Data management ensures the effective management, organization, and security of data, particularly when dealing with sensitive information such as people data. Because data management covers so many aspects, there are quite a number of skills you will want to consider building in your people analytics career. Some are skills you will use only in certain types of roles in your career, while others are critical for all people analytics professionals. The self-discovery assessment tables below are intended to give you a starting list to help you identify the data management skills most critical for you.

How to use these tables:

1. 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.
2. 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. 

Data Management Skills

Defining, Designing, and Collecting: Before you can analyze data you have to actually have data. That’s where these critical data management skills come in. Depending on the type of people analytics roles or activities you take on in your career you may or may not need a deep level of skills in these areas. For example, if you will be doing research or trying to assess things that haven’t been measured before, you’re going to need a deep level of skill in each of the following. However, if you are in a role where you will only use data that has already been defined, created, and collected by someone else, you may only need to be at the “Aware” or “Learner” level for the skills in this section.

Secure Data Storage: This area focuses on using the right tools and techniques to ensure data privacy, prevent unauthorized access, and maintain compliance with regulations. The depth of your skills in this area will depend on your specific role. For instance, if you’re responsible for managing a large people analytics platform or HR information system, you’ll need a “Skilled” or greater level of understanding of database systems and data security best practices. However, if you primarily access pre-processed data for analysis, you might focus more on gaining a general understanding of the storage systems and security measures already in place. Given the nature of the data involved in people analytics, skills regarding security, privacy, and compliance will be critical for all roles.

Data Transformation and Cleaning: All people analytics roles, even those working with data that is provided by someone else, will require at least some data cleaning, integration, and validation skills. This might involve tasks like formatting inconsistencies, resolving duplicate entries, merging data sets, or just ensuring that the right data is being used to suit the purpose of the analyses.

If you are in a role where you will work directly with a system to retrieve data you may need stronger skills in extraction and transformation than if you are in a role where data is provided to you ready for use. Many people in the roles that retrieve the data are also asked to prepare the data for use by other people and so a level of “Skilled” or higher level may be required for all the skills in this section. 

People Data Governance & Ethics Skills

People data governance and ethics would more accurately be considered non-technical or leadership skills. However, for the sake of continuity we will address them here as they are the crucial foundation upon which all data management skills are built.

Data Governance: Data governance establishes the rules for managing people analytics data. It defines who can access and use the data, how it should be collected and stored, how it should be used, and what quality standards must be met. All roles will require this skill. In some roles, you might be heavily involved in designing and implementing data governance principles and policies. For others, you might be responsible for following and upholding those policies and principles using the data management skills listed above.

Data Ethics: Ethics may not be a specific skill, but rather something that should be woven through everything we do in people analytics. I mention it here because ethics should be integrated into the full data management strategy which touches every step of the people analytics process. Ethical considerations shape how data is collected, ensuring it’s done with consent and only gathers what’s truly necessary. People analytics often deals with sensitive employee information so ethical practices are necessary to ensure data security protects employee privacy and prevents unauthorized access. Data analysis can lead to biased results if not done ethically but when designed ethically they can help identify and address potential biases in the data to avoid unfair or discriminatory outcomes. Understanding and mitigating bias helps ensure fair and accurate insights from people analytics. Data governance frameworks that prioritize ethical principles can build a strong foundation for responsible data use. Beyond that they also help to build trust with employees. Employees are more likely to participate and provide accurate data when they know it’s being handled ethically. Data ethics is an essential skill that complements and strengthens all other aspects of data management for people analytics.

Self-Discovery:

Where are you today? Take a moment to assess your skill level in these areas and consider actions you will take to improve in the future. Circle the level where you believe your skills are today.

Bonus activity – Consider what level you would like to reach on each skill in the future and identify steps for practicing and building the skill.

Bonus Data Management Skill – Business Acumen

Data management skills go hand-in-hand with those data translator skills we talked about in part 1. So it is worth reiterating the importance of your business acumen skills. After all, you can’t measure or analyze something if you don’t know anything about it. You’ll need to translate business questions to data questions and data questions to measurement methods if you want to successfully align your people analytics to outcomes. And, you can’t possibly clean and prepare data for analysis if you don’t know what “good” data is supposed to look like. Spotting issues and knowing what is required of the data isn’t something you can do with just statistics or data manipulation skills. Only when you know about the organization and your people analytics goals will you have enough knowledge to design data management practices and identify certain issues. Refer back to the self-assessment you did in part 1 titled, “Self-Discovery: People Analytics Translator Skills” to see if you feel differently about any of these skills now.