IT teams require a strategic balance of hard and soft skills
You can’t hire based on technical skill alone. Yes, you need teams that know their way around modern architectures, cloud platforms, APIs, data ingestion, AI pipelines. That’s a given. But if your engineers can’t communicate clearly, can’t revise their thinking under pressure, or work poorly with others, then you’re putting drag on execution.
True IT performance comes from teams that are technically sharp and equally strong in problem solving, communication, and collaboration. You want professionals who can code, yes, but also those who can dissect a business challenge, plug into a wider team goal, and express complex realities in simple terms. It’s not glamorous, but it’s essential if you aim to scale tech with the business.
Ximena Gates, CEO and co-founder of BuildWithin, makes the point clearly. Her team doesn’t rely solely on technical assessments. From the very first conversation, they evaluate resilience, curiosity, and how people react under pressure. These are qualities that determine whether technical talent can actually drive outcomes. Gates put it simply: “High performance is like a relay race. Every team member must be a well-rounded athlete.” She’s right.
If you’re still hiring talent based purely on a resume of frameworks and certifications, you’re several years behind. Technical skills get you in the game. Soft skills keep you there, and take you further. The companies who get this right are already executing faster, adapting quicker, and producing higher business value from their IT spend.
Soft skills are indispensable
Let’s be clear: knowing how to code or run infrastructure isn’t the hard part anymore. Much of that is being automated or heavily abstracted. What matters now is how your team uses technology to solve actual business problems. That takes more than technical capability. It takes clear thinking and the ability to collaborate with teams who don’t speak tech.
Soft skills, like concise communication, adaptability under pressure, the ability to listen, are what create momentum in cross-functional environments. Without them, your IT talent operates in a silo. With them, you’re building systems and solutions that actually move your metrics.
Chris Campbell, CIO at DeVry University, hit the nail on the head. He said his team needs people who can “speak the language of the business.” That means explaining technical decisions without defaulting to jargon. It also means understanding what stakeholders care about and aligning tech work to real outcomes, faster delivery, risk mitigation, better margins.
Ramesh Kollepara, CTO at Kellanova, reinforces this mindset. He said that building a learning culture depends on balancing soft and hard abilities. His focus is long-term: creating durable skills, like curiosity and adaptability, that outlast any short-term trend or toolset evolution.
For C-suite leaders, the lesson here is direct: don’t separate technical and interpersonal aptitude when evaluating performance or planning team structures. Train both. Incentivize both. Because execution is multi-dimensional, and the future belongs to teams that can operate as one integrated unit, not fragmented technical experts working in isolation.
Hiring strategies must evaluate both hard and soft skills
If you want people who can actually ship results and not just recite buzzwords, you need to overhaul how you hire. Too many companies still treat the interview pipeline as a checklist process, technical screen, maybe a culture fit, then an offer. That’s not how top-tier teams are built.
Hiring now has to test for more than technical correctness. You need to know how people think, how they solve ambiguous problems, how they explain their logic, and whether they can handle working with product, sales, or operations without friction. If you skip that, you end up with high-cost talent producing low-impact output.
Louis Ormond, VP and GM at Toshiba America Business Solutions, explained their shift in approach. They run multi-interview loops, bringing in people from different teams who challenge candidates from multiple angles. It’s not just about whether you can solve the problem, but how clearly you explain your thinking. Erin DeCesare, CTO at ezCater, does something similar, her candidates are put into real-world scenarios that push them to interact with both technical data and stakeholder input simultaneously. It’s a pressure test for execution and collaboration.
John Samuel, COO at CGS, takes it further. He layers questions, moving between pure tech and interpersonal challenges. He wants to see where candidates fail, how they bounce back, who they blame when things go wrong. Chris Campbell at DeVry University adds behavioral criteria, he flags anyone who hides behind technical jargon when asked to explain concepts in a business context. If a candidate can’t break down what they do to someone outside IT, they’re not likely to drive cross-functional value.
This isn’t excessive. It’s efficient. When you’re building high-leverage tech teams, you can’t afford to onboard misaligned thinkers. You want professionals who hit the ground already fluent in execution and interaction. That starts with how you hire.
Continuous development increases IT team capabilities
Hiring is just the starting point. What matters most is what happens after talent joins your team. If you’re not actively developing people, technical range, soft skill depth, business alignment, you’re leaving future results to chance. Most companies play it passive. That’s lazy leadership.
Real capability building isn’t about occasional workshops or one-time feedback. It’s persistent and compounding. Systematic training must evolve with technology and business goals. That includes fluency in areas like machine learning and cloud architecture, but also emotional intelligence, strategic thinking, and communication across disciplines.
At Kellanova, global CTO Ramesh Kollepara runs structured development via the YODA initiative, Year of Development Always. His teams stay current on programming languages, emerging tech, and internal collaboration tactics all year. The point isn’t just education. It’s internal agility. Dennis Di Lorenzo at Micron Technology pushes this further. He aligns development targets to business outcomes and uses AI to assess skill gaps and personalize training paths. The result? A team that doesn’t just keep up, it anticipates.
John Samuel at CGS folds this directly into performance management. He runs quarterly reviews to track progress, adjust focus, and deliver coaching. This isn’t handled like a formality, it’s a feedback loop with accountability. If someone needs help with coding logic, they get it. If they need help managing conflict in a cross-functional team, they’re trained on that, too.
For executive leaders, this matters because scale and resilience depend on your people. If you train smart, review purposefully, and course-correct fast, you’ll end up with teams that move ahead of market shifts, not behind them. That’s how you keep your edge.
Cultivating a culture that reinforces balanced skill development
If you’re serious about performance, you need to create an environment where people aren’t afraid to ask for help or admit what they don’t know, technical or otherwise. Most organizations reward certainty over curiosity, which is a mistake. You scale faster when people are honest about gaps because that’s the only way to close them quickly.
Tech evolves by the month. What made sense a year ago is now outdated. The same goes for interpersonal demands, managing remote teams, presenting to nontechnical audiences, adjusting to hybrid workflows. If your culture doesn’t support openness and continuous learning, your teams will fragment. They’ll stagnate.
John Samuel, COO at CGS, puts it in plain terms: teams need space to develop both their core competencies and their interaction skills. That doesn’t happen through top-down process alone. It requires a culture where employees can say, “I’m struggling with this,” without fearing judgment or losing ground politically. Quarterly reviews, coaching conversations, and cross-team mentorships become tools, not checkboxes, only when people feel safe using them.
This is where leadership sets the tone. You can talk about growth mindset and agility all day, but unless your management behavior reflects it, people won’t act on it. Foster a habit of direct feedback. Normalize conversations about developing a better understanding of stakeholder needs or tightening up code reviews. Make it okay to be in-progress.
For C-suite leaders, the opportunity is big. A culture with open dialogue compounds its advantages. Teams adapt quicker, share knowledge faster, and build trust across departments. The payoff isn’t theoretical, it shows up in faster product cycles, improved cross-team execution, and a more resilient workforce. The companies that move like this don’t just retain top talent, they develop it.
Key takeaways for decision-makers
- Prioritize balanced hiring: Relying solely on technical skills limits team performance. Leaders should hire IT professionals who can code, problem-solve, and collaborate effectively to meet today’s complex business demands.
- Build tech talent that understands business: IT teams must communicate clearly and align their work with business goals. Prioritize training and hiring practices that build team fluency in business language and stakeholder needs.
- Redesign interview processes: Modern talent evaluation must equally assess technical execution and interpersonal effectiveness. Use multi-perspective interviews and real-world scenarios to identify candidates who can collaborate and deliver under pressure.
- Invest in continuous, targeted training: Ongoing development in both hard and soft skills is critical to keeping teams agile and aligned. Leaders should embed skill-building into performance reviews and tie learning outcomes to strategic goals.
- Normalize open feedback and growth discussions: Execution improves when teams feel safe acknowledging gaps and developing capabilities. Create a culture that supports direct dialogue, proactive learning, and cross-functional knowledge sharing.
