01 / 07
Decision Support System

Low Sales.
Expired Products.

How data and decision support can improve inventory management.

02 / 07
The Manager

Defining
the problem.

01

Low sales

Some products are not selling as expected.

02

Excess stock

Unsold products remain in inventory.

03

Expiry risk

Slow-moving products may expire before being sold.

04

Need for DSS

Management needs better data-driven decisions.

03 / 07
The Data Analyst

Understand
the data.

01

Sales volume

Measure how many units are being sold.

02

Inventory level

Track how many units are still available.

03

Sales velocity

Identify how quickly each product is moving.

04

Days to expiry

Find products that need immediate attention.

04 / 07
The Data

Where is the
risk?

Product Sold Stock Expiry
A 90010090d
B 45035030d
C 15045020d
D 10040015d
REMAINING STOCK
A
100
B
350
C
450
D
400
05 / 07
The DSS Expert

Predict.
Identify risk.

01

Sales forecasting

Use historical sales to predict future demand.

02

Expiry model

Combine stock, sales rate, and expiry period.

03

Risk levels

Classify products as low, medium, or high risk.

04

Recommendations

Turn analysis into clear actions for management.

6 / 7
The Decision Maker

Turn insight
into action.

01

Promote

Increase visibility of slow-moving products.

02

Discount

Use targeted offers for products nearing expiry.

03

Reduce orders

Avoid overstocking products with weak demand.

04

Monitor

Continuously track sales, stock, and expiry risk.

07 / 07
The Final Takeaway

Data →
Decision →
Better Inventory.

Sales Data
Forecast
Risk Analysis
Action
the team
The fake market's
employee numbers
Manager - 03 Data Analyst - 04 DSS Expert - 01 Decision Maker/ppt - 02 Presenter - 05