It’s Time To Bridge the Gap Between Data People and Non-data People

The data landscape has evolved at a tremendous pace in the last two years, resulting in a widening gap between data people and non-data people. If left unaddressed, this problem will continue to exacerbate and make it even harder for organizations to embrace a data-led culture.

For context, by non-data people, I’m referring to data consumers within organizations—primarily GTM teams who rely on accurate data being made available in analysis and activation tools they use every day.

Anyone who works in a data role, as an individual or as part of a team, is essentially a data person. Sometimes engineers are tasked with data engineering responsibilities, in which case they can also be referred to as data people.

Organizations today are making a serious investment in tools and initiatives aimed at broad-stroke cultural changes (read: data democratization), hoping to avoid the arduous route of taking small steps to empower individuals to do more with data every day.

This approach is, in fact, contributing to the gap between data people and non-data people. Bridging this gap is a hard problem with no one-size-fits-all solution, and I’d like to share some ideas that I believe can help.

What organizations can do to bridge the gap

It’s easier said than done and can take a while to show results, but I’d like to propose two concrete steps in this direction.

Evangelism

Organizations should consider hiring a bridge team or even just one person whose job is to understand and communicate the needs and the constraints of data and go-to-market teams to each other.

Think of this as bi-directional evangelism where GTM and data both have a better understanding of each other’s priorities and work towards keeping those priorities aligned.

In the long run, the bridge teams should help GTM teams with everything they want to know about the organization’s data infrastructure and at the same time, help data teams understand the impact of their work on business growth.

Companies that already have an ops function can think of the bridge team as an extension of the respective ops teams.

Enablement

I believe evangelizing without enabling is no good—more so when pushing for a new way of work.

Organizations must invest in a data knowledge repository containing answers to questions people have about the data infrastructure in place, and encourage GTM teams to keep asking questions. In fact, a Q&A repo like this can help data people too, especially those who are new to the org.

I’d like to clarify that I’m not referring to a data cataloging or discovery tool—it certainly has benefits but it’s not enough to just tell people what data is available.

There needs to be a system in place that allows anyone in the org to ask any question that they might have in regards to how data is collected, where it is stored, how it’s moved around, why certain data is not collected, and what is the process to change that, as well as who in the org is responsible for each of those items.

This is where the knowledge repo can make a big difference and can potentially improve collaboration between data and GTM teams. Organizations with a bridge team in place ought to be in a strong position to turn this idea into reality.

What individuals can do to bridge the gap

Organizations doing their part is not enough as individuals too have to do theirs.

Gaining a sound understanding of the organization’s data infrastructure and the purpose and benefits of the available data tools can go a long way for GTM teams to do more with data in their day-to-day. In fact, knowing basic SQL, while not at all necessary, can help people ask better questions and get faster answers.

Besides tapping into the knowledge of internal teams (bridge, ops, data), GTM people can also find answers to broader questions in external communities—data practitioners enjoy answering questions and the good ones don’t consider any question to be irrelevant or foolish.

Lastly, GTM teams must seek access to available data assets and figure out how they can utilize available data to improve the outcome of their efforts.

Non-data people should become passé

Referring to people as non-technical based on their roles is, to say the least, naive. Everybody—more so if they work at a tech company—is technical at some level; similarly, in the coming years, I hope it makes no sense to refer to people as non-data people if they work with data every day.

As you think about moving towards a data-led culture, make sure you’re laying the right foundation for clean data and reliable analytics by reading The Amplitude Guide to Behavioral Data & Event Tracking.