Developing a Strategic Framework for Enhancing Employee Engagement and Retention

 

Kirana Erlinda Yasmin1*, Madju Yuni Ros Bangun2, Henndy Ginting3

Master of Business Administration, Bandung Institute of Technology, Indonesia1*23

Email: kirana_erlinda@sbm-itb.ac.id1*

 

Abstract

Employee engagement is a critical focus in human resource management, particularly in industries with strategic significance such as the dairy industry in Indonesia. The Indonesian dairy industry plays a vital role in ensuring community nutrition and contributes significantly to the national economy through job creation and improving farmer welfare. As the market leader, PT Indosusu Nasional acknowledges that human resources are its primary asset and key to organizational success, while facing intense competition and high employee turnover. This study aims to analyze employee engagement at PT Indosusu Nasional, focusing on factors influencing engagement levels and their impact on employee retention. Data was collected through a survey involving employees from various departments of the company. The results in this study can be recommended to PT Indosusu Nasional as a strategy in retaining its employees are related to the company's reputation in building the company's image and conducting routine training for employees.

Keywords:

employee engagement, retention, turnover, dairy industry

 

Introduction

The dairy industry in Indonesia holds a strategic position in the national economy, contributing to both nutrition and employment. The dairy industry in Indonesia is witnessing significant strategic importance, poised for substantial growth and expansion. According to data from the Directorate General of Animal Husbandry and Animal Health of the Ministry of Agriculture of the Republic of Indonesia (Ditjen PKH Kementerian Pertanian RI), the current demand for milk in Indonesia reaches 4.3 million tons per year. However, domestic milk production is far from sufficient, as about 22.7% of the national milk demand is met from local sources, while the rest is met through imports. This discrepancy between supply and demand presents a significant opportunity for the fresh milk-producing industry in Indonesia.

Furthermore, one of the things that affects the high and low sales of products, especially in milk processing companies, is the management of human resources. Employees are one of the most important assets of an organization as they contribute to the growth and success of the organization (Danish & Usman, 2010). This contribution is made through engagement and will go beyond satisfaction and commitment to the desired effectiveness of the organization.

In this research, comparisons were made between dairy industries companies listed on IDX. Companies that are compared with PT Indosusu Nasional are PT Diamond Food Indonesia Tbk (DMND), PT Cisarua Mountain Dairy Tbk (CMRY), PT Campina Ice Cream Industry Tbk (CAMP). In such a competitive environment, it is crucial for companies to focus on growth, profitability, and market share. Despite its historical market leadership, the company faces contemporary challenges requiring thorough research and evaluation to maintain and enhance its position in the competitive dairy industry.

Analyzing external factors is crucial for understanding the dynamics that influence a company's performance. This research conducts a comparative analysis of various companies in the dairy industry to determine PT Indosusu Nasional's competitive standing. PT Indosusu Nasional demonstrates superior performance compared to the average of three other dairy industry companies analyzed. Despite having the fewest employees among them in 2022, PT Indosusu Nasional achieves high sales per employee.

 

Table 1. Sales and Number of Employee Each Companies

 

PT Indosusu Nasional

PT Cimory

PT Campina

PT Diamond

Average

Sales

Rp7,656.30

Rp6,378.00

Rp1,129.00

Rp8,461.77

Rp5,906.27

Number of Employee

970

3527

1357

7224

3,269.5

Sales per Employee

7.89

1.81

0.83

1.17

2.93

 

Data, PT Indosusu Nasional has experienced decrease in profit per employee profit per personnel cost.

Figure 1. Profit per Employee of PT Indosusu Nasional from 2018-2022

 

This indicates that the company has not maximized the efficiency of its workforce in generating profits because there is no increase in profit per employee per year.

 

Figure 2. Profit per Personnel Cost of PT Indosusu Nasional from 2018-2022

 

A declining ratio may imply that a large portion of the company's revenue is allocated to personnel costs, necessitating a review of the cost structure or exploration of ways to improve productivity. This indicates that the company is generating less profit relative to personnel costs over time.

In order to comprehending and analyzing external factors, investigating into internal factors is crucial for thorough examination. When analyzing the decline in profit per employee and stagnant profit per personnel cost, it becomes evident that there are underlying issues within the company's human resources domain.

 

Table 2. Employee Turnover Ratio

Decription

Unit

2022

2021

2020

Employee Turnover Ratio

%

9.46

3.24

5.67

 

Particularly in 2022, there was a significant increase in the turnover ratio compared to previous years. High employee turnover has an impact on the quality and quantity of production (Wu, 2012). It is important to discuss turnover importance because it has a relationship with the organizational performance (Ingersoll, 2001).

 

Methods

Participants

This research uses a quantitative approach in which data collection is carried out by distributing questionnaires to research samples. The number of participants in this study was 100 respondents consisting of several departments in the company.

Measures

This research wants to measure how much the level of employee engagement with the company is seen from several dimensions, where there are 8 dimensions that will be identified in this study. Where 8 dimensions consist of brand, leadership, performance, the work, the basic, company practices, business problems, people problems. Each of these dimensions consists of three sub-drivers (indicators) which are represented in the questionnaire questions. The number of items on the questionnaire is 30 items with 6 possible ratings using Likert-scale.

 

Results and Discussion

In this research, measurement models with reflective indicators are evaluated by convergent validity (AVE). AVE value> 0.5, the variable is said to be ideal, meaning that the indicator is valid to measure the construct it forms. The Cronbach's Alpha parameter was used in this study for consistency reliability testing, with a recommended value greater than 0.7. Composite reliability in PLS is carried out to test or measure how consistent the measuring instrument used is. A construct can be declared reliable if it has a composite reliability value> 0.70 (Ghozali, 2017). The results showed that the validity and reliability tests had met the requirements, which means that in this study each indicator is valid and reliable to measure the constructs formed.

 

Table 4. Validity and Reliability Test

Variable

AVE

Croncbach’s Alpha

CR

Company Brand

0.814

0.886

0.929

Leadership

0.794

0.868

0.920

Performance

0.625

0.875

0.922

The Work

0.672

0.819

0.892

The Basics

0.795

0.797

0.877

Company Practices

0.799

0.872

0.920

External Factors

0.784

0.703

0.833

Internal Factors

0.810

0.758

0.860

Say

0.860

0.725

0.879

Stay

0.705

0.767

0.895

Strive

0.733

0.837

0.925

 

A higher R-Square value indicates a strong predictive ability of the research model (Indrawati, 2015), showing how well the independent variable affects the dependent variable. The greater the R-Square value, the stronger the influence of the independent variable on the dependent variable.

 

Models

R-Square

Say

0.553

Stay

0.222

Strive

0.604

Table 5. R-Square Value for SEM-PLS Model

 

Hypothesis testing in SEM PLS is conducted by examining the significance value between constructs, t-statistics, and p-values. This study uses the bootstrapping method with a significance level of 0.05. A positive beta coefficient and a p-value less than 0.05 indicate a significant hypothesis. Additionally, if the calculated T value is greater than 1.660 (based on the t-table with df = N-1 and alpha 5%), the hypothesis is accepted.

 

Table 6. Hypothetical Testing

Hypothesis

Original Sample

Sample Mean

R2

T-Statistic

P-Values

Result

Company Brand -> Say

0.130

0.131

0.408

1.873

0.031

Influencing

Leadership -> Say

0.222

0.211

0.489

1.789

0.037

Influencing

Performance -> Say

0.045

0.077

0.490

0.280

0.390

Not Influencing

The Work -> Say

0.307

0.305

0.637

1.918

0.028

Influencing

The Basic -> Say

0.130

0.130

0.510

1.019

0.154

Not Influencing

Company Practices -> Say

(0.093)

(0.083)

0.209

0.928

0.177

Not Influencing

External Factors -> Say

(0.043)

(0.034)

0.204

0.553

0.290

Not Influencing

Internal Factors -> Say

0.240

0.233

0.562

2.067

0.020

Influencing

Company Brand -> Stay

0.276

0.279

0.358

2.617

0.005

Influencing

Leadership -> Stay

(0.075)

(0.076)

0.149

0.639

0.261

Not Influencing

Performance -> Stay

0.150

0.173

0.221

1.053

0.146

Not Influencing

The Work -> Stay

(0.141)

(0.146)

0.219

0.661

0.254

Not Influencing

The Basic -> Stay

0.033

0.012

0.258

0.232

0.408

Not Influencing

Company Practices -> Stay

0.059

0.059

0.184

0.501

0.308

Not Influencing

External Factors -> Stay

0.152

0.131

0.256

1.094

0.137

Not Influencing

Internal Factors -> Stay

0.219

0.239

0.336

1.233

0.109

Not Influencing

Company Brand -> Strive

0.042

0.039

0.358

0.737

0.231

Influencing

Leadership -> Strive

0.279

0.255

0.523

2.137

0.017

Influencing

Performance -> Strive

(0.077)

(0.065)

0.401

0.542

0.294

Not Influencing

The Work -> Strive

0.178

0.170

0.586

1.080

0.140

Not Influencing

The Basic -> Strive

0.229

0.242

0.563

2.040

0.021

Influencing

Company Practices -> Strive

0.035

0.036

0.343

0.384

0.351

Not Influencing

External Factors -> Strive

0.137

0.143

0.379

1.844

0.033

Influencing

Internal Factors -> Strive

0.280

0.274

0.636

2.826

0.002

Influencing

 

The bootstrapping test results for this research model show the influence of independent constructs (employee engagement drivers) on the dependent construct (employee engagement behavior). Among the engagement drivers, four engagement drivers were identified as factors influencing "Say" employee engagement behavior, 1 engagement driver was identified as a factor influencing "Stay" employee engagement behavior, and 4 engagement drivers were identified as factors influencing "Strive" employee engagement behavior, while the rest had no effect. For "Say" behavior, the significant variables are Company Brand, Leadership, Work, and Internal Factors. For "Stay" behavior, only the Company Brand variable is significant. For "Strive" behavior, the significant variables are Leadership, Basic, External Factors, and Internal Factors.

 

Discussion

The table below presents the ranking of employee engagement drivers, highlighting which drivers should be prioritized for improvement or maintenance. It is important to focus on the top-ranked drivers, especially those with lower scores, to ensure that they align with ideal employee behavior. Proper mapping of these drivers and implementation of appropriate preventive measures for critical drivers will lead to improved engagement.

 

Table 7. Engagement Drivers Ranking

Rank

SAY

STAY

STRIVE

1 (Most Influencing)

Internal Factors

Company Brand

Internal Factors

2

The Work

 

Leadership

3

Company Brand

The Basic

4 (Least Influencing)

Leadership

External Factors

 

To identify business solutions, data is mapped into a matrix correlating the current condition with engagement driver results, known as the matrix of influence and variable score (Fajar, 2017). This matrix illustrates the relationship between a company's current and anticipated conditions, with the X-axis representing the company's current condition based on average questionnaire scores, and the Y-axis representing the Beta values for each engagement driver based on engagement behaviors.

 

“SAY” Engagement Behavior Matrix

Figure 3. “SAY” Engagement Behavior Matrix

 

Based on the “Say” Engagement Behavior Matrix shown in Figure 3, it can be seen that there is one dimension in quadrant I, the dimension is the top priority (crucial) that need to be improved. The main sub-driver that needs to be improved is coaching of leadership drivers, which is represented by Q24. Hence, it is the company's top priority in improving the company with the aim of motivating employees to speak positively about the company to coworkers, relatives and customers.

 

“STAY” Engagement Behavior Matrix

Figure 4. “STAY” Engagement Behavior Matrix

 

Based on the “STAY” Engagement Behavior Matrix shown in Figure 4, the company does not face an urgent need for immediate improvements since there are no items in quadrant I (crucial). However, several items are in quadrant II, indicating high and average influence, and suggesting areas for improvement to enhance employee engagement. Data processing results show that the company brand is the only significant factor influencing "Stay" behavior. The main sub-drivers needing improvement are reputation and corporate responsibility, represented by Q18 and Q2. Thus, the company should focus on these areas to foster a stronger sense of belonging and commitment among employees.

 

“STRIVE” Engagement Behavior Matrix

Figure 5. “STRIVE” Engagement Behavior Matrix

 

Based on the "Strive" Engagement Behavior Matrix shown in Figure 5, it can be seen that there is one dimension that is in quadrant I, the dimension is a top priority (crucial) that needs to be improved. The main sub-driver that needs to be improved is coaching of leadership drivers represented by Q24. Hence, it is the company's top priority in improving the company so that employees are motivated and exert effort to achieve success in their work and for the company.

 

Conclusion

This research concludes that not all engagement drivers have a significant impact on employee engagement behaviors. Internal factors significantly influence "Say" and "Strive" behaviors, while the company brand impacts "Stay" behavior. Using a business solutions matrix, it was determined that leadership, specifically coaching, needs improvement for "Say" and "Strive" behaviors, and the company brand, including reputation and corporate responsibility, is crucial for "Stay" behavior. Enhancing these areas can positively impact the company and maintain its market leadership. Effective employee engagement and retention are vital, especially for high-performing employees, and require strategic human resoruce management.

 

References

 

Danish, R. Q., & Usman, A. (2010). Impact of reward and recognition on job satisfaction and motivation: An empirical study from Pakistan. International Journal of Business and Management, 5(2), 159.https://doi.org/10.5539/ijbm.v5n2p159

Fajar, A. (2017). The Identification of Employee Engagement Drivers of Generation X and Y at PT. Bank Central Asia, Tbk KCU Garut using Employee Opinion Survey,.

Ghozali, I. (2017). Ekonometrika Teori, Konsep dan Aplikasi dengan IBM SPSS 24 (A. Tejokusumo (ed.); III). Badan Penerbit Universitas Diponogoro Semarang.

Indrawati, P. D. (2015). Metode Penelitian Manajemen dan Bisnis Konvergensi Teknologi Komunikasi dan Informasi. Bandung: PT Refika Aditama.

Annual Report PT Campina Ice Cream Industry Tbk (2022).

https://www.campina.co.id/v4/wp-content/uploads/2023/04/AR-CAMP-2022-High-Res.pdf

Annual Report PT Cisarua Mountain Dairy Tbk (2022).

https://cimory.com/uploads/investors/attachment_VIGapq1680150126.pdf

Annual Report PT Diamond Food Indonesia Tbk (2022).

https://www.diamondfoodindonesia.com/cfind/source/files/annual-report/ar%20dmnd%20fy%202022.pdf

Bakker, A. B., & Demerouti, E. (2008). Towards a model of work engagement. Career Development International, 13(3), 209–223. https://doi.org/10.1108/13620430810870476

Deloitte. (2017). Employee engagement reimagined. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/human-capital/us-cons-engagepath.pdf

Fitz-enz, J. (1990). Getting and keeping good employees. In personnel. 67(8): 25-29.

Hewitt, A. (2015). Aon Hewitt’s Model of Employee Engagement. Retrieved August,7, 2017

Ingersoll, R., 2001. Teacher Turnover and Teacher  Shortages: An Organizational Analysis. American Educational Research Journal, 38(3): 499-534.

Salim, D (2019). Designing The Framework for Transforming The Human Resource Practices in Employee Engagement and Retention at PT Biscuit Enak Indonesia. Masters’ Final Project, Institut Teknologi Bandung.

Sinkowitz-Cochran, R. L. (2013). Survey design: To ask or not to ask? That is the question…. Clinical Infectious Diseases, 56(8), 1159-1164.

Wu, X. (2012). Factors Influencing Employee Turnover Intention:The Case of Retail Industry in Bangkok, Thailand. University of the Thai Chamber of Commerce.  

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