1. 4-1 McGraw-Hill/Irwin Operations Strategy Copyright © 2008 The McGraw-Hill Companies, Inc. All rights reserved. Capacity Strategy Chapter 4

2. 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

3. 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. 4-4 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

5. 4-5 Means of Adding Capacity  Human resources  Process technology  Information technology  Facilities  Suppliers or subcontractors  Extracting additional output from existing resources:  Quality improvement  Process optimization

6. 4-6 Capacity Management Time Horizons

7. 4-7 Capacity Expansion Alternatives Using Different Time Increments

8. 4-8 Capacity models: The Lead, Lag, Stay-Even Model Stay Even Policy

9. 4-9 The Lead, Lag, Stay-Even Model: Choosing Among Them

10. 4-10 Economies and Diseconomies of Scale in Facilities

11. 4-11 Sizing Capacity Increments when Demand is Known or Certain: Optimum Expansion Intervals

12. 4-12 Sizing Capacity Increments when Demand is Known or Certain: Guidelines  As discount rates rise, add capacity in smaller increments  Future expenditures on capacity are relatively less expensive  Thus, delaying expenditures is more economical  As scale factors rise, add capacity in smaller increments  Cost per increment of capacity goes down  Making larger investments in capacity up front isn’t worth it

13. 4-13 Choosing Between Capacity Expansion Internally and at a Contractor

14. 4-14 Lead time impact

15. 4-15 Hedging for uncertainty – For specific time in future  Inventory problem of  Capacity during a time period (e.g.. kg. per year) or, equivalently  Physical size of equipment (liters)  Set service level or use costs of not meeting capacity or falling short  Can use the newsvendor approach

16. 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%

17. 4-17 Concept: Find percentile corresponding to cost balance point (critical fractile or percentile) Demand corresponding To critical percentile Area equal to percentile

18. 4-18 Concept: Find percentile corresponding to cost balance point (critical fractile or percentile) Demand corresponding To critical percentile Area equal to percentile

19. 4-19 Normal distribution is an easy way to determine the appropriate demand levels 84% of areaCSLZ Under curve84%1 (Z=1)90%1.28 95% 1.64 99%. 2.33 Calculate required capacity as: Average demand + z * standard deviation of demand

20. 4-20 Note that high services greatly increase capacity!

21. 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 * σ gL  σ gL 2 = E(L) * σ g 2 + (E(g)) 2 * σ L 2  σ gL = SQRT (E(L) * σ g 2 + (E(g)) 2 * σ L 2 )  Where  E(L) = expected lead time  σ L = standard deviation of lead time  E(g) = expected growth  σ g = standard deviation of growth  Example: 2% growth, 5 year lead, 5% uncertainty in five years, 98% service  Increase = 5x2% + 1.96x5% = 19.8% increase

22. 4-22 Capacity Expansion under Uncertainty: Decision Analysis Models

23. 4-23 Capacity Expansion under Uncertainty: Multistage Decision Analysis Models

24. 4-24 Example for Genentech Build CCP3 Both approved Lung approved Neither approved Lung, Breast approved Option? Lung, Breast approved...... Large expansion......

25. 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 numbers Pooled capacity yields 2.33x938 = 2186

26. 4-26 Competition and Gaming with Capacity

27. 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