PEMP-EMM2506
Demand forecasting & Aggregate
planning in a Supply chain
Session Speaker
Prof.P.S.Satish
M.S Ramaiah School of Advanced Studies - Bangalore
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Introduction
• Forecasting provides an estimate of future demand
• Factors that influence demand and whether these factors will
continue to influence demand must be considered when
forecasting.
• Improved forecasts benefit all trading partners in the supply
chain.
• Better forecasts result in lower inventories,
reduced stock-outs,
smoother production plans,
reduced costs,
and improved customer service.
Walmart’s Strategy
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Demand Planning and Forecasting
Demand Planning
• Involves forecasting and other activities like Promotion etc.
Types: 1. Independent Demand ( Ex: Finished goods)
2. Dependent or Derived Demand
(Ex: components or subassemblies)
• Independent Demand items are forecasted whereas the
Dependent items can be derived from the latter
100 Refrigerators = 100 Compressors
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Approach to Demand Forecasting
• Understand the Objective of Forecasting
• Integrate Demand Planning and forecasting
• Identify factors that influence demand forecast
viz Demand, Supply and Product Side
• Understand and Identify customer segments
• Determine the appropriate forecasting technique
• Establish Performance and error measures for the
forecast.
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Classification of Forecasting
• Short range ( up to 1 year )
• Medium range ( up to 3 years )
• Long range ( more than 3 years )
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Forecasting Types
• Economic Forecast – IMF
• Technological Forecast – Euro Engines
• Demand Forecast – Matching Supply and Demand
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Forecasting Techniques
• Qualitative forecasting is based on opinion and intuition.
• Quantitative forecasting uses mathematical models and
historical data to make forecasts.
• Time series models are the most frequently used among all
the forecasting models.
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Forecasting Techniques- Cont.
Qualitative Forecasting Methods
Generally used when data are limited, unavailable, or not
currently relevant.
Forecast depends on skill and experience of forecaster(s) and
available information.
Four qualitative models used are:
1.
2.
3.
4.
Jury of executive opinion
Delphi method
Sales force composite
Consumer survey
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Forecasting Techniques- Cont.
Quantitative Methods
• Time series forecasting- based on the assumption that the
future is an extension of the past. Historical data is used to
predict future demand.
• Associative (causal) forecasting- assumes that one or more
factors (independent variables) predict future demand.
It is generally recommended to use a combination of
quantitative and qualitative techniques.
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Quantitative Methods
• Moving Average Method
• Exponential Smoothing
• Trend Projection
Time series model
• Linear Regression
Causal model
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Forecasting Techniques- Cont.
Components of Time Series- Data should be plotted to detect
for the following components:
– Trend variations: either increasing or decreasing
– Cyclical variations: wavelike movements that are longer
than a year
– Seasonal variations: show peaks and valleys that repeat
over a consistent interval such as hours, days, weeks,
months, years, or seasons
– Random variations: due to unexpected or unpredictable
events
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Forecasting Techniques- Cont.
Time Series Forecasting Models
– Simple Moving Average Forecasting Model. Simple
moving average forecasting method uses historical data
to generate a forecast.
– Works well when demand is fairly stable over time.
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Moving Average Method Calculations
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Sales of Washing Machine at Arvee Electronics
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Forecasting Techniques- Cont.
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Forecasting Techniques- Cont.
Time Series Forecasting Models
– Weighted Moving Average Forecasting ModelWhenever there is a detectable trend or pattern, in
order to be responsive, weights can be used.
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Forecasting Techniques- Cont.
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Disadvantage of moving average
• Lengthy calculations involved
• Need to keep historical Data
• Equal weightage or no basis for weightage
for the Data
To overcome these difficulties, exponential
smoothing is used
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Forecasting Techniques- Cont.
Time Series Forecasting Models
– Exponential Smoothing Forecasting Model- a weighted
moving average in which the forecast for the next
period’s demand is the current period’s forecast adjusted
by a fraction of the difference between the current
period’s actual demand and its forecast.
– Only two data points are needed.
Ft+1 = Ft+(At-Ft)
Where
Ft+1 = forecast for Period t + 1
Ft = forecast for Period t
At = actual demand for Period t
 = a smoothing constant (0 ≤  ≤1).
 = 2/(N+1)
Where N=
period of
moving
average ;
Typically 0.1
to 0.4
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Forecasting Techniques- Cont.
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Trend Projections
Least square method for finding the best-fitting line
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Least Square Method
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An Example
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Seasonal Variations in Data
• Monthly sales and demand of IBM notebook computer in
Bangalore is as shown below for 1999-2000.
Calculate 2001 demand for selling 1200 notebooks.
Month
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Sale
1999
80
75
80
90
115
110
100
90
85
75
75
80
Demand
2000
100
85
90
110
131
120
110
110
95
85
85
80
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Create a table in this format
Month
Sale
1999
Demand
2000
Avg.
1999-2000
Avg.
Monthly
Demand
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Avg.
Seasonal
Index
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IBM Notebook exercise … Contd
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Causal Forecasting Model
-Regression Analysis
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Causal Forecasting Model
• Consider’s several variables that are related
• Explain’s cause of time series
Ex: Sale of a product depends on:
Firm’s Advertising budget
Price charged
Competitor’s price
Promotional Strategies etc.
• Regression Analysis is a tool to develop causal model
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Forecasting Techniques- Cont.
Associative Forecasting Models- One or several external
variables are identified that are related to demand
– Simple (linear) regression. Only one explanatory variable
is used and is similar to the previous trend model. The
difference is that the x variable is no longer a time but an
explanatory or independent variable.
Ŷ = a + b1 x
– where
Ŷ = forecast or dependent variable
x = explanatory or independent variable
a = y-axis intercept of the line
b1 = slope of the line
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Forecasting Techniques- Cont.
Associative Forecasting Models– Multiple regression. Where several explanatory variables are
used to make the forecast.
Ŷ = a + b1x1 + b2x2 + . . . bkxk
– where
Ŷ = forecast or dependent variable
xk = kth explanatory or independent variable
a = Y-axis intercept of the line
bk = regression coefficient of the independent
variable xk
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Scatter Diagram
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Forecast Accuracy
The formula for forecast error, defined as the difference between
actual demand and the forecast, follows:
Forecast error, et = At - Ft
where
et = forecast error for Period t
At = actual demand for Period t
Ft = forecast for Period t
Several measures of forecasting accuracy follow:
– Mean absolute deviation (MAD)- a MAD of 0 indicates
the forecast = predicted demand.
= ∑ (forecast error) / n, where n is number of period.
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Formulae for Monitoring and Controlling forecast
• MAD = ( Sum of forecast errors / n ).
• Mean squared error (MSE)
= ( ( Sum of forecast error ) 2 / n ).
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Aggregate Planning
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Introduction
• Aggregate planning is done for period of 6 to
18 months
• It translates business plan and strategic intent
to operational decisions
• Purpose is to specify combination of
production rate, workforce and inventory in
hand needed
• In planning total expected demand is reckoned
without regard to product mix that makes up
the figure
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Aggregate Planning
• What is it?
– Once long term decisions are made, it is necessary to make intermediate
range plans that are consistent with long-range policies
– Management must work within the resources allocated by long-range
decisions
– Given the sales forecasts, the factory capacity, aggregate inventory levels,
and the size of the workforce, the manager must decide at what rate of
production to operate the plant over the intermediate term
– This intermediate-range planning is generally known as aggregate
planning
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Why Aggregate Planning is necessary?
• Fully load facilities and minimize overloading and
underloading
• Make sure enough capacity available to satisfy
expected demand
• Plan for the orderly and systematic change of
production capacity to meet the peaks and valleys of
expected customer demand
• Get the most output for the amount of resources
available
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Why Aggregate Planning necessary?
• To meet demand fluctuations like in festivals
• Capacity fluctuations – Number of working
days in month, unexpected shutdowns..
• Production rate cannot be changed without
proper planning
• Planning helps to manage anticipated demand
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Aggregate Planning
• Purpose
– Aggregate plans and master schedules provide common points at which
capacity and inventories are considered jointly in the light of firm’s longrange plans, and they provide inputs to the financial plan, the marketing
plan, and requirements planning and detailed scheduling decisions
– Several crucial decisions have to be made while generating an aggregate
plan
• Management may ask many inventory- and workforce- related questions
• To what extent should inventories be used for absorbing changes in demand
that might occur during the intermediate term?
• Should we absorb the fluctuations by varying the size of the workforce*
– Generally a mixture of strategies is preferred and is feasible
– An aggregate plan is a valuable procedure to help in the development of
operating budgets
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Aggregate Planning
• Purpose
– Products or services can be aggregated into a set of relatively
broad product families without getting into too much of detail
– A company can organize labour in various ways – based on
flexibility to handle different products/services, or, based on
product lines
– When time is considered, the planning horizon is an important
aspect. It is the length of time covered by an aggregate plan. A
company will usually look at time in the aggregate – months,
quarters, or seasons (rather than days or hours)
– Some companies use monthly planning periods for the near portion
of the planning horizon and quarterly periods for the later portion
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Aggregate Planning
• Purpose
– In practice, planning periods reflect a balance between the needs for
• a limited number of decision points to reduce planning complexity
• flexibility to adjust output rates and the workforce levels when
demand forecasts exhibit seasonal variations
• Relationship of aggregate to other plans is in figure below
Business or
Annual plan
Aggregate
plan
MPS or
Workforce schedule
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Aggregate Planning
• Managerial inputs from various functional areas to aggregate
plans
Operations
Current, future
& workforce
capacities
Materials
Supplier capabilities
Storage capacity
Materials availability
Distribution and
Marketing
Customer needs,
Demand, Competition
Aggregate plan
Accounting and
Finance
Cost data, financial
Condition of firm
Human resources
Labour market
Conditions, training
capacity
Engineering
New products, design changes
machine standards
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Aggregate planning process
• The process for preparing aggregate plans is dynamic
and continuing, as aspects of the plan are updated
periodically when new information becomes available
and new opportunities emerge*
• The steps are:
–
–
–
–
Determining demand requirements
Identifying alternatives, constraints and costs
Preparing an acceptable plan
Implementing and updating the plan
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Aggregate planning process
• The process flow chart
Determine
requirements for
planning horizon
Identify
alternatives,
constraints and
costs
Prepare
prospective plan
for planning
horizon
No
Move ahead to
Next
planning session
Implement and
update the plan
Is the plan
acceptable?
Yes
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Aggregate planning process
• Determining demand requirements
– The first step in the planning process is to determine the
demand requirements for each period of the planning horizon
– For production plans, the requirements represent the demand
for finished goods and the external demand for replacement
parts
– For staffing plans, the planner bases forecasts of staff
requirements for each workforce group on historical levels of
demand, managerial judgment and existing backlogs for
services
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Aggregate planning process
• Identifying alternatives, constraints and costs
– Constraints represent physical limitations or managerial
policies associated with the aggregate plan
• Examples of physical constraints might include training facilities
capable of handling only so many new hires at a time, machine
capacities that limit maximum output, or inadequate inventory storage
space
– A planner usually considers several types of costs when
preparing aggregate plans
• Regular-time costs
• Overtime costs – typically 150% of regular time wages
• Hiring (advertising jobs, interviews, etc.) and layoff (exit interviews,
severance pay, etc.) costs
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Aggregate planning process
• Identifying alternatives, constraints and costs
– A planner usually considers several types of costs ….
• Inventory holding costs that vary with the level of inventory
investment: the costs of capital tied up in inventory, variable storage
and warehousing, etc.
• Backorder and stock out costs like the costs of lost sales and the
potential cost of losing the customer’s sales to competitors
• Hiring (advertising jobs, interviews, etc.) and layoff (exit interviews,
severance pay, etc.) costs
– Preparing an acceptable plan
• This is an iterative process (plans may need to go through several revisions
and adjustments
– Implementing and updating the plan which requires the commitment of
all functional area managers
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Aggregate planning process
• Developing and evaluating the level production plan
– One possible level strategy, which uses a constant number of
employees that will satisfy demand during the planning
horizon, is determined by using the maximum amount of
overtime in the peak period
– Under time is used in slack periods
– Level strategy can lead to considerable under time
– Cost of this unused capacity depends on whether under time
is paid or unpaid
– The planning can be done with a spreadsheet^
– Example problem follows
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Aggregate planning
• Details
– A manufacturing firm’s aggregate plan, called a production plan
focusses on production rates and inventory holdings
– A service firm’s aggregate plan, called a staffing plan, centers on
staffing and other labour related factors
– Based on the long-term goals of a company, the aggregate plan
specifies how the company will work for the next year or so
toward these goals within existing equipment and facility capacity
constraints
– For manufacturing companies, the aggregate plan links strategic
goals and objectives with production plans for individual products
and the specific components that go into them
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Aggregate Planning
• Details
– For service firms the aggregate plan links strategic goals with detailed
workforce schedules
– When we say aggregate, the sense is that the planning activities at this
early stage are concerned with homogeneous categories, such as gross
volumes of products or number of customers served
– Illustration below gives the aggregate plan of a motor manufacturer
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Aggregate planning
• Strategies
– Many aggregate planning strategies are available to the
manager
– The many functional areas in an organization that give input
to the aggregate plan typically have conflicting objectives for
the use of the organization’s resources
– The objectives could be:
• Minimize costs/maximize profits – If customer demand is not affected
by the plan, minimizing costs will also maximize profits
• Maximize customer service – Improving delivery time and on-time
delivery may require additional workforce, machine capacity, or
inventory resources
• Minimize inventory investment – Inventory accumulations are
expensive because the money could be used for more productive
investments
• Maximize utilization of plant and equipment – Processes based on a
line flow strategy require uniformly high utilization of plant and
equipment
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Aggregate planning
• Strategies
– The objectives (cont’d):
• Minimize changes in production rates – Frequent changes in
production rates can cause difficulties in coordinating the
supplies of materials and require production line rebalancing
• Minimize changes in workforce levels – Fluctuating workforce
levels may cause lower productivity because new employees
typically need time to become fully productive
– Balancing these various objectives to arrive at an acceptable
aggregate plan involves consideration of various alternatives
– A classification scheme is shown in the next slide
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Aggregate planning-Meeting Demand
• Pure Strategy : One of the variable say workforce is
changed to absorb demand fluctuation
• Mixed Strategy : Here more than one variable say
workforce and inventory are changed to absorb
fluctuations
This is mostly used in Industries
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Aggregate planning-Meeting demand
• Chase Strategy : Match the production rate
needed by hiring and laying off employees as
the order rate varies. For this pool of trained
people must be available as volume increases.
Has motivational issues.
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Aggregate planning-Meeting Demand
• Level Strategy : Making a stable workforce
working at constant output rate. Shortages
and surpluses are absorbed by fluctuating
inventory levels, order backlogs and lost
sales. Potential implication decreased
customer service level and increased
inventory costs
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Aggregate Planning-Meeting Demand
• Stable workforce – Variable work hours :
Vary the output by varying number of hours
worked through flexible work schedules or
overtime. Better employee motivation.
Overtime cost extra
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Medium-Term Capacity Adjustments
• Workforce level
– Hire or layoff full-time workers
– Hire or layoff part-time workers
– Hire or layoff contract workers
• Utilization of the work force
– Overtime
– Idle time (under time)
– Reduce hours worked
• . . . more
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Medium-Term Capacity Adjustments
• Inventory level
– Finished goods inventory
– Backorders/lost sales
• Subcontract
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Aggregate Plans for services
• For standardized services, aggregate planning may be simpler
than in systems that produce products
• For customized services,
– there may be difficulty in specifying the nature and extent
of services to be performed for each customer
– customer may be an integral part of the production system
• Absence of finished-goods inventories as a buffer between
system capacity and customer demand
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Yield Management
• It is a process of allocating right type of
capacity to the right type of customer at the
right price and time to maximize revenue or
yield
E.g. :- Airlines booking in advance at
cheaper prices
- Hotel booking in advance
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Yield Management
Yield Management is most effective when :
• Demand can be segmented by customer
• Fixed costs are high and variable costs are
low
• Inventory is perishable
• Product can be sold in advance
• Demand is highly variable
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Session Summary
•
Analysing demand forecasts has been explained
•
Time series and causal models have been demonstrated
with examples.
•
Strategies adopted in aggregate planning has been
elucidated
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