demographic diversity in the workplace and its effect on...

Anne Onsarigo and Thomas Katna Ngni, International Journal of Research in Engineering, IT and Social

Sciences, ISSN 2250-0588, Impact Factor: 6.565, Volume 08 Issue 08, August 2018, Page 81-96

http://indusedu.org Page 81

This work is licensed under a Creative Commons Attribution 4.0 International License

Demographic Diversity in the Workplace

and Its Effect on Employee Performance: A

Case of IBM Kenya

Anne Onsarigo1 and Thomas Katua Ngui

2

1(The Catholic University of Eastern Africa, Kenya)

2(Senior Lecturer, The Management University of Africa, Kenya)

Abstract: The need for this study stemmed from the desire by organizations to embrace workforce diversity in a

bid to enhance employee performance. The main purpose was to establish the effects of workforce diversity on

employee performance in Kenya with focus on the technology industry. The objective of the study was to identify

the diversity attributes that exist at IBM Kenya, and establish their effect on employee performance. This study’s

theoretical background was based on three theories, namely reinforcement theory, equity theory, and

organizational citizenship behavior (OCB) theory. The study adopted a descriptive research design. The study

targeted employees of IBM Kenya with focus on employees working at the IBM headquarter offices in Nairobi.

The sample size was 105 employees. Primary data was collected using structured questionnaires. The

researcher used drop and pick method in administering the questionnaire. Data analysis was done using

computer analysis software, SPSS version 23.0. Both descriptive and inferential statistics were carried out and

the findings were provided using distribution tables. From the findings, employees of IBM Kenya strongly

agreed that there was gender balance in the organization, which motivated them to remain committed at work,

they also agreed that the policies that existed in the organization, giving equal opportunities for growth and

development regardless of gender, age or educational background improved employee performance over time.

Further findings revealed that having different age groups in senior positions encourages and motivates

employees; good working relationships between employees of different age groups improved employee

performance, and involvement of members of different age groups in solving problems and in decision making

enhanced employee performance. Additionally, working with employees with different educational levels or

backgrounds has improved their performance. The study concluded that workforce diversity practiced by

technology companies highly influenced performance of employees leading to overall organizational

performance. The study then recommended that the government in collaboration with other stakeholders in the

technology industry should ensure that there are effective workforce diversity policy guidelines in a bid to

enhance employee performance which highly contributes to organizational performance and growth.

Keywords: Workforce Diversity and Employee Performance

I. INTRODUCTION

Workforce diversity

According to Abdel (2012) workforce diversity is a multi-faceted concept that will continue to evolve

as more industries move towards both working in and recruiting employees from a global market place.

Workforce diversity means creating an inclusive environment in the workplace that accepts each individual's

differences, embraces their strengths and provides opportunities for all staff to achieve their full potential.

Diversity is really all the attributes that define a person, these include but are not limited to: age, ethnicity,

ancestry, gender, physical abilities/qualities, race, sexual orientation, educational background, geographic

location, income, marital status, military experience, religious beliefs, parental status, and work experience. A

common misconception about diversity is that only certain persons or groups are included under its umbrella,

when in fact, exactly the opposite is true. Workforce diversity is a multi-faceted concept that will continue to

evolve as more industries move towards both working in and recruiting employees from a global market place

(Abdel, 2012). Organizations that promote and achieve a diverse workplace will attract and retain quality

employees and increase customer loyalty (Al Gore, 2000). For public organizations, diversity also translates

into effective delivery of essential services to communities with diverse needs. Leaders and managers within

organizations are primarily responsible for the success of diversity policies because they must ensure that the

policies are effective. The leaders and managers within organizations must incorporate diversity policies into

every aspect of the organization’s functions and purpose (Al Gore, 2000).

Employee performance is a means of carrying out actions efficiently and effectively by the employees

to achieve the predetermined objectives of an organization (Baldwin, 2008). It is normally looked at in terms of

outcomes or employee’s output against the set individual objectives populated from the company objectives

(Armstrong, 2010). However, it can also be looked at in terms of behavior (Armstrong, 2007).





According to Bates and Horton (1995) performance is a multi-dimensional contrast, the measurement

of which varies, depending on a variety of factors. They also state that it is important to determine whether the

measurement objective is to assess performance outcome or behavior. A more comprehensive view of

performance is achieved if it is defined as embracing both behavior and outcomes. Brumbrach (1988) argued

that performance means both behavior and results. Behaviors emanate from the performer and transforms

performance from abstraction to action. This therefore means that when one is managing performance of teams

and individuals, both input (behavior) and output (results) should be considered. It has become increasingly

evident that organization’s must incorporate diversity into their business, in order for them to create better

innovations and achieves better financial outcomes.

International Business Machines, Kenya

The International Business Machines Corporation is an American multinational technology company

headquartered in Armonk, New York, United States, with operations in over 170 countries. The company began

in 1911 as the Computing-Tabulating-Recording Company (CTR) and was renamed "International Business

Machines" in 1924. IBM manufactures and markets computer hardware, middleware and software, and provides

hosting and consulting services in areas ranging from mainframe computers to nanotechnology. IBM is also a

major research organization, holding the record for most U.S. patents generated by a business (as of 2018) for

25 consecutive years.

Nicknamed Big Blue, IBM is one of 30 companies included in the Dow Jones Industrial Average and

one of the world's largest employers, with (as of 2016) nearly 380,000 employees. Known as "IBMers" (IBM,

2018). IBM began operating directly in East Africa since 1958 and has recently transformed into a Cognitive

solutions company powered by Cloud. For over sixty years, IBM Kenya has been highly involved in

encouraging growth and development within East Africa. The Nairobi office is the operations headquarters for

IBM in the region overseeing eight countries including Tanzania, Uganda, Burundi, Rwanda, Ethiopia, South

Sudan and Djibouti. Long term partnerships within the industries such as telecommunications, government, oil

and gas sectors has allowed them to focus on providing innovative solutions which speak to the needs of local

citizens (IBM, 2015)

In 2010 under the leadership of the Chief Executive Officer (CEO),Ginni Rometty, IBM Kenya began

an expansion strategy which saw the number of employees grow from 20 in 2010 to about 300 employees in

2018 (IBM, 2018). The growth in number of employees also saw an increasingly diverse workforce been

brought on board.

According to IBM CEO, Ginni Rometty (2018), IBM thinks about diversity the way they think about

innovation — both are essential to the success of their business. When they innovate, technology becomes

smarter for clients and creates new opportunities for growth. When they incorporate diversity into their

business, they create better innovations and outcomes. IBM has embraced diversity, and it gives opportunities

for IBMers and their clients to achieve their full potential.

However, no tranformation comes without challenges. From 2013 IBM Kenya has not been meeting its

yearly targets in most of the business brands due to the ongoing transformation (IBM, 2015). During a strategy

session held in 2015, IBM Kenya committed to adopting best diversity practices in the workplace including

hiring employees of different ages, increasing the number of female employees, employing and assigning duties

based on educational qualifications, having a career development guide for all employees, rewarding ideas and

innovations of the employees regardless of their backgrounds (IBM, 2015). However, a study on the effect of

the adopted workforce diversity initiatives on employee performance in IBM Kenya has not been conducted.

Therefore this study sought to establish the existence of workforce diversity at IBM Kenya and its effect on

employee performance. This study focused on primary dimensions of diversity in the workplace specifically

three types; gender, age, and educational background.

Problem statement

Understanding the effect of workforce diversity in the workplace is key to organizational sustainability.

According to Williams and O’Reilly (1998) and Passos and Caetano (2005), it is imperatively evident from

previous studies that workplace diversity can be either detrimental or beneficial for employee performance.

According to studies that have been conducted in relation to the issue of workplace diversity, it’s become visible

that gender, age, educational background and ethnicity are the main differences that can affect employee

performance within an organization. However, there is limited research that specifically focuses on diversity in

the workplace and its effect on employee performance. This is supported by Hambrick and Mason (2012) who

noted that lack of sufficient pieces of evidence that can help organizations to link the existing relationships

between workforce diversity and employee performance is seemingly proving to be one of the most complex

issues than what is implied in most research discussions. Thus, this study sought to bridge the research by

focusing on the effect of workforce diversity on employee performance. With a focus was on gender, age, and

educational background diversity in IBM Kenya.

https://en.wikipedia.org/wiki/Computing-Tabulating-Recording_Company

https://en.wikipedia.org/wiki/Computer_hardware

https://en.wikipedia.org/wiki/Middleware

https://en.wikipedia.org/wiki/Computer_software

https://en.wikipedia.org/wiki/Internet_hosting_service

https://en.wikipedia.org/wiki/Consultant

https://en.wikipedia.org/wiki/Mainframe_computer

https://en.wikipedia.org/wiki/Nanotechnology

https://en.wikipedia.org/wiki/Patents

https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average





Research Objectives

The purpose of this study was to establish how diversity in the workplace can influence performance of

employees with focus on IBM Kenya. Specifically, the study tends to;

i) Identify the diversity attributes or practices that exist at IBM Kenya

ii) Establish the effect of gender diversity on employee performance at IBM Kenya

iii) Establish the effect of age diversity on employee performance at IBM Kenya

iv) Determine the effect of educational background diversity on employee performance at IBM Kenya.

Scope and delimitations of the study

This study focuses on the technology industry with focus on IBM Kenya, sampling its respondents

from the IBM Kenya headquarters at Hurlingham, Nairobi which is representative of IBM East Africa. The

study only focuses on diversity and employee performance. The study focused only on gender, age and

educational background of employees.

II. LITERATURE REVIEW Theoretical Review

Equity theory

Equity theory was first developed in 1963 by John Stacey Adams who was a workplace and behavioral

psychologist. The theory was regarded as one of the many theories of justice. Adams (1963) argues that

employees seek to maintain equity between what they put into a job and what they receive from it against the

perceived inputs and outcomes of others. The theory concentrates on the concept of fairness in the workplace.

Employees may thus, compare the inputs they devote to the work with the outputs they receive from the

organization. The theory further emphasizes on the need for a balance of employee inputs and outputs as

compared to others (Drafke & Kossen, 2002). Once employees feel that their inputs do not commensurate to the

treatment they receive from the organization, which means it lacks the element of fairness, they are demotivated

resulting in poor employee performance.

Equity theory suggests that employee perceptions of what they contribute to the organization, what

they get in return, and how their return-contribution ratio compares to others inside and outside the organization

determine how fair they perceive their employment relationship in terms age, gender and educational

background (Adams, 1963). External equity exists when an employer gives equal opportunities to candidates

regardless of gender, age and educational background. Internal equity exists when an employer treats all

employees equal despite their age, gender, and educational background. Equity theory brought to the attention

of the researchers that both external equity and internal equity are very important for employee performance

hence the need to determine whether IBM Kenya’s workforce diversity practices incorporated external equity.

Empirical Review

Internationally, industry practitioners as well as an increasing number of scholars, argue that diversity

is a positive factor that leads to competitive advantages for firms (Farley, 2003; Richard, 2006). Wentling and

Rivas (2013) did a study on status of diversity initiatives in selected multinational corporations in the United

States. The purpose of the study was to provide information on the status of diversity initiatives in selected

multinational corporations, to report on the dimensions of the diversity initiatives, and to interpret the dynamics

of the corporate response to workforce diversity. Eight multinational corporations headquartered in the United

States were selected for the study. Two methods of data collection were used: semi-structured face‐to‐face

interviews and document analysis. Diversity managerdirectors were asked to provide information on their

diversity initiatives; on the planning, implementation, and evaluation of diversity initiatives; and on plans for

future diversity initiatives. The study revealed that multinational corporations are planning, implementing, and

evaluating a large number and variety of diversity initiatives not only in the United States but also

internationally. Further findings of the study revealed that youngsters who are in their learning ages are always

willing to learn as many things and ideas as possible. In contrast, older people who have vast work experiences

are more mature and thus have more problem-solving skills.

However, another study ran by Mwatumwa (2015) on the effect of workforce diversity on employee

work performance with particular focus on the County Government of Mombasa (CGM). With a target

population comprised of employees of the CGM working in the County Assembly. Where data was collected

through self-administered questionnaires and was descriptively analyzed. Found that workforce diversity is a

well-accepted phenomenon at the CGM and that there was no discrimination detected resulting from ethnic,

gender or educational background. The workforce was harmonious but without expectations of high or low

performance based on an employee`s demographic background. Further findings indicated that an employee`s

ethnic, gender and educational background did not have any contributory effect on performance. From

Mwatumwa’s (2015) findings, workforce diversity does not influence employee work performance at the

County Government of Mombasa.





Conceptual framework

Figure 1. Conceptual Framework

Source: Author (2018)

Theoretical Framework

Study was guided by various theories, these include: Reinforcement Theory.

III. RESEARCH DESIGN AND METHODOLOGY Research design

This study adopted descriptive research design which, according to Chandran (2004) and Kothari

(2008), is the most appropriate for studying social phenomena due to its ability to describe a situation and

portray an event, or situation as it exists. The use of descriptive research design in this study enabled the

researcher to establish the status of IBM Kenya’s workforce diversity and describe its effect on employee

performance as it currently exists.

There are three basic types of descriptive research methods: observational, case-study, and survey

methods (Jackson, 2009). The researchers found it appropriate to apply both the case-study method and the

survey method. According to Jackson (2009), case study research involves an in-depth study of an individual or

group of individuals while in survey method participants answer questions administered through interviews or

questionnaires. In this study, the researchers used IBM Kenya as the case study and a survey was conducted

whereby participants of this research answered questions administered through questionnaires. The researchers

used the quantitative approach through closed-ended questions to acquire specific, accurate and relevant

information that ensured the objectives of this study were achieved.

Population of Study

The population of this study comprised of all employees of IBM Kenya. According to the IBM Kenya

Database (2018), the total number of employees of IBM Kenya is 320. This number was the study population of

this research. However, the researchers targeted employees working at the headquarters of IBM Kenya in

Hurlingham, Nairobi. Therefore, the target population for this study was 105 employees working at IBM

headquarters in Nairobi, Kenya.

Sample size

According to Sekaran and Bougie (2010), a sample size larger than 30 and less than 500 are

appropriate for most empirical research. In a descriptive research, 10% of the target population is adequate for a

sample size (Mugenda 2008). However, if the target population is less than 200, then census is applied

(Mugenda, 2008). A census is a complete enumeration of all the items in the target population (Kothari, 2004).

Since the target population for this study was 105, which was less than 200, the researchers applied the census

technique during data collection. Therefore, the sample size for this study was the same as the target population

– all the 105 employees working at IBM headquarters in Nairobi, Kenya as shown in Table 3.1.

Table 3.1: Target Population and Sample Size

Type of employees Target Population Sample Size

Managers 40 40

Technicians 25 25

Data Analysts 10 10

Engineers and Designers 5 5

Procurement officers 5 5

Human resource officers 5 5

Administrators 5 5

Legal Advisor 5 5

Tax Leaders 5 5

Total 105 105

Source: IBM Kenya Database (2018)

Data collection instruments

For this study, the researcher chose to use a structured questionnaire to collect primary data. This is a

questionnaire that contains closed-ended questions. Closed-ended questions are short and specific (Yang, 2008),

and in most cases they are a pre-coded set of questions to which respondents recorded their answers within





closely delineated alternatives (Upgrade & Shende, 2012). The closed-ended questions enabled the researcher to

obtain precise and specific information on diversity attributes at IBM Kenya and its effect on employee

performance. In addition, closed-ended questions eased data analysis since the responses were pre-coded.

Data collection procedures

After obtaining all the legal documents for data collection, the researchers recruited and trained three

research assistants to help in data collection. The research assistants together with the researchers made a prior

visit to the headquarters of IBM in Nairobi. They introduced themselves and explained the purpose of the study

and consulted with the administration of IBM Kenya for the possibility and appropriate time to distribute the

questionnaires to the employees and even booked appointments with those that agreed to participate in the

study. The questionnaires were self-administered hence the research assistants employed ‘drop and pick’

method of collecting data. All employees working at the headquarters of IBM in Nairobi were issued with

questionnaires to fill.

Validity and reliability

The accuracy of data to be collected largely depends on the data collection instruments in terms of their

validity and reliability. Similarly, validity is the degree to which results obtained from the analysis of the data

represent the phenomenon under study (Mugenda, 2008). Validity checks whether a questionnaire is measuring

what it purports to measure (Bryman & Cramer, 1997). The study made use of both construct validity and

content validity.

Construct validity aimed at dividing the questionnaire into several sections by ensuring that each

section assessed a specific objective and ensured that the questions asked closely tied to the conceptual

framework of the study. For content validity, the questionnaire was examined by human resource scholars to

check for relevance of the statements, objectivity, meaning and clarity. From the evaluation, the questionnaire

was adjusted accordingly before the pilot study and data collection exercise.

In this study, Cronbach's alpha coefficients (α) were used to determine the average internal consistent

(reliability) of items that were on multiple Likert scale. The higher the (α) coefficient the more reliable was the

construct. As a rule of the thumb, the acceptable range of Cronbach alpha coefficient is between 0.70 and 0.90

or higher depending on the type of research. For exploratory or descriptive research, 0.70 or more is acceptable

while 0.80 and 0.90 are acceptable for basic research and applied sciences respectively. Therefore, the

researcher conducted Cronbach alpha test using questionnaires obtained from the pilot study exercise. The

findings were as shown in Table 2.

Table 2: Cronbach’s Alpha Coefficients for Multiple Likert Scale Items

Category of multiple Likert scale items Cronbach's

Alpha

Cronbach's Alpha Based

on Standardized Items

No. of

Items

Gender diversity attributes .880 .881 7

Age diversity attributes .713 .787 8

Educational background diversity attributes .807 .858 8

Effect of gender diversity in work place on

employee performance

.757 .768 6

Effect of age diversity in workplace on employee

performance

.775 .790 5

Effect of educational background diversity on


.676 .689 8

Indicators of employee performance .957 .948 9

From Table 3, Cronbach's alpha coefficients for all variables with multiple Likert scale items was

approximately 0.7 or more, which indicates that the level of internal consistency for the items that were used in

each variable was acceptable hence the items were reliable to measure the variables of this study. This implies

that the questionnaire that was used in this study was reliable hence the findings were accurate and relevant.

Data Analysis Plan

Quantitative data that was obtained during data collection was first cleaned to remove incomplete

questionnaires and irrelevant answers. Only duly filled questionnaires were analyzed. First, the pre-coded

responses in the questionnaires were keyed into the Statistical Package for Social Science (SPSS) version 23.0.

Then the researcher analyzed the data using both descriptive and inferential statistics.

According to Kothari (2008) descriptive statistics provides for important distribution of scores by use

of statistical measures of dispersion, distribution and central tendencies. Descriptive statistics describe the basic

features of the data that was obtained from the field. It did not provide the relationship between the independent

variables (Diversity at IBM Kenya) and the dependent variable (employee performance at IBM Kenya). It only

summarized and described the study findings. Frequencies, standard deviations, percentages and means were

used in this study for descriptive statistics.

For inferential statistics, multiple regressions were carried out to determine the relationship between

each of the three independent variables and employee performance. It predicted the existence of relationships





and or influence of predictor variable on dependent variables. Essentially, multiple regression analysis is an

extension of bivariate regression analysis that allows for simultaneous investigation of the effects of two or

more independent variables to the underlying single-scaled dependent variable (Abbas, Qasar & Hameed, 2010).

The analysis was significant because it enabled the researcher to find out which independent variable had great

effect on the underlying dependent variable. In addition to that, the researchers could also assess the regression

coefficients for each independent variable to understand the relationship that exists between single dependent

variable and multiple independent variables (Zikmund, 2003). The regression formula that was used in this

study is:

Y = β0 + β1x1 + β2x2 + β3x3+ β4x4+ ε

Where: Y is the employee performance as result of workforce diversity adopted by the technology industry in

Kenya.

B0 is a constant

β1 to β4 are the coefficient of the independent variables

x1 to x4 are the independent variables where

ε is the error term

Response Rate

The study targeted a sample of 105 respondents who included employees of IBM Kenya working at the

headquarters in Nairobi. However, out of a total of 105 questionnaires that were administered, only 80 were

duly filled and returned, thus making the response rate of this study to be 76% (80) as shown in Table1.

Mugenda (2008) and Neuman (1997) noted that in a descriptive study, a response rate of 50% is adequate for

analysis and reporting, 60% is good, and 70% and above is excellent. Therefore, this study’s response rate of

76% (80) was excellent hence satisfactory enough for analysis, reporting and drawing conclusions. The response

rate was a true representative of the study population.

Table 1: Response rate

Category of respondents Target

sample size

Actual

respondents

Response rate

Managers 40 36 90%

Technicians 25 22 88%

Data Analysts 10 7 70%

Engineers and Designers 5 2 40%

Procurement Officers 5 2 40%

Human Resource Officers 5 2 40%

Administrators 5 3 60%

Legal Advisors 5 3 60%

Tax Leaders 5 3 60

Total 105 80 76%

Descriptive Analysis

During data collection, the researcher listed several items/statements corresponding to diversity at the

workplace and its influence on performance of employees in the technology industry in Kenya. The respondents

(employees) were asked to rate the statements on a Likert scale of 1–5 whereby 1=Strongly Disagree,

2=Disagree, 3=Not sure, 4=Agree and 5=Strongly Agree. The “Means” and “Standard Deviation” for each

statement were established to provide a generalized feeling of the respondents on their perception on the

influence of diversity on their performance.

For generalization purposes, an outcome with a mean of 1 and less than 1.5 implied that the employees

strongly disagreed with the item/statement that the researcher used to rate their level of agreement hence the

attribute would be deemed to have no influence on employee performance. Means greater than 1.5 and less than

2.5 implied that the employees were disagreed with the item/statement that the researcher used to rate their

perception; hence the attribute had influence on employee performance to little extent. Means greater than 2.5

and less than 3.5 implied that the employees were not sure with the item/statement that the researcher used to

rate their perception; hence the attribute had influence on employee performance to some extent. Means greater

than 3.5 and less than 4.5 implied that the employees agreed with the item/statement that the researcher used to

rate their perception, hence the attribute would be deemed to have influence on employee performance to a great

extent. Means that are more than 4.5 implied that the employees strongly agreed with the item/statement that the

researcher used to rate their perception hence the activity had influence on employee performance to a very

great extent.

On the other hand, Standard Deviation describes distribution of the respondents’ feedback in relation to

the Mean. It provides an indication of how far the individual responses to each statement deviate from the Mean.

A Standard Deviation of more than 1 shows that there is no consensus on the respondents’ feedback, while a





standard deviation of greater than 0.5 but less than 1 shows that the responses are moderately distributed. When

the Standard Deviation is less than 0.5, it is an indication that the responses are concentrated around the Mean.

Information of the respondents

Information of the respondents helped the researcher to know the factors that could have influenced the

respondent’s answers, interests and opinions. In addition, it helped the researcher to compare responses and how

they varied between subgroups of the respondents. The researcher concentrated on gender, age, education level,

position respondents held at work, and period respondents had worked in their organization.

Gender diversity

Study findings on gender of the employees of IBM Kenya indicated that close to half (56.3) of the

employees of IBM Kenya who participated in this study were male while 43. 7% were female which indicates

that the gender ratio of the respondents of this study was approximately 1:1; an indication that there was gender

balance in this study thus information obtained was reliable. Based on these findings, it is concluded that there

is gender diversity in IBM Kenya.

Age diversity

The study’s findings on the age bracket of the respondents showed that most (62.5%) of the

respondents were 26-35 years, followed by 20.0% who were 36-45 years, then 18-25 years at 16.3%, and only

one respondent who was 46-55 years at 1.2%. Cumulatively, majority (78.8%) of the respondents were the

youth (18-35 years) while a few (21.2%) were adult (more than 35 years). These findings show that there is age

diversity among employees of IBM Kenya.

Level of education of the respondent

Study findings on the level of education of the respondents shows that most (48.7%) of the employees of

IBM Kenya had a bachelor’s degree, followed by 38.8% who had a Masters’ degree, 2.5% had a PhD, while

very few (1.2%) had only a secondary education. These findings show that there is diversity in educational

background at IBM Kenya.

Position held by employees at IBM Kenya

Respondents were required to indicate the position they held in their organization (IBM Kenya).

Findings presented show that most (27.5%) of the respondents were technicians and this could be attributed to

the fact that IBM is a technology company which requires more technicians in its operations. Following the

technicians are project managers at 18.8%, operational managers at 10.0%, business and data analyst at 8.8%,

marketing and sales managers at 7.5%, ICT managers at 5.0% among others. These findings show that most

participants of this study held different positions hence the findings truly represented all categories of

employees in the technology industry.

Period respondents had worked at IBM Kenya To establish the respondents’ experience with technology companies, respondents were asked to

indicate the number of years they had worked with their organization. Their responses show that slightly more

than half (57.5%) of the respondents had worked at IBM Kenya for a period of 1 – 5 years, 27.5% had worked

for a period of 6 – 10 years, 11% had worked for 11-20 years, while a few (5.0%) had worked with IBM Kenya

for less than a year. The findings show that participants of this study had varied experience within the

technology industry with majority having experience of at least one year. With at least one year experience in

the technology industry, majority of the respondents of this study were probably aware of diversity practices in

the technology industry and its effect on employee performance hence the information they provided was

reliable.

Diversity attributes at the workplace

The first objective of this study was to identify the diversity attributes or practices that exist at IBM

Kenya. There were three types of diversity that the study focused on, namely gender, age, and educational

background diversities.

Gender diversity attributes

The study sought to establish the existence of gender diversity attributes at IBM Kenya. First,

employees of IBM Kenya were asked to indicate whether there is gender diversity in their organization.

Findings were as shown in Table 2.

Table 2: Whether there is gender diversity at IBM Kenya

Whether there is gender diversity at IBM Kenya Frequency Percentage (%)

Yes 72 90.0

No 8 10.0

Total 80 100.0

From the findings in Table 2 above, close to all respondents at 90% agreed that there is gender

diversity at IBM Kenya. This implies that there are various attributes of gender diversity that are being

implemented by IBM Kenya. Therefore, various attributes of gender diversity were listed and respondents were

asked to indicate the extent to which they agreed or disagreed to the attributes. The findings were as shown in

Table 3


Sciences, ISSN 2250-0588, Impact Factor: 6.565, Volume 08 Issue 08, August 2018, 1-96



Table 3: Gender diversity attributes at IBM Kenya

Gender diversity attributes N Mean Std. Deviation

There is gender balance among employees of IBM Kenya 80 3.8375 1.08434

During hiring and recruitment of employees, IBM Kenya gives

equal opportunities to both male and female

80 3.9875 0.96119

There is equal opportunities for growth and development for

both male and female employees

80 3.9125 0.99612

Our organization has a career development for both male and

female employees

80 3.9125 1.06965

Our organization’s leadership comprise of both male and female 80 3.9125 1.06965

Our organization’s training and development program is

developed to meet the criteria/requirement of the male and

female gender.

80 3.8625 1.17725

Our organization involves both male and female in decision-

making

80 3.8750 1.14045

From the findings in Table 3, employees of IBM generally agreed (3.5≤ Mean> 4.5) that: there is

gender balance among employees of IBM Kenya, IBM Kenya gives equal opportunities to both male and female

during hiring and recruitment of employees, there is equal opportunities for growth and development for both

male and female employees, IBM Kenya has a career development plan for both male and female employees,

the leadership of IBM Kenya comprise of both male and female, training and development program of IBM

Kenya is developed to meet the criteria/requirement of both genders, and that IBM Kenya involves both male

and female in decision-making.

These findings on gender diversity attributes clearly show that IBM Kenya highly values gender

diversity among its employees. According to Burns and Bush (2016), unlike men, women do not have an upper

hand during hiring. As if not enough, women are also discriminated against when it comes to receiving equal

salaries for equal work and even job promotions. As a matter of fact, most females who replace their male

counterparts always receive lower salaries. In addition to that, other researchers have also shown that gender

discrimination is amongst the most challenging issues at the organizational levels that affects productivity

(Francisco et al., 2005).

Age diversity attributes

First, respondents were asked whether there is age diversity among employee at IBM Kenya. From the

findings in Table 4, majority of the respondents at 88.8% agreed that there is age diversity at IBM Kenya while

11.2% disagreed that there is age diversity.

Table 4: Whether there is age diversity among employees in IBM Kenya

Age diversity among employee of IBM Kenya Frequency Percentage (%)

Yes 71 88.8

No 9 11.2

Total 80 100.0

From the findings in Table 4, it is evident that there is age diversity at IBM Kenya. The researcher

went further to identify the attributes of age diversity that exists at IBM Kenya. Study findings were as shown in

Table 5.

Table 5: Age diversity attributes

Age diversity attributes

N Mean Std.

Deviation

I am positive about age diversity in this workplace 80 3.8375 0.86337

Our organization hire employees without discrimination of their

age

80 3.8750 0.80150

Our organization’s current leadership comprise of people in

different age groups

80 3.6875 0.97557

There is no age biasness in the current employees of IBM

Kenya

80 3.7625 0.98397

Our organization provides equal opportunities for training and

career development despite the age of the employee

80 3.8375 0.87791

My team leaders include members of different age groups in

solving problems and in decision making.

80 3.9125 0.85970

The age differences in work group do not cause conflict 80 3.9000 0.89443

At work, there is good bonding with people of different age

group.

80 3.8250 0.88267





From the findings in Table 5, employees of IBM Kenya generally agreed (3.5≤ Mean> 4.5) that: they

were positive about age diversity in their workplace, IBM Kenya hire’s employees without discrimination of

their age, current leadership of IBM Kenya comprise of people in different age groups, and there was no age

biasness in the current employees of IBM Kenya. The employee also agreed (3.5≤ Mean> 4.5) that: IBM Kenya

provides equal opportunities for training and career development despite the age of the employee, team leaders

in IBM Kenya include members of different age groups in decision making and solving problems, they also

agreed that the age differences in teams do not cause conflict, and that there is teaming with people of different

age groups in their workplace.

These findings demonstrate that indeed there is age diversity at IBM Kenya. According to Gellner and

Veen (2013), company performance can be improved by complementing values brought by different age groups.

Having employees of the same age group on its own can have a negative effect on productivity.

Attributes of Educational diversity in workplaces Employees of IBM Kenya were asked whether there is educational background diversity among them.

Findings in Table 6, indicate that majority of employees of IBM Kenya at 82.5% agreed that there is educational

background diversity at IBM Kenya while 17.5% denied that there is educational background diversity among

them.

Table 6: Whether there is education background diversity at IBM Kenya

Whether there is education background diversity at IBM

Kenya

Frequency Percentage (%)

Yes 61 82.5

No 14 17.5

Total 80 100.0

With majority of employees of IBM Kenya agreeing that there is educational background diversity

among them, the researcher further asked them to indicate the extent to which they agreed to various attributes

of educational background in workplaces. Their responses were as shown in Table 7.

Table 7: Educational background diversity attributes

Findings shown in Table 7, indicate that employees of IBM generally agreed (3.5≤ Mean> 4.5) that:

the recruitment plan of IBM Kenya is based on the education background of the employees, the leadership

comprise of people with higher academic qualifications, educational qualification of employees correspond to

the position they held at IBM Kenya, and that IBM Kenya rewards specialized education and skills. Further,

employees of IBM generally agreed (3.5≤ Mean> 4.5) that: IBM Kenya provides paid study leave to employees

who go for further studies to enhance their performance, opportunities for educational growth and advancement

exist for employees who have lower qualification in education, that team leaders of IBM Kenya includes all

members at different education level in problem solving and decision making, and that IBM Kenya gives equal

treatment when it comes to the diversity of education background.

These findings imply that indeed there is educational background diversity at IBM Kenya. Gwendolyn,

(2012) found that various organizations did implement education diversity initiatives to get employees to work

effectively together toward achieving organizational goals. Employee’s education background can be a

showcase of one’s knowledge, skills, and capability. Holland (1997) thought that the choice of a specific major

in school may reflect one’s cognitive strength and personality.

Educational background diversity attributes

N Mean Std.

Deviation

The recruitment plan of the organization is based on the education

background of the employees

80 3.7500 0.89301

The organization’s leadership comprise of people with higher academic

qualifications

80 3.6750 0.91090

Educational qualification of employees correspond to the position they hold

at IBM Kenya

80 3.6250 0.97273

Our organization rewards specialized education and skills 80 3.6500 1.09197

The organization provides paid study leave to employees who further their

education that will enhance their performance.

80 3.7125 1.06965

Opportunities for educational growth and advancement exist for employees

who have lower qualification in education.

80 3.7750 1.10207

The team leader includes all members at different education level in

problem solving and decision making.

80 3.5750 1.21983

The organization gives equal treatment when it comes to the diversity of

education background.

80 3.6750 1.06468





Effect of diversity on employee performance

The purpose or general objective of this study was to establish how diversity in the workplace has

influenced performance of employees in the technology industry with focus on IBM Kenya. Therefore, this

section provides the effect of diversity in workplace on employee performance.

Effect of gender diversity on employee performance

The second objective of this study was to establish the effect of gender diversity on employee

performance in IBM Kenya. To achieve this, six common effects of gender diversity on employee performance

were listed and respondents were asked to indicate the extent to which they agreed or disagreed to the effects.

Their responses were as summarized in Table 8 below.

Table 8: Effect of gender diversity on employee performance

Effect of gender diversity on employee performance N Mean Std.

Deviation

Gender balance among employees of IBM Kenya has motivated me to

remain committed hence improved performance at work

80 3.8000 0.95996

The organization’s policy of giving equal opportunities for growth and

development for both gender has improved my performance over time

80 3.8500 1.00757

Availability of a career development for both gender has improved

performance of employees

80 4.7875 6.40943

Gender balance in leadership of IBM Kenya has motivated employees

hence improving their performance

80 3.9000 1.00127

The organization’s training and development program that meet the

requirement has improved employee performance

80 3.7875 1.00245

Involvement of both male and female in decision-making gives

employees freedom to express themselves hence motivating them to

perform better at work.

80 3.6625 1.04268

From the findings in Table 8, employees of IBM Kenya strongly agreed (Mean score of 4.7875) that

availability of a career development for both gender has improved performance of employees at IBM Kenya.

Further, the employees generally agreed (3.5≤ Mean> 4.5) that: gender balance among employees motivate

them to remain committed at work, organizational policy of giving equal opportunities for growth and

development for both gender improve employee performance over time, gender balance in organizational

leadership improve employee performance through motivation, organizational training and development

program that meet the requirement improve employee performance, and involvement of both gender in

decision-making gives employees freedom to express themselves hence motivating them to perform better at

work. These findings imply that gender diversity at workplace is very influential in enhancing employee

performance hence enhancing organizational growth.

In line with this study’s findings on the effect gender diversity on employee performance;

Organizations typically benchmark against companies that are gender inclusive in employee relations to chart

their success in fostering diverse and gender inclusive work environments (Daniels, 2004). It is also worth

noting that we live in a world where women are constantly stereotyped against certain characteristics like

ability, aggression, and ambitious, which are presumed to be the characteristic that make an employee

successful as they climb the corporate ladder, with most cultures around the globe adhering to that notion.

Because of these assumptions, many organizations obviously prefer to hire men compared to women as they are

perceived to be better performers. The challenge is to first overcome the thought that women are not capable of

performing certain types of work.

Effect of age diversity on employee performance

The third objective of this study was to determine effect of age diversity on employee performance.

Therefore, the researcher sought to achieve this objective by listing five common effects of age diversity on

employee performance and asking respondents to indicate the extent to which they agreed or disagreed to the

age diversity effects. Their responses were as summarized in Table 9 below.

Table 9: Effect of age diversity on employee performance

Effect of age diversity on employee performance

N Mean Std.

Deviation

Having different age groups in senior positions encourage and motivate

employees to perform in their work

80 3.7375 0.85305

Provision of equal opportunities for training and career development all age

groups has improved performance of employees

80 3.8125 0.82820

Involvement of members of different age groups in solving problems and in

decision making has enhanced employee performance

80 3.7375 0.97752





Lack of employee conflicts due to age differences in work group has improved


80 3.7375 1.01562

Good bonding with employees of different age groups has improved my

performance

80 3.7375 1.01562

As shown in Table 9, the employees of IBM Kenya generally agreed (3.5≤ Mean> 4.5) that having

different age groups in senior positions encourage and motivate employees to perform in their work, good

bonding with employees of different age groups improved their performance, and that involvement of members

of different age groups in solving problems and in decision making enhanced employee performance.

Additionally, the employees agreed (Mean score of 3.7375) that lack of employee conflicts due to age

differences in work group improved employee performance. The employees also agreed (Mean score of 3.7375)

that provision of equal opportunities for training and career development of all age groups improved

performance of employees. These findings have demonstrated that age diversity at workplaces in technology

industry plays major role on employee performance.

The effects of age diversity on employee performance are consistent with organizational behaviour.

Research on age-group relations at workplaces shows that conflict is a common outcome when employees of

different age groups encounter each other. By definition, diverse work teams include members who can be

identified as belonging to distinct age groups. When findings from research on age group relations is applied to

understanding dynamics within diverse teams, the natural prediction is that age diversity in work teams leads to

negative outcomes such as disruptive conflict that must be avoided (Turner & Haslam, 2001).

The method adopted for managing a diverse workforce in terms of age can either be detrimental to the

employee performance and productivity or can bring out the full potential in them depending on how effective it

is. Employees who feel more valued work hard while the age group of employees that consider themselves as

minority group feel less valued leading to lower performance. This can be because of stereotyping, and

prejudice within an organization (Goetz, 2001). Therefore, when an organization ignores the existence and

importance of age diversity, conflicts can emerge and neither the corporation nor its employees will realize their

potential. The main undoing of age diversity in the workplace is increase in conflicts. These conflicts arise

largely due to ignorance, prejudice feelings or derogatory comments that cause lack of acceptance. These lead to

negative dynamics such as ethnocentrism, stereotyping, cultural or age clashes with the feeling of being superior

to others. If management ignores such conflicts; the employee performance may suffer (Otike, Messa &

Mwalekwa, 2005).

Age diversity has become an unavoidable fact of life in many organizations (Kunze et al., 2013).

According to the social identity and self-categorization theories; people will classify themselves into age groups

based on characteristics that they identify with and as a result, they will tend to favour these groups at the

expense of other groups different from theirs (Kunze et al., 2013). Gelner and Stephen (2009) both show us that

conflicts can be frequent where there is a generational gap.

Effect of educational background diversity on employee performance

The fourth and last objective of this study was to establish the effect of educational background

diversity in workplaces on employee performance. Nine effects of educational background diversity on

employee performance were designed and respondents were asked to indicate the extent to which they agreed or

disagreed to those effects. Study findings were as shown in Table 10 below.

Table 10: Effect of educational background diversity in the workplace on employee performance

Effect of educational background diversity in the workplace on employee

performance

N Mean Std.

Deviation

Working with employees with different educational levels or background

has improved my performance at work.

80 3.9500 1.04215

Due to educational background diversity at IBM Kenya, employees are

very innovative

80 4.0000 0.96784

I get committed and motivated to complete my tasks because the

organization rewards my educational advancements

80 3.9250 0.96489

Specialized skills and trainings offered by our organization has improved

my performance at work

80 3.9125 0.98333

The organization’s career development guide and rewards on educational

achievements has improved my performance at work

78 3.9103 0.90001

I enjoy and remain committed to my work because the organization

provides equal treatment to its employees despite their educational

background

80 3.8875 1.00623

The organization’s principle of involving all members at different

education level in problem solving and decision making has improved my

performance

80 3.8625 1.07614





I am confident at my work due to my education background 80 3.9125 1.02121

Table 10 reveals that employees of IBM Kenya generally agreed (3.5≤ Mean> 4.5) that

working with employees with different educational levels or background has improved their performance,

educational background enhance employee performance through innovation and employees get committed and

motivated to complete their tasks because the organization rewards their educational advancements. Also, the

employees agreed (3.5≤ Mean> 4.5) that: they were confident at their work due to their education background,

IBM Kenya’s career development guide and rewards on educational achievements improved employee

performance, and they enjoyed and remained committed to their work because IBM Kenya provides equal

treatment to its employees despite their educational background. Finally, the employees agreed (3.5≤ Mean>

4.5) that IBM Kenya’s principle of involving all members at different education level in problem solving and

decision making improved their performance and specialized skills and trainings offered by IBM Kenya

improved employee performance.

Based on these findings, it is probable to conclude that educational background diversity in workplaces

is very influential on employee performance hence the need to adopt best practices of educational background

workforce diversity. According to Dutton and Duncan (1987), educational background diversity is assumed to

be associated with cognitive diversity, which expands a team’s informational resources and enhances its

problem-solving capacity. Thus, within the context of top management teams, educational background diversity

broadens the range of cognitive perspectives needed to recognize strategic opportunities and consider various

strategic alternatives, which enhances a team’s ability to identify and deal with environmental conditions.

The relationship between educational background diversity and employee performance may be more complex

than has been articulated in the past. However, the current study established that IBM Kenya’s team comprised

of employees with varying academic qualifications across the organization. Based on literature and this study’s

findings, it is logical to conclude that organizations with highly diverse employees in terms of educational

background may have a broader range of perspectives and skills, which may enhance strategic problem-solving

and decision-making capabilities. Consequently, such organizations may experience higher employee

performance hence high growth rate.

Attributes of employee performance

The researcher sought to measure employee performance using various attributes as shown in Table 11

below.

Table 11: Indicators of employee performance

Indicators of employee performance

N Mean Std.

Deviation

I enjoy my tasks and the division’s work approach 80 5.0075 8.09781

I am committed to the mission and direction of my organization 80 3.9000 0.90847

I am comfortable working with IBM Kenya and am proud to be

associated with the organization

80 4.0125 0.92084

I am motivated to complete the task that is assigned to me 80 5.0005 6.33494

I am able to perform in all key areas of my role 80 4.0125 0.90699

I co-operate and work well with my colleagues. 80 3.9500 0.88447

I maintain consistency in my work 80 3.9875 0.83429

I always meet deadlines on tasks assigned to me 80 3.9125 0.91671

I am always responsible for my work 80 3.9625 0.99929

I have good relationship with my leaders and fellow employees

From the findings in Table 11, employees of IBM Kenya who participated in this study strongly agreed

that they enjoyed their tasks and the division’s work approach (Mean score of 5.0075) and they were motivated

to complete the task that was assigned to them (Mean score of 5.0005. This is a clear indication the employees’

performance at IBM Kenya was excellent. In addition, the employees generally agreed (3.5≤ Mean> 4.5) that:

they were committed to the mission and direction of IBM Kenya, they were comfortable working with IBM

Kenya and proud to be associated with the organization, they were able to perform in all key areas of their role,

they co-operated and worked well with each other colleagues, they always met deadlines on tasks assigned to

them, and that they maintained consistency in their work.

These findings on the attributes of employee performance assert that employees in the technology

industry who participated in this study performed well. According to Baldwin (2008), employee performance is

a means of carrying out actions efficiently and effectively by the employees in order to achieve the

predetermined objectives of an organization. Armstrong and Baron (2010) noted that employee performance is

normally looked at in terms of outcomes or employee’s output against the set individual objectives populated

from the company objectives. Additionally, employee performance can be viewed in terms of behavior. It is

how well an employee is fulfilling the requirements of the job and it is determined by a combination of three

main factors namely: efforts, ability and direction.





According to Bates and Horton (1995), performance is a multi-dimensional contrast, the measurement

of which varies, depending on a variety of factors. They also state that it is important to determine whether the

measurement objective is to assess performance outcome or behavior. A more comprehensive view of

performance is achieved if it is defined as embracing both behavior and outcomes. Brumbrach (1988) argues

that performance means both behavior and results. Behaviors emanate from the performer and transform

performance from abstraction to action. This therefore means that when one is managing performance of teams

and individuals, both input (behavior) and output (results) should be considered.

Inferential Statistics

The researcher used inferential statistics techniques to allow this study to use the population sample to

generalize about the entire population from which the sample was drawn. The study applied the regression

analysis, the Summary Model, Analysis of Variance, and regression correlation coefficient of determination to

determine the predictive power of the influence of diversity attributes on employee performance in technology

industry Kenya using IBM Kenya as a case study.

Regression aanalyses

Using the statistical package for social sciences (SPSS) version 23.0, the researcher used multiple

regression analysis to test relationship between diversity at IBM Kenya (gender diversity, age diversity, and

education background diversity) which were the independent variables and employee performance in IBM

Kenya which was the dependent variable. The regression analysis coefficients were used in the determination of

the relationship between the dependent variable (employee performance in IBM Kenya) and the independent

variables (gender diversity, age diversity, and background education diversity). The coefficients explain the

extent to which changes in the dependent variable can be explained by the change in the independent variables

or the percentage of variation in the dependent variable that is explained by all the three independent variables.

IV. MODEL SUMMARY Table 12 shows the Model Summary of the regression analysis that was conducted.

Table12: Model Summary of the regression analysis

Model R R

Square

Adjusted

R Square

Std. Error

of the

Estimate

Change Statistics

R Square

Change

F

Change

df1 df2 Sig. F

Change

1 .899a .808 .091 .46603 .008 0.829 79 1 .007

From Table 12 above, findings indicate the three independent variables (gender diversity, age diversity,

and education background diversity) that were studied explain only 80.8% on the effect on employee

performance in IBM Kenya as represented by the R Square (R2). This therefore means that other factors not

studied in this research contribute 19.2% of the influence on employee performance. Therefore, further research

should be conducted to investigate the other factors (19.2%) that influence performance of employees in the

technology industry in Kenya.

ANOVA Results

Table 13 is a summary of the ANOVA statistics obtained from the mean of variables within workforce

diversity that influence employee performance in the technology industry in Kenya. ANOVA cross tabulated

results were obtained based on the consideration of average values of respondents’ views and opinions on the

influence of workforce diversity on employee performance. Estimates were made based on the respondents’

perception on the influence of gender diversity, age diversity, and background education diversity on employee

performance.

Table 13: ANOVA of the Regression

ANOVAb

Model Sum of Squares Df Mean Square F Sig.

Regression 3.517 79 0.330 1.029 .007a

Residual 1.043 1 0.320

Total 4.550 35 b. Predictors: (Constant): gender diversity, age diversity, and background education diversity

a. Dependent variable: employee performance in technology industry in Kenya

The significance value obtained in the regression model is used to measure whether the relationship

between the independent variables and the dependent variable is statistically significant. From the table above,

the significance value (p) for the relationship between the workforce diversity adopted by technology industry in

Kenya and employee performance is 0.007. Since the significance value (p) for this relationship is less than the

statistically acceptable significant value of 0.05 i.e. p ≤ 0.05, it is then concluded that the relationship between

the workforce diversity adopted by the technology industry in Kenya and employee performance is statistically

significant in predicting how diversity influence’s performance of employees. The F critical at 5% level of





significance was 0.320. Since F calculated is greater than the F critical (value = 1.029), this shows that the

overall model was significant.

Coefficient of Correlation

The researcher conducted multiple correlation analysis to determine the relationship between

workforce diversity and employee performance in technology industry in Kenya. The tested variables included:

gender diversity, age diversity, and background education diversity. The results were as presented Table 14

below.

Table 14: Coefficient of correlation compensation strategies-employee performance

Model Un-standardized Coefficients Standardized

Coefficients

t statistics Sig.

Level

B Std. Error Beta

(Constant) 1.767 0.489 3.615 .007

1 Gender diversity attributes in

workplace

0.128 .139 .190 .916 .006

2 Age diversity attributes in

workplace

0.143 .100 .211 1.434 .011

3 Educational background

attributes in workplace

0.253 .105 .310 2.396 .006

Dependent variable: Employee performance in technology industry in Kenya

As per the SPSS generated table above, regression equation

Y = β0 + β1x1 + β2x2 + β3x3+ β4x4+ ε

Where: Y is the employee performance as result of workforce diversity adopted by technology industry

in Kenya.

B0 is a constant

β1 to β4 are the coefficient of the independent variables

x1 to x4 are the independent variables where

ε is the error term.

Therefore,

(Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + ε) becomes:

(Y= 1.767+ 0.128X1+ 0.143X2+ 0.253X3) + ε

From the established equation, it implies that if workforce diversity in the technology industry in

Kenya (gender diversity, age diversity, and educational background diversity) is considered and kept constant at

zero, employee performance in the technology industry in Kenya will be effective at 1.767. However, the data

findings analyzed indicate that taking all other independent variables (workforce diversity) at zero: a unit

increase in gender diversity attributes in workplace will lead to a 0.128 effectiveness in performance of

employees in the technology industry in Kenya; a unit increase in age diversity attributes in workplaces will

lead to a 0.143 effectiveness in performance of employees in the technology industry in Kenya; while a unit

increase in educational background diversity attributes in the workplace will lead to a 0.253 effectiveness in

performance of employees in the technology industry in Kenya. From these findings, it can be concluded that,

diversity adopted by the technology industry in Kenya has great influence on performance of employees.

At 5% level of significance and 95% level of confidence, the relationships between workforce diversity (gender

diversity, age diversity, and educational background diversity) adopted by the technology industry and the

employee performance were all significant. This is because the statistical significant value (p) of each diversity

type was less than 0.05 implying that the relationship of each diversity type with employee performance was

statistically significant.

V. CONCLUSION In today’s competitive environment in the corporate world, employees’ performance continues to make

a significance impact on the success or failure of any organization with regards to achieving organizational

goals and objectives. This means that an organization must get the employees’ priorities right to continue to

remain relevant in today’s competitive corporate environment. Among the priorities of the employees is the

organizations’ workforce diversity practice. Workforce diversity practices motivate employees leading to

enhanced performance. As a result, organizations gain a competitive advantage in the market place due to

improved employee performance that provide a platform for growth in terms of market share and profitability.

In this regard, study findings show; that gender balance among employees motivates them to remain committed

at work, organizational policies that provide equal opportunities for growth and development for both gender

improve employee performance over time have ascertained that workforce diversity has a great influence on

employee performance, that having different age groups in senior positions encourage and motivate employees

to perform in their work, and that involvement of members of different age groups in solving problems and in





decision making enhanced employee performance, and that involving all members at different education levels

in problem solving and decision making improves their performance. The study findings revealed that providing

equal opportunities of growth and development without discrimination based on gender, age, or educational

background is very important in influencing employee performance in the technology industry. Therefore, it is

reasonable to conclude that workforce diversity practiced by technology companies highly influence’s

performance of employees leading to overall organizational performance. This could be the factor that

contributes to growth and dominance of IBM Kenya in the technology industry not only in Kenya but

internationally.

Recommendations

Based on the study’s findings, the following are the recommendations of this study:

The government in collaboration with other stakeholders in the technology industry should ensure that

there are effective policy guidelines on workforce diversity to enhance employee performance. This

will lead to improved organizational performance hence improved economic growth.

All technology companies should adopt best practices of workforce diversity to enhance employee

performance thus leading to improved organizational performance. The best practices of workforce

diversity should correspond to employers’ priorities for better performance.

Areas for further research

The study recommends a further research to be conducted to compare the influence of workforce

diversity and other factors that influence employee performance like good set of skills, productive work

environment, leadership style, organizational culture, trainings, motivation, renumerations among others. This

will provide a basis to conclude that workforce diversity in the technology industry influence’s employee

performance more or less than other factors.

A further study should be conducted on the workforce diversity in public technology companies and its

effect on employee performance. This due to the fact this study concentrated on a private technology

organization, i.e. IBM Kenya.

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About the Authors

Anne Onsarigo is a Master Degree Student of Catholic University of Eastern Africa Kenya, She holds

Bachelor's degree from Spicer Memorial College, India. Majoring in Computer Science. She is a HR

Practitioner.

Dr. Thomas Katua Ngui is a Senior Lecturer at The Management University of Africa, Kenya. He

previously served as Head of Department of Marketing and Management and also as Director Graduate

Business School at The Catholic University of Eastern Africa for the last 8 years. Dr. Ngui has published widely

in the areas of Human Resources Management, Entrepreneurship, Strategic Management and Corporate

Governance. He is also a Certified Management Consultant, Full Member of the Institute of Human resources

management (Kenya) and Full Member of The Kenya Institute of Management. Dr. Ngui is also a Member and

Chairman of the Finance and General Purpose Committee of the Board of Directors of Machakos Water and

Sewerage Company Ltd.

demographic diversity in the workplace and its effect on...

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