Biggest Productivity Killers for Data Teams: Battling Context Switching and Distraction
Intro
Who hasn’t started a new job or project and told themselves, “This time will be different”?
You’ve promised to stay organized, plan better, and avoid distractions.
But like that famous quote from Jurassic Park, “Life finds a way.”
In this case, life finds a way to pull us back into habits that prevent us from reaching our full potential. If you’re leading a data team, this often means juggling multiple projects, managing ad-hoc data requests, and attempting to keep everything in balance.
Amid the chaos, it often feels like nothing is truly getting done. You might even feel like you’re paddling in a vast ocean but never really making progress.
So, how do you actually get things done while leading a data team? Let's dive into some strategies that can help you overcome these challenges.
Massive Productivity Killers For Data Teams
For many data teams and leaders, the reality is that they often become a catch-all within an organization. From clear data projects to one-off integration and automation tasks, the range of responsibilities can be overwhelming. Add in the growing hype around data—especially what AI and other modern techniques can accomplish—and it’s easy for teams to end up with a larger scope of work than they can realistically manage.
This makes it difficult to actually complete projects and achieve the impact that data teams are expected to deliver.
Here are just a few key issues holding teams back:
Context Switching Initiatives
On an individual level, context switching means getting pulled in different directions on short-term initiatives: 15 minutes on one project, an hour on another, and before you know it, you’re scrolling through LinkedIn instead of focusing on work.
On a team scale, context switching can be harder to spot because the window can be far longer. For instance, spending a month on a migration project, two months on an AI project, and a week handling ad-hoc requests—by the end of the year, nothing significant gets done.
Don’t get me wrong—data teams do need to learn to balance ad-hoc work with long-term projects. But in my experience, focusing heavily on one or two larger initiatives and completing them tends to lead to faster success than juggling four or five big projects at once.
Bad Meeting Hygiene
Does this sound familiar?
Your team starts a new project and sets up a few recurring meetings to discuss progress. For the first couple of months, things are productive, but over time, these meetings become less about real work and more about going through the motions.
Eventually, they turn into distractions, pulling you away from delivering real impact. Before you know it, your days are filled with meetings with other teams about other projects, leaving you too tired to challenge their existence.
Lack Of A Clear Mission
Some data teams quickly become catch-all technical teams. I referenced this earlier, but instead of just focusing on data analytics, they might get pulled into iPaaS projects or automation workflows where they have little context or understanding of the subject matter.
Much of this is driven by a lack of a clear mission or set of priorities for the team at large. At the end of the day, if you don’t define what your team is focused on and what it’s not, every task will come your way. Now, this doesn’t mean you can’t take on work that might be out of scope for your current team.
I find the best way to ensure your team focuses on the write work is define a set of pillars of work that your team does do and define how that supports the business and in turn your mission.
For example, if you’re teams mission and pillars could be:
To empower our organization to be more customer-centric by providing insights that drive operational excellence, enhance personalized customer experiences, and maximize profitability across every channel.
To do so, our team focuses on:
Data Accessibility and Democratization - Meaning you’ll likely be taking on projects that pull data out from sources and centralize them in a data warehouse or data lake.
Data Governance & Security - If you only focus on giving access to data, you’re going to end up in a world of hurt security and privacy wise.
Customer-Centric Analytics - There are plenty of analytical projects your team could take on, HR, Operations, etc. But it might benefit the business to be focused purely on customers for the next year depending on the overall strategy.
Now, when another team asks you for an ad-hoc request, you can compare it against your overall mission(which should be aligned with the business). If it doesn’t drive your mission and thus the business's mission forward, it likely is not a good use of your time.
How To Ensure Your Data Team Gets Projects Done
So, how do we address the issues that hold your team back from delivering what the business actually needs?
Here are a few principles I’ve learned over the years:
#1 Break Projects Down Into Phases
You’ve likely heard the advice to break tasks down, but this principle applies to projects as well. Projects often have multiple phases, and treating them as one massive, year-long endeavor can lead to several challenges:
It makes it hard to stay flexible and adjust as the project progresses.
It’s tough to assess when phases are 100% complete because you may be juggling several phases simultaneously.
It can be hard to pause and focus on other important work.
It creates tension between you and the business as they wait for the entire project to be finished.
However, when you break projects into manageable phases, it not only keeps your team motivated but also makes it easier to adjust and deliver progress in small, more digestible chunks. I’ve found this approach to be especially effective in my consulting projects as well as my work at Facebook. Dividing projects into key phases and milestones helps maintain momentum and provides a clearer way to communicate what’s been completed.
#2 Clear Goals and Priorities
If your data team doesn’t have a clear set of overarching goals or priorities, it’s easy for things to get derailed. On the flip side, if you define goals, both for your team and the business, it becomes much easier to stay focused. For example:
“For the next three months, our goal is to accomplish X.”
This simple clarity makes it obvious to your team what should be prioritized on a day-to-day basis and, equally important, what should be deprioritized.
When the business approaches you with a large request, you can confidently tell them it’s not on your team's roadmap and give them a realistic timeline for when it can be tackled.
Again, by breaking projects into phases, you can clearly show when a new initiative can be added to your team’s project pipeline.
#3 Expect Ad-hoc Requests
When we planned out our next six months at Facebook, we always factored in time for ad-hoc work. You can’t avoid it—it’s part of the job.
Instead of resisting it, it’s far better to accept ad-hoc requests and find strategies to handle them effectively.
First, I am not saying you should say yes to every ad-hoc request. Be discerning.
Second, find times that are best suited for ad-hoc tasks. These shouldn’t interfere with your deep work hours. If the ad-hoc request is lighter work, consider handling it at the beginning or end of the day.
At the start of the day, tackling a few quick wins can give you a sense of accomplishment. By the end of the day, when you’re feeling a bit exhausted, handling simpler tasks might help you wind down.
#4 Clear Out Meetings Every Once And A While
"We deleted 322,000 hours of meetings," Shopify's chief operating officer Kaz Nejatian proudly shared in a recent interview.
Back in early 2023 Shopify announced that they:
Had created a bot that went into everyone's calendars and purged all recurring meetings with three or more people, giving them that time back.
I find that doing something similar with the meetings you have, especially at large organizations is a great way to see what meetings actually need to exist. I referenced bad meeting hygiene earlier, an easy fix is to get rid of any meetings that aren’t really being used for anything other than an update call.
#5 Create Space for Deep Work
As a data team leader, you set the example. If you’re constantly working and attending meetings, your team may feel compelled to do the same.
But if you set aside one day a week dedicated to deep work, your team will likely follow suit. I once worked with a manager who declared Wednesday as their deep work day. Soon enough, the entire team adopted Wednesday as their focused work day, too.
It was as if that day already had a full docket of meetings.
Another technique I use is to shift meetings to the beginning or end of the day. After experiencing the dreaded “30 minutes on, 30 minutes off” meeting schedule a few times, I realized the importance of making this shift for better focus.
Final Thoughts
Whether you’re working to get more done as an individual or leading a team, the core message remains the same:
Focus on doing less, but delivering longer-term value.
Create space for deep work.
Expect distractions—set aside time for ad-hoc work and make it easy to get back on track.
Set clear goals.
If you’re always chasing the latest trends or trying to keep up with what others are doing, you’ll never make real progress. It’s tempting to jump from project to project or take on more work, but eventually, you’ll find yourself stuck, spinning your wheels without moving forward.
As always, thanks for reading.
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