Chapter 13 Part 3 Notes: Constraint, Bottleneck, and Split-Off Decisions

Constraint, Bottleneck, and Volume Trade-offs

  • Concept overview

    • A constraint (bottleneck) is the part of the production process with the lowest capacity, i.e., the bottleneck in the chain. It determines the overall throughput.

    • If sales demand (forecast) exceeds capacity, the company must decide which products to produce and in what mix, given the constraint.

    • A production line can have a bottleneck at the first unit, the second unit, or any step; the area with the smallest capacity constrains the entire process.

    • The chapter links bottlenecks to contribution margin; decisions are made to maximize contribution margin under constraint.

  • Key decision principle under constraint

    • With constrained resources, fixed costs are unaffected; the goal is to maximize the contribution margin (CM).

    • We compare CM per unit vs CM per constrained resource to decide which products to emphasize.

    • The standard payoff measure becomes CM per constrained resource (not just CM per unit).

    • Formula foundations (definitions):

    • Contribution margin per unit: CM<em>u=PVC</em>unitCM<em>u = P - VC</em>{unit} where PP is selling price per unit and VCunitVC_{unit} is variable cost per unit.

    • Contribution margin per constrained resource (per unit of the constrained resource): CM<em>extperextconstrainedextunit=racCM</em>uextresourceperunitCM<em>{ ext{per ext{ constrained ext{-}unit}}} = rac{CM</em>u}{ ext{resource per unit}}

    • If the constrained resource is time (minutes) on a machine: CM<em>extperextminute=racCM</em>uextminutesperunitCM<em>{ ext{per ext{ minute}}} = rac{CM</em>u}{ ext{minutes per unit}}

    • If the constrained resource is material (pounds): CM<em>extperextlb=racCM</em>uextpoundsperunitCM<em>{ ext{per ext{ lb}}} = rac{CM</em>u}{ ext{pounds per unit}}

  • Illustrative curtain example (Curtains company)

    • Products: six-foot curtain, three-foot curtain, and a valance.

    • Given data (per unit):

    • Selling prices, variable costs, material usage, and sewing machine time:

      • Six-foot curtain: CM per unit = CMu=24CM_u = 24; material usage = 6 ft; machine time = 6 minutes.

      • Three-foot curtain: CM per unit = CMu=24CM_u = 24; material usage = 3 ft; machine time = 8 minutes.

      • Valance: CM per unit = CMu=30CM_u = 30; material usage = 4 ft; machine time = 16 minutes.

    • CM per constrained resource calculations:

    • Fabric (material) constraint:

      • Six-foot: CMextfabric=rac246=4$/ftCM_{ ext{fabric}} = rac{24}{6} = 4 \$/ft

      • Three-foot: CMextfabric=rac243=8$/ftCM_{ ext{fabric}} = rac{24}{3} = 8 \$/ft

      • Valance: CMextfabric=rac304=7.5$/ftCM_{ ext{fabric}} = rac{30}{4} = 7.5 \$/ft

      • Conclusion: The three-foot curtain offers the highest CM per fabric foot ($8/ft$).

    • Machine time constraint (per minute):

      • Six-foot: CMexttime=rac246=4$/extminCM_{ ext{time}} = rac{24}{6} = 4 \$/ ext{min}

      • Three-foot: CMexttime=rac248=3$/extminCM_{ ext{time}} = rac{24}{8} = 3 \$/ ext{min}

      • Valance: CMexttime=rac30161.88$/extminCM_{ ext{time}} = rac{30}{16} \approx 1.88 \$/ ext{min}

      • Conclusion: The six-foot curtain yields the highest CM per machine minute ($4/ min$).

    • Which product has the largest CM per unit? Valance ($30$) has the largest CM per unit, but it is not the best when you account for constrained resources (fabric or machine time).

    • Which product yields the most profitable use of fabric? Three-foot curtain ($8 per foot).

    • Which product yields the most profitable use of machine time? Six-foot curtain ($4 per minute).

    • Practical takeaway: Under a constraint, the best mix depends on which resource is tight and which profitability metric you optimize (per unit, per fabric foot, per minute, etc.). You often must produce a mix that satisfies demand while prioritizing the constrained-resource efficiency.

  • Alternative constraint example: constrained material (8,000 pounds available)

    • Data (per unit): selling price, direct materials, other variable costs, and material usage; material cost is 10/lb10/ lb.

    • Product components: X uses 4 lb per unit, Y uses 10 lb per unit, Z uses 5 lb per unit.

    • CM per unit (assume given): cmuX, cmuY, cmuZ (values provided in the scenario).

    • Compute CM per constrained resource (per pound):

    • CM<em>extperlb(X)=racCM</em>uX4CM<em>{ ext{per lb}}(X) = rac{CM</em>u_X}{4}

    • CM<em>extperlb(Y)=racCM</em>uY10CM<em>{ ext{per lb}}(Y) = rac{CM</em>u_Y}{10}

    • CM<em>extperlb(Z)=racCM</em>uZ5CM<em>{ ext{per lb}}(Z) = rac{CM</em>u_Z}{5}

    • Result: product Z is highest on a CM per pound basis, then X, then Y.

    • Decision rule with unlimited demand: produce in order of descending CMextperlbCM_{ ext{per lb}} until the 8,000 lb constraint is met.

    • If demand is limited (e.g., 500 units of each product), calculate total material used and allocate remaining constrained resource to the next best option:

    • Material required for 500 units: X = 500×4 = 2,000 lb; Y = 500×10 = 5,000 lb; Z = 500×5 = 2,500 lb; total = 9,500 lb (> 8,000 lb constraint).

    • Prioritize products by CMextperlbCM_{ ext{per lb}}: first satisfy Z (2,500 lb), then X (2,000 lb), remaining material = 8,000 − 2,500 − 2,000 = 3,500 lb.

    • For Y (10 lb per unit), you can make rac3,50010=350rac{3,500}{10} = 350 units.

    • Resulting mix under constraint: Z = 500 units, X = 500 units, Y = 350 units.

    • Total contribution margin under this constrained mix (assuming CM per unit values given):

    • CM = 500×CMuZ + 500×CMuX + 350×CMuY (subject to the constraint).

    • Key takeaway: You maximize CM by allocating the limited material to the product(s) with the highest CM per constrained unit first.

  • Managing constraints: strategic options to relieve or work around bottlenecks

    • If the constraint is a supplier/material shortage:

    • Source from a second vendor or alternate suppliers.

    • If the constraint is capacity (machine time, shifts):

    • Implement overtime (e.g., add a second/third shift).

    • Subcontract some production to external partners.

    • Acquire an additional machine or upgrade equipment.

    • Reallocate labor from non-bottleneck processes to the bottleneck;

    • Implement process improvements (e.g., Six Sigma) to remove redundancies and reduce defects.

    • If the constraint is labor or skill in a particular operation, consider process changes or cross-training to relieve the bottleneck.

  • Example: constrained labor time and outsourcing decision (ornate vs. modern table)

    • Problem setup: carving time is the constraint; selling price and variable costs yield a CM per unit; two products (ornate and modern) with different carving times.

    • Option to outsource: a nearby shop offers carving at $130 per hour.

    • Calculations per unit (carving time and CM per unit):

    • Ornate table: CM per unit = $100$ per hour of carving time.

    • Modern table: CM per unit = $200$ per hour of carving time.

    • Outsourcing cost: $130$ per hour.

    • Net CM from outsourcing per hour for each product:

    • Ornate: $100$ (in-house) vs $130$ (outsourced) → outsourcing reduces CM to $70$ per hour of carving time (if considered comparatively).

    • Modern: in-house CM $200$ per hour vs outsourcing $130$ per hour → outsourcing leaves $70$ per hour still available as net CM (i.e., you can outsource and still retain $70$ CM per hour).

    • Decision: Outsource the option where the outsource scenario still yields positive net CM per hour; in this example, outsourcing is advantageous for the modern table since it yields $70$ CM per hour relative to the bottleneck.

  • Joint product costs and split-off point (sell vs process further)

    • Split-off point: the point in a shared process where products can be separated into distinct final products.

    • Up to split-off, costs are joint and shared; after split-off, costs are incremental to each product. The cost incurred up to split-off is generally sunk for the decision at hand.

    • Byproducts and shared processing examples:

    • Lumber mill example: produce two by-products (e.g., two by fours of different lengths and sawdust).

    • After split-off, you may sell a byproduct as-is or process further to increase revenue (e.g., sawdust → fireplace logs).

    • The decision rule is to compare incremental revenue after processing further to incremental processing costs:

      • Incremental revenue after processing: extRev<em>extafterextRev</em>extsplitoffext{Rev}<em>{ ext{after}} - ext{Rev}</em>{ ext{split-off}}

      • Incremental cost after processing: CextafterC_{ ext{after}}

      • Net incremental benefit: NB=(extRev<em>extafterextRev</em>extsplitoff)CextafterNB = ( ext{Rev}<em>{ ext{after}} - ext{Rev}</em>{ ext{split-off}}) - C_{ ext{after}}

      • If NB>0NB > 0, process further; otherwise sell at split-off value.

    • For typical joint-cost problems, the split-off costs are irrelevant to the decision about processing further, because those costs are sunk up to the split-off point.

    • Common pitfalls: costs allocated to products at the split-off point are often based on sales volume shares, which may misstate the true incremental profitability of processing decisions.

  • Practical split-off example (meat processing style)

    • Setup: a joint process yields meat products that reach a split-off point; after split-off, additional processing costs are incurred to create final products (e.g., ham, bacon, pork chops).

    • Pre-split-off costs (joint): $J = 40{,}000$ (example).

    • Post-split-off additional processing costs (per product): bacon $C{b} = 20{,}000$, ham $C{h} = 30{,}000$, pork chops $C_{p} = 12{,}000$ (illustrative).

    • Final sales values after further processing (per product): ham, bacon, pork chops have different final sale revenues depending on further processing.

    • Sell-at-split-off alternative: you could sell each product at the split-off value (before processing) for a certain revenue.

    • Decision framework (incremental view): for each product i, compute per-unit or per-batch incremental revenue from processing versus selling at split-off, and subtract the incremental processing cost:

    • Incremental revenue per unit from processing: Ri=(extFinalsalepriceafterprocessing)(extsalepriceatsplitoff)R_i = ( ext{Final sale price after processing}) - ( ext{sale price at split-off})

    • Incremental cost per unit from processing: CiC_i

    • Net incremental benefit per unit: NB<em>i=R</em>iC<em>i=(F</em>iS<em>i)C</em>iNB<em>i = R</em>i - C<em>i = (F</em>i - S<em>i) - C</em>i where F<em>iF<em>i is the final sale price after processing and S</em>iS</em>i is the split-off sale price.

    • If NB<em>i>0NB<em>i > 0, processing further adds value; if NB</em>i<br>=0NB</em>i <br>= 0 or negative, sell at split-off value.

    • The example in the transcript walks through specific numbers to compare options and ultimately uses the incremental profit criterion.

    • Core takeaway: The joint costs up to split-off are sunk for the decision; only incremental revenues and incremental costs after split-off matter.

  • Summary of key takeaways

    • A constraint/bottleneck defines the maximum output; optimize product mix around the constrained resource.

    • When constrained, evaluate CM per constrained unit (per lb, per foot, per minute, etc.) to prioritize products.

    • If demand is unlimited, allocate the constrained resource to maximize CM per constrained unit until capacity is reached.

    • If demand is limited, allocate the constrained resource to meet the most valuable mix given both CM per constrained unit and stated demand, adjusting as necessary.

    • Short-term actions to relieve bottlenecks include outsourcing, overtime, additional machines, and shifting labor; long-term actions include supplier diversification and process improvements.

    • Split-off (joint) costs require the analyst to focus on incremental revenue versus incremental costs after the split-off point; joint costs are sunk and do not drive the decision to process further.

  • Quick reference formulas

    • CM<em>u=PVC</em>extunitCM<em>u = P - VC</em>{ ext{unit}}

    • CM<em>extperextconstrainedunit=racCM</em>uextresourceperunitCM<em>{ ext{per ext{ constrained unit}}} = rac{CM</em>u}{ ext{resource per unit}}

    • If the constrained resource is time (minutes): CM<em>extperextminute=racCM</em>uextminutesperunitCM<em>{ ext{per ext{ minute}}} = rac{CM</em>u}{ ext{minutes per unit}}

    • If the constrained resource is material (pounds): CM<em>extperextlb=racCM</em>uextpoundsperunitCM<em>{ ext{per ext{ lb}}} = rac{CM</em>u}{ ext{pounds per unit}}

    • Allocation rule under material constraint: sort by descending CMextperlbCM_{ ext{per lb}} and allocate resource until the constraint is met.

    • Split-off decision (per unit): NB<em>i=(F</em>iS<em>i)C</em>iNB<em>i = (F</em>i - S<em>i) - C</em>i where

    • FiF_i = final sale price after processing,

    • SiS_i = split-off sale price,

    • CiC_i = incremental processing cost.

    • Process further if NBi>0NB_i > 0; otherwise sell at split-off.