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Strategic Capacity Management Dr. Ron Tibben-Lembke Operations Management.

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Presentation on theme: "Strategic Capacity Management Dr. Ron Tibben-Lembke Operations Management."— Presentation transcript:

1 Strategic Capacity Management Dr. Ron Tibben-Lembke Operations Management

2 Ideal Capacity of a Process What is the capacity of the system? Should we add any capacity? How should we run the system? Where should we keep inventory? 50/hr 20/hr10/hr 40/hr

3 Ideal Capacity of a Process What is the capacity of the system? 6 min 5 min 4 min 5 min

4 Productivity Productivity = Outputs / Inputs Partial:Output/Labor or Output/Capital Multifactor: Output / (Labor + Capital + Energy ) Total Measure: Output / Inputs

5 Automotive Productivity Book Data: Jaguar: 14 cars/employee Volvo: 29 cars/employee Mini: 39 cars/employee

6 Growth of Service Economy

7 U.S. Productivity Gains Product Development team structure (Eg: Chrysler Prowler, Boeing 777) Facilities improvements (less WIP, better quality, flexibility) Keiretsu-like supplier cooperation -- tight cooperation Strong, independent boards of directors

8 U. S. Productivity Gains Increased 1.37% per year Increased 2.37% per year Potential sources of productivity gains: Capital investment (1.13%) Labor Quality(0.25%) Technological progress(0.99%) Computers really are making us more productive. Source: WSJ, 8/1/00, Further Gains in Productivity are Predicted, A2

9 US Productivity Growth

10 Improving Productivity Develop productivity measurements– you cant improve what you cant measure Identify and Improve bottleneck operations first Establish goals, document and publicize improvements

11 U.S. Work and Productivity Source: International Labor Organization, 1999

12 What Would Henry Say? Ford introduced the $5 (per day) wage in 1914 He introduced the 40 hour work week so people would have more time to buy It also meant more output: 3*8 > 2*10 Now we know from our experience in changing from six to five days and back again that we can get at least as great production in five days as we can in six, and we shall probably get a greater, for the pressure will bring better methods. Crowther, Worlds Work, 1926

13 Forty Hour Week Ernst Abbe, Karl Zeiss optics 1896: as much done in 9 as in 8.

14 Marginal Output of Time As you work more hours, your productivity per hour goes down Eventually, it goes negative. Chapman, 1909

15 Crunch Mode Ea_spouse: 12/04 Pre-crunch SO was working 7 * 13: 91 per week! Maybe time off at 6pm Saturday $5k signing bonus, couldnt quit Class action: April 06 $14.9m Why Crunch Mode Doesnt Work: 6 Lessons

16 Learning Curves time/unit goes down consistently Down by 10% as output doubles We can use Logarithms to approximate this If you ever need this, me, and we can talk as much as you want

17 Example 3.3 Pauls12345 Bottles Bags Newmans Bottles Bags

18 Example 3.3 Bottles Bags ,0501,180 3 bottle machines 150k each/yr = 450k 5 bag machines, 250k each/yr = 1,250k

19 Example 3.3 Bottles Machines12223 Mach. usage Workers Bags ,0501,180 Machines23455 Mach Usage Workers

20 Capacity Tradeoffs Can we make combinations in between? 150,000 Two-door cars 120,000 4-door cars

21 How much do we have? We can only sustain so much effort. Best Operating Level Output level process designed for Lowest cost per unit Capacity utilization = capacity used best operating level Hard to run > 1.0 for long

22 Time Horizons Long-Range: over a year – acquiring, disposing of production resources Intermediate Range: Monthly or quarterly plans, hiring, firing, layoffs Short Range – less than a month, daily or weekly scheduling process, overtime, worker scheduling, etc.

23 Service Differences Arrival Rate very variable Cant store the products - yesterdays flight? Service times variable Serve me Right Now! Rates change quickly Schedule capacity in 10 minute intervals, not months How much capacity do we need?

24 Capacity Levels in Service Zone of non-service < Zone of service Critical Zone Mean service rate, Mean arrival rate, =100% =70%

25 Adding Capacity Expensive to add capacity A few large expansions are cheaper (per unit) than many small additions Large expansions allow of clean sheet of paper thinking, re-design of processes Carry unused overhead for a long time May never be needed Small expansions may pave the cow path

26 Capacity Planning How much capacity should we add? Conservative Optimistic Forecast possible demand scenarios (Chapter 10) Determine capacity needed for likely levels Determine capacity cushion desired

27 Reengineering Business Process Reengineering (Hammer and Champy) Companies grow over time, adding plants, lines, facilities, etc. Growth may not end in optimal form Re-design processes from ground up

28 Capacity Sources In addition to expanding facilities: Two or three shifts Outsourcing non-core activities Training or acquisition of faster equipment

29 Decision Trees Consider different possible decisions, and different possible outcomes Compute expected profits of each decision Choose decision with highest expected profits, work your way back up the tree.

30 Decision Trees Example 3.4, p.65 Computer store thinks demand may grow. Expansion costs $87k, new site $210k, and would cost same if wait a year New site: 55% chance of profits of $195k. 45% chance of $115k profits. Expand Current 55% chance of $190k profits 45% chance of $100k profits Wait and see- enlarge store next year if demand grows If high demand, $190k with expanded store If high demand, $170 with current store If weak demand, $105k with current store Find the expected profits over 5 years, choose best one.

31 Decision Trees Decision point Chance events Outcomes Calculate expected value of each chance event, starting at far right Working our way back toward the beginning, choosing highest expected outcome at each decision

32 Decision Trees Revenue - Move Cost Revenue – Expand Cost Weak Growth Strong Growth Move Expand Revenue Rev – Expand Cost Rev - Expand Cost Wait and See Weak Growth Strong Growth Expand Do nothing Hackers Computer Store

33 Possible 5 year Revenues New, growth: 195*5 – 210 = 765 New, low:115*5 – 210 = 365 Expand, growth:190*5 – 87 =863 Expand, low:100*5 – 87 =413 Wait, strong, expand: *4-87=843 Wait, strong, do nothing: 170*5 = 850 Wait, low, do nothing: 105*5 =525

34 Decision Trees Weak Growth Strong Growth Move Expand Wait and See Weak Growth Strong Growth Expand Do nothing Hackers Computer Store

35 Making the Decision Starting at the far right, look at the Wait and See option. If demand is strong, we would obviously not expand. $850k is better than $843. Eliminate the Expand option

36 Decision Trees Weak Growth Strong Growth Move Expand Wait and See Weak Growth Strong Growth Expand Do nothing Hackers Computer Store

37 Expected Values Move: 0.55* *365 = $585,000 Wait and See: 0.55* *525 = $703,750 Expand: 0.55 * * 413 = $660,500 Highest expected value is to Wait and see, and either way, do nothing!

38 Decision Trees Weak Growth Strong Growth Move Expand Wait and See Weak Growth Strong Growth Expand Do nothing Hackers Computer Store $585, , ,750

39 Other considerations Another criteria to use is to pick the one with the highest down side. Under this, do nothing still wins. We could also consider the expected value of the future cash streams. PV = $100/(1+r) = $100/(1.16)=$86.27

40 Present Values - p.377 At 16%, Next year is worth =(1+rate)^(-years) Year 2: Year 3: Year 4: Year 5: per year for 5 years: 195 * (3.274)

41 Decision Tree-NPV 428, , , ,429 Weak Growth Strong Growth Move Expand 343, , , Wait and See Weak Growth Strong Growth Expand Do nothing Hackers Computer Store $310, , ,857

42 Real Options Assess the value to me of being able to change my mind in the future Changed problem slightly - Reduced benefit doing nothing, high demand

43 Decision Trees Weak Strong Move Expand Wait and See Expand Do nothing Hackers Computer Store Weak Strong Weak Strong $465, , , Weak Strong Do Nothing 598,750

44 Real Options If we didnt have the wait and see option, we would Do Nothing. Option to wait and see is worth $5,750 Move Expand Wait and See 465, , ,500 Do Nothing 598,750 $5,750

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