{"674283":{"#nid":"674283","#data":{"type":"news","title":"MSA Project Week Provides Students With Real-World Data Analytics Experience","body":[{"value":"\u003Cp\u003EBy Shelley Wunder-Smith\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEvery spring, the students enrolled in Georgia Tech\u2019s\u0026nbsp;\u003Ca href=\u0022https:\/\/www.analytics.gatech.edu\/node\/1\u0022\u003EMaster of Science in Analytics\u003C\/a\u003E\u0026nbsp;(MSA) program participate in a week-long team-based exercise that \u2014 by the project\u2019s end \u2014 has given them real-world experience in solving a data science problem from start to finish.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELast March, a record 21 teams wrangled data, created models, and analyzed findings to provide actionable insights and business recommendations. Project Week presented an opportunity for the students to practice using the academic analytics knowledge from their fall classes. Using a dataset provided by\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/posts\/ablasick_analytics-bestbuy-datajackets-activity-7018728600900169728-T7vQ?utm_source=share\u0026amp;utm_medium=member_desktop\u0022\u003EBest Buy, the 2023 Project Week sponsor\u003C\/a\u003E, the groups were challenged to create a one-week forecast for slow-selling SKUs that prioritized both accuracy and speed.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cBest Buy is one of the largest electronic retailers in the U.S., and they manage their supply chain logistics with data analytics. Specifically, they optimize their supply chain by using a predictive model to determine future sales of every product (SKU). The company has found, however, that some SKUs, such as refrigerators and DSLR cameras, are not predicted well by the model, since sales for them are more sporadic,\u201d explained\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/anamik-jhunjhunwala\/\u0022\u003E\u003Cstrong\u003EAnamik Jhunjhunwala\u003C\/strong\u003E\u003C\/a\u003E, who was part of Data Scientists on Discount, the first-place winning team.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cFor the project, we were asked to design a weeklong predictive model for these problematic SKUs, keeping two factors in mind: 1) low error in prediction, and 2) quick runtime,\u201d Jhunjhunwala continued. \u201cBest Buy gave us sample data to train our model; later, they gave us test data, with which we validated our model\u2019s efficiency. A big part of the project involved using the model to create business recommendations for Best Buy, as well as presenting this advice in a compelling storytelling format.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/paujor?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAACivLVEBXnHatizE6bxnv2MmwRMC9VRCk9c\u0026amp;lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3BA36Yc76qTI2yDVKW6Yei8A%3D%3D\u0022\u003E\u003Cstrong\u003EPaul Jordan\u003C\/strong\u003E\u003C\/a\u003E, a member of the second-place winning Scarce Prophets team, found the Project Week problem to be both engaging and challenging.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cIt was interesting to devise a well-performing model for slow-selling SKUs, in spite of the fact that they are slow-selling,\u201d he said. \u201cBecause of this factor, I initially thought the data would be too scarce to enable us to come up with any good model.\u0026nbsp;We worked on improving the sales forecasting for the slow-selling SKUs; this included analyzing these SKUs and creating several models using various internal and external features to help predict sales.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPrevious Project Week challenges have included anomaly order detection and response (Opex Analytics, an outdoor apparel manufacturing company); creating a predictive algorithm that consistently, quickly, and accurately classifies business according to NAICS codes (Wells Fargo); and identifying features in raw\u0026nbsp;cable spectral data that correlate with degraded service experience and lead to costly customer service transactions (Cox).\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cStudents have told us they like working on challenging problems that can\u2019t necessarily be solved in one week,\u201d said\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/ablasick\/\u0022\u003E\u003Cstrong\u003EAnn Blasick\u003C\/strong\u003E\u003C\/a\u003E, MSA director of career services and Project Week coordinator. \u201cThey also like projects that can be approached from numerous different angles and that require learning new skills, such as NLP [natural language processing], text mining, or predictive modeling.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAs the 2023 Project Week sponsor, Best Buy\u0026nbsp;provided not only the data science problem and dataset, they also offered $5,000 in prize money and team mentors who held \u201coffice hours\u201d during Project Week. The experience was a positive one for the company, and they are returning to sponsor this year\u2019s Project Week.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cBest Buy not only gained fresh perspectives from the students but also strengthened our partnership with the Georgia Tech MSA program, which is an important goal for us as we expand our hiring in Atlanta,\u201d noted\u0026nbsp;\u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/warrenhearnes\/\u0022\u003EWarren Hearnes\u003C\/a\u003E\u003C\/strong\u003E\u0026nbsp;(MSOR 1999, Ph.D. IE 1999), Best Buy\u2019s vice president of data science and chief data scientist, and MSA Advisory Board member.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWhen asked for his main takeaway from the 2023 Project Week, Data Scientists on Discount team member\u0026nbsp;\u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/joshua-j-cantera?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAACjn7gIBnM-82WmBLHXlmm8wbnZseTbCaKo\u0026amp;lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3BcVczjL%2FfR6Cs%2BMptrruY6Q%3D%3D\u0022\u003E\u003Cstrong\u003EJoshua Cantera\u003C\/strong\u003E\u003C\/a\u003E\u0026nbsp;shared, \u201cThis project was a great way to test the skills I learned over the course of my MSA studies. It\u2019s one thing to know how to create a predictive model, but it feels a whole lot better to know that I can make a\u0026nbsp;valid\u0026nbsp;predictive model. I feel much more confident about starting a career in analytics now.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.linkedin.com\/feed\/update\/urn:li:activity:7026291690982301696?updateEntityUrn=urn%3Ali%3Afs_feedUpdate%3A%28V2%2Curn%3Ali%3Aactivity%3A7026291690982301696%29\u0022\u003E\u003Cstrong\u003EWinning Teams\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003E1st Place, Data Scientists on Discount\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoshua Cantera\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJoseph Geibig\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAnamik Jhunjhunwala\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENikolaos Kavouras\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003E2nd Place, Scarce Prophets\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPaul Jordan\u003C\/p\u003E\r\n\r\n\u003Cp\u003ERavi Teja Kolipakula\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESanchita Porwal\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESuraj Shourie\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003E3rd Place, Rehoboam\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EXiang Li\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAjay Majmudar\u003C\/p\u003E\r\n\r\n\u003Cp\u003EKien Tran\u003C\/p\u003E\r\n\r\n\u003Cp\u003EShaojun Zhang\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003E4th Place, Data Super Jackets\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETimothy Cody\u003C\/p\u003E\r\n\r\n\u003Cp\u003EShannon Isaacs\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEmily Velez\u003C\/p\u003E\r\n\r\n\u003Cp\u003EChristina York\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe 2023 challenge was sponsored by Best Buy and focused on accurately forecasting sales for slow-selling items.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"The 2023 challenge was sponsored by Best Buy and focused on accurately forecasting sales for slow-selling items."}],"uid":"36359","created_gmt":"2024-04-19 17:33:19","changed_gmt":"2024-04-19 17:37:38","author":"ecalhoun8","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2023-04-19T00:00:00-04:00","iso_date":"2023-04-19T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"673777":{"id":"673777","type":"image","title":"1675198479758.jpeg","body":null,"created":"1713548232","gmt_created":"2024-04-19 17:37:12","changed":"1713548232","gmt_changed":"2024-04-19 17:37:12","alt":"Project Week Audience","file":{"fid":"257213","name":"1675198479758.jpeg","image_path":"\/sites\/default\/files\/2024\/04\/19\/1675198479758_0.jpeg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/04\/19\/1675198479758_0.jpeg","mime":"image\/jpeg","size":102698,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/04\/19\/1675198479758_0.jpeg?itok=AyqZREwZ"}}},"media_ids":["673777"],"groups":[{"id":"660346","name":"Master of Science in Analytics"}],"categories":[],"keywords":[{"id":"117311","name":"MSA"},{"id":"193648","name":"Project Week"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}