Human Resource planning in a Shore-based Integrated Steel Plant:
A System Dynamics Model
Dr. KR Divakar Roy
Principal
Thandra Paparaya Institute of Science and Technology
BOBBILI-535558, AP, India
divakarroy@ rediff.com
Dr. Saroj Koul
Assistant Professor
Fred C. Manning School of Business Administration
Acadia University, B4P2R6, NS, Canada
saroj.koul@ acadiau.ca
Abstract
This paper elaborates a model of Human Resource supply and demand as it affects the
productivity of a shore-based integrated steel plant using the System Dynamics method. The HR
scenario at the plant is examined over a period of ten years, during which it successfully
operated with one-third of the personnel in comparable steel plants in India. Also examined is
the optimal level of human resources necessary to ensure enhanced efficiency and productivity
levels, containing personnel, and redeploying surplus personnel through retraining and
relocation. The key parameters taken up are non-executive/executive ratio, personnel
productivity, and total workers. More precisely, it identifies policies related to (i) downsizing
personnel (ii) to decreasing non-executive/executive ratio, and (iii) improving labour
productivity and effectiveness.
Keywords: Manpower Policy, Downsizing, Labour Productivity, System Dynamics, shore-based
Steel Plants, India.
1. Background
At present the steel plant under study is being operated with one third of the manpower existing
in other comparable steel plants in India. In fact, the steel plants are now benchmarking on
manpower productivity of steel, i.e., steel produced per man-day employed. Thus the manpower
policy, obviously, is to derive a mode of downsizing. Here, SD model is used to test how long it
may take to achieve the targeted downsizing if the current situation is continued, ie., allow the
employees to retire at the mature age without any recruitment to those cadres.
2. Objectives
The manpower plan envisaged for the company aims at maintaining optimal level of manpower
to ensure enhanced efficiency and productivity levels, with a view to containing manpower,
redeploying existing surplus manpower through retraining and relocation. In view of the above,
the main focus of study is to (i) downsize the manpower, (ii) increase executive- non- executive
ratio, and (iii) improve labour productivity
2.1 Model description
The plant under study has achieved a labour productivity of 253 tonnes per man-year, which is
higher than any comparable steel plant in India. And the management aims at achieving a labour
productivity of 300 tonnes per man-year [1]. To achieve this target, the management aims at
downsizing its manpower by containing the regular manpower and eliminating the contractual
manpower. Also, the management aims at reducing the ratio of executives to non-executives in
works to 1:4 from the existing 1:8 for having effective control thus shifting the manpower
composition progressively from non-executive cadre to executive cadre. Also, management has
created a non-unionized junior officers cadre starting with 300 junior officers in 1996.
The dynamics of manpower mobility is captured in the causal loop diagram (Fig.1) and the flow
diagram (Fig.2). The manpower composition can broadly be divided into (i) executives (ii) non-
executives and (iii) ministerial staff. The direct recruitment is made in three stages for non-
executives (Technical), namely, Assistant Technician, Technician and Chargemen. Also,
Assistant technicians are being promoted as Technicians and they are in turn being promoted as
Chargemen. Also, Charge men are being promoted to Junior Officer Cadre. Executive cadres are
again being classified as (i) Front level executives (ii) Middle-level executives and (iii) top and
senior executives.
In the executive cadre, the main entry point is trainee executives. After successful completion of
the training they are placed in the cadre of front level executives and promoted to the cadres of
middle level executives and senior and top level executives.
Recruitment to the cadres of Assistant technician, technician, Chargemen and executives is
defined as a third order delay variables and are explained below:
1 a) The recruitment for lowest cadre in non-executive Technical category is Assistant
Technician cadre. After successful completion of training they are placed in that
category. Therefore, Assistant Technicians under training (ATECUT) is defined as level
variable as:
Asst Technicains promotion to Technicians Rate
Asst. Technicians~
iC \
\
Disab ( a
Wo Asst, th ‘hnicians Technicians
Recruitment rate Recruftment rab
Technicial a Tebficains promotion ~~
non executives = —— to Charge men rate
od Desired Charge men
_ Tokai Charge men —_
_—4, Charyemen promotion
‘to Junior Officers rate*
/
\ \
Discrepancy () |
\ eS } )
\ dtottices
Desired, ior Mee Jupidr
J re - y
\ ws _Charge men
“Recruitment Rate
“‘Votal Technicial man power. #————__ Pa
“~ Total Technicial SE‘Top level =+-
Executives #~ Executives “Middle Level
Executives promotion to
/ Front Level \ Top Sr.
+, Executives promotion to ‘Biecutives rate
eu wits Middle Level eS
hea caine Executives rate \ fo
if | /
Desired Juni a
are mor / Midate Level
Ministeted Staff. Front Level 6 Executives
a \ / Erenulves __ Techinical
{ 6) \ / ‘ Executives desired
ay f+
Distrepancy \ /
\ © i
\ Ministered Staff ho \ Front Level
Recruitment rate “Executives “7
Recruitment rate
Fig.1 Causal Loop Diagram of Manpower System
TECANICANS TISCREPANGI IN eo DICREANCY DTCHRG_ DESIRED TOTAL
DITEGH TE recusicuns 5 Deed CHARGEMEN Soe eens ae CuARCENEN
AC CRUTMEMY EAVING RATE penrineuent RAE EAVING RATE :
Ray
HNICIANS 7 ; (cuicRT! Hy
{ :DER TRAINING
D3 I -
TOCHRG
a TECHNICIANS
DITTEC tet PROMOTION 70 Sapien cn Tee
TOLAL NUMBER OF LHARGEMEN RATE CHARGHMENS EE
\ Fedynicins— (TPcHCR) cxaRcEse TUNE PEIN
at \ ROMOPION TFr1¢) opp]
/
D3
Boome o|
OM
TECHRTCIANS Srey NICIAN BY DESIRED JUNIOR JUNIOR 7 ‘HARGEMEN
RECRUITMENT RATE ICERS Ose: OFFICERRATE CHARGEMEN RATE RECRUITMENT RATE
sar) i *% SO isco Juntorlorricers
FRONOTONTD ASSISTANT TECHNICIANS | DRSRED OS
TECHNICIANN RATE
ASSISTANT TEGENIIANS
JUNOFR
LEAVING Rj
MINISTERIAL, ~
DESCREPANCY IN J
UNDER TRAINING
q TOTAL TOTAL
73 ASSISTANT JEEHNICLANS H MINISTERIAL STAF!
é ASTTEC JUNIOR OFFICERS
LEAVING RATE /
| parcur cers
RATE
}IRAINED ASSISTANT |
TECHNICIANS RATE /
ASSISTANT TECHNICIANS bo M sSTSTANT TECHNICIANS
RECRUITMENT RATE Z RETIREMENT RATE
DISAT
DESIRED
ASSISTANT EXECUTIVES UNDE! | Hy
TECHNICIANS TRAINING
rats
)ESIRED
ISENIOR AND
eC OTAL
MINSTERLALSTAM
Z RECRUITMENT RAT
f TOP
APMIDDLE LEY ‘F EXECUTIVES
MINIS
EXECUBWES MIDDLE LEVEL
= Newef a vEEW NC RATE executives _SETREMENTRATE DISSTE
£ [03 Brrcurnes Es RETIREMENT RATE me N
E FRLEXE AINE MIDLEX EXECUTIVES
Uae |
[DIEXE FRONT EVEL | amour a:
TECHNICAL EXEQUTIVES |
TTEXE!
( FLMLpHy EXECUTIVES.
L
SRTOPE
EXECUTIVES
RETIREMENT RAN A
FRONT ENTOn AN
m .
EXECUTIVES
5 : 10
organ Se cS No LAL ror
EXECUTIVES EXE
— PROMOTION RATE
SRT © MPancy IN &) funer SENIOR AND TO DeeCURT
VES
TOTAL EXECUTIVES OF EXECUTIVES RECRUMMENT RATE
SENIOR AND TOPLEVEL
EXECUTIVES RETIREMENT RATE
Figure 2 Flow Diagram of Manpower Sub-system
CALL DELAY (ATCRR1, ASTERR, AT1, AT2, TATECR, DATCUT)
where ATCRR1 =Assistant Technicians Recruitment Rate, initial.
AT1, AT2 =Delay constants.
DATCUT =Time Delay for Assistant Technicians under Training, a constant.
Thus, Technicians under training (TECHUT), Chargemen under training (CHRGUT)
Executives under training (EX ETUT) are defined as level equations as explained above.
and
2 a) Total Assistant Technicians (ASTTEC) is defined as a level variable and is given by the
following equation.
ASTTEC =ASTTEC + DT* (TATECR - ASTTPR - ASTRTR - ASTLGR)
where ASTTPR =Assistant Technicians Promotion to technicians Rate.
ASTRTR = Assistant Technicians Retirement Rate.
ASTLGR = Assistant Technicians Leaving rate.
b) Assistant Technicians Promotion to Technicians Rate (ASTTPR) is defined as rate
equation and is given by the following equation.
ASTTPR =ASTTEC/AY PTEC
where ASTTEC = Assistant Technicians.
AY PTEC=Assistant technicians promoted to Technicians/Y ear, a constant.
c) Assistant Technicians Retirement Rate (ASTRTR) is defined as a rate equation and is
given by the following equation.
ASTRTR =ASTTEC/ATRTAG
where ATRTAG =Assistant Technicians Retirement Age, a constant.
ATECUT=ATECUT+DT*(ASTERR-TATECR)
where ASTERR=Assistant Technicians Recruitment Rate
TATECR=Trained Assistant Technicians Rate
e) Assistant Technicians Recruitment Rate (ASTERR) is defined as rate variable and is
given by the product of discrepancy in Total Technicians (DISCAT) and Assistant
Technicians Recruitment per year (ASTERY ), a constant.
ASTERR = DISCAT* ASTERY
f) Discrepancy in Total Technicians (DISCAT) is the difference between Desired Assistant
Technicians (DISATC), a constant and Assistant Technicians (ASTTEC). It is defined as
an auxiliary equation.
DISCAT =DISATC -ASTTEC
g) Trained Assistant Technicians Rate (TATECR) is defined as a rate variable and can be
obtained from the following call delay function
h) Assistant Technicians leaving rate (ASTLGR) is defined as a rate equation and is given
by the following equation.
ASTLGR =ASTTEC * ATCLGF
where ASTLGF = Assistant Technicians Leaving rate Fraction, a constant.
Similarly, Total technicians (TOTECH), Total Chargemen (TOCHRG), Front line executives
(FRLEXE), Middle level executives (MIDLEX) and Senior and top level executives
(SRTOPE) are modeled as level variables as explained above.
3 a) junior officers (J UNOFR) are modeled as level variable as given below.
JUNOFR =JUNOFR + DT*(TCJOPR - JOFRTR - JOFLGR)
where JUNOFR =Junior officers
TCJOPR = Chargemen promoted as junior officers rate.
JOFRTR =Junior officers retirement rate.
JOFLGR =Junior officers leaving rate.
b) Chargemen promoted to Junior officer rate (TCJOPR) is defined as a rate variable and is
given by the following equation.
TCJOPR=DISCJO*TCHPRF
c) Discrepancy in Junior officer (DISCJO) is defined as an auxiliary equation and is given
by DISCJO=DISJOF-JUNOFR
where DISJOF= Desired Junior officers.
JUNOFR= Junior officers.
d) Junior officers retirement rate (JOFRTR) is defined as a rate variable and is given by
JOFRTR =JUNOFR/JORTAG
where JORTAG =Junior officers retirement age, a constant.
e) Junior officers leaving rate (JOFLGR) is defined as a rate variable.
JOFLGR =JUNOFR*JOFLGF
where JOFLGF =Junior officers leaving rate factor, a constant.
Total ministerial staff (TOTMNS) is modeled as a level variable.
TOTMNS =TOTMNS +DT*(TMNSRR - TMSRTR)
where TMNSRR =Total ministerial staff recruitment rate.
TMSRTR =Total ministerial staff retirement rate.
4 a) Total Ministerial staff (TOTMNS) is defined as a level equation and is given below.
TOTMNS=TOTMNS+DT*(TMNSRR-TMSRTR)
where TMNSRR=Ministerial staff recruitment rate
TMSRTR=Ministerial staff retirement rate
b) Ministerial staff recruitment rate (TMNSRR) is defined as a rate equation and is given by
the following equation
TMNSRR = DISTMS*MINSRF
where DISTMS = Discrepancy in total ministerial staff.
MINSRF= Ministerial staff recruitment rate factor, a constant.
c) Discrepancy in total ministerial staff (DISTMS) is defined as an auxiliary variable given
as DISTMS =DISCMS - TOTMNS
where DISCMS = Desired total ministerial staff, a constant.
TOTMNS =Total ministerial staff
d) Ministerial staff retirement rate (TMSRTR) is defined as a rate variable and is given by
TMSRTR = TOTMNS/TMSRAG
where TMSRAG = Ministerial retirement age, a constant
5) Total number of non-executives (TOTNEX) is defined as an auxiliary variable and is given
by the following equation.
TOTNEX =ASTTEC +TOTECH +TOCHRG 4UNOFR
where ASTTEC = Assistant technicians.
TOTECH =Total number of technicians
TOCHRG =Total Chargemen
JUNOFR =Junior Officers
6) Non-executives to Executives ratio (NEX EX R) is defined as a ratio between Total number of
Non-executives and to that of Total number of Executives and is given by the following
equation.
NEXEXR =TOTNEX/TOTEXE
where TOTEXE =Total number of executives.
TOTNEX =Total number of non-executives.
3. Computer simulation of the Model
This model consists of a total of 56 equations having 13 level variables, 25 rate variables, 4 third
order call delay variables and 14 auxilliary variables. The model is simulated for a period of 20
years from 1994 using DYMOSIM Software package. Simulation is carried out with the
assumption that the problem description would remain valid for this period. All together six
policies are tested and the results are verified with the available published data.
4. Model Validations
The following three variables have been selected for model validation. They are:
i) Total Technical Manpower
ii). Non- Executive to executives Ratio and
iii) | Manpower Productivity
Model generated data for a period of 10 years from 1993-94 to 2002-03 is plotted against the
historical data as indicated in the Fig.3 to Fig.5. It can be seen from figures that there is a very
good agreement between the model-generated data and that of actual data.
The slump in productivity during the year 1999 was due to the repair of coke ovens and shut
down of a blast furnace unit of the steel plant which underwent capital repair resulting in a huge
loss of production. The productivity of 258 tonnes per man-year predicted by the model
corroborates its validity and confidence.
4,1 Tests of Model structure
i) Structure verification test: The structure of the model was thoroughly validated such
that it clearly resembles the structure of the real life system. The model consists of
physical flows of manpower. Both the causal loop diagram and flow diagram consist of
variables which can be easily identified in the real life system.
17600
17400
17200
17000
— Model
—= Actual
16800
TOTAL TECHNICAL MANPOWER
16600
16400
16200
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
YEAR
Fig. 3 Total Technical Manpower
15
NPN- EXECUTIVE TO EXECUTIVE RATIO
35
—+ Model
= Actual
3
1994 1995 1996 1997 1998 1999
YEAR
2000
2001
2002
Fig 4 Non- executive to Executive ratio
280
260
240
MANPOWER PRODUCTIVITY
140
120
2003
—e— Model
= Actual
100
1994 1995 1996 1997 1998 1999
YEAR
2000
Fig.5 Manpower productivity
ii) Parameter verification test: All the parameters considered in the model correspond to
the real life system both conceptually and numerically. All these parameters are
identified and found to be consistent with the real life system.
iii) Dimensional consistency test: The model consists of 56 equations. All these
equations are written and thoroughly checked for dimensional consistency between the
influencing variables and of resultant variables. Thus the model is found to be
dimensionally consistent.
iv) Boundary adequacy (structure) test: As indicated by causal loop diagram and flow
diagram the factors considered in model have been adequate in addressing the various
issues related to real life system. The model boundary set in this study, therefore, is
considered adequate for the objectives with which the model developed.
4,2. Tests of Model behaviour
i) Behaviour reproduction test:
The validity of the model is further established by means of the statistical analysis of the
data. The results of the analysis are summarized in Table.1. A comparison of the
standard deviations also makes it very clear that the there is an excellent agreement of the
modeled data and actual data from the industry.
Table 1: Comparison of Model generated and Actual values for select variables
Executive / Non- Labour Productivity Technical Manpower
YEAR Executive Ratio
Model Actual Model Actual Model Actual
1993-94 6.92 6.92 114.22 114.2 17510 17510
1994-05 6.18 6.42 146.18 156.0 17101 17369
1995-96 5.18 5.45 176.34 185.0 17012 17200
1996-97 4.63 4.85 181.03 188.0 17265 17478
1997-98 4.27 4.41 188.14 189.0 17275 17354
1998-99 4.00 4.14 166.52 161.0 17265 17400
1999-00 3.78 3.92 196.7 192.0 17158 17254
2000-01 3.61 3.72 221.72 228.0 16965 16832
2001-02 3.47 3.58 231.72 228.0 16723 16694
2002-03 3.35 3.45 258.18 253.0 16461 16429
10
So
as to further enhance confidence in the model, t-test and F-test are conducted and the
results are tabulated in Table 2. The results are well within the limits and there is a close
agreement between the simulated data and that of the actual data. The difference in both
values is insignificant. On the basis of the qualitative and quantitative tests, it is thus
concluded that the model is replicating the real situation.
Table 2: t- test and F-test for Model and Actual values for selected variables
Variable Actual Model t- Values F-Values
Mean | Standard | Mean | Standard | [to(0.05) = 2.26] | [Fo9(0.05)= 3.18 ]
Deviation Deviation
Non 4686 | 1.2135 | 4539 | 1.2083 0.27145 7.0086
executive to
Executive
Ratio
Labour 187.5 38.84 188.0 41.96 0.02688 1.167
Productivity
Technical | 17196 | 401.34 | 17073 | 302.94 -0.77164 1.07552
Manpower
ii) Behaviour prediction test: Valid prediction of the real system behaviour can be made
only if the model structure, the managerial policies and time variation of exogenous
variables can be predicted (Mohapatra 1994). The model is run for the period from
2004 to 2013 and found that the results of the model are identical with that of the values
predicted by the management. This is vindicated by the results for period 2004 to 2006.
iii) Behaviour anomaly test: The model did not produce any behaviour anomalous to that
of the real system.
iv) Family member test: The model has been developed for an integrated steel plant
located in Visakhapatnam. But it is generic in nature and with appropriate
modifications in the initial values of the level variables and constants; it can be applied
to any other steel plant either in India or elsewhere.
v) Surprise behaviour test: The model did not produce any surprise or counter intuitive
behaviour.
vi) Boundary adequacy (behaviour) test: This test was intended to check whether the
model boundary can be expanded to include other related aspects like domestic sales,
export sales, owning captive mines. At aggregate level, however, inclusion of these
factors is not expected to produce significance changes in the model results.
11
vii) Behaviour sensitivity test: The model was tested for changed values of various
parameters. Qualitatively the model retains its behaviour for all the variables.
5. Policy options
Human resource planning is the process by which an organization should move from its current
manpower position to desired manpower position. In view of the current trends in industry with
emphasis on technology, cost reduction, quality and productivity etc., it is imperative to retrain
and redeploy the manpower on a continuous basis and the requirements of the manpower can be
met from internal human resources of the organization. The following six policies are considered
for implementation and forecasting the organizational behaviour in tune with the desired
manpower requirements.
Policy-1 (Base Run):
In this policy, it is assumed that the present trend with reference to recruitment to various
cadres will continue in future also.
Policy-2:
In this policy, it is presumed that there will not be recruitment for any cadre. In view of the
management aim at reducing manpower, this policy aims at examining the implications if the
recruitment is banned.
Policy-3:
The management aims at reducing the strength of non- executive cadre. In light of this
policy, it is assumed that there will not be any recruitment at non-executive level i.e., to the
cadres of assistant technicians, Chargemen, technicians and ministerial staff.
Policy-4:
In this policy, the implication of reducing the total length of service by 5 years, for all cadres
is tested. Government of India has been encouraging voluntary retirement by the employees
of public sector undertakings. In light of the above policy of the government, it has been
proposed to study the implications if total length of service is reduced by 5 years.
Policy-5:
In this policy, it is presumed that the total length of service is reduced by 5 years for non-
executives. As the management is intending to reduce the non- executive cadre, it is tested
what happens if the total length of service for the said cadre is reduced by 5 years.
Policy-6:
In this policy, it is presumed that the total length of service is reduced by 5 years for
executives only. The impact on the organization, if the length of service of executive cadre is
reduced by 5years is tested.
12
6. Results of model simulation
After simulating the model for different policy options listed above, the behaviour of key
variables was examined in detail. The base run (Policy-1) results have also been compared with
the available data. A comparative study of various policy results has been made. The results of
base run for the selected variables are presented in Table.3.
Table 3: Base run results of key variables
SI.
No. Variables 1994 1997 | 2000 | 2003 | 2006 | 2009 2013
1 Technical
18410 | 18483 | 17959 | 17169 | 16335 | 15548 | 14607
Manpower
2 Non-Executive to
Executive Ratio 7.33 5.12 | 4.05 | 3.56 | 3.25 | 3.02 2.76
3 Manpower
Productivity
(Tonnes/ 109 172 216 256 300 315 335
Man/year)
7. Policy analyses
The results of the policies adopted are shown in Figs.6 to Fig.8. A comparison of performance
under different policy options is given in Table 4.
7.1 Total technical manpower
Among the policies tested, Policy-2 is resulting in the lowest number followed by Policies-3, 4,
5, 6 and 1 (Table.4 and Fig.6). So as to bring down the strength of manpower, various options
like complete stoppage of recruitment, reduction of total length of service at various levels are
considered. At one stage, the government has offered a voluntary retirement scheme for public
sector employees. Because of this reason only, the implication of reduction in total length of
service is considered. But this policy is not having much impact in reducing the manpower and
the viable policy is stopping of recruitment totally for all cadres as it gives a solution as
contemplated by the management.
13
Table 4; Comparison of key Variables
SI.
No. Variables Year| Pi P, P; Py P; Ps
1 ee 2004 | 16889 | 16785 | 16868 | 16782 | 16822 | 16850
anpower
2007 | 16066 | 14839 | 15548 | 15679 | 15806 | 15939
2010 | 15300 | 12936 | 14173 | 14732 | 14894 | 15138
2013 | 14606 | 11259 | 12931 | 13905 | 14082 | 14430
2 Non-Executive
to EnoutiveRetio | 2004 | 344 | 3.51 | 344 | 346 | 3.42 | 3.48
2007 | 316 | 371 | 303 | 32 | 31 | 3.27
2010 | 2.95 | 3.9 | 2.06 | 2.97 | 285 | 3.08
2013 | 2.76 | 409 | 2.33 | 2.75 | 263 | 2.89
3 Manpower
Productivity 2004 | 255 | 257 | 256 | 257 | 256 | 256
2007 | 305 | 330 | 315 | 312 | 310 | 307
2010 | 320 | 378 | 345 | 332 | 329 | 323
2013 | 335 | 435 | 379 | 352 | 348 | 339
18000
17000
16000
15000
14000
13000
TOTAL TECHNICAL MANAPOWER
12000
11000
10000
2003 2004 = 2005
2006
2007
2008
YEAR
2009
2010
2011
2012 2013
Fig. 6 Total technical manpower with policy changes
14
> Policy-1
—= Policy: 2
= Policy: 3
Policy: 4
Policy: 5
—eSeries6
7.2 Non-executive to executive ratio
The best ratio is given by Policy-3 followed by Policies-5, 4, 1, 8 and 2 (Table.4 and Fig.7). But,
the ratios given by these policies are almost identical. However, it may not be practicable to
implement any one of these policies because of practical difficulties. In these policies, it
assumed either stoppage of recruitment or reduction in the total length of service, which is not
feasible in the prevailing environment. At present, the management wants to maintain a ratio of
1:4, which is reflected by Policy-2, and can be achieved by the year 2013.
7.3 Manpower productivity
The best result is given by the Policy-2, followed by Policies 3, 4, 5, 6 and 1(Table.4 and Fig.8).
Thus, Policy-2 is giving the best policy in view of the reduction in manpower. Therefore, the
management has to adopt Policy-2 to achieve its goal.
4.25
2
G 345 |—e—Policy- 1
FA Policy. 2
°°
£ 3.25 ~ © Policy- 3
« Policy: 4
g Policy: 5
$ 3.05 |-e-Seriesé
2
2.85
2.45
2.25
2003 2004 2005, 2006 2007 2008 2009 2010 2011 2012 2013
YEAR
Fig. 7 Non-executive to executive ratio with policy changes
= Policy- 1
—m—Policy- 2
= Policy- 3
= Policy- 4
—#— Policy: 5
—e-Series6
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
YEAR
Fig. 8 Manpower productivity with policy changes
8. Summary
Based on the detailed discussion on the results, the following conclusions are drawn.
1. There is a close resemblance between the data simulated by SD modelling and the actual
plant data, thus establishing the fact that SD modeling is very effective and useful in the
present study.
2. The SD model is further extended to design policies for effective utilization of
manpower.
3. Downsizing of manpower both at the executive and non-executive level needs to be
carried out so as to improve the productivity and techno-economics of the plant
operations.
4. The manpower rendered surplus can be retrained and redeployed in new and existing
facilities as the production capacity of the steel plant is being enhanced.
Notes
1. World standard of labour-productivity is 600 tonnes per man- year.
16
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17
