Data Alone Rarely Creates Impact

How did your academic background in economics and marketing shape your approach to business problem-solving?

Economics helped me understand concepts such as scale, resource allocation and value creation. It taught me that every problem has an economic dimension, and that solutions must justify the investment required to implement them.

Marketing, on the other hand, gave me a deeper understanding of customer segmentation, positioning, target audiences and value propositions. Together, these two disciplines have enabled me to approach business challenges holistically, by asking critical questions: What problem is being solved? Who is the customer? Is the solution scalable? Can it be monetised? And, most importantly, can it be implemented effectively?

This combination of economic thinking and customer-centricity has remained central to my consulting philosophy throughout my career.

You have worked across FMCG, media, analytics and technology consulting. How has this journey influenced your professional outlook?

While many view these as different industries, I see them through a common lens: the customer.

Whether I have been working in FMCG, media, insurance, analytics or technology, the underlying objective has remained the same — understanding customer needs and helping organisations solve problems more effectively. Each industry may involve different products, business models and technologies, but the core challenge stays constant: building relationships, understanding customer behaviour and delivering value.

This customer-first mindset has enabled me to transition successfully across industries, while continuously expanding my understanding of business and problem-solving.

How has data transformed consulting over the years, especially in the age of AI?

Data has become the foundation of modern consulting.

As organisations have evolved, data volumes have increased dramatically and become significantly more granular. What began as transactional and customer-level information has expanded into complex datasets capable of generating deeper behavioural insights and business intelligence.

Today, AI acts as a catalyst that helps organisations derive value from data more efficiently. However, AI is only as effective as the data powering it. Without high-quality, reliable data, organisations cannot generate meaningful insights or effective solutions.

As I often say, a principle from the early days of analytics remains highly relevant today: “garbage in, garbage out.” Strong data quality remains essential, regardless of how advanced the technology becomes.

What role does consulting play in an increasingly AI-driven business environment?

Consulting has always been about helping people solve problems.

While technologies, industries and business contexts have evolved, the essence of consulting remains unchanged. Whether I have been advising distributors in FMCG, helping media organisations optimise advertising investments, or supporting enterprises with AI-powered solutions today, consulting revolves around understanding business challenges and designing practical, scalable solutions.

What has changed is the scale and complexity of the problems being addressed. Today’s consultants are expected to combine domain expertise, business understanding, data analytics and technology capabilities to drive measurable outcomes for organisations.

Why is storytelling becoming increasingly important in analytics and consulting?

Data alone rarely creates impact. Organisations do not make decisions based on numbers alone; they act when those numbers are translated into a compelling narrative that explains what is happening, why it matters and what actions should follow.

Effective storytelling requires structure. It begins with context and objectives, moves through analysis and findings, and ultimately leads to insights and recommendations. Only when data is organised into a coherent story can it influence decision-making and drive action.

For consultants and analysts, the ability to transform complex datasets into clear and compelling narratives is increasingly becoming a critical leadership skill.

How do you approach leading diverse and cross-cultural teams?

Successful leadership begins with understanding people, rather than focusing on cultural differences.

Regardless of geography, most professionals share common aspirations: growth, learning, exposure, meaningful work and career advancement. By focusing on these shared motivations, leaders can build stronger connections and foster collaboration across diverse teams.

I also place great importance on helping team members understand the purpose behind their work. When individuals know why a task matters and how it contributes to broader goals, engagement and ownership naturally increase.

Combining empathy, communication, technical development and interpersonal growth creates an environment in which individuals and teams can perform at their best.

What is your approach to building high-performing teams and developing future leaders?

For me, leadership starts with recognising individual strengths.

Rather than expecting everyone to excel at everything, I believe effective leaders identify what each person does best and create opportunities that allow them to maximise those strengths. I compare this approach to building a well-balanced machine, in which every component plays a specific role in driving overall performance.

I also stress the importance of treating teams as collaborative units, rather than hierarchical structures. While responsibilities may differ, every team member contributes towards a shared objective.

A principle I often share is that leaders should never “ask a fish to climb a tree.” Understanding individual strengths and aligning responsibilities accordingly is essential for developing both performance and future leadership potential.

What advice would you give to aspiring leaders and consultants?

My advice is simple but powerful: lead by example.

I believe that credibility is built through action rather than words. Leaders who actively participate in solving problems, demonstrate commitment and remain willing to engage directly with challenges, inspire greater trust and followership from their teams.

My message to aspiring professionals is clear: never hesitate to get your hands dirty. The willingness to learn, contribute and solve problems firsthand remains one of the most valuable qualities any leader can possess. 

 

Data alone rarely creates impact. Organisations act when numbers are translated into compelling narratives that explain what matters and what actions should follow

 

AI is only as effective as the data powering it. Even today, the old principle remains true: garbage in, garbage out