{"id":17759,"date":"2023-10-17T12:45:48","date_gmt":"2023-10-17T16:45:48","guid":{"rendered":"https:\/\/d3.harvard.edu\/platform-digit\/?post_type=hck-submission&p=17759"},"modified":"2023-10-17T12:45:48","modified_gmt":"2023-10-17T16:45:48","slug":"fit-facts-flair-and-figures-a-foray-into-stichfixs-data-driven-styling-services","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/fit-facts-flair-and-figures-a-foray-into-stichfixs-data-driven-styling-services\/","title":{"rendered":"\u00a0Fit, Facts, Flair, and Figures: A Foray Into StichFix\u2019s Data-Driven Styling Services"},"content":{"rendered":"\n

The same people who can\u2019t decide whether or not Domino\u2019s is a tech or pizza company will be similarly troubled when they think about StitchFix. StitchFix is an e-commerce company that offers highly-customized styling to men, women, and children. At a high level, the business model works by pairing customers with a (human) stylist who ships them (on a cadence of the customer\u2019s choosing) boxes of hand-picked clothing, footwear, and jewelry that flatter customer\u2019s bodies, meet their needs (clothing for work, parties, exercise, etc), and are affordable. Customers return what they hate and buy what they love. Data is collected and used extensively and in-real-time <\/em>throughout the customer journey.<\/p>\n\n\n\n

StitchFix gathers and uses data implicitly and explicitly, on both the front-end and back-end to efficiently and personally select and send clothing based on customers\u2019 preferences. To cite a small number of examples of how these processes work, from StitchFix\u2019s technical blog<\/a>: (1) Specific data about customers\u2019 bodies, taste in clothing, and price range are acquired through a 15-20 minute survey customer fills out upon making an account. (2) StitchFix algorithms select inventory based on customer\u2019s responses. Stitchfix stylists (who filter the inventory once the algorithm picks it) are paired with customers using a complex algorithm whose inputs include, among other things, the history of relationship between stylist and client and the overlap between stylist and client tastes. (3) StitchFix closely monitors clients\u2019 feedback on stylist selections to iterate for future shipments. (4) Data is constantly collected to optimize shipping routes for clothing.

Example of StitchFix’s data gathering method during new user onboarding:<\/p>\n\n\n\n

<\/p>\n\n\n\n

The result of all of this? A not-so-lean, very mean, personal styling machine! Data is plentiful and cheap, but its utility is not. Deriving value from data depends on both the quantity and quality of data scientists working for Stitchfix. Such experts (who are generally expected to have at least an MS if not a PhD in data science) are in short supply and very expensive.  According to Indeed<\/a>, the average salary for a data scientist at StitchFix is a whopping (but well-deserved!) $240,000 per year. The reason might be found in Anaconda\u2019s recent research<\/a> that 63% of companies surveyed are worried that they won\u2019t be able to find data scientists they need in the future. Of the almost 6,000 employees at StitchFix, over 100 are data scientists<\/a>.  And a lot more than fluency in statistics and Python is demanded of them. According to StitchFix\u2019s blog, data scientists are hired to be lightly-supervised self-starters who are constantly asking and answering questions about how to use data to improve the user experience. StitchFix needs to think about how it will overcome the challenge of recruiting these highly-skilled, motivated individuals in the future.


While people might be the priciest, StitchFix has had to make other, substantial  investments to create a \u201crobust data platform.\u201d Culture and digital infrastructure are critical to the success of harnessing value from data. Eric Colson, the former Chief Algorithms OFficer (yes this is a thing and shows you how seriously Stitchfix takes its data!) argues that the entire organization must embrace \u201cthings like learning by doing, being comfortable with ambiguity, and balancing long- and short-term returns.\u201d It\u2019s unclear how capital is deployed to create a culture like this, but one can imagine significant amounts of time are demanded from leaders across the organization to create it. It serves to note that at StitchFix, data science is an independent department whose head reports to the CEO, a rare division of labor, even in tech companies. Digital infrastructure is more quantifiable. Data scientists as StitchFix have been given access to compute power and cloud systems to support their work. <\/p>\n\n\n\n

It would be irresponsible to conclude this blog post without acknowledging the fact that StitchFix\u2019s performance, at least according to its stock price, is in the gutter. When the company went public in 2017, it was trading at ~$15 per share, and now it is down to ~$3. This disappointment can be attributed to several factors-including the company\u2019s over-optimistic growth projections, TAM, a declining macro-environment, the rollout and then reversal of a cannibalizing line of business. But data-or its misuse-is worthy of blame as well. The Motley Fool\u2019s analysis<\/a> blames the company\u2019s over-reliance on data and algorithms, instead of stylists. (These algorithms apparently recommended sweaters to people in July.)  Stitchfix hasn\u2019t quite struck the right balance (yet) between maximizing human and technical capabilities.

Nothing kills (or makes) dreams like data.


Sources:<\/p>\n\n\n\n

https:\/\/multithreaded.stitchfix.com\/blog\/2019\/01\/18\/fostering-innovation-in-data-science\/#:~:text=At%20Stitch%20Fix%2C%20we%20have,millions%20of%20dollars%20in%20benefits.<\/a><\/p>\n\n\n\n

https:\/\/algorithms-tour.stitchfix.com\/#recommendation-systems<\/a><\/p>\n\n\n\n

https:\/\/multithreaded.stitchfix.com\/career\/data-scientist\/<\/a><\/p>\n\n\n\n

https:\/\/www.indeed.com\/cmp\/Stitch-Fix\/salaries\/Data-Scienti<\/a>

https:\/\/know.anaconda.com\/rs\/387-XNW-688\/images\/ANA_2022SODSReport.pdf<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"

Stitchfix, a personal styling company that relies on data and algorithms to make recommendations to people, has yet to properly balance its use of human capital and compute power.<\/p>\n","protected":false},"author":19399,"featured_media":17766,"comment_status":"open","ping_status":"closed","template":"","categories":[],"class_list":["post-17759","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/competing-with-data-4\/","yoast_head":"\n\u00a0Fit, Facts, Flair, and Figures: A Foray Into StichFix\u2019s Data-Driven Styling Services - Digital Innovation and Transformation<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/fit-facts-flair-and-figures-a-foray-into-stichfixs-data-driven-styling-services\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u00a0Fit, Facts, Flair, and Figures: A Foray Into StichFix\u2019s Data-Driven Styling Services - 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