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This Course Is a Mouthful

Here’s an excerpt from the course description for “Predictive Analytics for Planning and Forecasting: Case Studies with Weatherization”:

students will use Excel to apply statistical analysis and weatherization techniques from Planalytics. From this, students will develop more advanced time series skills applied to industry specific case studies

Sounds like an intense course; something you might expect to take if you were majoring in analytics, meteorology, math, or some other technical field.

But here are some other courses offered at this same college:

  • Draping II: Constructed Silhouettes
  • Sewing Techniques I
  • Model Drawing I for Fashion Designers
  • Lifestyle Collection Design

As you may have guessed, this is not your typical liberal arts college; in fact, it is Fashion Institute of Technology (FIT), located in New York City.

If someone told me they were going to FIT, I would expect him or her to be taking courses such as the four courses listed above. But I would have never thought that there was a course titled “Predictive Analytics for Planning and Forecasting: Case Studies with Weatherization”.

But here’s the full course description:

This course is intended for bachelor students interested in investigating the confluence of the art and science in retail planning. With a prior knowledge of merchandising, students will use Excel to apply statistical analysis and weatherization techniques from Planalytics. From this, students will develop more advanced time series skills applied to industry specific case studies with a goal to articulate how these techniques result in stronger sales, fewer markdowns and improved gross margins. Critical thinking will be required to compare and evaluate and report results with and without weatherization. The impact of weatherization on marketing strategies will also be addressed.

So the course seems to fit in quite well with the overall mission of FIT – to prepare students for the world of fashion.

It’s just another example of the reach of data analytics; there doesn’t seem to be an industry that hasn’t embraced the use of statistical techniques to better manage their operations.

What I find most unique about the course, and perhaps it’s because I don’t know much about the fashion industry, is studying the impact of weather on sales of clothing.

I can see courses that analyze the impact of discounts, displays, social media, advertising on sales, but weather seems a little out of the box.

However, according to the Wall Street Journal, weather fluctuations have increasingly been putting fashion designers and clothing retailers on the defensive. Merchandise is often ordered months in advance based on what the weather typically is at that time of year. But when temperatures are different from what was predicted—milder-than-usual winters, cold springs or otherwise inconsistent weather—clothes that are all wrong for the climate stay on racks and get discounted, hurting sales.

So it seems like the course is quite timely, combining hot topics like data analytics and climate change, and applying that knowledge to the world of fashion.

Given my fascination with the weather, it seems like it would be a great course to take.

The only downside – I’m sure I would be the worst dressed person in the class…

 

Published by

Jim Borden

Accounting Prof. at Villanova; happily married for 30+ years; father of 3 outstanding young men; vegan; interests: fitness, creativity, education, blogging, social media.

2 thoughts on “This Course Is a Mouthful”

  1. I’ll bet dollars to donuts these same models could be used for financial markets and fashion fads a like. I remember learning in business school that a product life cycle used the EXACT SAME formula as cell growth (and death) did in a petri dish.




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  2. I agree; to me that’s one of the benefits of a diversified workforce. You put people with different skill sets and different backgrounds on a project, and there’s a good chance they could offer a unique perspective on a problem that may have stumped others.




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