CXO of the week: Shashank Dubey, Co-Founder and Chief Revenue Officer, Tredence

Tredence is a data science and AI engineering company focused on solving the last mile problem in analytics. The ‘last mile’ is defined as the gap between insight creation and value realization. Tredence is more than 1,500 employees strong with offices in Foster City, Chicago, Toronto, and Bangalore, with the largest companies in retail, CPG, hi-tech, telecom, travel, and industrials as clients.

Shashank (Co-Founder and Chief Revenue Officer, Tredence) brings more than 13 years of research and consulting experience in applied mathematics and analytics. He has provided analytics consulting across multiple industries – retail, telecom, technology, online marketplace, airline, and healthcare.

Shashank leverages a unique mix of business consulting and advanced analytics experience to provide actionable insights to Fortune 500 businesses. Prior to co-founding Tredence, he held senior executive positions in a leading data analytics company. He holds an MBA from the Indian School of Business and a Bachelor in Engineering from IIT Madras, India.

In a recent chat with Shashank Dubey, Co-Founder, and Chief Revenue Officer, Tredence, he talks about his startup journey and what Tredence has been up to in the latest edition of CxO of the Week.

Can you describe Tredence's business framework and core offerings?

Tredence is on the cusp of a phenomenal change as a brand. As we re-discover our brand identity, we will double down on our DNA - as enablers of last-mile adoption of data science - which remains as relevant and distinctive as ever. We define the last mile as translating insights into outcomes that drive business impact. Despite the words “last mile,” it’s a culmination of all the efforts along the way to win at the last mile.

Our DNA anchors us and challenges our ecosystem to go beyond the possible to bring real value to our customers. We help businesses succeed in the age of data hegemony by developing industry-specific data science solutions. With a highly driven group of 1,700 data scientists, we tackle complex business challenges, enhance the value of analytics, and drive faster value realization.

We've pivoted from being an analytics services organization to a data science solutions organization that reflects the company's new go-to-market strategy with a renewed focus on providing vertical-specific solutions and innovation. The approach seamlessly aligns with our customer-centric culture and purpose to empower decisions that help our clients win.

Turnarounds require a culture of experimentation where employees can ideate, prototype, and co-create solutions with clients and partners. By placing innovation and curiosity at the heart of our business, we have institutionalized this culture and experience at Tredence.

What is Tredence's current growth rate, and what are your predictions for the next 5 years?

It's not the big that eats the small...it's the fast that eats the slow. Speed is the name of the game in the tech business. Our strategic intent of driving growth and agility for clients comes from 3 levers:

• Speed to action through accelerators

• Speed to value through industry and functional expertise

• Speed to scale through deep data and AI partnerships

Traditionally, Tredence’s business was spread across analytics services. However, our focus has shifted to AI products and data science solutions in the last 2-3 years. With a CAGR of 50% since inception, we are one of the fastest-growing companies in the booming data science industry. We have grown by 65% in FY 2022 and expect a 90-100% growth in FY 2023. Our target is to become a $1 billion valuation company by 2024.

How do you see the future of the data science industry? What developments can be expected in the future?

The data science industry has evolved into a huge ecosystem. It includes traditional system integrators, boutique analytics companies, captives, consulting firms, hyperscalers, and AI and data product companies. Fortune Business Insights predicts the global big data analytics market will reach USD $549.73 billion by 2028.

In the next 10 years, data science along with socioeconomic and behavioral economics is going to reinvent and disrupt every industry on this planet. The shift will focus on building business endurance, scale, and faster value realization. Global supply chain, pricing, change management, value-based services, trade operations, and customer experience management are some of the core functions that will significantly benefit from the shift.

Enterprises that thrive amid rapid transformation will accelerate along exponential growth curves, reorient relationships, disrupt value chains, and displace traditional practices.  The shift will multi-fold human-AI collaboration by automating the established and humanizing the exceptional.

The future of data science seems immensely positive and impactful, with more companies seeking to adopt data-driven decision-making. Developments in AI and machine learning will allow data scientists to automate more tasks and make more accurate predictions. In addition, the increasing popularity of open-source tools and platforms will make it easier for companies to get started with data science. I strongly feel the industry will continue to grow rapidly in both size and scope.

Can you give some examples of the results and impact that Tredence has been able to achieve for customers?

Tredence is not in the business of populating BI dashboards, rather we equip businesses with endurance and intelligence across the value chain with our domain and functional expertise.

Retail, for instance, relies heavily on data. To make informed decisions about product assortments, pricing, and promotions, retailers turn to data. Most retailers are feasting on data. But they're starved for insights.  Retailers struggle to drive customer engagement due to a lack of contextual intelligence and real-time access to customer insights across omnichannel touchpoints. Tredence built Cosmos, a customer 360 platform, to get a deep understanding of customers across first- and third-party sources to drive effective personalization strategies in real-time. The approach helped a large retailer achieve a six-fold increase in supplier data monetization and 10 point improvement in NPS.

In the same way, our AI solution helps CPG companies run effective trade promotion campaigns. Our care management data platform, HealthEM.AI, enables healthcare companies to deliver value-based care and reduce hospital costs by 30%.

Realizing value from data is a marathon, not a sprint. We act as a catalyst in navigating each client’s journey from insights to value realization for real and tangible business impact.

Did the current pandemic affect your work? If yes, please share a few insights that how did you tackle those challenges?

During his work to form the United Nations after WWII, Winston Churchill famously said, “Never let a good crisis go to waste.” This notion has stayed with me. ATOM.AI, our co-innovation platform, was built during the early COVID crisis in 2020. We have several Fortune 500 customers who are jointly building domain-specific AI and data science solutions through the Atom.AI platform. Today it has evolved into a vertical accelerator pack for enterprises.

Undoubtedly, COVID-19 created havoc across the globe. Global economies, businesses, and people came to a screeching halt. Nevertheless, the demand for AI and data science has grown multi-fold in the last 3 years. However, most enterprises struggle to embed data science into business processes. It's even more complicated and ambiguous to integrate intelligence across several functions for a 360 view of their data investments. In the right hands, data science and domain science can have a powerful convergent effect, and that is what we excel at. The approach has helped us escape competition through authenticity

What is your biggest piece of advice for individuals considering a career in data science?

It takes more than technical expertise to scale up a career in the data science industry. Enterprises will expect a deep generalist mindset with the right mix of domain experience, business consulting skills, and data science skills. Let's look at our CPG vertical; only those who understand the domain, the business challenges, and the different models can develop strategies that help clients expand and grow their trade promotions. The same applies to retail, manufacturing, and health care.

Across industries, Exploration (developing an inventive mentality and seeking out new ideas) and Exploitation (scaling that idea mindset) is essential for individuals and teams to growth.

Exploration is a long-term strategy that involves risk, uncertainty, the prospect of failure, and a lengthier payback period. On the other side, Exploitation is less risky and more predictable. The key to success is balancing Exploration and Exploitation, leading organizations to greater insights and success.