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/hr10/hr 40/hr

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

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

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

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

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

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.

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”

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

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

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

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

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.

Draw the decision tree

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

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

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.

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

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

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

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

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”

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

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!

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

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

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

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

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

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 Move Expand Wait and See 465, , ,500 Do Nothing 598,750 $5,750