A few months back we teamed up with Jason Strashek, the founder of Avanti, to discuss Starbucks and the future of online ordering and delivery. Our conclusion then was, given the problems with Starbucks’ online ordering rollout, they had trouble running basic A/B tests and using data in any meaningful way.
Business Insider validated our conclusions with an expose on Starbucks from their employees’ perspective. Some of it gets a little political but we’ve extracted the relevant content here.
Nothing gets cleaned. Nothing gets stocked. We’re getting screamed at by customers for not being fast enough, so we try to go fast, and we mess up the money, or we mess up the drinks, and then we get yelled at for messing up the money and messing up the drinks. It’s all incredibly tiresome. Just one more person on the floor in the afternoons and evenings would be incredible. …
There is no customer connection when we’re as busy and understaffed as we are. Again, put another person on the floor, and we can talk. I’ve had people call the store to complain that we seemed rushed and upset. The stress is overwhelming. A four-hour shift is too exhausting at this point, because there’s nobody to help us.”
— A current Starbucks employee
It sounds like there’s a chronic understaffing problem doesn’t it? Would it surprise you that the same company that can’t predict online ordering volume is having difficulty forecasting demand and staffing accordingly?
The article then goes one level deeper when it mentions…
Starbucks leaves most staffing decisions in the hands of store managers. According to the company, regional leaders didn’t see major issues last summer, and haven’t seen the need for changes beyond the regular course of business over the last year.
This is a HUGE problem. First, machines need to be writing optimum schedules when possible. Not only does machine learning increase revenue and profit by aligning labor hours with predicted demand, it can optimize each employee to the right shift, driving even more revenue based on behavioral patterns.
Second, brick and mortar needs to be about experience. Managers should be encouraging their employees to build better relationships with customers which drive increased check averages via upsells. This is a way better use of management time than writing mundane, and suboptimal, schedules.
The entire point of technology is to automate the mundane parts of the business so your brand ambassadors (i.e. employees) can build differentiated experiences for customers. Competing on solely cost and convenience has proven a death sentence for all retailers but Amazon, and a few of the brick and mortar incumbents are learning that they need to focus on the customer experience to survive.
Take a look at Best Buy, whose share price shot up by 20% after its latest earnings. Best Buy realized that it needed a tighter integration with ecommerce and that it must emphasize its differentiation: the customer experience. By working with Google, Samsung and Amazon (we know, ironic) it created customer experience zones where consumers could learn about new products in-person and buy the product on the spot. Another way to think of this value is like this:
Imagine you’re in the market for a TV. You have a smart home and you’re really unsure about TV integration. You spend considerable time reading reviews online and ultimately settle on a model. You buy it but it doesn’t work as expected. Now you have to ship the TV back and start all over again.
If you could walk into a Best Buy and have a conversation with a knowledgeable sales person, how much time did you just save? And how much is your time worth? This is the sort of differentiation that brick and mortar needs to consider if it wants to survive.
But we get that not of all them will make it through the transition. Food service has been mostly insulated from the cannibalization of online sales because food prep has to be local if it’s to be fresh. But don’t think there won’t come a day when faceless boxes maximize robotics and output acceptable food orders as quickly and as cheaply as possible. It’s then that Starbucks will really look short sighted for its lackadaisical approach to data.
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