When Good Management Becomes an Obstacle to Necessary Change

Angela Merkel’s recently published memoir Freedom arrives at a pivotal moment for organizational leadership. As Yascha Mounk notes in his recent Financial Times analysis, Merkel’s legacy reveals how competent management can coexist with systemic failure. This paradox resonates deeply in today’s digital transformation landscape.[1]

A campaign poster for Angela Merkel, 1995. Creative Commons.

The Architecture of Dependency

Merkel’s Germany built its success on what built its success on what former German Defense Minister Annegret Kramp-Karrenbauer described as a triple vulnerability: dependence on American security, Russian energy, and Chinese markets.[2] This architecture of dependency mirrors what we see in many global organizations’ digital transformations.

Consider Microsoft's recent AI initiatives. Despite its technological prowess, the company has found itself deeply dependent on OpenAI for core AI capabilities, investing over $13 billion in the partnership.[3] According to Helmond and Ferrari's research (2024), “there is no AI without Big Tech”—organizations have created similar triple dependencies in their AI initiatives by relying on single vendors for cloud infrastructure, data processing, and AI models.[4]

Examples of triple dependency:

A company using only Amazon Web Services (AWS) for cloud storage, Amazon SageMaker for data processing, and Amazon's pre-trained AI models for their machine learning projects.
A company relying solely on Microsoft Azure for all aspects of their AI development, including cloud storage, data pipelines, and AI models.

Potential solutions to mitigate this dependency:

Multi-cloud strategy:
Utilize different cloud providers for different aspects of an AI project, depending on specific needs and strengths of each platform.
Open-source AI tools:
Leverage open-source AI frameworks and models to build custom solutions and avoid reliance on a single vendor.
Best-of-breed approach:
Select the best data processing tools, AI models, and cloud infrastructure from different vendors to create a customized AI solution.

The Competency Trap

General Stanley McChrystal’s experience in Iraq provides a compelling lesson about over-optimization.[5] Although his forces won tactical battles, they lost strategically because they couldn’t adapt fast enough to a constantly evolving enemy.

Research by Goldsmith (2023) identifies how success in stable times can become a liability during periods of rapid change.[6] McKinsey’s research shows that 70% of digital transformation failures stem not from technical limitations but from an inability to reimagine existing competencies (McKinsey Digital, 2023).[7] Managers often fall into the trap of thinking that improving each part of their enterprise will improve the whole. However, the opposite is often true.

Consider IBM Watson's journey in healthcare.[8] While their deep enterprise computing expertise was profound, it actually hindered their ability to compete in the consumer AI market. The company’s $6.5 billion investment in Watson ultimately suffered from a curse of incumbent competency, creating a constraint as the field evolved.

Below the Waterline: The Hidden Dimensions of Change

Edgar Schein’s “waterline theory” (1985) provides a framework for understanding why both Merkel’s approach and many digital transformations falter.[9] Above the waterline lie visible elements: policies, technologies, and formal structures. Below are the cultural assumptions, power dynamics, and unstated fears that often determine outcomes.

The Silicon Valley Bank collapse offers a telling example.[10] While the Federal Reserve’s analysis focused on technical failures, subsequent studies by the U.S. Government Accountability Office revealed critical weaknesses in risk assessment culture and governance—classic below-the-waterline issues.[11]

The Ethics-Innovation Tension

Perhaps most revealing is how Merkel’s Germany and today’s tech leaders struggle to balance ethical considerations with competitive pressures. Frances Haugen's congressional testimony revealed Meta’s internal documents, demonstrating how even well-intentioned ethical guidelines can falter against market pressures—much like how Germany’s ethical foreign policy aspirations ultimately yielded economic imperatives.[12] [13]

Leadership in an Age of Transformation

The World Economic Forum’s 2024 Global Risks Report highlights how traditional management skills can become liabilities during fundamental transitions.[14] As O’Reilly and Tushman argue, successful transformation requires ambidextrous leadership—managing current operations while simultaneously reimagining the future.[15] This is precisely what both Merkel’s Germany and many organizations struggle with.

Moving Forward: Beyond Competent Management

The path forward requires a new leadership model beyond mere competent management. Drawing from both Merkel’s experience and contemporary organizational research, several principles emerge:

Strategic Autonomy: Organizations must balance efficiency with resilience, avoiding over-dependency on any single technology, vendor, or approach.
Authentic Transformation: Change must extend below the waterline, addressing cultural, structural, and technical issues as well as technical ones.
Ethical Integration: Organizations must integrate ethical considerations into their core strategic thinking rather than treat ethics as a constraint.

Conclusion: Timing, courage, and the ability to adapt

Merkel’s memoir and contemporary organizational research demonstrate that even the most competent management may not be enough, and the skills that drive success can become liabilities during fundamental transitions. The challenge for political and organizational leaders is recognizing when stewardship must give way to transformation and finding the courage to act on that recognition.[15] The most significant risk for political and corporate leaders may be the inability to recognize good timing.

Dr. Christine Haskell is a digital transformation advisor and author of Driving Data Projects (2024) and Driving Your Self Discovery: Leveraging Human Skills as a Catalyst for Data Transformations (2021, 2024), which examines how organizations can balance technical excellence with human-centered change.

Resources:

Mounk, Y. (2024). “The German Model is Failing” Financial Times Analysis.
The Briefing. (2022) “The war in Ukraine is going to change geopolitics profoundly.” The Economist.
Bloomberg. (2024). “Microsoft's $13 Billion Bet on OpenAI.”
Helmond, A., & Ferrari, F. (2024). Big AI: Cloud infrastructure dependence and the industrialisation of artificial intelligence. Big Data & Society. https://doi.org/10.1177/20539517241232630
https://hbr.org/2016/01/optimizing-each-part-of-a-firm-doesnt-optimize-the-whole-firm
Goldsmith, M. (2010). What Got You Here Won't Get You There: How Successful People Become Even More Successful. United Kingdom: Profile.
https://www.mckinsey.com/industries/retail/our-insights/the-how-of-transformation#/
https://medium.com/@14asaikiran06/the-rise-and-fall-of-ibm-watson-lessons-from-ais-journey-in-healthcare-8d43bb60cc85
Schein, E. (1985). Organizational culture and leadership: A dynamic view. Jossey-Bass.
https://www.nytimes.com/2023/04/28/business/economy/fed-silicon-valley-bank-failure-review.html
https://www.federalreserve.gov/publications/review-of-the-federal-reserves-supervision-and-regulation-of-silicon-valley-bank.htm
https://www.washingtonpost.com/technology/2021/10/26/frances-haugen-facebook-whistleblower-documents/
https://www.nytimes.com/2024/11/22/world/europe/merkel-memoir-trump-putin.html; https://www.nytimes.com/2018/12/05/world/europe/merkel-legacy-germany.html
World Economic Forum. (2024). Global Risks Report 2024.
Haskell, C. (2024). Driving Your Self Discovery: Leveraging Human Skills as a Catalyst for Data Transformations. Pencils to Pixels Publishing.