Let’s not overcomplicate People Analytics

About two years ago, I started being really interested in People Analytics. Prior to that, I was working in a role that involved a little HR Analytics. That was the first place where I tasted this area and I wanted to learn more about it.

I send an email every Sunday, once I publish my weekly article. I also share some good content. Mostly HR related.

When googling People Analytics, you get a lot of results that can discourage you. HR Metrics, Attrition, Cost of Hire, Time to Hire, descriptive, predictive, People Analytics vs HR Analytics, Tableau, BI, Business Intelligence, New Hire-Offer-Onboarding, hire-to-retire flow, HRIS, HRMS, HRM, HCM, Human Capital Management, say no to Human Capital Analytics, linear regression model, forecast, Opex, Capex, report, percentages, date, numbers, primary key, Excel.

But other than that, you only need to know this terminology only to understand what you are asked to do. In the end, everything is an Excel file at the end of the process. That you will send by email or save it on a shared folder in the cloud, where others can access it. An Excel file. 80% of HR processes have the same result: an Excel file.

Why is this important? Because Excel is the most used tool in any HR role and everyone should be proficient at working with it.

Extract raw data from your HR Database and start practicing. Extract in a CSV file. Format it Arial 10. Bold the header. Make it look like a table – add table lines. Remove grid. Freeze the top row. Delete not relevant columns (confirm the header of the report), filter, delete rows, copy-paste values. name it, save. 80% of my HR Analytics job was about this. If you add to this skill set vlookup, text to columns, ctrl+f1, date vs number vs text format, conditional formatting, data validation and knowing what a macro is, you can move anytime to a People Analytics role and you’ll be a top performer.

Let’s not complicate.

People analytics is easier than it sounds. I don’t understand why some people tend to over-complicate it. In my opinion, there are three segments where you should focus your learning/skills development:

  1. Excel – it’s probably the most used tool in any Data role and this applies to HR, too. The outcome of any analysis is an Excel file, containing descriptive or predictive information in an easy to understand way. Mostly descriptive. Most HR systems and analytics tools are primary key based (a unique identifier for employees) and you should be able to gather data about employees from various sources: HR Core, ATS, Performance Management systems etc. Topically, this is done using look up functions, mostly vlookup. So, make sure you understand the mechanics of vlookup: lookup value types (text, numerical), table array (fixed and dynamic arrays), column index (learn how columns function works) and the range lookup (what happens if you change true to false and vice-versa). Once you consolidate the data using lookup functions in one sheet, learn how to generate pivot tables from it and how to change from sum to count the grant totals. Some clients (the ones for whom you perform these analyses) want just simple counts of some elements -> learn how the Count, CountA and CountIF functions work. At this point, you will be able to perform probably 80% of your analytics request. To increase this percent, move to Conditional Formatting, Text to Columns, Data Validation. If you want to increase your turn around time, learn the mechanics of Macros and see if and how can you use it on your recurrent tasks. Excel is a very powerful tool if it’s used in the correct way. You might feel overwhelmed at the beginning, give it time. Practice is the king.

  2. HR Metrics – Cost of Hire, Time of Hire, Attrition/Turnover, Headcount, Overtime percentage, Tenure, New hire fail rate and so on. Get familiar with HR terminology. . Again, this comes with experience and point number 3.

  3. Business Analysis – more specific, requirements gathering. Learn what questions to ask to the end-user (the one who you are delivering your outcome) to make sure that you are on the same page. You should be able to asses if you can deliver the data she/he needs. Make sure you agree on the header of the report you will be working on, on the value types for specific columns (date vs tenure, percentage vs amount). Try to understand how the end-user is using this data -> maybe there is an easy way to deliver the same set of data in less time or with less effort.

People analytics is a combination of Data Analysis and Communication. The most important advice I can give to you is to be patient, to optimize your Excel workflow and to make sure that you understand the requirements of any report/analysis you are working on.

PS: Once you master the above 3 points, moving to any Business Intelligence tool it’s easy.

I send an email every Sunday, once I publish my weekly article. I also share some good content. Mostly HR related.