27 The Foundation of People Analytics

Data analysis and visualization are the rockstars of people analytics. They are the flashy techniques that get all the attention on stage but are useless on their own. Imagine spending hours analyzing your data, finding something really neat, getting your visualization just right, and then discovering that everything is just… wrong. Sadly, this happens often and when it does it is usually because the analysis was undertaken without first ensuring sound data management or because considerations of validity, reliability, or relevancy were ignored. As the saying goes: “garbage in, garbage out.”

Earlier I used an analogy about baking a cake, let’s continue with that here. Your analysis skills are like baking skills. Those skills might involve using all the latest kitchen gadgets and appliances. Or they may include skills in techniques, like knowing how to beat the eggs, sift the flour, whip the cream, and fold the ingredients like a pastry chef. Your data visualization skills then would be like those of a professional cake decorator – maybe you’re even so good you could be on one of those reality TV cake contest shows. But, even if those skills are all great if your ingredients (data) are rotten, that cake is going to be disgusting.

This is why data governance, data management, and research skills are critical in people analytics. Data management ensures all the data needed is there, that it is free from errors, and that it is appropriate and accessible for use. In our baking analogy, data management might include making sure the right ingredients are gathered and stored appropriately in the kitchen, it would also include making sure those ingredients are fresh and of good quality. Effective data management ensures quality and integrity throughout the process, from collection to analysis to reporting and beyond. Data governance includes data management but is a bit broader in scope. It sets the overall framework of policies and procedures for how things should be done, including how data should be managed. In our example, it keeps everyone who eats your cake safe by following proper health, sanitation, and safety processes. 

Research methods help ensure validity and reliability. They also help create new data in appropriate and useable ways. Research methods give you a process for knowing if the data you are creating or analyzing and the outcomes of your analysis reflect what you were trying to understand. In our analogy data analysis and visualization were the skills used to put all the cake ingredients together and bake it and data management and governance were the skills used to ensure the cake was made with the right ingredients and processes. Then we can think of research like ways of coming up with new recipes, doing taste tests, or the results from reviews by food critics and customers. Research method skills let you test whether your cake is any good. Because let’s face it, even if you correctly make a delicious and beautiful lemon chiffon cake using all the best ingredients and following that recipe perfectly, you are still going to upset the person who asked you for a double chocolate fudge cake.

I know you may need a break to go eat some cake now, but after you do, come back and we’ll talk more about these great foundational people analytical skills.