Council Post: Notes on the Nuances of Leadership
Once upon a time, my dream job was selling soap. And toothpaste. And oil. And a variety of other household goods which on their own seem trivial. But how one got good at it involved a journey through the towns and villages of India, visiting and sipping chai with owners of kirana stores, speaking to customers who straddled socio-economic strata, and learning the feet-on-the-street approach to racking up sales. Someone else ended up living that dream. And I sat in a plush office with a view of the ocean, cold calling John Deere dealers in Dorothy’s Kansas – some would be flummoxed to hear an accented voice from Mumbai (then Bombay); others, intrigued, would chat along and provide a wealth of information as did the farmers in Punjab and the auto accessory manufacturers in Madras. In the end, the trick to selling anything is understanding people. From an analyst working numbers, an analytics industry grew around me, and while we now strive for excellence in the science of data, the end goal is still to influence people. To buy, transact, fund, contribute, use, enable, take action. And internally, to align, problem-solve, model, story-tell, belong. With the volume and velocity of data generated, moving up the ladder makes it hard to live in the details. And the sophistication of tools and domain depth requires mastery of what we manage. A career choice that faces many of us – and we are lucky to have reached that level of maturity – is whether to be a broad leader or the uber SME. My journey, with personal circumstances and an inclination to experience variety – or avoid what seemed like boredom – took me across industries and functions. Hence, the former. It required me to understand the tractor market, sell fuel oil, develop pricing strategies for brick and mortar grocery stores, extend the UK built analytics models to Asian markets with their unique products and competitors, build a data dictionary of contact centre acronyms, figure out how to produce tech support YouTube videos in Portuguese, lay a foundation for social media command centres and soon after for performance management processes in a start-up, finally stepping gingerly into banking and finding my current niche spanning analytics, social impact, communications, campus recruitment and COVID-19 crisis management. With such a vast spectrum, perhaps the key pillars that my ‘leadership’ is founded on are keeping the customer in mind as one looks at data, keeping the people in mind as one leads teams, and adhering to and continually raising the bar for the quality of work one is associated with and wants to be known for. Some of the mantras I absorbed over the years: Begin with the customer. Read their actions and choices in the data. Personify them and imagine the individual, the families, the lifestyles. Agatha Christie taught us to look for a motive. Our profession doesn’t deal with grim mysteries, but the ‘why’ drives everything.Figure out answers to – What business are you in, how it makes money, and the part you play in it. When you start your career staring at code, correcting syntax and swimming in numbers, sometimes this does not seem important. But it is. Because when you present to the CEO and make the data talk, the CEO is wondering how to make the customer walk; into a store, an aisle, a branch, a purchase process.Feed your Strengths. Manage your Weaknesses. There are some of us who sit in a performance review and let the accolades slip by, waiting to hear what we did wrong or what we can improve. And then we work on the deficiencies often to hear the same the next time around.It is rare for a weakness to become a strength. Moving the needle from negative to zero will not make you a star. But honing your strengths and exploiting them just might. So, take in the praise and know that this is what you must bank on to succeed.Master your stuff but keep it simple. Being a data scientist demands a lot. You must be a poet and a quant, an artist and a geek. Loading up on certifications is not critical; knowing your models is. But most important is the ability to discern whether you need a hammer or a drill. Everything cannot be simplified, but what is the right level of complexity that a problem requires? Quoting Einstein, “Everything should be made as simple as possible, but no simpler.”Make people feel ‘awesome’. This was a Chris Arnold mantra. It is perhaps hard for others to emulate him, but the essence is to hear people, make them feel that they matter, that someone is enabling the paths they want to traverse. Presence, communication and the connection – all need to come together to make this possible.Be a mini-Ganesha – remove the obstacles. If you’re not the uber SME, the people who work for you often know more about what works or doesn’t and what they need in order to be more effective and supported. Get those smart people on your team and clear the weeds for them. If you can be charismatic and omniscient, more power to you. Not all have that luxury, though.Rethink the regret. Regret and resentment are not unnatural sentiments, and everyone has some incidents they can recall when these were triggered. Sometimes, the right amount of resentment can be very powerful – channelled into the right action; it could lead to phenomenal outcomes that may not have transpired had you stayed content in your largely comfortable zone. At times, people even resent another person leaving the organisation for other opportunities, not realising that one’s network and connections can be lifelong. Move on. And think of what you can do differently. Most of these don’t sound like tips for data scientists. Perhaps because as one takes on the mantle of leadership, the core principles are universal. I do believe, though, that exposure to business in ways that force you to think of people – customers, employees, teams – and what drives them is critical to leveraging the potential of data and bringing your strengths and leadership abilities to the forefront. This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill the form here.
Once upon a time, my dream job was selling soap. And toothpaste. And oil. And a variety of other household goods which on their own seem trivial. But how one got good at it involved a journey through the towns and villages of India, visiting and sipping chai with owners of kirana stores, speaking to […]
Exposure to business in ways that force you to think of people and what drives them is critical to leveraging the potential of data. 
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["AI", "data science", "analytics", "Aim", "RAG", "R", "Go", "GAN", "ViT", "programming_languages:R"]
Nidhi Pratapneni is a Senior Vice President at Wells Fargo India &amp; Philippines. She is Head of Public Affairs and leads the Product, Analytics &amp; Modeling (PAM) horizontal. Nidhi joined Wells Fargo in 2017 as COO of Knowledge Services to further diversify and grow the analytics capabilities in India and the Philippines. Before this, she worked as a consultant with McKinsey &amp; Co. in India, moving on to roles in Chemoil, Personify, and Safeway in California.