A Management Team for The Time of Digitalization
Digitalization and AI are rapidly reshaping how value is created and how work is organized. That imposes new minimum requirements on knowledge and ways of working for everyone in a management team. This article captures the essentials: why change is necessary, how digitalization differs from digital transformation, and the four competence domains that define the competent management team going forward.
Why now?
Technology has always driven productivity and competitiveness. Hence, people in leading position has always had to add new competencies to be able to support the technological progress necessary for their organizations to stay relevant. Back in the eighteen hundreds it was the steam engine and later electricity. Today, software and machines are intelligent and accessible enough that increasingly practical and cognitive tasks can be automated. Organizations that wait risk higher costs, weaker service experiences, and lower attractiveness versus competitors and citizens’ expectations.
For public sector competition is not the challenge. Instead, productivity gains become a social‑sustainability issue: without them, people will loose confidence in society and also suffer in very practical sense. In short, there is no alternative to exploring new technology now. And to do that, management teams need a set of skills, some timeless and others more relevant right now.
Four competence domains for the competent management team
1) Technological literacy – understand what is possible now and soon.
Build a shared, basic understanding of what AI, machine learning, and generative AI can—and cannot—do, especially in your domain. You rarely need to code, but you do need a common vocabulary and mental map of the tech. That improves discussion quality, decision‑making, and the ability to inspire employees—particularly in cultures that meet technology with caution.
2) Data‑driven ways of working – make insights measurable and recurring.
As more processes leave digital traces, data becomes a new “sense” for perceiving reality. Start by inventorying existing data, define meaningful metrics, and establish simple, regular follow‑up. The goal isn’t to measure everything—but to enable better decisions, faster learning, and clearer priorities
3) Innovation management – methodology, not luck.
Digitalization and sustainability ambitions require turning ideas into implemented reality. Research shows that organizations working systematically with innovation become far more successful over time. A management team should understand core processes (from idea and prototype to scaling), foster a test‑and‑learn culture, and allocate capacity to run multiple tracks in parallel.
4) Leading self‑organizing teams – increase speed, ownership, and collective intelligence.
Transformation is more expedition than package tour. The organization must explore several paths while operations keep running. Heavy central micro‑management becomes a bottleneck that dampens initiative and collective intelligence. Self‑organizing teams—even with very light formal leadership—can deliver strong effects but require:
- Clear goals in an anchored strategy (where we’re going, not exactly how), and
- A clear culture with norms for mandate, transparency, and collaboration.
Practical next steps for the management team
- Set a common minimum level of technological literacy (brief AI/data bootcamp for leaders).
- Inventory existing data and agree on 5–10 metrics with clear owners and weekly/monthly visibility.
- Establish a simple innovation flow (idea → test → decision → scale) and fund 2–3 priority tracks.
- Pilot a self‑organizing team in one area with clear goals, guardrails, and lightweight reporting.
- Strengthen governance: refresh strategy, decision rights, transparency principles, and basic cyber/data protection.
Questions for the next leadership meeting
- Which concrete customer/citizen value can we improve fastest with AI in the next 6–9 months?
- Which three data flows would best support decisions if visible every week?
- Where is central control a bottleneck today—and how do we test self‑organization there?
- What innovation process do we use – if any? How many ideas are in test right now?
- What minimum level of tech understanding should every leader reach—and how will we assess it?
Conclusion
Tomorrow’s competent management team is curious, data‑driven, methodical in innovation, and confident letting go of micro‑control. Courage to prioritize, willingness to learn, and the ability to apply technology—these are the keys to higher productivity, better services, and an organization that both delivers today and learns faster than the outside world tomorrow.