Sales and capacity planning ppt @ doms
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Transcript of Sales and capacity planning ppt @ doms
Sales and Capacity Planning
Lecture Outline
• The Sales and Operations Planning Process• Strategies for Adjusting Capacity• Strategies for Managing Demand• Quantitative Techniques for Aggregate Planning• Hierarchical Nature of Planning• Aggregate Planning for Services
14-2
Sales and Operations Planning
• Determines resource capacity to meet demand over an intermediate time horizon• Aggregate refers to sales and operations planning for
product lines or families• Sales and Operations planning (S&OP) matches
supply and demand• Objectives
• Establish a company wide plan for allocating resources
• Develop an economic strategy for meeting demand
14-3
Sales and Operations Planning Process
14-4
Monthly S&OP Planning Process
14-5
Meeting Demand Strategies
• Adjusting capacity• Resources to meet demand are acquired and maintained over
the time horizon of the plan
• Minor variations in demand are handled with overtime or under-time
• Managing demand• Proactive demand management
14-6
Strategies for Adjusting Capacity
• Level production• Producing at a constant rate and using inventory to
absorb fluctuations in demand• Chase demand
• Hiring and firing workers to match demand• Peak demand
• Maintaining resources for high-demand levels
14-7
Strategies for Adjusting Capacity
• Overtime and under-time• Increase or decrease working hours
• Subcontracting• Let outside companies complete the work
• Part-time workers• Hire part-time workers to complete the work
• Backordering• Provide the service or product at a later time
period
14-8
Level Production
14-9
DemandU
nits
Time
Production
Chase Demand
14-10
DemandU
nits
Time
Production
Strategies for Managing Demand
Shifting demand into other time periods Incentives Sales promotions Advertising campaigns
Offering products or services with counter-cyclical demand patterns
Partnering with suppliers to reduce information distortion along the supply chain
14-11
Quantitative Techniques For AP
• Pure Strategies• Mixed Strategies• Linear Programming• Transportation Method• Other Quantitative Techniques
14-12
Pure Strategies
14-13
Hiring cost = $100 per worker
Firing cost = $500 per worker
Inventory carrying cost = $0.50 pound per quarter
Regular production cost per pound = $2.00
Production per employee = 1,000 pounds per quarter
Beginning work force = 100 workers
QUARTER SALES FORECAST (LB)
Spring 80,000Summer 50,000Fall 120,000Winter 150,000
Level Production Strategy
14-14
Level production
= 100,000 pounds(50,000 + 120,000 + 150,000 + 80,000)
4
Spring 80,000 100,000 20,000Summer 50,000 100,000 70,000Fall 120,000 100,000 50,000Winter 150,000 100,000 0
400,000 140,000Cost of Level Production Strategy
(400,000 X $2.00) + (140,00 X $.50) = $870,000
SALES PRODUCTIONQUARTER FORECAST PLAN INVENTORY
Chase Demand Strategy
14-15
Spring 80,000 80,000 80 0 20Summer 50,000 50,000 50 0 30Fall 120,000 120,000 120 70 0Winter 150,000 150,000 150 30 0
100 50
SALES PRODUCTION WORKERS WORKERS WORKERSQUARTER FORECAST PLAN NEEDED HIRED FIRED
Cost of Chase Demand Strategy
(400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000
Level Production with Excel
14-16
Inventory atend of summer
Input by user=400,000/4
Cost of level production= inventory costs + production costs
Chase Demand with Excel
14-17
Workforce requirementscalculated by system
No. of workershired in fall
Production input by user;production =demand
Cost of chasedemand = hiring +firing + production
Mixed Strategy
• Combination of Level Production and Chase Demand strategies
• Example policies• no more than x% of workforce can be laid off in one quarter• inventory levels cannot exceed x dollars
• Some industries may shut down manufacturing during the low demand season and schedule employee vacations during that time
14-18
General Linear Programming (LP) Model
• LP gives an optimal solution, but demand and costs must be linear
• Let• Wt = workforce size for period t• Pt =units produced in period t• It =units in inventory at the end of period t• Ft =number of workers fired for period t• Ht = number of workers hired for period t
14-19
LP MODEL
14-20
Minimize Z = $100 (H1 + H2 + H3 + H4)
+ $500 (F1 + F2 + F3 + F4)
+ $0.50 (I1 + I2 + I3 + I4)
+ $2 (P1 + P2 + P3 + P4)
Subject to
P1 - I1= 80,000 (1)
Demand I1 + P2 - I2= 50,000 (2)
constraints I2 + P3 - I3= 120,000 (3)
I3 + P4 - I4= 150,000 (4)
Production 1000 W1= P1 (5)
constraints 1000 W2= P2 (6)
1000 W3= P3 (7)
1000 W4= P4 (8)
100 + H1 - F1= W1 (9)
Work force W1 + H2 - F2= W2 (10)
constraints W2 + H3 - F3= W3 (11)
W3 + H4 - F4= W4 (12)
Setting up the Spreadsheet
14-21
Target cell;cost of solutiongoes here
Solver will put thesolution here
When model is complete, Solve
Click here nextDemand Constraint
Workforce Constraint
Production Constraint
Cells where solution appears
Setting up the Spreadsheet
14-22
Click these boxes
The LP Solution
14-23
Optimal production plan
Cost of optimal solution
Solution is a mixof inventory, hiringand firing
Extra report options
Level Production for Quantum
14-24
Level = 12,000/12 = 1,000
Input by user
Excel calculates
these
Cost of level production
Chase Demand for Quantum
14-25
Input by user
Excel calculates
these
Cost of chase demandNo. workershired in Feb.
LP Solution for Quantum
14-26
Solver foundthis solution
Constraintequationsin these
cells
Optimal solution
Transportation Method
14-27
1 900 1000 100 5002 1500 1200 150 5003 1600 1300 200 5004 3000 1300 200 500
Regular production cost $20/unitOvertime production cost $25/unitSubcontracting cost $28/unitInventory holding cost $3/unit-periodBeginning inventory 300 units
EXPECTED REGULAR OVERTIME SUBCONTRACTQUARTER DEMAND CAPACITY CAPACITY CAPACITY
Transportation Tableau
14-28
Transportation Tableau
14-29
Burruss’ Production Plan
14-30
1 900 1000 100 0 5002 1500 1200 150 250 6003 1600 1300 200 500 10004 3000 1300 200 500 0
Total 7000 4800 650 1250 2100
REGULAR SUB- ENDINGPERIOD DEMAND PRODUCTION OVERTIME CONTRACT INVENTORY
Period 2’s endinginventory
Regular productionfor period 1
Cost of solution
Excel and Transportation Method
14-31
Other Quantitative Techniques
• Linear decision rule (LDR)
• Search decision rule (SDR)
• Management coefficients model
14-32
Hierarchical Nature of Planning
14-33
Items
Product lines or families
Individual products
Components
Manufacturing operations
Resource Level
Plants
Individual machines
Critical work
centers
Production Planning
Capacity Planning
Resource requirements
plan
Rough-cut capacity
plan
Capacity requirements
plan
Input/ output control
Sales and Operations
Plan
Master production schedule
Material requirements
plan
Shop floor
schedule
All work centers
Disaggregation
14-34
• Breaking an aggregate plan into more detailed plans
• Create Master Production Schedule for Material Requirements Planning
Collaborative Planning
• Sharing information and synchronizing production across supply chain
• Part of CPFR (collaborative planning, forecasting, and replenishment)• involves selecting products to be jointly managed,
creating a single forecast of customer demand, and synchronizing production across supply chain
14-35
Available-to-Promise (ATP)• Quantity of items that can be promised to customer• Difference between planned production and customer
orders already received
14-36
AT in period 1 = (On-hand quantity + MPS in period 1) –
(CO until the next period of planned production)
ATP in period n = (MPS in period n) –
(CO until the next period of planned production)
• Capable-to-promise• quantity of items that can be produced and mad available at a
later date
ATP
14-37
ATP
14-38
ATP
14-39
ATP in April = (10+100) – 70 = 40
ATP in May = 100 – 110 = -10
ATP in June = 100 – 50 = 50
= 30
= 0
Take excess units from April
14-40
Rule Based ATPProduct Request
Is the product available at
this location?
Is an alternative product available
at an alternate location?
Is an alternative product available at this location?
Is this product available at a
different location?
Available-to-promise
Allocate inventory
Capable-to-promise date
Is the customer willing to wait for the
product?
Available-to-promise
Allocate inventory
Revise master schedule
Trigger production
Lose sale
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Aggregate Planning for Services
• Most services cannot be inventoried
• Demand for services is difficult to predict
• Capacity is also difficult to predict
• Service capacity must be provided at the appropriate place and time
• Labor is usually the most constraining resource for services
14-41
14-42
Yield Management
14-43
Yield Management
Yield Management
14-44
NO-SHOWS PROBABILITY P(N < X)
0 .15 .001 .25 .152 .30 .403 .30 .70
Optimal probability of no-shows
P(n < x) = = .517Cu
Cu + Co
7575 + 70
.517
Hotel should be overbooked by two rooms