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Building High-Performance Analytics Teams Through Intentional Mentorship

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Building High-Performance Analytics Teams Through Intentional Mentorship

A framework I’ve developed and refined across multiple analytics teams.

Early in my leadership journey, I discovered that the most successful analytics teams aren’t just technically proficient; they’re built on foundations of mutual understanding and intentional mentorship. This realization came after observing how misaligned expectations and communication styles were creating unnecessary friction in otherwise talented teams.

The Challenge

In analytics environments, whether in sports organizations analyzing player performance or universities optimizing student success, we often focus intensely on technical skills while overlooking the human elements that make collaboration effective. I’ve seen brilliant analysts struggle not because they lacked skills, but because their working relationships weren’t optimized for their success.

The Solution: Structured Self-Awareness

I adapted and expanded a mentorship framework that transforms how analytics teams collaborate. By investing 30 minutes upfront in structured self-reflection, team members can prevent months of miscommunication and accelerate their growth trajectories.

This framework has helped me:

  • Increase team retention and satisfaction scores
  • Create more effective project assignments based on individual strengths
  • Build trust faster in cross-functional partnerships

Why This Matters to Individuals

Everyone in the group should answer these questions to help them gain a deeper understanding of themselves. Even if the results are not shared with others, the self-reflection enables you to see how external events and interactions shape your world. Additionally, you may find it easier to ask a colleague for help or explain your preferences.

Why This Matters for Analytics Leaders

In data-driven environments, we’re trained to measure and optimize everything, except often our own working relationships. This framework applies the same analytical rigor to human interactions that we apply to datasets.

Whether consulting with a new organization or building a long-term team, understanding these dimensions creates:

  • More effective knowledge transfer
  • Higher team productivity
  • Better project outcomes
  • Stronger analytical cultures

To make implementation easy, I’ve created a ready-to-use template that teams can customize for their specific context. Download the framework here (Google Docs/Word format).

How I Like to be Mentored

These questions are grouped into sections to make it easier for people to complete in stages if they prefer, and help group leaders quickly reference specific aspects of working relationships. Specifically, the questions are grouped to ensure:

  1. Progressive depth: Starts with big-picture goals, moves to personal attributes, then into tactical preferences, and finally addresses more vulnerable topics
  2. Logical grouping: Related questions are together (e.g., all timing preferences in one place)
  3. Psychological safety: More sensitive questions come after establishing context
  4. Actionable structure: Each section produces specific insights that a group leader can act on

Foundation & Goals: Understanding our partnership and aspirations

  • I want our working relationship to be…
  • Areas where I’m seeking growth and support include…
  • My top five priorities in life are…
  • I expect that this experience will affect my career goals by…
  • I envision success for myself within the next 6 months to 1 year as…

Strengths & Growth Areas: Leveraging what works and developing what doesn’t

  • My top three strengths are…
  • Areas where I’m actively working to improve include…
  • I want to learn [these specific skills, soft and technical] from you, and here is why…
  • I can help you learn more about…
  • I am enthusiastic and get excited about this/these aspect(s) of analytics and the work I do…

Working Style & Preferences: Optimizing our collaboration patterns

  • I like to work in [this type of working environment], and this is why…
  • How comfortable are you with ambiguity on a scale of 1-hedgehogs?1
  • My preferred learning style is… (select all that apply: visual | hands-on | reading | discussion)
  • My preferred communication mode is…
  • I prefer to have management meetings during the (select all that apply: morning | after lunch | afternoon)
  • I prefer to have group/technical meetings during the (select all that apply: morning | after lunch | afternoon)
  • I prefer to perform office-related tasks during the (select all that apply: early morning | mid-morning | late morning | after lunch | afternoon | evening | night)
  • I prefer to work on projects during the (select all that apply: early morning | mid-morning | late morning | after lunch | afternoon | evening | night)

Support & Communication: Building psychological safety and effective feedback loops

  • When receiving feedback, I prefer to receive feedback in the following manner… (frequency, format, setting)
  • When I need technical help, I usually…
  • When I need emotional help, I usually…
  • When I’m frustrated or facing challenges, I typically…
  • When I am stressed, I usually…
  • When approaching me about a concern, I want you to…
  • The best way to approach me with a concern regarding my work is…
  • The best way to approach me with a concern regarding my actions is…
  • I tend to approach others with a concern in the following manner…

Additional Context

  • Anything else I think is important to share:

Credits

  • Obtained from: https://current.org/wp-content/uploads/2021/06/How-I-Like-to-be-supervised.pdf
  • Originally created by: Campus Inclusion and Community, Northwestern University
  • Expanded by Emilio Xavier Esposito [ [LinkedIn](https://www.linkedin.com/in/emilioxavieresposito/) | [GitHub](https://github.com/emilioxavier) | [Bluesky](https://bsky.app/profile/exesposito.bsky.social) ]

Footnotes

  1. Yes, ‘hedgehogs’ is intentional. Sometimes the best scale endpoints are the ones that make you smile.↩︎

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