How Microsoft helped this bar figure out that vodka was costing it a fortune
Do you have any idea where your business makes and loses money? Would you like to find out?
Take a bar. If your business is serving drinks, you have to expect that the odd bottle will get broken or that bar staff will pour extra generous measures -- because the stronger the drinks, the bigger the tips. But suppose you could actually see what that means to your bottom line? If you could look at the data and work out which are your most profitable products and what costs you money, could you find a way of maximizing profit, minimizing loss while still keeping customers and staff happy?
For one Seattle bar that tried out an early version of Microsoft's Power BI cloud business intelligence service, the discrepancy between the alcohol bartenders were getting through and what they were charging for turned out to about $5,000 a month. The owner wasn't surprised; that's par for the industry. But then he found something that did surprise him: When he looked at sales and losses in more detail using Power BI's Q&A natural language tools for exploring data, the problem wasn't evenly spread across the 139 different kinds of alcohol in stock. Almost half of the missing money came from vodka sales, and of the six vodka brands the bar serves, just two brands -- Crown Russe and Stolichnaya -- were responsible for the majority of the losses.
And those two brands were making a big difference. The bar sells a lot of Bud Lite and even more vodka but the vodka was only making half as much profit as the Bud.
If you own a bar, you can count the bottles of beer and wine to see what you're serving and what you're losing. But when it comes to spirits, you have to weigh the bottles on a very precise scale, calculate the viscosity for that type of liquor and turn it into the ounces left in the bottle. It's a lot of work for everything you have on the shelves so this bar used a weekly inventory service that did the weighing. But when he saw how much money he was losing on just six bottles, the owner bought his own scales and started weighing the vodka every night and putting the results in a CSV file; he saved those in a folder that Power BI's Power Query tool was set to import and clean up automatically.
Then he used Q&A again to compare that to the employee records showing who was working the bar each night. He wanted to see how close each of them was getting to the 1.5 ounces of vodka that makes for the Goldilocks of cocktails; not too weak and not too strong.
Q&A lets you type in queries in close to normal English and automatically displays the results in the most relevant chart type. That made it clear that one bartender who had been working at the bar for a while was putting an average of 1.7 ounces in his cocktails, making strong drinks that bought in big tips, but costing the bar money. Another bartender was new and was only pouring 1.4 ounces each time -- and while they save money, those weaker drinks are likely to send customers to another bar.
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