Innovation Isn’t Chaos, It’s A System

Innovation is often labelled as a buzzword in today’s business lexicon. In your view, what does ‘innovation’ truly entail? How do you distinguish genuine innovation from mere rhetoric?

Innovation is not about mad scientists and chaos. The best innovations follow a disciplined, structured, and systems-driven process.

There are different ways to approach innovation, and I’d like to structure my response in two parts: first, what innovation entails, and second, how innovation can be made more effective within a system, rather than distinguishing between “genuine” and “ingenuine” innovation. 

To begin with, there are three paradigms through which we can look at innovation. The first is the temporal paradigm, which views innovation across short-term, medium-term, and long-term horizons. 

In the short-term, innovation solves yesterday’s problems. For example, you notice something going wrong — perhaps due to competitive pressures, regulatory changes, or geopolitical factors — and need to resolve it. This kind of innovation is about catching up and solving immediate issues. 

The medium-term perspective focuses on goals for the next one to two years. Here, innovation aligns with the organisation’s vision, ensuring progress without venturing into highly disruptive territory. You work with a clear understanding of the organisation’s direction and drive innovation accordingly. 

Lastly, long-term innovation is about aligning with the organisation’s broader vision — what it aspires to achieve in the next 10 years or more. This is where revolutionary ideas come into play. Think of Uber disrupting transportation, Elon Musk’s dreams of colonising Mars, or NASA’s advancements in space exploration. Such innovations aim to shape the future and leave a lasting legacy. 

Another paradigm is the quantum of innovation — the scale or degree of change being pursued. At the most basic level, you have incremental innovation, which involves minor improvements to a product, service, or process. For example, enhancing production efficiency, reducing costs, or slightly improving the quality of a product. 

The next level is medium-scale innovation, which offers a competitive advantage but isn’t entirely disruptive. For instance, replacing traditional toothpaste with chewable tablets — a notable improvement, but not a radical departure. 

Finally, there’s radical innovation, where the entire concept changes. For example, imagine a toothbrush releasing cleaning agents without toothpaste. In manufacturing, radical innovation might involve embedding a mini-factory within fishing trawlers, where fish are caught, cleaned, and canned onboard, significantly reducing supply chain inefficiencies. 

The third paradigm is the systems perspective of innovation. Contrary to popular belief, innovation isn’t just about chaotic creativity. It’s often a systematic, structured process involving internal and external stakeholders, a supportive organisational culture, dedicated resources, and defined procedures. Successful companies and industries — be it IKEA, Tesla, or Nordic fishing firms — follow a systems approach, ensuring that creativity is channelled effectively within a process. 

Joseph Schumpeter’s concept of “creative destruction” illustrates that innovation often requires breaking away from the status quo. However, industries sometimes stagnate due to inefficiencies and need fresh, often external perspectives to drive change. For instance, Tesla wasn’t founded by legacy car manufacturers, Uber didn’t come from traditional taxi companies, and Airbnb wasn’t created by hotel chains. These disruptors came from the outside, highlighting how both internal and external forces drive innovation. 

To sum up, innovation can be viewed through three lenses: temporal, quantum, and systems. Temporal innovation addresses immediate, medium-term, and long-term goals; quantum innovation spans incremental to radical changes; and the systems perspective ensures a structured, sustainable process. Genuine innovation isn’t about meeting a rigid definition — it’s about what organisations and industries prioritise and how they align their efforts with their goals. 

Moreover, this comprehensive view challenges the romanticised idea of innovation as purely chaotic or creative. It’s not about mad scientists or wild ideas emerging from disorder. The most innovative companies — whether in tech, manufacturing, or design — are often those that integrate creativity into a disciplined, systems-driven process. Innovators may not look like characters from a James Bond movie; they’re professionals working nine-to-five (or nine-to-eight) jobs, systematically advancing their organisations’ vision. While creativity plays a role, innovation thrives on structure, discipline, and a robust process. 

Behavioural sciences have traditionally been perceived as niche and emerging. Given your extensive experience, do you believe the time has finally come for behavioural science to take centre stage in business transformation? How do you see its role evolving in the near future? 

Behavioural science helps bridge the intent-action gap, offering tools to influence real-world decisions across health, finance, and consumer choices.

The answer is both yes and no. To borrow from Dickens, it’s the best of times and the worst of times for behavioural science. 

Why is it the best of times? Never before have organisations faced such immense challenges in adapting to change and driving innovation. The Covid-19 pandemic, geopolitical upheavals, and economic fluctuations have highlighted the need for fresh approaches to problem-solving. At the core of how the world operates is human behaviour. Everything — how nations behave, how industries behave, and how organisations and their leaders behave —has a behavioural component. 

During Covid, for instance, we saw a shift in leadership priorities. There was a renewed focus on what were traditionally labelled “soft skills” like empathy. Women leaders were often praised for outperforming their male counterparts due to their empathetic leadership styles. Although I personally disagree with the terminology of “soft versus hard leadership,” this trend underlined the growing recognition of behavioural factors in decision-making. 

In marketing, we see that traditional strategies that worked for decades are now falling short. Television commercials remain important for building awareness, but they’re no longer enough. Today’s consumers are bombarded with stimuli — short-form videos, social media reels, and endless streams of information. Decision-making has become increasingly complex due to limited time, overwhelming choices, and fragmented attention spans. Behavioural science provides critical insights into how consumers make decisions in this new environment. For instance, the classical economic model assumes rationality, yet we see behaviours that defy these assumptions. A consumer might meticulously compare telecom plans for hours, saving a few rupees, but walk into an Apple store and spend `30,000 impulsively on accessories. Behavioural science helps unpack these seemingly contradictory decisions. 

Then again, we see an intent-action gap. Whether it’s an organisation’s behaviour, a citizen’s behaviour, or a consumer’s behaviour, we are grappling for answers. What worked in the past —the proverbial carrots and sticks — no longer seems effective. This gap is a cornerstone of behavioural sciences, which focus on alternate ways of researching, influencing, and designing behaviour. This is also the foundation of the work by thinkers like Daniel Kahneman, who have explored the complexities of human decision-making and provided us with tools to address these challenges. 

At the societal level, this gap is evident in areas like financial and health behaviours. Despite the rise of fintech and health-tech influencers, are people becoming healthier? Not really. Are they making smarter financial decisions? Again, not as much as expected. For example, Indian consumers often avoid insurance and have poor savings habits, despite the availability of information. Behavioural science aims to bridge this gap between intent and action by understanding people and designing interventions that resonate with real-world behaviour. 

However, while the potential is immense, the challenges are significant. First, there’s no established “behavioural science industry.” Clients are often too preoccupied with solving immediate problems to explore new approaches. Bringing the science to them is the first hurdle. 

Second, there is a lack of India-specific case studies and proof of concepts (POCs). While behavioural science may have proven successful in Western contexts, clients often question its applicability in their unique environments. Creating relevant POCs requires investment in time and resources. 

Third, behavioural science is experimental by nature, and the term “experiment” can scare clients. People — including leaders and decision-makers — are inherently risk-averse and tend to default to traditional methods, even when those methods are less effective. Convincing them to adopt behavioural science and embrace experimentation is a significant challenge. 

Finally, it is difficult to find academics willing to engage in applied research. Behavioural science often straddles the line between academia and practice, and many academics prefer theoretical work over the messy realities of real-world implementation. 

To sum up, while behavioural science is gaining recognition and relevance, there’s still a long road ahead. It’s not just about understanding human behaviour but also about bridging the gap between theory and practice. With the right investments in proof of concepts and collaborative efforts between academia and industry, behavioural science can truly transform how we approach business, policy, and society. 

BIAS operates as a ‘Do-Tank’ rather than a traditional consulting firm. Could you share the inspiration behind this approach? What strategic vision drives BIAS, and how do you see this model transforming the consulting landscape? 

Clients kept asking: we have data, insights, frameworks — now what? BIAS was born to close that gap between knowledge and action.

Honestly, there wasn’t a single moment of inspiration behind creating a Do-Tank — it was driven by necessity. It emerged from the frustrations of clients and colleagues across industries who felt they were unable to move the needle on critical challenges despite having access to excellent tools, data, and frameworks. 

Take, for example, personal behaviours. Even with perfect health apps and advanced technology, not everyone exercises regularly, monitors their calorie intake, or follows through on actions they know are good for them. Not everyone buys insurance, drives safely, or makes decisions in their best interest. This gap — between what is known and what is done — sparked the question: What can be done differently? 

India has a robust market research and analytics ecosystem, complete with advanced AI, machine learning tools, and strong insights-generation capabilities. But many CXOs I spoke with — nearly 50 to 100 during the early days of BIAS — expressed the same frustration: We have the data and the insights. Now what? That was the genesis of the Do-Tank: bridging the gap between insights and action. 

A Do-Tank operates differently from traditional models. Most consulting firms approach problems from either a rational, analytical perspective or a purely creative one. For example, you’ll see solutions grounded in SBCC (social and behaviour change communication) or UI/UX design, which simplify consumer journeys, or in pricing strategies rooted in economics and finance. However, these approaches often miss the opportunity to combine science-based creativity with behavioural problem-solving. 

This is where behavioural science principles come in. Take pricing as an example. Traditional approaches to pricing focus on rational analysis — cost, margins, and market conditions. Behavioural science, however, examines how price communication and psychology influence decision-making. Concepts like decoy pricing and anchoring become critical tools for reframing price perceptions. For instance, after a certain point, consumers become desensitised to the word “free” or to seeing slashed prices. Behavioural science introduces nuanced approaches to overcome these cognitive blind spots. 

Another example is app design. Many apps are designed with functionality in mind, but often fail to consider real-world user behaviour. Some users may struggle with inclusivity, accessibility, or usability challenges. Behavioural science, combined with design thinking, helps address these obstacles by focusing on how users actually interact with the app, not just how designers intend them to. 

Behavioural science also brings unique value to advertising and communication. For instance, Rory Sutherland, Vice Chairman of Ogilvy, realised that in today’s world of overwhelming messaging clutter, traditional advertising approaches needed an overhaul. That realisation led to initiatives like Ogilvy’s Behavioural Science Practice, which leverages behavioural insights to create impactful communication strategies. 

BIAS builds on these ideas, applying behavioural science across domains to solve real-world challenges. By merging rigorous scientific methods with creative problem-solving, we address issues from pricing and design to communication and decision-making. The Do-Tank model ensures that insights are actionable and outcomes measurable, transforming not just how problems are approached but also how they are solved. 

In summary, the strategic vision behind BIAS is simple but powerful: combine behavioural science, creativity, and data to bridge the gap between knowledge and action. By doing so, we aim to reshape consulting for a world that demands both innovative thinking and practical solutions. 

Behavioural science is often associated with marketing, but its applications go far beyond that. What are some other ways behavioural science can promote business transformation? 

HR is one key area where behavioural science can have a significant impact. Let me start by drawing a parallel to marketing. Just as behavioural science helps marketers understand and influence consumer behaviour, it can also help HR teams address biases and create more equitable workplaces. 

In today’s diverse world, we often talk about inclusion and equity, but the reality is that humans are not immune to implicit biases. These biases stem from our evolutionary traits. In fact, biases have historically been survival mechanisms — helping us decide whether to fight, flee, or, in certain cases, find a mate. For example, if you see a six-foot-tall individual with an eye patch and a knife in a dark alley, your instinct is to run, not to consider whether they might just be misunderstood or differently abled. This immediate response is rooted in our primal instincts. 

However, while these biases served a purpose historically, they manifest in modern workplaces in ways that can perpetuate inequality. Let’s take diversity in organisations as an example. What are the kinds of diversity you would expect in a truly inclusive organisation? 

Diversity isn’t just gender or ethnicity. True inclusion examines privilege — geography, stability, disability, and socio-economic background must also be considered.

Gender representation is one obvious area, ensuring women have a strong presence in leadership and decision-making roles. 

Age diversity is another, breaking down hierarchies and encouraging inclusivity across generations. 

Religious and ethnic representation is equally critical to creating a workplace that reflects broader societal diversity. 

These are the more obvious categories, but behavioural scientists encourage organisations to look beyond them. For instance: 

Geographic diversity: Consider individuals from Tier 1 cities versus Tier 2 towns or villages. Someone from a rural background may face different challenges than someone from a metropolitan upbringing. 

Stability privilege: Employees who grew up in geopolitically stable regions have an inherent advantage compared to those from conflict zones. Organisations need to create opportunities for people from less privileged backgrounds to thrive. 

Disability representation: This includes both visible and invisible disabilities, ensuring an inclusive environment for all levels of ability. 

Socioeconomic diversity: Someone from a wealthy family has access to resources and opportunities that others may not. 

Criminal rehabilitation: There’s even scope to consider individuals with criminal backgrounds and offer them pathways to reintegrate into society. 

A concept I recommend exploring is the “wheel of privileges.” This framework helps identify different layers of privilege that often go unnoticed in organisational diversity strategies, from skin colour to access to education, geographic stability, and more. 

Behavioural scientists can work closely with HR teams to go beyond these surface-level biases and design systems that promote true equity and inclusion. Using insights from people science, HR can create not only diverse workplaces but also equitable environments where everyone has a fair chance to succeed. This approach transforms HR from simply managing diversity to actively leveraging behavioural insights to build more inclusive and high-performing organisations. 

BIAS operates at the intersection of academia, private sector and policy makers. Academia-industry collaboration often faces significant challenges, particularly when it comes to applying theoretical frameworks to real-world scenarios. From your experience at BIAS, what are the major barriers to effective collaboration, and what roadmap do you envision to bridge this gap? 

There are three major challenges in academia-industry collaboration that I’ve observed: 

The accepted range of error: In industry, speed often trumps precision. Businesses are typically comfortable working with 80 per cent accuracy if it means they can act quickly and seize opportunities. Missing the bus on timing can cost them dearly. This mindset is captured in terms like minimum viable product (MVP) — a concept the industry frequently relies on to balance basic due diligence with rapid execution. 

Academia, on the other hand, prioritises rigour and strives for perfection. For academics, quality cannot be compromised, even if it means extended timelines. This difference in priorities —perfectionism versus pragmatism — creates a fundamental tension. The challenge lies in marrying these two mindsets, finding a middle ground where timelines are reasonable, and quality is acceptable to both sides. 

Limited applied research expertise in academia: Another significant challenge, especially in the Indian context, is that academics often have deep theoretical knowledge but lack experience with applied research. In social sciences, such as behavioural science and marketing, the gap between theory and practice has widened considerably over time. 

For example, in your marketing classes, you’ve likely studied consumer psychology, societal changes, and social norms. But how often do we see marketing teams in the industry staffed with specialists like PhDs in sociology or consumer psychology? Rarely, if ever. In finance, sales, or marketing teams, professionals with academic backgrounds in these specialised fields are conspicuously absent. 

At BIAS, we’re trying to change this. We aim to serve as an interface that connects knowledge producers (academia) with knowledge users (industry). By fostering a continuous dialogue between these two worlds, we can ensure that academia focuses on applied research that directly addresses the needs of the industry, economy, and society. This feedback loop is critical: the industry provides real-world insights to academia, helping researchers understand what to study and how it can be practically applied. 

Bridging specialists and generalists: Academia often represents specialists, while the industry is typically made up of generalists. Both perspectives are valuable, but the lack of collaboration means these groups often operate in silos. Students, in particular, can benefit immensely from exposure to both worlds. By creating partnerships that encourage interdisciplinary dialogue and collaboration, we can bridge this divide and help students become versatile professionals who can navigate the demands of both academia and industry. 

At BIAS, we see ourselves as catalysts for this collaboration, helping academia and industry work together seamlessly. By building these bridges, we hope to transform not just how problems are studied but also how they’re solved. 

You’re a master of all trades — you’ve got an MBA, a Master’s in Public Policy, a Master’s in Design Thinking, and now you’re now pursuing a PhD at IIT-Delhi as well. You seem to have bridged the gap between being both a specialist and a generalist. For aspiring consultants and future generations, what would you recommend? Should we focus on a more generalised strategy or adopt a specialised approach to build our skill sets? 

It’s really a matter of choice. I call it the choice between the “B” and the “P.” The “B” stands for business — like the “B” in Bombay (or Mumbai, as we now call it) — and represents those who want to take care of business problems, solving challenges at the C-suite level. The “P,” on the other hand, stands for PhD and represents expertise. If you’re drawn to deep domain knowledge and becoming a subject matter expert, you go for the “P.” 

Ideally, though, the best approach is what we often call the T-shaped model. You should have a broad understanding of business —spanning finance, HR, marketing, and more — while also possessing some depth in a particular domain. Think of it as having minimal viable knowledge of the industry or domain you work in, alongside the ability to connect the dots across disciplines. 

Going forward, I would suggest aspiring professionals aim to specialise in what I call a “dual-focus approach.” I know it sounds contradictory — specialising while embracing duality — but it’s critical. Here’s why: If you focus solely on depth, you risk being seen only as a domain expert, a subject matter specialist, or what I’d call a knowledge producer. While that’s valuable — especially for roles like research or academia — it limits your ability to traverse the broader aspects of business. 

Conversely, if you only focus on the broader business context, like many leaders from past generations who were highly qualified engineers, you may struggle to engage meaningfully with experts in today’s specialised and dynamic world. In a rapidly changing environment, leaders now need to understand much more than just the basics of finance or marketing. They need to grasp digital marketing, UI/UX design, people science, and technology trends, among other things. 

For example, Mark Zuckerberg recently highlighted that for tech-driven companies, it’s critical for the top leadership to have a deep understanding of technology. This principle applies across industries — leaders need to know their domain as well as the business context. 

So, my advice? Don’t choose between business and subject matter expertise. Instead, integrate both. The ability to combine these dimensions will define successful leaders in the future. And honestly, people are talented and resourceful enough to achieve this balance with the right mindset and effort.