4-1McGraw-Hill/IrwinOperations Strategy Copyright © 2008 The McGraw-Hill Companies, Inc. All rights reserved.

Capacity Strategy

Chapter 4

4-2

Some issues from Biotech industry

Strategic impact of long lead times and (often) high financial impact

Models for timing and size Effects of variability Competitive factors

4-3

The Capacity Strategy Decision How much capacity should the company

have to cover expected demand in the short, intermediate and long term?

In what increments and when, or at what intervals, should the company add capacity?

What type of capacity should the company add?

Where in the value chain, internal or external to the company, should capacity be added?

4-4

Some Capacity Definitions Capacity: volume of output per period of

time Maximum or design capacity: the highest

rate of output that a process or activity can theoretically achieve

Effective or planned capacity: the output rate expected for a given activity or process

Demonstrated capacity: the actual level of output for a process or activity over time

Capacity utilization: the percentage of a facility’s maximum or effective capacity used by actual production

4-5

Means of Adding Capacity

Human resources Process technology Information technology Facilities Suppliers or subcontractors Extracting additional output from

existing resources:Quality improvementProcess optimization

4-6

Capacity Management Time Horizons

4-7

Capacity Expansion Alternatives Using Different Time Increments

4-8

Capacity models: The Lead, Lag, Stay-Even Model

Volu

me

Time

Lead Policy

Predicted demand

Lag Policy

Stay Even Policy

4-9

The Lead, Lag, Stay-Even Model: Choosing Among Them

4-10

Economies and Diseconomies of Scale in Facilities

4-11

Sizing Capacity Increments when Demand is Known or Certain: Optimum Expansion Intervals

4-12

Sizing Capacity Increments when Demand is Known or Certain: Guidelines

As discount rates rise, add capacity in smaller incrementsFuture expenditures on capacity are

relatively less expensiveThus, delaying expenditures is more

economical As scale factors rise, add capacity in

smaller incrementsCost per increment of capacity goes downMaking larger investments in capacity up

front isn’t worth it

4-13

Choosing Between Capacity Expansion Internally and at a Contractor

4-14

Lead time impact

4-15

Hedging for uncertainty – For specific time in future

Inventory problem ofCapacity during a time period (e.g.. kg. per

year) or, equivalentlyPhysical size of equipment (liters)

Set service level or use costs of not meeting capacity or falling short

Can use the newsvendor approach

4-16

Capacity expansion in Biotech Costs of not meeting demand are extremely large! Costs of extra capacity are large, but two orders of

magnitude lower Use newsvendor approach of costs of underage and

overage Co = Cost of overage, or cost of having one too many units

of capacity Cu = Cost of underage, or cost of having one too few units of

capacity Find z such that P(d<z) = Cu/(Co+Cu) For Genentech, this is 99.05%

4-17

Concept: Find percentile corresponding to cost balance point (critical fractile or

percentile)

Demand correspondingTo critical percentile

Area equal to percentile

4-18

Concept: Find percentile corresponding to cost balance point (critical fractile or percentile)

Demand correspondingTo critical percentile

Area equal to percentile

4-19

Normal distribution is an easy way to determine the appropriate demand levels

84% of area CSL ZUnder curve 84% 1(Z=1) 90%

1.28 95%

1.64 99%.

2.33

Calculate required capacity as:Average demand + z * standard deviation of demand

4-20

Note that high services greatly increase capacity!

Exhibit 4-24: Capacity Required as Service Level Increases

2500

3000

3500

4000

4500

5000

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1

Service Level

Cap

acit

y (U

nit

s)

4-21

How do we generalize for any lead time and also when the time is uncertain?

Required capacity increase = Expected demand growth over the lead time + z * σgL

σgL2 = E(L) * σg

2 + (E(g)) 2 * σL2

σgL = SQRT (E(L) * σg2 + (E(g)) 2 * σL

2)

Where E(L) = expected lead time σL = standard deviation of lead time E(g) = expected growth σg = standard deviation of growth

Example: 2% growth, 5 year lead, 5% uncertainty in five years, 98% service

Increase = 5x2% + 1.96x5% = 19.8% increase

4-22

Capacity Expansion under Uncertainty: Decision Analysis Models

4-23

Capacity Expansion under Uncertainty: Multistage Decision Analysis Models

4-24

Example for Genentech

BuildCCP3

Both approved

Lungapproved

Neitherapproved

Lung,Breast

approved

Option?

Lung,Breast

approved

.

.

.

Largeexpansion

.

.

.

4-25

Capacity Management and Flexibility

Capacity that can be used for multiple uses is more efficient in terms of hedging (safety capacity)

This can be in terms of flexible capacity or through postponement (stock components not finished goods)

Example: Suit one: sigma = 680 Suit two: sigma = 646

2.33 x sum = 3085 (99% service)Sigma for total demand is 938 (law of

large numbersPooled capacity yields 2.33x938 = 2186

4-26

Competition and Gaming with Capacity

4-27

Developing a Capacity Strategy

Understand the business strategy and competitive environment

Develop a demand forecast Identify capacity expansion (or

contraction) alternatives Apply relevant models to develop

capacity strategy Assess implications for flexibility and

balance Develop an implementation plan Implement, assess and measure results