System Dynamic Modeling of Human Resource Planning for a typical IT organization

1. N.S. Naraharia, H.N. Narasimha Murthyb, System Dynamic Modeling of Human Resource Planning for a typical IT organization

2. 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.

3. 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?

4. 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

5. 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.

6. 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

7. 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.

8. causal loop diagrams • The primary purpose of the causal loop diagrams is to depict the causal hypothesis during model development

9. 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

10. 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.

11. Notations • 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)

13. 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.

14. Discussion • 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 ito 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.

15. Discussion • 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.

16. 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