CEO Sit Down: MetaLogic Consulting with Rayan Goyal

A company providing creative machine learning and data science solutions for the world.

There is no question that machine learning and artificial intelligence have become a crucial component in business today. As companies collect more and more data, these tools have been deployed to help businesses derive meaningful insights and support business decisions. Having worked in the manufacturing sector, Rayan and Aditya quickly realized the need for sophisticated analytics in this industry and, after graduating from Babson College this past May, Rayan and Aditya started their own data science driven consulting firm MetaLogic Consulting. MetaLogic Consulting provides tailor-made, data driven solutions to manufacturing companies across the American Midwest and beyond. I had the privilege to sit down with one of the CEOs Rayan Goyal to learn more about how their company is making a serious impact driven by data.

Rayan, tell us about yourself!

Hey! I’m Rayan, and I am from Chennai, India. Growing up, I always had a passion for numbers and mathematics, which eventually led me to concentrate in Computational Finance and Data Analytics at Babson College. I also grew up in a very business-oriented environment, and so I have always wanted to start my own company. As soon as I graduated from Babson, my roommate Aditya Kaushika and I co-founded MetaLogic Consulting, which is a company that provides machine learning and data science solutions for primarily American manufacturing firms.

What was the inspiration behind starting your consulting practice MetaLogic Consulting and what differentiates your company from other consulting firms?

After working for multiple manufacturing companies in the Midwest and in India, Aditya and I realized that there was a lack of sophisticated analytics being implemented in large corporations that you would expect to have top-level analytics. We realized that most data scientists tend to flock to the east or west coast, leaving this huge untapped market in the Midwest. So, we came up with the idea of creating a machine learning and data science consulting company that specifically targets manufacturing companies in the Midwest.

To your second question, there are multiple factors that differentiate us from other consulting companies. As I mentioned before, we are targeting an industry and a market that tends to be ignored by large consulting firms. Also, we have an entire dedicated team that works on each project that we are hired for, which is very different from the “one consultant” approach that is standard in the industry. Furthermore, we not only provide end-to-end solutions, but we also tailor-make our services to unique customer requirements.

What is the mission and ethos of your company?

Broadly speaking, our mission is to help companies derive the most out of their data. You’d be surprised to know how many companies there are out there that collect a ton of data but don’t really do much with it. Our goal is to help them use this data in meaningful ways to grow, expand profits, and realize returns.

What is the greatest challenge that you have experienced in starting your new business?

I think that the biggest challenge that we encountered was that we had to repurpose our fundamental data science and machine learning knowledge to fit the different tools used by different companies. To be more specific, we had to re-learn, in a way, how to do what we do using the different softwares and environments that are used by various companies.

What makes machine learning and artificial intelligence so critical to business in today’s world?

At MetaLogic, we have always said that machine learning and artificial intelligence are no longer luxuries but are necessary to stay competitive in today’s business world. Let me give you a very simplified example to explain what I mean. Assume that you are a widget manufacturer that has only one machine. After using the machine for a year straight, it breaks down for two weeks. During these two weeks, you have an increase in costs (repairs and maintenance), a decrease in revenue (no inventory to sell), and a newly-developed perception of being unreliable.

To prevent all these things from happening, your company could have used a machine learning algorithm that tracks your machine usage data and tells you when you need to repair it or how to use it optimally to prevent breakdowns. Now, this is a very simplified example, but the point is that as businesses and processes get more complex, there are countless opportunities for machine learning and data science to help improve efficiencies. This is especially true if companies want to stay ahead of the curve and be competitive.

What is one thing that you wish more people knew about data science?

I think that there is a preconceived notion that data science, and machine learning specifically, is a field that is very complicated and overwhelming. A lot of executives only think of autonomous cars or highly sophisticated concepts when they think of machine learning, which, in turn, makes them feel like it is not applicable to their business. But, in reality, data science can be applied to the simplest of tasks at almost every single company in the world that collects data.

What about the future excites you?

I believe that the future is very exciting for data science as a whole. More companies are understanding the value in implementing machine learning and data science within their firms. This not only means a larger market for us but also leads to more deliberate and interesting decisions taken by companies across the board.