Video presentation demand management (Assessement 2_ Intro to logistics and scm omgt2085) 1b pdf

VINAMIT-JACKFRUIT CHIPS
LINE SUPPLY CHAIN PROCESS
01

Demand Management

02
Group 2Team 2

Procurement

03

04
05

Packaging

Distribution

Warehousing


Vinamit Company
background
Established in 1991; Chairman Nguyen Lam Vien, with
processing plants and farms in Binh Duong province
One of the leading companies in the agricultural food
processing industry in Vietnam

Since 2005, received the reward of “ The best of

Vietnam’s goods by Vietnamese consumers"
Continually expands to ASEAN countries, China, and
even difficult countries such as Japam, Europe and the
United States





DEMAND
MANAGEMENT


What is demand management?
Forecasting, planning for, and managing the products/services
demand
Balancing the customers' requirements with the company’s
capabilities of the supply chain and financial status
Forcing the supply chain to collaborate on activities related to
the
flow of products/services, information, and capital.
Vinamitproactively set up close collaboration
among management, inventory, supply chain,
and their marketing- sales teams.


1st MANAGERIAL RESPONSIBILITY

DEMAND FORECASTING
Demand

Forecasting

Reviewing & Analyzing historical and realtime sales data seasonal or economic trends
Researching and analyzing internal and
external
demand-influenced factors
=> Proving accurate estimation and prediction of
customers’ demand for future sales preparation.

Use skills & experience, and information
gathered from the product

Quantitative
Methods



Use time series forecasting
data), and analytical tools
predictions for future

(historical
to create



Analyze
customers’
demand
volatility

based on forecasting factors: random
variations, trends, seasonal patterns, and
business cycles.

Qualitative
Methods

Statistical
Forecast

Used when Vinamitaims to
bring its jackfruit chips
widely to new markets
with minimal past data
available to analyze.





Vinamit Demand forecasting case
Main targeted customers: young people and foreign visitors.
The changing in young customers eating traits that increase
packaged food and fruit snacks
The peak time period for tourism and foreign visitors is 6 months (Spring
to Summer)
=> Based on previous young traits changes (historical data), Vinamit forecasts
for increasing jackfruit chips supply in the future periods for 6 months
=> Based on peak time tourism in the past => increasing sales in 6 months
(Spring- Summer)

Increasing demand for tropical fruit snacks in China and Europe since 2018


Their changing eating habits (modern trends) => rising demand for healthier snacking
options in Europe and a decrease in consumption of sweet snacks with high calories.
Tropical fruit chips (jackfruit, banana, pineapple) exported to Europe
increased by 7%.


=> Based on historical data (2018), Vinamit can forecast to increase sales and exporting
volume in thenext period:1-2years.


An accurate demand forecasting drives
What Vinamit’ssupply

chain can receive

Provide predictive foundation background
and throughout demand understanding

01

Optimize and synchronize almost crucial supply chain
stages of the dried jackfruit line.

02

VALUE
03

04

Help supply chain schedules able to work on time, in
full, maximize SC efficiency, and optimize marketing
and sales activities for more profit gains.

Minimize stock-outs & reduce the excess inventory

and warehousing costs in case of oversupply of stock.

Help demand management proactively

influences demand.

Help demand management smoothly

communicates with other stages


KPI

accuracy
(FA)
Demand forecasting

Gains

❑

Having
benchmark for Vinamit accurately its
a
predictions for demand and sales.

❑

Be more confident to use the forecasts in reporting and
make the next short-term forecast demand

Forecast accuracy (%) ={1 –[Absolute
value of (Actual sales for time period –
Forecast sales for same time period) /
Actual sales for time period]} x 100
MEANING

Calculate the deviation of the actual

demand from the forecasted demand,

check forecast accuracy before
reporting for plans.

❑

Benchmark

❑

❑

Newly-launch product => Minimal historical
data: Forecast accuracy from 80% => Good
Large variations due to weather, seasonal,
competitor promotion => FA is recommended
from 90-95% for a useful forecasting
Finally, product lines with a long sales history
like dried jackfruit of Vinamit should target an
FA of 90% or better to ensure an exact forecast.








KPI WORKS
Good or not

Forecasting Accuracy (FA) KPI

Shortcomings
❑ Not 100% accuracy
❑ Use to calculate in the short-time period
❑ Easy prone to error when demand fluctuates when the actual sales
are affected by unexpected variations like Covid-19, or economic
crisis.
=> Provides a fragmented, short view of forecasting accuracy in
different periods, difficult to plan for the long term

Recommendation

Have the connection between forecasting accuracy of the
different periods to have a comprehensive view of demand
inlong run.








2nd MANAGERIAL RESPONSIBILITY

DEMAND PLANNING
Create and execute strategic and operational plans across the
supply chain in order to meet customer demand.
Collaborate with the Demand Forecasting Team, Sales and
Marketing, and Financial department to facilitate balanced plans
for S&OP processes.
Manage and communicate with other SC departments for on-time
and in-full supply.


Demand Planning

What Vinamit’ssupply

chain can receive

01

02

Helps track and maintain supply levels
Ensure Vinamithas enough supplies to meet actual

demand.
Balance supply-demand status

Drives transparency in volumes and healthy stocks at
the right time for future sales match through practical
planning strategies

VALUE
03
04

Help Demand managers effectively communication
with other stages to prepare for their processes

Increase efficiency, probability, and customer
satisfaction in production
Reduce unexpected operation costs.

▪

▪

Examples
Minimize excess storage
costs

Helps with logistic planning


Demand Planning KPI
Mean Absolute Percentage Error (MAPE)
Forecasting Error = Actual sales –Forecast sales
Mean absolute percentage error = Sum of (Forecast error for the
time period / Actual sales for that period) / Total number of

forecast errors x 100
MEANING
This defines the average of percentage errors (Take

the average of the difference between actual and

forecasted demand as %
❑

Good

❑
❑

The advantage of MAPE is that it relates each forecast error in
different periods to its actual observation.

This accuracy has the advantage of scale
Give a more precise value, take into account every value in list.