Human Resource Department since the time it was known as Personal Department has access to the information related to employees. Historically, this data has been used for diverse purposes, such as to preserve business records, to meet legal and regulatory obligations,and/or as evidence in litigation.Initially the information was confined to employee’s name, his/her address, qualification, marital status etc. to name a few. With time, many other information was acquired by HR Department. The employee data available with the HR Department many a time has raised concern about the ethical use of the data. The data from the interview, the data of the employees who have left the organization and also those who are working and all other associated data available with the HR Department may be misused, leading to a great concern.
With the event of Human resource analytics (HR analytics), the concern has further broadened. HR Analytics has been defined as-
“the area in the field of analytics that deals with people data and applying analytical process to the human capital data within the organization to improve employee performance and improving employee retention.”
There has been imbalance between what data can be used what cannot be used. With Predictive Analytics, many other data other than what was available with the HR Department has been accessed for example, text contained in company documents, email, instant messaging, and social media with an intention to visualizing employee interactions, mapping domain expertise, replaying past events, tracking employee sentiment, and providing insights into all human activity across the organization and to devise strategies for retention, training performance improvement, engagement to name a few. In context of the Ethical dilemma in HR Analytics,
let’s look at some of the examples what can be done using HR Analytics (Ref: Guenole, Nigel, Sheri Feinzig, and David Green. 2018. ‘The Grey Area’. IBM).
- How long the employee may be associated with organization can be identified using several data available.
- Analyze employee’s absence record to improve well-being programs and link Employee Assistance Program (EAP).
- Social network analysis and text analysis of work email traffic (who contacts whom, what is said) allows more accurate estimation of employee engagement using Natural Language Processing and Deep Learning.
- Statistical analysis identify that certain employees are chronically disengaged and identify the reason for disengagement.
- Data collected from personal development programs to incorporate in decision-making about a high potential program.
- New technology permits identification of employees who are making negative comments about their employer on public websites.
- Integrate data sets from different systems such as employee opinion surveys and performance management for strategic insight that will help with workforce planning.
The question that may strike in the mind in the first instance is “is this possible?” The answer to this question is yes. The next question comes up “Should we do this? or Can we do this” This question itself raises an imbalance as the employer would like to have the information at the same time it might be infringement to privacy of the employee concerned.
Let’s take an example to further elaborate on the same. A sales manager of a major services corporation, for example, may want to know which employees have the strongest relationships with executives at a client prior to visiting them and who best understands the subject of the meeting. Using various HR Analytics techniques an outline of network of relationships among employees, customers, vendors, and others, identifying subject matter experts can be made using employee data. From an organization’s perspective, the information is very vital but ethical conflicts can arise, say when the analysis identifies sensitive personal relationships that perhaps should not have existed on corporate servers in the first place.
On the contrary HR Analytics helps to answer some concern which has been always been existing as it’s a data driven and all information is available on demand was to why a particular decision was taken.
|Favouritism in hiring, training and promotiondecisions||Low trust in senior managers|
|Inconsistency in disciplinary measures||Lying to employees|
|Failure to maintain confidentiality of customers or employees||Pressure to compromise standards|
|Potential discrimination in appraisals and in allocating pay/non-pay reward||Failure to discipline or punish bad or abusive behavior|
|Maintaining a safe and healthy work environment||Retaliation against those reporting misconduct|
|Subcontractor conduct within outsourcing and off-shoring||Bad behavior by managers setting a poor example for everyone else|
|Harassment and bullying||Corruption|
Source: IES, 2015 (adapted from UK and US surveys 1991/2013)
There are both pros and cons in the usage of data in HR Analytics in reference to the ethical and legal issues. Indeed, HR analytics practitioners already advocate involving legal advisors from the outset of HR analytics projects. With the General Data Protection Regulation (GDPR) by European Union,which came into force on 28th May 2018 many questions were answered and the balance has shifted further towards employees. Under GDPR, an employee has the right to know which data is available with the employer and what it is being used for.
The Way Forward:
The approaches to ethical dilemmas would alsoideally be documented in company data usage policies. In manycases, however, decisions about the appropriatenessof analyses are grey, not black and white. Legislationand policies might not cover new technologies andapplications, for example.In cases where the legislation is silent, HR analyticsprofessionals might make decisions based on therisk of harm to workers or the firm, for example,asking how will it appear if there is an investigation.
The problem with this approach is that differentpeople have different interpretations of risk andharm, especially when those evaluating the risk andthose likely to experience damage due to the risk aredifferent people.
International Standard Organization technical committee released a document ISO/TC 260 – Human resource management having some recommendations under the section N46 – HR Metrics Final Recommendations wherein the data related to HR has been taken care and making up various matrices. ISO 30414, which covers the area of Knowledge management, also provides insights into various risk, whichcan be considered while designing the HR Analytics project.
Reference- Guenole, Nigel, Sheri Feinzig, and David Green. 2018. ‘The Grey Area’. IBM (https://www.ibm.com/watson/talent/talent-management-institute/ethical-dilemmas-hr-analytics/hrethical-dilemmas.pdf). Jacobs, Katie. 2017. ‘The Ethics of Gathering Employee Data’. HR Magazine(http://www.hrmagazine.co.uk/article-details/the-ethics-of-gathering-employee-data). Leong, Kon. 2017. ‘Is Your Company Using Employee Data Ethically?’. Harvard Business Review (https://hbr.org/2017/03/is-your-company-using-employee-data-ethically) https://eugdpr.org/http://www.e-rh.org/documents/ISO/ISO-TC260_N0046_N46_-_HR_Metrics_Final_Recommendations%5B1%5D.pdf