Capacity Planning OM
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Transcript of Capacity Planning OM
Capacity PlanningCapacity Planning
Atanu ChaudhuriAtanu Chaudhuri
Agenda• Criticality of capacity decisionsCriticality of capacity decisions• Capacity decisions over different time horizonsCapacity decisions over different time horizons• Factors influencing capacity decisions• Different approaches to capacity expansion • Concept of break-even volumes• Decision Trees and Capacity Decisions• Estimating required and available capacity• A capacity planning problem• Why companies fail to meet demand despite having
capacity?
Capacity decisions are tricky! --- One of the toughest decisions which business leaders have to take Holcim-owned cement major ACC expects the cement industry to add 70 million tonnes (mt) of fresh capacity this year, putting pressure on prices.With the new additions, the cumulative installed cement production capacity of the country may cross the 300 million tonne-mark.“In 2010, we expect an additional capacity of about 70 mt to materialise, more than half of which is coming up in south-west India. Despite a growing demand for cement, these capacity additions may create surpluses in some parts of the country,” said Mr N.S. Sekhsaria, Chairman, ACC
What started out as stock outs on the iPod touch at Amazon.com started spreading to other retailers and iPod models. Amazon.com, one of Apple's highest volume iPod resellers, has just recently pushed lead times on the 8 GB second-generation iPod touch to three to five weeks from 11 days while the 16 GB model remains at three to five weeks.
iPod touch, iPod nano, and even iPod shuffle are seeing shortages on different colors and capacities this week across several retailers including Best Buy, Target, Wal-Mart, and Crutchfield.com.
"Frankly, we find these sell-outs on iPods surprising given how difficult the macroeconomic environment is, putting a crimp on consumer spending," he told clients in a new report Wednesday. "
Source: http://www.thehindubusinessline.com/2010/03/27/stories/2010032752410200.htm
http://www.appleinsider.com/articles/08/12/03/apples_unexpected_ipod_shortage_spreading.html
Capacity decisions have long term implications…. An illustration from global chemical industry
Annual ethylene capacity additions by region (as a % of 2008 total capacity)
Significant capacity investments in East……Changing roles
China and Middle East contribute to 78% of new
capacity during 2009-2013
Source: CMAI, Deutsche Bank and DTT Chemical Group analysis.
National governments are increasingly playing a role in capacity buildup
Expected behaviors
China Net importer - due to significant demand. However some balance between local production and imports will be set.
India Net importer and merchant buyer - driven by free market needs. Has potential to influence based on demand.
Middle East Net exporter - with access to advantaged feedstock. Significant government play in the market.
Developed markets
Marginal production - driven by significant excess and older capacity.
4
Declining capacity investments in chemical industry in the developed world
1 34
Developing Developed
BASF (1)
BASF (7)
Huntsman (4)
LyondellBassell (15)
Dow (8)
Significant asset reductions… …Lower capacityAn evaluation of 35 major announced capacity
closures by leading playersCapacity reduction in developed markets 2008-2012
Ethylene and Derivatives1
Kt p
er a
nnum
Source: Company Websites, Press releases and news, CMAI, Deutsche Bank, and DTT Chemical Group analysis.(1) Ethylene derivatives include HDPE, LDPE, LLDPE, PVC and Ethylene Glycol.
5
Indian Auto Component Sector- Some firms are building capacities ahead, some are pegging investment growth to sales growth and some are cutting down investments
Mfg Sales, Capital Employed and Asset Turnover-Bharat Forge
0200400600800
100012001400160018002000
2002 2003 2004 2005 2006
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Mfg SalesCapital EmployedAsset Turnover
Mfg Sales, Capital Employed and Asset turnover-Yuken India
0
10
20
30
40
50
60
70
80
90
2002 2003 2004 2005 2006
0
1
2
3
4
5
6
7
Mfg Sales
Capital Employed
Asset Turnover
Mfg sales, capital employed and asset turnover-Talbros Automotive Component
0
20
40
60
80
100
120
140
160
2002 2003 2004 2005 2006
0
1
2
3
4
5
6
7
Mfg Sales
Capital Employed
Asset Turnover
Mfg sales, capital employed and asset turnover-Munjal Auto
0
50
100
150
200
250
300
350
2002 2003 2004 2005 2006
0
1
2
3
4
5
6
7
8
Mfg Sales
Capital Employed
Asset Turover
Firms in Electronics and Chemicals industries in India also show different patterns in
capital investments
Mfg Sales, Capital Employed and Asset Turnover-Jubilant Organosys
0
200
400
600
800
1000
1200
1400
1600
2003 2004 2005 2006
1.700
1.750
1.800
1.850
1.900
1.950
2.000
Mfg Sales
Capital Employed
Asset Turnover
Mfg sales, capital employed and asset turnover-TVS Electronics
0
50
100
150
200
250
2002 2003 2004 2005 2006
0
2
4
6
8
10
12
SalesManf
CapEmp
Asset Turnover
Mfg sales, capital employed and asset turnover-Kavveri Telecom
0
5
10
15
20
25
30
2002 2003 2004 2005
0
1
2
3
4
5
6
7
8
SalesManf
CapEmp
Asset Turnover
Mfg Sales, Capital Employed and Asset Turnover-Zicom Electronic Security
Systems
0102030405060708090
100
2002 2003 2004 2005 2006
0.0000.2000.4000.6000.8001.0001.2001.4001.6001.8002.000
SalesManf
CapEmp
Asset Turnover
How do firms ta
ke these
capaci
ty
decisio
ns? W
e will
learn th
e basi
cs in
today’s
class
Bajaj Auto has a waiting list of three weeks for their top- selling product Pulsar, pushing demand for these bikes up to 80,000 units per month from 55,000 units. Honda Motorcycle & Scooter India (HMSI) has a waiting period of four weeks for their scooters Activa and Deo. Two-wheeler majors clearly did not expect this surge in demand. “Since January, demand has surged by 20%.
Long waiting times for products usually indicate Long waiting times for products usually indicate long term capacity planning or aggregate planning long term capacity planning or aggregate planning problems problems
Source: http://economictimes.indiatimes.com/news/news-by-industry/auto/two-wheelers/Rising-consumer-optimism-to-drive-bike-demand/articleshow/5895736.cms
With competition hotting up, this might result in lost sales
Significance of capacity decisionsSignificance of capacity decisions
The throughput (quantity to be sold), or The throughput (quantity to be sold), or the number of units a facility can hold, the number of units a facility can hold, receive, store, or produce in a period of receive, store, or produce in a period of timetime
Determines Determines fixed costsfixed costs
Determines whetherDetermines whetherdemand will demand will be satisfied or notbe satisfied or not
Planning over three time horizonsPlanning over three time horizons
Capacity decisions over different time horizons
• Long term decisions include: – When, how much, and in what form to alter capacity
• Medium term decisions include:– How much inventory to hold– Level of manpower required– Whether to sub-contract or not?– To buy new equipment or not
• Short term decisions include: – Scheduling specific jobs, orders, allocating resources
(manpower, equipment)
Considerations for capacity decisionsConsiderations for capacity decisions
Forecast demand with reasonable accuracy Understand the technology and capacity
increments Find the optimum operating level
(volume)
Capacity decisions are influenced by Capacity decisions are influenced by economies and diseconomies of scaleeconomies and diseconomies of scale
Economies of Economies of scalescale
Diseconomies of Diseconomies of scalescale
25 - room roadside 25 - room roadside motelmotel 50 - room 50 - room
roadside motelroadside motel
75 - room 75 - room roadside motelroadside motel
Number of RoomsNumber of Rooms2525 5050 7575
Ave
rage
uni
t cos
tA
vera
ge u
nit c
ost
(Rup
ees
per
room
per
nig
ht)
(Rup
ees
per
room
per
nig
ht)
Companies also need to understand learning effects while planning capacity
Cumulative Units Produced0 100 200 300 400 500
Pro
cess
ing
tim
e p
er
un
it in
hou
rs
0
0.3
0.25
0.20
Standard time
Capacity should be calculated considering the standard time
Companies can use flexible facilities to Companies can use flexible facilities to address demand variability across productsaddress demand variability across products
100% 100% –
80% 80% –
60% 60% –
40% 40% –
20% 20% –
0 0 –
Nis
san
Chr
ysle
r
Hon
da
GM Toy
ota
Ford
Percent of North American Vehicles Made Percent of North American Vehicles Made on Flexible Assembly Lineson Flexible Assembly Lines
How can companies manage demand?How can companies manage demand? Demand exceeds capacityDemand exceeds capacity
Curtail demand by raising prices, scheduling longer Curtail demand by raising prices, scheduling longer lead timelead time
Catering to only specific segmentCatering to only specific segment
Long term solution is to increase capacityLong term solution is to increase capacity
Capacity exceeds demandCapacity exceeds demand Stimulate market through product launches, advertising Stimulate market through product launches, advertising
etcetc
Product changes and upgradesProduct changes and upgrades
Adjusting to seasonal demandsAdjusting to seasonal demands Produce products with complementary demand Produce products with complementary demand
patterns, if possiblepatterns, if possible
How can companies match capacity with How can companies match capacity with demand?demand?1.1. Making staffing changesMaking staffing changes
2.2. Adjusting equipmentAdjusting equipment Purchasing additional machineryPurchasing additional machinery
Selling or leasing out existing equipmentSelling or leasing out existing equipment
3.3. Closing facilitiesClosing facilities
4.4. Improving processes to increase throughputImproving processes to increase throughput
5.5. Redesigning products to facilitate more throughputRedesigning products to facilitate more throughput
6.6. Adding process flexibility to meet changing product Adding process flexibility to meet changing product preferencespreferences
May not always be necessary, instead balance flow of product/services through the facility
Different approaches to capacity Different approaches to capacity expansionexpansion
(a)(a) Leading demand with Leading demand with incremental expansionincremental expansion
Dem
and
Dem
and
Expected Expected demanddemand
New New capacitycapacity
(b)(b) Leading demand with Leading demand with one-step expansionone-step expansion
Dem
and
Dem
and
New New capacitycapacity
Expected Expected demanddemand
(c)(c) Capacity lags demand with Capacity lags demand with incremental expansionincremental expansion
Dem
and
Dem
and
New New capacitycapacity
Expected Expected demanddemand
Where will this capacity expansion Where will this capacity expansion approach be suitable?approach be suitable?
(a)(a) Leading demand with incremental Leading demand with incremental expansionexpansion
Expected Expected demanddemand
New New capacitycapacity
Dem
and
Dem
and
Time (years)Time (years)11 22 33
Where will this capacity expansion Where will this capacity expansion approach be suitable?approach be suitable?
(b)(b) Leading demand with one-step expansionLeading demand with one-step expansion
New New capacitycapacity
Expected Expected demanddemand
Dem
and
Dem
and
Time (years)Time (years)11 22 33
Where will this capacity expansion Where will this capacity expansion approach be suitable?approach be suitable?
(c)(c) Capacity lags demand with incremental Capacity lags demand with incremental expansionexpansion
Expected Expected demanddemand
Dem
and
Dem
and
Time (years)Time (years)11 22 33
New New capacitycapacity
Companies should also account for lifecycle stages while evaluating capacity alternatives
Should be careful in making large, irreversible investments, need more flexibility
Systematically build capacity without overshooting by large extent
Focus on efficient utilization of existing capacity
Need of flexibility of equipment and manpower increases
Break even volumes many times become the focal point of a business plan
• When we were planning facilities for the car and working out a business plan, the business plan shown to me was looking at a figure of 200,000. I said 200,000 cars is crazy. If we can do this we should be looking at a million cars a year, and if we can't do a million then we shouldn't be doing this kind of car at all. But such a figure (a million cars) has never been achieved in the country before.
• If it had to be done the conventional way, it would have meant investing many billions of dollars. So we looked at a new kind of distributed manufacturing, creating a low-cost, low break-even point manufacturing ….
Ratan Tata on Nano
Source: http://tatanano.inservices.tatamotors.com/tatamotors/index.php?option=com_content&task=view&id=96&Itemid=169
Break-Even AnalysisBreak-Even Analysis
Technique for evaluating process and Technique for evaluating process and equipment alternativesequipment alternatives
Objective is to find the point in rupees and Objective is to find the point in rupees and units at which cost equals revenueunits at which cost equals revenue
Requires estimation of fixed costs, variable Requires estimation of fixed costs, variable costs, and revenuecosts, and revenue
Break-Even AnalysisBreak-Even Analysis
Fixed costs are costs that continue even if Fixed costs are costs that continue even if no units are producedno units are produced Depreciation, taxes, debt, mortgage paymentsDepreciation, taxes, debt, mortgage payments
Variable costs are costs that vary with the Variable costs are costs that vary with the volume of units producedvolume of units produced Labor, materials, portion of utilitiesLabor, materials, portion of utilities
Contribution is the difference between selling Contribution is the difference between selling price and variable costprice and variable cost
Break-Even AnalysisBreak-Even Analysis
Costs and revenue are linear functionsCosts and revenue are linear functions
We actually know these costsWe actually know these costs
Time value of money not consideredTime value of money not considered
AssumptionsAssumptions
Profit corrid
or
Loss
corri
dor
Break-Even AnalysisBreak-Even AnalysisTotal revenue lineTotal revenue line
Total cost lineTotal cost line
Variable costVariable cost
Fixed costFixed cost
Break-even pointBreak-even pointTotal cost = Total revenueTotal cost = Total revenue
–
900 900 –
800 800 –
700 700 –
600 600 –
500 500 –
400 400 –
300 300 –
200 200 –
100 100 –
–| | | | | | | | | | | |
00 100100 200200 300300 400400 500500 600600 700700 800800 900900 10001000 11001100
Cos
t in
rupe
esC
ost i
n ru
pees
Volume (units per period)Volume (units per period)
Break-Even AnalysisBreak-Even Analysis
BEPBEPxx == break-even break-even point in unitspoint in unitsBEPBEP == break-even break-even point in rupeespoint in rupeesPP == price per unit price per unit (after all discounts)(after all discounts)
xx == number of units number of units producedproducedTRTR== total revenue = Pxtotal revenue = PxFF == fixed costsfixed costsVV == variable cost per unitvariable cost per unitTCTC== total costs = F + Vxtotal costs = F + Vx
TR = TCTR = TCoror
Px = F + VxPx = F + Vx
Break-even point Break-even point occurs whenoccurs when
BEPBEPxx = =FF
P - VP - V
Break-Even AnalysisBreak-Even Analysis
BEPBEPxx == break-even break-even point in unitspoint in unitsBEPBEP == break-even break-even point in rupeespoint in rupeesPP == price per unit price per unit (after all discounts)(after all discounts)
xx == number of units number of units producedproducedTRTR== total revenue = Pxtotal revenue = PxFF == fixed costsfixed costsVV == variable cost per unitvariable cost per unitTCTC== total costs = F + Vxtotal costs = F + Vx
BEPBEP = BEP= BEPx x PP
= P= P
==
= =
FF(P - V)/P(P - V)/P
FFP - VP - V
FF1 - V/P1 - V/P
ProfitProfit = TR - TC= TR - TC
= Px - (F + Vx)= Px - (F + Vx)
= Px - F - Vx= Px - F - Vx
= (P - V)x - F= (P - V)x - F
Break-Even ExampleBreak-Even Example
Fixed costs = Rs. 10,000Fixed costs = Rs. 10,000 Material = Rs.75/unit Material = Rs.75/unitDirect labor = Rs.1.50/unitDirect labor = Rs.1.50/unit Selling price = Rs.4.00 per unit Selling price = Rs.4.00 per unit
BEP = =BEP = =FF
1 - (V/P)1 - (V/P)Rs.10,000Rs.10,000
1 - [(1.50 + .75)/(4.00)]1 - [(1.50 + .75)/(4.00)]
Break-Even ExampleBreak-Even Example
Fixed costs = Rs.10,000Fixed costs = Rs.10,000 Material = Rs.75/unit Material = Rs.75/unitDirect labor = Rs1.50/unitDirect labor = Rs1.50/unit Selling price = Rs. 4.00 per unit Selling price = Rs. 4.00 per unit
BEP = =BEP = =FF
1 - (V/P)1 - (V/P)$10,000$10,000
1 - [(1.50 + .75)/(4.00)]1 - [(1.50 + .75)/(4.00)]
= = $22,857.14= = $22,857.14$10,000$10,000
.4375.4375
BEPBEPxx = = = 5,714 = = = 5,714FF
P - VP - V$10,000$10,000
4.00 - (1.50 + .75)4.00 - (1.50 + .75)
Break-Even ExampleBreak-Even Example
50,000 50,000 –
40,000 40,000 –
30,000 30,000 –
20,000 20,000 –
10,000 10,000 –
–| | | | | |
00 2,0002,000 4,0004,000 6,0006,000 8,0008,000 10,00010,000
Dol
lars
Dol
lars
UnitsUnits
Fixed costsFixed costs
Total Total costscosts
RevenueRevenue
Break-even Break-even pointpoint
Break-Even ExampleBreak-Even Example
BEP =BEP =FF
∑∑ 1 - x (W1 - x (Wii))VVii
PPii
Multiproduct CaseMultiproduct Case
wherewhere VV = variable cost per unit= variable cost per unitPP = price per unit= price per unitFF = fixed costs= fixed costs
WW = percent each product is of total dollar sales= percent each product is of total dollar salesii = each product= each product
Restaurant with multiple productsRestaurant with multiple products
Annual ForecastedAnnual ForecastedItemItem PricePrice CostCost Sales UnitsSales Units
SandwichSandwich $. 2.95$. 2.95 $.1.25$.1.25 7,0007,000Soft drinkSoft drink .80.80 .30.30 7,0007,000Baked potatoBaked potato 1.551.55 .47.47 5,0005,000TeaTea .75.75 .25.25 5,0005,000Salad barSalad bar 2.852.85 1.001.00 3,0003,000
Fixed costs = $. 3,500 per monthFixed costs = $. 3,500 per month
Restaurant with multiple productsRestaurant with multiple products
Annual ForecastedAnnual ForecastedItemItem PricePrice CostCost Sales UnitsSales Units
SandwichSandwich $. 2.95$. 2.95 $. 1.25$. 1.25 7,0007,000Soft drinkSoft drink .80.80 .30.30 7,0007,000Baked potatoBaked potato 1.551.55 .47.47 5,0005,000TeaTea .75.75 .25.25 5,0005,000Salad barSalad bar 2.852.85 1.001.00 3,0003,000
Sandwich $. 2.95 $. 1.25 .42 .58 $. 20,650 .446 .259Soft drink .80 .30 .38 .62 5,600 .121 .075Baked 1.55 .47 .30 .70 7,750 .167 .117 potatoTea .75 .25 .33 .67 3,750 .081 .054Salad bar 2.85 1.00 .35 .65 8,550 .185 .120
$. 46,300 1.000 .625
Annual WeightedSelling Variable Forecasted % of Contribution
Item (i) Price (P) Cost (V) (V/P) 1 - (V/P) Sales $ Sales (col 5 x col 7)
Fixed costs = $. 3,500 per monthFixed costs = $. 3,500 per month
Restaurant with multiple productsRestaurant with multiple products
Annual ForecastedAnnual ForecastedItemItem PricePrice CostCost Sales UnitsSales Units
SandwichSandwich $2.95$2.95 $1.25$1.25 7,0007,000Soft drinkSoft drink .80.80 .30.30 7,0007,000Baked potatoBaked potato 1.551.55 .47.47 5,0005,000TeaTea .75.75 .25.25 5,0005,000Salad barSalad bar 2.852.85 1.001.00 3,0003,000
Fixed costs = $3,500 per monthFixed costs = $3,500 per month
BEP$ =F
∑ 1 - x (Wi)Vi
Pi
= = $67,200$3,500 x 12
.625
Daily sales = = $215.38
$67,200312 days
.446 x $215.38$2.95 = 32.6 33
sandwichesper day
Decision Trees and Decision Trees and Capacity DecisionCapacity Decision
-$90,000-$90,000Market unfavorable (.6)Market unfavorable (.6)
Market favorable (.4)Market favorable (.4)$100,000$100,000
Large plant
Large plant
Market favorable (.4)Market favorable (.4)
Market unfavorable (.6)Market unfavorable (.6)
$60,000$60,000
-$10,000-$10,000
Medium plantMedium plant
Market favorable (.4)Market favorable (.4)
Market unfavorable (.6)Market unfavorable (.6)
$40,000$40,000
-$5,000-$5,000
Small plant
Small plant
$0$0
Do nothing
Do nothing
Decision Trees and Decision Trees and Capacity DecisionCapacity Decision
-$90,000-$90,000Market unfavorable (.6)Market unfavorable (.6)
Market favorable (.4)Market favorable (.4)$100,000$100,000
Large plant
Large plant
Market favorable (.4)Market favorable (.4)
Market unfavorable (.6)Market unfavorable (.6)
$60,000$60,000
-$10,000-$10,000
Medium plantMedium plant
Market favorable (.4)Market favorable (.4)
Market unfavorable (.6)Market unfavorable (.6)
$40,000$40,000
-$5,000-$5,000
Small plant
Small plant
$0$0
Do nothing
Do nothing
EMV = (.4)($100,000) + (.6)(-$90,000)
Large Plant
EMV = -$14,000
Decision Trees and Decision Trees and Capacity DecisionCapacity Decision
-$14,000
$13,000
$18,000
-$90,000-$90,000Market unfavorable (.6)Market unfavorable (.6)
Market favorable (.4)Market favorable (.4)$100,000$100,000
Large plant
Large plant
Market favorable (.4)Market favorable (.4)
Market unfavorable (.6)Market unfavorable (.6)
$60,000$60,000
-$10,000-$10,000
Medium plantMedium plant
Market favorable (.4)Market favorable (.4)
Market unfavorable (.6)Market unfavorable (.6)
$40,000$40,000
-$5,000-$5,000
Small plant
Small plant
$0$0
Do nothing
Do nothing
Estimating Required Capacity• Projected demand = D
• Standard labour hours required per unit =SL
• Efficiency of labour =EL
• Labor required = D*SL/EL
• Similarly required capacity can be calculated for machine
A contract manufacturer makes products for large food companies It got orders to make 800 bottles of 500 gm tomato ketchup and 1200 bottles of 500 gm jam every day.In a year there are 300 working daysThe ketchup and jam can be bottled using similar machines.It takes 2 minutes to bottle 12 ketchup bottles and 3 minutes to bottle 10 jam bottles. Efficiency of bottling machine is 95% Find out the required number of bottling machine hours per annum for the contract manufacturer
Solution to the problem
• Number of ketchup bottles in a year = 800*300
• Number of jam bottles in a year = 1200*300
• Bottling machine hours for ketchup in a year =
800*300*(2/12)/(0.95*60) = 701.75
• Bottling machine hours for jam in a year =
= 1200*300*(3/10)/(0.95*60) = 1894.74
Total bottling machine hours required per annum= 701.75+1894.74 = 2596.49
Comparing required and available capacity• Currently one bottling machine is available with the manufacturer
which runs 2 shifts of 8 hours each.
• Historical data shows that machine is under breakdown and maintenance 10% of the available hours in a year and other 10 % of the time is spent in setting up the machine while changing from ketchup to jam and vice versa
• What is the available capacity?
• What will be the machine utilization in a year? Can it take further orders from the same or different manufacturer to fill up the bottling machine capacity?
Available capacity = 300*2*8*(1-0.2) = 3840 hoursUtilization = 2596.49/3840 =0.67 or 67%Apparently yes, 33 % of bottling machine capacity is available to take further ordersWill depend on capacity of other processes and bottleneck capacity (nothing to do with bottles!!!)
Ketchup manufacturing process
Pulping Filtering Cooking
FinishingBottlingLabeling and
Packing
3 hours 45 minutes 2.5 hours
2 hours 2 hours 15 minutes 2 hours
Time mentioned are for 400 kg of tomato ketchup i.e. 800 bottles of 500 gm each
For ketchup manufacturing, process with bottleneck capacity is pulping as it takes maximum time to process 400 kg of tomato ketchup
Jam manufacturing process
Crushing and chopping
Pasteurizing Cooking
BottlingLabeling and
Packing
3.0 hours 1.5 hours 4.5 hours
6 hours 3 .5 hours
Time mentioned are for 600 kg of mixed fruit jam i.e. 1200 bottles of 500 gm each
For jam manufacturing, process with bottleneck capacity is bottling as it takes maximum time to process 600 kg of mixed fruit jam
Further calculations• Remember, there is only 1 bottling machine
which is being used for both ketchup and jam manufacturing
• When are the ketchup and jam arriving at the bottling machine?
• Ketchup will arrive at bottling machine 8 hrs 15 minutes after start of process while jam will arrive at bottling machine 9 hours after start of process
Pulping Filtering Cooking
FinishingBottlingLabeling and
Packing
3 hours 45 minutes 2.5 hours
2 hours 2 hours 15 minutes 2 hours
Crushing and chopping
Pasteurizing Cooking
3.0 hours 1.5 hours 4.5 hours
Labeling and Packing
3 .5 hours
You can play this game of maximizing throughput
• How much quantity of jam and ketchup can the manufacturer produce in a day?
• You have to take decisions about scheduling jam and ketchup manufacturing, batch size of jam and ketchup manufacturing
• Objective will be to maximize total profit• This will also depend on profit made from jam and
ketchup• So, will the manufacturer produce more jam or more
ketchup?
Capacity issues in service industry
• Need of responsiveness- customers may not wait for long
• Managing demand volatility- no option of inventory• Manage both peak hour and non-peak hour demand • Trade off between utilization and performance
measures like waiting time
Demand and Capacity Management in the Service Sector
Demand management Appointment, reservations, FCFS rule
Capacity management Full time,
temporary, part-time staff
Capacity planning alternatives for service firms
Issues for consideration Peak Hour/High Demand Period
Non Peak Hour/Lean Period
Operations Strategy Standard offering Customized offerings
Service Portfolio Narrow offering Wide offering
Demand Management Reservations Special tariffs, offers
Resources Management Multi-skilled workforceAdding temporary workforceIncreasing working time
Dedicated tasksTraining and developmentReduced work hours
A bank teller example• Arrival rate of customers at the teller counter = 15 per hour = ra
• Service rate at the teller = 20 per hour =re
• Utilization of the teller facility = 15/20 =0.75 =u• What is the probability that there are atmost 2 persons in front of the
teller counter? • Pn = long run probability of having the system with ‘n’ jobs/customers
in process sequence • For the system to be stable, P n-1*ra = Pn *re
• Thus, Pn = u* P n-1
• P0 = 1-u , P1 = u*P0 = u(1-u)• probability that there are atmost 2 persons in front of the teller counter
= P0+P1+P2 = 0.25 + 0.25*0.75+ 0.75^2*0.25 =0.578
Service growth stages and capacity addition
EntrepreneurialMultisite
rationalizationGrowth Maturity
Limited service at a single location
Based on some novel idea
Or filling the gaps based on customer needs
Multi-skilled personnel
Tries adding additional services to the current location
After exhausting local market, ventures to grow beyond original location
Complexity of managing multiple sites increase
With multi-site operations, operating costs increase
Volume increases significantly
At some point, operational complexity outstrips growth related benefits
Need fresh ideas
Existing facilities need remodeling
Operational efficiency takes precedence
May be necessary to modify the service concept
Capacity planning must address the issue of duplicating changes across the entire business
Wrap-up
• Significance of capacity decisions• Capacity planning over different time horizons• Considerations for capacity planning• Capacity expansion strategies and applicability• Break-even analysis and decision tree• Estimating required and available capacity• Why companies fail to meet demand despite having
capacity• Capacity planning in services