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89 percent of all companies still operate with functional hierarchies, matrix structures, or traditional business-unit models. Meanwhile, organizations using product and platform teams deliver features 2.5 times faster and cut their IT costs by 60 percent. By 2026, the gap between outdated structures and new performance capabilities will become a strategic risk.<\/strong><\/p>\n Most IT departments across DACH-region companies evolved organically over time: Business units place project requests; IT delivers. Requirements flow through committees, budgets are allocated annually, and success is measured by on-time delivery – not business impact. This model worked when technology was merely a cost center. In 2026, technology is the central engine of value creation.<\/p>\n The McKinsey Global Tech Agenda 2026<\/a> makes the rupture unmistakable: Among 600 surveyed technology and business leaders, 50 percent plan to increase their technology budgets by more than four percent in 2026. At the same time, AI has displaced both cybersecurity and infrastructure modernization as the top investment priority. Pouring this capital into legacy structures amounts to burning it.<\/p>\n Source: McKinsey State of Organizations, 2025<\/p>\n McKinsey defines the target model as follows: Technology teams organize around user-facing products – and the underlying platforms that enable them. Instead of projects with defined start and end dates, teams are permanent, with clear ownership over a digital product or platform component.<\/p>\n The data speak clearly. Nearly 50 percent of top performers in McKinsey\u2019s survey report that business and technology teams jointly and iteratively develop strategic plans. Across all respondents, that figure stands at 29 percent – nearly double the rate recorded in the previous survey. The trend is unmistakable – but the majority still lags behind.<\/p>\n Concretely, this means: A CIO<\/a> who restructures their team along product-and-platform principles reduces coordination overhead between business units and IT. Product teams understand the business context because domain experts are embedded permanently. Platform teams ensure shared infrastructure – data, AI models, APIs – is available to all product teams.<\/p>\n Those who assume product teams represent the final stage underestimate the pace of change. In 2026, McKinsey introduced the concept of the agentic Organization<\/a>: organizations where humans and AI agents – both virtual and physical – collaborate at scale. Not as isolated experiments within innovation units – but as the core operating model.<\/p>\n The numbers are compelling: AI-centric organizations achieve 20-40 percent lower operating costs and 12-14 percentage points higher EBITDA margins, per McKinsey. And one in four executives expects AI agents to function as autonomous team members in the near term.<\/p>\n For boards, this means: The question is no longer whether<\/em> AI agents will be integrated into the operating model – but how fast<\/em>. Organizations still struggling to shift from project-based to product-based structures will find the leap to an AI-integrated organization nearly impossible.<\/p>\n \n\u201cCIOs must restructure their IT operating models to capture AI value. Current organizational designs are not built to scale AI initiatives.\u201d Germany accounts for 24.5 percent of Europe\u2019s digital transformation revenue. Money is flowing – but into which structures? Practice reveals three typical roadblocks across the DACH region:<\/p>\n First:<\/strong> Co-determination and works councils. Shifting from functional teams to cross-functional product units affects job descriptions, reporting lines, and often collective bargaining agreements. What US multinationals implement in quarters takes months of negotiation in Germany.<\/p>\n Second:<\/strong> Historically grown ERP landscapes. Bosch Digital manages over 50 ERP systems and 80 subsystems across more than 300 legal entities in over 100 countries. Introducing platform teams requires simultaneously addressing this technical debt – or else new teams lack the foundational platform they need to build upon.<\/p>\n Third:<\/strong> A shortage of technically skilled leaders. According to McKinsey, top performers hire technical leaders at nearly twice the rate: 37 percent versus 19 percent among average companies. In German mid-sized firms, these profiles are frequently absent altogether.<\/p>\n The good news: Success rates for operating-model transformations have tripled. Today, 63 percent reach their goals – up from 21 percent a decade ago. The difference lies in methodology.<\/p>\n 1. Map value streams – not org charts.<\/strong> Which digital products and platforms generate business value? These value streams define team structure – not historical departmental logic.<\/p>\n 2. Governance before structure.<\/strong> McKinsey recommends first establishing a governance framework that aligns the technology organization with strategic priorities. Without clear decision rights and prioritization mechanisms, any reorganization fizzles.<\/p>\n 3. Platform teams as the foundation.<\/strong> The platform layer – data, AI models, decision systems – must exist as a standalone organizational unit. McKinsey calls this the Intelligence Layer<\/em>: a unified layer of data, AI models, and decision systems used by all product teams.<\/p>\n 4. Involve Financial Managers early.<\/strong> Top performers hire more Financial Managers to ensure technology investments deliver measurable ROI. Linking IT spend to business outcomes isn\u2019t optional – it\u2019s a board-level responsibility.<\/p>\n 5. Transform iteratively – not via Big Bang.<\/strong> Transitioning from functional to product-based organization rarely succeeds in one step. Define pilot areas, gather insights, then scale incrementally. The 20-30 percent ROI loss caused by poor operating-model alignment stems largely from half-hearted transformations.<\/p>\n The question for the board<\/a> is not technical – it\u2019s organizational: Do we want an IT department that fulfills orders – or a technology organization that creates business value? The former is cheaper to set up but costs 20-30 percent of potential ROI. The latter demands restructuring – but delivers demonstrably superior results.<\/p>\n Gartner puts it plainly: CIOs must restructure their operating models to capture AI value. Those still thinking in projects – not products – in 2026 will miss the transition to the agentic Organization – and thus forfeit the next competitive advantage.<\/p>\n The digital operating model is not an IT initiative – it\u2019s a board-level decision. The evidence is unequivocal: Product and platform teams deliver faster, cheaper, and with greater business impact. The next evolutionary stage – the integration of AI agents as full team members – is already at the door. CIOs who delay restructuring deny their companies access to productivity gains McKinsey quantifies at 20-40 percent. The alternative is the status quo – and that carries a 20-30 percent ROI penalty.<\/p>\n A digital operating model describes how a company structures its technology organization to create business value. At its core, it represents the shift from project-based IT delivery to permanent product and platform teams bearing end-to-end responsibility for digital offerings.<\/p>\n<\/details>\n Agile methods change how teams work internally. A digital operating model changes the organization itself: reporting lines, budget allocation, decision rights, and collaboration between business and IT. Without structural change, agility remains trapped at the team level.<\/p>\n<\/details>\n A full transformation typically takes 18-36 months. McKinsey recommends an iterative approach: define a pilot area, establish governance, then scale incrementally. In the DACH region, co-determination extends timelines by six to twelve months.<\/p>\n<\/details>\n A central one. Per McKinsey, top performers deliberately hire Financial Managers to tie technology investments to measurable ROI. The CFO must understand that IT budgets are no longer allocated by cost center – but by value stream – and that platform investments amortize across multiple products.<\/p>\n<\/details>\n A concept coined by McKinsey in 2026 describing organizations where humans and AI agents collaborate at scale. AI agents don\u2019t just handle discrete tasks – they act as autonomous team members within workflows. Prerequisites include an operating model that institutionalizes data-driven decision systems and AI platforms as formal organizational units.<\/p>\n<\/details>\n CIO Agenda 2026: Between Cost Pressure and Innovation Imperative<\/a><\/p>\n Board Reporting for IT: 5 Metrics the Board Actually Understands<\/a><\/p>\n AI Is Not a Tech Problem: Why 27 Percent of CEOs Fail at Their Own Organizations<\/p>\n cloudmagazin: The VMware Cost Trap 2026 – Why IT Teams Are Exploring Alternatives<\/a><\/p>\n MyBusinessFuture: AI in Mid-Sized Companies – Why Firms Hesitate<\/a><\/p>\nTL;DR<\/h2>\n
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Why the Old IT Organization No Longer Works<\/h2>\n
The Product-and-Platform Model: What Top Performers Do Differently<\/h2>\n
The Agentic Organization: McKinsey\u2019s Next Evolutionary Stage<\/h2>\n
\nGartner, Predicts 2026: CIOs Must Restructure Their IT Operating Models to Capture AI Value<\/cite>\n<\/p><\/blockquote>\nDACH Reality Check: Why Transformation Is Especially Hard Here<\/h2>\n
Five Steps Toward the Digital Operating Model<\/h2>\n
What the Board Must Decide Now<\/h2>\n
Conclusion<\/h2>\n
Frequently Asked Questions<\/h2>\n
What is a digital operating model?<\/strong><\/summary>\n
Why isn\u2019t agile transformation enough?<\/strong><\/summary>\n
How long does it take to transition to the product-platform model?<\/strong><\/summary>\n
What role does the CFO play in the digital operating model?<\/strong><\/summary>\n
What is the agentic Organization?<\/strong><\/summary>\n
Further Reading<\/h2>\n
More from the MBF Media Network<\/h2>\n