Thriving in People Analytics: Embracing Ambiguity & Applying Science

For our people analytics series, eqtble had a chat with Nicole Ferguson to discuss the essential skills for those looking to excel in the field. Contrary to popular belief that technical skills, such as R, Python, or Tableau, are the primary drivers of success, Ferguson emphasizes the importance of dealing with ambiguity and employing the scientific method in people analytics.

Dealing with Ambiguity: A Pivotal Skill for People Analytics Professionals

Nicole Ferguson shares her perspective on the most valuable skill for people analytics professionals, stating, "A lot of times when I read these posts on LinkedIn or webinars or I'm hearing about them in podcasts, people will be like, 'oh, you need to learn R, you need to learn Python, Tableau is where it's at, oh have you tried SQL?' Let me tell you, I've tried all of those, and that has not been what has led to my success in people analytics." Instead, she believes that the ability to navigate and thrive in ambiguity is crucial for success in the field.

Ferguson further explains that the most remarkable people analytics professionals she has worked with have one standout trait: "they deal really well with ambiguity." In a field that often involves making sense of complex and uncertain situations, the ability to work effectively in ambiguous environments is paramount.

The Power of the Scientific Method in People Analytics

Ferguson suggests that the key to cutting through ambiguity is applying the scientific method, which enables professionals to "isolate that factor that you need to study and all this chaos of the organization." By systematically breaking down complex issues and identifying the critical variables at play, people analytics professionals can generate actionable insights and recommendations for their organizations.

Mastering the scientific method in people analytics involves several steps:

  1. Formulating a hypothesis: Start by developing a testable hypothesis based on the issue or question at hand, while considering the organizational context.

  2. Designing a study: Create a research design that allows for the systematic investigation of the hypothesis, taking into account relevant variables, potential confounding factors, and the unique characteristics of the organization.

  3. Collecting data: Gather the necessary data to test the hypothesis, ensuring its accuracy, reliability, and relevance to the organizational context.

  4. Analyzing data: Use appropriate statistical techniques to analyze the data and determine if the results support the hypothesis, while considering potential biases and limitations in the data.

  5. Drawing conclusions: Interpret the results, taking into account the broader organizational context, and make recommendations based on the findings. Consider the implications of the results for stakeholders and decision-makers within the organization.

By embracing the scientific method, people analytics professionals can bring rigor and structure to their work, enabling them to better navigate ambiguity and make sense of complex organizational issues.


In our conversation with Nicole Ferguson, we learned that the ability to thrive in ambiguity and harness the scientific method are indispensable skills for success in people analytics. By focusing on isolating specific factors amidst organizational chaos and employing a systematic approach to problem-solving, professionals in the field can generate valuable insights and recommendations to drive strategic decision-making. While technical skills, such as proficiency in R, Python, or Tableau, are important, it is the ability to navigate and make sense of ambiguity that truly sets apart exceptional people analytics professionals.

Connect with Nicole Ferguson.