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Procurement strategy group decision
making of an organization
P. S. Chakraborty
Adult, Continuing Education & Extension Department, Jadavpur University,
S. Ghosh
Mechanical Engineering Department, Jadavpur University,
G. Majumdar
Mechanical Engineering Department, Jadavpur University,
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Decision taken by a group is always better than
individual decisions as group talent is more than that
of any individual.
Maximum cases of group decision making
processes are dominated by Yes-No voting system,
which may not reflect the decision makers realintention.
This paper deals with a case study of procurement
strategy decision making process for a manufacturingorganization with the help of Analytic hierarchy
process based group decision making model
considering preference intensity of individual voters.
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The final decision is taken based on the ratio of
benefit from particular criteria to cost andassociated risk involved on that particular
criterion.
At the end it is also shown that this model maynot be feasible in dealing with the issues having
interdependencies i.e. when it is must to choose
one of the issues.
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Introduction:
Timely strategic decision makings are having long
time implication on the organization performance
and must be taken considering their future impact on
business and the relationship with existing partners.
In this fast changing business scenario it is not
possible for any individual to have knowledge on
every aspects of business.
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In maximum number of cases, group decisions are
made based on Yes-No voting system, which
indirectly influences few participants to side with the
majority.
In some cases few participants can not make up
mind, as they like both the issues up to certain
extent justifying the importance of preferenceintensity while decision making.
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For example a participant may like an issue 65%,
but may not like by 35%. In that case under
traditional Yes-No voting system he would vote for
No, which does not reflect the real desire or
intention of the voters or participants.
Saaty and Shang (2007) proposed a conceptual
framework based on AHP to tackle social decision
making. They discussed the deficiencies oftraditional Yes-No voting system, where intensity of
preference of individual voters are not taken into
account.
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If preference intensity or real desire of individual
voter is taken care, then the result may differ from
traditional system.
The idea expounded and propounded in the above
paper is mostly extended for a manufacturingorganizations procurement strategy group decision
making.
It is also found that this model may not be feasible
when there is interdependency between the issues
i.e. when one of the issues must be chosen.
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Methodology :
oAt first step issues are assessed under benefit,cost and risk hierarchy.
o In the second step each issue is divided into two
alternatives as to do it or not to do it under the
benefit, cost and risk hierarchies.
o In the third step ratio of benefit to cost multiply
risk are calculated for to do it or not to do it
alternatives of all the issues.
o These alternatives address the intensity of
preference for the decision maker.
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o These ratios assess the expected benefit and
associated cost and risk involved for the issues.
o In the fourth step for each issue, among the two
alternatives to do it or not to do it, which ratio
scores maximum in the third step is the fate for
that issue.
o Detail methodology is available at Saaty and
Shang 2007. Steps are compiled as follows:
Step 1- Compute the weightage of each criterionunder all the hierarchies.
Under each criterion compute the relative
importance of each issue.
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Step 2-
Divide each issue into two alternatives.
Compute the relative importance of each alternative.
Step 3-
Calculate the benefit / cost x risk ratio.
Step 4-Decision based on the above Ratio
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Case study:
This case is the problem of long term strategic
decision making process of an organization. In
this case benefit for particular criteria to cost
involved and associated risk are calculated.
All the departmental heads of the organization
were asked to take part in this decision making
process.
Under each hierarchy various criteria areconsidered. Under benefit hierarchy various
criteria considered are decrease employee
number, social obligation fulfillment and
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Under cost hierarchy various criteria considered
are productivity cost, capital cost and opportunity
cost.
Under risk hierarchy various criteria considered
are future competitiveness, product damage and
long lead-time.
This model was used to solve the problem faced
by an automobile manufacturer to procure critical
component for the assembly. Various issues considered for this analysis are
produce at own plant, develop ancillaries and
procure from reputed manufacturer.
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These issues are considered under benefit, cost
and risk hierarchies. In AHP pairwise comparison the priority value is
given in a scale of 1 to 9 by asking some simple
questions. One typical question may be To
decrease the number of employee, how much
important produce at own plant is when compared
to develop ancillaries?.
The AHP weightage in all the cases are thegeometric mean of the decision makers, as it was
difficult to arrive at a consensus weight.
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Table 1 shows procedure for generating priority
for benefit hierarchy using AHP.
Under benefit hierarchy these criteria weights are
written just below the criteria.
Priority weights were determined from pairwise
comparison. Relative importance of Produce atown plant is calculated as
(0.4 x 0.2) + (0.1x 0.45) + (0.5x0.6) = 0.425.
Table 2 shows various issues and criteria undercost hierarchy.
Similarly in table 3 various issues and criteria
under risk hierarchy are shown.
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Benefit
Decrease
Employee
number
0.40
Social
obligation
fulfillment
0.10
Competitive
infrastructur
es
0.50Importance
0.20
0.30
0.50
0.45
0.35
0.20
0.60
0.30
0.10
0.425
0.305
0.270
Table 1: Weightage under benefit hierarchy
Produce at own
plant
Develop ancillaries
Procure from
reputed
manufacturers
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Cost
Productivity
cost
0.40
Capital
cost
0.45
Opportunity
cost
0.15 Importance
0.35
0.30
0.35
0.60
0.30
0.10
0.45
0.30
0.25
0.478
0.300
0.223
Table 2: Weightage under cost hierarchy
Produce at own plant
Develop ancillaries
Procure from reputed
manufacturers
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Risk
Future
Competitivenes
s
0.3
Product
damage
0.3
Long
lead-time
0.4
Importance
0.5
0.4
0.1
0.1
0.3
0.6
0.1
0.3
0.6
0.220
0.330
0.450
Table 3: Weightage under risk hierarchy
Produce at own
plant
Develop ancillaries
Procure from
reputed
manufacturers
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Benefit
Decrease
Employee number0.4
Social obligation
fulfillment0.1
Competitive
infrastructures0.5
Produce at own plant
Do not produce at
own plant
Develop ancillaries
Do not develop
ancillaries
Procure from reputed
manufacturers
Do not procure from
reputed
manufacturers
Local
rating
0.9
0.1
0.75
0.25
0.9
0.1
Table 4: Overall rating under benefit hierarchy
Local Global Local Global GlobalLocalOverall
rating
0.18
0.02
0.225
0.075
0.45
0.05
0.75
0.25
0.6
0.4
0.8
0.2
0.3375
0.1125
0.21
0.14
0.16
0.04
0.9
0.1
0.6
0.4
0.75
0.25
0.54
0.06
0.18
0.12
0.075
0.025
1.825
0.575
1.510
0.890
1.755
0.645
0.884
0.461
0.736
0.549
0.904
0.467
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Cost
Productivity
cost0.40
Capital cost
0.45
Opportunity
cost0.15
Local
rating
0.9
0.1
0.75
0.25
0.75
0.25
Table 5: Overall rating under cost hierarchy
Local Global Local Global GlobalLocalOverall
rating
0.315
0.035
0.225
0.075
0.2625
0.0875
0.8
0.2
0.7
0.3
0.8
0.2
0.48
0.12
0.21
0.09
0.08
0.02
0.8
0.2
0.6
0.4
0.6
0.4
0.36
0.09
0.18
0.12
0.15
0.10
1.780
0.620
1.555
0.845
1.600
0.800
0.985
0.530
0.747
0.534
0.721
0.512
Produce at own plant
Do not produce at ownplant
Develop ancillaries
Do not develop
ancillaries
Procure from reputed
manufacturers
Do not procure from
reputed manufacturers
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Overall
rating
Risk
Future
competitiveness
0.3
Product
damage
0.3
Long
lead-time
0.4
Local
rating
0.8
0.2
0.75
0.25
0.6
0.4
Table 6: Overall rating under risk hierarchy
Local Global Local Global GlobalLocal
0.40
0.10
0.30
0.10
0.06
0.04
0.75
0.25
0.75
0.25
0.60
0.40
0.075
0.025
0.225
0.075
0.36
0.24
0.80
0.20
0.70
0.30
0.70
0.30
0.08
0.02
0.21
0.09
0.42
0.18
1.645
0.655
1.555
0.745
1.360
0.940
0.755
0.416
0.752
0.459
0.636
0.484
Produce at own plant
Do not produce at own
plant
Develop ancillaries
Do not develop ancillaries
Procure from reputed
manufacturers
Do not procure from
reputed manufacturers
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Ratio of Benefit / (Cost x Risk) for alternatives
Decision (to do or not to do)
Produce at own plant = 0.884 / (0.985 x 0.755)
= 1.19
Do not produce at own plant = 0.461 / (0.503 x 0.416) No
= 2.21
Develop ancillaries = 0.736 / (0.747 x 0.752)= 1.31
Do not develop ancillaries = 0.549 / (0.534 x 0.459) No
= 2.24
Procure from reputed manufacturers = 0.904 / (0.721 x 0.636)
= 1.97Do not procure from reputed = 0.467 / (0.512 x 0.484) Yes
Manufacturers = 1.88
Table 7: Decision on issues based on ratio
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Result:
Table 7 shows the benefit / (cost x risk) ratio for
all the six alternatives. The benefit / (cost x risk)
ratios are the basis for choosing or rejecting the
particular issues.
In case of Produce at own plant alternative this
ratio is less than Do not produce at own plant
alternative.
Similarly in case of Develop ancillaries this ratio
is less than Do not develop ancillaries. Both these
issues will not be considered.
In case of Procure from reputed manufacturers
this ratio is more than Do not procure from
reputed manufacturer.
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So this issue will be chosen as procurement
strategy of that particular critical compent.
Now if the criteria weightage under cost hierarchy
are changed as follows.
The productivity cost and opportunity cost
weightage are changed from 0.4 to 0.3 and 0.15 to0.25 respectively, keeping capital cost weighatge
constant.
Then again benefit / (cost x risk) ratio for all the six
alternatives are calculated, which is shown in table 8.
From table 8 it is clear that all the issues will be
rejected.
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Ratio of Benefit / (Cost x Risk) for alternatives
Decision (to do or not to do)
Produce at own plant = 0.884 / (0.921 x 0.755)
= 1.27
Do not produce at own plant = 0.461 / (0.412 x 0.416) No
= 2.70
Develop ancillaries = 0.736 / (0.665 x 0.752)= 1.47
Do not develop ancillaries = 0.549 / (0.446 x 0.459) No
= 2.69
Procure from reputed manufacturers = 0.904 / (0.636 x 0.636)
= 2.23Do not procure from reputed = 0.467 / (0.422 x 0.484) No
Manufacturers = 2.29
Table 8: Decision on issues based on ratio after weightage modification
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Conclusion:
In this case procurement strategy was chosen
considering the intensity of preference of individualparticipants, not as per traditional Yes-No voting
system. The objective as well as subjective judgment
considering multiple issues is taken care off using
AHP methodology. This model is suitable for any
other kind of decision making process, though people
may not yet be ready for such voting system, instead
traditional Yes-No voting system. It can also beconcluded that this model may not be proved feasible
in case of interdependence between the issues i.e.
when one of the issues must be chosen.
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Acknowledgement:
This project has been funded by Jadavpur
University (Jadavpur University Research Grant-Ref. No. P1 / 1730/ 05 dated 28.10.2005)
References:
Bhattacharya A, Sarkar B, Mukherjee S K. A new methodfor plant location selection: a holistic approach.
International Journal of Industrial Engineering: Theory
Application and Practice 2004; 11; 330-338.
Chakraborty P S, Majumder G, Sarkar B. Performanceevaluation of existing vendors using Analytic Hierarchy
Process. Journal of Scientific and Industrial Research
2005; 64; 648-652.
8/6/2019 Presentation GD
27/31
3.Choudhury A K, Shankar R, Tiwari M K. Consensus-basedintelligent Group decision making model for the selction
of advance technology. Decision Support systems 2006;42; 1176-1799.
4.Fan Z P, Ma J, Jiang Y P, Sun Y H, Ma L. A Goalprogramming approach to Group decision making based
on multiplicative preference relations and fuzzy preference
relations. European Journal of Operational Research
2006; 174; 311-321.
5.Gerwin D. Manufacturing flexibility: a strategicperspective. Management Science 1993; 39; 395-410.
6.Ghodsypour S H, Obrien C. A decision support system forsupplier selection using an analytic hierarchy process andlinear programming. International Journal of Production
Economics 1998; 56-57; 199-222.
8/6/2019 Presentation GD
28/31
7.Hua Z S, Jiang W, Liang L. Adjusting inconsistencythrough learning in group decision making and its
application to Chinas MBA recruiting interviews. Socio-Economic Planning Sciences 2007; 41; 195-207.
8.Kraus S. Strategic Negotiations in Multi-agentEnvironments. Massachusetts Institute of Technology
Press: Cambridge; 2001; 17-29.
9.Lootsma F A, Schuijt H. The multiplicative AHP, Smart andElctre in a common context. Journal of Multi-Criteria
Decision Analysis 1997; 6.
10.Mirani R, Moore D, Weber J A. Emerging technologies
for enhancing supplier-reseller partnerships. IndustrialMarketing Management 2001; 30(2); 101-114.
11.Mich L, Gaio L, Fedrizzi M. On Fuzzy logic-basedconsensus in group decision, Procedings IFSA 1993; 698-
700.
8/6/2019 Presentation GD
29/31
12.Mikhalov L. Group prioritization in the AHP by fuzzypreference programming method. Computers and
Operations Research 2004; 31.13.Ragatz G L, Handfield R B Scannell T V. Success factors
for integrating suppliers into new product development,
Journal of Poduct Inovation Management 1997; 14; 190-
202.
14.Saaty T L. The Analytic Hierarchy Process. McGraw-Hill:New York; 1980.
15.Saaty T L, Shang J S. Group decision-making: Head-count versus intensity of preference. Socio-Economic
Planning Sciences 2007; 41; 22-37.16.Sarkar B, Choudhary J P, Mukherjee S K. Selection ofprofessionals using Analytic Hierarchy approach. Journal
of Institute of Engineers (India). Interdisciplinary Division
2000; 16-18.
8/6/2019 Presentation GD
30/31
17.Shih H S, Shyur H J, Lee E S. An extension of TOPSISfor Group decision making. Mathematical and Computer
Modelling 2007; 45; 801-813.18.Srdjevic B. Linking AHP and Social choice methods to
support group decision making in water management.
Decision Support System 2007; 42; 2261-2273.
19.Wanyama T, Far B H. A protocol for multi-agentnegotiation in a group-choice decision making process.
Journal of Network and Computer Applications 2007; 30;
1173-1195.
20.Weele A V. Purchasing and Supply Chain Management:
Analysis, Planning and Practice. Thomson Learning:London; 2000.
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