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5. Strategic Capacity Planning

5. Strategic Capacity Planning. Dr. Ron Lembke Operations Management. 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/hr. 10/hr. 40/hr. Ideal Capacity of a Process.

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5. Strategic Capacity Planning

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  1. 5. Strategic Capacity Planning Dr. Ron 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/hr 10/hr 40/hr

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

  4. 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, World’s Work, 1926

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

  6. How much do we have? • Design capacity: max output designed for • Effective Capacity • We can only sustain so much effort. • Output level process designed for • Lowest cost per unit • Efficiency = Actual Output Effective Capacity • Possible to run > 1.0 for long • Utilization = Actual Output/Design Capacity

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

  8. 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.

  9. 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”

  10. 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

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

  12. Cost-Volume Analysis R*Q FC+VC*Q Break-Even Point Volume, Q FC = Fixed Cost v = variable cost per unit Q = quantity R = revenue per unit R-v=contrib. margin

  13. Cost Volume Analysis Solve for Break-Even Point For profit of P, Q = P + FC R - v

  14. 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.

  15. Draw the decision tree

  16. Working Right to Left, eliminate any Possible decisions we can.

  17. Compute Expected Values of Remaining Decisions Build small = 0.4 * $40 + 0.6 * $55 = $16 + $33 = $49 $49 $62 Build large = 0.4 * $50 + 0.6 * $70 = $20 + $42 = $62

  18. Decision Trees Example • 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.

  19. 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

  20. Rev – Expand Cost Revenue - Move Cost Revenue - Move Cost Revenue – Expand Cost Revenue – Expand Cost Rev - Expand Cost Revenue Decision Trees Strong Growth Move 0.55 Weak Growth 0.45 Strong Growth 0.55 Hackers’ Computer Store Expand Weak Growth 0.45 Expand Wait and See Strong Growth Do nothing 0.55 Weak Growth 0.45

  21. 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: 170+190*4-87=843 • Wait, strong, do nothing: 170*5 = 850 • Wait, low, do nothing: 105*5 = 525

  22. 843 765 365 863 413 850 525 Decision Trees Strong Growth Move 0.55 Weak Growth 0.45 Strong Growth 0.55 Hackers’ Computer Store Expand Weak Growth 0.45 Expand Wait and See Strong Growth Do nothing 0.55 Weak Growth 0.45

  23. 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”

  24. 843 765 365 863 413 850 525 Decision Trees Strong Growth Move 0.55 Weak Growth 0.45 Strong Growth 0.55 Hackers’ Computer Store Expand Weak Growth 0.45 Expand Wait and See Strong Growth Do nothing 0.55 Weak Growth 0.45

  25. Expected Values • Move: • 0.55* 765 + 0.45*365 = $585,000 • Wait and See: • 0.55*850 + 0.45*525 = $703,750 • Expand: • 0.55 * 863 + 0.45 * 413 = $660,500 • Highest expected value is to Wait and see, and either way, do nothing!

  26. 765 365 863 413 850 843 525 Decision Trees $585,000 Strong Growth Move 0.55 Weak Growth 0.45 660,500 Strong Growth 0.55 Hackers’ Computer Store Expand Weak Growth 0.45 Expand 703,750 Wait and See Strong Growth Do nothing 0.55 Weak Growth 0.45

  27. Time Value of Money? • 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

  28. 428,487 166,544 535,116 240,429 556,630 529,874 343,801 Decision Tree-NPV $310,613 Strong Growth Move 0.55 Weak Growth 0.45 402,507 Strong Growth 0.55 Hackers’ Computer Store Expand Weak Growth 0.45 Expand 460,857 Wait and See Strong Growth Do nothing 0.55 Weak Growth 0.45

  29. 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

  30. 843 820 525 820 525 863 365 765 413 Decision Trees 0.25 Strong $465,000 Move 0.75 Weak Hackers’ Computer Store 0.25 Strong 533,000 Expand Weak 0.75 Expand 604,500 0.25 Strong Wait and See Do nothing Weak 0.75 598,750 0.25 Strong Do Nothing Weak 0.75

  31. Real Options • If we didn’t have the wait and see option, we would Do Nothing. • Option to wait and see is worth $5,750 604,500 Wait and See $5,750 598,750 Do Nothing 533,000 Expand 465,000 Move

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