Back of House USA was founded on November 22, 2017. Rodney McLeod Jr. of the Super Bowl Champion Philadelphia Eagles tapped Sir Kevin James, designer and owner of ShopCore (4 locations in DC Metropolitan Area) and his best friend Jonathan Mason, a Wall Streeter and hedge fund founder, to create a progressive men’s streetwear store that provides high-fashion to an area skipped over by brands for places like LA and NYC. BOH struggles with inventory management and digital sales. BOH is located in Pentagon City Mall, a Simon Mall next to the Pentagon, but the founders know that Brick-and-Mortar retail stores are failing generally. The founders want to explore the options of machine learning to assuage inventory concerns and promote digital sales. Exploring the journey of CEO Katrina Lake (MBA ’11), one can see how BOH must work hard to obtain the scale necessary to support this endeavor.
- Machine learning is an outlet that, at scale, can revolutionize the order flow of a small retailer by streamlining buying decisions, fortifying trend forecasting, and eventually cutting down on costs.
- The founders are working to identify top talent at HBS to create a strategy for machine learning. One founder invested and worked in a data visualization start-up in DC as well as a Real Estate, machine learning start-up in Durham, NC. In the long run, the company wants to pivot to an influencer/brand centric recommendation engine. Many people don’t actually care what they wear—they only care what their favorite celebrity/influencer and friends wear. We’ll deliver those recommendations through reality-priced brands (Fear of God sells $1,000 T-shirts at times. Kanye West would wear them, but the price point is simply unattainable to John Smith).
- The company needs to establish the cost-benefit analysis of machine learning. There is a tipping point and a ceiling that need to be addressed with machine learning pursuits. The amount of data that is necessary to be successful is astronomical. Also, one must truly understand the personnel needs to create an engine like this. Funding and cost structure will be paramount for BOH.
- The open question for the company is: As we grind towards the efficiency of automation, what is the responsibility of corporations to their employees, the industry, and the communities in which they exist in. BOH has piloted BOHCares, and their mission is very much community focused. Corporations give the empty promise of “jobs coming that we can’t foresee”, but BOH will not hide behind that. They will truly address the corporate responsibility of corporations in the world of Netflix and Stichfix.
Jonathan Mason personal photo library.
BOH is a small clothing retailer in Pentagon City Mall. The founders want to solve inventory management and digital sales issues. The founders have been following the rise of Katherine Lake’s Stitchfix for some time. Jonathan Mason worked with a few Stichfix employees at First.io, a machine learning start-up (also worked with design/machine learning wiz Glenn Vanderburg), but Mason really had to understand SFIX as he participated in the IPO for his hedge-fund. Mason’s fund was allocated shares in the IPO by JPMorgan. This relationship has served as a wealth of knowledge for BOH.
BOH wants to mimic the approach of how to “differentiate ourselves through personalization” by making “unique and personal selections by combining data and machine learning with expert judgement” (Lake 2018). The founders understand the game plan very well based on their experience; however, they are reticent of the high capital intensity and the sheer need for an astronomical amount of data for the algorithm to be useful. It is hard to know—How good is the actual underlying technology? Mason fears that, at a previous start-up he worked at, the machine learning engine was a black box and the fact that everyone had a PHD was an answer for most probing questions.
The market did not react well to SFIX initially. This brought about claims of SFIX being another Theranos, a blood drawing scam that raised millions. The market has since changed its tune and SFIX trades $10 above its initial pricing. Lake states, “Our algorithm helps us see these trends earlier and more accurately, so we can stock inventory more efficiently and be ready for spikes in demand” (Lake 2018). This is at the heart of BOH’s strategy. BOH wants to create a model that promotes fashion tourism around the globe. BOH will pair expert stylists globally, extensive influencer analysis, and machine learning based trend forecasting. Customers will be given recommendations based on their friend’s preferences and the preferences of their favorite influencers—the expert stylists will then scour the globe for cheaper, undiscovered brands that fit the customers need.
The lasting question in conclusion the BOH team must analyze is: If this model became ubiquitous, what jobs arise for retail workers in the future?
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Lake. Stitch Fix’s CEO on selling personal style to the mass market (Links to an external site.)Links to an external site.. Harvard Business Review 96, no. 3 (May/June 2018): 35-40.
Jonathan Mason Personal Photo Library