unit1 om

Operations Management (ME-601)

Prof. S. N. Varma

Ref.

Stevenson WJ; Operations Management; TMH

Hopp WJ and Spearman ML; Factory Physics; McGraw-Hill

Chary SN; Production and OM; TMH

Learning Objectives

Define the term operations management Compare and contrast service and manufacturing

operations Describe the operations function and the nature of

the operations manager’s jobBriefly describe the historical evolution of operations

managementIdentify current trends that impact operations

management

Operations ManagementOperations Management (OM) is defined as:

OM is management of input resources and the process of conversion to value added output of goods and/ or services to provide utility and satisfaction to customers.

The management of organization resources and systems/ processes that create/provide goods and/or services

OM affects: Organizations’ ability to competeEfficiency and effectiveness of non-profit organizationsNation’s ability to compete internationally

04/07/2023 Prof. S.N. Varma 1-4

The OrganizationThe Three Basic Functions

Actual functional division may be moree.g. Outsourcing, Info management(MIS) …

Organization

Finance Operations Marketing

21-Feb-12 Prof. S.N. Varma 1-5

Value-Added Conversion Process

The operations function involves the conversion of inputs into outputs

InputsMoney, Man, Machine, Material,INFO

Transformation/Conversion

process

Outputs Goods Services

Control

Efficiency Feedback

Effectiveness FeedbackFeedback and control

Value added

Dr. S.N. VARMA

The Resources Recycle

TRANSFORMATION / PROCESSING SYSTEM OF THE ENTERPRISE

MONEY- LAND, BUILDING

EQUIPMEN, MACHINES

MANAGERS(PLAN ETC)

LABOUR (OPERATION)

RAW-MATERIAL

PRODUCT /SERVICES

CONSUMER

RE

VE

NU

E

GOVERNMENT

REGULATIONS

LOBBYING

CONSUMER-ADVOCACY

SUPPLIERSLABOUR

MANAGERSFINANCIAL INSTSTOCK-

HOLDERS

INPUTS PROCSSINGOUTPUTS

RISK MONEY

TAXESCOST

WAGES

INTEREST

SALARY

04/07/2023 Prof. S.N. Varma 1-7

Types of Operations

Operations ExamplesGoods Producing Farming, mining, construction,

manufacturing, power generationStorage/TransportationWarehousing, trucking, mail

service, moving, taxis, buses,hotels, airlines

Exchange Retailing, wholesaling, banking,renting, leasing, library, loans

Entertainment Films, radio and television,concerts, recording

Communication Newspapers, radio and televisionnewscasts, telephone, satellites

04/07/2023 Prof. S.N. Varma 1-8

Automobile assembly, steel making

Home remodeling, retail sales

Automobile Repair, fast food

Goods-services Continuum

Computer repair, restaurant meal

Song writing, software development

Goods Service

Surgery, teaching

04/07/2023 Prof. S.N. Varma 1-9

Value added Food Processor

Inputs Processing Outputs

Raw Vegetables Cleaning Canned vegetables Metal Sheets Making cans

Water CuttingEnergy CookingLabor PackingBuilding LabelingEquipment

04/07/2023 Prof. S.N. Varma 1-10

Value added Hospital Process

Inputs Processing Outputs

Doctors, nurses Examination Healthy patientsHospital Surgery

Medical SuppliesMonitoringEquipment MedicationLaboratories Therapy

04/07/2023 Prof. S.N. Varma 1-11

Manufacturing or Service?

Tangible Act

Key differences- Goods v/s Services

Characteristic Goods Service

OutputProduction and delivery time

TangibleDifferent-seq

IntangibleSame

Variability of input Low HighLabor content Low HighVariability of output Low High

Measurement of productivity Easy Difficult

Opportunity to correct problems High Low

Inventory High LowEvaluation of output Easier DifficultPatentable Usually Not usual

1-12

OM is a major component of SCM. decisions:Deciding where to locate facilities What type of layoutForecastingCapacity planningSchedulingManaging inventoriesAssuring qualityMotivating employeesMarketing and Distribution managementAnd more . . .

Scope of Operations Management

Shift in Jobs v/s National Development

Three Basic Area

Under developed

Developing

Developed

Agriculture 80% 40% 8%

Manufacturing

12% 40% 30%

Services 8% 20% 62%

04/07/2023 Prof. S.N. Varma 14

© 20e River, N.J. 07458 Prof. S N Varma 1-15

Development of Service Economy

04/07/2023 Prof. S.N. Varma 1-16

Year Mfg. Service45 79 2150 72 2855 72 2860 68 3265 64 3670 64 3675 58 4280 44 4685 43 5790 35 6595 25 7500 30 70

02 25 75

U.S. Manufacturing vs. Service Employment

0102030405060708090

45 50 55 60 65 70 75 80 85 90 95 00 02 05

Year

Per

cent

Mfg.

Service

Decline in Jobs, but they are importantWhy Decline in jobs? Due to success in mgt (objective)

Productivity: Increasing productivity allows companies to maintain or

increase their output using fewer workers

Outsourcing (win-win, divide and improve): Some mfg. work has been

outsourced to more productive companies.Importance of Farming/ Mfg.

Food is a primary physical need Mfg. - Over 30% jobs with lucrative salary

Mfg. - Accounts for over 70% of value of U.S. exports

Average full-time compensation in mfg. about 20% higher than average of all

workers

Manufacturing workers more likely to have benefits

Productivity growth in manufacturing in the last 5 years is more than double in

U.S. economy

Challenges of Managing ServicesService jobs are often less structured than

manufacturing jobsCustomer contact is higherWorker skill levels are lowerServices hire many low-skill, entry-level workersEmployee turnover is higherInput variability is higherService performance can be affected by

worker’s personal factors

Basic Product-Process matrix

21-Feb-12 Prof. S.N. Varma 19

One of a Kind Low Volume

Multiple Products Moderate Volumes

Few Major ProductsHigh Volume

Commodity Products

Project

Job Shop

Batch

Line/ Mass Pr

Continuous Flow

Very Poor Fit(Unskilled)

Very Poor Fit(Genious)

Low ----------------VOLUME----------------- HighHigh --------Time between parts-------------- LowJumbled--Flow smoothness---------------- Smooth

Low

--

VA

RIE

TY

(pa

rts)

--

Hig

hLo

w

--P

roce

ss F

lexi

bilit

y-

Hig

hH

igh

--

Sta

ndar

diza

tion-

--

Low

Basic Plant Layouts


Basic Processes

Layout Examples

Continuous Flow Production (Fluid)

Product piping Refinery, Sugar Commodities

Mass Production Product Layout, Connected mechanized material transfer, assembly lines

Automobile, TV, Packed Food

Batch Production Mixed Flow, Cellular Layout, Disconnected lines,

Watches, Drilling Rigs

Job-shop Prod., Jumbled Flow

Process Layout Tools,

Project work, Jumbled Flow

Site work layout Dams, Ships, Houses

Decision MakingSystem Design-Structural–capacity

–location

–arrangement of departments

–product and service planning

–acquisition and placement of

Equipments - project works

System operation- infrastructural

–Product mix–

Inventory, Shop Floor C

– Master Prod Schedule–

04/07/2023 Prof. S.N. Varma 21

-- Personnel

Forecast, Aggregate plan

--Demand synch, Pull, CONWIP

-- Quality assurance

04/07/2023 Prof. S.N. Varma 1-22

Use of Models in Decision MakingA model is an abstraction of reality.

What are the pros and cons of models?

Tradeoffs

1. Physical or Iconic models e.g. 3D-models of plane, car, bldg2. Analogue or schematic models e.g. graphs, contours, pie diagram3. Symbolic or mathematical models e.g. algebraic, differential

equation

Dr S. N. VARMA

Mathematical Models

Mathematical models: Deterministic models

Allocation: LPP, IPP, Goal Prog, TPP, Assignment, Sequencing, Network models; Deterministic Inventory models, Dynamic P Non linear prog.; Capital Investment;

Probabilistic models Forecasting Decision theory, games and competitive strategy. Queuing and waiting models Probabilistic Dynamic programming Probabilistic Inventory Replacement

Simulation and Meta-heuristics algorithms for non-LP and combinatorial optimization:

Tabu search, simulated annealing, Genetic A, DE, teacher learner algo.

Merits and Demerits of ModelingAdvantages of Modeling:

Easy to use, less expensiveRequire user to organize, define problem and analysis Increase understanding of the problemEnable “what if” questionsConsistent tool for evaluation and standardized formatPower of mathematics

Disadvantages of modeling:Quantitative information may be emphasized over qualitativeModels may be incorrectly applied and results misinterpretedUse of models does not guarantee good decisions


How models are used? Phases/ methodology of Modeling: -

1. Search, define and formulate problem, list alternatives to evaluate.

2. Make hypothesis, construct model and validate with the real system

3. Experiment and deduct results leading to model conclusion & theory

4. Evaluate alternatives & compare/ verify with real system attributes

5. Select best solution, establish controls and implement.

6. Post audit

Dr S. N. VARMA

Real System

Hypothesis and modeling

Model conclusions, theory

Real system attributes

Draw conclusions

Formulate/ Inductive generalize

Test theory, verify

Experiment, deductions

Validate,

revise

Implement

04/07/2023 Prof. S.N. Varma 1-26

Pareto Phenomenon• A few factors account for a high

percentage of the occurrence of some event(s).

• 80/20 Rule - 80% of problems are caused by 20% of the activities.

How do we identify the vital few?

04/07/2023 Prof. S.N. Varma 1-27

Business Operations Overlap

Operations

FinanceMarketing

04/07/2023 Prof. S.N. Varma 1-28

Operations Interfaces

Public Relations

Accounting

IndustrialEngineering

Operations

Maintenance

Personnel

Purchasing

Distribution

MIS

Legal

04/07/2023 Prof. S.N. Varma 1-29

Suppliers’ Suppliers

DirectSuppliers Producer Distributor Final

Consumer

Simple Product Supply Chain

Supply Chain: A sequence of activitiesAnd organizations involved in producingAnd delivering a good or service

04/07/2023 Prof. S.N. Varma 1-30

Stage of Production Value Added

Value of Product

Farmer produces and harvests wheat $0.15 $0.15

Wheat transported to mill $0.08 $0.23

Mill produces flour $0.15 $0.38

Flour transported to baker $0.08 $0.46

Baker produces bread $0.54 $1.00

Bread transported to grocery store $0.08 $1.08

Grocery store displays and sells bread $0.21 $1.29

Total Value-Added $1.29

A Supply Chain for Bread

Historical Evolution of OM

From craft production to Industrial revolution (1770’s)Scientific Management, Work Study (1911-FW Taylor)

Mass production Interchangeable partsDivision of labor

Human relations movement (1920-80)Ergonomics, fatigue (Gilberth)Hawthorn Experiment (Not illumination but Motivation- Elton Mayo)Need hierarchy, hygienic-motivating factors (Maslow, Hertzberg)Theory-X and theory-Y (Mc Gregory)Theory Z, JIT Lean Mfg., TQM (Ohno Taichi)

Decision models (1915, 1960-80’s)Influence of Japanese manufacturers, Outsourcing

Management and IT RevolutionTechnology: The application of scientific discoveries to

the development and improvement of goods and servicesProduct and service technologyProcess technologyInformation technology revolution

The Internet, ERP, e-business, e-commerce Management technologyGlobalizationManagement of supply chainsOutsourcingAgility

Transparency Masters to accompany Heizer/Render – Principles of Operations Management, 5e, and Operations Management, 7e

© 2004 by Prentice Hall, Inc., Upper Saddle River, N.J. 07458 1-33

The Heritage of Operations Management

Division of labor (Adam Smith 1776 and Charles Babbage 1852)

Standardized parts (Whitney 1800)

Scientific Management (Taylor 1881)

Coordinated assembly line (Ford/Sorenson/Avery 1913)

Gantt charts (Gantt 1916)

Motion study (Frank and Lillian Gilbreth 1922)

Quality control (Shewhart 1924; Deming 1950)

Computer (Atanasoff 1938)

CPM/PERT (DuPont 1957)



The Heritage of O M -Contd

Material requirements planning (Orlicky 1960)

Computer aided design (CAD 1970)

Flexible manufacturing system (FMS 1975)

Baldrige Quality Awards (1980)

Computer integrated manufacturing (1990)

Globalization(1992)

Internet (1995)



Eli Whitney¨ Born 1765; died 1825¨ In 1798, received

government contract to make 10,000 muskets

¨ Showed that machine tools could make standardized parts to exact specifications¨ Musket parts could be used in

any musket© 1995 Corel Corp.



Frederick W. Taylor¨ Born 1856; died 1915¨ Known as ‘father of scientific

management’¨ In 1881, as chief engineer for

Midvale Steel, studied how tasks were done¨ Began first motion & time studies

¨ Created efficiency principles

© 1995 Corel Corp.



Taylor: Management Should Take More Responsibility for

Matching employees to right jobProviding the proper trainingProviding proper work methods and

toolsEstablishing legitimate incentives for

work to be accomplished



Frank & Lillian Gilbreth

¨ Frank (1868-1924); Lillian (1878-1972)

¨ Husband-and-wife engineering team

¨ Further developed work measurement methods

¨ Applied efficiency methods to their

home & 12 children! ¨ (Book & Movie: “Cheaper by the

Dozen,” book: “Bells on Their Toes”)

© 1995 Corel Corp.



¨ Born 1863; died 1947¨ In 1903, created Ford

Motor Company¨ In 1913, first used

moving assembly line to make Model T¨ Unfinished product

moved by conveyor past work station

¨ Paid workers very well for 1911 ($5/day!)

Henry Ford

‘Make them all alike!’

© 1995 Corel Corp.



W. Edwards Deming¨ Born 1900; died 1993¨ Engineer & physicist¨ Credited with teaching

Japan quality control methods in post-WW2

¨ Used statistics to analyze process

¨ His methods involve workers in decisions



Contributions FromHuman factorsIndustrial engineeringManagement scienceBiological sciencePhysical sciencesInformation science



Significant Events in OM Division of labor (Smith, 1776) Standardized parts (Whitney, 1800) Scientific management (Taylor, 1881) Coordinated assembly line (Ford 1913) Gantt charts (Gantt, 1916) Motion study (the Gilbreths, 1922) Quality control (Shewhart, 1924) CPM/PERT (Dupont, 1957) MRP (Orlicky, 1960) CAD and Flexible manufacturing systems (FMS) Manufacturing automation protocol (MAP) Computer integrated manufacturing (CIM)



New Challenges in OMLocal or national

focusBatch shipmentsLow price bid

purchasingLengthy product

developmentStandard productsJob specialization

¨ Global focus¨ Just-in-time¨ Supply chain partnering¨ Rapid product

development, alliances¨ Mass customization¨ Empowered employees,

teams

From To

Ethical IssuesFinancial statementsWorker safetyProduct safetyQualityEnvironmentCommunityHiring/firing workersClosing facilitiesWorker’s rights

Factory Physics and dynamicsDefinitionsWorkstations: a collection of one or more identical machines.

Parts: a component, sub-assembly, or an assembly that moves through the workstations.

End Items: parts sold directly to customers; relationship to constituent parts defined in bill of material (BOM).

Consumables: bits, chemicals, gasses, etc., used in process but do not become part of the product that is sold.

Routing: sequence of workstations needed to make a part.

Order: request from customer.

Job: transfer quantity on the line.

Definitions (cont.)Throughput (TH): for a line, throughput is the average quantity

of good (non-defective) parts produced per unit time.

Work in Process (WIP): inventory between the start and endpoints of a product routing.

Raw Material Inventory (RMI): material stocked at beginning of routing.

Crib and Finished Goods Inventory (FGI): crib inventory is material held in a stock-point at the end of a routing; FGI is material held in inventory prior to shipping to the customer.

Mfg. Lead/ Cycle Time (CT): time between release of the job at the beginning of the routing until it reaches an inventory point at the end of the routing.

Customer Lead Time: Time between customer order and delivery

Definitions (cont.)

Definition: A manufacturing system is a goal-oriented network of processes through which parts flow.

Structure: Plant is made up of routings (lines), which in turn are made up of processes.

Focus: Factory Physics® is concerned with the network and flows at the routing (line) level.

ParametersDescriptors of a Line:

1) Bottleneck Rate (rb): Rate (parts/unit time or jobs/unit time) of the process center having the highest long-term utilization, thus slowest flow.

2) Raw Process Time (T0): Sum of the long-term average process times of each station in the line.

3) Congestion Coefficient (): A unit less measure of congestion.Zero variability case, a = 0.“Practical worst case,” a = 1.“Worst possible case,” a = W0.

Little’s lawThis is a non-congestion, steady-state system flow law:

Time in system/ cycle time, CT=WIP/rb

Insights:Fundamental relationshipSimple units transformationDefinition of cycle time (CT = WIP/TH)WIP is main reason for delays, not process variance (though exp.

process variance with high capacity utilization causes high WIP)

Relationship:Critical WIP (W0): WIP level in which a line having no congestion

would achieve maximum throughput (i.e., rb) with minimum cycle time (i.e., T0).

W0 = rb T0

The Penny-Fab-1 exampleCharacteristics:

Four identical in series.Each takes 2 hours per piece (penny).No variability.CONWIP job releases.

Parameters:rb =

T0 =

W0 =

a =

0.5 pennies/hour

8 hours

0.5 8 = 4 pennies

0 (no variability, best case conditions)

The Penny-Fab-1 (WIP=1)The Penny-Fab-1 (WIP=1)

Time = 0 to 8 hours

Penny Fab-1 Performance

WIP TH CT THCT 1 0.125 8 1 2 0.250 8 2 3 0.375 8 3 4 0.500 8 4 5 6

The Penny Fab-1 (WIP=5)The Penny Fab-1 (WIP=5)

Time = 0 to 10 hours

Penny Fab-1 Performance

WIP TH CT THCT 1 0.125 8 1 2 0.250 8 2 3 0.375 8 3 4 0.500 8 4 5 0.500 10 5 6 0.500 12 6

TH vs. WIP: Best Case

0

0.1

0.2

0.3

0.4

0.5

0.6

0 1 2 3 4 5 6 7 8 9 10 11 12

WIP

TH

rb

W0

1/T0

CT vs. WIP: Best Case

02468

101214161820222426

0 1 2 3 4 5 6 7 8 9 10 11 12

WIP

CT

T0

W0

1/rb

Best Case Performance

Best Case Law:

The minimum cycle time (CTbest) for a given WIP level, w, is given byCTbest = T0 , if w ≤ W0

= w / rb, otherwise

The maximum throughput (THbest) for a given WIP level, w is given by,THbest = w/ T0 if w ≤ W0

= rb otherwise

Best Case Performance (cont.)

Example: For Penny Fab-1, rb = 0.5 and T0 = 8, so W0 = 0.5 8 = 4,

which are exactly the curves we plotted.

otherwise.

4 if

,2

,8CTbest

w

w

otherwise.

4 if

,5.0

,8/THbest

ww

Worst Case Observation: The Best Case yields the minimum

cycle time and maximum throughput for each WIP level.

Question: What conditions would cause the maximum cycle time and minimum throughput?

Experiment:Set process times same as Best Case (so rb and T0

unchanged)follow a marked job through systemimagine marked job experiences maximum queueing

Worst Case Penny FabWorst Case Penny Fab

Time = 0 hours


Time = 8 hours


Time = 16 hours


Time = 24 hours


Time = 32 hours Note:

CT = 32 hours= 4 8 = wT0

TH = 4/32 = 1/8 = 1/T0

TH vs. WIP: Worst Case

0

0.1

0.2

0.3

0.4

0.5

0.6

0 1 2 3 4 5 6 7 8 9 10 11 12

WIP

TH

rb

W0

1/T0

Best Case

Worst Case

CT vs. WIP: Worst Case

048

121620242832

0 1 2 3 4 5 6 7 8 9 10 11 12

WIP

CT

T0

W0

Best Case

Worst Case

Worst Case Performance Worst Case Law: The worst case cycle time for a given WIP level, w, is given by,

CTworst = w T0 ( CTbest= w/rb ,=wT0 / W0 )

The worst case throughput for a given WIP level, w, is given by,

THworst = 1 / T0 (Thbest = rb = W0 / T0 )

Randomness? None ! perfectly predictable, but bad!

Practical Worst Case Observation: There is a BIG GAP between the Best

Case and Worst Case performance. Question: Can we find an intermediate case that:

divides “good” and “bad” lines, and is computable?

Experiment: consider a line with a given rb and T0 and variable process time of maximum variability (exp.):single machine stationsbalanced lines, each station has same average timevariability such that all WIP configurations (states) are

equally likely (possible with memory-less exp Process T)

PWC Example – 3 jobs, 4 stations

State Vector State Vector1 (3,0,0,0) 11 (1,0,2,0) 2 (0,3,0,0) 12 (0,1,2,0) 3 (0,0,3,0) 13 (0,0,2,1) 4 (0,0,0,3) 14 (1,0,0,2) 5 (2,1,0,0) 15 (0,1,0,2) 6 (2,0,1,0) 16 (0,0,1,2) 7 (2,0,0,1) 17 (1,1,1,0) 8 (1,2,0,0) 18 (1,1,0,1) 9 (0,2,1,0) 19 (1,0,1,1) 10 (0,2,0,1) 20 (0,1,1,1)

clumped up states

spread out states

Note: average WIP at any station is 15/20 = 0.75, so jobs are spread evenly between stations.

Practical Worst Case

Let w = no. of jobs in system, N = no. stations in line, and t = average process time at all stations:

Average time at a station= time for (this + other) jobs

CT(single) = (1 + (w-1)/N) t

CT(line) = N [1 + (w-1)/N] t = Nt + (w-1)t = T0 + (w-1)/rb

= (W0 + w – 1)/ rb

TH = WIP/CT = [w/(w+W0-1)] rb

From Little’s Law

Practical Worst Case Performance

Practical Worst Case Definition: The practical worst case (PWC) cycle time for a given WIP level, w, is given by,

CTpwc = T0 + (w-1)/ rb

The PWC throughput for a given WIP level, w, is given by,

THpwc = w rb / (W0 + w – 1)

where W0 is the critical WIP.

TH vs. WIP: Practical Worst Case

0

0.1

0.2

0.3

0.4

0.5

0.6

0 1 2 3 4 5 6 7 8 9 10 11 12

WIP

TH

rb

W0

1/T0

Best Case

Worst Case

PWCGood (lean)

Bad (fat)

CT vs. WIP: Practical Worst Case

048

121620242832

0 1 2 3 4 5 6 7 8 9 10 11 12

WIP

CT

T0

W0

Best Case

Worst Case PWC

Bad (fat)

Good

(lean)

Penny Fab Two

10 hr

2 hr

5 hr 3 hr

Penny Fab Two

StationNumber

Number ofMachines

ProcessTime

StationRate

1 1 2 hr j/hr

2 2 5 hr j/hr

3 6 10 hr j/hr

4 2 3 hr j/hr

rb = ____________ T0 = ____________ W0 = ____________

0.5

0.4

0.6

0.67

0.4 p/hr 20 hr 8 pennies

Penny Fab Two Simulation (Time=0)

10 hr

2 hr

5 hr 3 hr

2

0

0.1

0.2

0.3

0.4

0.5

0 2 4 6 8 10 12 14 16 18 20 22 24 26

WIP

TH

Penny Fab Two Performance

Worst Case

Penny Fab

PF 2

Best Case

Practical Worst Case

1/T0

rb

W0

Note: processtimes in PF2have var equalto PWC.

But… unlike PWC, it hasunbalancedline and multimachine stations.

Intelligence region

Ignorance region

Penny Fab Two Performance (cont.)

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10 12 14 16 18 20 22 24 26

WIP

CT

Worst Case

Intelligence region

Best Case

Practical Worst

Case

T0

1/rb

W0

Ignorance region

Qualitative categories of Variability Quantitatively we have many discrete (Binomial- tossing

coin/dice, Poisson-Q system) and continuous variable (Expnl. Normal) distributions.

Qualitatively we can categories the variability as follows: Adverse variability Favorable variability Fair variability (Equal rectangular probability- random) Maximum variability (Exponential, memory-less distr.) Minimum var. (Any distr. with low Coeff. Of Var. σ/µ)


Surprise conclusions1. Variability can be due to Bad control or Randomness or both, but

badly controlled variability , knowingly or unknowingly, is worse than randomness. e.g. in a card game why we want random card? Why we select random person among all equal assumed.

2. Contrary to the balancing of connected and paced assembly line( no waiting Q), throughput of a non paced balanced flow shop with exponential distributed process time can be improved by unbalancing a station of the line. Since all stations are balanced and have TH equal to rb , a station can be unbalanced only by increasing TH of any station, which in turn (1). Reduces T0 , W0 (2). Reduce Q and BN mc

3. Contrary to the belief that throughput can only be increased by improving TH of a BN mc, increasing TH of non BN station will result in less congestion and slightly better results.


wTH

Prof. S.N. Varma 82

Thanks for Attention.Better info/ knowledge?

Break 2. Time?

21-Feb-12

2-83

Learning ObjectivesExplain Planning-controlling terms; strategic, tactical,

operation; interrelation- without plan what to control?Describe and give examples of time-based strategiesList and briefly discuss the primary ways that

business organizations compete. List reasons for the poor competitiveness of some

companies. Explain why strategy is important for competitivenessContrast strategy and tacticsMIS (ERP) as a strategic Tool for competitiveness

2-84

Learning Objectives

Define the term productivity and explain why it is important to organizations and to countries.

Relation between productivity and standard of livingRelation between Standard of living and happinessProductivity, distribution of benefits and social justiceProductivity and employment shift to servicesList some of the reasons for poor productivity and

some ways of improving it.

Planning and Control ConceptsWhy planning?

Planning is a significant and ongoing activity for mgt and individuals. It provide a framework for taking decisions leading towards the Mission. A Plan is necessary for any activity, though many times it is informal, not on form.

What is a plan:Def. A plan is predetermined course of actions to achieve certain goalsA plan is necessary to measure deviations and control the activities

MISSION

VISION

Goals

Objectives

Strategies

Plans, Budgets

What How

General

Specific

Policies, Rules

Tactics

Planning TerminologyDefinition of terms

Term Definition Example

Mission Broad statement of purpose of organization, assignment, task

Provide high quality product and service

Vision Dream, Aspiration, future state Become fortune 500 Co

Goals Gen. statement of what to achieve

Reduce service-response time without increasing staff

Strategies

Gen. approach to achieve goals

Improve process for handling service-requests

Objective Specific measurable results Reduce service completion time to 2 days

Plan, budgets

Schedule of activities to achieve objectives

Revise service call request

Policy Limit to acceptable behavior Design user friendly interface

2-87

Planning Example

Rita is a high school student. She would like to have a career in business, have a good job, and earn enough income to live comfortably.

Mission: Live a good lifeGoal: Successful career, good income

Strategy: Obtain a college education

Tactics: Select a college and a major

Operations: Register, buy books, take courses, study, graduate, get job

2-88

Planning and Decision Making

Mission

Goals

Organizational Strategies

Functional Goals

Finance Strategies

MarketingStrategies

OperationsStrategies

Tactics Tactics Tactics

Operatingprocedures

Operatingprocedures

Operatingprocedures

Dr. S.N. VARMA

Why Planning is difficult?Why Planning is frequently neglected ? It is a difficult cognitive (hard mental) activity. Avoid cognitive strain. It expose future uncertainties, human tend to avoid uncertainties. It reduce freedom of action (perceived), human avoid restrictions. It needs intensive efforts and concentration so need shut out other

activities It take decision without actual evaluation of envir., assumptions can

be wrong. Due to unreal planning or changes in environment, they are ignored

many times so people become reluctant to planning. It introduce inflexibility in action

Plans have Hierarchy as well network dependency

Strategic plan- time fencing few years (1-5, or more), refer to STRUCTURE

Tactical plan- time few months (1-15), refer to INFRASTRUCTURE/ OPERATION

Operational plan- time fencing freeze to few weeks (1-12), refer to CONTROL

Other plans

Contingency plan (when some distant (Im-) possibility happen)Daily, weekly, monthly,… Five year plans with nesting.

Strategies, policies, SWOTStrategy is from Greek ‘strategos’ (=general)= long-term course of

actionPolicies are general statements/ understandings to guide mgt

decisions; but strategies are to guide resource applications to achieve the goals.

Strategic plans must be supported by tactical and operational planning.

Strategic (general) planning means to analyze current situation, form mission and decide course of actions using resources to achieve goals.

The strategic plan process involve consideration of input (including goal), enterprise profile, top manager orientation, environment & alternative

Opportunity (maxi)

External fact

Threat (mini)

Weakness (mini)--------Internal factors------------------Strength (maxi)

SO strategy (maxi-maxi)

Most successful, utilize strength to take advantage of Opportunities

WO strategy (mini-maxi)e.g. development strategy to overcome weakness and take advantage of opportunity

WT strategy (mini-mini)

e.g. retrenchment, liquidation or joint venture by merging

ST strategy (maxi-mini)

e.g. use of strength to cope with or avoid threats

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Core Competency and Strategy

Distinctive/ Core CompetenciesThe special attributes or abilities that give anorganization a competitive edge

LocationsDistinctive/ core competency, specializationProduct mix and servicesCost, quality, time, flexibilityScale-based strategies

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Banks, ATMsConvenienceLocation

DisneylandNordstroms

Superior customer service

Service

Burger KingSupermarkets

VarietyVolume

Flexibility

Express Mail, Fedex,One-hour photo, UPS

Rapid deliveryOn-time delivery

Time

Sony TVLexus, CadillacPepsi, Kodak, Motorola

High-performance design or high quality Consistent quality

Quality

U.S. first-class postageMotel-6, Red Roof Inns

Low CostCost

Examples of Competitive Strategies

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Strategy FormulationDistinctive/ Core competenciesEnvironmental scanningSWOTOrder qualifiersOrder winnersStrategic decisions must consider globalizationWhat works in one country may not work in anotherOther issues

Political, social, cultural, and economic differences

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Strategy Formulation

Order qualifiers Characteristics that customers perceive as

minimum standards of acceptability to be considered as a potential purchase

Order winnersCharacteristics of an organization’s goods or

services that cause it to be perceived as better than the competition

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External FactorsEconomic conditionsPolitical conditionsLegal environmentTechnologyCompetitionMarkets

Key External and Internal Factors

Internal Factors• Human Resources• Facilities and equipment• Financial resources• Customers• Products and services• Technology• Suppliers

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Strategy must be followed by tactical/ operation plans

Tactical strategy–to take decisions for infrastructure and resources to achieve organization objectives

Operations strategy – The approach, consistent with organization strategy, that is used to guide the operations function.

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Strategic OM DecisionsDecision Area Affects

Product/ service design Costs, quality liability and environment

Capacity Cost structure, flexibility

Process and layout Costs, flexibility, skill level, capacity

Work design Quality of work life, employee safety, productivity

Location Costs, visibility

Quality Ability to meet or exceed customer expectations

Inventory Costs, shortages

Maintenance Costs, equipment reliability, productivity

Scheduling Flexibility, efficiency

Supply chains Costs, quality, agility, shortages, vendor relations

Projects New products, services, or systems

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Quality and Time Strategies

Quality-based strategiesFocuses on maintaining

or improving the quality of an organization’s products or services

Quality at the sourceTime-based strategies

Focuses on reduction of time needed to accomplish tasks

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Competitiveness:

How effectively an organization meets the wants and needs of customers relative to others that offer similar goods or services

Product-Portfolio matrix by BCGCapital Investment and returns are key

issues in strategic plan as well in project plan since it is an important resource; returns vary in rate, risk

Product-Portfolio matrix (Henderson, Boston Consultancy Group, 1970) help in deciding where capital and other resources should be invested STAR PRODUCTSQ-MARK ? PRODUCTS

Release funds by divesting DOGS

Generate funds to investCASH COWS

High

Indus-try growth

LowLow ------------------------Market Share--------------------------- High

Porter Competition-Model,1980Five basic forces affecting competency

and profit potential of industry


NEW ENTRY Threat

Existing Intra industry Rivalry

Bargaining Power of

SUPPLIERS

SUBSTITUTE Threat

Bargaining Power of BUYERS

Bargaining Power of Suppliers/Buyers

For Suppliers this includes: Input differentiation Supplier concentration Volume Cost relative to total dollars

For Buyers this includes: Buyer concentration Volume Integration

Entry Barriers Economies of scale

Product Differences

Brand Identity

Access to distribution

Cost advantages

Government policy

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Competitive Marketing, Operation Functions

Competitive Marketing Functions:Identifying consumer wants and needsPricingAdvertising and promotion

Competitive Operation Functions:Product and service designCostLocationQualityQuick response

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Why Some Organizations Fail

Too much emphasis on short-term financial performanceFailing to take advantage of strengths and opportunitiesNeglecting operations strategyFailing to recognize competitive threatsToo much emphasis in product and service design and

not enough on improvementNeglecting investments in capital and human resourcesFailing to establish good internal communicationsFailing to consider customer wants and needs….

Push/Pull View of Supply ChainsA Pull process is one driven by customer order and A Push process is

one started by supplier/ mfr in anticipation of customer order

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Procurement,Manufacturing and

Replenishment cyclesCustomer Order

Cycle

CustomerOrder Arrives

PUSH PROCESSES PULL PROCESSES

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Push-Pull view of Manufacturing StrategiesA Pull process is one driven by customer order and A Push process is

one started by supplier/ mfr in anticipation of customer order

A supply/ demand chain can be a pull process (ETO) or a combination of Push and Pull processes depending on the customer order decoupling point

Inventory Location Cust.-order decoupling ptMfg strategy/ environment

Supplier Raw Material WIP Finished Goods^ ^ ^ ^

ETO MTO ATO MTS

ETO = Engineer To Order; MTO = Make To Order

ATO = Assemble To Order (Modular Mfg); MTS = Make To Stock/ Store

Push-Pull Boundary

Customer Order

Push Process Pull process

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ProductivityProductivity: A measure of the effective use of

resources, usually expressed as the ratio of output to input; P = Output / Input (This is a Total measure)Value of this ratio must be more than 1 (synergy)

Partial measures = output/(single input)E.g. Output ; Output ; Output ; Output ;

Labour Raw Material Machine Energy

Multi-factor measures = output/(multiple inputs)E.g. Output ; Output

Labour+Capital+Energy Labour+Machine

Productivity Growth = Current P – Previous P

Previous P

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Units of output per kilowatt-hourDollar value of output per kilowatt-hour

Energy Productivity

Units of output per dollar inputDollar value of output per dollar input

Capital Productivity

Units of output per machine hourValue added / machine cost

Machine Productivity

Units of output per labor hourUnits of output per shiftValue-added per labor hour

Labor Productivity

Partial Productivity Examples

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Factors Affecting Productivity• Capital• Technology• Management• Quality• Standardization• Searching for lost or misplaced items• Scrap rates• Labor turnover, New workers, Layoffs• Safety• Use of Internet, Computer viruses, IT • Design of the workspace• Hygienic Policy and Motivation• Incentive plans that reward productivity

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Improving ProductivityGet management supportDevelop productivity measuresWork study, Method Improvement, Time StandardsMeasure and publicize improvementsEstablish reasonable goalsDetermine critical (bottleneck) operationsDon’t confuse productivity (P>1); efficiency (E< 1)

Standard Of Living and HappinessImproving Productivity generate surplus

and increases material wellbeing- SOL

High SOL does not guarantee Happiness.

Answer is in statistics- a high SOL has high positive correlation with Happiness


Productivity and EmploymentObjective of productivity improvements is to produce

more with less workerSo we should not wonder or worry for job shift!Presumption- there are infinite work to be done.It is the responsibility of Society and Government to

distribute benefits of productivity with social justice.Leisure time increases with increased productivity (If

your needs are minimum, you can rest without work) Energy can save labor and we feel better- happy.Not only happy but energy also improve longevity.


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