WORKLOAD MEASUREMENT USING DIARY SAMPLING METHOD FOR HUMAN RESOURCE REQUIREMENT PLANNING: CASE STUDY AT PT. JASA MARGA (PERSERO)



Similar documents
PT Jasa Marga (Persero) Tbk (JSMR) : Company Profile and SWOT Analysis

Charts, Tables, and Graphs

Chapter 10. Key Ideas Correlation, Correlation Coefficient (r),

16 Learning Curve Theory

ANALYSIS OF TREND CHAPTER 5

Nominal and Real U.S. GDP

1. What is the critical value for this 95% confidence interval? CV = z.025 = invnorm(0.025) = 1.96

Outline. Definitions Descriptive vs. Inferential Statistics The t-test - One-sample t-test

Module 3: Correlation and Covariance

Confidence Intervals for Spearman s Rank Correlation

Fixed vs. Variable Costs

MERCER S COMPENSATION ANALYSIS AND REVIEW SYSTEM AN ONLINE TOOL DESIGNED TO TAKE THE WORK OUT OF YOUR COMPENSATION REVIEW PROCESS

Independence Day 2016 Holiday Period Traffic Fatality Estimate

CHAPTER 05 STRATEGIC CAPACITY PLANNING FOR PRODUCTS AND SERVICES

Job Sharing for Non-Academic Staff Policy

(More Practice With Trend Forecasts)

In order to describe motion you need to describe the following properties.

Models of a Vending Machine Business

Case Study: Alex Charter School Gordon Johnson, California State University, Northridge, USA Raj Kiani, California State University, Northridge, USA

Assessing Research Protocols: Primary Data Collection By: Maude Laberge, PhD

THE UNIVERSITY OF CHICAGO, Booth School of Business Business 41202, Spring Quarter 2014, Mr. Ruey S. Tsay. Solutions to Homework Assignment #2

Master of Business Administration

New Year Holiday Period Traffic Fatality Estimate,

Measures of WFM Team Success

Chapter 7 Factor Analysis SPSS

UNIVERSITY OF MUMBAI

INTERPRETING THE ONE-WAY ANALYSIS OF VARIANCE (ANOVA)

SPSS Tests for Versions 9 to 13

1. CORPORATE SUPPORT SERVICES DEPARTMENT - HUMAN RESOURCES DIVISION

Risk and return (1) Class 9 Financial Management,

7. Comparing Means Using t-tests.

STRATEGIC ALIGNMENT AND CAPACITY BUILDING FOR THE HR COMMUNITY

y = a + bx Chapter 10: Horngren 13e The Dependent Variable: The cost that is being predicted The Independent Variable: The cost driver

Examining Motivation Theory in Higher Education: An Expectancy Theory Analysis of Tenured Faculty Productivity

Lean Six Sigma Analyze Phase Introduction. TECH QUALITY and PRODUCTIVITY in INDUSTRY and TECHNOLOGY

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number

Time series analysis in loan management information systems

Lesson 1: Comparison of Population Means Part c: Comparison of Two- Means

Spreadsheet software for linear regression analysis

Week TSX Index

Budgetary Planning. Managerial Accounting Fifth Edition Weygandt Kimmel Kieso. Page 9-2

table to see that the probability is (b) What is the probability that x is between 16 and 60? The z-scores for 16 and 60 are: = 1.

Importance of Information Technology in Reaching HR Effectiveness: Example of Local and International Banks in Russia

APPRAISAL POLICY AND PROCEDURE FOR SUPPORT STAFF 1

Lin s Concordance Correlation Coefficient

Testing for Granger causality between stock prices and economic growth

Forecasting the first step in planning. Estimating the future demand for products and services and the necessary resources to produce these outputs

Chapter 13 Introduction to Linear Regression and Correlation Analysis

JOB DESCRIPTION. Starting at 16,945 per annum with progression to 19,509 per annum, pro rata for part-time

Higher Diploma Programme in Financial Services. Syllabus

JOB DESCRIPTION. 5. ORGANISATION CHART: Reports to the Institute of Medicine Administrator. Institute of Medicine Directors

HUMAN RESOURCE MANAGEMENT

PROJECT MANAGER. Grade: Salary:

LEARNING OFFICER (80%FTE) EIGHTH IN THE EAST Ref: SC2752

1 Define Management. Explain Mintzberg Managerial Roles. 12M

Chapter 2 Theoretical Framework JOB SATISFACTION OF EMPLOYEES

Title: Lending Club Interest Rates are closely linked with FICO scores and Loan Length

EFFECTS OF INFORMATION TECHNOLOGY ON FIRM PERFORMANCE: DO SMALL BUSINESS OWNERS BELIEVE IT?

Data Analysis, Research Study Design and the IRB

Simple linear regression

Forecasting Methods. What is forecasting? Why is forecasting important? How can we evaluate a future demand? How do we make mistakes?

CORRELATION ANALYSIS

The Marketing Mix Strategy in Influence to the Competitive Advantage

Formula for linear models. Prediction, extrapolation, significance test against zero slope.

RISK ANALYSIS IN FEASIBILITY STUDY OF BUILDING CONSTRUCTION PROJECT: CASE STUDY - PT. PERUSAHAAN GAS NEGARA INDONESIA

HOW DO I GET MORE MONEY?

Confidence Intervals for One Standard Deviation Using Standard Deviation

Higher Diploma Programme in Business and Human Resource Management. Syllabus

Regression Analysis: A Complete Example

(AA12) QUANTITATIVE METHODS FOR BUSINESS

Simple Predictive Analytics Curtis Seare

Evaluation Human Resourches Information System (HRIS) The University Of Bina Darma Using End User Computing Satisfaction (EUCS)

Simple Linear Regression Inference

Module 5: Multiple Regression Analysis

Chapter 7: Simple linear regression Learning Objectives

SIMPLE HRM SOLUTION FOR THE MOST COMPLEX HR PRACTICES

Statistical Rules of Thumb

17. SIMPLE LINEAR REGRESSION II

11. Analysis of Case-control Studies Logistic Regression

University of Essex. Term Paper Financial Instruments and Capital Markets 2010/2011. Konstantin Vasilev Financial Economics Bsc

WEB APPENDIX. Calculating Beta Coefficients. b Beta Rise Run Y X

Mario Guarracino. Regression

Part 2: Analysis of Relationship Between Two Variables

Control Charts - SigmaXL Version 6.1

Executive Master's in Business Administration Program

2) The three categories of forecasting models are time series, quantitative, and qualitative. 2)

Part 1 : 07/27/10 21:30:31

Module 5: Statistical Analysis

MM5002 Accounting. MBA Programme. January 2014 MASTER OF BUSINESS ADMINISTRATION SCHOOL OF BUSINESS AND MANAGEMENT YEU50.

Using R for Linear Regression

Premaster Statistics Tutorial 4 Full solutions

QUANTITATIVE METHODS. for Decision Makers. Mik Wisniewski. Fifth Edition. FT Prentice Hall

Transcription:

WORKLOAD MEASUREMENT USING DIARY SAMPLING METHOD FOR HUMAN RESOURCE REQUIREMENT PLANNING: CASE STUDY AT PT. JASA MARGA (PERSERO) Aurik Gustomo School of Business and Management, Institut Teknologi Bandung Bandung, West Java, Indonesia E-mail: aurik@sbm.itb.ac.id Jann Hidajat Tjakraatmadja School of Business and Management, Institut Teknologi Bandung Bandung, West Java, Indonesia E-mail: jannhidajat@sbm.itb.ac.id Teuku Jeffry Farizal Head of Human Resource Planning Department, PT. Jasa Marga (Persero) East Jakarta, Indonesia ABSTRACT PT. Jasa Marga is state-own company which conducting highway network and maintaining all highway in Indonesia. Since 1998, this company developed competence based human resource management (CB-HRM). To support implementing CB-HRM, PT. Jasa Marga also identify human resource requirement to make operations efficiently. This research project use diary sampling method. Diary sampling is tool to collect data of employee activities during work-hours. Each employee was asked to fill in activity form by her/his self. After completing observation activities for ten days, these data was processed using workload analysis software. The result of this software is job workload for one year. Job workload will be used to calculate number of employees requirement. And based on this calculation in this year, this data will be used to predict how many number of employees for each job is required for next five years. KEY WORDS: Workload, Diary Sampling, Human Resource Planning 1. Introduction PT. Jasa Marga has designed integrated human resource management system (I-HRMS) since 1998. Integrated-HRMS have to be able to guide and improve developing human resource effectively. This company hope their employess have ability to create adding value. Employees have to give service excellent for their customers whom using highway in Indonesia. Figure-1 show the concept of IHRMS. Using I-HRMS we can decide, for instance employee requirement, selection and recruitment plan, HR development plan, salary and incentive system, and performance assesment Workload information is method to calculate employee quantity requirement. Workload is important factor to determine policy on HRM system, e.g. employee requirement planning, together with job analysis to design salary system. Last but not least is to allocate job task and responsibility. Workload terminolgy refer to time parameter. It s mean that percent of using working time effectively by employees during his/her work hour (Niebel, 1999). Workload not only calculate spending time for productive work but aslo included human aspects, e.g. fatique, personal requirements, and unavoidable delay. This factors is called allowances (Barnes, 1989). 1

W O R K L O A D Recruitment Salary and Incentive System Career System Job Profile and Employee Profile Performance System HR Development Selection Figure-1: Concept of Integrated Human Resources Management Source: Tjakraatmadja, J.H., Gustomo, A., Widyanti, A., Putro, U.S. (2). Pengukuran Beban Kerja Karyawan PT Jasa Marga (Persero). LAPI ITB Project Report. 2. Research Methodology For non-routine job, e.g. office work, administration, managerial work, researcher, and engineer, is difficult to measure spending time for his/her work. The distribution of spending time for this job can be measured using observation while his/ her work hours for long time. However this method isnot efficient for observer. To cover this problem, work sampling is efficient approach to measure workload for this job types. Work sampling is method to measure and record job activities randomly with specific time interval for representative employee(s). Definition of work sampling contain two main articulation: 1. Choosing job holder sample If there are only few job holder in one job, it s will be valid data if all job holder can be observed. But if not possible, we can take some job holder as sample data to be observed. 2. Choosing time interval for observation Observation will be conducted based-on determination of time interval. As long as possible observation can be done for each this time interval for employee sample. But usually maximum number of observation is not more than 2/3 possible observation frequent total. Workload output have to be able to represent work load for one year. But in practice, its not possible to observe job activities over one year. So, workload which be resulted during observation days have to convert to one year workload using load rating factor. One year workload output which be resulted based-on respondent measurement can generalize as job workload. This job workload will be used to calculate ideal number of employees. And based on this calculation in this year, this data will be used to predict how many number of employees for each job is required for next five years. Prediction model consider factors affected workload fluctuation. 2.1. Diary Sampling Method This research use diary sampling method to observe job activities. In diary sampling method, each respondent be given trust to self fill-in observation sampling form on observation time. Respondent was asked to record and fill his/ her activities every 15 minutes during work hours. 2

Each respondent have been given diary book that contain all possible activities. So, each respondent only fill-in this diary book by using tally in appropriate activity at that observation time This research aim to show how diary sampling method implemented. So, we will focus only for one job, is office administration in HR department at Jagorawi Branch Office of PT Jasa Marga. 2.2. Data Calculation Number of office administration employees is six. This research take two employees as respondent. Work sampling was conducted for two weeks. Output of this observation is percent of productive (p) for two weeks (ten work-days). Before continuing calculation until get job workload, this data have to pass on statistical tests. In work sampling method, they have two kind of statistical test, are homogenity test and sufficient test. 2.2.1 Statistical Test 2.2.1.1 Homogenity Test Control limit will be determined using formula: BKA = p + 3 p(1-p) 3 BKB = p - 3 p(1-p) 3 BKA = upper limit BKB = lower limit p = productive average 2.2.2. Job Workload Calculation Steps to calculate workload in sampling method are: 1. Calculate percent of productive average percent _ of _ productive _ perday p = number _ of _ days 2. Calculate normal workload (Bk-n) for two weeks BKn[2 MINGGU] = p x r BKn = normal workload p = productive average r = rating factor rating factor is factor to convert respondent workload to be workload average. Workload average describe workload for employee who has average ability in skill and effort. Rating factor for each respondent was assessted by employee superordinat. 3. Calculate normal workload (Bk-n) for one month BKn [1 BULAN] = BKn[2 MINGGU] x { (k1 x a) + (k2 x b) + (k3 x c)} k1 = conversion factor for daily high load K2 = conversion factor for daily avg load 2.2.1.2 Sufficient Test Number of data requirement will be determined using formula: (1 p) N p k3 a b c = conversion factor for daily low load = percent of high load in one month = percent of avg load in one month = percent of low load in one month With: N = min. data requirement p = productive average This sufficient test use 1 for significant level and 95 for confidence level. All parameter values above was determined by researcher through conducting interview with head of human resource department (employee super-ordinate). 3

. Calculate normal workload (Bk-n) for one year BKn [1 TAHUN] = BKn [1 BULAN] x { (k x q) + (k5 x r) + (k6 x s)} k = conversion factor for monthly high load K5 = conversion factor for monthly avg load K6 = conversion factor for monthly low load q = percent of high load in one year q = percent of avg load in one year r = percent of low load in one year All parameter values above was determined by researcher through conducting interview with head of human resource department (employee super-ordinate). 5. Calculate standard workload (BK) for one year BKi [1 TAHUN] = BKn [1TAHUN] x (1 + L) BKi L = workload/ year for employee-i = allowances factor 6. Calculate job workload Formula: BK [JABATAN] = BKi [1 TAHUN] / N BK [JABATAN] = Job workload N = Number of respondent 2.2.3 Determining Employees Requirement J d = (J x BK) / t = ideal number of employees J d J = number of employees existing t = conversion factor to consider adding employee to determine t parameter value, factors to consider is based-on benefit cost ratio calculation between adding or no adding employee. Based-on discussion with counterpart team of PT Jasa Marga, t-value was determined 1,2. 2.2. Prediction of Employee Requirement First step to predict employee requirement is to find main factor(s) affected increasing workload. This research identify first factor will be attempted is traffic volume. This hypothesis will be tested using correlation test between average workload in every office branch with traffic volume in every office branch. Table-1 below show that s data and figure-2 show plot data and correlation level for two variables. This test show that regression coefficient, R 2 =.9268. Its mean that there is significant correlation between traffic volume with workload per branch office. So that way we can use traffic volume to predict number of employee requirement. Using time-series model, traffic volume will be forecasted for next five years. Based-on forecast result, will be determined conversion factor to predict number of employee requirement. For example : Traffic volume at Jagorawi highway in 23 = 29. cars Forecast result for traffic volume at Jagorawi highway in 25 = 3. cars So, increasing workload conversion factor at 25 = 3./29. = 1,3 Finally, we can predict number of employee requirement using formula: J i = J x BK x K i J i = number of employees year-i J = number of employees year- BK = workload year- = conversion factor for year-i K i

Table-1 Average workload and traffic volume per office branch No 1 2 Data Type Num of Employee (N) Avg workload (avg BK) 3 N x avg BK Traffic Volume B-Type Branch Office SEMA RANG PALI KANCI MEDAN PADA LUENYI SURA BAYA A-Type Branch Office TANGE RANG JAGO RAWI CIKAM 12 169 237 8 525 587 815 77 93 91.35 113.26 985 85.8 15. 1255 93.3 22.9 173 5865 2532 3986 81.23 393.1 2 11293 81.5 27.85 766 15966 9 88.8 517. 758 2389 82.33 67.98 5717 28327 PEK 89.7 692.6 697 27921 CTC 88.17 831. 3821 5639 3 Volume lalu Lintas 5 5 35 3 25 2 15 1 5 Perbandingan volume lalin dengan N x Beban Kerja Rata- Rata y = 51.3x - 57113 R 2 =.9268 1 2 3 5 6 7 8 9 N x Beban Kerja Figure-2 Graph of traffic volume vs workload for every branch office 3. Data Result and Analysis 3.1 Data Result Process of data calculation use software was created by Gustomo, Aurik (23). Data calculation outputs are: For respondent-1: BKn[2 MINGGU] = 86,87 BKn[1 TAHUN] = 8,2 and for respondent-2: BKn[2 MINGGU] = 8, BKn[1 TAHUN] = 75,9 BK[JABATAN] = 76,55 Its mean that workload for office administration job in HR Department of Jagorawi Office Branch at PT Jasa Marga is 76,55. 5

3.2. Number Employees Calculation in 23 J d = ROUNDUP [(J x BK) / t] With data: J = 6 employees BK = 76,55 t = 1,2 so, J d = Its mean that actually number of employee requirement for office administration job in HR Department of Jagorawi Office Branch at PT Jasa Marga is employees only. 3.3. Prediction of Employee Requirement 3.3.1 Forecasting of Traffic Volume Figure-3 show graph of traffic volume in 1999 22. Regression linier approach result the correlation coefficient is,9951 or there is strong correlation between two variable. So, function: y= 18.131x + 21.365, can be used to predict traffic volume for next years. Table-3 show resulting of traffic volume prediction for 2 28. Using this forecast and refer to example formulation to calculate increasing workload conversion factor in 2.2., the value of increasing workload conversion factor show in table- below. Table- Workload conversion factor Year Conversion Factor 2 1.662 25 1.132 26 1.1986 27 1.2679 28 1.3399 3.3.2 Prediction of Employee Requirement Finally, we can predict number of employee requirement using formula: J i = J x BK x K i (look at again in 2.2.). Table-5 below show resulting of employee requirement prediction for 2 28. Table-5 Number of employees requirement for 2-28 Year Workload Number of Employess 2 81.62 5 25 86.69 5 26 91.76 5 27 96.82 5 28 11.89 6 Jagorawi 3 25 2 15 1 5 1 2 3 Series1 Linear (Series1) y = 18131x + 21365 R 2 =.9951 Figure-3 Data plot for increasing traffic volume at Jagorawi highway 6

Cabang Table-3 Prediction of traffic volume for 2-28 Tahun 2 25 26 27 28 Jagorawi 2922 31151 328282 3613 365. Conclusion 1. Using work sampling method, number of employees requirement for office administration job in HR Department of Jagorawi Office Branch at PT Jasa Marga is only four employees in 23. Meanwhile, number of job holder in this job is six employees in 23. 2. In this case, traffic volume variable can be used to predict increasing job workload. 3. Number of employees requirement for 2 28 show in table below. Year Number of Employess 2 5 25 5 26 5 27 5 28 6 5. References Barnes, Ralph M. (198). Motion and Time Study: Design and Measurement of Work. John Wiley & Sons. Hidajat, T.J., Gustomo, A., Widyanti, A., Putro, U.S. (2). Pengukuran Beban Kerja Pegawai PT. Jasa Marga (Persero). Laporan Proyek PT. LAPI ITB. Niebel, B., Freivalds, A. (22). Methods, Standards, and Work Design. (22). 7 th edition. John-Wiley & Sons. New York. 7