.png)
Data Leadership: 3 Tips To Sustain Context Switching
- Christian Steinert
- Sep 23
- 5 min read
From SQL to Boardroom: A Field Guide to Thriving in Data's Multi-Hat Reality
This past week was a learning journey. 'Tis the season of weddings and family obligations - I went back to my hometown for the week in Wisconsin. However, the time home was not wasted on the business front. I managed to conduct business commitments as well - visiting my alma mater and having productive chats with faculty of their nursing school. I also got deep in development, grinding away on client work.
I'm trying to immerse myself in healthcare right now, so learning from the people of the institution that built my foundational knowledge of business was a convenient path. I'll tell you - something overlooked as a data consultant, and data leadership in general, is the chronic context switching required to be successful.
I'll have weeks drowning in code. Sometimes it's just me managing a client's entire data stack end to end. From database administrator to analytics engineer to analyst & product manager, I find myself switching between these roles each hour of the day.
If you layer business development meetings on that, you then have to pull yourself out of coding mode into sales mode. THAT is truly hard.
Joe Reis dropped a brilliant article on politics in data and the three hats we data professionals wear at any given time. It got me thinking…
More than any time before, his points resonated heavily with me this week. Work piles up and client deadlines are real. The focus has always been on showing value quickly at Steinert Analytics, but to do that in practice requires project management, true focus, and advanced data engineering expertise as we all know.
Meanwhile, you also have a business (or a team in the case of data leaders) to run. After a deep-dive conversation with my marketer, things are going to pivot and change slightly with my approach to getting in front of the right people. I won't expand on that, but the point here is that this is yet another subject area I'm simultaneously trying to master - lead generation. All while dealing with complex data infrastructure, organizational client politics and sales conversations.
Phew - it's no wonder data leaders and consultants get burnt out quickly.
That's why I want to give you 3 tips for navigating this reality. I ensured these tips not only apply to consultants, but data leaders too. I always speak from MY experience. I've never led an in-house data team as a full time employee. However, I have a taste for what it's like leading healthcare data teams as a consultant and chief data strategist of Steinert Analytics.
Here we go…
Tip #1: Master the Art of Rapid Mental Gear Shifting
First and foremost - take a break before shifting into a different role. If you're heads down in code for the morning, go take a 10 minute walk or eat some food before stepping into sales calls for the afternoon.
At least for me, this helps me reset and be present - even if it's something small like standing up at my desk or doing a 2 minute guided meditation.
The physical or ritualistic actions of shifting into that different mode have helped me greatly. They change your physiological state. Either cardio or guided breathing tend to be the best ways for myself to gain back control and switch modes.
I want to expand on staying in the present. This has always been the most challenging piece for me. Even when on calls, I've found my mind racing ahead to connect the dots for a code solution or sales outcome. I can't be the only one.
This detracts from truly understanding the task at hand. Whether writing SQL logic for one specific metric or understanding a prospect's data problems, the present should be your only focus.
Tip #2: Communicate Your Value Story Across Contexts
I always focus on the outcome. Whether I'm six layers deep in a 2,000 line SQL query or preparing for a data strategy discussion with a CEO, I always tie what I'm doing back to the business outcome.
Always ask the question - how does this generate business value?
An outcome-first mindset isn't something that's natural. Especially as a data engineer. We like to focus on solving the coding problems at hand, rather than the business outcome the overall product build supports. I attribute this to the great pressure and stress placed on engineers to deliver quickly.
Focusing on the outcome changes the course of execution in the development process. It forces us to build in a way that supports the goal. Not what supports the task at hand. Furthermore, constantly being in this mindset allows you to quickly flip the conversation from using an advanced REGEX expression in SQL to how the report drives an ROI for the business.
Tip #3: Strategically Timeblock Your Calendar
I haven't mastered this yet. I have calendar blocks for deep work focus daily. However, I haven't structured my calendar in a way that dedicates certain days and times to code vs. sales and business development.
Here's what I've learned works better than random scheduling: batch similar contexts together when possible. Instead of alternating between coding and sales calls throughout the day, I'm experimenting with "theme days" or at minimum "theme blocks."
Mondays and Tuesdays become my heavy development days. Wednesday morning is reserved for business development calls and strategic thinking. Thursday morning is client check-ins and project management. Friday is reserved for content creation in the AM and client check-ins in the PM.
The key insight? Context switching has a cognitive cost. Every time you shift from writing complex SQL to explaining healthcare data strategy to a prospect, your brain needs recovery time. By batching similar activities, you reduce the total switching overhead.
But here's the reality - perfect batching isn't always possible. Client emergencies happen. Prospects can only meet at specific times. That's why the first two tips are so critical. When you can't control the switching, you need systems to handle it gracefully.
I also block "transition time" between different types of work. A 15-minute buffer between a deep coding session and a sales call isn't wasted time - it's essential recovery time that makes both activities more effective.
The Bottom Line
Context switching in data leadership isn't going away. If anything, it's intensifying. The most successful data professionals I know aren't the ones who avoid switching - they're the ones who've learned to thrive in it.
Your ability to speak database optimization with a CTO in the morning and healthcare ROI with a nursing administrator in the afternoon isn't a burden - it's your competitive advantage. The market rewards leaders who can bridge technical depth with business strategy.
But sustainability is key. Burnout is real, especially in our field where the technical demands keep growing while business expectations accelerate. These three strategies - intentional gear shifting, outcome-focused communication, and strategic calendar management - aren't just productivity hacks. They're survival skills for modern data leadership.
As I continue building Steinert Analytics and diving deeper into healthcare data, I'm constantly refining these approaches. The week in Wisconsin reminded me that our best insights often come from stepping outside our daily routine and seeing our work from different perspectives.
The nursing faculty at my alma mater didn't care about my SQL optimization techniques. They cared about patient outcomes. My client needed their new report to work, period. My marketer wanted to understand who best to position our sales outreach to. Same expertise, different contexts, different value stories.
That's the reality of data leadership in 2025. And honestly? I wouldn't have it any other way.
What's your biggest context switching challenge? How do you maintain quality while wearing multiple hats? Comment below!
Christian Steinert is the founder of Steinert Analytics, helping healthcare & roofing organizations turn data into actionable insights. Subscribe to Rooftop Insights for weekly perspectives on analytics and business intelligence in these industries.
Also - check out our free Healthcare Analytics Playbook email course here.
Comments