29 Explore & Engage: People Data Management and Governance

Here are some strategies to help you integrate more data management and governance into your skill development journey:

1. Read about data policies, regulations, standards, and management practices. To uphold good data management practices you have to be aware of them. In “Step 2. Build Your Non-Technical Skills” we talked about the importance of continually consuming information as part of being a data consumer. So, be sure to include articles and resources that cover data governance examples and data management practices. Stay up to date on data privacy and security laws, regulations, and standards so you know how to follow them appropriately before beginning any analytics project.
   • Personal note: I used to find reading policies and regulations so boring until I realized how important they were. Now you’ll find videos on my YouTube channel where you can see just how weirdly excited I am when there is some new standard, law, or regulation related to data. I even became the global convener of the HRM Safe Data Handling Standard for the International Organization for Standardization (ISO 30439). For me, reading laws, regulations, and standards was a lot like learning statistics. At first, it was super awkward and everything seemed like gibberish, but once you get the hang of it you realize how powerful it is to possess the knowledge.
2. Include data management professionals in your community. Build connections with the individuals who own data management for the systems you use. They can tell you about the processes and measures in place to manage data. There are people analytics experts with depth in data management but I encourage you to also seek out specialized data management professionals from outside the people analytics field to learn from as well.
3. Include subject matter experts in your data management efforts. It’s not just data management professionals who can help you in your data management efforts. Those who are experts in the topic or subject matter that your data is focused on should be included as well. They will often know how to define and measure the things you are trying to analyze with more nuance and understanding. They will notice data quality issues no one else can. And, they can provide additional context to explain and interpret the outcomes of your analyses. For example, if you are doing an analysis that includes data about employee salaries and you are not a compensation professional, invite one to the conversation. Your subject matter experts don’t actually need to have any data or analytics experience to identify issues – they’ll know when something seems inaccurate or out of place if you work alongside them.
4. Start with one data set and work out from there. As you saw in our example, there are so many pieces to the data management puzzle. I recommend working on building your skills by finding one data example that you can work through from start to finish – like I did in our engagement survey example in the last section. Pick a topic and type of data that you are most interested in or one that you might work with. Some questions you can seek answers to are: How is the data measured and defined? What is the collection method? How does the technology or collection method work? How is it stored? For how long? Who can access it? How can it be extracted? In what kind of format? What kind of transformation or cleaning needs to be done? How can it be assessed for accuracy, validity, and reliability? What processes and policies are in place for how it can be used and reported on? What privacy and security controls are in place? Finding answers to each of these questions will build your data management skills.