Businesses selling clothing and other fashion items face obstacles in trying to forecast how much product to order: tastes and...
GMAT Information and Ideas : (Ideas) Questions
Businesses selling clothing and other fashion items face obstacles in trying to forecast how much product to order: tastes and styles change quickly, while manufacturing clothing takes a significant amount of time. Researchers Youran Fu and Marshall Fisher have found that combining sellers' own data with information gathered from social media can dramatically improve the accuracy of such forecasts—by 24 to 57 percent in the cases they directly studied. Better predictions mean demand is easier to meet without retailers becoming overstocked.
Which choice best states the main idea of the text?
Using multiple data sources can enhance the ability of sellers in the fashion industry to anticipate demand.
Social media is revolutionizing how both sellers and researchers view the fashion industry.
Becoming overstocked is the main preoccupation of sellers trying to forecast demand for fashion items.
Retailers can use their own data to accurately predict how tastes and styles are evolving.
Step 1: Decode and Map the Passage
Part A: Passage Analysis Table
| Text from Passage | Analysis |
|---|---|
| 'Businesses selling clothing and other fashion items face obstacles in trying to forecast how much product to order: tastes and styles change quickly, while manufacturing clothing takes a significant amount of time.' |
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| 'Researchers Youran Fu and Marshall Fisher have found that combining sellers' own data with information gathered from social media can dramatically improve the accuracy of such forecasts—by 24 to 57 percent in the cases they directly studied.' |
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| 'Better predictions mean demand is easier to meet without retailers becoming overstocked.' |
|
Part B: Passage Architecture & Core Elements
Visual Structure Map:
PROBLEM: Fashion forecasting challenges
SOLUTION: Research shows multiple data sources improve accuracy
BENEFIT: Better demand management, less overstocking
Main Point: Research shows that combining multiple data sources (sellers' own data plus social media information) can significantly improve fashion retailers' ability to forecast demand.
Argument Flow: The passage establishes the forecasting difficulty in fashion retail, then presents specific research demonstrating how combining data sources dramatically improves prediction accuracy, and concludes by explaining why this improvement matters for retailers.
Step 2: Interpret the Question Precisely
What's being asked? The main idea of the entire text
What type of answer do we need? The central message that captures what the passage is fundamentally about
Any limiting keywords? 'Main idea' means we need the overarching point, not a supporting detail
Step 3: Prethink the Answer
- The correct answer needs to capture that this passage is fundamentally about improving forecasting in fashion retail
- It should mention the use of multiple data sources (not just one type)
- It should mention the fashion/clothing industry context
- It should mention the improvement in forecasting or predicting demand
- The right answer should combine these elements to show that using different types of data together helps fashion businesses better predict what customers will want
Using multiple data sources can enhance the ability of sellers in the fashion industry to anticipate demand.
- Captures the core finding about 'multiple data sources' (sellers' data + social media)
- Correctly identifies the fashion industry context ('sellers in the fashion industry')
- Focuses on the key benefit ('enhance the ability...to anticipate demand')
- Matches our prethinking perfectly - it's about combining different data types to improve forecasting
Social media is revolutionizing how both sellers and researchers view the fashion industry.
- Focuses too narrowly on social media as the main point
- Makes social media seem like it's 'revolutionizing' the entire industry and research perspective
- Misses that the passage is specifically about forecasting accuracy, not broader industry transformation
Becoming overstocked is the main preoccupation of sellers trying to forecast demand for fashion items.
- Takes a supporting detail (overstocking concern) and makes it the main focus
- Suggests overstocking is the 'main preoccupation' when the passage presents it as just one consequence of poor forecasting
- Students might choose this because overstocking is mentioned and seems important, but it's actually just explaining why better forecasting matters
Retailers can use their own data to accurately predict how tastes and styles are evolving.
- Only mentions sellers' 'own data' and ignores the crucial social media component
- The passage specifically emphasizes that combining multiple sources is what creates the improvement
- Misses the key research finding about the power of using data together