research

1.4 Hypothesis of the Study .............................................................................................4

Chapter 2: Review of Literature .....................................................................................5

2.1 HR Systems ...............................................................................................................5

2.1.1 Human Resources Information System (HRIS) ..................................................5

2.1.2 Human Resources Management System (HRMS) ..............................................6

2.2 Historical Overview and Evolution in HR Systems ...................................................6

2.3 Impact of HRMS and HRIS on Work Performance ..................................................8

2.4 HRIS and HRMS Functionality and Applications ....................................................9

2.4.1 Employee Self-Services (ESS) ..........................................................................10

2.4.2 Applicant Tracking Software (ATS) .................................................................10

2.5 Implementation of HRMS and HRIS ......................................................................11

Chapter 3: Research Methodology ................................................................................14

3.1 Methodology ............................................................................................................14

3.2 Research Design .......................................................................................................14

3.3 Instrumentation (Survey) ..........................................................................................15

3.3.1 Pilot Survey .......................................................................................................15

3.3.2 Complete Survey ...............................................................................................16

3.3.3 Questionnaire Validity ..........................................................................................16

3.3.4 Questionnaire Stability ..........................................................................................17

3.4 Population and Sampling .........................................................................................18

3.5 Data Collection and Analysis Procedures ...............................................................19 Chapter 4: Results and Discussion ................................................................................20

4.1 Variables of the Study Population ...............................................................................20

4.2 Testing Research Hypothesis ......................................................................................21

4.2.1 Hypothesis 1 .....................................................................................................21

4.2.2 Hypothesis 2 .....................................................................................................23

4.2.2.1 Differences Related to Gender Variable ...................................................23

4.2.2.2 Differences Related to Age Variable ........................................................24

4.2.2.3 Differences Related to Qualification Variable ..........................................25

4.2.2.4 Differences Related to Years of Experience Variable ..............................27

4.2.2.5 Differences Related to Work Nature Variable ..........................................28

4.2.2.6 Differences Related to Work Region Variable .........................................29

4.2.3 Hypothesis 3 .....................................................................................................30

4.2.3.1 Differences Related to Gender Variable ...................................................30

4.2.3.2 Differences Related to Age Variable ........................................................31

4.2.3.3 Differences Related to Qualification Variable ..........................................32

Chapter 5: Recommendations, and Conclusions .........................................................34

5.1 Discussion - Current HRMS Model Building .............................................................34

5.1.1 Current Recruitment Module .............................................................................34

5.1.2 Current Workforce Management Module ........................................................35

5.1.3 Current Performance Management Module .....................................................35

5.1.4 Current Training and Development Module ....................................................36

5.2 Recommendation- Smart HRMS Model Building ......................................................37

5.2.1 Suggested Recruitment Module .......................................................................38

5.2.1.1 Applicant Tracking Software (ATS) .........................................................39

5.2.1.2 Onboarding ...............................................................................................40

5.2.2 Suggested Workforce Management Module ....................................................40

5.2.3 Suggested Performance Management Module .................................................42

5.2.4 Suggested Training and Development Module ................................................43

5.3 Conclusion ............................................................................................................45

5.3 Future Enhancement ............................................................................................46 References.........................................................................................................................47

Appendix A (Complete Survey)......................................................................................52

Appendix B (Pilot Survey)..............................................................................................59 Appendix C (Population)................................................................................................66

LIST OF TABLES

Table

CONTENTS

P

AGE No.

Table 1 Correlation Coefficients Calculation .........................................................17

Table 2 Cronbach's Alpha ......................................................................................18

Table 3 Socio-Demographic Characteristic ...........................................................21

Table 4 Pearson Test ..............................................................................................22

Table 5 (T) Test - Illustrate the Difference According to the Gender Variable .....24

Table 6 ANOVA Differences According to Age Variable ....................................25

Table 7 LSD Test of the Differences in Each Category of Age ............................25

Table 8 ANOVA Differences According to Qualification Variable ......................26

Table 9 LSD Test of the Differences in Each Category of Qualification ..............26

Table 10 ANOVA Differences According to Years of Experience Variable ..........27

Table 11 LSD Test of the Differences in Each Category of Years of Experience ..28

Table 12 ANOVA Differences According to Work Nature Variable ......................28

Table 13 LSD Test of the Differences in Each Category of Work Nature ..............29

Table 14 ANOVA Differences According to Work Region Variable .....................29

Table 15 LSD Test of the Differences in Each Category of Work Region .............30

Table 16 (T) Test - Illustrate the Difference According to the Gender Variable .....31

Table 17 ANOVA Differences According to Age Variable ....................................32

Table 18 LSD Test of the Differences in Each Category of Age ............................32

Table 19 ANOVA Differences According to Qualification Variable ......................33

Table 20 LSD Test of the Differences in Each Category of Qualification ..............33

LIST OF FIGURES

Current HRMS ..........................................................................................34

FIGURES

CONTENTS

PAGE No.

Figure

1

Figure 2 Smart HRMS .............................................................................................38

Figure 3 Suggested Recruitment Model ..................................................................39

Figure 4 Suggested Workforce Management Model ..............................................42

Figure 5 Suggested Performance Management Model ...........................................43

Figure 6 Suggested Training and Development Model ...........................................45

II

VI

ABSTRACT

Employees are an organization’s most important assets. Investing in improving the functions of the Human Resources Management System (HRMS) allows organizations to help employees realize their full potential and improve their decision-making skills. The purpose of this paper is to introduce a decision aid on the new trend that is being used increasingly in the business world, which is the smart system. In particular, to examine its need and potential for the Human Resource Management System in the Ministry of National Guard Health Affairs. First, the Human Resources systems and technology is being reviewed, besides the historical and evolution timeline of this industry since its beginning in 1940’s. This paper will also include review in different key functions and smart application used in implementing smart HR systems.

In addition, this study investigates the need and impact of the smart HR system to serve as a decision aid in several human resource processes. Both performance outcomes and awareness of system users are analyzed in an experiment in which the intended users of the smart system served as subjects. The study draws largely from behavioral decision theory for its theoretical support and to the subjective environment. The researcher concludes this initial research endeavor by presenting some preliminary findings after analyzing the current needs and gaps, and suggesting new smart HRMS model that will cover several areas such as automating the recruitment cycle, implementing effective workforce management, tracking the performance and evaluation processes, and enabling the training.

Keyword: HRMS, Human Resources, Ministry of National Guard Health Affairs, HR

Model, Smart HRMS, BI, Dashboard, Training, ERP, Appraisal

Introduction

1

1.1 Statement of the Problem

The importance of this research is to know the need in the implementation of the smart systems and artificial intelligence on the Human Resources Management System in the Ministry of National Guard Health Affairs. With the current system, although there are multiple human resources processes available in the system, there are still some processes performed manually by the staff, which result on several drawbacks; for example, increasing the number of required HR staff, which leads to higher costs raised from staff’s payroll and offices allocation. Furthermore, important information for decision-making is not being shared in a timely manner. In addition, there is higher possibility of human data entry error.

On the other hand, in the newly built model, the smart system will close the gap and replace all the manual work in order to overcome and upgrade the existing features. The model will cover the applicable implementation of using smart systems, such as automatic filtering of the qualified candidates in job applications, online appraisal and 360performance feedback, and establishing training portal to increase the accessibility of training material across the organization.

1.2 Objectives of the Study

The purpose of this study is to identify the need and impact of smart system on the Human Resources Management System in Ministry of National Guard Health Affairs in particular. The study will identify the ineffectiveness areas of the current Human Resources

Management system and processes in Ministry of National Guard Health Affairs and analyze the impact of smart system utilization on problem-solving outcomes within Human Resources Management context. The main reason for this research is that many human resource decisions, such as employment decisions involve multiple criteria like scientific qualification, gender, experience, previous work, physical characteristics, personal characteristics, etc. The adoption of a smart system can help the human resources management to avoid discrimination and take accurate and timely decisions. Also, it would help the employees perform their jobs in a more efficient way, reduce human mistakes, improve the quality, and provide this information in a timely and accurate way.

Research objectives can be formulated as follows:

· To study the existing smart system adopted in the current HRMS in the Ministry of National Guard Health Affairs.

· To evaluate the level of satisfaction of employees with the current HRMS in the

Ministry of National Guard Health Affairs.

· To evaluate the level of employees’ awareness about the current HRMS and their level of cooperation in the Ministry of National Guard Health Affairs.

· Evaluate the gap between the current and proposed model of HRMS in the

Ministry of National Guard Health Affairs.

· Build a new model for the HRMS in Ministry of National Guard Health Affairs with reference to the findings.

1.3 Research Question

The research problem crystallizes in the following questions:

· What are the current smart HRMS features available in the Ministry of National

Guard Health Affairs?

· To what extent are employees aware of the current HRMS features in the Ministry of National Guard Health Affairs?

· What is the impact of smart systems in the satisfaction level of existing employees in the Ministry of National Guard Health Affairs?

· What is the areas to be included in the new smart HRMS model in the Ministry of

National Guard health affairs?

1.4 Hypothesis of the Study

In light of the research objectives, the following hypotheses can be formulated:

H1: “What is the relationship of job satisfaction of human resources services in terms of gender, age, qualification, years of experience, nature of work, and place of residence?”

H2: “Are there significant statistically differences among the study sample in the employees' awareness about the current characteristics of the human resources management system in the Ministry of Health in the National Guard according to variable (gender, age, qualification, years of experience, nature of work, place of residence)”

H3: “Are there significant statistically differences among the study sample in the employees' perception about the training in the Ministry of Health in the National Guard according to variable (gender, age, qualification)”

2 Review of Literature

2.1 HR Systems

HR related research use several terms interchangeably to describe the HR system, such as Human Resource Information System (HRIS) and Human Resource Management System (HRMS). Since the terms are repeatedly used through the study, below is a detailed definition for each:

2.1.1 Human Resource Information System (HRIS)

HRIS can be defined in several ways. A Human Resource Information System

(HRIS) “is a systematic procedure for collecting, storing, maintaining, retrieving, and validating data needed by an organization about its human resources” (Cathcart, 1999; Lippers & Swiercz, 2005). HRIS is the integration of both Human Resource and Information Technology (Markova, 2012). HRIS is not only about storing data in the computer, it is covering wider approach, which include storing, analyzing and controlling the HR related data (Bingöl, 2006). Therefore, it is not limited to software or hardware that process the technical functions, such as storing and analyzing an organization’s human resources data. It is an integrated system that contain all staffs’ data, policies, and procedures, which are essential to manage all human resources functionality (Hendrickson, 2003). HRIS is a powerful tool available in the hands of decision makers; it is providing information that is timely, accurate, concise, relevant, and complete (Moussa, 2014). HRIS is a database system that acts as an interface link HR with information technology. It is established for the purpose of supporting the HR functions, such as storing and analyzing data and assisting in the management of human capital in terms of tracking and making decisions (Dilu Gebreslassie & Kebede, 2017).

2.1.2 Human Resource Management System (HRMS)

Human Resource Management System (HRMS) is a set of integrated systems and processes that link human resource management with information technology, which provide an opportunity to revolutionize the organization (Ferguson & Reio, 2010). HRMS is defined as the utilization of staff to encourage a higher level of productivity, better performance and effectiveness to achieve the organization’s goals and objectives (Bucata & Rizescu, 2016). Human Resources Management is one of the key factors of the organizational sustainability, since organization is basically relying on its human capital. HRMS is the tools that used to provides a multitude of necessary information with high flexibility and automation to increase the organization competitive advantage (Margatama, 2017; Tansley, Newell & William, 2001). HRMS comprises several organization's processes and affects other management subsystems. It define the procedures for business path dependency design and separate management subsystems (Anisimov, Obukhova,

Aleksakhina, Zhaglovskaya, & Kudra, 2017)

2.2. Historical Overview and Evolution in HR System

During the 1940’s and 1950’s, computer functionality was much more limited than what it is today. Starting from the 1960’s, HR departments used a computer-based applications process for payroll activities and to store employee data. In the 1970’s, some of the larger organization began establishing their own HRIS. In the 1980’s, only 40% of the organizations were using HRIS, whereas, others were reluctant to change (Buzkan, 2016).

Nowadays, the advancement of technology in the twenty-first century has clearly change the way people can work (Holland & Bardoel, 2016). In the modern workplace, the HR system is going beyond the simple systems that store and retrieve data, it is a collection of various information systems, including, Decision Support System (DSS), online communication, artificial intelligence (AI), and automatic processing (Weeks, 2013; Lepak, Marrone, & Takeuchi, 2004). System experts believe that recent innovations, such as the Internet of Things (IoT) and other technologies, will lead all HR areas such as the HR systems, functions, and management to face a change of demands. As a result, this will lead to a major transformation from simple HR management systems to smart HR management systems, in order to better align with the expectations and requirements of the organization and staff (Strohmeier, Piazza, Majstorovic, & Schreiner, 2016). HR services and functions are rapidly changing as a response to the changes of organizational culture, societal norms, and recent advancements in information technology. Although information technologies help HR professionals in enhancing the delivery of services, they also increase the pressure on them to provide better and faster services, and with an enhanced quality, that fits the greater staff, managers, and other service users’ expectation of HR services and functions (Hendrickson, 2003).

The focus of HR systems has shifted over time from basic functions, such as storing staff’s information, to a more advanced and automated management of human assets (Alharthey & Rasli, 2012). Recently, HR professionals have been facing some challenges due to the rapidly changing technological landscape, government rules and regulations, and high market competition (Bucata & Rizescu, 2016). Although HR functions have been largely bureaucratic in the past, HR departments today are responsible for providing support to management at all levels to show the return on investment for the organization

(Recardo, 2016).

2.3 Impact of HRMS and HRIS on Work Performance

A research study conducted by Weeks in 2013 aims to measure the degree of correlation between the automation of human resources elements like collecting, storing and retrieving the HR’s information with the organization’s ability to make more informed and effective long-term decisions regarding the positioning, utilization, and retention of its human resources. The findings show that HRIS enable the organization’s decision makers to have direct access to the human resources information without involving the Human Resource Department, which leads to improved efficiency and effectiveness with regards to decision making (Weeks, 2013). HR systems enhance the organization’s efficiency and improve the HR functions response time by automating the functions, eliminating duplicate efforts, and better organizing the HR staff’s tasks and duties (Weeks, 2013).

Over the last two decades, the strong competitive pressures and the changing regulatory requirements have driven all organizations, regardless of the organization size, to strongly depend on HR systems and the available analytical tools to enable the management to improve the effectiveness of its human assets and making better decisions about utilizing those assets (Hendrickson, 2003). As mentioned by Dilu, Gebreslassie, and Kebede in their study conducted in 2017; that focuses on measuring the impact of HR smart system on the healthcare industry, hospitals, clinics, and other health divisions were able to achieve success and positive result after the implementation of HR smart system. Economists in this era trust the importance of organizations investing in human resources and technology infrastructure, as they can enhance an organization’s competitiveness if managed well as other functions such as finance (Bucata & Rizescu, 2016).

Almutawa, Muenjohn, & Zhang were arguing in their study that there is no strong relation between staff commitment and HR system practices. This means that regardless of the effective implementation of HR system and management; if the staff does not believe that the new HR system is improving their skills, encouraging them, and enabling them to engage in HR system formulation, there will be no obvious enhancement in the staff commitment and performance (Almutawa, Muenjohn, & Zhang, 2016). Bucata and Rizescu, argue that the perfect implementation of HR management system and strategies will improve the productivity and the efficiency of the organization (Bucata & Rizescu, 2016). As well as, a study conducted in 2013 over 120 companies shows a positive impact of effective HRMS implementation on employee turnover and overall organization performance (Rodriguez & Ventura, 2013).

2.4 HRIS and HRMS Functionality and Applications

Employees at all levels in the organization use HRIS. Consequently, its functionality should meet all different needs and expectations. For example, managers have a high expectation on the important role of HR systems to give them a competitive advantage and help them meet the organization’s goals and objectives. From the managers’ perspective, HR systems will provide them with the best services and functionality, such as data collection and analysis tools, performance and appraisals management, recruitment and retention techniques, project management, employees’ career and skills development, and online training (Obeidat, 2012; Hendrickson, 2003). On the other hand, from the employees’ point of view, because they are the end-users of most of the services available in the system, they require HR systems to have a web-based access with 24/7 availability and easy self-service tools to simplify the usability of the HR functions (Hendrickson, 2003). HR systems with up-to-date information can assist in calculating the employees’ balances and deductions based on their work through the system, which will facilitate the human capital management and increase the employees’ trust of their managers’ decisions (Alharthey & Rasli, 2012)

HRMS will control and facilitate several human resources activities, such as human capital planning, recruitment and selecting staff, orientation and training, managing compensation, attendance, performance appraisal, staff scheduling, communication and relation, staff retention, and handling complaints. This will result in improving the knowledge of management and their efficiency in performing the work in order to meet the organization’s goal (Boateng, 2007; Hu, 2015; Zielinski, 2016).

2.4.1 Employee Self-Services (ESS)

HR professionals need specialized technologies to run under the umbrella of HRMS in order to perform a variety of functions. One of the specialized tools available in HRMS is the Employee Self-Services (ESS). ESS is a function that enables the staff and their managers to have a direct access to HR related information without asking HR department to provide it. ESS is supporting the organization by increasing the efficiency of the decisions. Another benefit of ESS is cost reduction; Weeks’s research shows that the organization can save an average $225 in transaction costs by using ESS and saving printing costs. Additionally, ESS reduces the probability transcription errors by allowing staff to enter and update their information directly through the system. Furthermore, ESS enhances the accessibility of the system by providing staff access through their Internet browser anywhere and anytime (Weeks, 2013).

2.4.2 Applicant Tracking Software (ATS)

In order for organizations, particularly larger organizations, to track a remarkable number of resumes and applications received in recruitment procedure, they need a strong HR system that will support and facilitate the process of tracking and evaluating all candidates to avoid any unfavorable consequences (Hendrickson, 2003). A specialized technology that is operated under the HRMS is the Applicant Tracking Software (ATS), which is a computer software that supports the HR professionals in online recruitment activities (Drucker, 2016). As stated by Weber in 2012, “Procter & Gamble” had received around one million candidates applying for 2,000 vacant positions, which is an average of 500 candidates per position. Although ATS is a useful function in managing the recruitment process, it is not the key function that will determine the selection of the HRMS. There are other functions considered as more valuable based on the organization needs (Gale, 2001).

2.5 Implementation of HRMS and HRIS

One of the important criteria that organizations focus on when choosing the HR system is to be both useful and cost effective. In order to control the cost and maintain the quality, organizations can utilize the ready (off-the-shelf) HR software such as Oracle and SAP as an alternative to building custom software, which is very flexible and adjustable. Along with providing the organization with wide access to global standards and best practices. On the other hand, organizations should consider the installations, training, and maintenance costs (Weeks, 2013; Alharthey & Rasli, 2012; Kroot, 1998).

In recent years, the investments on information technology have had a significant impact on almost every HR function. Information technology automated previously manual functions and processes in areas such as recruitment, training, compensation, and human capital management. Automation resulted in improved data quality, while improving timeliness and reducing costs (Hendrickson, 2003). Al-Harthey and Rasli, which was aimed at analyzing the HR system practices in the Kingdom, conducted a study of 100 organizations in the Saudi Arabian market in 2012. The study found that half of the organizations’ staff do not utilize the HR system. In addition to that, most of the organizations in the sample are using extra resources other than HR systems. Furthermore, the study shows that among organizations in the Saudi market, the staff is not satisfied with current level of HR system, besides the awareness among HR professional and managers of the importance of shifting to new technologies that is more effective which will satisfy the greater demand of the organizations (Alharthey & Rasli, 2012).

When an organization is planning to implement a new smart HR system, it needs to consider two areas related to the staff. First, the training cost, effort, and time that will be spent by the organization to guarantee the effective utilization of the system by the staff. Second, the importance of staff involvement in developing the strategies, plans and the overall solution in order to minimize the possibility of people resisting the changes (Weeks, 2013). Based on the awareness of the importance of efficiently and effectively managing the human assets; there is an obvious growth in investment on the information technologies and systems that support HR management and processes (Dilu, Gebreslassie, & Kebede, 2017).

On the other hand, some of issues mentioned in Weeks’ study pointed to obstacles to the implementation of current HR systems such as, the complex system interface, inflexible functions, difficulty of using the system, lack of knowledge about the system, and insufficient integration with other internal systems (Weeks, 2013).

There are different points of views on which departments should implement and manage the HRMS systems. Some argue that the HR department is the key end user who will utilize the HRMS, while others claim that HRMS will not be effective unless information technology department manages it (Drucker, 2016). With the advancement of technology, the HRMS has evolved into internet-based systems, which require less oversight by the IT department. However, this has raised an issue regarding the privacy of employee information (Gale, 2001). When implementing HR systems, continuous evaluation is required. As suggested by Zielinski, the process of assessing and evaluating the system needs to be completed every 2 years in order to adjust the functions to meet the changing needs by organizations (Zielinski, 2016).

3 Research Methodology

3.1 Methodology

The researcher adopted the analytical descriptive approach, which aims to study the phenomenon, as it exists in reality and is concerned as a precise description and it expresses descriptive and quantitative expression. This approach does not collect information about the phenomenon in order to investigate its manifestations and its different relations, but rather to analysis. Which link a set of variables with each other, and try to determine the relationship between two or more measurable variables, and the degree of this relationship

3.2 Research Design

The researcher relied on two main sources of information. First, the secondary sources: The researcher begun the study with the theoretical framework of the research to collect the secondary data sources, which give initial understanding of the study’s topic. This include scholarly, published articles, books, periodicals, reports, and previous studies that covering the same topic of study from different perspective and during several eras. At the end of the literature review, researcher has a comprehensive understanding of different angles and viewpoints around the topic. As well as, discover the areas that need deep investigation which help in designing the survey to collect the required information.

Then, researcher need to get closer to the actual environment of the study by looking for first-hand primary source of data. The researcher sought to collect the preliminary data and the original evidence to address the analytical aspects of the research topic through the survey as a main research tool specially designed for this purpose. The survey aims to discover the current HR system and functions available in MNGHA, besides measure the staff awareness and satisfaction level. As well as, recognize the staffs’ perceptions regarding the organization’s ability to upgrade their HR system and the impact of this upgrade on the work performance and decision efficiency. In order to build new HRMS model that able to overcome all the discovered issues.

3.3 Instrumentation (Survey)

An organization’s-based study has been piloted then completely conducted in five hospitals affiliated with Ministry of National Guard Health Affairs. The theoretical model, which was discussed in Chapter 1 and 2, are being verified using a survey. The researcher utilize the web-based survey (questionnaire) as the main source of collecting primary data; since the study population is located in five cities across the Kingdom of Saudi Arabia (Riyadh, Jeddah, Dammam Al Ahsa, Al Madinah). The web-based questionnaire is one of the most economical and convenient instrument for measuring large populations, which can reach as much as possible of employees in different locations. As well as, the questionnaires’ answers can be automatically collected and stored into the database.

3.3.1 Pilot Survey

A pilot study or feasibility study is a trial-version of the complete study used to test the selected research instruments such as interview or questionnaires. To increase the efficiency in conducting the survey, researcher use a pilot survey in the beginning to verify the questionnaire using a smaller sample size before releasing it to the actual sample size (Van Teijlingen & Hundley, 2001). The pilot online questionnaire was developed on six sections with initial 33 questions as shown in (Appendix B) that are subject to modification and development after analyzing the pilot results.

The sections were categorized based on the main research questions and hypothesis.

The first section is about the socio-demographic characteristics of the study sample such as, gender, age group, qualification, role, length of experience, and work’s region. The second section aimed to measure the awareness and satisfaction level of employees regarding the current HR services. Then, third section will shift to measure the staff’s perception of the new smart HR system. Fourth section targeted to measure the impact of smart HR services on the effectiveness of management decisions. Fifth section analyze the main reasons that motivate staff to require the upgrade to smart HR system. Last section was developed to measure the staff’s believes on the organization applicability to upgrading to smart HR system. Moreover, the online questionnaire contained open questions to take in account different perspectives and ideas.

3.3.2 Complete Survey

After analyzing the pilot survey responses, the researcher was able to recognize if the resulted data is meaningful, and if it answers the exact research’s questions and effectively measuring the hypothesis. In this stage, researcher was able to solve the questionnaire weaknesses and areas need to be modified; some questions were modified, some are deleted, and the responses of the open questions were transferred into additional question. The complete questionnaire was organized based on the same six sections with total of 31 questions as shown in (Appendix A).

3.3.3 Questionnaire Validity

The validity of the questionnaire means to what degree the designed scale measures what it is actually designed for (Parsian & Dunning, 2009). Also, validity means the inclusion of all the elements that must be included in the analysis on the one hand, and the clarity of its items and items from the other hand so that it is understood for all who use it

(Concidine, Botti, Thomas, 2005). The researcher verified the validity of the study tool through calculating the correlation coefficient between the degrees of each statement of the questionnaire to the overall degree of the axis to which the paragraph belongs. The results were as shown in Table 1

It is clear from Table 1 that the correlation coefficients between the score of each item and the total score of the study axes are all positive and statistically significant at 0.01. This means that there is a high degree of internal consistency and the correlation of the axis to its items, reflecting a high degree of validity to the scale.

3.3.4 Questionnaire Stability

The stability of the search tool is to ensure that the answer is almost the same if repeated to the same persons (Concidine, Botti, Thomas, 2005). To measure the stability of the study tool, the researcher used Cronbach's Alpha. Table 2 shows that the Cronbach's Alpha stability coefficient ranged between (0.762 and 0.954). The general stability of the study instrument was 0.883, all of which have high stability values indicating that the questionnaire has a high degree of stability, in the field application of the study.

3.4 Population and Sampling

The survey’s result will be respected and considered valuable only when it is trustworthy and demonstrative for the organization. However, the challenge facing the researchers is determining the perfect population and sample size. The sample is a portion of the total population that will represent the population’s perspectives if it selected wisely (Israel, 2013).This study will be entitled for Ministry of National Guard Health Affairs that operate in five regions across the Kingdom of Saudi Arabia in Riyadh, Jeddah, Dammam, Al Ahssa, and AL Madinah. The targeted participants are MNGHA employees from the all five regions, with a total population around 18,000 employees as shown in Appendix C.

The selected sample was targeting both male and female, with different age group, diverse qualification and background, different department such as medical and nonmedical, and including all employment levels. First, a smaller sample was chosen for the purpose of conducting a pilot survey. The questionnaire has been distributed to a sample of 75 participant with different regions and several characteristic (15 from each region).

The contribution rate was equal to 84% (63 responses received out of the 75 sample size).

Then, a web-link for the complete survey has been distributed to around 800 employees. The sample size was determined with confidence level of 95% which was equal to 500 . The received answers were equal to 547 respondents. From the 547 there were some random answers, which need to be dropped out of the results. As a final point, 502 considered as a valid response to be analyzed.

3.5 Data Collection and Analysis Procedures

The data that collected from pilot and complete survey has been passed throw validity and stability test, then exported and analyzed using the Statistical Package for Social Sciences (SPSS 19.5) to calculate ratios and use the appropriate statistical tests in order to access indicators of value that support the subject of the study. In-depth observation and testing were used to collect qualitative data. Thematic content analysis was used to analyze the qualitative data.

4 Results & Discussion

4.1 Variables of the Study Population

This study based on a number of variables related to the personal and occupational characteristics of the participants. The researcher used the frequency and percentages to represent it. The researcher classified the participants in terms of gender, age, qualifications, years of experience, nature of work, and region, which have significant indications on the study results, as well as reflecting the scientific background of the individuals of the society. Table 3 is showing the socio-demographic characteristic of the pilot and the complete sample responses.

4.2 Testing Research Hypothesis

4.2.1 Hypothesis 1

H1: “What is the relationship of job satisfaction of human resources services in terms of gender, age, qualification, years of experience, nature of work, and place of residence?”

In order to answer this hypothesis, the researcher used Pearson Test and the results are shown in Table 4

Table 4 shows that:

· There was a positive and statistically significant relationship between job satisfaction of human resources services and gender. The correlation between them was (0.410) at a level of significance (0.00) which is less than (0.05) indicating a positive and statistically significant relationship between satisfaction and gender (male and female). - There was a positive and statistically significant relationship between job satisfaction of human resources services and age. The correlation between them was (0.500) at a level of significance (0.01) which is less than (0.05) indicating a positive and statistically significant relationship between satisfaction and age, as getting older increases the job satisfaction.

· There was a positive and statistically significant relationship between job satisfaction of human resources services and educational qualification. The correlation between them was (0.631) at a level of significance (0.03) which is less than (0.05) indicating a positive and statistically significant relationship between job satisfaction and educational qualification as the higher educational qualification the more job satisfaction. - There was a positive and statistically significant relationship between job satisfaction of human resources services and experience years. The correlation between them was (0.600) at a level of significance (0.001) which is less than (0.05) indicating a positive and statistically significant relationship between job satisfaction and experience years as the more experience years the more job satisfaction.

· There was a positive and statistically significant relationship between job satisfaction of human resources services and work nature. The correlation between them was (0.598) at a level of significance (0.03) which is less than (0.05) indicating a positive and statistically significant relationship between job satisfaction and work nature.

· There was a positive and statistically significant relationship between job satisfaction of human resources services and work region. The correlation between them was (0.681) at a level of significance (0.01) which is less than (0.05) indicating a positive and statistically significant relationship between job satisfaction and region of work.

4.2.2 Hypothesis 2

H2: “Are there significant statistically differences among the study sample in the employees' awareness about the current characteristics of the human resources management system in the Ministry of Health in the National Guard according to variable

(gender, age, qualification, years of experience, nature of work, place of residence)” 4.2.2.1 Differences Related to Gender Variable

Among the study sample relating the employees’ awareness about the current characteristics of the human resources management system in the MNGHA according to the variable of gender, the researcher used (T) test for two independent sample, that present in the table 5

The results indicated in the Table 5 show statistically significant differences at the level of 0.05 and lower relating the employees' awareness of the current characteristics of the HRMS system in the MNGHA according to the gender variable. The value of T Test (-0.424) at a level of significance (0.02) which is less than (0.05) indicating statistically significant differences at the level of 0.05 or less in the employees' awareness of the current characteristics of the HRMS in the MNGHA according to the gender variable. Arithmetic averages shows that the differences were in favor of females because they got the higher arithmetic average. The researcher explains the result of this category as (females) is the most prevalent among the sample.

4.2.2.2 Differences Related to Age Variable

In order to determine whether there are statistically significant differences between the study sample in the employees' awareness of the current characteristics of the human resources management system in the MNGHA according to the variable of age; the researcher used "one way ANOVA" as shown in the Table 6

The difference was (0.438) at the level of (0.046) less than (0.05) indicating that there are statistically significant differences among the sample of the study in the employees' awareness of the current characteristics of the human resources management system in the MNGHA according to the variable of age. To determine the validity of the differences in each age group towards the direction of this axis, the researcher used LSD test, and the results are shown in the Table 7.

Arithmetic averages shows that the differences were in favor of study sample (25 – 35 years old) because they got the higher arithmetic average. The researcher explains the result that this category is the most prevalent among the sample.

4.2.2.3 Differences Related to Qualification Variable

In order to determine whether there are statistically significant differences between the study sample in the employees' awareness of the current characteristics of the HRMS in the MNGHA according to the variable of qualification; the researcher used "one way ANOVA" as shown in the Table 8

The difference was (1.238) at the level of (0.029) less than (0.05) indicating that there are statistically significant differences among the sample of the study in the employees' awareness of the current characteristics of the HRMS in the MNGHA according to the variable of qualification. To determine the validity of the differences in each age group towards the direction of this axis, the researcher used LSD test, and the results are shown in Table 9.

Arithmetic averages shows that the differences were in favor of study sample whose their

qualification is the bachelor degree because they got the higher arithmetic average. The researcher explains this result that category is the most prevalent among the sample.

4.2.2.4 Differences Related to Years of Experience Variable

In order to determine whether there are statistically significant differences between the study sample in the employees' awareness of the current characteristics of the HRMS in the MNGHA according to the variable of years of experience; the researcher used "one way ANOVA" as shown in the Table 10

The difference was (0.848) at the level of (0.016) less than (0.05) indicating that there are statistically significant differences among the sample of the study in the employees' awareness of the current characteristics of the human resources management system in the MNGHA according to the variable of experience years. To determine the validity of the differences in each age group towards the direction of this axis, the researcher used LSD test, and the results are shown in Table 11.

Arithmetic averages shows that the differences were in favor of study sample who is their experience years from 5 to 10 because they got the higher arithmetic average. The researcher explains this result that category is the most prevalent among the sample.

4.2.2.5 Differences Related to Work Nature Variable

In order to determine whether there are statistically significant differences between the study sample in the employees' awareness of the current characteristics of the HRMS in the MNGHA according to the variable of work nature; the researcher used "one way ANOVA" as shown in the Table 12

The difference was (0.270) at the level of (0.003) less than (0.05) indicating that there are statistically significant differences among the sample of the study in the employees' awareness of the current characteristics of the human resources management system in the MNGHA according to the variable of work nature. To determine the validity of the differences in each work nature towards the direction of this axis, the researcher used LSD test, and the results are shown in Table 13.

Arithmetic averages shows that the differences were in favor of study sample whose work nature (administration) because they got the higher arithmetic average. The researcher explains this result that category is the most prevalent among the sample.

4.2.2.6 Differences Related to Work Region Variable

In order to determine whether there are statistically significant differences between the study sample in the employees' awareness of the current characteristics of the human resources management system in the MNGHA according to the variable of work region; the researcher used "one way ANOVA" as shown in the Table 14

The difference was (2.752) at the level of (0.028) less than (0.05) indicating that there are statistically significant differences among the sample of the study in the employees' awareness of the current characteristics of the HRMS in the MNGHA according to the variable of work region. To determine the validity of the differences in each work region group towards the direction of this axis, the researcher used LSD test, and the results are shown in the Table 15.

Arithmetic averages shows that the differences were in favor of study sample who work in Riyadh because they got the higher arithmetic average. The researcher explains this result that category is the most prevalent among the sample.

4.2.3 Hypothesis 3

H3: “Are there significant statistically differences among the study sample in the employees' perception about the training in the Ministry of Health in the National Guard according to variable (gender, age, qualification)”

4.2.3.1 Differences Related to Gender Variable

Among the study sample relating the employees’ perception about the current training in the MNGHA according to the variable of gender, the researcher used (T) test for two independent sample, that present in the table 16

The results indicated in the Table 16 show statistically significant differences at the level of 0.05 and lower relating the employees' perception of the current training provided in the MNGHA according to the gender variable. The value of T Test (-0.593) at a level of significance (0.001) which is less than (0.05) indicating statistically significant differences at the level of 0.05 or less in the employees' awareness of the current training in the MNGHA according to the gender variable. Arithmetic averages shows that the differences were in favor of females because they got the higher arithmetic average. The researcher explains the result of this category as (females) is the most prevalent among the sample.

4.2.3.2 Differences Related to Age Variable

In order to determine whether there are statistically significant differences between the study sample in the employees' perception in the MNGHA according to the variable of age; the researcher used "one way ANOVA" as shown in the Table 17

The difference was (1.023) at the level of (0.036) less than (0.05) indicating that there are statistically significant differences among the sample of the study in the employees' perception of training in the MNGHA according to the variable of age. To determine the validity of the differences in each age group towards the direction of this axis, the researcher used LSD test, and the results are shown in the Table 18.

Arithmetic averages shows that the differences were in favor of study sample (less than 25) because they got the higher arithmetic average. The researcher explains the result that this category is the most willing to learn and train.

4.2.3.3 Differences Related to Qualification Variable

In order to determine whether there are statistically significant differences between the study sample in the employees' perception of the training in the MNGHA according to the variable of qualification; the researcher used "one way ANOVA" as shown in the Table 19.

The difference was (2.142) at the level of (0.004) less than (0.05) indicating that there are statistically significant differences among the sample of the study in the employees' perception of the current training in the MNGHA according to the variable of qualification. To determine the validity of the differences in each age group towards the direction of this axis, the researcher used LSD test, and the results are shown in Table 20.

Arithmetic averages shows that the differences were in favor of study sample whose their

qualification is the bachelor degree because they got the higher arithmetic average. The researcher explains this result that category is the most prevalent among the sample.

5 Recommendation and conclusion

5.1 Discussion - Current HRMS Model Building

This section is discussing the current implemented HRMS models and functions.

Since the researches in an employee in the same study’s organization (MNGHA), it gives a good opportunity of testing and observing the HR related processes. Figure 1 is a general representation on the existing HRMS models and functions.

5.1.1 Current Recruitment Module

As recognized by observing the current recruitment process, job seekers are able to check the vacant position, the qualification required, region of the vacant, closing date, and then, submit online through the MNGHA website: (http://ngha.med.sa/English/eServices/jobseekers/Pages/default.aspx). After submission, their information will be stored automatically in the database.

On the other hand, recruitment specialist will manually filtering and processing the vast number of applications received. They are responsible for initial screening all applications to complete any missing documents. Later on, they will manually filtering the matching candidates to start scheduling the interviews. All of those activities are consuming the recruitment department a lot of time, effort as well as raising the cost.

5.1.2 Current Workforce Management Module

Currently, in MNGHA, the workforce management module involve tracking the staff attendance, leave planning, financial benefits, and budget. For the attendance, the organization is using a biometric system, which record time and attendance in independent table in the database. Therefore, that information are not linked with the employees’ salary, which requires the Administrative Audit staff to continuously overseeing the shortage in the working hours for each employee to send it to HR department to calculate the equivalent salary deduction.

However, for the leave planning and financial benefits. All information is being processed and automatically calculated through Enterprise Resource Planning (ERP) system (ORACLE). Which as a result will facilitate the role for HR department.

5.1.3 Current Performance Management Module

Employees’ evaluation process in MNGHA is conducted in an annual base, and it is a paper-based standard form that is common to all employees regardless of their actual job duties or objectives. After filling the evaluation form, manager will attach it and submit it in ORACLE system without asking other opinion. When HR receives the form, they will decide the amount of salary increase is deserved based on his evaluation grade, which can increase the possibility of data-entry mistakes. The current process is consuming the managers’ time, and effect emotionally on the employees. However, it is not effective and rarely improve performance because it is not tailored to each employee goals and objectives, the evaluation’s criteria’s are vague and subject to subjectivity, focusing on the past only, and it is allow bias and personal judgement.

5.1.4 Current Training and Development Module

Training and Development Department is currently not utilizing the system. The processes of registration and certification are manual. The announcement of any available training is 2 weeks ahead through email with PFD registration form attachment. Interested candidates print the form, fill it manually, and get it signed by the department head. Then, go and submit the hardcopy of the form physically in the Training and Development Department. After gathering all forms, staff start filtering them to accept specific number; they are following several criteria to filter like the number of courses taking during the year, the relevance of the training topic to the candidate nature of work, and the registration time. Later on, accepted candidates informed by email. When training is completed, candidates are requested to fill paper format survey about the course, and they receive a hardcopy of the certificate signed by Training and Development Department head.

The current training process is having several issues that discovered through survey and observation. First, the training schedule and topics are not announced early to help employees arranging their schedules. Second, the registration process is manual, which consuming the candidates’ time and effort. Third, since the organization have around 18,000 employee, as a result a number of forms received is large number, which make the filtration process require more staff and time to be completed, and increase the possibilities of errors and discrimination. Fourth, a limited number of staff will benefit from the training courses provided each year due to time and budget limitation versus the large number of candidates.

5.2 Recommendation- Smart HRMS Model Building

The aim of the new smart model is to close the gaps that discovered by the survey and the observation, which can be summarized in the following areas:

· Manual processes

· Lack of awareness

· Real-time data reachability

· Inefficient training

The new smart model should be successfully implementing the modules and functions shown in Figure 2, which will be discussed in details in this Chapter.

5.2.1 Suggested Recruitment Module

MNGHA is a huge organization with five hospitals distributed across the Kingdom of Saudi Arabia. As a result, organization face a great challenge in managing the recruitment process. In order for the proposed smart HRMS to overcome the drawbacks of the existing model especially in recruitment module. It is suggested to implement two complementary procedure as shown in Figure 3.

5.2.1.1 Applicant Tracking Software (ATS)

Applicant Tracking Software (ATS) is a software that streamline the complete recruiting process and improve the HR efficiency (Drucker, 2016). ATS can offer several advantage to the organization. It is narrowing down the time needed for filtering and processing applicants to a controllable total, which will result in reducing the HR department’s costs (Quast, 2015; Weber, 2012). The ATS software is offering several important features.

One of the key feature in ATS is decreasing the undesirable applications by asking applicants knockout question, if the answer is not meeting the requirement, it will not allow completing the submission (Drucker, 2016). For example, if the position’s requirement is having PMP certificate, the first question will be whether candidate is having it or not, if the answer is No, then terminate the submission. Another feature is automatically filtering the huge application number to a manageable quantity. It is classifying and ranking candidates as qualified or unqualified based on evaluating their qualification such as education and work experience without human interactions, which minimize the discrimination possibilities. The ATS will provide a list of candidates who have the basic qualifications required, but the selection of candidates is still up to the Human Resources department after the interview and final assessment (Drucker, 2016).

It is also suggested to have a feature under the ATS, which allow applicants to access their profile, view their applications’ status and update their information (Drucker, 2016). As observed in the recruitment office, it is a time consuming to reply to each inquiry received by phone, email, or office visit.

5.2.1.2 Onboarding

Moving out from recruitment stage into the onboarding and training stage for period would help in increasing the awareness of the new employees about the organization’s environment, culture, policies, procedures, and available services. The survey result shows that majority of fresh employees with less than 5 years’ experience are not aware about the services that available in the system and didn’t receive any initial training or user guide. The most requested training was the HR Employee Self Services (ESS), followed by Portal services, mobile application, ERP modules, and lastly about the biometric attendance system.

5.2.2 Suggested Workforce Management Module

The output of the first module (Recruitment Module) is an employee who is familiar with the organization’s culture. Each employee should be managed under the workforce management (WFM) module. WFM is the umbrella that contain all employees’

performance and productivity related information, such as leave and attendance data, tasks workflow, and work scheduling (Eberhard, Polster, Schmaranz, 2011). That information are currently available separately in two independent tables in the database. The first table is for recording the attendance and timing for employees (recorded automatically by fingerprint system), the data available in this table is not linked with any table and is not effecting the payroll calculation. The second set of tables are for ERP system, where it is a collection of integrated tables like payroll, leaves, and tasks workflow.

Applying an effective WFM will enable the organization to develop Business Intelligent (BI) dashboards as shown in Figure 4. BI is a data visualization tool, that aggregate raw data from multiple sources and convert it into business analysis metrics, and meaningful real-time data through utilizing charts and graphs. This dashboard with its customizable interface will enable decision makers to make a better-informed decision and workforce analytics (Kappor, 2010; Luminiţa & Magdalena, 2009).

As recognized from the survey; more than half of the sample size, especially managers are demanding to have Business Intelligent (BI) dashboards for easily tracking the work progress and developing smart reports. Where they also believe it will increase the effectiveness of the decision. On the other hand, only 26% of the sample (majority are managers and administrators) were suggesting to link attendance with payroll for automatic calculation.

Accordingly, it is recommended to apply an effective WFM that will integrate all related tables (attendance and ERP) to have a comprehensive view. This view can be used in developing rich dashboard that will enable managers and staff to have accurate and timely information, and as a result, it will facilitate the work tracking and making decision (Kappor, 2010).

5.2.3 Suggested Performance Management Module