Breaking the Barriers: Why Transformation Stalls in Everyday Work

Karolina Kristić, Chancellor/CFO, Frankfurt School of Finance & Management.

Most transformation initiatives fail not because the target vision is wrong, but because day‑to‑day realities prevent change from taking hold. Cultural norms, limited resources, leadership behaviour and missing competencies quietly block progress, often long before KPIs show it.

In this case‑study interview, Karolina Kristić, Chancellor and CFO of Frankfurt School of Finance & Management, shares hands‑on insights into the real barriers that hinder transformation in daily operations, and what leaders and controlling functions can do to remove them.
 

Which cultural or social barriers most often slow down transformation once it reaches daily operational work?

Once transformation reaches daily operations, the real barriers are rarely technical. They are social: pace, uncertainty, overloaded middle managers and the quiet return to old habits. Current employer surveys still rank culture and resistance to change among the biggest obstacles, and that matches what I see. People are asked to change while targets, approval lines and workloads stay the same. Being ‘not digital native’ is less an age issue than a mindset issue; curiosity matters more than birth year. And many firms claim to tolerate failure, but the first visible mistake is still punished. That is not a learning culture; it is theatre.

From your experience, where do resource constraints genuinely block change and where are they used as an excuse?

Recent employer surveys are very clear: after skills and culture, regulation is one of the main barriers to transformation, and that matches my experience. Real resource constraints exist where organisations lack people who can combine business judgement, technology and fast decision-making, or where regulation is still being operationalised. The EU AI Act is a good example: the guardrails are necessary, but many firms are still waiting for perfect clarity instead of building capability. In most cases, the bigger problem is not absolute scarcity, but poor prioritisation. The resources are there, just locked in legacy tasks, slow governance and defensive behaviour. Too many people focus on protecting roles instead of improving outcomes.

What leadership behaviours unintentionally undermine transformation, even when intentions are good?

Leaders undermine transformation when they speak about empowerment but keep the important decisions for themselves. Another common mistake is demanding accountability without modelling it, hiring only for technical skills and not for judgement or character, and treating motivation as if it could be managed by supervision alone. Strong people do not need babysitting; they need clarity, standards and room to take manageable risk. The worst signal is when high performers see that extra effort is neither rewarded nor protected, while underperformance is tolerated. At that point, the organisation stops believing the change is serious.

Which competence gaps are most critical during transformation, and how quickly can organisations realistically close them?

This is not just my impression; current employer surveys still put skills gaps at the top of transformation barriers. The biggest competence gaps are contextual thinking, problem framing, judgement and collaboration. AI does not remove the need for expertise; it raises the premium on it. If the input is weak, the output is simply faster nonsense. Prompting matters, but good prompting depends on real knowledge. Networking and team spirit are also underestimated, because transformation usually fails at the interfaces between functions, not in the strategy deck. Basic AI literacy can be improved within months, but deeper business judgement and cross-functional trust take much longer and have to be built in real work.

What can controlling and finance do, practically, to identify and remove these barriers before transformation loses momentum?

Controlling and finance should act as the organisation’s early-warning system. They can help by turning KPIs into management narratives rather than mathematical rituals. Numbers should show where momentum is real, where it is stalling and why. Because finance works across business units, it can see the cost of silos more clearly than most functions. Practically, I would track adoption, decision speed, capacity shifts, exception rates and rework alongside classic financial metrics. Finance should also force common data definitions and trusted data across the organisation. Its role is not only to report variance, but to surface hidden friction early and make ownership impossible to avoid.
 

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