Sometimes, I know I’m going to have to work a relatively difficult technical problem. The kind of task where a few minutes of inspired work could easily be more productive than 8+ hours of me mindlessly grinding at the same problem, getting frustrated about how I’m not getting anywhere.
Not all of my tasks are like that, but for the tasks where I know will be stretching my abilities to their max – my success or failure has very little to do with time spent, and much more to do with energy available.
Over the course of a few years, performance on these type of deep work tasks is also what separate the upper-tier vs replacement-level data scientists.
On the other hand, for the more mundane tasks, the time management perspective is much more relevant. If you have five half-hour meetings tomorrow, you’re going to need 2.5 free hours to attend those meeting. If you have to read some requirements or sanity check someone else’s code, that’s more time dependent and it doesn’t really matter if you’re feeling especially inspired.
For a data scientist working in a realistic environment, how can the right balance be found?
This is going to be a multi-part article series discussing time management vs energy management; this first part will discuss what I think is the first step: getting on the same page with your manager.
Clearly communicate with your manager (and their manager if necessary)
Especially for data science managers who have never actually been a data scientist themselves, it’s likely that they will not be thinking about your calendar and workload from an energy management perspective.
To them, they probably don’t see much of a problem with multiple intermittent meetings showing up on your Tuesday calendar. They might think it’s maybe ‘not ideal,’ but they also probably won’t appreciate how much of a productivity killer this is for a data scientist trying to do deep work.
Put another way, some managers don’t think interruptions are especially disruptive, and how you can get right back into near-optimal productive mindset within three minutes. For a manager who is multi-tasking all day, that is their reality. Unfortunately, data scientists have very different type of challenges to work on, and not all managers appreciate this yet.
It’s not just having a block of time – if I already had my energy drained from a previous burdensome administrative or bureaucratic meeting, I’m going to have a hard time being highly productive for the immediately proceeding deep work task. This requires me switching between two very different mindsets, and that switch is neither quick nor efficient.
I’ve discussed this with my data science industry group, and we generally agree that a good (if somewhat uncomfortable) approach is to have a very frank, upfront conversation with your manager about this.
High urgency vs high priority items
Conversely, there are maintenance and administrative items we all need to take care of as part of the job, and some of these require meetings. And sometimes, the meetings are urgent.
Realistically, from a manager’s perspective, of course they want you to be productive and spend most of your energy working on the team’s strategic goals. However, unless you clearly communicate with your manager, they might not be aware that you’re getting overwhelmed with high-urgency items, and have little energy left for the actual high-priority items.
Depending on your manager and the team’s current workload, they might be able to immediately assist in helping to remove the lower-priority productivity killers off of of your plate – or if the team is too strapped for resources right now, at least recognize where you’re coming from and mention they’ll try to assist in the future.
However, if your manager doesn’t at least theoretically recognize that you being interrupted all the time might not be the best data science environment – it might be time to look for a new job.
In a future article, I’ll discuss some more thoughts about data scientist energy management (beyond just getting on the same page with your manager).
Below are some examples of related concepts that I’m currently thinking about, but will have some (hopefully) useful thoughts to share later:
- Diplomatically saying no, and getting your manager to step in if necessary
- Delegating tasks and efficiently onboarding team members
- Shamelessly blocking off extended blocks of time on your calendar
- Recognizing early-stage burnout and taking aggressive action
- Forcing yourself to take a vacation that’s actually relaxing (and not a death march of fun)
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