Introduction
Dealing with bias in the workplace is hard. Bias can take many forms and fall into conscious and unconscious bias. Unconscious bias is hidden inclinations or preferences you may not even be aware of. Awareness of these biases is the first step in tackling workplace prejudice. Once we know our biases we can train and put in place systems to mitigate bias and discrimination in the workplace.1, 2, 3, 4, 5
Understanding bias in the workplace is key as it allows us to identify and address our own biases. This allows for a more diverse and inclusive workplace. Both employers and employees need to get the impact of bias in the workplace. For employees, awareness of bias in the workplace means recognition of personal discrimination and being able to spot when others may be facing discrimination. Bias in the workplace brings many risks including high turnover, stifling of ideas, legal issues, negative culture and lack of diversity of people and ideas.6, 7, 8, 9
Additionally, recognizing workplace bias empowers individuals to stand up against injustice.
Confirmation Bias: This is the inclination to look for facts that support a certain attitude or opinion that one already holds.
Similarity-Attraction Bias: The inclination to give special treatment to people in the same group.
Conformity Bias: Taking decisions which are in line with the group concepts or thinking.
Affinity Bias: The tendency to seek the company of people with whom they already share something in common.
Contrast Effect: Hypocrisy in comparing candidates with other candidates.
Halo and Horns Effect: Replacing other impressions people have about a certain person with a positive or negative one they have towards that person.
Attribution Bias: All the credit or blame, which people award to an individual for their achievements or setbacks, based on their perceived character flaws or incompetence.
Appearance Biases: Judging people, assessing their worth, or setting standards of beauty, for height or weight.
Intuition Bias: When it comes to assessing the character of a particular person, relying largely on third-party opinions and other hard-core facts is still subordinate to trusting one’s own feelings and intuitions in that regard.
Research Methodology approach
In this research the data that is used is Qualitative data, which can be judgments and observations. However, to improve the dissemination of the research, the case study is included. 10, 11, 12, 13
Prominent Case Studies
In a legal case that was launched in the US, Google was singled out for Discrimination in the course of its hiring process and the discrimination was well articulated along gender and race. The Department of Labor accused Google of discriminative hiring practices and so, Google was made to compensate to the tune of $3. In August, 2007, they agreed to pay 8 million for back pay and interest for the case.
There is another one that is citing Amazon the American Company and the Equal Employment Opportunity Commission (EEOC). Workplace discrimination was performed by Amazon to women and non-White candidates. The EEOC decided that discrimination in hiring was against Amazon’s policies; Amazon was left with having to pay $1. ,563,000 was for back pay and interest out of which 1 million was paid to the employees of the banks. 1 million is interest.
In a case in the USA, Sony offered employment discrimination on the ground of age to its employees. Some six years ago, EEOC accused Sony of discriminating in employment and Sony was compelled to pay $1. During the process of liquidation it was calculated that the companies owed the employees 4 million dollars as back pay and interest.
Microsoft also joined other companies whereby there was bias in employment in USA. Thus, females were locked out from promotion in their jobs. It was due to the EEOC that it was revealed that Microsoft was engaging in discrimination to hire and even after a settlement, the company was found to have violated the norms by which it ought to have operated and as a result, was taken through a process where it was required to pay $2. 2 Million in back pay and the interest which has accumulated on such pay.
In the case of Coca-Cola and the Equal Employment Opportunity Commission (EEC) USA, Coca cola company was sued on allege Racism in staffing; particularly affecting the staffing of the minority candidates. It was after an investigation by the EEOC that bias was established in the hiring process of the employees, and a settlement was arrived at whereby Coca-Cola was to pay $1. Requested $ 4 million as arrears and interest.
HP was into the similar kind of case, HP v. Equal Employment Opportunity Commission (USA), in which HP was charged of discriminating against the elder applicants and in that way was charged of age discrimination in the recruitment process. The EEOC after investigation established that HP had been prejudice in its hiring process. Pursuant to the said settlement, HP was obliged to pay $1. and $1 million in back wages plus interest.
Hindustan Unilever (HUL): favouritism which is rebuked in most organisations by involving the treatment of the workers by the employer in line with their skin colour preferences. HUL was under pressure in 2020 over some of its skin lightening products. The company recently decided to change the name of its ‘Fair & Lovely’ cream to reflect the prejudice that such a product reinforced color bias and that only those with fair skin were presentable. It was driven by protests against racism and the marketing of rules of oppression of the Black women and girls’ body.
Torrent Pharmaceuticals: Charges of sex discriminative implications. In fiscal year 2018–19, a sexual harassment case was lodged against Torrent Pharmaceuticals by a former employee claiming gender discrimination. Moreover based the complainants’ statement, she was let go after the complained company upon repotting she went on maternity leave. This case has an essence of analysing the issue of fair treatment if not protection of pregnant employees.
Uber had been in a fix in the public domain in 2017 when it was accused of sexual harassment and discrimination. Further internal investigation uncovered significant organisational dysfunction arising from a racist HR system. This misconduct led to changes into many of the company’s Human Resource policies and management philosophies, and its effects demonstrate the implications of reputational and operational reputations when a business and its employee relations are poorly managed.14, 15
Suggestions and actions for transparent HR practices
It is rather obvious that bias in the human resources department should not be a part of the working environment. Here are some suggested measures to address and reduce HR bias:
Here are some suggested measures to address and reduce HR bias:
Pay for Bias Training and Awareness Programs
Unconscious Bias Training: Seminars or meetings that may feature presentations focused on prejudice employees, particularly those in the human resources department, have.
Diversity and Inclusion Education: Curricula that centre on the concept and the ways to implement diversity and how to support it.
Standardize HR Processes
Structured Interviews: Standardized interview questions and processes should be set in order to minimize the discrepancies that rise from the evaluation of different persons.
Blind Recruitment: Do not use the applications or CVs of candidates during the shortlisting process, this is avoiding racism, sexism or tribalism against the applicants.
Objective Performance Metrics: Use objective performance indicators for performance appraisals and promotions since most of the assessments are subjective.
Diverse Hiring Panels
Mixed-Gender and Multicultural Panels: This is due to likely being better to have a variety of people in the hiring committees in order to avoid tendencies to produce groupthink.
Inclusive Decision-Making: Make sure that decision making teams are in some cases comprise of different parameters in other to curb cases of bias making.
The propagated use of Technology and AI should be proper use or ethical use of technology and artificial intelligence.
AI-Powered Recruitment Tools: Leverage AI and machine learning algorithms to shortlist candidates according to the skills and experience profile but ‘check’ the filters periodically to avoid the reinforcement of prejudice.
Analytics for Bias Detection: Use of HR analytics thus to consist of monitoring and tracking of bias trends in those key areas of recruitment, promotions, and compensation.
Improve a Culture for Acceptance of Responsibilities
Bias Reporting Mechanisms: Establish a secure line of reporting for employees to report any incidence of bias or discrimination and free them from any form of revengeful action.
Transparent Decision-Making: Popular: Make the human resource decisions like recruitment, promotions, and compensation as open as possible to encourage organization’s members to trust the HR department.
Diverse Talent Pipeline
Outreach and Recruitment Initiatives: Search for candidates from the different hard-to-fill positions by cultivating partnerships with diverse educational institutions/hiring companies.
Mentorship Programs: Implement a successful mentorship and sponsorship programs because it encourages movement up the corporate ladder for people of colour.
Legal Compliance and Best Practice
Adherence to Anti-Discrimination Laws: Make sure that everything that has to do with Human Resources is free from discrimination in accordance with the laws within the country as well as the internationally.
Benchmarking Best Practices: Regularly compare company’s performance with the best practices in all aspects of DE&I.
Leadership Commitment
Executive Endorsement: Secure organisational commitment to support both the identification of DEI objectives and the advancement of those objectives.
Role Modeling: Employers and managers must realize that they are responsible to be the role models in the organization for creating DEI.
Thus, every organization should consider the use of these measures that can significantly decrease the level of HR bias per se achieving the aim of having a fair, diverse and inclusive workplace.
Conclusion
Bias, however, may make a team more cohesive. Personal biases in selecting employees can lead to homogeneous thinking which stymies innovation and creative problem solving. This also facilitates the establishment of better teams and helps members feel comfortable. It cultivates loyalty. People are absent from work fewer times and fewer staff quit jobs. Hiring is made faster through bias by making use of a strength rather than weakness as preferences sometimes do not mean choosing less able persons but instead pointing out those who are better from among several candidates.
A similar team would perhaps understand each other better because they have similar backgrounds and views, this makes talking easier because there is no confusion and fighting tends to become less. The team becomes stronger in that there are fewer cases of backbiting and more loyalty comes from the teammates due to the fact that they think alike about most things.
