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How To Cultivate Data Culture: A Data Analyst’s Guide

This is a guide to building up data-driven organizations as a data analyst. Learn how to cultivate data culture.

How To Cultivate Data Culture: A Data Analyst’s Guide

In my past work experience as a Data Analyst, I was regrettably unable to see through one of the larger projects that I had ever started – the seemingly insurmountable task of changing my company’s culture into one one that was data driven.

This was a task entrusted solely to me, the only Data Analyst in the organisation. While the process of cultivating data culture was supposed to be more of a team effort, I was able to achieve small successes on my own – when some of my initiatives yielded positive feedback from stakeholders. Gradually, these discrete victories started piling up and gaining momentum, and the end vision of a data driven organization suddenly seemed much more achievable than before!

This article is a list of findings on what worked in my efforts to inspire data culture in my organization. I honestly think that these perspectives are relevant not just to Data Analysts, but to everyone and anyone looking to power their organizations to greater heights.


What is Data Culture?

It is probably apt to address what the term ‘data culture’ refers to. In a conference paper published in 2019, Wolfgang Kremser and Richard Brunauer seek to understand what having a data culture entails, by surveying how different organizations define it in the workplace. The authors helpfully make the following distinction between data culture and data driven culture:

  • Data culture – refers to the standards and attitudes that employees (within an organization) manifest through their actions when dealing with situations involving data
  • Data driven culture – a heightened quality of data culture, when employees of an organization possess greater appreciation of data and its associated applications

In the context of this article, my efforts in my previous workplace aimed to perpetuate a reliance on product data to drive decision making. As the strategic decisions around me (surrounding feature prioritization, onboarding monitoring) were traditionally based on user feedback and heuristics, my organization’s data culture was one that was more reliant on user-triggered alerts than it was based on proactive monitoring of data. Firefighting was prevalent and as such, I made it my personal goal to inculcate data driven mindsets in my stakeholders.


1) Laying the foundations for a data driven organization: Case studies

Data Analyst responsibilities

As a Data Analyst, my day-to-day responsibilities included:

  1. Data collection and interpretation
  2. Dashboard development (for monitoring and reporting purposes)
  3. Data modeling
  4. Other ad-hoc tasks (data requests, new data projects etc.)

In addition to these, I was seen as the steward for all things data related. Product owners would approach me separately with their own specific data requirements. Because of this, my stakeholders could only see and appreciate the insights relevant to them, without a holistic understanding of a ‘bigger data picture’.

Case studies to inspire a data driven approach to problem solving

To overcome this, I presented a series of ‘case studies’ of several popular user journeys to them:

Through such case studies, my Product Owners were presented with possible methods through which they could derive insights from their application data. Inspired by the possibilities of what they could do with such information, they became more obsessed about generating patterns from their data.

Some anecdotes:

“Hey Gab, could we do a user journey for my document import tool? I want to see if users are dropping off the journey because they want to double-check on their company information.”

“Hi Gab, can we look at the user journeys from this particular page? I want to see the split, how many users proceed down this path compared to the other.”

As a whole, I felt that the case studies provided an element of relatability to my stakeholders. It simplified the task of data analysis and made it more accessible to them, therefore encouraging a data driven mindset.


2) Empowering stakeholders with data driven mindsets and practices

With my stakeholders now familiar with the practice of looking at their data and thinking up insights that they might be interested in, I then looked to empower them with the skills needed to generate these insights on their own. As the saying goes, ‘Give a man a fish, and you feed him for a day. Teach a man to fish, and you feed him for a lifetime.’

Over time, my role in this process retracted to a more consultative one, where the stakeholders would only ask technical questions surrounding the use of the user engagement tool that was being used. In the space of a few weeks, my Product Owners were able to develop their own case studies and share them with the others! These people were now data stewards on their own, empowered by their new knowledge and possibilities that I had presented to them.


3) Long term: defining a sustainable data driven strategy

In the grand scheme of things, I was but a lowly Data Analyst gunning for organizational change. Throughout my journey, I was extremely lucky to have the support of my immediate supervisor, who gave weight to the initiatives that I proposed and challenged my thought process. Without his help, my ideas to challenge existing work processes would have most definitely been met with resistance.  I would therefore consider having sponsors to push your ideas forward as essential when creating a sustainable analytics culture within an organization.

In addition, I felt that it was important as a Data Analyst to remain continuously updated on the latest data trends and tools, and introduce them to my stakeholders - This would keep them excited about potential new ways to improve the way they look at data, further building up their data driven mindsets.


Conclusion

I’d like to round up this article with some words of encouragement to my Data Analysts readers out there – Data Analysts are the non-replaceable foundation of any modern, data-driven organization in the world today. While creating a data reliant company culture from scratch might seem very daunting, it does help to break up the entire process into smaller tasks. By spreading your passion for data to the people you work with, you might be pleasantly surprised by how easy and enjoyable organizational change could get. With that, I wish you well my reader, in your mission to create your own data driven culture.