Forecasting uses historical data to predict future trends in order to help companies plan production, inventory, personnel, and facilities. It is based on demand for goods and services compared to production costs. Forecasting helps formulate strategies, project cash flows and capital requirements, allocate budgets, and anticipate hiring needs. There are various forecasting methods including qualitative methods like expert judgment and quantitative methods like exponential smoothing and linear regression. Capacity planning establishes the maximum output rate of a facility and involves allocating capital for equipment and planning workforce and inventory levels. Factors like demand forecasts, resources, product nature, and maintenance affect capacity planning.

1. FORECASTING AND CAPACITY
PLANNING

2. What is Forecasting?
Process of predicting a future event based on historical data Underlying
basis of all business decisions
• Production
• Inventory
• Personnel Facilities

3. Definition
Forecasting is the use of historic data to determine the direction of
future trends by companies to allocate resources and budgets for an
upcoming period of time. This is typically based on demand for the
goods and services it offers, compared to the cost of producing them.

4. Focus
• Technological
• Economical
• Demand

5. SIGNIFICANCES
• Formulate Strategies
• Project cash flows and capital requirements.
• Allocate budgets Anticipate hiring needs.
• Plan Operation System Design
• Process design
• Product design
• Quality design
• Operation support system design

6. Good Forecast
• Cost effective
• Data Availability
• Accuracy
• Simple
• Flexible
• Right Assumptions
• Consistent Quality

7. Factors Affecting
• Demand determinants
• Product Data
• Product Life Cycle (PLC)
• Customer
• Government
• SCM
• Competition
• Substitutes

8. Objectives of Forecasting
• Production and Operations – Plant capacity, Production quantity,
Materials Requirement, Support services, etc.,
• Marketing – Demand, Sales plan, promotional activities, supply chain,
etc.,
• Finance – Budgets, capital requirements, return on investments, etc.,
• Research – Expansion, differentiation, etc.,

9. Selecting the method
• Availability of data
• Demand
• Time
• Purpose of forecasting
• Validity of past data
• Cost involved
• Technology trends
• Flexibility

10. Demand Patterns
• Historical – No change in demand over period of time
• Seasonal – Based on seasonal variables
• Cyclical – Based on the length of single cycle
• Trend – Trend of demand in the past

11. Types of Forecasts by Time Horizon
Short-range forecast
• Usually < 3 months
Medium-range forecast
• 3 months to 2 years
Long-range forecast
• > 2 years
• For example, some colleges and universities look 30 to fifty years ahead,
industries engaged in long distance transportation (steam ship, railroad) or
provision of basic power (electrical and gas utilities, etc.) also look far
ahead (20 to 100 years).

12. Methods of Forecasting
• Qualitative
• Expert Judgement
• Delphi Method
• Test Marketing
• Simulation
• Survey
• Quantitative Exponential
• Exponential smoothing
• Linear Regression
• Time series

13. • Delphi Method - Executives answer the basic question in several
rounds.
• Expert Judgment – Expert in the field decide upon the demand based
on certain analysis
• Test Marketing – A product is released tom a smaller market and
based on the response in that market, forecast is done
• Simulation – Virtual
• Survey – A survey is conducted to understand the customer
requirement

14. https://slideplayer.com/slide/9323036/
• Simple Moving Average Assumes an average is a good estimator of
future behavior Used if little or no trend Used for smoothing Ft+1 =
Forecast for the upcoming period, t+1 n = Number of periods to be
averaged A t = Actual occurrence in period t

15. • Weighted Moving Average
Gives more emphasis to recent data Weights decrease for older data
sum to 1.0 Simple moving average models weight all previous periods
equally This slide introduces the “weighted moving average” method.
It is probably most important to discuss choice of the weights.

16. • Exponential Smoothing
Assumes the most recent observations have the highest predictive
value gives more weight to recent time periods Ft+1 = Ft + a(At - Ft) et
Need initial forecast Ft to start. Ft+1 = Forecast value for time t+1 At =
Actual value at time t = Smoothing constant

17. • Linear Regression Y = Dependent Variable X = Independent Variable
a = Intercept b = Slope of the independent variable X

18. • General Guiding Principles for Forecasting
1. Forecasts are more accurate for larger groups of items. 2. Forecasts
are more accurate for shorter periods of time. 3. Every forecast
should include an estimate of error. Before applying any forecasting
method, the total system should be understood. Before applying any
forecasting method, the method should be tested and evaluated. 6.
Be aware of people; they can prove you wrong very easily in
forecasting

19. • Capacity is the maximum output rate of a facility
Amount of output a system is capable of delivering over a specific
period of time

20. • Capacity is usually purchased in “chunks” and it involves
Capacity Planning Capacity planning is the process of establishing the
output rate that can be achieved at a facility: Capacity is usually
purchased in “chunks” and it involves Allocation of capital for
additional facility & equipment Planning workforce & inventory levels,
& day- to-day use of equipment

21. • How to measure Capacity
There is no one best way to measure capacity Output measures &
Inputs measures

22. • Factors that affect Capacity Plan
Demand forecast Availability of resource – HR, material, technology,
etc., Nature of the product Maintenance

23. • Types Design capacity: Maximum output that can be possibly
attained
Effective capacity: Maximum output considering all factors Production
capacity: Maximum rate of Production Maximum capacity: Maximum
output that a facility can achieve under ideal conditions

24. • Calculating Equipment Effectiveness
Measures how much of the available capacity is actually being used:
Measures effectiveness Use either effective or design capacity in
denominator Actual Output Effectiveness = (100%) Capacity

25. • Example : In the bakery example the design capacity is 30 custom
cakes per day. Currently the bakery is producing 28 cakes per day.
What is the bakery’s capacity utilization? Utilization = (28/30) * 100%
=93%

26. • Example : In the bakery example the design capacity is 30 custom
cakes per day. Currently the bakery is producing 28 cakes per day.
What is the bakery’s capacity utilization? Utilization = (28/30) * 100%
=93%

27. • Types of Capacity Plans
Long Range Capacity Planning Location Decisions Technology
decisions Developing new production line / product Investment
Decisions Short Range Capacity Planning Inventory planning and
fluctuations Scheduled maintenance Hiring HR Working capital
requirement

28. • Capacity Planning Process
Step 1: Identify Capacity Requirements Step 2: Develop Capacity
Alternatives Step 3: Evaluate Capacity Alternatives Step 4 : Select the
appropriate Capacity Alternate

29. • Evaluate Capacity Alternatives
The methods available to evaluate the worthiness of the projects are
Present Worth Annual Equivalent PW= Capital Investment + (Annual
Revenue * PV of A) AE = (Capital * PVA)+(Salvage*PVA)+ Return