From digital failure to organizational intelligence
The Evolution Hidden Behind Static Statistics
While companies in 2007 were digitizing existing processes, today's organizations are rebuilding their entire organizational architecture. They're grappling with AI-human hybridization, digital sovereignty, distributed tech ecosystems, and regulatory frameworks that didn't exist two decades ago.
If sector-wide failure rates remain stable despite years of experience, it's because challenge complexity has exploded faster than our collective ability to master it. The real problem isn't the failure rate itself—it's the persistent inability to measure and navigate organizational complexity.
Too many organizations still confuse activism with performance. They measure velocity instead of client impact. They multiply initiatives instead of solving structural problems.
Why Banking Crystallizes All Organizational Complexity
As a Digital Factory Director, I witness this complexity explosion daily. Banking institutions carry multiple societal expectations: quality service, absolute trust, maximum security, continuous innovation, positive environmental impact, and digital sovereignty.
Unlike fintechs that can focus on specific segments, traditional banks must simultaneously:
Maintain critical legacy systems (decades of accumulated technical debt)
Comply with constantly evolving regulations (KYC, AML, GDPR, DORA)
Manage complex IT architecture from successive mergers
Integrate AI while preserving decision explainability
Ensure service continuity while modernizing infrastructure
McKinsey reveals traditional banks are 40% less productive than digital natives, with 4-6 month deployment cycles versus 2-4 weeks for fintechs. BCG confirms over 60% of banking tech spending goes to "run-the-bank" rather than "change-the-bank."
This complexity explains why traditional change management methods, designed for simpler worlds, reach their limits in our sector.
The Four-Legged Stool Method: Turning Complexity Into Competitive Advantage
Why the stool analogy? It perfectly illustrates organizational complexity management reality. A stool becomes immediately unstable when it loses one leg. With only two legs, it's guaranteed collapse. This absolute interdependence reflects exactly what happens in transformations: neglecting one pillar destabilizes the entire system.
This method, inspired by Toyota Production System fundamentals, doesn't claim to revolutionize sector statistics overnight. It aims for something more pragmatic: transforming organizational complexity into a predictive management system that learns faster, limits potential failure scope, and maximizes value creation even in uncertainty.
Pillar 1 - Lagging Indicators: Obsession with Final Client Value
The first leg revolutionizes metrics relationships in complex environments. Gone are KPIs disconnected from client value—those vanity metrics that reassure committees without creating real impact. In banking, this means measuring outcome rather than output: user adoption vs features deployed, client time-to-value reduction vs completed sprints, compliance experience improvement vs formal conformity.
Instead of counting launched AI projects, we measure client experience improvement through AI. Instead of celebrating completed technical deployments, we track response time reduction and resilience improvement. This approach creates sustainable strategic alignment where priorities constantly change.
Without this first leg, organizations lose direction in growing complexity.
Pillar 2 - Leading Indicators: Anticipation in Uncertainty
The second leg transforms reactive organizations into predictive systems capable of navigating uncertainty. These operational milestones become early warning signals—organizational radar detecting weak signals before they become major crises.
Think Kanban applied at organizational scale: each indicator triggers action at the right moment, avoiding overproduction and waste. In banking, this means anticipating regulatory evolution, detecting team saturation signals, identifying critical system performance drift before client impact.
Companies using predictive indicators multiply their transformation success chances by 7x according to sector studies. More crucially in complex environments: they develop adaptation capacity that helps them bounce back faster after inevitable difficulties.
Without this second leg, organizations suffer complexity instead of anticipating it.
Pillar 3 - Visualization: Collective Intelligence Facing Complexity
The third leg materializes an organizational Andon adapted to banking complexity. Making problems visible to everyone transforms each collaborator into an intelligent performance sensor, capable of detecting weak signals in environments where complexity often masks dysfunctions.
This radical transparency changes the game in traditionally opaque banking: instead of hiding dysfunctions from fear of sanctions, teams expose them to resolve them faster. This translates to real-time dashboards revealing hidden interdependencies, transparency rituals about systemic blockages, organizational health metrics visible to all.
McKinsey confirms organizations with clear objective communication are 3.5x more likely to succeed in transformation. But in complex environments, the challenge exceeds communication: it's about creating collective intelligence capable of understanding and managing systems no one masters individually.
Without this third leg, complexity remains opaque until it generates crises.
Pillar 4 - Collaborative Resolution: Intelligent Distributed Autonomy
The fourth leg embodies Gemba Walks spirit applied to banking complexity: going to see in the field, where value is created and innovative solutions emerge. In banking, this means responses to complex challenges are born from combining field expertise: branches, call centers, development teams, risk managers, compliance officers.
This approach multiplies complex problem-solving capacity without creating bureaucracy. Field teams, who daily experience systemic interdependencies, often develop more relevant solutions than external consultants. 98% of companies adopting collaborative frameworks report significant transparency improvement.
Without this fourth leg, organizations remain paralyzed by centralization facing complexity.
The System Effect: Creating Hybrid Intelligence
This four-legged stool method creates virtuous feedback loops specifically designed for banking complexity. Lagging indicators reveal real impacts in environments where effects are often delayed, Leading indicators anticipate consequence cascades in interdependent systems, Visualization makes complexity intelligible for collective action, and Resolution generates distributed learning that continuously enriches the entire system.
It reconciles apparently irreconcilable tensions of modern banking management: rapid innovation versus regulatory stability, team autonomy versus systemic coherence, economic performance versus public interest mission.
From Sector Activism to Systemic Intelligence
In a sector where statistics show 70% of transformations don't reach their objectives, where challenges complexify faster than collective capacity to master them, this stool method offers an alternative to usual organizational activism observed in the industry.
It doesn't promise to make complexity disappear—that would be illusory. It proposes something more realistic and powerful: transforming an organization into a learning system capable of navigating complexity, leveraging it, and creating sustainable value even in uncertainty.
Institutions succeeding in transformations today aren't those avoiding complexity, but those developing collective intelligence to manage it. This method allows banking institutions to develop this intelligence while maintaining regulatory robustness and public interest mission.
The secret of banking resilience in a complex world isn't in excessive simplification or local optimization. It lies in the capacity to create an environment where everyone contributes to understanding and solving systemic problems, guided by indicators revealing hidden dynamics, in a system that learns and continuously improves.
🚀 CALL-TO-ACTION
Which leg needs strengthening in your organization? Is it measuring real impact, anticipating consequence cascades, visualizing interdependencies, or building distributed collective intelligence?
Share your biggest complexity challenge in banking transformation—I'd love to explore how the four-legged stool method could apply to your specific context.