5 Ideas to Foster Data Scientists/Analysts Engagement Without Suffocating in Meetings

Author:Murphy | View: 22930 | Time: 2025-03-23 12:21:39

When managing a Data Science or a Data Analytics team, it can be a challenge to find a good balance between enabling uninterrupted focus time for your team members and fostering engagement, collaboration, and a team spirit. Throughout my journey as a team leader, I've tried numerous iterations and approaches to achieve this balance. In this article, I'll outline the five essential touchpoints that I currently have that work well for me and my team.

Whether you're an Analytics team leader seeking inspiration or a data scientist yearning for relief from "too many meetings", I hope these insights will invigorate your own professional journey.

1 – Morning standup

Cadence: Daily
Duration: 15min

Directly taken from the agile methodology, the morning stand-up is a brief yet essential daily gathering happening first thing in the morning (at a consistent time). Although some folks might start their day earlier, the standup meeting serves as a unifying launchpad for the entire team. During this meeting, everyone, including the manager, takes turns providing concise updates on the following:

What they accomplished yesterday,
What they plan to achieve today,
Any obstacles or blockers that require offline discussion with the relevant parties

Why a morning stand-up meeting?

→ Fosters Focus and Commitment: It instills a sense of purpose and commitment to the team's daily objectives.

→ Enhances Awareness and Collaboration: It provides team members with insights into each other's projects and progress, fostering connections and promoting collaboration.

→ Early Blocker Identification: Identifying roadblocks at an early stage prevents wasted efforts and ensures smooth progress.

→ Keeps the Manager Up to Date: The meeting keeps the manager well-informed about the team's progress, allowing for effective oversight.

Unless it pertains to the whole team, more in-depth conversations should be taken offline with the relevant parties. This short meeting is also the opportunity for the manager to do minor announcements or reminders to complete admin tasks. (More details on the morning stand-up here).

Reflections on Alternative Approaches:

Operating in full Agile mode, using a sprint cadence: This approach has been proven highly effective for a dedicated development team working on a singular product or project. However, its application to an Analytics/Data Science practice presents challenges. The fundamental issue being that team members often engage in diverse projects or analyses, many of which don't neatly align with the standard sprint cycle – Data Science projects tend to extend beyond the typical 2 to 3-week sprint duration.

This divergence in project timelines and scopes also meant that only a fraction of some Agile ceremonies (planning and backlog grooming sessions) aligned with the specific needs of individual Data Scientists. It became apparent that attempting to shoehorn diverse and multifaceted Data Science tasks into the rigid structure of traditional Agile sprints presented significant inefficiencies.

2 – Friday "Work In Progress" Presentation

Cadence: Weekly
Duration: 15min +

We recently implemented this as a way to foster collaboration without having to book an extra time slot in the calendar. This initiative, which replaces the standard daily stand-up on Fridays, takes on the essence of a mini braintrust. It is scheduled for a crisp 15 minutes but as Friday mornings are usually less meeting intensive, conversation is free to go longer if needed.

It's a space where one volunteer can informally present a piece of work in progress, seeking the collective wisdom of the team on various aspects, such as:

"I'm working on this model, and would love to hear what you think"
"I'm thinking of 2 ways to solve this problem, which option is the best?"
"Here is what I'm about to present to stakeholders, how can I make it better?"

Why a "Work In Progress" presentation?

→ Communication skills: This session offers a regular platform to hone summarization and communication skills.

→ Deeper Insight: It provides the team with a window into the technical intricacies of ongoing projects and tasks

→ Collaborative Problem-Solving: It encourages team members to engage and bounce ideas from each other

This format struck a good balance, fostering active participation and collaboration while offering the flexibility for those with a deeper interest in the subject to explore it further.

Reflections on Alternative Approaches:

Initially, I conducted these braintrust sessions as separate 1-hour Meetings, a format that could have allowed for more in-depth, technical conversations. However, it became evident that participants often opted to skip these sessions in favor of task or project completion, resulting in less-than-ideal attendance. Moreover, the 1-hour duration sometimes acted as a deterrent for volunteers to step forward and share their ongoing work.

3 – Data Science team meeting

Cadence: Monthly
Time: 1h

This more formal gathering happens monthly (see note below for cadence choice) and is the opportunity to step back from day-to-day tasks/projects and reflect on the team's ways of working and future opportunities. We also try to invite someone from a different functional area to introduce the work that they do and discuss potential synergies. Our meeting structure adheres to the following framework:

5min: A quick update on administrative matters and essential reminders.
25min: A) Retrospective, providing an opportunity to reflect on our past experiences OR B) strategy/roadmap update and projects planning, enabling us to look forward
30min: guest from the organization

Why a Data Science team meeting?

→ Reflect and Plan: This meeting offers the chance to step back, reflect on the past, and set our sights on the future

→ Ownership of Ways of Working: It empowers our Data Scientists to take charge, dissecting what worked well, what didn't, and committing to improvements

→ Project Visibility: It gives the team visibility into upcoming projects and the opportunity to align with projects that resonate with their interests and expertise.

→ Broadening Horizons: It broadens our team's understanding of the organization, nurturing connections and partnerships with different functions of the business

Reflections on Alternative Approaches:

These meetings were originally bi-monthly and solely focused on doing a retrospective, as we would address other elements through different touchpoints. However, as our team expressed an appetite for more insights into projects assignments and strategy, we consolidated some of these other touchpoints which allowed for a stand-alone monthly team meeting.

In a different setting without morning standups and less regular 1:1s, I found that the weekly cadence for a team meeting was effective. This format included a blend of administrative updates, Kanban board reviews, and weekly project or technical insights presentation by team members.

4 – Individual One-on-One

Cadence: Weekly
Duration: 30min

This is the space in the weekly schedule which is dedicated to the data scientist or data analyst. Here is a great resource on how to set up and conduct successful One-on-Ones. I've adapted mine to the following structure:

JIRA/Kanban board review and update (5min or less)
The priority for the conversation is to NOT talk about specific projects or tasks, but rather provide opportunity to the individual to bring what they want to chat about on the table.
Feedback, coaching, professional development
Quarterly goal-checking and planning
If time allows – then a conversation about a project or task could happen

Why an Individual One-on-One?

→ Relationship Building: It establishes and cultivates a relationship between the Data Scientist/Analyst and their manager and builds trust

→ Growth and Development: It fosters the growth and development of the Data Scientist/Analyst through personalized feedback and coaching, in addition to nurturing managerial growth through reciprocal feedback. See this article for details on expectations for different levels of Data Scientists/Analysts.

Every quarter-end, our attention shifts towards assessing our annual goals, which encompass both organizational/project targets and individual professional development objectives, as we check our progress towards achieving.

Reflections on Alternative Approaches:

We have explored the option of a 45min conversation every 2 weeks but this fell short for us. Our conversation often concluded within 30min and the two-week intervals between sessions seemed too lengthy to maintain a strong connection.

Kanban Board review: we originally set aside separate meeting for Kanban board review. We later incorporated into a slightly longer morning standup. Both options didn't resonate well for the same reasons as operating in full Agile: given the more individual nature of Data Scientists/Analysts tasks and projects, only limited portions of the meeting was relevant to each person. It then made sense to amalgamated this individualized touch-point with the One-on-One meeting as a quick admin item to tick before getting into the core conversation.

5 – Department Team Meeting

Cadence: Monthly
Duration: 1h-1.5h

The last thing to foster Data Scientist/Analyst engagement and team spirit, well I don't do it myself – it's the broader team monthly meetings. It usually comprises some of the following elements:

Introducing new team members
Recognition of successful projects or team members
Updates from the department Director or VP
Business updates
Fun activity
Project shares
Organization culture activity

Why a Department Team Meeting?

→ It exposes the Data Scientists/Analysts to the broader department and builds a sense of belonging

→ It allows the individuals to understand how their work fits in the department

→ It helps identify expertise in the department and resources to use for a current or future blocker

Conclusion: Here you have it, the essential touchpoints that – for me – are not overburdening work schedules but allow to nurture engagement and team spirit. Of course, it remains subject to continuous refinement and adaptation!

What do you think is redundant or non-essential in those 5? What are some of the things you do differently that work well for you and your team? Please let me know in the comments below!