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Operations Management: Sustainability and Supply Chain Management

Third Canadian Edition

Chapter 13

Aggregate Planning and Sales and Operations Planning

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Outline

Global Company Profile: Frito-Lay

The Planning Process

The Nature of Aggregate Planning

Aggregate Planning Strategies

Methods for Aggregate Planning

Aggregate Planning in Services

Yield Management

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Learning Objectives (1 of 2)

When you complete this chapter you should be able to:

Define aggregate planning and sales and operations planning

Identify optional strategies for developing an aggregate plan

Prepare a graphical aggregate plan

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Learning Objectives (2 of 2)

When you complete this chapter you should be able to:

Solve an aggregate plan via the transportation method of linear programming

Understand and solve a yield management problem

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Frito-Lay (1 of 2)

More than three dozen brands, 15 brands sell more than $100 million annually, 7 sell over $1 billion

Planning processes covers 3 to 18 months

Unique processes and specially designed equipment

High fixed costs require high volumes and high utilization

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Frito-Lay (2 of 2)

Demand profile based on historical sales, forecasts, innovations, promotion, local demand data

Match total demand to capacity, expansion plans, and costs

Quarterly aggregate plan goes to 38 plants in 18 regions

Each plant develops 4-week plan for product lines and production runs

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Aggregate Planning (1 of 4)

The objective of aggregate planning is to meet forecasted demand while minimizing cost over the planning period

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Aggregate planning covers intermediate-range decisions, usually 3 to 18 months ahead.

LO 1: Define aggregate planning.

The Planning Process

Determine the quantity and timing of production for the intermediate future

Objective is to minimize cost over the planning period by adjusting

Production rates

Labour levels

Inventory levels

Overtime work

Subcontracting rates

Other controllable variables

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This slide provides the list of the major decisions undertaken in aggregate planning. Notice that scheduling of specific workers and products is not done in aggregate planning—such decisions represent short-term scheduling (Chapter 15) that will be based at the appropriate time on the constraints produced from the aggregate plan. The aggregate plan helps the firm prepare for any necessary hiring and layoffs of workers to come in the intermediate future. It also signals when to set up subcontracting relationships and orders.

Aggregate Planning (2 of 4)

Required for aggregate planning

A logical overall unit for measuring sales and output

A forecast of demand for an intermediate planning period in these aggregate terms

A method for determining costs

A model that combines forecasts and costs so that scheduling decisions can be made for the planning period

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This slide identifies the four things needed for aggregate planning.

Planning Horizons

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This slide (Figure 13.1) helps to distinguish the various planning horizons and associated tasks and personnel responsible for the decisions. Aggregate planning provides the link between long-range capacity decisions (Supplement 7) and short-range scheduling of workers and jobs (Chapter 15). Long-range capacity decisions certainly impact the flexibility of aggregate plans.

Aggregate Planning (3 of 4)

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This slide (Figure 13.2) shows how aggregate planning fits into the larger production planning system.

Aggregate Planning (4 of 4)

Combines appropriate resources into general terms

Part of a larger production planning system

Disaggregation breaks the plan down into greater detail

Disaggregation results in a master production schedule

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The aggregate plan is described in general terms. Disaggregation of the plan breaks it down into more detail for more specific planning such as the master production schedule, which is a timetable that specifies what is to be made and when (Chapter 14).

Aggregate Planning Strategies

Use inventories to absorb changes in demand

Accommodate changes by varying workforce size

Use part-timers, overtime, or idle time to absorb changes

Use subcontractors and maintain a stable workforce

Change prices or other factors to influence demand

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This list presents legitimate planning strategies. The aggregate plan may suggest one or a combination of the strategies.

LO 2: Identify optional strategies for developing an aggregate plan.

Capacity Options (1 of 5)

Changing inventory levels

Increase inventory in low demand periods to meet high demand in the future

Increases costs associated with storage, insurance, handling, obsolescence, and capital investment

Shortages may mean lost sales due to long lead times and poor customer service

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These slides describe the five capacity options, named so because they do not try to change demand but attempt to absorb demand fluctuations. Firms can change inventory levels, building up anticipatory inventory during periods of low demand. We know from Chapter 12 that inventory is expensive, so this can be a costly approach for firms experiencing very seasonal demand.

Capacity Options (2 of 5)

Varying workforce size by hiring or layoffs

Match production rate to demand

Training and separation costs for hiring and laying off workers

New workers may have lower productivity

Laying off workers may lower morale and productivity

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Firms can vary the workforce size as demand conditions change. This strategy may work well if hiring and firing costs are not too high and significant training of new employees is not necessary. The human resource implications of this strategy need to be carefully considered.

Capacity Options (3 of 5)

Varying production rate through overtime or idle time

Allows constant workforce

May be difficult to meet large increases in demand

Overtime can be costly and may drive down productivity

Absorbing idle time may be difficult

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Firms can vary production rates using overtime and idle time. This strategy may work well for short-term or relatively small demand changes, but it becomes expensive and potentially unmanageable for reacting to major demand shifts.

Capacity Options (4 of 5)

Subcontracting

Temporary measure during periods of peak demand

May be costly

Assuring quality and timely delivery may be difficult

Exposes your customers to a possible competitor

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Firms can subcontract out excess demand that they cannot handle internally. The unit cost of this strategy is typically higher than the internal production cost, and the strategy carries with it the usually risks of delegating any task.

Capacity Options (5 of 5)

Using part-time workers

Useful for filling unskilled or low skilled positions, especially in services

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Firms can use temporary or part-time workers during peak demand periods. This practice may work well, particularly in service industries. However, there have been concerns in recent years that big companies are hiring too many temporary employees and avoiding paying benefits such as health insurance in the process. Concerns like this can damage a firm’s reputation as a good corporate citizen.

Demand Options (1 of 3)

Influencing demand

Use advertising or promotion to increase demand in low periods

Attempt to shift demand to slow periods

May not be sufficient to balance demand and capacity

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These slides cover demand options, through which firms try to smooth out changes in the demand pattern over the planning period. A smoother demand pattern implies less necessity for implementing one of the expensive capacity options. Instructors can present examples showing that sometimes a smooth demand pattern can result in higher overall profit than a varying pattern with higher total demand (i.e., the varying pattern might have more revenue but the additional costs of meeting that varying demand might outweigh the revenue gain).

This slide shows that firms can influence demand through the use of advertising and promotions in low-demand periods. Such strategies are also known as off-peak pricing, and we see them all the time in the form of matinee movie specials, cheap rates at ski resorts during the summer, etc. Some of this generated demand may be new customers enticed by the promotion, but the rest may be shifted demand (customers moving from high-demand periods to low-demand periods). Shifted demand produces a smoother demand pattern overall.

Demand Options (2 of 3)

Back ordering during high-demand periods

Requires customers to wait for an order without loss of goodwill or the order

Most effective when there are few if any substitutes for the product or service

Often results in lost sales

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Firms sometimes intentionally plan backorders during high-demand periods. These come at a cost and assume that customers will be willing to wait to receive the product (a potentially dangerous assumption). Firms with some sort of monopoly power are often in a better position to employ this strategy.

Demand Options (3 of 3)

Counterseasonal product and service mixing

Develop a product mix of counterseasonal items

May lead to products or services outside the company’s areas of expertise

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Firms sometimes employ the strategy of counterseasonal products and service mixing. Producing products with different high-demand seasons such as snowmobiles and jet skis can smooth out demand over the year. Another form of this technique sells seasonal products to markets in the Northern Hemisphere for part of the year and to markets in the Southern Hemisphere for the other part of the year.

Methods for Aggregate Planning

A mixed strategy may be the best way to achieve minimum costs

There are many possible mixed strategies

Finding the optimal plan is not always possible

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A combination of the different aggregate planning options may turn out to be the best strategy. There are also two extreme strategies: chase and level.

LO 3: Prepare a graphical aggregate plan.

Mixing Options to Develop a Plan (1 of 2)

Chase strategy

Match output rates to demand forecast for each period

Vary workforce levels or vary production rate

Favoured by many service organizations

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This slide describes the chase strategy, where demand is “chased” by production. Little or no inventory is held, and the strategy may result in a significant amount of hiring and worker layoffs.

Mixing Options to Develop a Plan (2 of 2)

Level strategy

Daily production is uniform

Use inventory or idle time as buffer

Stable production leads to better quality and productivity

Some combination of capacity options, a mixed strategy, might be the best solution

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This slide describes the level strategy, where workforce levels and production rates remain constant over time. The changing inventory levels option applies here. Human resource difficulties are usually minimized using a level strategy, but the inventory costs may be significant.

Graphical Methods (1 of 2)

Popular techniques

Easy to understand and use

Trial-and-error approaches that do not guarantee an optimal solution

Require only limited computations

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Graphical methods represent trial-and-error approaches to the aggregate planning problem. Slide 25 identifies the five steps involved. And, actually, Steps 1–4 are required for any of the aggregate planning solution methods.

Graphical Methods (2 of 2)

Determine the demand for each period

Determine the capacity for regular time, overtime, and subcontracting each period

Find labour costs, hiring and layoff costs, and inventory holding costs

Consider company policy on workers and stock levels

Develop alternative plans and examine their total costs

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LO 3: Prepare a graphical aggregate plan.

Roofing Supplier Example 1 (1 of 2)

Table 13.2 Monthly Forecasts

Month	Expected Demand	Production Days	Demand Per Day (computed)
Jan	900	22	41
Feb	700	18	39
Mar	800	21	38
Apr	1200	21	57
May	1500	22	68
June	1100	20	55
	6200	124	Blank

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These slides cover continuing Examples 1–4 from the text. Slide 26 presents the demand data for the examples. Note that the daily demand is based on the number of production days per month, which varies for this firm. Slide 27 graphs the average forecasted monthly demand per day as compared to the average daily demand overall of 50 units. The ensuing three examples present three different strategies for meeting the forecasted demand. Slides 28–31 present the raw data along with Example 2—a level strategy with constant workforce. This strategy builds anticipatory inventory in the first few months to be drawn down in later months. The only costs incurred are regular labour and inventory costs.

Roofing Supplier Example 1 (2 of 2)

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Roofing Supplier Example 2 (1 of 4)

Table 13.3

Cost Information	Blank
Inventory carrying cost	$ 5 per unit per month
Subcontracting cost per unit	$20 per unit
Average pay rate	$10 per hour ($80 per day)
Overtime pay rate	$17 per hour (above 8 hours per day)
Labour-hours to produce a unit	1.6 hours per unit
Cost of increasing daily production rate (hiring and training)	$300 per unit
Cost of decreasing daily production rate (layoffs)	$600 per unit

Plan 1 – constant workforce

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Roofing Supplier Example 2 (2 of 4)

Month	Production Days	Production at 50 Units per Day	Demand Forecast	Monthly Inventory Change	Ending Inventory
Jan	22	1100	900	+200	200
Feb	18	900	700	+200	400
Mar	21	1050	800	+250	650
Apr	21	1050	1200	-150	500
May	22	1100	1500	-400	100
June	20	1000	1100	-100	0
					1,850

Total units of inventory carried over from one month to the next = 1850 units

Workforce required to produce 50 units per day = 10 workers

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Roofing Supplier Example 2 (3 of 4)

Costs		Calculations
Inventory carrying	$9250	(= 1850 units carried x $5 per unit)
Regular-time labour	99 200	(= 10 workers x $80 per day x 124 days)
Other costs (overtime, hiring, layoffs, subcontracting)	0
Total cost	$108 450

Total units of inventory carried over from one month to the next = 1850 units

Workforce required to produce 50 units per day = 10 workers

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Roofing Supplier Example 2 (4 of 4)

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Roofing Supplier Example 3 (1 of 5)

Table 13.2 Monthly Forecasts

Month	Expected Demand	Production Days	Demand Per Day (computed)
Jan	900	22	41
Feb	700	18	39
Mar	800	21	38
Apr	1200	21	57
May	1500	22	68
June	1100	20	55
Blank	6200	124	Blank

Plan 2 – subcontracting

Minimum requirement = 38 units per day

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Slides 32–36 present Example 3—a level strategy to cover the lowest-demand period along with subcontracting for all other months. The only costs incurred are regular labour (lower than Example 2) and subcontracting.

Roofing Supplier Example 3 (2 of 5)

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Roofing Supplier Example 3 (3 of 5)

Table 13.3

Cost Information
Inventory carrying cost	$ 5 per unit per month
Subcontracting cost per unit	$20 per unit
Average pay rate	$10 per hour ($80 per day)
Overtime pay rate	$17 per hour (above 8 hours per day)
Labour-hours to produce a unit	1.6 hours per unit
Cost of increasing daily production rate (hiring and training)	$300 per unit
Cost of decreasing daily production rate (layoffs)	$600 per unit

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Roofing Supplier Example 3 (4 of 5)

In-house production = 38 units per day × 124 days

= 4712 units

Subcontract units = 6200 – 4712

= 1488 units

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Roofing Supplier Example 3 (5 of 5)

Costs		Calculations
Regular-time labour	$75 392	(= 7.6 workers × $80 per day × 124 days)
Subcontracting	29 760	(= 1488 units × $20 per unit)
Total cost	$105 152

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Roofing Supplier Example 4 (1 of 4)

Table 13.2 Monthly Forecasts

Month	Expected Demand	Production Days	Demand Per Day (computed)
Jan	900	22	41
Feb	700	18	39
Mar	800	21	38
Apr	1200	21	57
May	1500	22	68
June	1100	20	55
Blank	6200	124	Blank

Plan 3 – hiring and layoffs

Production = Expected Demand

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Slides 37–40 present Example 4—a chase strategy via hiring and layoffs. The costs incurred in this plan are regular labour, hiring, and layoff costs.

Roofing Supplier Example 4 (2 of 4)

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Roofing Supplier Example 4 (3 of 4)

Table 13.3

Cost Information	Blank
Inventory carrying cost	$ 5 per unit per month
Subcontracting cost per unit	$20 per unit
Average pay rate	$10 per hour ($80 per day)
Overtime pay rate	$17 per hour (above 8 hours per day)
Labour-hours to produce a unit	1.6 hours per unit
Cost of increasing daily production rate (hiring and training)	$300 per unit
Cost of decreasing daily production rate (layoffs)	$600 per unit

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Roofing Supplier Example 4 (4 of 4)

Table 13.4 Cost Computations for Plan 3

Month	Forecast (units)	Daily Prod Rate	Basic Production Cost (demand × 1.6 hrs/unit × $10/hr)	Extra Cost of Increasing Production (hiring cost)	Extra Cost of Decreasing Production (layoff cost)	Total Cost
Jan	900	41	$ 14 400	—	—	$ 14 400
Feb	700	39	11 200	—	$1200 (= 2 × $600)	12 400
Mar	800	38	12 800	—	$600 (= 1 × $600)	13 400
Apr	1200	57	19 200	$5 700 (= 19 × $300)	—	24 900
May	1500	68	24 000	$3300 (= 11 × $300)	—	27 300
June	1100	55	17 600	—	$7,800 (= 13 × $600)	25 400
			$99 200	$9000	$9,600	$117 800

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Comparison of Three Plans

Table 13.5 Comparison of the Three Plans

Cost	Plan 1	Plan 2	Plan 3
Inventory carrying	$ 9250	$ 0	$ 0
Regular labour	99 200	75 392	99 200
Overtime labour	0	0	0
Hiring	0	0	9000
Layoffs	0	0	9600
Subcontracting	0	29 760	0
Total cost	$108 450	$105 152	$117 800

Plan 2 is the lowest cost option

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Slide 41 summarizes the costs of the three plans. In this problem, the subcontracting option was the best among the three options, although that would certainly not always be the case.

Mathematical Approaches

Useful for generating strategies

Transportation Method of Linear Programming

Produces an optimal plan

Management Coefficients Model

Model built around manager’s experience and performance

Other Models

Linear Decision Rule

Simulation

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This slide identifies the mathematical approaches for generating good strategies that are described in the text.

LO 4: Solve an aggregate plan via transportation method of linear programming.

Management Coefficients Model

Builds a model based on manager’s experience and performance

A regression model is constructed to define the relationships between decision variables

Objective is to remove inconsistencies in decision making

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The idea behind the management coefficients model is quite different. We assume that previous decisions were good ones and so we create a regression model that relates certain input variables such as demand and labour to past aggregate planning decisions. Future decisions can be based on the resulting regression equations. This minimizes inconsistencies in future decision making.

Other Models

Linear Decision Rule

Minimizes costs using quadratic cost curves

Operates over a particular time period

Simulation

Uses a search procedure to try different combinations of variables

Develops feasible but not necessarily optimal solutions

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Two other models are mentioned in this slide. One of the most important original foundational operations management models was the famous HMMS rule, developed by Holt, Modigliani, Muth, and Simon. This model handles quadratic cost curves, which in some situations may be more realistic than linear cost models.

Computer simulation, on the other hand, represents a high-volume trial-and-error method, searching for the best alternative among many possibilities. The main downside of simulation that that optimal solutions are not guaranteed.

Summary of Aggregate Planning Methods (1 of 2)

Table 13.8 Summary of Four Major Aggregate Planning Methods

Techniques	Solution Approaches	Important Aspects
Graphical methods	Trial and error	Simple to understand and easy to use. Many solutions; one chosen may not be optimal
Transportation method of linear programming	Optimization	LP software available; permits sensitivity analysis and new constraints; linear functions may not be realistic

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These slides reproduce Table 13.8 from the text, comparing aggregate planning techniques.

Summary of Aggregate Planning Methods (2 of 2)

Table 13.8 Continued

Techniques	Solution Approaches	Important Aspects
Management coefficients model	Heuristic	Simple, easy to implement; tries to mimic manager’s decision process; uses regression
Simulation	Change parameters	Complex; may be difficult to build and for managers to understand

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These slides reproduce Table 13.8 from the text, comparing aggregate planning techniques.

Aggregate Planning in Services

Controlling the cost of labour is critical

Accurate scheduling of labour-hours to assure quick response to customer demand

An on-call labour resource to cover unexpected demand

Flexibility of individual worker skills

Flexibility in rate of output or hours of work

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Aggregate planning techniques apply equally as well in services as in manufacturing, but services often implement more demand management strategies. As the control of labour cost is critical in service firms, this slide identifies four successful techniques for doing that

Five Service Scenarios (1 of 2)

Restaurants

Smoothing the production process

Determining the optimal workforce size

Hospitals

Responding to patient demand

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Five different service scenarios are described in these slides. Slide 52: For restaurants, some amounts of anticipatory inventory can be produced during slack periods (rapid inventory perishability is an important consideration), but most demand changes are accommodated by labour capacity changes. Hospitals may have floating staff positions capable of filling in for the very uncertain demand fluctuations in different departments.

Five Service Scenarios (2 of 2)

National Chains of Small Service Firms

Planning done at national level and at local level

Miscellaneous Services

Plan human resource requirements

Manage demand

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Slide 53: For chains of small service firms such as funeral homes, oil change outlets, photocopy centers, and tire centres, central planning may be appropriate if the central office can influence demand via special promotions. “Miscellaneous services” include businesses such as financial, transportation, and many communication and recreation services that provide intangible output. Along with managing demand to minimize the need for extra highly paid professionals during peak periods, these firms need to determine how to fully utilize the professionals during low-demand periods.

Law Firm Example

Table 13.9 Labour Allocation at Klasson and Avalon, Forecasts for Coming Quarter (1 lawyer = 500 hours of labour)

Labour-Hours Required

Capacity Constraints

(1)

(2)

(3)

(4)

(5)

(6)

Forecasts

Category of Legal Business	Best (hours)	Likely (hours)	Worst (hours)	Maximum Demand in People	Number of Qualified Personnel
Trial work	1800	1500	1200	3.6	4
Legal research	4500	4000	3500	9.0	32
Corporate law	8000	7000	6500	16.0	15
Real estate law	1700	1500	1300	3.4	6
Criminal law	3500	3000	2500	7.0	12
Total hours	19 500	17 000	15 000	Blank	Blank
Lawyers needed	39	34	30

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Slide 54 presents Example 6 from the text. Here the law firm analyzes lawyer requirements under best-case, likely, and worst-case demand scenarios. The example suggests a potential shortage (if business is booming) in lawyers to handle trial work and corporate law. Overtime may be adequate to cover the shortfall, but, eventually, more lawyers may need to be hired.

Five Service Scenarios

Airline industry

Extremely complex planning problem

Involves number of flights, number of passengers, air and ground personnel, allocation of seats to fare classes

Resources spread through the entire system

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Slide 55: The airline industry is considered by some to represent the “mother of all scheduling problems.” And even if a good schedule is produced that satisfies all constraints and maximizes revenue, weather or mechanical problems can wreak havoc on the system.

Five Service Scenarios

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Yield Management

Allocating resources to customers at prices that will maximize yield or revenue

Service or product can be sold in advance of consumption

Demand fluctuates

Capacity is relatively fixed

Demand can be segmented

Variable costs are low and fixed costs are high

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Yield management (also known as revenue management) changes the focus of aggregate planning from capacity management to demand management. Successful yield management implementations have generated millions of dollars of additional revenue for some companies. On the other hand, active yield management programs can drive consumers crazy as they may always feel, for example, that someone else on the airplane must be receiving the same service for a lower price. With yield management, companies keep raising and lowering prices in an attempt to extract as much money from customers as possible while simultaneously trying to fill every seat on the airplane, room in the hotel, or seat in the rock concert. Organizations with perishable inventory (airlines, hotels, car rental agencies, cruise lines, etc.) have the shared characteristics identified in this slide that make yield management of interest to them.

LO 5: Understand and solve a yield management problem.

Yield Management Example (1 of 2)

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These illustrate Example 7 from the text. Slide 57 (Figure 13.5) shows the current demand curve as it relates to the current pricing scheme of charging $150 for every room. Because the hotel does not price discriminate based on willingness to pay, potential revenue is lost. Slide 58 (Figure 13.6) shows how additional revenue can be extracted by charging two different price levels.

Yield Management Example (2 of 2)

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Yield Management Matrix

Figure 13.7

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This slide (Figure 13.7) separates firms into level of predictability of use and variability of price. The industries in Quadrant 2 are traditionally associated with yield management. Nevertheless, with enough imagination, firms in the other quadrants can implement certain yield management techniques. Instructors could insert a short class discussion here by having students try to identify good yield management techniques for the industries listed

Making Yield Management Work

Multiple pricing structures must be feasible and appear logical to the customer

Forecasts of the use and duration of use

Changes in demand

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Firms need to manage the three issues identified in this slide to make yield management work. The third issue, “changes in demand,” has at least three components. First, the firm must be able to handle the increased demand with its available resources. Second, customer service must be able to address consumer concerns that arise when the pricing structure may not seem logical and fair to all customers. Third, the firm must deal with any overbooking occurrences arising from an imperfect forecast.

Summary

Aggregate planning is important to set levels of inventory, production, subcontracting, and employment

Planning horizon is usually 3 to18 months

Many different techniques can be applied, both mathematical and graphical.

Less complexity in techniques is favoured by most operations managers.

The aggregate plan output leads to more detailed planning and scheduling

Service firms can also use yield management

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Total expected demand

Average

requirement

Number of production days

6200

50units per day

124