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Operations ManagementOperations Management
Class 4 Class 4
Demand Management and ForecastingDemand Management and ForecastingDesign of goods and servicesDesign of goods and services
source: (Heizer & Render 2008) and (Gardiner 2008)source: (Heizer & Render 2008) and (Gardiner 2008)
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Learning ObjectivesLearning Objectives
– Define and understand demand managementDefine and understand demand management– Understand three forecasting time horizonsUnderstand three forecasting time horizons– Understand quantitative and qualitative Understand quantitative and qualitative
forecasting modelsforecasting models– Apply moving average forecasting methodApply moving average forecasting method– Calculate mean average deviationCalculate mean average deviation– Define product life cycleDefine product life cycle– Describe a product development systemDescribe a product development system– Build a house of qualityBuild a house of quality
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Part 1 ForecastingPart 1 Forecasting
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Demand Demand (DG book)(DG book)– Need for a product or serviceNeed for a product or service– What the customer wants – may not be What the customer wants – may not be
the same as what the company is willing the same as what the company is willing or able to supplyor able to supply
– Strategic Decision, prepare for future Strategic Decision, prepare for future demand (Finished Goods Inventory – demand (Finished Goods Inventory – Service Staffing Levels etc.)Service Staffing Levels etc.)
– Companies can influence demand Companies can influence demand – ‘‘Demand Forecasting’Demand Forecasting’
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Components of DemandComponents of DemandD
eman
d fo
r pro
duct
or s
ervi
ce
| | | |1 2 3
4Year
Average demand over four years
Seasonal peaks
Trend component
Actual demand
Random variation
Figure 4.1Figure 4.1
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What is Forecasting?What is Forecasting?• Process of predicting future event.Process of predicting future event.• Forecast is an estimate of future demandForecast is an estimate of future demand• Underlying basis for business decisions Underlying basis for business decisions
(capital expenditure)(capital expenditure)• Capacity PlanningCapacity Planning• Facility PlanningFacility Planning• Process PlanningProcess Planning• Operations PlanningOperations Planning• Equipment, Personnel, Materials, InventoryEquipment, Personnel, Materials, Inventory
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Time HorizonsTime Horizons• Short-range forecastShort-range forecast
• Up to 1 year, generally less than 3 monthsUp to 1 year, generally less than 3 months• Purchasing, job scheduling, workforce levels, job Purchasing, job scheduling, workforce levels, job
assignments, production levelsassignments, production levels• Medium-range forecastMedium-range forecast
• 3 months to 3 years3 months to 3 years• Sales and production planning, budgetingSales and production planning, budgeting
• Long-range forecast (ball park)Long-range forecast (ball park)• 33++ years years• New product planning, facility location, research and New product planning, facility location, research and
developmentdevelopment
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Seven Steps in ForecastingSeven Steps in Forecasting• Determine the use of the forecastDetermine the use of the forecast• Select the items to be forecastedSelect the items to be forecasted• Determine the time horizon of the forecastDetermine the time horizon of the forecast• Select the forecasting model(s)Select the forecasting model(s)• Gather the dataGather the data• Make the forecastMake the forecast• Validate and implement resultsValidate and implement results
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Forecasting ApproachesForecasting Approaches
Quantitative Methods Quantitative Methods (what has happened in the past will happen in the (what has happened in the past will happen in the
future, ‘numerical’)future, ‘numerical’)
• Used when situation is ‘stable’ and historical data Used when situation is ‘stable’ and historical data existexist• Existing productsExisting products• Current technologyCurrent technology
• Involves mathematical techniquesInvolves mathematical techniques• e.g., forecasting sales of color televisionse.g., forecasting sales of color televisions
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Forecasting ApproachesForecasting Approaches
Qualitative MethodsQualitative Methods(subjective, judgmental)(subjective, judgmental)
• Used when situation is vague and little data Used when situation is vague and little data existexist• New productsNew products• New technologyNew technology
• Involves intuition, experienceInvolves intuition, experience• e.g., forecasting sales on Internete.g., forecasting sales on Internet
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Qualitative MethodsQualitative Methods• Jury of executive opinionJury of executive opinion
• Pool opinions of high-level Pool opinions of high-level experts, sometimes experts, sometimes augment by statistical augment by statistical modelsmodels
• Delphi methodDelphi method• Panel of experts, queried Panel of experts, queried
iterativelyiteratively
• Sales Force CompositeSales Force Composite• Customer SurveyCustomer Survey
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Two Quantitative MethodsTwo Quantitative Methods
• Simple Moving Average Simple Moving Average • Weighted Moving AverageWeighted Moving Average
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Moving AverageMoving Average
• MA is a series of arithmetic means MA is a series of arithmetic means • Used if little or no trendUsed if little or no trend• Used often for smoothingUsed often for smoothing
• Provides overall impression of data Provides overall impression of data over timeover time
Moving average =Moving average = ∑∑ demand in previous n periodsdemand in previous n periodsnn
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MA ExampleMA Example
JanuaryJanuary 1010FebruaryFebruary 1212MarchMarch 1313AprilApril 1616MayMay 1919JuneJune 2323JulyJuly 2626
ActualActual 3-Month3-MonthMonthMonth Shed SalesShed Sales Moving AverageMoving Average
(12 + 13 + 16)/3 = 13 (12 + 13 + 16)/3 = 13 22//33
(13 + 16 + 19)/3 = 16(13 + 16 + 19)/3 = 16(16 + 19 + 23)/3 = 19 (16 + 19 + 23)/3 = 19 11//33
101012121313
((1010 + + 1212 + + 1313)/3 = 11 )/3 = 11 22//33
What could we use if a trend exists? What could we use if a trend exists? WMAWMA
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Forecasting ErrorsForecasting Errors• Lies, Damned Lies and ForecastsLies, Damned Lies and Forecasts
– Always incorrect, to some extentAlways incorrect, to some extent
• Multiple reasonsMultiple reasons– Inappropriate MethodInappropriate Method– Past data does not hold true for the futurePast data does not hold true for the future
• Mean Absolute Deviation MADMean Absolute Deviation MAD– Used to measure the forecasting errorUsed to measure the forecasting error
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MADMAD
Mean Absolute Deviation Mean Absolute Deviation ((MADMAD))
MAD =MAD =∑∑ |Actual - Forecast||Actual - Forecast|
nn
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Design of Goods and ServicesDesign of Goods and Services
• Strategically important.Strategically important.– Get it right, huge success AppleGet it right, huge success Apple– Get it wrong, Sony Betamax/BluRay?Get it wrong, Sony Betamax/BluRay?
• Focus customer satisfactionFocus customer satisfaction– Need to understand their requirementsNeed to understand their requirements– Voice of the customerVoice of the customer
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Design Design
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Design of Goods and ServicesDesign of Goods and Services
• Focus on Core Strengths (SWOT)Focus on Core Strengths (SWOT)– What are we really good atWhat are we really good at
• Intel focus on microprocessorsIntel focus on microprocessors• Sony > Electronics- Sony > Electronics-
TV’s>Music>Movies>Games?TV’s>Music>Movies>Games?
• Goal Goal – Meet the demands of the marketplace with Meet the demands of the marketplace with
a competitive advantagea competitive advantage
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OpportunitiesOpportunities
• Customer DrivenCustomer Driven• Technology DrivenTechnology Driven• Social-demographic changeSocial-demographic change• Political or Legal changePolitical or Legal change
““Innovate or die”Innovate or die”
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Product Life CyclesProduct Life Cycles
Negative cash flow
IntroductionIntroduction GrowthGrowth MaturityMaturity DeclineDecline
Sale
s, c
ost,
and
cash
flow
Sale
s, c
ost,
and
cash
flow Cost of development and productionCost of development and production
Cash Cash flowflow
Net revenue (profit)Net revenue (profit)Sales revenueSales revenue
LossLoss
Figure 5.1Figure 5.1
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Product Development StagesProduct Development Stages
Scope of product
development team
Scope for design and engineering
teams
Evaluation
Introduction
Test Market
Functional Specifications
Design Review
Product Specifications
Customer Requirements
Ability
IdeasFigure 5.3Figure 5.3
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Organising For Product Organising For Product Development Development
•Traditional Approach Traditional Approach •Distinct DepartmentsDistinct Departments
•R&D, Marketing, Design, ProductionR&D, Marketing, Design, Production
•MuIti-disciplinary ApproachMuIti-disciplinary Approach•Product Development Teams Product Development Teams •Representatives from all departmentsRepresentatives from all departments
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Quality Function DeploymentQuality Function Deployment•Identify customer Identify customer wantswants•Identify Identify howhow the good/service will satisfy the good/service will satisfy customer wantscustomer wants•Relate customer wants to product howsRelate customer wants to product hows•Identify relationships between the firm’s Identify relationships between the firm’s howshows•Develop importance ratingsDevelop importance ratings•Evaluate competing productsEvaluate competing products•Compare performance to desirable Compare performance to desirable technical attributestechnical attributes
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QFD House of QualityQFD House of Quality
Relationshipmatrix
How to satisfycustomer wants
Interrelationships
Com
petit
ive
asse
ssm
ent
Technicalevaluation
Target values
What the customer
wants
Customer Customer importance importance
ratingsratings
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House of Quality ExampleHouse of Quality Example
Your team has been charged with Your team has been charged with designing a new camera for Great designing a new camera for Great Cameras, Inc.Cameras, Inc.The first action is The first action is to construct a to construct a House of QualityHouse of Quality
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House of Quality ExampleHouse of Quality Example
CustomerCustomerimportanceimportance
ratingrating(5 = highest)(5 = highest)
Lightweight 3Easy to use 4Reliable 5Easy to hold steady 2Color correction 1
What the What the customer customer
wantswants
What the Customer
Wants
RelationshipMatrix
TechnicalAttributes and
Evaluation
How to SatisfyCustomer Wants
Interrelationships
Ana
lysi
s of
Com
petit
ors
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House of Quality ExampleHouse of Quality ExampleWhat the Customer
Wants
RelationshipMatrix
TechnicalAttributes and
Evaluation
How to SatisfyCustomer Wants
Interrelationships
Ana
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Com
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Low
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How to SatisfyCustomer Wants
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Lightweight 3Easy to use 4Reliable 5Easy to hold steady 2Color corrections 1
House of Quality ExampleHouse of Quality ExampleWhat the Customer
Wants
RelationshipMatrix
TechnicalAttributes and
Evaluation
How to SatisfyCustomer Wants
Interrelationships
Ana
lysi
s of
Com
petit
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High relationshipHigh relationshipMedium relationshipMedium relationshipLow relationshipLow relationship
Relationship matrixRelationship matrix
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House of Quality ExampleHouse of Quality ExampleWhat the Customer
Wants
RelationshipMatrix
TechnicalAttributes and
Evaluation
How to SatisfyCustomer Wants
Interrelationships
Ana
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Relationships Relationships between the between the things we can dothings we can do
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House of Quality ExampleHouse of Quality Example
Weighted Weighted ratingrating
What the Customer
Wants
RelationshipMatrix
TechnicalAttributes and
Evaluation
How to SatisfyCustomer Wants
Interrelationships
Ana
lysi
s of
Com
petit
ors
Lightweight 3Easy to use 4Reliable 5Easy to hold steady 2Color corrections 1Our importance ratings 22 9 27 27 32 25
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House of Quality ExampleHouse of Quality Example
Com
pany
A
Com
pany
B
G PG PF GG PP P
Lightweight 3Easy to use 4Reliable 5Easy to hold steady 2Color corrections 1Our importance ratings 22 5
How well do How well do competing products competing products meet customer wantsmeet customer wants
What the Customer
Wants
RelationshipMatrix
TechnicalAttributes and
Evaluation
How to SatisfyCustomer Wants
Interrelationships
Ana
lysi
s of
Com
petit
ors
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House of Quality ExampleHouse of Quality ExampleWhat the Customer
Wants
RelationshipMatrix
TechnicalAttributes and
Evaluation
How to SatisfyCustomer Wants
Interrelationships
Ana
lysi
s of
Com
petit
ors
Target values(Technical attributes)
Technical evaluation
Company A 0.7 60% yes 1 ok GCompany B 0.6 50% yes 2 ok FUs 0.5 75% yes 2 ok G
0.5
A
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House of Quality ExampleHouse of Quality Example
Completed Completed House of House of QualityQuality
Lightweight 3Easy to use 4Reliable 5Easy to hold steady 2Color correction 1Our importance ratings
Low
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Com
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Com
pany
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G PG PF GG PP P
Target values(Technical attributes)
Technical evaluation
Company A 0.7 60% yes 1 ok G
Company B 0.6 50% yes 2 ok F
Us 0.5 75% yes 2 ok G0.
5 A
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22 9 27 27 32 25
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ReferencesReferences• Heizer, J., & Render, B. (2008). Heizer, J., & Render, B. (2008). Operations managementOperations management (9th (9th
ed.). Saddle River, New Jersey: Pearson Prentice Hall.ed.). Saddle River, New Jersey: Pearson Prentice Hall.
• Gardiner, D.,(2008). Gardiner, D.,(2008). Operations Management for Business Operations Management for Business Excellence Excellence (2(2ndnd ed.). Rosedale, North Shore: Pearson Education ed.). Rosedale, North Shore: Pearson Education New Zealand.New Zealand.