Professional Development Framework

Building analytics cultures through individual growth and continuous learning.

Professional development represents the intersection of individual growth and evolving expertise in our field. Through leading analytics teams in higher education, I’ve developed frameworks that balance these elements while recognizing that each person’s development path is unique and aligned with their immediate and long-term goals.

Mentoring as Continuous Exchange

Many organizations treat mentoring as a phase, something for new hires or early-career professionals that ends once someone reaches a certain level. This approach misses the fundamental nature of effective mentorship.

In successful analytics teams, mentoring is a lifelong practice involving the exchange of new ideas and methods, career navigation guidance, and diverse perspectives on shared experiences. A critical aspect of this framework: mentor and mentee roles are fluid and often shift within a single conversation. Both parties learn from each other, creating reciprocal value that strengthens the entire team.

The mentorship relationship I’ve cultivated serves as a safe space for asking questions, voicing concerns, and maintaining openness and honesty. The guiding principle: “If I tell you the truth while being kind, can we still be friends?” This approach fosters compassionate, supportive, and trusting relationships. Ideally, mentorship meetings occur in neutral spaces, outside either person’s office, to reinforce this collaborative dynamic.

To operationalize this framework, I encourage team members to complete a “How I Like to be Mentored” reflection (a structured activity that helps individuals articulate their communication preferences, learning styles, and feedback needs). Sharing and discussing these documents at the start of a mentorship relationship establishes clear expectations and mutual understanding.

Curated Learning Resources

The following collection represents resources that have informed my approach to analytics leadership, team development, and technical practice. They’re organized into three areas that mirror the key competencies for effective analytics work: professional development, data and modeling philosophy, and technical implementation.

Professional Development

Joy, Inc.: How We Built a Workplace People Love by Richard Sheridan Bookshop | Amazon | Apple Books
Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days by Jake Knapp with John Zeratsky & Braden Kowitz Bookshop | Amazon | Apple Books
Make Time: How to Focus on What Matters Every Day by Jake Knapp & John Zeratsky Bookshop | Amazon | Apple Books

Data & Modeling Philosophy

The History of the Data Economy: A four-part series from Significance Magazine and Impact that provides comprehensive context on how data has evolved as an essential organizational asset, current applications, and potential future implementations.
- “Part I: The birth of customer insight” by Timandra Harkness DOI
- “Part II: Analytics arrives” by Timandra Harkness DOI
- “Part III: The new kings and queens of data” by Timandra Harkness DOI
- “Part IV: The future” by Timandra Harkness DOI
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil Bookshop | Amazon | Apple Books
Invisible Women: Data Bias in a World Designed for Men by Caroline Criado Perez Bookshop | Amazon | Apple Books
Big Data: Does Size Matter? by Timandra Harkness (ebook only) Bloomsbury | Amazon | Apple Books
The Address Book by Deirdre Mask Bookshop | Amazon | Apple Books
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us about Who We Really Are by Seth Stephens-Davidowitz Bookshop | Amazon | Apple Books

Technical Implementation (aka Coding & Programming)

Learning Foundations

A First Course in Statistical Programming with R 3rd Edition by W. John Braun & Duncan J. Murdoch Bookshop | Amazon | Apple Books 1st Edition | Apple Books 2nd Edition
Learn to Program 3rd Edition by Chris Pine Bookshop | Amazon | Apple Books. This book uses Ruby to teach fundamental programming concepts. Translating examples to your preferred language provides valuable additional practice.

Development Philosophy

The Missing README: A Guide for the New Software Engineer by Chris Riccomini and Dmitriy Ryaboy Recommended purchase from No Starch Press where you can buy the ebook (PDF, Mobi, and ePub) OR the print book with FREE ebook | Bookshop | Amazon | Apple Books
Kill It with Fire: Manage Aging Computer Systems (and Future Proof Modern Ones) by Marianne Bellotti Recommended purchase from No Starch Press where you can buy the ebook (PDF, Mobi, and ePub) OR the print book with FREE ebook | Bookshop | Amazon | Apple Books
97 Things Every Programmer Should Know: Collective Wisdom from the Experts edited by Kevlin Henney O’Reilly | Bookshop | Amazon

These frameworks have been developed and refined through leading analytics teams in higher education environments. They’re designed to be adaptable across organizational contexts, from sports analytics to academic research to corporate settings, while maintaining focus on building collaborative, high-performing analytics cultures.