1 Operations Management Lesson 4 Capacity Planning and Forecasting.

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Operations Management

Lesson 4Capacity Planning and

Forecasting

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What you will learn in this unit: Capacity Planning Making Capacity Planning Decisions Forecasting Process Types of Forecasting Methods Qualitative Methods Quantitative Methods

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Capacity planning

Capacity is the maximum output rate of a production or service facility

Capacity planning is the process of establishing the output rate that may be needed at a facility. Setting the effective capacity of the operation to meet the required demands

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Measuring Capacity Examples

There is no one best way to measure capacity Output measures like kegs per day are easier to understand With multiple products, inputs measures work better

Type of BusinessInput Measures of

CapacityOutput Measures

of Capacity

Car manufacturer Labor hours Cars per shift

Hospital Available beds Patients per month

Pizza parlor Labor hours Pizzas per day

Retail storeFloor space in square feet

Revenue per foot

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Capacity Information Needed

Design capacity: Maximum output rate under ideal

conditions A bakery can make 30 custom cakes per

day when pushed at holiday time Effective capacity:

Maximum output rate under normal (realistic) conditions

On the average this bakery can make 20 custom cakes per day

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Calculating Capacity Utilization Measures how much of the available

capacity is actually being used:

Measures effectiveness Use either effective or design

capacity in denominator

100%capacity

rateoutput actualnUtilizatio

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Example of Computing Capacity Utilization: In the bakery example the design capacity is 30 custom cakes per day. Currently the bakery is producing 28 cakes per day. What is the bakery’s capacity utilization relative to both design and effective capacity?

93%(100%)30

28(100%)

capacity design

output actual nUtilizatio

140%(100%)20

28(100%)

capacity effective

output actual nUtilizatio

design

effective

The current utilization is only slightly below its design capacity and considerably above its effective capacity

The bakery can only operate at this level for a short period of time

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How Much Capacity Is Best?

The Best Operating Level is the output that results in the lowest average unit cost

Economies of Scale: Where the cost per unit of output drops as volume of output

increases Spread the fixed costs of buildings & equipment over

multiple units, allow bulk purchasing & handling of material Diseconomies of Scale:

Where the cost per unit rises as volume increases Often caused by congestion (overwhelming the process with

too much work-in-process) and scheduling complexity

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Best Operating Level and Size

Alternative 1: Purchase one large facility, requiring one large initial investment Alternative 2: Add capacity incrementally in smaller chunks as needed

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Other Capacity Considerations Focused factories:

Small, specialized facilities with limited objectives

Plant within a plant (PWP): Segmenting larger operations into

smaller operating units with focused objectives

Subcontractor networks: Outsource non-core items to free up

capacity for what you do well Capacity cushions:

Plan to underutilize capacity to provide flexibility

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Making Capacity Planning Decisions

The three-step procedure for making capacity planning decisions is as follows: Step 1: Identify Capacity Requirements Step 2: Develop Capacity Alternatives Step 3: Evaluate Capacity Alternatives

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Good forecasts are essential for effective capacity planning.But so is an understanding of demand uncertainty because it allows you to judge the risks to service level.

When demand uncertainty is high the risks to service level of under provision of capacity are high.

DE

MA

ND

TIME

Distribution of demand

DE

MA

ND

TIME

Only 5% chance of demand being higher than this

Only 5% chance of demand being lower than this

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Forecasting Steps What needs to be forecast?

Level of detail, units of analysis & time horizon required

What data is available to evaluate? Identify needed data & whether it’s

available Select and test the forecasting model

Cost, ease of use & accuracy Generate the forecast Monitor forecast accuracy over time

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Types of Forecasting Models

Qualitative methods: Forecasts generated subjectively by

the forecaster

Quantitative methods: Forecasts generated through

mathematical modeling

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Quantitative Methods Time Series Models:

Assumes the future will follow same patterns as the past

Causal Models: Explores cause-and-effect relationships Uses leading indicators to predict the future E.g. housing starts and appliance sales

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Time Series Data Composition

Data = historic pattern + random variation Historic pattern to be forecasted:

Level (long-term average) Trend Seasonality Cycle

Random Variation cannot be predicted

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Time Series Patterns

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Causal Models Often, leading indicators can help to predict

changes in future demand e.g. housing starts Causal models establish a cause-and-effect

relationship between independent and dependent variables

A common tool of causal modeling is linear regression:

Additional related variables may require multiple regression modeling

bxaY

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Linear Regression

XXX

YXXYb

2

Identify dependent (y) and independent (x) variables

Solve for the slope of the line

Solve for the y intercept

Develop your equation for the trend line

Y=a + bX

XbYa

22 XnX

YXnXYb

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Linear Regression Problem: A maker of golf shirts has been tracking the relationship between sales and advertising dollars. Use linear regression to find out what sales might be if the company invested $53,000 in advertising next year.

22 XnX

YXnXYbSales $

(Y)Adv.$

(X)XY X^

2Y^2

1 130 32 4160 2304

16,900

2 151 52 7852 2704

22,801

3 150 50 7500 2500

22,500

4 158 55 8690 3025

24964

5 153.85

53

Tot 589 189 28202

9253

87165

Avg

147.25

47.25

153.85531.1592.9Y

1.15X92.9bXaY

92.9a

47.251.15147.25XbYa

1.1547.2549253

147.2547.25428202b

2

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How Good is the Fit? Correlation coefficient (r) measures the direction and strength of

the linear relationship between two variables. The closer the r value is to 1.0 the better the regression line fits the data points.

Coefficient of determination ( ) measures the amount of variation in the dependent variable about its mean that is explained by the regression line. Values of ( ) close to 1.0 are desirable.

.964.982r

.98258987,1654*(189)-4(9253)

58918928,2024r

YYn*XXn

YXXYnr

22

22

22

22

2r

2r

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How do you cope with fluctuations in demand?

How do you cope with fluctuations in demand?

Absorb Demand

Absorb Demand

Adjust output to

match demand

Adjust output to

match demand

Change demand

Change demand

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Absorb demand

Absorb demand

Keep output level

Keep output level

Make to

stock

Make to

stock

Make customer

wait

Make customer

wait

Part finished,Finished Goods, orCustomer Inventory

QueuesBacklogs

Have excess

capacity

Have excess

capacity

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Types of Aggregate Plans Level Aggregate Plans

Maintains a constant workforce Sets capacity to accommodate average demand Often used for make-to-stock products like appliances Disadvantage- builds inventory and/or uses back orders

Chase Aggregate Plans Produces exactly what is needed each period Sets labor/equipment capacity to satisfy period demands Disadvantage- constantly changing short term capacity

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Absorb Demand Level capacity plan› Anticipation inventory

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Principles of the Chase Method

The chase method helps firms match production and demand by hiring and firing workers as necessary to control output

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Adjust output to match demand

Chase capacity plan

› Adjustment methods Overtime & idle time Workforce size Part-time staff Sub-contracting

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The tasks of capacity planning Some key questions

Calculate Capability of Operations Resources

Calculate Capability of Operations Resources

Allocate Resources Over Time

Allocate Resources Over Time

Design “Capacity Control” Mechanisms

Design “Capacity Control” Mechanisms

Forecast Demand or Revenue Potential

Forecast Demand or Revenue Potential

Can you predict the most likely demand at any point in time?

Can you predict the uncertainty in demand at any point in time?

Can you predict the most likely demand at any point in time?

Can you predict the uncertainty in demand at any point in time?

Do you have realistic work standards??

Do you understand the capacity constraints of all the necessary resources?

Do you have realistic work standards??

Do you understand the capacity constraints of all the necessary resources?

What are the options for capacity allocation?

What are their cost, revenue, work capital and service level implications?

What are their flexibility implications?

What are the options for capacity allocation?

What are their cost, revenue, work capital and service level implications?

What are their flexibility implications?

Do you monitor actual demand against forecast?

Do you adapt forecasts accordingly?Do you replan capacity accordingly?

Do you monitor actual demand against forecast?

Do you adapt forecasts accordingly?Do you replan capacity accordingly?