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This article was originally published on CIO.com by Metis Strategy Partner Chris Davis, Managing Director Tony Qamar, and Senior Associate Grace Cozier.
CIOs are under pressure to deliver on AI’s promise. Yet history shows that many digital transformations have underdelivered — not because of strategy, process or technology, but because of people. Without engaged, enabled and aligned employees, even the most promising AI initiatives will stall. Models may be built, but they won’t be trusted or adopted. Workflows may be reengineered, but without buy-in, they’ll sit unused.
At Metis Strategy, our work alongside technology leaders, driving some of the world’s most complex transformations, has resoundingly taught us that success is always people first. The same lessons apply today as organizations pursue AI-powered transformations: those that succeed put people and culture at the center. Culture shapes every element of the operating model — what decisions are made, how decisions are made, how resources are prioritized and how quickly the company adapts.
Despite strong intentions and significant investments, many transformations falter because leaders misjudge where the true risks lie. A common failure pattern is over-indexing on technology or process while neglecting people. New AI platforms or workflows are often launched with great fanfare, but without engagement, enablement and alignment, employees struggle to adapt and value goes unrealized.
As the ADKAR framework highlights, sustainable change requires more than a solution — it requires awareness, desire, knowledge, ability and reinforcement at the individual level.
Another pitfall occurs when transformations become process exercises rather than engines of business value. When initiatives are framed as IT-only or designed around governance for its own sake, they lose relevance and fail to inspire the commitment needed for lasting change.
Transformations also stall when priorities are scattered or poorly communicated. Without enterprise-wide alignment, programs become optional, teams are spread too thin and execution suffers. In these cases, even well-designed AI strategies cannot deliver impact.
Finally, cultural resistance or a lack of trust can quietly derail transformations. Employees who do not see how AI initiatives align with their own incentives may disengage, breeding fatigue and undermining momentum. Without trust in data, models and leadership, adoption falters no matter how advanced the technology.
For CIOs, avoiding these patterns is essential. The organizations thriving in the AI era are those that design transformations with people and culture at the center from the very beginning. Through our client work, we’ve identified four cultural elements that consistently shape transformation outcomes — and four actions leaders can take today to strengthen them.
Successful transformations align operating models with customer needs. Too often, companies define themselves as “sales-led” or “product-led” and allow that orientation to drive key decisions. While this can create enterprise clarity, it risks sidelining customers or alienating parts of the organization.
In contrast, enterprises that adopt a true customer-first approach build resilience and agility across functions. Their operating models align incentives, prioritize experiences and ensure teams move in step with market needs. As explored in Achieving product success: A five-step framework for customer-centric design, an article written by Metis Strategy’s own Andre Lopes de Carvalho, organizations that embed customer centricity into their design and delivery processes create more value and are better equipped to sustain transformation.
Revisit your mission, values and incentive structures. Ensure they reinforce a culture where the customer is the anchor for decision-making at every level and for every department.
Digital and AI transformations are demanding. Employees must adapt to new ways of working, acquire new skills and deliver against rising expectations — all while managing day-to-day responsibilities. Without meaningful investment in people, fatigue and disengagement set in, jeopardizing transformation success and putting millions of dollars of investment at risk.
Leading organizations counter this by embedding continuous learning into their cultures. Targeted learning and development (L&D) programs, aligned with transformation priorities, not only upskill employees but also strengthen commitment to shared goals. The best programs address both business outcomes and personal growth — answering “what’s in it for me” alongside company goals.
Provide protected time and resources for development. Tie L&D investments directly to transformation outcomes to ensure employees are motivated and equipped to deliver. Acknowledge that meaningful learning requires space — even during working hours.
Leadership sets direction, but decision-making structures determine speed. Transformations falter under traditional command-and-control models, where approvals and escalations slow progress. The fewer people responsible for making decisions, the slower progress will be made.
Our experience shows that pushing decisions closer to the problem accelerates execution, improves accountability and fosters innovation. Empowered teams make better, faster choices — particularly when leaders set clear guardrails and reinforce trust. A decision-making framework, for example, clarifies which choices can be made locally and which warrant escalation, enabling faster, distributed decision-making.
Reduce layers of approval and empower small, cross-functional teams with decision rights. Ensure leadership behaviors reinforce empowerment, not control.
No transformation follows a straight path. Markets shift, technologies evolve and customer expectations change. AI adoption in particular requires experimentation — testing models, validating outcomes and adapting quickly to advances. Thriving organizations build cultures of experimentation where teams are encouraged to test, learn and adapt at speed.
We’ve seen this approach succeed when companies create the time and structure for experimentation, whether through dedicated capacity, lightweight governance or innovation programs. Not all experiments can succeed, so rather than penalizing failures, promote a culture that encourages learning from them. The result is not just innovation but resilience — a workforce confident in navigating uncertainty. As Jamie Engstrom emphasized in Technology, talent and transformation at caterpillar, curiosity and collaboration ensure experimentation is both grounded in business value and disciplined execution.
Normalize test-and-learn practices across teams. Protect capacity for experimentation, ensure lessons are shared and reward adaptability as much as execution.
Every transformation involves new strategies, processes and technologies. What ultimately determines success or failure is whether leaders place people and, by extension, culture, at the center. People shape decision-making, innovation and execution; they are the connective tissue of the operating model. CIOs who recognize culture as a true differentiator are better positioned to navigate complexity, make effective decisions and deliver sustained impact.
Wolters Kluwer’s ongoing transformation from a traditional publishing business to a cloud-first, AI-driven enterprise illustrates how people and culture drive successful AI-powered transformations. When we spoke with CIO Mark Sherwood, he discussed how customer centricity is reinforced through business relationship managers (BRM) who bridge technology and business units, ensuring digital investments are aligned with customer and market needs.
Learning and development are emphasized as employees build new skills in cloud, AI and data governance, enabling them to adapt to rapidly evolving technologies. Distributed decision-making is strengthened by embedding BRMs to bring tech and business closer together, ensuring alignment and enabling smarter choices on priorities and resources. Agility is fueled by a test-and-learn mindset, with experimentation balanced by strong ethical AI practices and disciplined measurement.
By maintaining a strong culture and people-first approach, Wolters Kluwer has accelerated its evolution and positioned itself as a leader in delivering trusted, technology-enabled solutions across industries.
CIOs today face constant change — none more urgent than the rise of AI. Shifting customer expectations, new competitive threats and accelerating disruptions are magnified in the AI era. Anchoring transformation in people and culture is what turns volatility into opportunity and lasting advantage.
For CIOs, the mandate is clear: build operating models that not only work today but also adapt continuously for tomorrow. That requires embedding four cultural practices at the center of every digital and AI transformation:
When CIOs champion these actions, they move beyond technology deployment to transformation that is embraced, scaled and sustained. Put people first and digital and AI transformations become not only achievable, but sustainable.
This article was originally published on CIO.com by Metis Strategy Partner Michael Bertha.
The days of treating corporate and digital strategy as separate entities are over since their convergence has become central to data-driven transformation. Yet very few companies believe in it strongly enough to restructure themselves around that reality.
“Investments and behaviors follow org design,” says Sandeep Davé, CBRE’s chief knowledge officer. “In the era of AI, the world requires integration, not isolation.”
For Davé, becoming chief knowledge officer represents more than a role change. It reflects a deliberate reframing of how CBRE approaches technology, strategy, and data.
The company, which serves clients in more than 100 countries and offers services ranging from capital markets and leasing advisory to investment management, project management and facilities management, has long been strategy-led. By elevating Davé from CDTO into a newly created role that unites corporate strategy, research, and data with the overall technology direction, CBRE is signaling that these functions are inseparable in shaping the company’s future.
Davé points to three forces behind the move.
The first is scale and complexity. With our scale — the clients, asset classes, services, and global reach — CBRE needed a way to harness and translate its vast data assets into knowledge and insights. “If we can see every property we touch, and convert that data into knowledge and insights, we create a formidable competitive moat,” he says.
The second is AI as a differentiator. “The thing that distinguishes what you can do with AI is data,” he says. “If AI delivers the transformative impact it promises, then your data foundation, governance, and strategic alignment will determine your rate of success.”
The third is organizational maturity. After years of scaling cutting-edge technology across the business, including the latest AI offerings, CBRE now has the platforms, infrastructure, and cultural readiness to take a bold next step. Functions that once operated in isolation are being reshaped.
Research offers a clear example of that reshaping. “We’re elevating our global research function by streamlining processes and improving outcomes,” Davé says. “Now, by applying AI and automation, we’re increasing efficiency while also significantly enhancing the quality of our outputs.”
The unification of functions reinforces a central truth in broad technology and AI adoption that context is king. Without it, even the most advanced tools deliver limited results. When technology, research, and strategy move together, the impact can be transformative.
Evidence of that transformation is already visible at CBRE. In facilities management, predictive analytics now inform repair-versus-replace decisions, cut duplicate work orders, and optimize service delivery. And across the enterprise, more than 65,000 employees use Ellis AI, the firm’s gen AI platform, to access trusted data, generate insights, and automate routine tasks.
“Tools alone don’t bend the cost curve,” says Davé. “It’s important to understand the environment, intent, and nuances that shape intended outcomes. When we combine the richness of our data with the insight of our people and the discipline of strategy, AI stops being a showcase of use cases and becomes a driver of real market differentiation.”
CBRE’s establishment of this position, particularly under Davé, signals a deliberate strategic move that says consolidating key functions under one remit is more purposeful and productive.
Conway’s Law is a useful reminder here whereby systems often mirror the communication patterns and structures of the organizations that build them. Fragmented companies and cultures yield fragmented technology solutions. For leaders serious about capturing the full value of AI, progress will demand more than governance frameworks or technology investments. It may require rethinking reporting lines, incentives, and collaboration models.
Convergence isn’t just an idea, it’s an operating model. And the future of AI-driven transformation will be shaped not only by the technology deployed, but how organizations choose to design themselves around it.
For the first time in history, the workforce is no longer exclusively human. Digital teammates – AI systems that reason, act, and collaborate – are stepping into roles once reserved for people. They don’t clock in, they don’t get tired, and they don’t just follow instructions. They execute, adapt, and learn.
This shift is not about efficiency alone. It challenges the very design of organizations and marks the start of an AI-powered workforce transformation: what work belongs to people, what belongs to machines, and how leaders optimize the two.
Leading organizations are no longer experimenting with AI on the margins. They are embedding digital teammates directly into core workflows as part of a broader AI-powered workforce transformation, like handling customer support, testing product prototypes, and triaging IT service requests.
AI agents represent the next evolution of digital labor. Unlike task automation or copilots, which assist individuals with a narrow task or within a workflow, AI agents assume defined roles, act with greater autonomy, and can interact directly with systems and people. This makes them colleagues, not just assistants.
The payoff is more than efficiency: it reshapes the very design of the workforce. When AI can reliably take on a portion of work once reserved for humans, leaders must ask harder questions: Which tasks should remain the domain of human judgment and creativity? Which can be automated or augmented by AI? And how must teams and departments be redesigned to reflect this new mix?
This is where CIOs step in.
For decades, CIOs have been asked to deliver platforms, tools, and integrations. With the rise of digital teammates, the mandate expands: reimagine the workforce itself.
This shift requires a new kind of leadership. CIOs must take on responsibilities that mirror those of a CHRO, ensuring digital teammates are recruited, trained, integrated, and governed with the same discipline applied to human colleagues.
This is what it means to act as the CHRO of AI: extending workforce discipline to a new class of digital teammates. Talent acquisition becomes capability selection. Learning and development becomes fine-tuning. Org design becomes orchestration. Performance management becomes governance. Change management becomes enablement.
The CIO’s role, in partnership with HR, is to redesign departments and teams around this new mix of talent.
This reframes the CIO’s role from tool deployer to workforce architect. Technology leadership and people leadership are no longer separate. Together, CIOs and CHROs must redesign teams and departments around the optimal mix of human talent and technology, clarifying which tasks demand human judgment and creativity, and which can be automated or enhanced by AI. Organizations that embrace this expanded partnership will build more adaptive, resilient workforces, while those that cling to pre-AI structures will struggle to compete.
Every workforce depends on performance management. Digital teammates are no different. CIOs must design the frameworks, processes, and accountability structures that ensure AI colleagues contribute reliably, safely, and in alignment with business priorities.
It begins with clarity. Just as CHROs define competencies and goals for people, CIOs must set criteria for AI effectiveness – accuracy, fairness, security, and resilience. Oversight must then be institutionalized through a dedicated team or cross-functional governance council empowered to manage evaluations and address complex questions.
From there, the process becomes a cycle of measurement, feedback, and action. Models are reviewed, failures investigated, and input gathered from the employees who work alongside them. High performers are promoted and scaled; weaker ones are reassigned or, if unfixable, “fired.”
As we argued in our article Beyond the Buzzword: Treating AI as a Business Capability, success comes not from isolated pilots but from embedding AI with the same rigor as any other enterprise capability, across people, processes, tools, and measurement. Centralized governance is critical to doing this well. Enterprises need a unified platform to deploy, monitor, and audit AI agents, manage access to sensitive data, and enforce oversight in key workflows.
Governance, framed this way, is not about control. It is about performance management; treating digital teammates with the same discipline applied to people, and ensuring they remain trusted contributors to the enterprise.
Drug maker Moderna offers an early example of this shift. In 2024, the company merged its digital and HR functions under a Chief Digital & Human Capital Officer. The move reflected a simple but powerful truth: humans and AI together form a single workforce. This was accompanied by a shift from “workforce planning” to “work planning,” redesigning teams based on what tasks are best done by people versus AI.
Through a partnership with OpenAI, Moderna has built over 3,000 tailored GPT agents, embedded across clinical, regulatory, and HR workflows. Some function like digital teammates in drug development, helping with dose selection in clinical trials or preparing regulatory responses. Others operate as virtual HR analysts, routing employee questions to the right processes, essentially automating what used to be a junior HR role.
The lesson is clear: in the AI era, workforce and digital transformation are inseparable. CIOs who align them will lead while those who separate them will lag.
The rise of digital teammates is not a distant future, it is an unfolding reality. CIOs don’t need to wait for new titles or reorganizations. They can begin today by laying the foundation for human–AI collaboration.
Immediate steps include:
We saw this firsthand in our work with a Fortune 150 SaaS company. Together we developed a GenAI-powered support agent that now resolves 40% of routine IT service desk issues. By embedding the agent directly into ITSM workflows, the company reduced ticket volume while freeing IT staff to focus on complex cases, demonstrating how governance, integration, and workforce redesign must come together for AI teammates to deliver measurable ROI.
Digital teammates are not a side project. They are reshaping the very structure of work. The organizations that succeed will be those that integrate AI colleagues with the same rigor, culture, and leadership applied to human employees.
Frontier firms are already moving in this direction by flattening hierarchies, embedding digital teammates into core processes, and empowering humans to focus on the uniquely human work of judgment, creativity, and leadership. For CIOs, the mandate is clear: step into the role of CHRO of AI in close partnership with HR, and design the workforce of the future.
At Metis Strategy, we work with technology and business leaders to put these ideas into practice – aligning strategy, governance, and culture so digital teammates become trusted contributors. If you are exploring how to integrate AI into your workforce, reach out to learn how we can help you move from pilots to scaled impact.
Now a household name in personal finance, Intuit was founded in 1983 by Scott Cook. The company’s four decades of success — the company reported 2022 annual revenue of $12.7 billion and a portfolio of valued products including TurboTax, QuickBooks, Credit Karma, Mint, and Mailchimp — has been possible in part by the company’s dedication to innovation. Innovation is necessary for modern businesses to maintain a competitive advantage, meet evolving customer needs, and attract top talent. Prioritizing innovation can also improve the IT-business relationship by positioning the IT organization as a partner that is uniquely suited to evaluate ideas and pursue those most likely to succeed.
Two conversations on Peter High’s Technovation podcast with Intuit’s Chief Information Security and Fraud Prevention Officer, Atticus Tysen, and Chief Data Officer, Ashok Srivastava, show how Intuit has reinvented itself through IT-driven experimentation driven by a desire to solve real business problems and foster a strong IT-business partnership in the process. These interviews show how a formalized test-and-learn process, a set of practices formalizing the steps taken to ideate, conduct pilots, analyze results and scale valuable ideas across an enterprise, can be used to systematically scale innovation and deliver a range of benefits. Among them:
–Change the culture of the IT organization to encourage more frequent ideation and support team members in voicing ideas they might not have previously
–Empower the IT organization with data and agility that allows it to show up as a true business partner
-Increase the influence of the IT organization to build trust and credibility with the business
-Eliminate silos and encourage expansive thinking to ensure the creation of durable, enterprise-grade solutions
Intuit’s innovation journey highlights these improvements in action, as we’ll see below. We will also share Metis Strategy’s 10-step test-and-learn process that you can implement in your own organization.
“At Intuit, experimentation is everyone’s job,” said Brad Smith, Intuit’s former Executive Chairman. Building a culture of experimentation and innovation requires creating a safe space to allow risk-taking and encourage more people to bring ideas to the table. Intuit’s IT organization prides itself on its hypothesis-driven testing culture designed to pursue new ideas with clear business outcomes rather than rely on legacy solutions, bolstering the IT organization’s strategic value.
Solidifying a test-and-learn process positions IT organizations to play a more active role with business teams, understand customer needs, unlock innovation opportunities, and change the culture of IT from reactive order-takers who “just” keep the lights on to partners who help shape the future of the enterprise. At Intuit, the test-and-learn process is guided by the company’s two innovation competencies, Customer Driven Innovation and Design for Delight, which drive all solution development and ensure strategic focus throughout the ideation process. These defined principles, outlined and enforced by the Intuit labs, help narrow down and develop winning ideas by ensuring new solutions unlock value and solve real problems.
IT leaders must be change champions to ensure the successful adoption of a test-and-learn process and the subsequent shift in culture required to improve the IT-business partnership. Broad participation in the test-and-learn process happens when the process is accessible and engagement is encouraged across all roles and tenures.
Intuit’s technology leaders incentivize innovation by giving employees unstructured time for ideation and solutioning, which fosters their participation in the test-and-learn process and refines the company’s ideation muscle outside of day-to-day responsibilities. Other incentives used to ensure test-and-learn participation include the Scott Cook Innovation Awards, which recognize employee innovators; mentorship programs to guide new participants through the test-and-learn process; rotational development programs to upskill employees; and workshops to refine critical thinking skills.
By enabling test-and-learn experimentation, IT leaders can begin to change their organizations’ culture and empower the IT organization to become a true business partner. Intuit notes that the test-and-learn culture has enabled a durable competitive advantage that allows the company to differentiate itself from competitors while focusing on what matters most to its customers.
In a recent survey, 63% of CIOs reported that they struggle to communicate IT’s business value to business partners. Formalizing a test-and-learn process can improve that communication by giving IT leaders the data needed to tell their innovation story and tie new ideas to tangible business outcomes.
Test-and-learn experimentation produces data surrounding the feasibility and value of scaling an idea. Ideas that are ultimately chosen to scale are backed by data on their projected success and business impact. IT organizations can also provide their business counterparts with data on risk mitigation and projected costs based on the initial testing.
Tysen names data as the primary enabler for successful test-and-learn experimentation as it creates opportunities to take calculated risks. Tysen and Srivastava work together to break down data silos and democratize data so teams can more effectively derive and deliver insights.
Pairing test-and-learn with agile delivery methods can promote a culture that rewards failing fast, iterating, and delivering value in the shortest sustainable time. Intuit focuses on lessons learned from experiments rather than if one was a success or a failure.
Intuit’s innovation competency, Design for Delight, further showcases agile ways of working by prioritizing constant customer feedback, quick prototypes, and iterative solutions to ensure initiatives pursue maximum customer value.
Since experimentation often happens on top of day-to-day responsibilities, transparent and realistic expectations must be set to prevent under-delivery or delays and preserve working relationships. Tysen manages business expectations by ensuring that the IT organization outperforms traditional IT metrics as a prerequisite for experimentation. Operational excellence builds trust between IT and business partners and creates space for test-and-learn experimentation that builds that trust further via successful ROI-generating innovation initiatives.
The typical IT delivery muscle must be refined, and often rebranded, to position the IT organization as an innovator rather than an expensive bottleneck. Tysen says his organization builds credibility with the rest of the business by leveraging business metrics and KPIs, not just IT metrics, when evaluating ideas generated through the test-and-learn process. Applying business metrics to IT-generated ideas ensures that the IT organization and the business are being held to the same standard and can help ensure fair appraisal and understanding of each initiative’s value.
In a recent survey, fewer than 5% of CIOs reported that they spend time talking about business outcomes or measuring the business outcomes created by the technology they deploy. This is a significant oversight preventing buy-in and limiting the IT-business partnership. Tysen emphasizes the importance of listening to partners to ensure his organization accurately understands their problems so he knows what is needed to create relevant soultions. The consistent use of business metrics across Intuit also ensures the appropriate acknowledgment of IT’s test-and-learn successes.
Test-and-learn experimentation breaks down traditional business silos and seeks to prevent ad-hoc ideation, eliminate repetitive solutioning, and facilitate cross-functional collaboration. It also promotes enterprise thinking, a practice of monitoring cross-functional requirements, scalability considerations, and long-term needs such as reducing future rework and technical debt.
Srivastava notes that Intuit’s process for test-and-learn experimentation relies on conducting deliberate tests that solve specific and identified problems rather than needless, temporary solutions. Test-and-learn experimentation not only brings MVPs to life with speed but also facilitates deliberate and intentional conversations about long-term considerations and dependencies during the product creation process, ensuring that the final product meets as many consumer needs as possible.
When working with clients seeking to streamline and scale innovation, we use a 10-step test-and-learn process to govern the intake of ideas, manage stakeholder expectations, accurately reflect capacity, and capture data to inform a solution’s journey. This process helped a recent client identify and eliminate silos that hindered collaboration while elevating the IT organization to the status of a business partner rather than an order taker.
Implementing a test-and-learn experimentation process enables an organization to narrow an infinite number of ideas and pursue only those that will deliver the most value. The IT organization is uniquely positioned to facilitate this process and help the business identify winning ideas due to its digital testing capabilities and data collection methodologies.
Working closely with business partners can help teams across the organization avoid placing big bets on ideas that may drain their resources without delivering the needed value. Prioritizing resource allocation based on test data and iterating throughout the solution development process creates a virtuous cycle where the business will increase its speed to market for winning ideas while guaranteeing maximum customer satisfaction.
The benefits that come from implementing a test-and-learn process will not be realized overnight. A structured approach to change management and user adoption is needed to ensure an effective transition. It makes sense to start small. With support from internal change champions, consider piloting a beta test-and-learn process, secure quick wins, and use that momentum to facilitate a broader rollout.
Once adopted, an enterprise might face execution hurdles that prevent maximum value realization. For example, a company may not have the discipline needed to define the hypotheses that drive testing, resulting in the creation of tests that do not produce the needed information.
Alternatively, existing data collection and analysis capabilities may not be sufficient to derive conclusive test results. An enterprise may also suffer from “analysis paralysis,” which can create stagnation when a test fails and lacks ownership over revisions. To learn more about avoiding these experimentation pitfalls, see this article that outlines how business experimentation frameworks can help mature a test-and-learn culture across an enterprise.
As we recently passed the two anniversary of the pandemic, necessitating those of us who could work remotely to primarily do so, quite a bit has changed. Some companies have begun to return to office work on a hybrid basis, and roughly three-quarters of companies suggest that the path forward will be hybrid.
Whereas in 2019 and years prior, all work was assumed to primarily take place in an office, now there is optionality. Employees have different visions for what works best for them. Whereas one employee may long for more work in the office, others never wish to step foot in an office again, avoiding commutes and maximizing time with family in the process. These differences of opinion run the risk of creating conflict. To alleviate that possibility, a framework can be helpful. That framework can guide employees to determine together when to work in an office. With that in mind, here are five Cs to determine when work is best done together in an office:
A team may choose to connect when team members from different cities happen to be in the same city. This offers opportunities to bond, to break bread and to share experiences.
Connection may also come in the form of a firm gathering. Especially for firms where most work will be done virtually, outside of the confines of an office, some have elected to have all firm gatherings or department gatherings either in a city where an office hub exists or at a destination, such a Miami during the winter or a hiking destination during the summer. These are opportunities for connection that bond teams together. Colleagues can get to know each other outside of the work setting, and the next gathering may be the light at the end of the tunnel that keeps them looking forward to time with the firm.
Given the emphasis on virtual work over the past two years, there has been much call to evaluate where creative collaboration is best done. Most research suggests that when teams are called upon to create they do so best in person. Though online tools such as Miro and Mural offer worthy alternatives to the traditional white board, brainstorming in the same room together continues to offer greater chances to catch lightning in a bottle and draw out the best ideas for the company. True creation often entails developing something new. This might be a new innovative product, for example. Again, bringing together a cross-functional team in the same room where each can easily hear from each other, note all that is happening, and the like is the fastest path to success.
The office setting is often best suited for collaboration beyond creation, as well. One can think about a linear path in the collaboration process. As a new project or initiative is identified, the kickoff may best done in person. This collaboration can help mete out a plan, determine who will be responsible for what, and what sub-teams might collaborate on which details. There will likely be a period where individuals will have solo work to accomplish before the next collaboration is necessary. Thus, through the life of the initiative, it will be appropriate to work independently for a period and then to collaborate in person together. This can be a force multiplier to productivity, as during periods where independent work is appropriate, one can avoid the commute, perhaps leveraging a bit of the time that would have been spent doing so to drive the independent work to its conclusion.
At a time when so many people are leaving jobs as part of the so-called great resignation, it is all the more important to invest in one’s people. Better coaching, counseling, and career planning are key investments to make. An in person meeting is often best to read reactions to guidance provided, praise given, and constructive criticism proffered. These are conversations where trust can be won or lost, and it is best to be in person for more of them, if possible. Ironically, it is often the youngest members of our teams who appreciate the importance of in person career planning least but benefit the most from such guidance. It must be proven to them that these conversations are worth their while with the results that they might garner from more explicit planning sessions.
Last among these factors is the need to celebrate together. During the period of virtual work primarily, where meetings tended to stick to agendas that fit in 30 or 60 minute windows and then each team member spread like seeds to the next series of meetings with other people, many took for granted the need to celebrate all that we accomplish along the way. When a project concludes, when promotions are announced, when quarterly earnings are made public, among many reasons to possibly celebrate, taking the opportunity to do so forges bonds, while also making explicit the accomplishments of the team.
None of this is to say that these five activities can only happen in offices. None should wait for everyone to be in the same place at the same time to happen, of course, but in the balance, these are activities that are best done in the office. The framework is clarifying. It articulates a means of cutting through conflicting opinions of whether to meet in person or not. One can imagine colleagues debating whether an activity should be done virtually or if it rises to the level to warrant a trip into the office. One could determine if the activity aligns with the categories given, and if so, make the call to do so. Hybrid work is tricky as we have the unleveling of the playing field in earnest, but by setting up some simple ground rules together with sound explanations of why the path has been chosen will ensure that you are building trust across the team for the long term.
Peter High is President of Metis Strategy, a business and IT advisory firm. He has written two bestselling books, and his third, Getting to Nimble, was recently released. He also moderates the Technovation podcast series and speaks at conferences around the world. Follow him on Twitter @PeterAHigh.
The fifth and final Metis Strategy Digital Symposium of 2021 is in the books. Thank you to the global CIOs, CEOs, and entrepreneurs who joined the conversation.
Looking to 2022, technology leaders said developing and maintaining strong cultures, motivating teams, and providing continuous learning and development opportunities are among their continued priorities. Also on the CIO agenda: maintaining agility and momentum following a period of significant digital acceleration. Additional highlights from the event are below. Check out our YouTube channel and the Technovation podcast in the coming weeks for recordings of individual panel discussions.
New ways of working enable agility and speed to market. CIOs noted that a continued shift to product-based operating models, paired with advanced applications of data and analytics, has led to greater enterprise agility. More nimble technology architectures also support more nimble operations.
Increased customer adoption of digital channels during the pandemic accelerated the shift to new team structures, roles and responsibilities and reinforced the need to deliver products and services to customers faster and with less friction. Michael Ruttledge, CIO at Citizens Financial, noted a 30% increase in the use of digital channels. Over the past year, his team has introduced more than 900 features in its mobile app. Citizens has leveraged advanced technology in those efforts, Ruttledge said, “but at the same time we’ve had to get that to market very quickly, and we’ve done that by changing our agile culture.”
Pairing new ways of working with agile, scalable technology architectures has helped the IT organization at Target move faster and deliver more value across the organization, CIO Mike McNamara said. Today, Target has hundreds of products across the business that can release updates daily or weekly. “The rate limiter is how quickly our business and our guests can absorb change rather than how quickly we can produce it,” McNamara said. “That speed and agility has just been a phenomenal benefit to the business.”
Fostering a strong culture is more critical than ever. As the war for talent intensifies and organizations embrace more flexible working arrangements, technology leaders are thinking about how best to foster a sense of connectivity and maintain innovative cultures as teams collaborate in new ways, both in the office and remotely.
Asurion CIO Casey Santos noted that her team is telling the company’s story in a more personal way, emphasizing the strength of their culture and technology, becoming more flexible, and relying on less formal recruiting techniques. Santos’ team is also training leaders at the company to be better coaches and sponsors so that they can help employees through their journey at the company. Asurion is also bulking up its internship, internal mobility, and rotational programs.
Underpinning many of those actions is a push to create learning and development opportunities for talent across the organization. As the pace of change continues to accelerate, “lifelong learning isn’t optional anymore,” said Sri Donthi, Chief Technology Officer at Advance Auto Parts. He shared the guiding principles he has followed while developing an engineering culture: creating a comfortable environment for employees to challenge themselves and excel; starting with the customer in mind while looking at the big picture; and keeping innovation top of mind. Donthi emphasized the need to lead with empathy and care, and encouraged fellow leaders to develop skills including crisis leadership, virtual leadership, and inspirational leadership.
Companies double down on upskilling and talent initiatives. Creating learning and development opportunities remains top of mind for CIOs in the year ahead, with 35% of participants noting reskilling or upskilling as their talent development priority in 2022, followed by enhancing employee experience.
Toptal Co-Founder and CEO Taso Du Val predicts that there will be a plethora of online courses that will allow employees to earn certifications. More meaningful content and a better user experience, among other factors, will make these programs more impactful than traditional education programs, he said.
Citizens Financial introduced academy programs that allow engineers to spend 10 days learning skills such as React, Java, Python, or learning APIs, CIO Michael Ruttledge said. The company also developed 38 different badging and certification programs across a range of technologies. At Discover Financial, the Discover Technology Academy runs a series of courses while also serving as a hub for multidisciplinary teams to share their knowledge and experience with others, encouraging collaboration and allowing innovation to scale more effectively.
Target CIO Mike McNamara said engineers at the company are expected to spend 20% of their time on learning and development, part of the framework Target has built to recruit, develop, and provide continued learning experiences for teams. He’s also proud that many leaders who have worked under his leadership have taken on CIO or senior executive roles at large companies around the world.
Common platforms enable data-driven customer experience at scale. Heading into 2022, leaders across industries continue to develop and refine platforms that allow their organizations to leverage analytics and AI across a broader range of products and services, deliver sufficient governance, and scale new solutions quickly.
At Experian, EVP & Global Head of Analytics and AI Shri Santhanam is leveraging a technical and commercial platform, along with the company’s vast troves of data, to develop more products powered by AI and machine learning. Common platforms allow Experian to bring in new data sets more easily and create more sophisticated models that give individuals, particularly those whose experiences may not have been reflected in traditional models, access to credit.
Anjana Harve, Global Chief Information Officer at Fresenius Medical Care, has focused on developing a platform that helps patients manage their care effectively and provides continuous insights throughout the user journey from early care to dialysis treatment. Through connected platforms, Fresenius can drive standardization, bring innovation and speed to end users, and guide workflows while providing the most relevant and personalized information for patients and clinicians.
Leaders continue to unlock new capabilities with data and analytics. Nearly 40% of attendees noted that they expect to see the most technology investment in data and analytics in the year ahead, and 71% noted that advanced AI is the emerging technology that holds the most promise for their organizations in 2022.
Discover Financial CIO Amir Arooni emphasized the importance of advanced AI in giving customers “actionable data that empowers them.” Applications of AI at Discover include real-time fraud detection and analyzing past spending data to advise customers on what to purchase and when, providing guidance on how to save more money and earn rewards.
Advanced analytics techniques are also making strides in the construction industry, which has begun to embrace technology as more digital tools, accessible via the cloud, went mobile. Turner Construction CIO Warren Kudman said the industry is “waking up to the value of data” and has used digital tools to visualize and manipulate environments virtually, reducing the likelihood of costly mistakes. Turner is also using data and ML to track and assess safety conditions at job sites, proactively identify interventions, conduct remote inspections, and track materials as they arrive on job sites.
Dean Del Vecchio, CIO and Chief of Operations at Guardian Life, discussed how the company is using data and AI to develop insurance products faster, easier, and with less friction for customers. Thanks to new tools and new ways of working, some processes that used to take 45 days have been cut to 30 seconds, he said.
Like so many companies over the past year and half, Ralph Lauren has had its resilience tested as a result of the Covid-19 pandemic. It had to shut down stores and offices, and had to advance efforts to better interact with customers and associates alike, safely.
Fortunately for the company, Janet Sherlock, who has been the chief information officer of Ralph Lauren for the past four years, initiated a number of initiatives that gave the company a leg up. Her purview is such that she has unusual influence for a CIO. She runs strategy and overall management of all of the technology including design conceptualization through to the point when products are distributed to either wholesale partners, the company’s stores, or directly to the company’s consumers. Her team is also responsible for store technology and the full ecosystem of in-product management and user experience. Additionally, Sherlock oversees all global digital platforms, marketing technology, data analytics, and data science. All of this is on top of global infrastructure, cybersecurity, IT risk, compliance, and privacy.
Among the fortuitous programs that were in place prior to the pandemic that aided the company’s transition during the pandemic was a hybrid flexible work arrangement called Flex Place. Upon this foundation, Sherlock’s team rapidly rolled out virtual appointment booking. Her team had already made significant progress on curbside pickup for customers. Completing its rollout ensured that the company could still do business through stores even if customers were unable or less willing to go in them.
“I think our biggest shift left efforts was probably in virtual stores,” said Sherlock. “We had been considering our approach to virtual stores before Covid hit but that was something that we pulled forward very quickly and aggressively. Our stores were such masterpieces, and the experience is so unique, we felt it was important to offer the world of Ralph Lauren to our customers, even if they couldn’t physically visit our stores.” Her team rolled out a rich virtual store experience and quickly integrated it with the company’s e-commerce platform so that customers could purchase certain products via hotspots directly from their virtual experience. “At this point, we have seven different virtual store experiences, and are continuing to build on the capabilities that we have in our virtual store environment,” noted Sherlock.
One of the thornier issues that Sherlock and team had to grapple with how to assist Ralph Lauren’s design and merchandising teams, each of whom relied and thrived on in-person collaboration. Sherlock’s team set up a design collaboration platform for them to use, and it proved to be a silver lining of the pandemic inasmuch as the teams developed new ways to work and collaborate. Now the design and merchandising teams anticipate an ability to continue to work both in person and virtually, adding flexibility to their work routines.
Another process that the company took for granted had to be done in person was the product approval process, which traditionally relied on in-person meetings to discuss milestones related to lines, styles, and fit approvals. It was long assumed that those involved had to be able to physically see and touch the material in order to make decisions. “We were able to leverage our 3D product development for the approval process, which also had the side benefit of streamlining the process,” said Sherlock. “We [also] had to create online experiences to replicate and replace our showroom visits, and support different virtual ordering processes for our wholesale partners.”
As Sherlock contemplated the future, she noted three strategic priorities: experiences, data, and automation. The overarching benefit of these foci should be greater nimbleness for the company. The experiences center around creating a variety of customer journeys and allowing customers to engage in the ways that best suit them rather than dictating how they shop and purchase products from Ralph Lauren. “Everything is interoperable between our online, our [marketing technology] and our in-store capabilities are blended together so we can create seamless experiences and we have some really cool ones planned for the future,” noted Sherlock.
Next, she believes data strategy will be a critical area of focus. “We’re being very deliberate about the overall data strategy for the core elements of data, things like our product data, our digital assets, our customer data, thinking strategically about where they’re stored, how they’re accessed and leveraged, how they’re maintained,” said Sherlock. “[This will impact not only] data analytics, but [it will allow Ralph Lauren] to serve up on a real-time basis things like personalization, real-time actions, real-time decision-making…Then, of course, it leads to our capabilities in advanced analytics and data science, which for us is a major area of emphasis and focus.” She refers to IT as the “connective tissue” of the enterprise relative to data, and that this is a discipline that will lead to better collaboration across the traditional silos of the company.
Sherlock believes that greater degrees of automation will improve the efficiency of all that IT delivers while further modernizing the practices of the company to better compete in the digital age. Sherlock and her team have implemented a variety of changes that have overturned decades of inherited wisdom about how business can be done, providing new benefits along the way. Necessity is the mother of invention, it is said, and many inventions have been created due to the necessities that the pandemic has driven.
It may seem strange to think of a technology or digital leader being responsible for aligning strategy across the enterprise. Since the inception of the CIO role, strategies were often created and then brought to them. They were not engaged in the strategic planning processes of the rest of the organization. Instead, they had to bring to life the outcomes of those strategies.
If you think about it, though, aside from the chief executive officer, only the chief financial officer and chief human resources officer has the breadth of purview comparable to a CIO or chief digital officer, and the technology and digital executives are increasingly involved in customer-facing activities in a way that the CFO and CHRO roles have not historically been.
Technology and digital leaders must recognize that they engage with the rest of the enterprise and the company’s customers, and that is rare if not unique. As such, they must leverage this advantage to a greater extent in fostering strategic alignment.
Strategic alignment means ensuring there is alignment from enterprise strategy to divisional, business unit, or functional strategy. This alignment is often misunderstood or lacking in companies, and that disconnect means wasted effort and money for the enterprise.
Further, a lack of well-articulated plans at the divisional level means the path to bringing those plans to life will be murky at best. For reasons of self-preservation and value-creation, technology and digital leaders must push for better.
Translating IT strategy from the enterprise level to the divisional level is important because it is at the divisional level where the work is done. Enterprise strategy typically calls out objectives related to revenue growth, cost efficiency, customer satisfaction, geographic expansion, product innovation and the like. It is the divisions of the company that determine how each of those will happen.
Let’s take revenue growth as an example. Growing revenue is vital to the health of a company, but each function — from sales and marketing to specific product or service areas — contributes in different yet important ways. The specifics of what each function will do needs to be formulated clearly to have teams go and find the new revenue through the various mechanisms available across the company.
Engage teams to conduct an analysis of strengths, weaknesses, opportunities and threats (SWOT). Such analyses are typically simple, easy to understand, and ensure that leaders can gather information quickly, easily and at the right level of granularity:
As you gather feedback from these SWOTs, it is important to categorize the feedback into topics like people, processes, product, brand, geography or market, finance, customers, organization or culture, competition, technology, vendors or partners, and the like. These form the vestigial versions of objectives for the enterprise or division.
Optimally, you should gather that feedback into a common framework of objectives, goals, tactics and measures.
Each objective should have a goal associated with it. This is a success metric that helps chart the path to success.
Using the same rather generic enterprise strategies, the goals might be defined as revenue growth (grow revenue by 15% in the next year), cost efficiency (grow costs at a rate 5% under revenue growth in the next year), customer satisfaction (improve customer satisfaction with our products from 70% satisfied to 80% satisfied in two years), geographic expansion (open 10 new offices in the coming year) or product innovation (introduce two, $50 million revenue products in the next year).
Try to limit the number of goals to two, as if you go for more than that, the strategy is less of a filter and is permeable to too many ideas.
Next, the digital and technology leader can brainstorm tactics with members of the enterprise or divisional team who are experts in the area noted by a given objective. As noted above, these are the various actions available to the company (or division) that help it reach the goal(s) articulated.
It is important to note that tactics should never include the name of a particular solution. The extent to which a project name or a vendor product is noted in a strategic plan renders it more important than it is. The action is one thing; the means of delivering the action are another.
You may believe that Salesforce is the solution you wish to use for customer relationship management, but better to articulate the need for CRM than to note the solution. The solution should be debated.
The tactics can be more plentiful, and during the brainstorming phase, definitely err on the side of more rather than fewer tactics. After the list is finalized, the tactics should be prioritized. The prioritization should be undertaken based on the perception of which ones are being pursued today, which ones are likely to be pursued in the near term, which will be undertaken in the medium term, which will be undertaken later, and which ones may or may not be undertaken.
Finally, a measure or measures should be defined for each tactic. For the same reason noted for the goals, try to limit them to two. For the goals and measures, remember the acronym SMART.
Our current moment has provided an opportunity for CIOs and other technology leaders to be the catalyst for their firms’ strategic evolution. These executives should take advantage of driving digital change. Otherwise, they risk digital driving them.
Peter A. High is the author of GETTING TO NIMBLE: How to Transform Your Company into a Digital Leader and President of Metis Strategy, a management and strategy consulting firm focused on the intersection of business and technology.
With all the ways digital innovation has enabled companies to remain productive during the pandemic, one of the most positive outcomes is improved collaboration across traditional business silos. In my new book, Getting to Nimble: How to Transform Your Company into a Digital Leader, I discuss how enterprises have made these silos more permeable, creating greater partnerships along the way.
Consider the following five examples and how they could apply to your digital transformation efforts.
Talented technologists are in high demand at most organizations, tasked with helping teams in other divisions figure out the digital implications of their ideas and strategize accordingly. In many cases, these ideas come from the technologists themselves. Companies that provide such “T-shaped” career paths offer an enormous advantage, developing leaders with great breadth and depth of experience. When they ascend to “chief” roles, they do so with a much clearer understanding about how value is created within the enterprise.
Agile methodology has been a boon for collaboration across the enterprise.
The traditional “waterfall” method of development involves someone from the business side (outside of IT) placing an order with the IT department. The IT team then develops this order, with little input from the business side until the project is completed months later.
In contrast, agile development includes the intended audience or user of the project in development from ideation through completion. With each iteration, the user validates value, and features are amplified or turned off accordingly. In some cases, the entire project may even be scrapped as a result of what the team learns.
DevOps blends two traditionally siloed parts of the technology and digital domain: development and operations. In a traditional project development model, developers take a project from ideation through completion, and the operations team then moves it forward. There is often a moment in the lifecycle when the project is “thrown over the wall” from development to operations (even this phrase highlights the distance and disconnects between the activities of the two groups).
DevOps instead makes delivery teams responsible for production issues and fixes, whether legacy or new, drawing them into the lifecycle earlier. Greater levels of involvement and accountability make for better work products.
The migration from a project to a product orientation is another area that benefits from greater collaboration. Internal “products” are also good examples of this – think order-to-cash, onboarding new hires, or creating a mobile customer experience.
These products potentially involve great value, and the product teams are typically cross-divisional or cross-discipline: They might include tech and digital, marketing, sales, operations, and any other division to which the product is relevant. A product leader should lead the cross-functional team, and that team should be prepared to remain intact for a longer period of time than the typical project.
An early example of this type of project orientation comes from Atticus Tysen, Chief Information and Security Officer at Intuit. When Tysen became CIO, he brought with him a product orientation, defining products for IT to drive. By developing in long-term teams, each team member was able to develop a higher level of expertise in the product area than they would have in a more traditional project structure.
Data strategy has also driven more cross-functional thinking. Done well, all strategy should invite greater collaboration across traditional silos since value is truly driven at the intersection of the disciplines. Data strategy should apply everywhere data is gathered, secured, synthesized, and analyzed – across the entire company.
Many companies have found it useful to have a leader who drives data strategy on the company’s behalf. To do this effectively, that leader (whether the CIO, the chief data officer, or another IT role) should engage leaders in other parts of the company to ensure that the data strategy is as comprehensive and useful as possible.
These are just a few areas where stronger collaboration is happening across industries and geographies. Companies that fail to take advantage of these trends risk falling behind more nimble players in their industry.
Peter A. High is the author of GETTING TO NIMBLE: How to Transform Your Company into a Digital Leader (Kogan Page, Spring 2021) and President of Metis Strategy, a management and strategy consulting firm focused on the intersection of business and technology. He has advised and interviewed many of the world’s top CIOs and leaders at multi-billion-dollar corporations like Gap, Bank of America, Adobe, Time Warner Inc., Intuit, and more.
Technology executives continue to tackle urgent tasks related to the COVID-19 pandemic, from supporting a surge of remote workers to keeping critical business systems running. But as remote work becomes the new normal (at least for the next few weeks), many CIOs are also grappling with larger cultural questions, primarily how to keep teams engaged and productive while working from home.
Below are a few practices leaders can take to maintain a culture of engagement and prepare their teams to emerge empowered on the other side of this crisis.
This is a time of immense uncertainty for both companies and individuals. Personal and professional routines have changed overnight as people make the shift to working remotely. Regardless of job title, everyone on your team is making an adjustment. One of the easiest ways to help create stability is to acknowledge that adjustment and do what’s possible to help the transition go smoothly.
A small but concrete way to do this is to provide training sessions on how to use various collaboration tools. While an IT team may be proficient in making calls on Zoom or communicating with Slack, others may using the technology for the first time. (One technology executive I spoke with recently said a training session for Zoom drew more than 5,000 sign ups.) Developing these opportunities is a simple way help your teams navigate the change and get to work faster.
“Every CIO knows change is not just about technology, it’s about people, process and technology,” Citrix CIO Meerah Rajavel wrote in a recent blog post. The company’s IT team worked closely with HR to craft the company’s work-from-home policy and develop a list of resources. “We decided to lean in and take a walk in the user’s shoes and collect feedback along every step of their journey that could be used to deliver a superior experience that would enable them to perform at their best.”
When visiting corporate innovation labs in recent years, it has been increasingly common to see a company’s leadership principles hanging poster-size on walls throughout the building, a not-so-subtle reminder of the firm’s cultural tenets. With the switch to remote work, it is now more incumbent upon executives to ensure those principles remain top of mind. Consider posting your team’s strategic priorities in prominent places across virtual channels and reference them when communicating with team members. Doing so can serve as a reminder that just because employees are no longer in the office, the company is still guided by the same vision.
While CIOs should continue to share frequent business updates with their teams, they can also magnify key wins and lessons learned. When working together in an office, it can be easier to see and celebrate victories, or to notice when something doesn’t work as it should. Without a shared physical space, CIOs can help develop cohesion by broadcasting the stories of teams solving challenging problems or otherwise rising to the occasion during the crisis.
Regardless of the message you are communicating, be clear and tailor it to the platform you are using. A request delivered “face to face” via video conference may come across differently than a terse message on Slack. Also, while it may sound dated, don’t be afraid to use the phone. While there is a plethora of communication tools at our fingertips, sometimes an old fashioned phone call can help you deliver a message most efficiently.
It is easy to think about remote work as an isolated activity, but it’s worth considering how it can help create new connections. As Adam Ely, deputy chief information security officer at Walmart, said in a recent LinkedIn post: “I spoke to one company that said this drove (security teams) to have better relationships with people in business lines they didn’t know.” Those teams now have a better understanding of their colleagues’ business processes and plan to work more closely with peers across the business. It is a potential silver lining for IT, where strong relationships with business partners are increasingly critical to growth.
The surge in virtual communication tools can help foster these connections. Virtual coffee chats, lunch breaks and happy hours have sprouted up both inside and outside the office as people look for new opportunities to connect. At health technology firm Cerner Corp., which has 27,000 employees working from home, teams are using collaboration tools in new ways, such as creating specific channels for discussing health-related topics, sharing work-from-home tips or sharing photos of their home offices.
While many companies are still in crisis response mode, it is increasingly important for CIOs to think about how their teams can emerge from the crisis in a position of strength. This presents an opportunity to bring a variety of voices into the conversation, working with colleagues across the organization to research the technologies and trends that are likely to rise in importance over the coming months. Even if your organization is unable to invest in those technologies today, exploring business cases now can prepare you to move quickly when the time is and give people a role in shaping the organization’s future.
As the shift toward remote work continues, leaders will be tasked with creating an inclusive work culture that also encourages productivity and innovation. Prioritizing health and safety, equipping employees with the right tools and fostering new forms of collaboration can go a long way toward making it happen.
