N.S. Naraharia, H.N. Narasimha Murthyb,
System Dynamic Modeling of Human
Resource Planning for
a typical IT organization
Abstract
• This paper is a report on the study conducted to
investigate the changing dynamics of the Human
Resource Planning (HRP) systems in typical Information
Technology (IT) industries. Human Resource Planning
subsystem in an organization involves analyzing and
forecasting the talent requirements of the
organization. The main focus in the study was to
construct and develop a system dynamic model for the
human resource planning process.
• System Dynamics is used as a research vehicle to
provide useful insights for human resource planners in
arriving at the Strategic plans in achieving the strategic
plans for the organization.
HR Subsystem
• The human resource planning subsystem in an IT
organization is faced with the challenge of matching
supply and demand.
• The human resource planners need to address cultural
and technological issues in a global, market driven,
flexible strategic planning for the human resource.
• Integration of the IT organization with the eco system is
crucial for deriving optimal plans for managing human
resources.
• How does this compare to the Hospitality industry?
Concerns
• The top three concerns of the top
management in a Information Technology
product and services companies are managing
the labour cost, managing risk and rapid pace
of technology changes requiring quick skill
transformation and adaptation.
• What do you think the top concerns are for HR
executives in the Hospitality industry
• Human Resource Planning can be defined as a
systematic analysis of Human Resource needs
in order to ensure that correct numbers of
employees with the necessary skills are
available when they are required. When a
company prepares its planning program, it
should bear in the mind that their staff
members have their objective they need to
achieve.
Human resource forecasting
• Human resource forecasting of demand and
supply, using statistical techniques or
mathematical models are commonly used.
• There has been a number of attempts by both
academia and the industry practitioners to
develop human resource planning
methodologies and approaches to address the
specific issues of planning in organizations
System dynamics models
• System dynamics models expose the dynamic
characteristics of a project or a set of projects.
Important variables associated in the system are
captured in the modeling process. The variables vary
along the timeline and the system behavior would
consequently change. To respond to such changes, one
has to thoroughly understand quantified impacts of the
changes of leading indicators (variables).
• The different variables in the system are interrelated to
each other in the feedback structure. These
relationships can be represented diagrammatically to
portray the system structure.
causal loop diagrams
• The primary purpose of the causal loop
diagrams is to depict the causal hypothesis
during model development
Stock and Flow diagrams
• As with a causal loop diagram, the stock and flow
diagram shows relationships among variables
which have the potential to change over time.
• The main purpose of the flow diagram is to
represent the detailed flow structure of the
system in terms of the fine policy structures so as
to facilitate the development of the mathematical
model for simulation.
• Current workforce levels vs future workforce
levels
Modeling Approach
• Existing model to predict HR requirements, career
paths for an individual in the organization,
whether specific problems are identified, how
many to be recruited at the junior most level,
promotion of an individual from one level to
another, how many individuals need to be hired
for higher levels in the structure, uncertainty
factors from supply and market side, level of
attrition and retention strategies the
organization is adopting.
Notations
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Stock Variables
NOLi : Number of employees present at Level i, where i = 1 to 5
Flow Variables
NOHi : Number of employees being hired into Level i at a given time period, where
i = 1 to 5
NO Pij: Number of employees being promoted from Level i to Level j at a given time
period i = 1 to 5, j = 1 to 5 and necessarily j > i
NO Qi: Number of employees quitting or leaving the company from Level i at any
given time period (where i = 1 to 5)
Converter Variables
Rij: Number of employees required for present projects at level i and project j
where i = 1 to 5 and j = 1 to 2
RAij: Ratio of number of employees at Level i to number of employees at Level j
where i = 1 to 5 and j = 1 to 5 and necessarily j < i
A Li: Attrition at Level i (where i = 1 to 5)
H to P j: Hiring to Promotion Ratio for Level j ( where j = 2 to 5)
Discussion of Results
• The Model constructed for a typical IT organization with 5 Cadre levels,
was simulated with the initial values in the Base case scenario.
• The stocks of the model in terms of the employees at level i at a given
period was assumed reasonably.
• The flow variables were defined based on the processes of hiring,
promotion, quitting through voluntary separation and resignation. The
converters variables arise from the demand for projects at different levels.
• The demand scenario for the human resource considering the present
projects and planned projects were created, using typical values for the
converter variables.
• The control variables were defined .to stipulate the cadre structure in the
typical organization expressed as ratio of stocks at various levels with
reference to other levels.
• The attrition rates at different levels were assumed based on typical
percentage values observed as a general trend in the IT industry.
• The hiring to promotion ratio was considered as the converters in the
model.
Discussion
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The results of the model, for the input data set as depicted in the scenario 1, were
obtained graphically after the simulation run.
The graph (a) indicates the linear growth of the stocks, at different levels on a
quarter to quarter basis. The model output in (b) gives the number of hires at
different levels, considering the dynamics of the human resource.
The pattern of hiring in a quarter to quarter can be desired as policy variable using
this output.
Similarly, the output figure 3 give the policy input for HR planners, to decide on the
numbers to be promoted.
This is based on the dynamics of flow of the human resource stocks from level i to
level j.
The figure 4 indicates the outflow of stocks in terms of number of quitting on a
quarter to quarter periods. This graphical pattern at levels 1 and level 2 show an
increasing trend, as would be expected in a typical IT organization. This is to be
expected as the attrition rates are higher at lower cadres.
This corroborates the practicalities in the Industries.
Discussion
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The attrition rates being lower at the higher grades, the figure 4 indicates constant
slope. This again corroborates the evidences as seen in practice in the typical IT
organizations.
The graph patterns for stocks, hires, promoted and leaves of human resource were
identical for all the sets of input data.
The experiments were repeated for trial runs, for input condition of scenario 2
(The assumed values of variables given in table 2 : Attrition Rates Assumed With
Respect To Base Case Scenario) The results for Scenario 1 and scenario 2 for all
the runs are tabulated as an excel output sheet. The excel output sheet shown,
gives the stocks and flows at the end of the simulation run. The graphical output
and the excel output sheets will be of great help to the decision makers in studying
the effect of the dynamics of the human resource flow in the organization.
The stock status of the human resources, at equilibrium is depicted in the output
graphs.
The results of the study will be useful for the HR planners in framing the strategic
human resource plan. The system dynamics model once constructed will help the
planners in repeatedly studying the effects of supply and demand uncertainties on
the organizational human resources.
Conclusion
• This paper has demonstrated the capability of
the System Dynamics modeling framework to
model the human resource planning process.
The System dynamic model developed in this
case study can help any medium IT
organization in the dynamic human resource
planning, in response to Supply and demand
uncertainties