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M.R. Asks 3 Questions: Shub Bhowmick, Co-founder & CEO, Tredence Inc.

By February 16, 2023Article

With over two decades of experience advising on tech strategy, M&A integration and operations improvement, Shub Bhowmick’s career has thrived with building and running high impact projects in a wide range of industries.

According to Forbes, Shub’s expertise favours his ability to breakdown complex problems, identify risks, assess business value and then provide recommendations on remediation/value attainment. All of which stemmed from his MBA at Northwestern University’s Kellogg School of Management, and a Bachelor of Technology with honors in Chemical Engineering from IIT-BHU in India.

M.R.Rangaswami: Everyone’s betting on analytics and AI, how should a company evaluate an AI vendor?

Shub Bhowmick: At a recent event, Reid Hoffman said, “You are sacrificing the future if you opt-out of AI completely.” The AI and data science industry continues to evolve at light speed, and this year will be no different. However, enterprises are adjusting their expectations as cost reduction and shareholder value realization are fast becoming a central theme.

In light of the increasing importance of AI in business today, companies worldwide are justifiably spending more time and effort evaluating AI consultants. Data science solutions are more valued than ever before because they help companies differentiate themselves from the competition and spark organic growth.

Identifying the right AI partner or solution can be challenging since everyone claims to be able to solve every problem, every time. First, it is important to know what problems your business is trying to solve; don’t go into this evaluation blindly—ensure that you have a clear list of what you need and what business goals you’re aiming to accomplish. Then, you need to take a closer look at your options: What problems are the various AI vendors solving (and how effective is their work)? What industries do they have experience with? Are they growing and innovating or standing still? Do they have a regional or global presence? Can they support a broad range of users?

Ultimately, doing things at the edge is what the future is about. A combinatorial focus on innovation, customer-centricity, business value realization and custom solutions will help you find the best AI vendor for your organization.

M.R.: What are the most effective ways for companies to use AI and ML to reduce costs and maximize profitability?

Shub: AI and machine learning technology have quickly become integral parts of digital transformation strategies for businesses, as these solutions are essential for improved efficiency, cost-cutting and maximizing profits. AI has the potential to integrate everything within an enterprise from customer insights to hyper-personalization, order generation, warehouse inventory optimization, the right routing optimization, delivery, products shown on the catalog, POS data and finally to pricing. To illustrate their immense capability and potential further, let’s look at some real-world use cases. 

For instance, a customer intelligence platform like COSMOS helps retailers get 360-degree visibility into the customer, both when they are with you and with the competition. The platform delivers real-time access to customer insights with seamlessly integrated first- and third-party data to run multiple experiments and perform holistic measurements.

Similarly, the role of AI in CPG and manufacturing is significant, where a solution like supply chain control tower future-proofs supply chain with prescriptive insights and helps companies handle future disruptions and opportunities, with centralized control. 

When used in collaboration, AI and ML can predict what products and services will be in greater demand so that businesses can maximize sales and growth opportunities while engaging fewer resources. AI and ML are designed to help companies decrease costs while growing profitability. This is just one of the many reasons more businesses are turning to the latest data science solutions.

M.R.: What is the last-mile problem in AI and how can it be solved?

Shub: The last-mile problem in AI is the critical gap between insight creation and value realization—it has long been one of the most challenging issues for organizations across various industries and continues to test companies today. While generating insights is certainly worthwhile, if you can’t use them to change behavior or move the dial, then that gap is both costly and unproductive for companies. 

Tredence ensures insights are actionable and impactful so our clients can grow revenue, remove barriers to innovation and uncover new opportunities to create meaningful and sustainable value. Working with several Fortune 100 CDOs, we help enterprises understand the economic value of data and the importance of leading a data-driven organization. With all that in mind, our goal is to be on every CDO’s speed dial in the next 2-3 years. We excel at solving the last-mile problem and helping organizations create true value; with Tredence, you can solve vertical and horizontal issues.

M.R. Rangaswami is the Co-Founder of

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