defining success metrics tailored to each team type ensures that performance is measured in a way that reflects their contributions. Adoption, uptime, and customer experience are all critical, but the specific emphasis will vary based on whether a team is customer-facing, platform-focused, or service-oriented.
Encouraging cross-team collaboration is equally important. A strong product operating model is not about isolating teams but about fostering an ecosystem where platform teams, enterprise application teams, and product teams work in tandem. Aligning their priorities and reinforcing shared ways of working will drive efficiency and long-term success.
The transition to a product operating model isn’t just for digital-first teams—it’s for all of technology. Whether your team is building customer-facing products, enabling developers with reusable platforms, or maintaining critical enterprise applications, the fundamental principles of product thinking apply universally.
by At first glance, the shift toward product thinking may seem tailor-made for teams working on customer-facing digital products, like mobile apps or eCommerce experiences, where new features are envisioned in lockstep with business units that have P&L responsibility. But what about teams maintaining enterprise applications like SAP and Salesforce? Or those responsible for shared APIs, IT Ops, and core platforms, which serve multiple product teams rather than direct customers?
Advancements in artificial intelligence have opened the door for innovative ways companies can deliver unique and personalized customer experiences. Join us virtually on May 21 for our next Metis Strategy Digital Symposium where global business and technology executives describe how AI has improved their organizations, how they are continuing to foster a customer-centric mentality, and what the future of technology and digital looks like in the Age of AI.
C-level technology leaders, register here reserve your spot and stay tuned for agenda updates. We look forward to seeing you!
(Click here for highlights from our most recent Digital Symposium, and stay tuned to our YouTube channel for videos of our panel discussions.)
12:00 – 12:15 p.m.
Welcome and Introductions
Welcome and introduction to the Metis Strategy team
Peter High, President, Metis Strategy
12:15 – 12:40 p.m.
Customer Experience in the Age of AI
Marty Brodbeck, Chief Technology Officer, Priceline
Bala Subramanian, Chief Digital & Technology Officer, UPS
Moderated by Steven Norton; Co-Head Executive Networks, Research, and Media; Metis Strategy
12:40 – 1:05 p.m.
Driving Digital Innovation Ahead of Disruption
Greg Moore, Chief Information Officer, KB Home
Michael Lucas, Chief Information Officer, Wilson Sonsini
Moderated by Chris Davis, Partner & West Coast Office Lead, Metis Strategy
1:05 – 1:30 p.m.
Shaping the Story: Future-Oriented Talent and Innovation
Monica Caldas, Global Chief Information Officer, Liberty Mutual
Amir Kazmi, Chief Information & Digital Officer, WestRock
Moderated by Alex Kraus, Partner & East Coast Office Lead, Metis Strategy
1:30 – 1:45 p.m.
Entrepreneur Spotlight: CEO of Augment
Scott Dietzen, CEO, Augment
Moderated by Peter High, President, Metis Strategy
1:45 – 2:15 p.m.
Emerging AI Opportunities in Pharmaceuticals and Healthcare
Diogo Rau, Chief Information & Digital Officer, Eli Lilly
Cindy Hoots, Chief Digital Officer & Chief Information Officer, AstraZeneca
Greg Meyers, Chief Digital & Technology Officer, Bristol Myers Squibb
2:15 – 2:40 p.m.
Blueprint for AI Organizational Readiness
Praveen Jonnala, Chief Information Officer, CommScope
Tim Dickson, Chief Digital & Information Officer, Regal Rexnord
Moderated by Michael Bertha, Partner & Central Office Lead, Metis Strategy
2:40 – 2:55 p.m.
Closing Remarks and Adjourn
Click here for highlights from our February Metis Strategy Digital Symposium, or watch the panels on our YouTube channel. We look forward to seeing you!
Thank you to everyone who attended and participated in the 14th Metis Strategy Digital Symposium. Highlights from the event are below. Stay tuned to the Metis Strategy Youtube channel and Technovation podcast in the coming weeks for recordings of individual panel discussions. We look forward to hosting the next Metis Strategy Digital Symposium in December – more details to come soon.
As generative AI continues to flood the headlines, technology and digital leaders are busy discerning hype from reality and exploring use cases that can deliver tangible value across their organizations.
While many companies have used AI in their operations for a while, the rapid rise of generative AI has drawn outsized attention from colleagues well outside the IT department. As a result, many CIOs and their peers have turned their focus toward the tools, processes, and skills needed to take advantage of the emerging technology at scale. Tech leaders are also honing their storytelling skills as they paint a picture for colleagues and customers of how AI-based technologies can drive growth and deliver new, value-added experiences.
In conversations with technology leaders across a variety of industries, we have found that those most successful in their AI endeavors so far are driving excellence across four overlapping workstreams: educate, explore, experiment, and expand. The speakers at this year’s Symposium were no exception. In order to prepare their organizations for an AI-driven future, they noted the following priorities:
Building cross-functional AI teams
Many organizations are taking an interdepartmental approach to developing AI strategies, bringing together stakeholders from across the business to prioritize use cases, build solutions and lead change management.
At Total Quality Logistics, CIO Ryan Kean built a Center of Excellence with 12 people across business units to evaluate new automation use cases, assessing whether or not to develop them based on expected value, tangible benchmarks, and reusability across the enterprise. Kean noted that while a decentralized approach may work for some organizations, it could lead to chaos in others if citizen development happens in silos. At TQL, the CoE model has helped to ensure proper governance, monitoring and development of new solutions.
Similarly, at real estate giant Cushman & Wakefield, Chief Digital and Information Officer Salumeh Companieh’s team has developed an AI task force that includes members from departments including cybersecurity, legal and procurement, to name a few. The task force has developed a standardized process that is helping CBRE actively review 200 use cases globally, delivering necessary governance while focusing on driving client value, market differentiation, and delivering unique insights.
Measuring customer and employee experiences
Speakers noted the critical role advanced AI tools can play in enhancing the digital experience for customers, but emphasized the need for a quality data foundation and clear measures to ensure progress is made.
Keeping customers and employees front and center will be key to enabling increased value and competitive differentiation with AI. To do that, technology leaders must continue to measure and assess progress on these initiatives regularly. DXC Technology CIO Kristie Grinnell conducts both employee NPS and external NPS surveys to measure whether her department is providing the tools and data that create frictionless experiences across the board, noting that both of those measurements should go up as the digitization journey continues. Grinnell also uses sentiment analysis to understand how employees are feeling and uses that feedback to guide employee experience initiatives. She noted that embracing accountability and ownership for specific services over the past years has helped push internal NPS scores from the low 20s to the mid 30s.
The most insightful methods that leaders use to gauge internal and external customer satisfaction and experience are Net Promoter Score (NPS/eNPS) and Customer Sentiment Analysis
At the Home Depot, CIO Fahim Siddiqui noted the virtuous cycle between great employee experience and customer experience: “If you take care of your associates, they will take care of your customers, and everything else takes care of itself.” To ensure that he is providing the right digital features and capabilities, Siddiqui provided all 400,000 customer-facing associates with a handheld device that connects them to the data and insights they need to help customers throughout the network. He also noted that this process sometimes involves interacting with a generative AI model that provides natural language responses to associate queries. Siddiqui noted that employee engagement has reached its highest level, and positive leadership behaviors are also on the rise.
Driving strategic automation
Generative AI tools have created new opportunities to automate and enhance a range of business processes. It is shifting the conversation around automation from one solely of efficiency to one of organizational effectiveness and growth.
One of the quickest ways that technology leaders have unlocked value for their customers and employees is training chatbots on company knowledge bases, ultimately reducing the time it takes to access critical information, answering queries in an easy to understand way, summarizing documents, and enhancing internal search and support. During peak tax season, Intuit employs 20,000 employees to provide advice to customers, resulting in 25 million conversations between customer agents and customers. To extract insights from these conversations and increase agent productivity, CIO Rajan Kumar has been employing AI/ML to provide automatic responses. Kumar’s team is now exploring and implementing a similar chatbot and user interface to provide support for internal employees around IT help desk, HR and procurement questions related to the employee experience.
The top generative AI use cases that MSDS attendees are prioritizing are answering customer queries, summarizing documents, and enhanced internal search/support
Driven by accelerated customer expectations, KeyBank developed a virtual assistant, called MyKey, to connect customers to the contact center and intelligently route support questions to staff faster and more intuitively. CIO Amy Brady has already seen value realized from these digitization efforts, including improved revenue, delivering more to clients with self-service, and improving the job of support agents while reducing turnover in support centers. She shared how improving the agent experience reduced uncertainty around automation. “We can be aspirational and get people engaged, driven by the impact,” she said.
Evolving their approaches to talent development
The rapid rise of generative AI has reignited conversations about how technology will change the way we work. It’s early days, but it’s becoming clearer that successful enterprise adoption will require not just new tools and processes, but also new skills and mindsets. Because generative AI doesn’t require users to know how to code, and doesn’t always require technical experts to drive these applications, the talent paradigm is changing. The shift is prompting technology leaders to reassess talent strategies and the skillsets required to prepare companies to be future ready.
Frustrated with many existing corporate education tools, Mars Global Vice President Shubham Mehrish and his team set about rewriting the playbook to create a more digitally savvy workforce. Mehrish is focused on education at every level of the organization, both top-down and bottom-up, and uses a range of educational and storytelling approaches to communicate with different stakeholders. The rise of AI is also prompting him to think differently about what he is looking for in technologists. Some of the key traits that he believes will mark successful candidates moving forward include curiosity, collaboration, and experimentation.
About one third of MSDS participants said that they are focused on general awareness and basic education in their AI talent development programs
Paramount CIO Lakshman Nathan reflected on the possibility that many companies won’t necessarily need data science or machine learning experts to drive AI applications, changing the way he approaches talent strategy. He is also working to increase general awareness of AI across the organization, including re-educating teams on technologies and processes that already exist inside the organization. “Business users are technologists now,” Nathan said. To increase general AI awareness, Nathan’s team set up a central site for everyone at the company to understand the AI process and get on the same page. The effort is collaborative across security, privacy, and technology teams to evaluate and expedite best use cases.
Aligning AI initiatives to business strategies
In order to generate the best value out of AI, technology leaders have to take a strategic approach aligned to business strategy. While there are many potential use cases for AI, technology departments are in a key position to assess the current and future state of AI-enhanced organizations tailored to specific business goals and industry requirements.
Assessing the best AI strategies to generate value requires thinking about the overall ecosystem and value chain. At NRG Energy, Chief Data and Technology Officer Dak Liyanearachchi is having the Data organization and the IT organization pull data together to focus more on the cost-benefit analysis: “will it generate the value we want?” At the same time, Liyanearachchi is evaluating the role that AI and generative AI will play in shaping the energy industry. He said that AI and technology enables his teams to focus more on the demand side of the energy grid and drives services to create better transparency around energy consumption for customers and households.
CIOs have to make sure they have the basics down before investing in new transformation. To prepare for tackling generative AI strategy and change management, Western Digital’s CIO Sesh Tirumala is looking at two buckets: perform and transform. He emphasized that leaders “get the keys to have a transformational agenda only if you are doing a good job in your perform.” After aligning on the fundamentals and the forecasting view, leaders can prepare their organization to be data-driven with action- and decision-making moving forward. “We don’t just manage for today and yesterday, but align on where we need to be [in terms of] talent strategy, outsourcing strategy, and IP […] to think about the problems of the future. How do you prepare and inspire the organization to look 3-5 years out?”
The majority of respondents at the Metis Strategy Digital Symposium indicated that they are either developing/defining AI strategy or implementing AI strategy across some teams
Rising to the C-Suite sits atop the list of career aspirations for many professionals, both inside and outside technology. No two career journeys are exactly the same, and those who have reached the level of the CIO, COO, and the like all have a unique story to tell.
On the Technovation podcast, Peter High, President of Metis Strategy and author of Getting to Nimble, interviews C-level technology executives across industries on a number of topics, including how they got to where they are today and what they see as difference-makers in their careers.
In this video, the following executives share their “secrets to success:”
See below for the full video and a list of key takeaways.
Mentors and coaches provide many benefits to professionals during their careers, providing candid advice while also keeping them grounded and on track. Michelle Greene, Chief Information Officer of Cardinal Health, says she has been intentional about having a mentor to guide her in her leadership role and help create a support system for her development and well-being. She notes that we pay for trainers when we want to get in shape, so why not invest in a coach to guide professional development? “If you’re serious about your career development, you have to embrace that.”
Similarly, among many things, mentorship has taught Rahul Jalali, Chief Information Officer of Union Pacific, to set “impossible goals” and work to develop his career beyond what you might have seen for yourself on your own.
“Jump and trust that the safety net will appear,” says Cindy Hoots, Chief Digital Officer & Chief Information Officer of AstraZeneca. She attributes her success in part to being open to the opportunities that were presented to her and saying yes to different roles she was asked to do, even if they weren’t something she “wanted” to do at the time. As she reflects on these roles, they now serve as some of the most pivotal ones in her career.
Similarly, Rima Qureshi, Chief Strategy Officer of Verizon, suggests not rigidly planning out a career trajectory, but rather seeing and taking opportunities as they come. “They take you in a direction that you may not have expected.”
It may sound obvious, but it bears repeating: leadership requires an ability to constantly listen and learn. In that spirit, Ramon Richards, Chief Information Officer of Fannie Mae, encourages leaders not to hesitate to ask questions. “If there’s something you don’t understand,” says Ramon, “you’re probably not the only one.”
Ashok Srivastava, Chief Data Officer of Intuit, suggests that the ability to listen to each other is a critical way of learning. “We have to be able to accommodate other points of view, and we have to be able to grow from those interactions.”
Within an organization, the single most important asset is talent. People build solutions, interact with customers, and drive the business. Leaders have a responsibility to develop talent and foster a collaborative culture. “Ultimately, 90% of my job is people,” says Teddy Bekele, Chief Technology Officer of Land O’Lakes, “It’s unleashing that power in the people who then can go do the work.”
To be successful in a leadership role, it’s critical that you understand your team and prepare them to operate in a dynamic environment. Rob Mills, Chief Technology, Digital Commerce, and Strategy Officer of Tractor Supply Company emphasizes this point. “That’s what makes a great leader,” says Rob. “Understand the team and how they’re willing to embrace and accept change.”
The success you find in your career will be easier to attain once you find your passion. “Figure out what elements of your job are not just a job,” suggests Neal Sample, former CIO of Northwestern Mutual. “Figure out what it is that makes you excited about it.” A role that ignites that internal drive will inevitably generate commitment and keep you on pace for success.
Kevin Vasconi, CIO of Wendy’s, agrees, noting that passion comes through in the work product. “If you get up too many days and you’re not enjoying what you’re doing,” he says, “you probably should try to find something else to do, because life’s too short, right?”
For more insights into the secrets to technology leaders’ success and other anecdotes from their career journeys, be sure to check out the full podcast episodes and YouTube channel.
Metis Strategy President Peter High joined Joel Beasley on the Modern CTO Podcast to discuss why the winning strategies in the future of work aren’t clear yet; why tech leaders should never commit to one-way doors; and how Domino’s avoided becoming the next Blockbuster.
Listen to the episode here:
Check out the Modern CTO Podcast here.
Produced by ProSeries Media
Marta Zarraga is a seasoned chief information officer, having held the post at Aviva, Vodafone, and British Telecom. In February 2021, Zarraga joined Capital Group, a 90 year old financial services company that manages more than $2.3 trillion in equity and fixed income assets for millions of individual and institutional investors around the world. As others who have taken on new posts in the past year during the global pandemic, this has been an unusual experience for Zarraga, as she is operating in quarantine, unable to meet in person with her new colleagues. The situation is even more unusual in that she is, for the time being, based in London, whereas Capital Group’s headquarters is in Los Angeles.
When asked how her priorities changed during the pandemic, Cathy Bessant, the Chief Operations and Technology Officer of Bank of America said, “It’s hard to remember where we were prior to the pandemic!” Much has changed for everyone, but for a technologist who leads a team that numbers nearly 100,000, there are silver linings to the crisis. “We were used to trite sayings, like, ‘We are living in a digital world,’ but it has played out,” she noted. “Now we are.”
Technology has been a savior of sorts. Companies have leaned on their digital revenue streams as physical revenue streams have dried up and leveraged technology to collaborate and remain productive. But it has not been a panacea. “Technology is the path forward, but we have a keener understanding of its limitations, as well,” Bessant said.
In a recent poll of multiple hundred CIOs to understand how many of them anticipated spending levels on “digital transformation” on a par with, higher, or lower than 2019, nearly 80% of responses indicated that they would have a higher spending level in 2020 on digital transformation initiatives. This is remarkable given the need for cost containment in light of the pandemic and the economic crisis that it has created, but it is driven by the fact that those companies that transformed their operations and their ability to derive digital revenue streams earlier are the companies that have done best during this time of crisis. Executive teams of most companies now realize that this needs to be a priority. Cut costs elsewhere but use some portion of that savings to invest back into further digital transformation.
Michael Smith, the Chief Information Officer of Estee Lauder, brought together a group of technology executives for a conference the day following George Floyd’s death. Given the terrible circumstances of his demise and the subsequent protests in the wake of the tragedy, the technology topics that the group planned to discuss did not seem so meaningful. Ralph Lauren’s CIO Janet Sherlock decided this was a good time to talk about how the gathered executives could be agents for change. Inspired by Sherlock’s comments, Smith decided to activate the ideas, reaching out to his network, fleshing out the ideas further. Earl Newsome, the CIO for the Americas at Linde Inc. was a member of the original group and a primary architect defining the approach.
