IN recent times, there has been no dearth of debate on why businesses must be allowed to use employee data.
Numerous strong cases have been presented by People Analytics (data-driven approach to manage people at work) thought leaders on different business models for monetising employee data hoping to leave little scope for employee disgruntlement, public criticism or increased legislation. All of these are actually very convincing. But, even then, organisations that are hoping to, or already are, mining their employee data are faced with a constant challenge of justifying their position as data stewards.
While organisations explicitly state that the employee data which the employee generates in the context of business or using the organisation’s infrastructure or identity is “owned” by the organisation, employees believe that anything that is personally identifiable to the individual cannot be subject to any analysis, no matter what it is for. Somewhere in the middle is a perspective that the insights from employee data need to be democratised, but all that follows taking employee consent after explaining “what data” and “where exactly it is going to be used”, and the use is limited only to that instance.
In my view, by keeping in mind the fundamentals of People Analytics, organisations may be able to reach a more satisfactory solution to who owns the data, who owns the learning from it and how and why, by monetising it, everyone can benefit.
To begin, organisations must ask themselves, what type of data to analyse and how to analyse it? The answer to the first question is simple: People Analytics is about employees, so employee data is its fuel. The second question is even easier to answer: Data analysis can be approached through pivot charts, consulting frameworks or technology.
As People Analytics focuses on employee data, the employee — or, more specifically, his relationship with the organisation — becomes the next logical step for understanding his relationship with his data. An employee’s relationship with an organisation has multiple components or facets. These include professional development, aligned values, community impact, value systems, etc. As the demand for employee data increases, it adds another vector into this relationship — the “employee-employer data relationship”.
To illustrate this with an analogy, there are organisations which own and take responsibility for the professional development of their people. More often than not, it is related to the culture of the land. For example, traditional organisations in countries like Japan and India (where the community culture is very strong) believe that the responsibility, growth and professional development of an employee is purely the responsibility of the employer. The presumption here is that the organisations has “adopted” the employee, it continuously learns about the employee, and, hence, knows what drives the employee and what he is good at. The expectation is that the employee also submits to this approach.
The other end of the spectrum has organisations which believe that the employee should chart their own professional growth and the organisation will support it if it is in line with its direction. The tenet here is that the employee has a symbiotic relationship of mutual value, and the expectations are well-understood on both sides (meaning you are fired if your current capability doesn’t help us). Most organisations fall somewhere in between these two extremes.
I believe the evolution of “data relationship” that employees have with the employer would also take a similar direction. It will be nuanced, but will not have a universal equilibrium, and will be specific to every organisation. So, who owns and who learns from employee data will get stated, described and deliberated at the start of every “employee-employer” relationship. By owning and managing this debate together, organisations and their employees can both enjoy the benefits of data democratisation.
Arun Sundar, a writer, TEDx speaker and business leader, is the Chief Strategy Officer at TrustSphere, the fast-growing Pioneers of Relationship Analytics. He is also the chairman of the Asia Analytics Alliance (A special interest group of Asia Cloud Computing Association) and a Board member with Asia Cloud Computing Association.