DEMAND FORECASTING IN SUPPLY CHAIN. Role of forecasting in supply chain. FACTORS OF FORECAST FORECASTING METHODS:

1. Given to:
SIR ZAFAR SIDDIQUIE
Presenters:
MARYAM QAZI
VARDA SHAIKH
HIBA SHAIKH
CHP#7 DEMAND FORECASTING
IN SUPPLY CHAIN

2. Role of forecasting in supply chain
• Forecasting is the basis for all strategic & planning decisions in a supply
chain.
• Some decisions that utilizes forecasts & can be enhanced through
collaborative forecasting among supply chain.
• These decisions fall into following categories:
1. Production: It includes scheduling, inventory control, aggregate planning
& purchasing.
2. Marketing: It includes sales, promotion, advertizing & new product
introduction.

3. 3. Finance: Plant or equipment investment
& budgetary planning.
4. Personnel: Work force planning, hiring &
layoffs.

4. Characteristics of forecast
Forecasts are always wrong .
It should includes:
• expected value of forecast
&
• measure of forecast error
Student Biryani

5. Characteristics of forecast
Long-term forecast are usually less accurate
than short-term forecast.
Pizza hut always introduce their deals in short
term forecast.

6. Characteristics of forecast
Aggregate forecasts are usually more
accurate than disaggregate forecast.
•Product quantity.
•Sales forecast.
•Time.
Samsung.

7. • Definition: Assessment of current and future
economic performance in individual countries.
• Example: Boulevard mall now in Hyderabad.
1. STATE OF ECONOMY
FACTORS OF FORECAST

8. 2. PLANNED PRICE DISCOUNTS:
• To sell in high quantities.
• EXAMPLE: Careem promo codes for
special events (Eid codes).

9. 3. ACTION COMPETITORS HAVE TAKEN:
• Keep an eye on the competitors so can
take better actions than them.
• Example: Uber Vs Careem
Charges
Rs.13 per km
Charges
Rs.18 per km

10. FORECASTING METHODS:
1. Qualitative:
• Market Research-obtain information to make
accurate predictions about buying habits of a
customer.
• Through-surveys and interviews.
• Example-final year group project.

11. 2. TIME-SERIES:
• Quantitative forecasting technique.
“Data gathered over time to identify trends”.
• Example- Careem expanding in Islamabad.

12. 3. CAUSAL
• Cause-and-effect relationship.
• Example-Summer clearance sale 2017.
• Discounts stimulates sales.
Discounts
Sales

13. 4. SIMULATION
Creating a model to understand the actual
system.
• Example-prototype of final year group
project.

14. THANK YOU