Markov Analysis and Forecasting

Markov Analysis and Forecasting

Internal labor market description

Job stability

Job stability refers to the degree of retaining ones functionality in a department or unit. For instance, remaining in full time sales, part time sales, assistant sales manager position or the regional managers position (Heneman, 2006).  According to the probability figures, DoortoDoor sports Equipment Company experienced 50% to 80% employee stability.

Exit (turnover rates)

Turnover rates refer to the degree of employees exit from the company or shifts to other institutions for rudeness, poor performance, low appraisal ratings, undervaluing employees, lack of mentorship, poor decision making and ability inadequacy (Heneman, 2006). The company experienced turnover rates ranging from 5% to 35%.

Promotion paths

Promotion refers to the shift from a lower position to a higher position due to excellent performance ratings, proper decision making, mentorship and coaching (Heneman, 2006). In accordance to DoortoDoor sports Equipment Company, there are three functional levels.  Shifts in position only occurred within assistant sales manager to regional sales manager (ASM to RSM), full time sales people to assistant sales manager (SF to ASM) and part time salespeople to assistant sales manager (SP to ASM).

Transfer paths

Transfer refers to limited movement of employees within the same functional level (Heneman, 2006).  Movement only occurred within the first level where full time sale persons moved to the part time sales unit (SF to SP) and where employees from the part time sales unit moved to the fixed sales unit (SP to SF).

Demotion path

Demotion refers to the shift from a higher function to a lower function in an organization. In DoortoDoor sports Equipment Company, only two movements occurred, that is, Regional sales manager to assistant sales manager (RSM to ASM), assistant sales manager to part time sales (ASM to SP) or assistant sales manager to full time sales unit (ASM to SF).

Number forecast in the different DoortoDoor job groups in 2016

Transition probability matrix

Job category                        level SF SP ASM RSM Exit
Sales, full time (SF) 1 0.50 0.10 0.05 0.00 0.35
Sales, part time (SP) 1 0.05 0.60 0.10 0.00 0.25
Ass sales mgr (ASM) 2 0.05 0.00 0.80 0.10 0.05
Regional sales mgr (RSM) 3 0.00 0.00 0.00 0.70 0.30

 

In order to get the probable workforce outcome, pick the employee column figures and multiply by the probability figures which will result in the workforce availabilities. Sum up the figures at the end of the column to get SF (260), SP (140), ASM (80), RSM (26) and Exit (224). The employees amounting to two hundred and twenty four is predicted to leave the company and will not be available for 2016 operations.

Available Forecast

 

Job Category Current Workforce        SF SP ASM RSM Exit
SF 500 250 50 25 0 175
SP 150 7.5 90 15 0 37.5
ASM 50 2.5 0 40 5 2.5
RSM 30 0 0 0 21 9
Sum 730 260 140 80 26 224

                                                        

The constant percentage changes are as a result of human resource frameworks and protocols which were in operation between 2015 and 2016. The probability figures enable transitional forecasting for the organizational employees over the operational period.

Possible limitations to the forecast

The following are the limitations associated with the above forecast.

Population size

It is recommended to obtain   a number of employees exceeding twenty for each function in the organization as the figure is used in calculating transitional likelihoods. In cases where the numerator deviations are small, minute population sizes will have significant deviations in the transitional probability figures (Carpinone, 2015). Thus, when forecasting future occurrences, manipulating probable change on minute population’s results in unstable forecasting which may not be reliable in decision making.

Interval movement ignorance

Markov analysis only concentrates on two periodical extremes, that is,  t and t+1. It only looks at the workers positional changes at the start and end of the operational period. It ignores the fact that constant movements occur in between the operational period and thus minimizes reliability. In order to reduce the unnoticeable movements, the gaps between the periods should be minimized, for instance, less than two years.

Combining functions

An organization is characterized by an integration of different functions which operate to reach and attain similar goals. When determining the probable future outcomes, extreme functions may be used, for instance, Regional Senior Management and Sales Representatives part time and full time. Where these positions are distinct and have a difference of more than one level, utilizing the figures may disagree with stipulations and visions of the human resource and planning function (Carpinone, 2015).

Outcome reflection

The resultant probabilities only show the likely movements of the workers in the organization. It fails to outline comprehensively the reasons for the positional changes. In calculating the probable forecast, all the workers are assigned the same probability of positional change. In reality, management takes into account several factors before making any decision to allow transfer, promotion, demotion or exit. Some of these factors include punctuality, job quality, personal presentation review results, and positive client response and individual appraisal outcomes (Carpinone, 2015).  Including these functions in decision making will differentiate the probabilities of positional change among the organizational employees

References

Carpinone, A., Giorgio, M., Langella, R., & Testa, A. (2015). Markov chain modeling for very-short-term wind power forecasting. Electric Power Systems Research, 122, 152-158.

Heneman−Judge: Staffing Organizations. (2006). Markov Analysis and Forecasting Availabilities. Mc Graw Hill Companies.

 

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