PRODUCTION ANALYSIS PRODUCTION ANALYSIS
Dec 22, 2015
PRODUCTION ANALYSISPRODUCTION ANALYSIS
SCOPESCOPE
PRODUCTION POSSIBILITY ANALYSIS.
― LAW OF VARIABLE PROPORTION.
― LAW OF RETURN TO SCALE.
ISOQUANT - ISOCOST ANALYSIS.
OUTPUT
PRODUCTIONPRODUCTION
PRODUCTION ANALYSISPRODUCTION ANALYSIS
INPUT
PRODUCTION: CONVERSION OR TRANSFORMATION
OF INPUTS TO OUTPUT.
PROCESS ADDS VALUE TO INPUTS TO SATISFY
NEEDS/ WANTS.
PRODUCTION: ADDITION OF VALUE/ UTILITY.
DEFENCE SERVICES PRODUCERS – THEY
SATISFY NEEDS OF NATIONAL SECURITY
OUTPUT PRODUCTION ANALYSIS
PRODUCTIONPRODUCTION
PRODUCTION ANALYSISPRODUCTION ANALYSIS
INPUT
PRODUCTION ANALYSIS: LAWS GOVERNING
RELATIONSHIP BETWEEN INPUTS & OUTPUTS.
LAWS HELP DECIDE OPTIMAL COMBINATION OF
INPUTS (RESOURCES) FOR DESIRED RESULTS AT
LOWEST COST. DEFENCE SERVICESDEFENCE SERVICES
LAWS
LAW OF VARIABLE PROPORTIONS.
LAW OF RETURN TO SCALE.
ANALYSIS TECHNIQUES
PRODUCTION POSSIBILITY ANALYSIS.
ISO-COST / ISO-QUANT ANALYSIS.
PRODUCTION ANALYSISPRODUCTION ANALYSIS
OUTPUT PRODUCTION ANALYSIS
PRODUCTIONPRODUCTION
PRODUCTION ANALYSISPRODUCTION ANALYSIS
INPUT
PRODUCTION ANALYSIS: LAWS GOVERNING
RELATIONSHIP BETWEEN INPUTS & OUTPUTS.
LAWS HELP DECIDE OPTIMAL COMBINATION OF
INPUTS (RESOURCES) FOR DESIRED RESULTS AT
LOWEST COST.
SUBSTITUTION OF RESOURCE
WITHIN ONE INPUT ITSELF: INCREASE/ DECREASE
ONE INPUT BY ANOTHER.
PRODUCTION FUNCTIONPRODUCTION FUNCTION
• INFANTRY Vs MECHANISED
• AD AIRCRAFT Vs MISSILES
• GUNS Vs GROUND STRIKE AIRCRAFT
PRODUCTION FUNCTION
• RELATIONSHIP BETWEEN INPUTS AND
OUTPUTS
• P = f (R1,R2…Rn)
HOW TOTAL & MARGINAL OUTPUT IS AFFECTED
BY CHANGE IN ONE INPUT KEEPING OTHER
INPUTS CONSTATNT.
“AS PROPORTION OF ONE FACTOR IN A
COMBINATION OF FACTORS IS INCREASED,
MARGINAL & AVERAGE OUTPUTS WILL INCREASE
THEN AFTER A POINT, FIRST MARGINAL AND
THEN AVERAGE OUTPUT WILL DIMINISH”.
APPLICABLE IN SHORT RUN.
LAW OF VARIABLE PROPORTIONSLAW OF VARIABLE PROPORTIONS
EFFECT ON OUTPUT: THREE STAGES
INCREASING RETURNS – MARGINAL RETURN
RISES
CONSTANT RETURNS – MARGINAL RETURN
FALLS
DIMINISHING RETURNS – MARGINAL RETURN
BECOMES NEGATIVE
LAW OF VARIABLE PROPORTIONSLAW OF VARIABLE PROPORTIONS
LAW OF VARIABLE PROPORTIONSLAW OF VARIABLE PROPORTIONSPRODUCTION OF AMN SHELLS PER MACHINE PER
HOUR IN ORD FACTORY
NO OF WORKERS
TOTAL PRODUCTION
AVERAGE PRODUCTION
MARGINAL PRODUCTION
STAGES OF PRODUCTION
1 8 8 8
2 20 10 12
3 36 12 16
4 48 12 12
5 55 11 8
6 60 10 5
7 60 8.6 0
8 56 7 - 4
LAW OF VARIABLE PROPORTIONSLAW OF VARIABLE PROPORTIONSPRODUCTION OF AMN SHELLS PER MACHINE PER
HOUR IN ORD FACTORY
NO OF WORKERS
TOTAL PRODUCTION
AVERAGE PRODUCTION
MARGINAL PRODUCTION
STAGES OF PRODUCTION
1 8 8 8 I
2 20 10 12 I
3 36 12 16 I
4 48 12 12 II
5 55 11 8 II
6 60 10 5 II
7 60 8.6 0 III
8 56 7 - 4 III
LAW OF VARIABLE PROPORTIONS
LABOUR
TP
MP/AP
STAGE I II III
1 2
AP
MP
B
A
MP > APAP > MP
INCREASING RETURN: INCREASE IN OUTPUT MORE
THAN PROPORTIONATE TO INCREASE IN INPUT
OPTIMAL POINT
IN EMPLOYMENT
OF FACTOR
CONSTANT RETRUN: INCREASE IN OUTPUT
PROPORTIONATE TO INCREASE IN INPUT
DIMNISHING RETURN: INCREASE IN OUTPUT LESS
THAN PROPORTIONATE TO INCREASE IN INPUT
EXAMPLES OF LAW OF VARIABLE PROPORTIONS
NO OF AIRCRAFT TAKING PART IN BOMBING MISSION AND DESTRUCTION SOUGHT.
NO OF GUNS ALLOTTED TO NEUTRALISE A TARGET AND EFFECT ACHIEVED.
AMOUNT OF TIME ALLOCATED TO TRAINING AND STANDARDS ACHIEVED.
NO OF MEN ALLOCATED TO A TASK AND OUTPUT.
IN SHORT, IN SITUATIONS WHERE ONE FACTOR IS INCREASED, WHILE OTHERS REMAIN CONSTANT.
ASSUMPTIONS
NO CHANGE IN TECHNOLOGY
IMPROVEMENT IN TECHNOLOGY BOUND
TO RAISE OUTPUT.
ONLY ONE FACTOR VARIABLE, REST
CONSTANT.
LAW OF VARIABLE PROPORTIONSLAW OF VARIABLE PROPORTIONS
LAW OF RETURN TO SCALELAW OF RETURN TO SCALE
DEALS WITH EFFECT ON OUTPUT, WHEN ALL
INPUTS CHANGE SIMULTANEOUSLY IN SAME
RATIO - DOUBLE, TREBLE ETC…
LARGER THE SCALE OF ACTIVITIES – LOWER
GENERALLY THE COST OF ACHIEVING
OUTPUT.
ECONOMIES OF SCALE ARISE FROM LARGE
SCALE ACTIVITIES.
LAW OF RETURN TO SCALELAW OF RETURN TO SCALE
ECONOMIES RESULT FROM
EFFICIENT USE OF RESOURCES
FULLER UTILISATION OF EXISITING CAPACITY
R&D
ECONOMIES OF SCALE
TRUE ONLY UP TO A POINT.
THEN DIS-ECONOMIES SETS IN.
THREE STAGES
INCREASING RETURNS – MARGINAL RETURN
RISES
CONSTANT RETURNS – MARGINAL RETURN
CONSTANT
DIMINISHING RETURNS – MARGINAL RETURN
DIMNISHES
LAW OF RETURN TO SCALELAW OF RETURN TO SCALE
RETURNS TO SCALERETURNS TO SCALE(PRODUCTION OF AMN SHELLS IN ORD FACTORY PER MACHINE)
FACTORS OF PRODN EMP TOTAL PRODUCTS/RETURNS
MARGINAL PRODUCT/
RETURNS
STAGE OF RETURN TO SCALE
RETURNS TO SCALERETURNS TO SCALE(PRODUCTION OF AMN SHELLS IN ORD FACTORY PER MACHINE)
FACTORS OF PRODN EMP TOTAL PRODUCTS/RETURNS
MARGINAL PRODUCT/
RETURNS
STAGE OF RETURN TO SCALE
1 WORKER+3 hrs
RETURNS TO SCALERETURNS TO SCALE(PRODUCTION OF AMN SHELLS IN ORD FACTORY PER MACHINE)
FACTORS OF PRODN EMP TOTAL PRODUCTS/RETURNS
MARGINAL PRODUCT/
RETURNS
STAGE OF RETURN TO SCALE
1 WORKER+3 hrs
2 WORKERS + 6 hrs
RETURNS TO SCALERETURNS TO SCALE(PRODUCTION OF AMN SHELLS IN ORD FACTORY PER MACHINE)
FACTORS OF PRODN EMP TOTAL PRODUCTS/RETURNS
MARGINAL PRODUCT/
RETURNS
STAGE OF RETURN TO SCALE
1 WORKER+3 hrs
2 WORKERS + 6 hrs
3 WORKERS + 9hrs
4 WORKERS+ 12 hrs
5 WORKERS +15 hrs
6 WORKERS + 18 hrs.
7 WORKERS + 21 hrs
8 WORKERS + 24 hrs
9 WORKERS + 27 hrs
RETURNS TO SCALERETURNS TO SCALE(PRODUCTION OF AMN SHELLS IN ORD FACTORY PER MACHINE)
FACTORS OF PRODN EMP TOTAL PRODUCTS/RETURNS
MARGINAL PRODUCT/
RETURNS
STAGE OF RETURN TO SCALE
1 WORKER+3 hrs 200
2 WORKERS + 6 hrs 500
3 WORKERS + 9hrs 900
4 WORKERS+ 12 hrs 1400
5 WORKERS +15 hrs 1900
6 WORKERS + 18 hrs. 2400
7 WORKERS + 21 hrs 2800
8 WORKERS + 24 hrs 3100
9 WORKERS + 27 hrs 3200
RETURNS TO SCALERETURNS TO SCALE(PRODUCTION OF AMN SHELLS IN ORD FACTORY PER MACHINE)
FACTORS OF PRODN EMP TOTAL PRODUCTS/RETURNS
MARGINAL PRODUCT/
RETURNS
STAGE OF RETURN TO SCALE
1 WORKER+3 hrs 200 200
2 WORKERS + 6 hrs 500 300
3 WORKERS + 9hrs 900 400
4 WORKERS+ 12 hrs 1400 500
5 WORKERS +15 hrs 1900 500
6 WORKERS + 18 hrs. 2400 500
7 WORKERS + 21 hrs 2800 400
8 WORKERS + 24 hrs 3100 300
9 WORKERS + 27 hrs 3200 100
RETURNS TO SCALERETURNS TO SCALE(PRODUCTION OF AMN SHELLS IN ORD FACTORY PER MACHINE)
FACTORS OF PRODN EMP TOTAL PRODUCTS/RETURNS
MARGINAL PRODUCT/
RETURNS
STAGE OF RETURN TO SCALE
1 WORKER+3 hrs 200 200 STAGE OF INCREASING RETURNS
2 WORKERS + 6 hrs 500 300
3 WORKERS + 9hrs 900 400
4 WORKERS+ 12 hrs 1400 500
5 WORKERS +15 hrs 1900 500 STAGE OF CONSTANT RETURNS
6 WORKERS + 18 hrs. 2400 500
7 WORKERS + 21 hrs 2800 400 STAGE OF DECREASING RETURNS
8 WORKERS + 24 hrs 3100 300
9 WORKERS + 27 hrs 3200 100
STAGE 1
STAGE 3
STAGE 2
1 2 3 4 5 6 7 8 9 10 11
MARGINAL
OUTPUT
NO OF COMPOSITE UNITS OF FACTORS OF PRODUCTION
4
3
2
1
0
6
5
MARGINAL PRODUCT CURVE
OPTIMAL POINT IN
EMPLOYMENT OF FACTORS
LAW OF RETURN TO SCALELAW OF RETURN TO SCALE
DIS-ECONOMIES START OPERATING AS SCALE
OF ACTIVITY IS RAISED BEYOND A POINT.
OPTIMUM MIX OF INPUTS TO ACHIEVE THE
RESULT VARIES WITH THE DEGREE OF
RESULT DESIRED.
APPLICABLE IN LONG RUN.
CDR MUST ANALYSE THAT MARGINAL RETURN
IN TERMS OF RESULT NOT LESS THAN
MARGINAL INCREASE IN INPUT.
LAW OF RETURN TO SCALELAW OF RETURN TO SCALE
PRODUCTION POSSIBILITY ANALYSISPRODUCTION POSSIBILITY ANALYSIS
• DETERMINES MAX RESULT POSSIBLE WITHIN
GIVEN RESOURCE ALLOCATION.
• ANALYSIS OF ONE INPUT – TWO OUTPUT CASE.
• DETERMINES MOST EFFICIENT COMBINATION
OF TWO FOR MAXIMISING RESULTS WITHIN
GIVEN ONE INPUT.
• TECHNIQUE MAKES USE OF PRODUCTION
POSSIBILITY CURVE.
PRODUCTION POSSIBILITY ANALYSISPRODUCTION POSSIBILITY ANALYSIS
EXAMPLE
• ALLOCATED BUDGET – C CRORES.
• ACQUISITION OF OPTIMUM COMBINATION OF
OFFENSIVE POTENTIAL (OP) AND DEFENSIVE
POTENTIAL (DP).
• C CRORE – 400 OP OR 930 DP POSSIBLE.
• DEFENCE PLANNER FORMULATES PRODUCTION
POSSIBILITY SCHEDULE.
PRODUCTION POSSIBILITY SCHEDULEPRODUCTION POSSIBILITY SCHEDULE(INPUT- DEFENCE RESOURCES OUTPUT -OP&DP)
POSSIBLE COMBINATIONS
OFFENSIVE POTENTIAL
DEFENSIVE POTENTIAL
A 400 0
B
C
D
E 0 940
COMBINATIONS POSSIBLE
PRODUCTION POSSIBILITY SCHEDULEPRODUCTION POSSIBILITY SCHEDULE(INPUT- DEFENCE RESOURCES OUTPUT -OP&DP)
POSSIBLE COMBINATIONS
OFFENSIVE POTENTIAL
DEFENSIVE POTENTIAL
A 400 0
B 300 520
C 200 730
D 100 870
E 0 940
COMBINATIONS POSSIBLE
REAL SITUATION PRODUCTION POSSIBILITY REAL SITUATION PRODUCTION POSSIBILITY
SCHEDULE CAN BE FORMULATED BASED ON COST SCHEDULE CAN BE FORMULATED BASED ON COST
BENEFIT ANALYSIS, SYSTEM ANALYSIS AND ORBENEFIT ANALYSIS, SYSTEM ANALYSIS AND OR
PRODUCTION POSSIBILITY CURVEPRODUCTION POSSIBILITY CURVE
0 200 400 600 800 1000 1200
500
400
300
200
100
0
E1
E2
E3I2
I1
NON FEASIBLE COMBINATION
DEFENSIVE POTENTIAL
OFFENSIVE
POTENTIAL
COMBINATIONS ON PP
CURVE ARE THE UTMOST
THAT BUDGET CAN FETCH
COMBINATIONS I 1 & I 2
NOT GETTING BEST
OUT OF BUDGET
PP CURVE FOR BUDGET C + X CRORES
EFFICIENCY
PRODUCTION POSSIBILITY CURVEPRODUCTION POSSIBILITY CURVE
0 200 400 600 800 1000 1200
500
400
300
200
100
0
E1E2
E3
DEFENSIVE POTENTIAL
OFFENSIVE
POTENTIALE4
CONCAVE NATURE OF PP CURVE
MARGINAL RATE OF TRANSFORMATION:
(MRT) AMOUNT OF ONE OBJECT GIVEN
TO ACHIEVE EXTRA AMOUNT OF OTHER
MRT: INCREASES PROGRESSIVELY
BECAUSE RESOURCES LESS AND
LESS ADAPTABLE TO OTHER
OBJECT IS DIVERTED.
PRODUCTION POSSIBILITY CURVEPRODUCTION POSSIBILITY CURVE
0 200 400 600 800 1000 1200
500
400
300
200
100
0
E1E2
E3
DEFENSIVE POTENTIAL
OFFENSIVE
POTENTIALE4
ALL COMBINATIONS ON PP CURVE
EFFICIENT: WHICH TO CHOOSE?
IC1
A
B
C
D
INDIFFERENCE CURVEINDIFFERENCE CURVE
ALL POINTS YIELD EQUAL LEVEL OF
MILITARY UTILITY OR EFFECTIVENESS.
DECISION MAKER INDIFFERENT TO
CHOICES BETWEEN COMBINATIONS.
0 200 400 600 800 1000 1200
500
400
300
200
100
0
DEFENSIVE POTENTIAL
OFFENSIVE
POTENTIAL
0 200 400 600 800 1000 1200
500
400
300
200
100
0
DEFENSIVE POTENTIAL
OFFENSIVE POTENTIAL
IC 2 IC 3IC 1
INDIFFERENCE MAPINDIFFERENCE MAP
EACH CURVE REPRESENTS
DIFFERENT LEVEL OF
EFFECTIVENESS.
PRODUCTION POSSIBILITY CURVE WITH INDIFFERENCE MAP SUPERIMPOSED
0 200 400 600 800 1000 1200
500
400
300
200
100
0
DEFENSIVE POTENTIAL
OFFENSIVE POTENTIAL
IC 2 IC 3IC 1
E1
E3
E4
E
N
N
I-INEFFICIENT
E- POSSIBLE & OPTIMUM
N-NON FEASIBLE
I
I
I
E2
E5
PRODUCTION POSSIBILITY CURVE WITH INDIFFERENCE MAP SUPERIMPOSED
0 200 400 600 800 1000 1200
500
400
300
200
100
0
DEFENSIVE POTENTIAL
OFFENSIVE POTENTIAL
IC 2 IC 3IC 1
E1
E3
E4
E
I
I
I
E2
E5
PP CURVE SHOWS ALL
COMBINATIONS UTMOST
THAT BUDGET CAN FETCH
(EFFICIENCY) .
INDIFFERENCE CURVE
SHOWS ALL COMBINATIONS
HAVING EQUAL LEVEL OF
MILITARY UTILITY
(EFFECTIVENESS) .
INDIFFERNCE CURVE ANALYSISNATIONAL SECURITY VS DEVP
0 10 20 3040 50 60 70 80 90
LEVEL OF SECURITY %
RATE OF ECO DEVP
20
10
POLICY FEASIBILITY
CURVE BASED ON
GDP
(TOTAL RESOURCES)
POLICY FEASIBLE AREA
0
INDIFFERENCE CURVE
DEFENCE EXP VS DEVP
0 10 20 3040 50 60 70 80 90
LEVEL OF SECURITY %
RATE OF ECO DEVP
20
10
INDIFFERENCE CURVES SHOWING THE DEGREE TO WHICH NATIONAL INTERESTS ARE METIC5
IC 4IC3
0
IC2
IC1
PRODUCTION POSSIBILITY CURVE WITH INDIFFERENCE CURVE SUPERIMPOSED
DEFENCE EXP VS DEVP
0 10 20 3040 50 60 70 80 90
LEVEL OF SECURITY %
RATE OF ECO DEVP
20
10
INDIFFERENCE CURVES SHOWING THE DEGREE TO WHICH NATIONAL INTERESTS ARE METIC5
IC 4IC3POLICY FEASIBLE AREA
0
POLICY FEASIBILITY CURVE BASED ON GDP(TOTAL RESOURCES)
E D
C
A
BIC2
IC1
PRODUCTION POSSIBILITY CURVE PRODUCTION POSSIBILITY CURVE APPLICATIONSAPPLICATIONS
A SQN OF TPT AIRCRAFT LIFTING MEN AND
MATERIAL.
AN ENGINEER COY CLEARING MINES AND
CONSTRUCTING DEFENCES.
A SET OF MACHINES PRODUCING TWO PRODUCTS.
FORCES USED NOW AND HELD IN RESERVE.
ALL SITUATIONS WHERE ONE RESOURCE CAN BE
USED FOR TWO PURPOSES
ISOQUANT CURVEISOQUANT CURVE
0 20 40 60 80 100
100
80
60
40
20
0
BOMBS
BOMBERS
10 TARGETS DESTRUCTION
TWO COMBINATION OF INPUTS
GIVING SAME OUTPUT
MORE BOMBERS WITH SINGLE BOMBS
BOMBERS WITH TWO BOMBS
LESSER NO OF BOMBERS
FLYING MORE SORTIES
ISOQUANT CURVESISOQUANT CURVES
20 TARGETS
30 TARGETS
40 TARGETS
0 20 40 60 80 100
100
80
60
40
20
0
BOMBS
BOMBERS
10 TARGETS
50 TARGETS
DIFFERENT ISOQUANT FOR
DIFFERENT OUTPUTS
IT IS POSSIBLE TO MOVE
TO HIGHER LEVEL OF
OUTPUT BY INCREASING
ATLEAST ONE INPUT.
ISOCOST LINE OR EXCHANGE CURVE OR EQUAL COST LINE OR BUDGET LINE
0 20 40 60 80 100
100
80
60
40
20
0
BOMBS
BOMBERSXX
YY YY11
VARIOUS COMBINATIONS OF
BOMBERS AND BOMBS THAT CAN
BE PROCURED IN GIVEN BUDGET
ISOQUANT & ISOCOSTCURVESISOQUANT & ISOCOSTCURVES
0 20 40 60 80 100
100
80
60
40
20
0
BOMBS
BOMBERS
20 TARGETS
50 TARGETS
30 TARGETS40 TARGETS
10 TARGETS
E1E
ISOCOST shows exchange/
subs between items keeping
budget constant (ECONOMY).
ISOQUANT shows exchange/ subs
between items keeping output
constant (EFFECTIVENESS).A
BD
ISOQUANT AND ISOCOST ANALYSIS ISOQUANT AND ISOCOST ANALYSIS APPLICATIONSAPPLICATIONS
SITUATIONS WHERE TWO PARTIALLY SUBSTITUTABLE FACTORS PRODUCE SAME OUTPUT.
EFFECTIVENESS IN A GIVEN BUDGET.
COMBINATION FOR A GIVEN BUDGET AND EFFECTIVENESS.
BUDGET INCREASE REQUIRED FOR ENHANCING EFECTIVENESS.
REDUCTION IN EFFECTIVENESS DUE TO BUDGET CUT OR INCREASE IN PRICE.