Overcoming analysis paralysis: Nimbus co-founder Nish Ithayakumar on driving impact with data

Listen to the full conversation with Nish on the Grow With It podcast:

Most companies are not lacking in data. In fact, they’re overflowing with it. The problem comes when they need to put that data to work.

“The companies I've worked at and the companies I've helped, they all actually have more data than they realize and they all really struggle with operationalizing that data,” says Nish Ithayakumar is the Co-founder of Nimbus.

“And I believe they struggle because there are really two functions when it comes to data. One is the consistent transporting and the creation of data sets. So think of that as the data teams. They create these pipelines and they take data from one place to another, whether it's centralized or separated. That's not what we're talking about when we're operationalizing data. What we're talking about is using that data for decision making or initiatives.” 

Building trust in the data is, according to Ithayakumar, an challenge that is overlooked by many people in positions like his. “If I told you we had a thousand monthly active users last month, [you might ask] what is active? What is a user? And when using that data, there's a genuine lack of trust in data and, and people have been burned by it. So they ask a lot of questions, which slow things down and cause a lot of analysis paralysis.”

“So one of the really important things that companies can do is set the right framework, structure and accountability. Put that in place so that people can use the data and operationalize it and drive impact.” 

The answer is surprisingly simple. To build trust and put data to work, companies need to put a data quarterback in place. Someone who has ownership and accountability, and is tasked with not just building dashboards or finding the right data, but identifying how that data will be used and how it will drive a KPI or specific objective. Once this is in motion, other individuals and departments will start to see the value of the data and their trust will be restored. 

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Building a database of Unity’s TAM

As a keen gamer himself, when Ithakaymur joined Unity, he was excited to dig into the data to see every game that’s ever been made and who made it. He soon realized, that data didn’t exist.   

“The problem is that this data is often external and it's like incredibly messy. And so one of the things that I was responsible for at Unity is building out this games database.”

With this database, Unity were hoping to learn what games are on the market, the engines they were built on, what tech stacks they were using, and what platforms they were on. 

The goal of this database was, ultimately, growth. It was a project that was tied to revenue and Ithayakumar had the job of building the database, getting stakeholders to trust it, and getting sales teams excited about it. 

“There's all these companies that are putting together information on what games are out there. And they all collect the information differently. Some are middleware between game launchers. Some are community sourced. What it comes down to at first is collecting this information and, and rationalizing what is going to be the highest quality set of information.

Now, next to that, there are game like platforms or game retailers, and they're selling games and they have to maintain information on what the price of a game is when it was launched and who the developer is. And then internally at Unity, we also had our own information based on who we're selling to... The challenge was we had to get all of that together.” 

This is the point where many people in a similar position may hit a roadblock due to lack of resources, and where the important role of building excitement came in. 

“We talked to all the different stakeholders that would benefit from this. We got excitement and tried to understand what they really wanted. Then we mapped out and created this like mock data set of like what could really add value. And then I went around and I got excitement and I got support for it. Having got support, we could get the resources needed to be able to fill in the gaps.”

With the gaps filled and a realistic view of the games landscape in an accurate database, Ithayakumar had essentially built an accurate total addressable marketplace. What’s more, he was able to give the sales team a database of companies that don’t use Unity, and when their last game was released. With this information, the SDRs could make accurate guesses of when these companies would be starting their next game and could get ahead of their competitors with proactive outreach. 

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Bringing big data lessons to a startup

Today, Ithayakumar is one of the founders of a company called Nimbus, which lets developers code on the cloud so they can access their environment from any device, and never have to worry about batteries draining or environments breaking. 

Through his experiences at Unity and elsewhere, Ithayakumar has learned that building the best product means getting out and talking to people. So the company has been focused on interviewing people from a product perspective, and using third-party tools like Amplemarket to pick out keywords on LinkedIn to find people who care about what they’re building. 

This data, combined with product data that shows what people are actually doing with the product, is helping Nimbus to build the a product that is a perfect market fit. 

How to start building a database of potential customers

“Find the most data apt person in your team, find the most hungry pirate type person in your team, put them together and just let them run wild,” Ithayakumar says.

“Let them run wild and come back to you with their wildest ideas that everyone's going to say no to. And then unblock them, let them go build that. And I think you'll see a ton of great results in doing that.” 

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