Data Science: Predict and tailor the future
Welcome back to The Zista Podcast. Today, we’re shifting our focus to the influential world of data science, a field that’s reshaping how businesses anticipate and shape the future.
If you caught our recent episodes, you’ll remember Dhaval Thanki. With 18 solid years in tech, digital SAAS, and analytics, Dhaval has played a pivotal role in driving startups and helping them succeed. Dhaval is currently the Executive Vice President at Loginext, and we’re delighted that he is joining us again.
In this episode, we’ll dive deep into data science, understanding its essential role in today’s business landscape. Dhaval will guide us through its significance, how businesses are striking a balance between personalization and privacy, and why he believes ‘Data makes marketing disappear.’ We’ll also touch on the evolving skills needed for tomorrow’s data scientists.
This is an episode packed with valuable insights. Whether you’re new to data science or an industry insider looking to keep pace with its evolution, there’s something here for everyone.
Welcome back to The Zista Podcast. Today, we’re delving into the transformative realm of data science. Beyond just algorithms and models, data science has become a compass for businesses, guiding them in predicting and tailoring future strategies.
Listeners from our previous episodes will undoubtedly recall our esteemed guest, Dhaval Thanki. With a remarkable 18-year journey in tech, digital SAAS, and analytics, Dhaval has not only observed but actively shaped the transformation of many enterprises. Today, leading as the Executive Vice President at Loginext, he’s back to bestow upon us more of his valuable expertise.
In this episode, we’re set to explore the depths of data science, dissecting its profound impact on business decisions and trajectories. Guided by Dhaval, we’ll unravel why and how data science serves as the backbone for many successful ventures, and delve into the nuances of balancing personalization with privacy. Beyond just the mechanics, we’ll also tap into the philosophy of data, understanding why ‘Data makes marketing disappear’ and the evolving skill set essential for the future data scientists.
This episode promises more than just knowledge; it’s a guidepost for those who aspire to harness the full potential of data in their endeavors. For anyone eager to understand the vast expanse of data science, from its intricacies to its overarching impact, this episode promises a wealth of knowledge. Join us in this enlightening journey, where data meets the future.
The amount of data produced every 48 hours is far greater than the data produced from the dawn of civilization up to 2004, highlighting the massive influx of data generation in the digital age.
- Regardless of their domain, modern businesses function more like tech companies, embedding data and technology at their core. Examples like Tesla demonstrate the fusion of conventional industries with cutting-edge technology and data analytics.
- Ethical data usage is pivotal in the digital age. Companies like Apple prioritize customer privacy, emphasizing the need to strike a balance between personalization and maintaining user trust.
- As every professional becomes, in essence, a data professional, understanding and leveraging data becomes indispensable for success in any field.
- Beyond the technical realm, creativity and the ability to think outside the box determine the true differentiators in data science and analytics.
- The future of data-driven businesses lies in how adeptly they can harness data to enhance customer experiences. A symbiotic relationship is envisioned where businesses cater to customer needs using data, leading to mutual success.
Q1: What is the most rewarding aspect of working in the data science field?
A: Dhaval’s 18-year-long journey in the data and digital realm remains invigorating. He begins by drawing attention to the remarkable evolution of the data landscape. A notable perspective from Eric Schmidt, Ex-CEO of Google, illustrates the pace of this change: the amount of data humanity created from its inception up to 2004 is now being produced every 48 hours.
The initial phase of Dhaval’s career was rooted in a firm named ‘Directions’, a frontrunner in CRM and data-driven marketing. They were instrumental in launching some of the pioneering loyalty programs we see today. This experience laid the groundwork for Dhaval’s proficiency in data-driven decision-making, strategies, and marketing.
The years spanning 2008 to 2012 marked the digital revolution. Dhaval was strategically positioned at its forefront, witnessing the rise of digital marketing and technology milestones like iPhones, app stores, and the dominance of platforms such as Google, Facebook, and LinkedIn. As an entrepreneur running his digital marketing firm, Dhaval had a distinctive relationship with Google. Their agency was among the few to have a unique credit line with Google, signifying the tech giant’s commitment to promoting the digital advertising paradigm. During this time, a considerable chunk of marketing budgets was allocated to traditional channels, with digital representing a mere 5%-10%. The potential of digital, however, was undeniable. Dhaval recounts engaging discussions with CEOs about this shift. He advocated for increasing digital marketing budget allocation from its then 3%-4% to at least 10%-15% because of its superior cost-effectiveness. He recalls specific instances where brand endorsements, even those featuring celebrities, were shelved in favor of digital customer acquisition, primarily because digital acquisition costs were substantially lower than traditional mediums.
The subsequent phase (2014-2018) was dominated by the surge of Software as a Service (SaaS) and product-driven businesses. The assertion that “SaaS is eating the world” became evident, with monumental shifts like Microsoft’s transformation under Satya Nadella, emphasizing subscription and cloud services. Dhaval’s endeavors during this period involved introducing innovative products to the market and deepening his expertise in the SaaS domain.
Dhaval’s association with Cartesian Consulting marked his intensive foray into AI and data science. Here, he contributed significantly to leveraging cutting-edge AI, machine learning, and data science techniques, particularly through product approaches and SaaS offerings.
Currently, as a part of LogiNext, the world’s premier logistics automation platform, Dhaval synthesizes his vast experiences from all previous phases. He continues to harness his extensive knowledge in digital marketing, SaaS, AI, and data science to innovate and drive the logistics automation domain.
Reflecting on his career, Dhaval acknowledges the highs and lows, market disruptions, and invaluable learnings he’s garnered. His trajectory underscores a tale of adaptability, growth, and an unwavering passion for the ever-evolving data and digital landscape.
Q2: Will more businesses adopt data science and data analytics in the future?
A: According to Dhaval, the shift towards a data-centric business model is not just anticipated; it’s already underway. Every modern company, regardless of its traditional sector, essentially operates as a tech company. This transformation is evident when observing industries that once seemed distant from technology. Banks, for instance, heavily rely on data and tech to function. Elon Musk’s assertion that Tesla isn’t merely a car company but a tech entity further underscores this transition. The immense data collected by Tesla vehicles is funnelled back into their systems to enhance core features, making vehicles safer and more energy-efficient.
The evolution driven by data is double-edged. On one hand, data is an invaluable asset. It enriches customer experiences, as seen with smartphones. Features like “Hey Siri” or “Hey Google” are possible because these devices constantly process data, waiting for the user’s command. On the other hand, the abundance of data and its movement to the cloud has raised concerns. Misuse of data and data-driven crimes are growing issues in our digital age. With this great power comes an even greater responsibility. Companies in possession of vast customer data must ensure they wield it ethically and responsibly.
Leadership plays a pivotal role here. The direction in which a company steers its data utilization can shape societal outcomes. Tools and technologies, like data, are neutral by nature. Drawing a parallel, Dhaval likens it to a knife: it can be used constructively, for tasks like chopping vegetables, or destructively. The responsibility lies in the hands of the users, or in this case, businesses and their leadership.
Apple serves as an exemplary model. Despite their potential to amass enormous customer data, they selectively capture only what’s essential for their devices or AI functionalities, like Siri. Such choices, grounded in customer interests, may sometimes appear counterproductive in the short term. However, they can foster trust and loyalty in the long run, leading to sustained business growth. The key lies in striking a balance: keeping the customer at the heart of the data narrative instead of purely business interests.
In Dhaval’s view, the future landscape will be dominated by data-driven businesses. Their success will hinge on how adeptly they can harness data to enhance customer experiences. In this envisioned symbiotic relationship, businesses cater to customer needs using data, leading to satisfied customers who reciprocate with loyalty. Data, in this scenario, becomes the linchpin, driving mutual success for both businesses and their customers.
Q3: How can companies balance personalization and privacy?
A: Dhaval emphasizes the fundamental role of valuing customer privacy in today’s digital era. Companies need to strike a balance between offering personalized experiences and respecting user privacy, and according to him, it boils down to ethical decision-making.
Customer-centric Approach: Central to his argument is the notion of placing the customer at the heart of a company’s data policy. Companies should prioritize protecting customer interests, even if it means making tough decisions concerning data processes. For instance, most digital platforms and applications have extensive terms and conditions. While they’re vital, the majority of users skim past them. Dhaval suggests that organizations can make these terms transparent by breaking them down into concise bullet points. Highlighting what kind of data will be captured, its purpose, and providing an easy opt-out option, signals that a company is transparent and respects user autonomy.
Building Trust and Loyalty: Dhaval believes that the foundation of enduring brands isn’t just marketing strategies or promotional deals. Instead, it’s about garnering the trust, loyalty, and respect of customers. If businesses transparently communicate their intentions and data usage policies, they’re more likely to foster long-term loyalty. In return, customers recognize these efforts and can bring immeasurable value to a business.
Leading by Example: Apple serves as a prime example in the realm of data privacy. Their staunch commitment to user privacy sets them apart from many contemporaries. They’re transparent about their data policies, distinguishing between data stored on devices and that which is uploaded to the cloud. Further, they ensure users are aware of third-party apps accessing their data by prompting permissions explicitly. Such conscientious choices might sometimes come at a short-term cost, like reduced advertiser revenue, but they establish long-term trust.
Relevance over Intrusiveness: Lastly, Dhaval highlights the importance of contextual relevance in advertising. Using Google as an example, he points out that when users receive ads about products they’ve shown interest in, these ads transform from mere promotions to valuable content. Such tailored advertising offers both personalization and value without compromising privacy. By keeping the customer at the center of data-driven strategies, companies can make decisions that benefit both their business and their users in the long run.
In conclusion, navigating the nexus of personalization and privacy is undoubtedly challenging. However, with the right ethical framework and a customer-centric approach, businesses can succeed in this endeavor.
Q4: What skills and competencies do Data Science and Analytics students beed?
A: Dhaval offers a comprehensive viewpoint on the essential competencies required in the evolving field of data science and analytics.
Every professional is a Data Professional: In today’s digitized age, Dhaval posits that every professional, irrespective of their field, is essentially a data professional. Whether one is a creator, designer, or even an art director, every decision they make impacts data. From determining color choices based on user preferences to understanding user behavior in specific contexts, being data-literate is no longer a luxury but a necessity. It’s crucial for professionals to comprehend how data influences their work, enabling them to measure, quantify, and enhance their contributions effectively.
Data Literacy as the New Norm: While specific roles, like that of a database engineer or data scientist, may require deeper immersion in data, Dhaval insists that a foundational level of data literacy is indispensable for everyone. This foundational understanding aids professionals in leveraging data effectively, regardless of their domain, establishing it as a critical factor for success.
Beyond Traditional Skills – Creativity is Key: While coding and programming skills remain essential, they are now universally accessible thanks to open-source platforms and resources like GitHub. Consequently, mere technological proficiency doesn’t provide a competitive edge anymore. Dhaval emphasizes that the real differentiator is one’s ability to apply this knowledge innovatively and think outside the box. This links back to his assertion about the significance of being both left-brained (analytical) and right-brained (creative).
Breaking Conventional Molds: The power of thinking differently can lead to transformative results. To illustrate, if multiple data scientists were given the same problem, the variances in their models would be marginal. To truly innovate, professionals need to approach problems distinctively, emphasizing effectiveness over efficiency.
The Six Thinking Hats Approach: Drawing inspiration from Edward de Bono’s “Six Thinking Hats,” Dhaval emphasizes the importance of multifaceted thinking. By donning various ‘hats’ – analytical, creative, executional, among others – professionals can gain a holistic perspective on problems, paving the way for more impactful solutions.
Continuous Learning in a Democratic World: Finally, Dhaval advocates for the continuous pursuit of knowledge. With the vast reservoir of data and resources available today, every professional has a democratic opportunity to hone their skills, innovate, and excel in their respective domains.
In conclusion, while technical skills are fundamental, the future of data science and analytics lies in holistic, creative, and multifaceted approaches. As Dhaval articulates, it’s about constantly evolving and leveraging both data and creativity for groundbreaking solutions.
Q5: Can data make marketing disappear?
A: Dhaval dives deep into this intriguing concept by referencing the words of an iconic design visionary.
Jony Ive’s Profound Design Philosophy: Jony Ive, the Chief Design Officer at Apple and the creative mind behind the design language of revolutionary products like the iPhone, Mac, and Apple Watch, has often emphasized the fusion of design and user experience. Along with Steve Jobs, Ive once mentioned in a keynote that technology is at its zenith when it becomes invisible to the user. This means that a device should be so intuitively designed that the boundary between the user and the device vanishes, creating a seamless experience.
The Integration of Users and Technology: The essence of Ive’s statement centers on the concept that technology should be so refined and intuitive that users shouldn’t feel they’re interacting with a machine. Instead, there should be an effortless flow between them and the device, enhancing the overall experience.
From Technology to Marketing: Drawing parallels to marketing, Dhaval believes that just as technology should fade into the background, so should marketing. The aim is to design a product or service so attuned to customer needs that it essentially sells itself. This is where the evolved perspective of the ‘Four Ps of Marketing’ comes into play, emphasizing ‘product, product, product, product’. The product should be so well-designed and aligned with user needs that it negates the need for traditional marketing.
Data-Driven Marketing equals Seamless Experience: With the right data, one can understand and bridge the gap between customer requirements and what a product or service offers. When a user searches for a product on Google, for instance, and they’re shown an ad tailored to their interests, that advertisement becomes content rather than a disruption. This targeted approach, powered by data, ensures that marketing feels like a natural conversation rather than a hard sell.
Making Marketing Disappear: The ultimate goal, as Dhaval articulates, is to make marketing feel non-existent. By harnessing the power of data, brands can create products and campaigns that resonate so deeply with consumers that they don’t feel they’re being marketed to. Instead, they feel they’re engaging in a mutually beneficial dialogue with the brand.
The Seamless Fusion of Tech and Marketing: Just as technology should be a seamless extension of the user, marketing too should seamlessly bridge the product and the consumer. Achieving this requires immense effort to simplify complex processes, making them appear effortless. And, according to Dhaval, it’s data that enables brands to realize this vision, embodying the ethos that “data makes marketing disappear.”
In summary, for a truly immersive and user-centric experience, both technology and marketing must become invisible, working in harmony behind the scenes. And it’s through the intelligent application of data that this seamless integration can be achieved.