Aggregate Sales and

Operations Planning

Planning Horizon

Aggregate planning: Intermediate-

range capacity planning, usually

covering 2 to 12 months.

Short

range

Intermediate

range

Long range

Now 2 months 1 Year

Long-range plans

Long term capacity

Location / layout

Intermediate plans (General levels)

Employment

Output

Inventory

Subcontracting

Overtime/Under Time

Short-range plans (Detailed plans)

Machine loading

Job assignments/sequencing/work schedules

Overview of Planning Levels

Hierarchical Approach to Planning

Aggregate Planning

Also called “Sales and Operation

Planning”

The term has been coined by companies to

refer to the process that helps companies

keep demand and supply in balance

What does Aggregate Mean?

Overall terms

Product families or product lines rather than

individual products

Big picture approach to planning

Aggregate, for example # bicycles to be

produced, but would not identify bicycles by

colour, size, type etc.

Aggregate Planning

Quarter 1

Jan Feb Mar

150,000 120,000 110,000

Quarter 2

Apr May Jun

100,000 130,000 150,000

Quarter 3

Jul Aug Sep

180,000 150,000 140,000

Disaggregation

In the manufacturing environment the process of breaking down the aggregate plan into greater detail is called disaggregation

Disaggregation results in Master Production Schedule (MPS)

MPS Purchasing

Production of parts or components

Aggregate Plan to Master

Schedule

Aggregate

Planning

Disaggregation

Master

Schedule

Master schedule: The result of

disaggregating an aggregate plan;

shows quantity and timing of

specific end items for a scheduled

horizon.

Aggregate Planning

It determines the resource capacity a firm will need to meet its demand over an intermediate time horizon

In this time frame it is too early to determine production level by SKU but too late to arrange additional capacity

Aggregate Planning

Aggregate planning: General plan

Combined products = aggregate product

Short and long sleeve shirts = shirt

Single product

Pooled capacities = aggregated capacity

Dedicated machine and general machine = machine

Single capacity

Time periods = time buckets

Consider all the demand and production of a given month

together

Quite a few time buckets

Why Aggregate Planning?

Provides for fully loaded facilities, thus

minimizing

Overloading and under loading

Minimizing cost over the planning period

Adequate production capacity to meet

expected aggregate demand

Optimize balance between demand and

supply

Why Aggregate Planning?

A plan for orderly and systematic change

of production capacity to meet peaks and

valleys of expected customer demand

Getting the most output for the amount of

resources available, which is important in

times of scarce production resources

Steps in Aggregate Planning

1. Begin with sales forecast for each

product that indicates the quantities to be

sold in each time period (usually weeks,

months, or quarters) over the planning

horizon (3-18 months)

2. Total all the individual product or service

forecast into one aggregate demand.

Steps in Aggregate Planning

3. Determine capacities (regular time, OT,

Subcontracting) for each period

4. Identify company policy (chase, level)

5. Determine unit costs for regular time, OT,

subcontracting, holding inventories, back

orders, layoffs etc.

Steps in Aggregate Planning

6. Develop alternative plans and compute

cost for each

7. Select the best alternative that satisfies

company’s objectives

Strategies for Meeting Demand

Proactive

Alter demand to match capacity

Reactive

Alter capacity to match demand

Mixed

Some of each

Strategies for Meeting Demand

Proactive strategies

Influencing Demand

Offer discounts and promotions

Increase advertising in slack periods

Counter seasonal products

Lawnmowers (summer) and snow-blowers (winter)

Strategies for Meeting Demand

Reactive Strategies

Changing inventory levels

Vary workforce size (hiring and lay-off)

Varying shifts

Varying working hours

Varying production through overtime or idle time

Subcontracting

Inputs to Aggregate Planning

Production rates

Demand forecast

Policies on work force changes

Costs (inventory, hiring, firing, OT, sub-

contracting)

Inventory levels

Outputs of Aggregate Planning

Total cost of a plan

Projected levels of

Inventory

Output

Employment

Subcontracting

Inventory Calculations

Inventory Calculations

# Workers Calculations

Graphical Method

Popular techniques

Easy to understand and use

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

Require only limited computations

Graphical MethodMonth Expected

Demand

Production

DaysDemand /

day

Avg. daily

demand

Jan 900 22 41 50

Feb 700 18 39 50

March 800 21 38 50

April 1200 21 57 50

May 1500 22 68 50

June 1100 20 55 50

6,200 124

Graphical Method

Note: Forecast differs from average demand

Aggregate Planning Techniques

Two pure forms of aggregate planning strategies

Level Production

Maintain constant workforce and adjust inventory

Chase Demand

Hiring and Firing people

Mixed Strategy

Combination of

Overtime, under time, & subcontracting

Part Time employees

Hiring and firing

Inventory

Backordering

Note: When one alternative: Pure Strategy

When two or more are selected: Mixed strategies

Level Strategy

It is an aggregate planning in which daily

or monthly production is uniform

Toyota and Nissan follow this strategy

Finished goods inventory go up or down to

buffer the difference between demand and

production

Works when demand is stable

Level Production Strategy

LEVEL PRODUCTION STRATEGY

Assume begin inventory: 2000

Chase Strategy

It attempts to achieve output rates that

match demand forecast for that period.

This strategy can be accomplished by:

Vary workforce levels (hiring and firing)

Chase Demand Strategy

CHASE DEMAND STRATEGY

OVERTIME & SUBCONTRACTING

Chase vs. Level

Chase Approach

Advantages

Investment in inventory

is low

Labor utilization in high

Disadvantages

The cost of adjusting

output rates and/or

workforce levels

Level Approach

Advantages

Stable output rates and

workforce

Disadvantages

Greater inventory costs

Increased overtime and

idle time

Resource utilizations vary

over time

Mixed Strategy

For most firms, neither a chase strategy

nor a level strategy is likely to prove ideal,

so a combination of options must be

achieved to meet demand and minimize

cost

More complex than pure ones but typically

yield a better strategy

Mixed Strategy

Examples

Do not hire or lay off workers, adjust the production

rate by varying the number of shifts, use inventory

and subcontracting to match supply and demand

Do not hire or lay off workers, use subcontracting

during periods of high demand and build inventory

during periods of low demand

MIXED STRATEGY

Linear Programming

Approaches to AP

Finds minimum cost solution related to

regular labour time, overtime,

subcontracting, caring inventory, and costs

associated with changing the size of

workforce

Mathematical Techniques to

Aggregate Planning

Linear Programming

Optimal solutions

Cost minimization

Profit maximization

Appropriate when cost and variable

relationships are linear

Application in industry limited

Transportation Method in AP

Transportation Method in AP

Transportation Method

(An Example)

Total Costs

Period Demand Regular

Production

Overtime Subcontract End

Inventory

1 900 1000 100 0 500

2 1500 1200 150 250 600

3 1600 1300 200 500 1000

4 3000 1300 200 500 0

Total 7000 4800 650 1250 2100

Total Cost: 4800×$20+650×$25+1250×$28+2100×$3 = $153,550

Transportation Method

(Second Example – Prob 7)

Transportation Method: Cost of

Plan Period 1: 50($0)+300($50)+50($65)+50($80)=$22,250

Period 2: 400($50)+50($65)+100($80)=$31,250

Period 3: 50($81)+450($50)+50($65)+200($80)=$45,800

Total Cost: $99,300

Simulation Models in AP

Development of computerized model under variety of conditions to find reasonably acceptable solutions

Advantages Lends itself to problems that are difficult to solve

mathematically

Experimenting system behaviour without any risk

Compresses time to understand system

Understand system behaviour under wide range of conditions

Simulation Models in AP

Limitations

Simulation does not produce optimal

solutions, it merely indicates approximate

behaviour for a set of inputs

Simulations are based on models, and

models are only approximation of reality

Summary of Aggregate

Planning Techniques

Technique Solution

Approach

Characteristics

Spreadsheet Heuristic (trial and

error)

Intuitively appealing,

easy to understand,

solution not optimal

Linear Programming Optimizing Computerized

Simulation Heuristic (trial and

error)

Computerized

models can be

examined under

various scenarios