31 Self-Discovery: People Analytics Research Skills
How to use these tables:
- Read the description of each skill and make your best estimate of your current level of ability based on the following scale:
- Aware: You are brand new to this skill. You may know about it conceptually, but have not yet completed the task yourself.
- Learner: You’re just to learn this skill or still rely on detailed instructions and guides to complete this task.
- Skilled: You have some ability in this area, but you still need assistance or to tackle certain parts or advanced aspects.
- Expert: You confidently handle challenges in this topic area, do not need support, and can clearly and simply explain concepts to others.
- Strategist: You are applying this technique in new ways and creating new ways of doing this, you are able to mentor/guide intermediates and advanced individuals in this skill.
- Optional: Determine if there are any skills for which you would like to have a different future skill level and indicate your desired level. Keep in mind, that your desired skill levels may change over time and may change as you consider different possible career options. You will likely come back to this table and change your desired levels many times.
Note. Don’t worry too much about where you rate yourself, there’s no true score or measurement for something like this. The scale provided is only meant to provide a general sense of guidance and to serve as a thought provoking exercise.
| Skill | Description | Current Level (Aware/Learner/ Skilled/Expert/Strategist) | Desired Level (Aware/Learner/ Skilled/Expert/Strategist) |
| Research Frameworks | Understand and learn to follow both systematic (e.g., scientific method) and iterative (e.g., design thinking) research frameworks. | ||
| Research Design | Understand different research methodologies. The ability to select appropriate methods (experimental, quasi-experimental, non-experimental, qualitative, quantitative, mixed methods, etc.) to answer questions and test hypotheses. | ||
| Hypothesis Development and Testing | The ability to formulate clear, testable statements about relationships between variables (e.g., “Flexible work schedules will lead to increased employee satisfaction”). The ability to select the appropriate hypothesis testing methods and interpret the results. | ||
| Data Collection and Analysis | The ability to gather and analyze data effectively, ensuring reliability (consistency) and validity (measures what it intends to). Understand which data collection and analysis methods are appropriate for the selected research design and method (surveys, interviews, focus, groups, experiments, prototype testing, observations, etc.) to answer questions and test hypotheses. | ||
| Sampling Methodology | Understand different sampling methodologies and an ability to select and apply the appropriate technique given constraints and data needs in a manner that creates the most appropriately representative sample (e.g., simple random, stratified, convenience, quota sampling, etc.). | ||
| Modeling Techniques (for variable relationships) | Understand the theoretical underpinnings of moderation, mediation, and clustering. The ability to recognize situations where a third variable might be influencing the relationship between other variables. Creating interaction terms in models and interpreting interaction effects. Choosing appropriate statistical tests for the appropriate variable relationships (e.g., regression, structural equation modeling, factor analysis). | ||
Bonus Research Skills
Research goes hand-in-hand with many of the data consumer and data translator skills we talked about in part 2. So it is worth reiterating the importance of critical thinking to support your ability to analyze information, identify patterns, and ask insightful questions. And, never has a skill been more important to research than the ability to be a data translator – this is the most critical skill to be able to effectively transform business problems into people analytics questions that can then be researched and tested using your data doer skills to analyze the results of your research findings. It is also important to emphasize communication so that you are able to present your research findings in a clear, concise, and compelling way to others. Research is also a great area to practice being a data consumer by conducting what are called literature reviews. In a literature review you read and review past studies and findings on the topic(s) you are researching and critically evaluate the thoughts, theories and findings of others to provide a solid foundation for your understanding and the context of your study. Refer back to the self-assessments you did in part 2 to see if you feel differently about any of these skills now.