By H. Krishnanunni, IAS
Observation
Butterfly flaps…
Implementing technology is rarely as simple as conceiving it. Across multiple projects at every level of the Indian public sector, I have seen well-intentioned technology initiatives not yielding intended results—not because of lack of effort or investment, but because of recurring structural challenges. Too often, technology adoption leads to layering digital interfaces atop legacy systems without fundamentally rethinking entrenched processes, approvals, and priorities.
Instead of unlocking the full potential of digital transformation, these initiatives risk creating digital replicas of old inefficiencies, sustaining bottlenecks, diffusing accountability, and even amplifying friction. Despite the criticality, projects struggle with this reality; early digitalisation efforts may appear modern on the surface but behave like their analog predecessors underneath.
This experience revealed that the heart of the problem lies not in the technology itself, but in how systems are designed and adapted to real-world needs. The reluctance to challenge outdated frameworks is one issue. The failure to embed continuous learning and a narrow focus on quantifiable activities rather than meaningful change further undermine lasting progress.
Reflection
Principles
Genuine transformation demands a fundamentally different approach—one built on three key principles:
- Process Reinvention: Redesigning processes instead of replication. True progress is achieved only when processes are fundamentally rethought and redesigned, rather than simply digitising existing systems.
- Feedback-driven Adaptation: Embracing feedback-driven adaptability. Continuously collecting and acting on feedback allows systems to remain responsive and evolve to meet real needs.
- Outcome Orientation: Measuring success through outcomes, not just outputs. Genuine impact results from working towards meaningful, real-life outcomes—not merely measuring the number of activities, financial expenditure, or similar parameters.
Each of these principles, drawn from my practical experience so far, has repeatedly proven essential for sustainable system design in public service.
Principles to Practice
In practice, a major flaw in many technology projects is that existing multi-level approval systems are simply digitalised, leading to only marginal improvements. The process becomes a digital twin of the old: while processing speeds increase, the workflow itself remains long, redundant, and often cumbersome. The introduction of a new digital interface adds to the woes rather than simplifies them.
Had processes been genuinely reengineered, digitisation could have saved time by simplifying steps, reducing the training load, improving efficiency, cutting costs, and enabling quicker adaptation in response to change.
Another persistent pitfall in public sector digital transformation is misunderstanding the promise of analytics, and more crucially, confusing outputs with outcomes. These terms are widely hyped but poorly understood. It’s common to see projects and processes, like audits, focus on measurable outputs—such as amounts spent from allocated funds or numbers of activities achieved—while real outcomes, like the actual impact on people, often go unmeasured. In aspects like public procurement, even after technology adaptation, limitations of concepts like lowest bid as an indicator of efficiency result in quality failures and eventual cost overruns—the very opposite of the intended outcome.
During my time implementing the “Punnagai” tele-health and tele-education initiative in the tribal areas of Erode district in Tamil Nadu, I found these lessons especially instructive. Instead of merely placing traditional classroom formats online—which would simply replicate existing access barriers in digital form—we fundamentally reimagined how to deliver education in remote areas.
The model we built was shaped by continuous engagement with the community, custom-tailored digital content, and a flexible mentoring system that responded to context. Real-time feedback mechanisms allowed us to address new challenges as they appeared—adjusting teaching approaches and reallocating resources accordingly. Most importantly, success metrics were redefined: beyond tracking sessions or technology usage, the initiative focused on what truly mattered—literacy improvement, confidence gains, and sustained participation among students who had previously struggled to access quality education.
Thus, integrating the principles of reform over replication and clarity on outcomes versus outputs is not just theoretical but essential. My experience with “Punnagai” convinced me that true digital transformation materialises and sustains only when processes are truly reimagined, feedback is actively used for adaptation, and the focus remains grounded in real, measurable social impact.
Revelation
The Grand Design
While it is good to share such successes in the public administration sphere, failures are no less important. The wise learn from both and strive to be better. Curiously enough, one can observe that these principles are not just human inventions—they are also ever-present in natural systems. Nature, through the logic of evolution, operates on a “survive or perish” model: old forms are not blindly replicated, feedback from the environment is instant and uncompromising, and only outcomes matter—measured by survival and fitness.
Nature’s Survival Logic: Process, Feedback, and Outcomes
Nature’s evolutionary playground is governed by a relentless “survive or perish” imperative. Biological processes never succeed by simple imitation. Each adaptation is relentlessly shaped and tested by real-world feedback: traits or systems that ignore their environment or fail to produce functional outcomes are ruthlessly eliminated. In this sense, nature is the purest practitioner of redesign, analytics, and outcome-orientation—an impartial, decentralised system always optimising for survival through continuous feedback and uncompromising results.
Humanity: The Source of Antithetical Principles
Humans, as players in nature’s game, are unique. Evolution gifted us consciousness, language, memory, and complex social bonds—traits that allowed the creation of technology, law, storytelling, and culture. Yet these very blessings seeded traits antithetical to nature’s raw logic:
- Psychological Bias: Humans instinctively are overwhelmingly loss-averse, resist uncertainty, and choose stability over necessary disruptive change. Our minds default to what is comfortable, habitual, and familiar.
- Sociological Structure: Societies, through tradition, hierarchy, and politics, are often designed to preserve harmony over excellence, comfort over innovation, consensus over disruption. This echoes ancient philosophical observations—from Plato to Kautilya—recognising that the very best, if disruptive, may not be chosen to lead; collective stability is preferred to transformative greatness.
- Technological Reflection: Technology, being human-created and human-operated, inevitably mirrors our biases and inertia. Systems are designed for ease, not always excellence; feedback is tempered by hierarchy, not always by data.
The Newcomer
Artificial intelligence presents a tantalising prospect. Unlike its human creators, a well-designed AI can, under ideal circumstances, create technologies based on the same bias-free principles that drive nature: redesign for purpose, learn and adapt from data, and commit to real, measurable outcomes. Free from inherent human biases, it can create systems that genuinely simplify life and optimise utility.
Yet, a paradox looms: AI inherits the biases of its makers, no matter how minuscule. Every line of code, every dataset, every optimisation decision is shaped by human priorities, histories, and perceptions. While AI may be less susceptible to human bias, it can never be entirely free of them. The goal, then, is not universal objectivity, but achieving a bias balance so that AI-driven systems remain adaptable, functional, and contextually appropriate for their intended users, with transparency on the bias.
This synthesis—spanning evolutionary biology, philosophy, psychology, sociology, and technology—highlights a universal truth: effective system design, whether in nature or society, is rooted in continuous adaptation, feedback sensitivity, and outcome focus. Humans, with their complexity, add layers of bias and inertia that must be consciously managed—especially in the creation and deployment of technology.
As we embrace artificial intelligence and seek to govern its evolution, the interplay of these disciplines becomes more important than ever. Understanding where nature’s wisdom ends and human foibles begin is critical—not to achieve perfection, but to build systems that are both wise and effective.
Retrospection
The wisdom of nature—redesign, feedback, and outcome—is ever-present, while human systems inevitably wrestle with bias and inertia. Technology, and especially AI, can magnify both our failings and hopes. The challenge is not to eliminate bias, but to learn from nature’s models, transcend our limitations where we can, and design with humility, adaptability, and real-world impact always in view. Let the right flutters result in a transformative butterfly effect—one that not only mirrors nature’s wisdom but also strengthens public service and societal outcomes.
The author is an IAS officer of 2012 batch.