Aging Chain used within Human Resources - HR (Netlogo)

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WHAT IS IT?

The life cycle of the employee in the company is based on the chain of Aging (Aging Chains) model proposed by John Sterman in the book Business Dynamics: Systems Thinking and Modeling for a Complex World.

Staff evolution model can map the evolution of professionals’ careers, taking into account PROMOTION and OUTFLOW along employee life cycle, from hiring up to retirement.

During this cycle there is a DELAY that makes the employee takes certain time to pass from beginner to more experienced positions. There is also ANOTHER DELAY for the employee to pass from the last employee stage, master, to finish his career at that company. The closure can be prematurely finished, along the intermediate stages.

The model was adapted from the original to allow SHORT-TERM OR LONG-TERM LEAVES, and the main consequence is the consequent delay for their evolution/promotions, causing the employee to remain longer at each stage.

Agent Based Modelling allows modelling each agent individually. For this model there is a PROBABILITY for each different agent leaving the company, as well as a different TIME for the agent to STAY TEMPORARY OUT of the company.

The model then allows the manager to perform simulations changing parameters until he gets to a number of hires that allows, through the replacement of staff, to keep company with a suitable crew to keeping running it’s services.

HOW IT WORKS

AGENTS (employees) can assume different STATUS:

Employee-Trainee (T) is true when the agent is a beginner
A common Employee (C) is true after beginners promotion
Employee-Master (M) is true after Employee promotion

When an AGENT is OUT OF THE COMPANY, status assume values as follows:

Trainee_OutOfWork (T) is true if beginner is is out
Employees_OutOfWork (C) if true if common employee is out
Masters-OutOfWork (M) is true if master is out

The system starts with all employees being trainees and no one out of company.

Number of employees hired along the year represents the quantity of new employees that are inserted in the system, in the beginning of each new year.

Along the time, the 3 groups of agents (T, M, C) age.

Comment: (fraction-1 = 0,8 means 20% will be fired (or leave definitely) and 80% remains and can be promoted - this is common in a public company

delay-promotion-1 - defines how long (years) does it takes to be promoted from T to C

Comment: (fraction-2 = 0,9 means 10% will be fired (or leave definitely and 90% remains and can be promoted . This or other value could be applied to a prived company.

delay-promotion-2 defines how long (years) does it takes to be promoted from C to M

delay-retirement - defines the number of masters that left for retirement that year

Whilst AGING,

HOW TO USE IT

select the number of new employees (trainees) are entering the company.
Than try to change fraction_1 consider a test after a period and part of them will not be promoted, only X %.
Run the model and observe the graphic.
Do the same with fraction_2
Run the model again and observe the graphic.

THINGS TO NOTICE

So, consider:

These parameters reflect the opportunity that the company offers for public workers for building a career for life in the company. Nowadays the profile of the youth follows a different behavior, they does not think of staying in the same organization for all his life.

This parameter reflects the TURNOVER of the company. In a public company should be low, a private company whose majority of workers are young this value is higher or a telemarketing firm, for example, where there is need of manpower very knowledgable.

THINGS TO TRY

The sum of parameters: delay_promotion_1 + + delay_promotion_2 delay_retirement is 35 years, time considered for general retirement in Brazil (if you are finding that the employee be a lifetime in the company).
So, consider:
delay_promotion_1 = 2; delay_promotion_2 = 4; delay_retirement = 29 years.

These parameters reflect the opportunity that the company offers for public workers for building a career for life in the company. Nowadays the profile of the youth follows a different behavior, they does not think of staying in the same organization for all his life. With 29, see what happens to the graphic.

Now, reduce this parameter to 10 and see if the graphic shows the same performance. Compare both graphics and final numbers and the applicaton stops.

Do changes with fracions and compare graphics and final classes of employees. Observe how many employees are still working in the company, after some years, depending on the paramenters.

Change Fractions 1 and 2 that represent the percentge of people who are expected to leave the company. Try 20% for promotion from beginners to common employees and 10% for promotion from common employees to masters.

Remmember:

This parameter reflects the TURNOVER of the company. In a public company should be low, a private company whose majority of workers are young this value is higher or a telemarketing firm, for example, where there is need of manpower very knowledgable.

Change Fraction T, C and M. These parameters indicate the percentage of removal.

These parameters reflect two things: 1) the state of health of the population (employees), if a job quite unhealthy this value can be high. Former coal mine 2) if a majority of employees in new age woman is depending of the country this value may represent the birth rate. Ex factory making clothes in China vs. Brazil x Bolivia etc …

Change Delay T, C and M, that indicate the time of removal.

These parameters reflect two things: 1) high if the health status of the population is very poor, an important point may be the HDI of the region. 2) if it is a University staff may be away for a long time due to Masters, PhDs, Post-docs or Sabbatical year in some cases.

EXTENDING THE MODEL

This model can be extended to the Market field, to monitor consumers behaviour.
Suppose instead of employees you have class of consumers.
As consumers enter a fidelity programme they receive a white status. As long as they consume, they become more confident. However, they can stop to consume during a period and also can leave the programme.

NETLOGO FEATURES

Marketing Consumers simple model (with aging chains) http://api.adm.br/netlogo/Marketing/## RELATED MODELS

Organizational Responsibility Model (Passos, Chamovitz & Theodoulidis, 2013)

CREDITS AND REFERENCES

Thanks for Uri Wilensky

References:

NetLogo website. http://ccl.northwestern.edu/netlogo/,

PASSOS, G.F. CHAMOVITZ, I. Modelo De Responsabilidade Organizacional, Aplicado Em Empresa Pública De Tecnologia Da Informação E Fundamentado Em Dinâmica De Sistemas. In: IX Congresso Nacional de Excelência em Gestão – CNEG 2013, 2013, Rio de Janeiro – RJ.

PASSOS, G.F. CHAMOVITZ, I., THEODOULIDIS, B. Organizational Responsibility Model: Dealing with demand for services higher than installed capacity. Article accepted for presentation at the IEEE SMC 2013 Conference (SMC: Systems Science), October, 2013.

STERMAN, J. Business dynamics: systems thinking and modeling for a complex world.Boston, MA: Irwin McGraw-Hill, 2000

CC BY-NC-SA 3.0

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

CC BY-NC-SA 3.0

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

CC BY-NC-SA 3.0

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at uri@northwestern.edu.