How Low-Code/No-Code is Engaging Teams

Last month, I spotted a Notion ad in the NYC subway. Apparently, I wasn’t the only one who noticed as the r/Notion Reddit thread was peppered with Notioners who ran into ads in the London and Paris subways. When I got off at my station in midtown, there was another ad with a familiar yellow background from Miro that greeted me. This was my first time encountering both apps “offline” after working remotely for the last 3 years.

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A movement is underway: the transformation from the traditional business suite to something new. And with that, the transformation of the knowledge worker to the citizen developer.

The typical business suite of tools that consists of Powerpoint, Excel, and Word seems to be soon evolving into the suite of Zapier, Airttextable and Webflow. That’s certainly already true in my company and startups but soon I believe these tools will start appearing on people’s resumes as a core part of their marketable skills.

As a non-technical founder, I’m excited by the low-code/no-code (LCNC) movement. What’s underlying the adoption of these tools is even more important - it’s about democratising how innovation happens, and how quickly things are done. No code tools enable people regardless of their role or the background to solve the problems that are right there in front of them without involving a centralised tech team and backlogs.

That’s what I see taking place at my company. For instance, our marketing team already had the building blocks to create a workflow that’s optimised for their function and metrics. By using Airtable and Zapier, the team can move faster, and solve their own use case.

There are a number of debates from developers about the merits of no code/low code and whether or not developer teams are no longer needed. The truth is that no code/low code actually takes the burden off from the centralised IT and lets developers focus on solving the real complex, hairy problems that need professional developers and leave some of the simpler things to those department level use cases to the “citizen developers”.

**The same is the case in data teams. **Most companies are waiting for their lean data science teams to analyze new opportunities for improvement when more power can be given to the business user.

The current analytics process often starts with someone from the business suggesting a hypothesis of what might be a useful insight within their dataset. The business team will then work with a data scientist to gather and combine data into a structured format. After weeks or even months of the upfront work, data scientists can finally test if there was indeed a conclusion that’s statistically significant. If not, they might restructure the underlying data and start again. This manual process, combined with a talent shortage has driven a significant gap between data science demand and access.

Currently, Eskwelabtexts works with more than 180 companies in helping them create a talent engine for data. There has been a shift in the past year where data-savvy organisations are moving from hiring data professionals to enabling teams to become self-sufficient in answering their own data questions. We talked more about this trend in the “End of hiring for Growth” article. This move to democratise the ability to work with data also corresponds with tools like DataRtextobot, and Unsupervised which promise business users to generate advanced analytics without a data science team. Even market leaders like Databricks are seeing the value of “citizen data scientists”, demonstrated by their 2021 acquisition of 8080 Labs.

Seeing this first hand from inside Eskwelabs, I noticed that speed and productivity are not the only benefits for the team whether it’s in no-code development or data science. The engagement level that people feel when they can actually participate in making the workplace better for themselves and their colleagues is underrated, and the diversity of talent of those coming from underrepresented backgrounds who can now access development through no-code can further be explored.

Of course, LCNC is not a one-size-fit-all solution. Any tool’s impact can only be multiplied when people yielding it are charged with the mindsets to create solutions. So the other side of the coin for LCNC is the skills education and the critical thinking and data literacy to solve problems.

I’m confident more subway ads highlighting this shift will continue to pop up, whether it’s for a tool or a way for people to learn, the no-code future has arrived.

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