Trying to Build Better Workers with Social Analytics


Shah, Rawn

April 22, 2013

The New York Times published an article “Big Data, Trying to Build Better Workers” last week that focused on what is described as a ‘new’ area of work-force science. It’s a nice to say so, but the reality is that this is fresh lipstick on the continuing drive to understand workplace attitudes, psychology and sociology. Calling it new is a nice way to draw attention to a key way of improving our organizations, but it doesn’t need to be. The difference now is that better data analysis tools, integrated with employee process execution data, is associated with the currently vogue Big Data analytics.

The article takes an example of detecting ‘honesty’ as a personality attribute that one company found correlated to 20-30% longer stay in the company than those that didn’t score highly in their test. The challenge here is based on a simple scenario (e.g., ‘Do you know how to cut-and-paste?’) that is testable on an objective level. It is much more complicated to create tests that relate to the more complex moral scenarios of that employees typically face, especially when the action to be tested creates subjective results, even if simple.

What is the real innovation here? It is not the ability to create and send out personality questionnaires and surveys. Building the right survey and asking the right questions is a significant challenge in itself, but this has been done for quite a while.

It also isn’t about looking at the behavioral data of how people send messages, when and during what process step. That too has been collected in log files and analyzed by itself by IT departments for ages.

The innovation here is about bringing it all together, this large volume, multivariate data that can be associated to particular psychographic profiles, or even individuals. It is the integration of the data first, and then new models for finding the needle in the haystack of data.

Simply said, companies are now putting more stock in not just fielding surveys asking personality questions, but they are cross-referencing it to enterprise processes, as well as the people in those processes.

It comes back with showing particular correlations to process improvement gains, and that in the social science sphere is where it may get closest to evidence. You have to look deeper into these systems. Correlation is not causality as always, but it is good evidence that it can happen.

This is where you need help. It is a technical and a business problem in one. One technical challenge lies in data integration and master data management. Another challenge lies in building employee profile and segmentation systems that can be referenced and maintain privacy while blinding identify information when required. ERP software and database companies like IBM, SAP and Oracle are key to delivering these capabilities. The business problem comes in the form of what questions, factors and characteristics to look for, and how to ask these questions. This is where the specific domain knowledge of Kenexa (an IBM company), SuccessFactors (an SAP company), Deloitte, or Vovici, or the many independent HR consultants focused on employee performance analysis. The magic happens when the two knowledge domains come together.

If you notice, this gets down into the weeds. We are no longer talking about large groups of people that fit into known categories, but micro-segmentation into smaller and smaller groups of people that are dynamically identified from a mixture of attitude and behavior. This is where the field of Social Analytics as applied to the domain of HR comes in because it is no longer just about discrete individual attitudes but peer group and social interactions. [Take a look at my ebook as a quick primer on the subject].

The big picture people often miss out is that this in concept is no different than doing detailed analysis on customer behavior over their lifecycle. This is easier in some ways since you can more easily reach the data, for a longer period of time, and in greater detail that can be mapped to individuals (e.g., employees), than you typically can get from the limited transactions with an individual customer.

It is also more complicated because there tend more databases with employee and process information across more departments and business functions than with customer information. Plus, there are more issues in accessing this information while trying to maintain privacy of employees. It can be done on a practical level.

Yet, most companies are very willing to invest towards better ways to understand customers, and less so into understanding their employees. This is not an either-or choice, but about improving productivity and possible also improving the customer experience as well. Let’s not forget that HR and people management is just as much as creating innovation and opportunity.


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