Practice Case Study 2: Retail Inventory Optimization - 18.5.2 | 18. Data Science for Business and Decision- Making | Data Science Advance
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18.5.2 - Case Study 2: Retail Inventory Optimization

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is demand forecasting?

💡 Hint: Think about how businesses predict what customers will want to buy.

Question 2

Easy

Define overstock.

💡 Hint: What happens when items are not sold quickly enough?

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the primary goal of demand forecasting in retail?

  • To increase stockouts
  • To optimize inventory levels
  • To increase overstock

💡 Hint: Consider the purpose of predicting demand.

Question 2

True or False: Linear Programming can assist in making inventory management decisions.

  • True
  • False

💡 Hint: Think about how businesses make mathematical decisions.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

A retailer currently has 1,000 units of a product that they expect to sell 800 units in the next quarter. If the holding cost per unit is $5 and they want to reduce overstock by 15%, what will be their new target inventory?

💡 Hint: Calculate how much inventory is unnecessary using the excess from the forecast.

Question 2

A grocery chain uses LP to determine the optimal order quantity for 4 products with varying sales trends. How can you structure their LP model to minimize costs while maintaining stock availability?

💡 Hint: Think about each product's demand and costs to structure the LP equation effectively.

Challenge and get performance evaluation