Grade 12 06.12.2024 Accounting issue

Calculate Days Sales of Inventory (DSI) for 2022. Based on the financial data, calculate Days Sales of Inventory (DSI) for 2022.

• 102.2 days

• 100 days

• 80 days

• 95 days

Calculate Days Sales of Inventory (DSI) for 2023. Based on the financial data, calculate Days Sales of Inventory (DSI) for 2023.

• 125 days

• 130.4 days

• 127 days

• 135 days

What is the significance of the increase in DSI from 102.2 days (2022) to 130.4 days (2023) for Global Apparel Ltd.'s financial performance?

• The company can improve liquidity by selling inventory more slowly.

• The company has more capital tied up in unsold inventory, reducing liquidity and increasing storage costs.

• The company has reduced inventory costs as products sell quickly.

• The company increases profit by holding inventory longer.

In the fashion industry, what risk is associated with high DSI?

• Risk of obsolescence, leading to decreased value or markdowns

• Risk of high demand exceeding inventory

• Risk of increased labor costs

• Risk of rapid revenue growth

High DSI directly impacts which department in Global Apparel Ltd.?

• Inventory Management

• Human Resources

• Accounting

• Product Development

How can high DSI affect retailers?

• Retailers may not receive new products on time, affecting customer satisfaction.

• Retailers may increase orders due to constant stock availability.

• Retailers may increase product prices due to surplus stock.

• Retailers are unaffected by high DSI.

Which recommendation can help Global Apparel Ltd. reduce DSI?

• Use data analytics for accurate demand forecasting

• Hold more inventory to ensure constant availability

• Increase product prices to boost profit

• Reduce orders from suppliers

How does using data analytics for demand forecasting affect DSI?

• Increases DSI as the company holds more inventory

• Decreases DSI as inventory aligns closely with actual demand

• Has no effect on DSI

• Increases DSI as the company needs to order more stock

What is the main benefit of using data analytics in demand forecasting?

• Helps increase product prices

• Helps accurately determine demand and avoid excess inventory

• Helps expand production quickly

• Helps reduce labor costs

What information can data analytics provide to assist in demand forecasting?

• Production time

• Seasonal purchasing trends and historical sales data

• Warehouse rental costs

• Maintenance costs