Project managers are doing exactly what they were taught to do. They build plans, chase team members for updates, and report status. Despite all the activity, your leadership team is wondering why projects take so long and cost so much.

When projects don’t seem to move fast enough or deliver the ROI you expected, it usually has less to do with effort and more with a set of common mistakes your project managers make because of how they were trained, and what that training left out. Most project teams operate like order takers instead of the business-focused leaders you need to deliver your organization’s strategy.

To accelerate strategy delivery in your organization, something has to change. The way projects are led needs to shift, and traditional project management approaches and mindsets won’t get you there.

Here are the most common project management mistakes we see holding teams back, and what you can do to help your project leaders shift from being order takers to drivers of IMPACT: instilling focus, measuring outcomes, performing, adapting, communicating, and transforming.

Mistake #1: Solving project problems instead of business problems

Project managers are trained to solve project problems. Scope creep. Missed deadlines. Resource bottlenecks. They spend their days managing tasks and chasing status updates, but most of them have no idea whether the work they manage is solving a real business problem.

That’s not their fault. They’ve been taught to stay in their lane in formal training and by many executives. Keep the project moving. Don’t ask questions. Focus on delivery.

But no one is talking to them about the purpose of these projects and what success looks like from a business perspective, so how can they help you achieve it?

You don’t need another project checked off the list. You need the business problem solved.

IMPACT driver mindset: Instill focus

Start by helping your teams understand the business context behind the work. What problem are we trying to solve? Why does this project matter to the organization? What outcome are we aiming for?

Your teams can’t answer those questions unless you bring them into the strategy conversation. When they understand the business goals, not just the project goals, they can start making decisions differently. Their conversations change to ensure everyone knows why their work matters. The entire team begins choosing priorities, tradeoffs, and solutions that are aligned with solving that business problem instead of just checking tasks off the list.

Mistake #2: Tracking progress instead of measuring business value

Your teams are taught to track progress toward delivering outputs. On time, on scope, and on budget are the metrics they hear repeatedly. But those metrics only tell you if deliverables will be created as planned, not if that work will deliver the results the business expects.

Most project managers are taught to measure how busy the team is. Everyone walks around wearing their busy badge of honor as if that proves value. They give updates about what’s done, what’s in progress, and what’s late. But the metrics they use show how busy everyone is at creating outputs, not how they’re tracking toward achieving outcomes.

All of that busyness can look impressive on paper, but it’s not the same as being productive. In fact, busy gets in the way of being productive.

IMPACT driver mindset: Measure outcomes

Now that the team understands what they’re doing and why, the next question to answer is how will we know we’re successful.

Right from the start of the project, you need to define not just the business goal but how you’ll measure it was successful in business terms. Did the project reduce cost, increase revenue, improve the customer experience? That’s what you and your peers care about, but often that’s not the focus you ask the project people to drive toward.

Think about a project that’s intended to drive revenue but ends up costing you twice as much to deliver. If the revenue target stays the same, the project may no longer make sense. Or they might come up with a way to drive even higher revenue because they understood the way you measure success.

Shift how you measure project success from outputs to outcomes and watch how quickly your projects start creating real business value.

Mistake #3: Perfecting process instead of streamlining it

If your teams spend more time tweaking templates, building frameworks, or debating methodology than actually delivering results, processes become inefficient.

Often project managers are hired for their certifications, which leads many of them to believe their value is tied to how much of and how perfectly they create and follow that process. They work hard to make sure every box is checked, every template is filled out, and every report is delivered on time. But if the process becomes the goal, they’re missing the point.

You invested in project management to get business results, not build a deliverable machine, and the faster you achieve those results, the higher your return on your project investments.

IMPACT driver mindset: Perform relentlessly

With a clear plan to drive business value, now we need to show them how to accelerate. That means relentlessly evaluating, streamlining, and optimizing the delivery process so it helps the team achieve the project goals faster.

Give them permission to simplify. When the process slows them down or adds work that doesn’t add value, they should be able to call it out.

This isn’t an excuse to have no process or claim you’re being agile just to skip the necessary steps. It’s about right-sizing the process, simplifying where you can, and being thoughtful about what’s truly needed to deliver the outcome. Do you really need a 30-page document no one will read, or would two pages that people actually use be enough? You don’t need perfection. You need progress.

Mistake #4: Blaming people instead of leading them through change

A lot of leaders start from the belief that people are naturally resistant to change. When projects stall or results fall short, it’s easy to assume someone just didn’t want to change. Project teams blame people, then layer on more governance, more process, and more pressure. Most of the time, it’s not a people problem. It’s how the changes are being done to people instead of with them.

People don’t resist because they’re lazy or difficult. They resist because they don’t understand why it’s happening or what it means for them. And no amount of process will fix that.

IMPACT driver mindset: Adapt to thrive

With an accelerated delivery plan designed to drive business value, your project teams can now turn their attention to bringing people with them through the change process.

Change management is everyone’s job, not something you outsource to HR or a change team. Projects fail without good change management and everyone needs to be involved. Your teams must understand that people aren’t resistant to change. They’re resistant to having change done to them. You have to teach them how to bring others through the change process instead of pushing change at them.

Teach your project teams how to engage stakeholders early and often so they feel part of the change journey. When people are included, feel heard, and involved in shaping the solution, resistance starts to fade and you create a united force that supports your accelerated delivery plan.

Mistake #5: Communicating for compliance instead of engagement

The reason most project communication fails is because it’s treated like a one-way path. Status reports people don’t understand. Steering committee slides read to a room full of executives who aren’t engaged. Unread emails. The information goes out because it’s required, not because it’s helping people make better decisions or take the right action.

But that kind of communication doesn’t create clarity, build engagement, or drive alignment. And it doesn’t inspire anyone to lean in and help solve the real problems.

IMPACT driver mindset: Communicate with purpose

To keep people engaged in the project and help it keep accelerating toward business goals, you need purpose-driven communication designed to drive actions and decisions. Your teams shouldn’t just push information but enable action. That means getting the right people and the right message at the right time, with a clear next step.

If you want your projects to move faster, communication can’t be a formality. When teams, sponsors, and stakeholders know what’s happening and why it matters, they make decisions faster. You don’t need more status reports. You need communication that drives actions and decisions.

Mistake #6: Driving project goals instead of business outcomes

Most organizations still define the project leadership role around task-focused delivery. Get the project done. Hit the date. Stay on budget. Project managers have been trained to believe that finishing the project as planned is the definition of success. But that’s not how you define project success.

If you keep project managers out of the conversations about strategy and business goals, they’ll naturally focus on project outputs instead of business outcomes. This leaves you in the same place you are today. Projects are completed, outputs are delivered, but the business doesn’t always see the impact expected.

IMPACT driver mindset: Transform mindset

When you help your teams instill focus, measure outcomes, perform relentlessly, adapt to thrive, and communicate with purpose, you do more than improve project delivery. You build the foundation for a different kind of leadership.

Shift how you and your organization see the project leadership role. Your project managers are no longer just running projects. You’re developing strategy navigators who partner with you to guide how strategy gets delivered, and help you see around corners, connect initiatives, and decide where to invest next.

When project managers are trusted to think this way and given visibility into the strategy, they learn how the business really works. They stop chasing project success and start driving business success.

More on project management:

• Project management guide: Tips, strategies, best practices
• What is a project manager? The lead role for project success
• 5 early warning signs of project failure
• 10 project management myths to avoid
• 16 tips for a smooth switch to agile project management
• The 22 best project management tools for business
• Scrum vs. Lean vs. Kanban: Comparing agile project management frameworks
• How to pick the right project management methodology for success
• Agile project management: A comprehensive guide
• 8 common project management mistakes — and how to avoid them
• Top 11 project management certifications for 2017
• 10 traits of highly effective project managers
• 8 goals every project manager should aspire to achieve
• Project management: 7 steps to on-time, on-budget, goal-based delivery

AI initiatives by and large have fallen short of expectations.

That’s the conclusion of most research to date, including MIT’s The GenAI Divide: State of AI in Business 2025, which found a staggering 95% failure rate for enterprise generative AI projects, defined as not having shown measurable financial returns within six months.

Moreover, tolerance for poor returns is running out, as CEOs, boards, and investors are making it clear they want to see demonstrable ROI on AI initiatives.

According to Kyndryl’s 2025 Readiness Report, 61% of the 3,700 senior business leaders and decision-makers surveyed feel more pressure to prove ROI on their AI investments now versus a year ago.

And the Vision 2026 CEO and Investor Outlook Survey, from global CEO advisory firm Teneo, noted a similar trend, writing that “as efforts shift from hype to execution, businesses are under pressure to show ROI from rising AI spend,” noting that 53% of investors expect positive ROI in six months or less.

“There is pressure on CEOs and CIOs to deliver returns, and that pressure is going to continue, and with that pressure is the question, ‘How will you use AI to make the company better?’” says Neil Dhar, global managing partner at IBM Consulting.

Laying the foundation for success

Matt Marze, CIO of New York Life Group Benefit Solutions, is confident he can deliver AI ROI in 2026 because he’s been getting positive returns all along. The key? Pursuing and prioritizing AI deployments based on the anticipated value each will produce.

“We started our AI journey with a call to action in December 2023 by the CEO, and from the start we wanted to be a technology, data, and AI company to drive unparalleled experiences for our customers, partners, and employees. So all along the value question, the ROI was very top of mind,” Marze explains.

Marze and his executive colleagues approach AI investments “the same way we think about all our investments” — that is, considering how they’d impact the company’s earnings plan. “We look at operating expense reduction, margin improvement, top-line revenue growth, customer satisfaction, and client retention, but at the end of the day it boils down to our earnings contribution,” he says.

Marze highlights practices that keeps the organization focused on ROI, such as prioritizing AI initiatives for areas that are AI-ready in terms of available data, systems, and skills; using returns from those to fund subsequent initiatives; and designing AI systems in ways that allow for reusability so that subsequent projects can get off the ground more efficiently.

“We’re doing all that very strategically,” Marze says, explaining that this approach enables the organization to select AI projects where there are realistic expectations for ROI rather than merely hopes for vague improvements.

“We want to be nimble and move with urgency, but we also want to do things the right way. And because we fund our investments out of our P&L, we think about spending. We have that P&L mindset. We don’t like to waste money,” he adds.

Marze also credits the company’s ongoing commitment to modernization as helping ensure AI projects can deliver returns. “We built a foundation, and that put us in a good position to capitalize on AI,” he says. “There is a readiness component to leveraging AI effectively and to driving AI ROI. You have to have strategic data management, modernized computing, modernized apps, and cloud-native solutions to take advantage of AI.”

Marze expects those same disciplines and approaches to continue enabling him to pick AI initiatives that deliver measurable value for the organization as his company looks to reimagine work using AI and to bring full agentic solutions into its core processes.

The payback on the various proposals vary, he notes, and the anticipated timeline for payback for some can be a few years out, but he’s confident that the positive returns will be there.

Moving from elusive to realized ROI

Others are not as confident that their AI projects will deliver ROI — or at least ROI as quickly as some would like. Some 84% of CEOs predict that positive returns from new AI initiatives will take longer than six months to achieve, according to the Teneo report.

Their perspective may be colored by the past few years, when ROI has been elusive for many reasons, say researchers, analysts, and IT execs.

Many early AI initiatives were experiments and learning opportunities with little or no relevance to the business, says Bret Greenstein, CAIO at West Monroe. They often didn’t address the organization’s needs or goals and atrophied as a result. And even when the AI projects did address real pain points or business opportunities, they often failed to deliver value because the data or technology needed to scale wasn’t there or cost more to modernize than the anticipated ROI. And while some delivered modest gains or improved experience, they were either difficult to quantify or small enough to not move the needle.

“If you go back to the early days of the web and mobile, the same thing happened, before people learned there are new metrics that mattered. It just takes time to figure those out,” Greenstein says.

Now, three years after the arrival of ChatGPT and generative AI, the enterprise has matured its understanding of AI’s potential.

“We’re clearly in the third wave where more clients understand the transformational value of AI and that it’s about new ways of working,” Greenstein says. “Those who are getting ROIs are the ones who see it as a transformation and work with the business to rethink what they’re doing and to get people to work differently. They know transformation work is required to see an ROI.”

To ensure AI projects deliver ROI, Palo Alto Networks CIO Meerah Rajavel selects initiatives that deliver velocity (“Speed is the name of the game,” she says), efficiency (“Can I do more with less?”), and improved experience. “This forces us to reimagine experiences and processes, and it absolutely changes the game,” she says.

Rajavel assesses each AI initiative’s success on the outcomes it produces in those categories, noting that her company has adopted that focus all along and continues to use it to determine which AI investments to make.

As a case in point, she cites a current project that uses AI to automate 90% of IT operations — a project that is already delivering gains in velocity, efficiency, and experience. Rajavel says automated IT operations jumped from 12% when the project started in early 2024 to 75% as of late 2025 — an improvement that has halved the costs of IT operations.

Metrics and targets

Many organizations haven’t taken a strategic approach when deciding where to implement AI, which helps explain why AI ROI has been so elusive, says IBM’s Dhar. “Some sprayed and prayed rather than systematically asking, ‘How will the technology make my company better?’” he adds.

But top management teams are increasingly looking at AI “as a way to transform — and to transform their businesses dramatically,” he says. “They’re reinventing all their functions, and they’re transforming functions to make them better, stronger, and cheaper, and in some cases they’re also getting top-line growth. Two years ago, there was a lot of experimentation, proofs of concept; now it is transformation, with the most sophisticated management teams looking for returns within 12 months.”

Linh Lam, CIO of Jamf, had been deploying AI to solve pain points but is now using AI “to rethink how we do things.” She sees those as the opportunities to generate the biggest gains.

“I feel like we’re going to see more and more of that, where the technology forces us to rethink how we’re doing things, and that’s where the real value is,” she says.

That’s certainly the case in terms of the AI initiatives Jamf now prioritizes.

“Two years ago, there was more tolerance to say, ‘Let’s try it.’ Now we’ve moved well beyond that, so if someone is bringing something in and they have no semblance of the potential value except it’s going to make life better, we’re going to push back on that. We’re looking at the goals stakeholders have and setting metrics to measure outcomes,” she says. “I feel like the realm of possibility with what you can do with AI and AI agents almost feels limitless. But you’re still running a business, and you want to make decisions in a logical, smart way. So we have to make sure we’re bringing the right value.”

Turning IT challenges into a virtuous cycle for AI transformation

There are challenges, of course, to getting positive returns on AI initiatives — even when they’re carefully selected for their potential, says Jennifer Fernandes, lead of the AI and technology transformation unit at Tata Consultancy Services in North America.

According to Fernandes, many organizations are stymied by legacy technology, process debt, and data debt that keeps them from being able to scale AI projects and see measurable value.

And they won’t be able to scale their AI ambitions and see impactful returns until they pay off that debt, she adds.

Cisco’s AI Readiness Index found that only 32% of organizations rate their IT infrastructure as being fully AI ready, only 34% rated their data preparedness as such, and just 23% considered their governance processes primed for AI.

Fernandes advises CIOs to tackle that debt strategically and use AI to pay it down. Moreover, using AI to modernize IT will bring efficiencies to IT operations while also building IT’s capacity to support more AI use cases and addressing deficits in the organization’s data layer, she says.

The increased efficiency produces returns that can be reinvested in other AI projects, which will be more likely to produce ROI due to the modernization that resulted from the earlier AI project, Fernandes explains.

Moreover, this self-funding model not only helps build the modern tech stack and data program needed to power AI in IT and other business units but also focuses attention on ROI from the start, helping ensure CIOs and their business peers pursue AI initiatives that generate positive returns.

“You’re generating enough savings to pay down your debt, and you’re building incrementally, you’re transforming as you go,” Fernandes says. “And with this [approach], CIOs don’t have to go and say, ‘Give me money to fix these things.’ Instead they can say, ‘I have this model, and if we bring AI in here, we can generate returns, and we can then reinvest to drive these other transformations. Now the CIO can say, ‘I am generating the funding for AI for you.’”

Every product starts with a spark: a big idea, a bold vision, a belief that your team can build something transformative. But between vision and launch lies the messy middle: translating strategy into a roadmap to get real work done.

In How strategy and alignment can make or break your product launches, I explored how a clear, unified strategy sets the foundation for success. The next step is turning this strategy into a tangible, time-bound plan the team can rally around. This is where a roadmap comes in. It’s the blueprint that turns ambition into outcomes.

A roadmap isn’t just a scheduling exercise. It’s an act of translation, connecting the why of a product strategy with the how of execution. When done well, it inspires confidence, motivates teams and ensures everyone — from engineers to executives — is rowing in the same direction.

Why roadmaps matter

The pace of technological change has never been faster. In an era defined by AI, automation and continuous delivery, product teams can’t afford to drift. A roadmap provides the anchor to keep everyone aligned amid constant flux.

Yet many organizations still treat roadmaps as static artifacts — a one-and-done exercise intended to appease executives or investors. That’s a mistake. The most effective roadmaps are living documents evolving with the product and market realities.

According to a Gartner analysis of product roadmapping tools, organizations that maintain flexible, continuously updated roadmaps see up to a 25% improvement in release predictability and stakeholder satisfaction. That’s because teams focus less on prediction and more on iteration; mapping not just what will happen, but how they’ll adapt when things inevitably change.

A roadmap gives shape to uncertainty. It doesn’t eliminate ambiguity; it transforms uncertainty into structured possibility.

From vision to roadmap: Where the rubber meets the road

At this stage, excitement gives way to reality. After articulating the vision comes the hard part: making trade-offs, defining milestones and turning “someday” into “next sprint.”

Here’s how to build a roadmap that actually works:

1. Start with near-term accuracy. Focus on what can be confidently delivered in the next 3–6 months. Early precision matters more than long-term speculation. Anything beyond a year should remain directional, not definitive.
2. Create collaborative ownership. Don’t dictate the roadmap; instead, build it with the team. Involve engineers, designers, project managers and documentation writers from day one. The most successful teams I’ve led — at Splunk, SentinelOne, Chronosphere and elsewhere — emerged from collective input, not top-down mandates.
3. Establish delivery milestones. Early milestones should be small, celebratory and achievable, like the first working prototype, the first dataset successfully processed and the first customer beta. These moments build excitement, energize people and create visible momentum.
4. Plan the process. Roadmap creation isn’t something to be squeezed into an hour-long Zoom call. Schedule dedicated time — ideally 1–2 days in person — for structured collaboration. If the team is remote, leverage digital whiteboards like Miro or Notion to simulate the in-person energy virtually. If possible, establish a clear set of outcomes, customer profiles to target and key deliverables. While this may not be your final roadmap, it gives everyone time to digest and react to what’s being proposed rather than starting from scratch.
5. Capture decisions in a system of record. Once the roadmap is drafted, commit it to a tool the whole organization can access. Regardless of the tool — Jira, Productboard or another specialized platform — consistency is key.

A roadmap built in isolation is a roadmap doomed to fail. The point isn’t to get everyone to agree on everything, it’s to surface disagreements early and align on the next concrete steps forward.

Milestones: The secret to sustainable momentum

If strategy defines direction, milestones are the engine that keeps the train moving. Too often, teams treat milestones as arbitrary checkpoints or internal deadlines. Done right, these can become powerful tools for motivation, alignment and storytelling.

Start small. The first milestone might be as simple as “ingest and store sample data.” That’s enough to celebrate! Over time, milestones should evolve in ambition, but not necessarily in complexity. The key is proximity: Each milestone should be achievable in 1–3 months, not six.

Why does this matter? Because long, nebulous timelines erode morale. Frequent, visible progress sustains it. Teams that regularly celebrate small wins see measurable boosts in productivity and engagement.

And don’t keep those wins quiet. Market your team’s successes across the company. Share demos, post updates in Slack and host show-and-tells. Visibility breeds trust. When executives see tangible progress, they’re far more likely to protect a product roadmap from shifting priorities.

Perfection isn’t the goal, consistency is. A product that ships 80% of what’s planned every quarter will outperform one that promises the moon but delivers sporadically.

What not to do

Building a roadmap is as much about what to avoid as what to include:

• Don’t plan a year out with false precision. The further out the project, the less accurate the assumptions will become.
• Don’t assign GA dates prematurely. It’s better to deliver great products later than mediocre ones on time.
• Don’t roadmap in fragments. Avoid 1:1 syncs or piecemeal updates; they create drift and confusion.
• Don’t mistake alignment for consensus. Disagreement is healthy; it means the team cares enough to challenge ideas.

Above all, don’t boil the ocean. Focus on small, meaningful steps that collectively build momentum. Vision is the north star, but execution is the path to get you there.

Roadmaps are team sports

The best roadmaps aren’t written by PMs — they’re co-authored by teams. That’s why I advocate for bottom-up collaboration anchored in executive alignment. Before any roadmap offsite, sync with the CEO or leadership team. Understand what they care about and why. If they disagree with priorities, resolve those conflicts early. Then bring that context into a team workshop.

During the session, identify technical leads — those trusted voices who can translate into action. Encourage them to pre-think tradeoffs and dependencies before the group session. That preparation pays off when tough calls need to be made in the room.

The roadmap meeting itself should feel like a design sprint: energetic, creative, grounded in shared accountability. Use a flexible medium — whiteboards, sticky notes, shared docs — to keep ideas flowing. Once decisions are made, codify them. The goal is alignment, not perfection.

After the team has shaped the roadmap, close the loop with your executive stakeholders. Play the plan back to them, clearly, confidently and with evidence. Show how the proposed roadmap unlocks parts of the market the company couldn’t access before, strengthens your ability to win against specific competitors or opens meaningful new revenue or customer segments. When possible, quantify impact. Executives don’t just want to know what you’re building, they need to see why it matters and the scale of the opportunity it creates.

AI: the invisible ingredient

Until now, I’ve intentionally avoided calling out AI. Instead of a feature on the roadmap, AI must now be part of the product’s DNA.

The best teams don’t ask, “Where can we add AI?” They ask, “Where can AI make our users’ lives easier or our processes more efficient?” Whether it’s automating documentation, accelerating anomaly detection or enhancing decision making, AI should serve as an enabler, not an add-on.

In practice, this means incorporating AI into the ideation process. During roadmap planning, prompt team leads to identify repetitive pain points or data-rich opportunities where AI can augment human capability. Over time, this mindset will become second nature — a quiet but transformative force that compounds with every release.

A roadmap and a promise for success

The perfect roadmap doesn’t exist and that’s the point. Remember, the goal isn’t to build a flawless plan, but a resilient one. As President Dwight D. Eisenhower said, “Plans are useless, but planning is indispensable.”

Every successful product I’ve launched followed the same rhythm:

• Start with clarity of purpose.
• Translate that purpose into concrete, time-bound steps.
• Align the team through collaboration and visibility.
• Celebrate progress relentlessly.

Vision without execution is hallucination. But execution without vision is chaos. The magic of product leadership lies in balancing both: crafting a roadmap that’s both inspiring and achievable.

As you build yours, remember a roadmap is a promise. It says: we know where we’re going and we’ll get there — one milestone at a time.

This article is published as part of the Foundry Expert Contributor Network.
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As organizations accelerate their shift from traditional data center environments to hybrid and multi-cloud architectures, the scale and complexity of these initiatives demand a new caliber of project leadership. Having recently led a multi-year enterprise-wide data center transformation with global stakeholders, I’ve seen firsthand that technology alone is not what ensures success. Leadership is the key.

Even the most advanced platforms and tools can fall short without a project manager who brings the right mindset, adaptability and technical fluency. These programs are simultaneously technical undertakings and organizational-change journeys.

Based on lessons learned from managing one of the most ambitious transformations in my organization, here are the five skills essential for any project manager responsible for navigating cloud and data center modernization.

1. Systems thinking & architectural awareness

Data center transformations operate at an enterprise scale, where no system exists in isolation. Every application, integration point and data flow is part of a wider ecosystem and understanding that ecosystem is critical from day one. Systems thinking means looking beyond servers and environments to examine business processes, downstream dependencies, data protection needs and operational realities.

This requires asking targeted questions such as:

• What is the business impact if this application is down for four hours or more?
• How many teams, processes or users rely on it?
• What are its recovery objectives and how does it interact with upstream and downstream systems?

With these insights, project managers can make informed decisions about cutover sequencing and avoid grouping applications solely by physical infrastructure — an approach that often leads to outages or misplaced dependencies. Indeed, a recent empirical study of migrating legacy systems to cloud platforms identified a lack of architectural mapping and understanding of interdependencies as a key risk factor in migration failures.

Takeaway

Architectural awareness isn’t memorizing components; it’s understanding how a single change reverberates across the entire enterprise system.

2. Elastic governance & proactive risk anticipation

Large-scale migrations rarely follow a predictable or linear path. They unfold in iterative phases, each introducing new variables, technical constraints and lessons learned. Because of this, a traditional waterfall approach quickly becomes a liability. What teams need instead is an elastic governance framework that provides structure while adapting to shifting realities.

Elastic governance means adjusting processes, decision models and approval flows as new insights surface. Each application and business unit often carries its own architecture, dependencies and constraints, so a one-size-fits-all model simply doesn’t work. During our migration, daily interactions with implementation teams, developers and product owners gave me real-time visibility into emerging issues and allowed us to refine our approach continuously.

This approach mirrors trends highlighted in the ISACA Journal’s 2023 article, “Redefining Enterprise Cloud Technology Governance.” ISACA argues that traditional governance frameworks are far too rigid for modern cloud environments. Instead, they advocate for adaptive, decentralized models that empower teams to respond quickly as new constraints and dependencies emerge.

Vendor-related challenges were especially common with aging legacy systems. Proactive engagement — rather than reactive firefighting — helped us avoid failures and maintain momentum.

Takeaway

Governance should guide, not grind. Flexibility is essential for managing uncertainty and sustaining progress in complex transformations.

3. Stakeholder coordination and strategic communication

In enterprise-wide transformation programs, stakeholder alignment is often the difference between controlled progress and project derailment. Every migration window, firewall rule adjustment, environment change or sequence shift requires close coordination across security, networking, infrastructure, operations, product teams and business leadership — all operating with their own priorities and pressures.

Research shows that stakeholders often have different “frames” of a digital transformation and successful programs actively manage these perspectives to create shared understanding and alignment. Similarly, a 2023 KPMG report highlights that building trust among stakeholders — particularly around risk, security and compliance — is essential for successful cloud adoption.

A critical part of this role is translation. The project manager must convert technical constraints into clear, business-friendly updates while also translating business expectations into actionable direction for engineering teams. This dual fluency reduces misunderstanding and accelerates decision-making.

To maintain alignment, structured communication becomes essential. I established predictable rhythms — daily standups, weekly product syncs, monthly executive briefings and shared dashboards — to ensure transparency, quick escalation and consistent visibility into progress and risks.

Takeaway

The stronger and more structured the communication, the smoother and more predictable the migration.

4. Technical fluency & decision facilitation

Modernization initiatives involve ongoing decisions about whether to re-host, re-platform or re-architect applications. While a project manager doesn’t need to be the most technical person in the room, they must understand the implications of each option well enough to facilitate informed decision-making.

Technical fluency builds credibility with developers, architects, vendors and deployment teams. It also enables the project manager to ask the right questions, challenge assumptions and guide discussions toward solutions. This is especially important given the “6 Rs” of cloud migration — re-host, re-platform, refactor (re-architect) and others — which are commonly used to rationalize workloads based on business goals and technical fit.

Takeaway

Technical fluency enables clarity, connection and better decisions.

5. Resilience & change leadership

Data center transformations are long, complex and filled with uncertainties. Unexpected technical issues, compliance demands and shifting business priorities can slow down momentum and strain teams. According to the KPMG report mentioned earlier, many organizations struggle with operational resilience — more than half experienced outages or compliance issues in their cloud operations over the past year. This reinforces the importance of proactive governance and risk management. In such environments, a resilient project manager provides clarity, maintains stability and ensures the team keeps moving forward.

During our project, an unexpected compliance mandate required rapid reprioritization and additional resources. With leadership support, we realigned the plan and still met the migration deadline. Maintaining team morale during such periods is just as important as technical delivery.

Takeaway

Resilient teams don’t resist change; they stay confident through it.

Integrating the 5 skills: The project manager as transformation leader

A data center transformation is more than a technical project — it reshapes processes, roles and behaviors across the organization. When these five skills come together, the project manager transitions from a delivery role into a true transformation leader.

• Systems thinking eliminates hidden dependencies.
• Elastic governance adapts to evolving needs.
• Stakeholder coordination maintains across-the-board alignment.
• Technical fluency builds trust and accelerates decision-making.
• Resilience keeps teams focused during disruption.

The most effective transformation leaders balance discipline with flexibility.

Measuring success beyond migration

Traditional success metrics such as reduced downtime, regulatory compliance and cost optimization are important. But true success becomes clear only when the organization demonstrates improved adaptability and stronger collaboration between IT and the business.

When a project manager embeds adaptability deep into the organization, the transformation continues long after the final cutover.

The future-ready project manager

Looking ahead, managing a data center transformation a decade from now will be fundamentally different. The next generation of migrations will involve greater complexity, including advanced automation, AI-driven orchestration, multi-cloud environments and more sophisticated compliance and security requirements. Without continuous upskilling, project managers will struggle to lead confidently in this evolving landscape.

Future-ready leaders must be both technologically fluent and human-centered. They need to leverage data effectively, make decisions at the pace of AI and automation and understand emerging tools and methodologies. At the same time, they must maintain essential human leadership qualities — trust, accountability, resilience and the ability to inspire teams under pressure.

By balancing these technical and human skills, project managers remain indispensable. They not only ensure that migrations succeed technically but also guide teams and organizations with purpose, clarity and adaptability, enabling sustainable transformation that goes beyond the immediate project and strengthens the organization’s long-term capabilities.

Closing thoughts

Data center transformation was not an easy migration, as it was a complicated and most ambitious undertaking by the organization. Orchestrating more than a hundred stakeholders was not an easy feat and we accomplished it with meticulous planning and risk management. Hence, a project manager with those five skills doesn’t just lead, they become the transformation agents for the organization. As the saying goes: Real transformation happens when leadership turns complexity into clarity and uncertainty into forward motion.

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Sviluppare una roadmap, nel mondo dei CIO (Chief Information Officer), significava pensare a cinque o dieci anni avanti riguardo alle tendenze tecnologiche e poi pianificare e prepararsi per esse.

Ma con tecnologie impreviste e immediatamente dirompenti che diventano un fatto dell’IT di oggi, inclusa la necessità di difendersi da esse in un batter d’occhio, sviluppare roadmap tecnologiche diventa molto più che pianificare aggiornamenti a tecnologie e sistemi obsoleti. La complessità e la lungimiranza coinvolte riducono notevolmente l’orizzonte delle aspettative del CIO, rendendo una sfida stabilire anche un orizzonte temporale IT di tre anni [in inglese].

Cosa comporta esattamente creare una roadmap IT oggi, e come possono i CIO garantire che le roadmap che realizzano rimangano rilevanti? Ecco come ripensare il vostro approccio data la strada accidentata che vi attende.

Prepararsi alla disruption (interruzione/sconvolgimento)

La pianificazione della roadmap IT dipende ancora dalla comprensione dell’attuale panorama tecnico e dalla proiezione delle implicazioni a lungo termine dei cambiamenti previsti negli anni a venire. Al momento, l’AI (Intelligenza Artificiale) appare come la forza più impattante sui sistemi IT e sulle operazioni aziendali nei prossimi 10 anni. La sua continua evoluzione risulterà in una maggiore automazione e cambiamenti nell’interfaccia uomo-macchina che faranno sembrare le operazioni aziendali, anche tra soli cinque anni, piuttosto diverse da come sono oggi. L’intelligenza artificiale in sé è un importante elemento di disturbo per le operazioni e i sistemi per cui bisognerà pianificare.

Come afferma la società di consulenza tecnologica West Monroe [in inglese]: “Non avete bisogno di piani più grandi, avete bisogno di mosse più veloci”. Questo è un mantra appropriato per lo sviluppo della roadmap IT oggi.

I CIO dovrebbero chiedersi da dove arriveranno i più probabili elementi di disturbo per i piani aziendali e tecnologici. Ecco alcuni dei principali candidati:

Resilienza organizzativa e gestione del rischio: l’azienda è preparata per lo spostamento di posti di lavoro e le ridefinizioni dei ruoli [in inglese] che si verificheranno man mano che verranno implementate più automazione e AI? I dipendenti saranno adeguatamente formati ed equipaggiati con le competenze e le tecnologie che dovranno essere utilizzate in un nuovo ambiente aziendale? E i sistemi? Quali sistemi probabilmente terranno il passo con il tasso di cambiamento tecnologico e quali no [in inglese]? Qual è il Piano B se un sistema viene improvvisamente reso obsoleto o inoperativo?

Sicurezza: l’AI sarà utilizzata sia da attori buoni che cattivi, ma mentre i cattivi attori iniziano a colpire le organizzazioni con attacchi assistiti dall’intelligenza artificiale [in inglese], l’IT interno ha gli strumenti e le competenze giuste per respingere questi attacchi e rispondere? O l’IT può sviluppare un approccio più preventivo per rilevare, anticipare e prepararsi a nuove minacce alla sicurezza basate sull’AI? Il vostro team di sicurezza possiede gli ultimi strumenti e competenze di sicurezza AI per fare questo lavoro? E da un’altra prospettiva: Avete la strategia, le competenze e la tecnologia per difendere adeguatamente la vostra stessa infrastruttura di intelligenza artificiale [in inglese] quando sorgono attacchi contro di essa?

Catene di approvvigionamento: il panorama geopolitico sta cambiando rapidamente. L’azienda, incluso l’IT, è pronta a passare a fornitori alternativi e rotte della catena di approvvigionamento se i fornitori attuali o le rotte della catena di approvvigionamento subiscono un impatto negativo? E i sistemi possono tenere il passo con questi cambiamenti?

Failover (Garantire la continuità operativa): avete sistemi ridondanti in atto se si verifica un evento disastroso in una particolare geozona e dovete eseguire il failover? E se i vostri sistemi, l’AI e l’automazione diventano totalmente inoperativi, l’azienda ha in organico dipendenti che possono tornare ai processi manuali se necessario?

Sviluppare una roadmap IT resiliente

Comprensibilmente, i CIO possono sviluppare roadmap tecnologiche rivolte al futuro solo con ciò che vedono in un momento presente nel tempo. Tuttavia, hanno la capacità di migliorare la qualità delle loro roadmap rivedendo e revisionando questi piani più spesso.

Oggi, la carenza in molte aziende è che la leadership scrive piani strategici solo come esercizio annuale. Dato il tasso di cambiamento della tecnologia, mettere via una roadmap IT per 12 mesi senza revisioni periodiche e modifiche per adattarsi ai cambiamenti dirompenti non è più fattibile. I CIO dovrebbero rivedere le roadmap IT almeno trimestralmente. Se queste ultime devono essere alterate, i CIO dovrebbero comunicare ai loro CEO, ai consigli di amministrazione e ai colleghi di livello C cosa sta succedendo e perché. In questo modo, nessuno sarà sorpreso quando dovranno essere apportate modifiche.

Man mano che i CIO si impegnano maggiormente con le linee di business, possono anche mostrare come i cambiamenti tecnologici influenzeranno le operazioni e le finanze aziendali prima che questi cambiamenti avvengano. Possono avvisare il consiglio e la direzione di nuovi fattori di rischio che probabilmente sorgeranno dall’IA e da altre tecnologie dirompenti, e garantire che queste interruzioni e rischi siano considerati nel piano di gestione del rischio aziendale. In questo modo, i CIO possono mantenere l’allineamento del piano strategico IT e della roadmap con la strategia aziendale.

Ugualmente importante è sottolineare che un cambiamento sismico nella direzione della roadmap tecnologica potrebbe avere un impatto sui budget.

Ad esempio, se le minacce alla sicurezza guidate dall’IA iniziano a colpire l’IA aziendale e i sistemi generali, l’IT avrà bisogno di strumenti e competenze pronti per l’IA per difendere e mitigare queste minacce. È possibile che debba essere fatta un’eccezione di budget o una riallocazione di fondi affinché le giuste tecnologie e formazione possano essere acquisite. Problemi finanziari possono sorgere anche sulle catene di approvvigionamento aziendali o IT se un particolare fornitore è improvvisamente non disponibile e/o devono essere trovate rotte di fornitura alternative.

Infine, la formazione del personale IT dovrebbe diventare un elemento standard nelle roadmap IT, e non solo un’opzione. Le roadmap IT passate avevano la tendenza a soffermarsi solo sulle previsioni tecnologiche e di sistema, omettendo spesso elementi come la riqualificazione della forza lavoro.

Con il rapido cambiamento tecnologico, la riqualificazione del personale dovrebbe essere una loro componente obbligatoria perché è l’unico modo per pianificare e garantire che l’IT rimanga all’altezza del compito di lavorare con le nuove tecnologie. La riqualificazione dovrebbe includere anche piani di formazione trasversale per i membri del personale IT in modo che siano in grado di lavorare in più ruoli se l’IT deve reindirizzare rapidamente le risorse.

Ripensare – o rimpiangere

Come disse una volta Benjamin Franklin: “Fallendo nel prepararsi, ci si sta preparando a fallire”.

Ora è il momento per i CIO di trasformare la roadmap IT in un documento più malleabile e reattivo che possa accogliere i cambiamenti dirompenti nel business e nella tecnologia che le aziende probabilmente sperimenteranno.