Members of the Columbia community and guests recently gathered for Navigating Enterprise Transformation: Data, People, and Strategy in Action, part of the M.S. in Information & Knowledge Strategy (IKNS) Seminar Series. The event featured Michael Raj, vice president of Strategic Modeling & Analytics at Verizon, who offered a behind-the-scenes look at what large-scale transformation requires inside a complex organization. The seminar concluded with a Q&A and a lively networking reception among students, executives from around the New York metro area and other participants.
The seminar’s premise closely reflected the interdisciplinary structure of the IKNS program. Rather than treating data, people, and strategy as separate components of organizational change, the seminar examined what happens when all three have to work together at once.
“It’s not just about data. It’s not just about people, and it’s not just about strategy,” said Blake DiCosola, Ph.D., associate professor of practice in IKNS, as he introduced the event. “It’s actually about how do all three of these things work together, all at once.”
Raj drew on his experience leading Strategic Modeling & Analytics at Verizon, where his team works across network, commercial, customer, finance, and other functions. His central argument was that sophisticated technology alone does not create transformation. Organizations also have to make the resulting insights actionable, earn trust across teams, and align people around common outcomes.
Turning data into decisions
For Raj, the first challenge is making sure analytics actually influence what an organization does.
Companies often begin transformation efforts with familiar problems: data distributed across different systems, organizational units measuring success with different key performance indicators, and reports arriving too late to support real-time decisions. Raj compared relying on outdated reporting to driving while looking at a photograph of the road taken a month earlier.
At Verizon, analytics can inform decisions ranging from predicting customer churn and measuring network experience to determining where to invest capital. But building a technically strong model is only the beginning.
Models have value, Raj argued, when their outputs can be connected to measurable business outcomes and translated into decisions. A model that performs well in isolation but is never adopted may be technically impressive without producing meaningful organizational change.
That distinction has become even more important as AI tools make it easier to build models, conduct research, and develop prototypes. The difficult part increasingly lies elsewhere: determining which problems are worth solving, connecting solutions to business priorities, and convincing others to use them.
The theme mirrors the broader IKNS curriculum, which approaches data and analytics as one part of a larger process of data-driven management rather than an end in themselves.
Building trust and changing behavior
The conversation then turned to the people behind transformation.
Raj emphasized that many transformation efforts fail not because the underlying technology is inadequate, but because people do not trust, understand, or adopt the new approach. That makes change management, organizational incentives, and influence essential parts of the work.
One problem emerges when individual departments and leaders are rewarded for different outcomes. Each group may succeed according to its own metrics while the organization as a whole moves in competing directions. Successful transformation therefore requires organizations to align incentives and measures with the larger goal they are trying to achieve.
Trust also matters when introducing new analytical tools. If employees cannot understand how a model reaches its recommendations, Raj said, asking them simply to accept its output can become a barrier to adoption, particularly when those recommendations affect their work.
He encouraged students entering organizations to look beyond formal organizational charts and understand how influence actually moves through a company.
“It’s really important for you to map the influence,” Raj said.
That means identifying the people others trust, bringing them into the process early, and co-creating solutions with the teams expected to use them. Raj also encouraged teams to identify and celebrate smaller milestones rather than waiting for a transformation to produce one major result months or years later. Early wins can demonstrate value, build credibility, and create momentum for larger changes.
For students and early-career professionals, Raj extended that emphasis on relationships to career development. He encouraged students to identify both mentors who can help them navigate challenges and sponsors who can advocate for them when opportunities arise.
Breaking down organizational silos
The third pillar, integration and strategy, brings those elements together.
Raj illustrated the challenge through decisions about Verizon’s network. A network team may prioritize building where service can be improved most. Supply chain leaders may focus on where equipment is available. Finance may prioritize cost, while customer experience teams focus on what will most benefit customers.
Each perspective is reasonable on its own. The problem arises when each function optimizes independently.
To counter that, Raj described the importance of cross-functional transformation teams that include people with credibility and expertise across different parts of the organization. Rather than allowing network, finance, supply chain, and customer experience to arrive at separate answers, the goal is to develop a shared view of the problem and determine which outcome creates the greatest value for the organization and its customers.
That need for integration also shapes how Raj thinks about AI. An “AI-first” mindset, he explained, should not mean inserting AI into every stage of an existing process.
“It’s not replacing 10 steps with 10 AI steps,” Raj said.
Instead, organizations should use the technology as an opportunity to question whether the existing process needs 10 steps in the first place. Could it be redesigned around two? Could longstanding approvals, workflows, or assumptions be reconsidered rather than simply automated?
The goal is not technology adoption for its own sake, but a willingness to rethink how work gets done.
During the Q&A, Raj translated that principle into advice for students and early-career professionals hoping to influence change from within an organization. Rather than arriving with 10 or 15 ideas, he recommended narrowing the list to the few with the clearest potential impact, showing what would change before and after implementation, and using early results to build credibility.
He also emphasized adaptability. Technical expertise remains important, but professionals increasingly need to move between different business contexts, work with incomplete information, and communicate across teams with different priorities.
Raj ultimately returned to the idea that gave the seminar its title. Data, people, and strategy cannot be approached sequentially, with one team building a solution before handing it to another team to implement. They have to move forward together.
A superior algorithm alone, he argued, is not enough. Lasting transformation depends on whether people trust it, whether organizations can integrate it into the way they work, and whether the resulting change produces value that can actually be measured.
About the Program
Columbia University’s M.S. in Information & Knowledge Strategy (IKNS) degree integrates data, people, and strategy skills for the AI age. The flexible and interdisciplinary curriculum trains leaders across the entire value chain of data-driven management: Getting the data and analytics right (e.g., AI adoption, business analytics), creating a high performing, people-centric culture (collaboration, team/project management, organizational psychology), and finally the right change management to turn your strategy into reality.
IKNS is available full-time or part-time, online or in-person on Columbia’s landmarked campus right here in New York City. To maximize opportunities for networking and community building, our online students join our New York-based students on Columbia’s campus for three in-person Residencies during their studies. The M.S. in IKNS is a STEM-designated degree.
Students train under world-class faculty, including former and current executives from Google, IBM, NASA, and Oliver Wyman, and join a powerful global alumni network in coveted positions, including at Alphabet, Goldman Sachs, Nike, Pfizer, and the World Bank.
For more IKNS insights, news, and events, please go to our website, connect with us on LinkedIn, or attend one of our online info sessions. Visit the School of Professional Studies website to learn more about the SPS Student Experience.
