Not a month passes, when I am asked by clients about Big Data in HR. Across most South East Asian markets (and surely globally), Big Data and Workforce Analytics is a hot topic. Proactively, HR leaders are thinking about how they could apply Big Data analytics in the workforce context.
Is this the real solution HR departments need? How can HR departments espouse a more evidence-based and integrated approach to workforce analytics and planning?
I recently read a piece on LinkedIn titled “HR Data is Not Big Data – Not Yet”
. Using some simple back-of-the-envelope calculations, the author estimated that the total size of the HR dataset would be about 1-13GB (assuming 10,000 employees, 5 years of data, 100 variables and finally, using a liberal multiplying factor). That certainly doesn’t sound “big” to me. You could potentially carry that amount of data on a USB drive!
Experts say that Big Data has 5 characteristics or 5Vs:
- Volume: Refers to vast amounts of data
- Velocity: Refers to the speed with which new data is generated and the speed of movement of the data – every day, every hour, every second
- Variety: Refers to the different types of data available e.g. structured data (relational databases, financial data, talent variables like performance ratings, survey results etc.) and unstructured data (photos, videos, sensor data, social media updates etc.).
- Veracity: Refers to the messiness or trustworthiness of the data
- Value: Refers to the ability to convert data into insights of value
HR data, in its current form, fails several of these tests. It lacks the volume, velocity and sometimes veracity too. However, it has variety and is, without doubt, highly valuable to companies.
As a result, I like to think about “Small Data” and “Long Data” as terms which are more relevant and practical for a majority of the HR functions.
Companies need to start working with Small Data or structured data that already exists in HR systems to answer high-yield questions about the workforce. For instance, connecting data from employee surveys, customer surveys, financial results and other HRIS data to show the linkages or identifying what factors differentiate high performers.
Similarly, they could use Long Data or workforce data over 5-10 years to show trends in workforce productivity, investment, supply etc. over time. For instance, looking at how the performance of high-potential talent changes as they are rotated across business units / functions or how changes in employee engagement levels correlate with changing business performance, employee attrition etc.
I recently read Work Rules
, the book by Laszlo Bock, Google’s SVP of People Operations. And it is full of brilliant examples of how Google applies such analytical techniques to inform all their HR decisions. It’s not necessarily Big Data, but it’s a highly effective approach which emphasizes focus, framing the right question and using data to make decisions. (P.S. I highly recommend the book).
So, my simple advice is – do not get caught up (and overwhelmed) by the term Big Data. Subtract the word “Big” and focus on converting Data into Insights.