How a “People First” Culture Drives Tech Success

How a “People First” Culture Drives Tech Success
March 11, 2019
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“There’s no great product that doesn’t have a great team. So, there’s no great team that can’t achieve a great result”.

Said Gabriel Cismondi, the iGenius COO striving to keep our culture as fresh and innovative as crystal herself. Like any startup exec, his work is hands-on and varied.

He’s worked hard to craft a culture where talented innovators can thrive, putting “people first”, and ensuring their passion fills the workplace. After all, our team members are “the ones who are going to be trying to find the better way to do things,” Gabriel added.

There are plenty of tricky tasks to get right when managing a team, but Gabriel was keen to discuss one in particular:

Giving feedback — attitude of sensitivity

Everybody loves to give and get good feedback — but it’s tougher to handle when it goes the other way. This is where Gabriel has really fine-tuned the iGenius philosophy, putting the focus on the issue, not the person.

“When it comes to sometimes giving feedback to correct an attitude or improve something, the most important thing to remember is that you’re not trying to fix a person, you’re trying to fix something that happened,” he said.

Making something personal when things go wrong is sure to dull the team member’s passion — an asset we consider as important as their talent. So, Gabriel prefers to “have the sensitivity of understanding that you’re talking with a human being and that we’re not just what we do at work”.

Giving tech working the human touch

What does that mean in practice? It all starts with a chat to “focus on the data, and try to understand why things aren’t going the way you desire, and what we could do to improve it”.

It’s not about playing the blame game. It’s about asking the right questions:

What’s going on?

Is there anything preventing you from doing your job in the most efficient way?

Is there anything wrong about the project or the team?

Is it something personal? (If yes, you don’t have to talk about it, or maybe you want to.)

Do you need someone’s help?

“That’s what I mean by sensitivity — it’s important to make people understand that they are free to talk about anything.”

This is just one element of Gabriel’s mission to stay “one step ahead” of a rapidly growing AI industry:

Spotify-inspired agility

Based in our London office, Gabriel’s immersed himself in the city’s thriving tech community. His goal to “get inspired” in “probably the best city in Europe for startups and technology” has helped form iGenius’ agile approach.

Influenced by Spotify’s squad framework, our management model focuses on rapid, incremental changes rather than hasty wholesale ones.

“Small steps. Execute something, measure the outcomes. If it’s good, let’s go on. If it’s bad, let’s fix it. It’s about taking very small, fast steps, so we can change the direction or fix things as fast as possible,” Gabriel explained.

Our design dream team doing their thing

With a 100-person team, spread over four international offices (Milan, California, London and Switzerland), iGenius is growing. We may be a startup, but Gabriel’s innovative approach has helped us work like an enterprise.

What did he have to say about crystal, our AI-powered advisor for data intelligence?

Built for people

Getting useful info from numbers is normally a data scientist’s job, but it’s become more important than ever for it to be everyone’s. Democratizing data access is key, and what Gabriel finds so wonderful about crystal.

“We say get data talking,” he said.

“Because not many people know what’s under the hood, how a database works, or all the layers of complexity. But, everybody knows how to speak.”
“So, anyone in your business can just take a smartphone, asking something about the business, and you can get the data straight away, in the simplest and easiest way: the conversational one.”

He touched on how simple crystal is to install too — being an out-of-the-box solution, cutting down on hassle and time.

“We go from the data level to the client-facing part of the application — meaning we solve everything in the middle, we integrate, we do all the processing, we have all the AI, the everything. We have a fully working solution.”

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