Most popular posts
- What makes great boards great
- The fate of control
- March Madness and the availability heuristic
- When business promotes honesty
- Due diligence: mine, yours, and ours
- Alligator Alley and the Flagler (?!) Dolphins
- Untangling skill and luck in sports
- The Southeastern Growth Corridors
- Dead cats and iterative collaboration
- Empirical evidence: power corrupts?
- A startup culture poses unique ethical challenges
- Warren Buffett and after-tax returns
- Is the secret to national prosperity large corporations or start-ups?
- This is the disclosure gap worrying the SEC?
- "We challenged the dogma, and it was incorrect"
- Our column in the Tampa Bay Business Journal
- Our letter in the Wall Street Journal
Other sites we recommend
Moneyball moment for restaurants
Anthony Lye – President and CEO of portfolio company Red Book Connect – writes in Restaurant Hospitality magazine that widely available mobile and cloud technology have created a “Moneyball moment” for the restaurant industry.
The restaurant industry is having its Moneyball moment. Now that mobile and cloud technology are cheap and widely available, any restaurant can collect, analyze and act on huge swaths of data. Whether you have an Oakland A’s or New York Yankees budget, your restaurant has the ability to cut costs and increase profits by using big data that was invisible until recently.
When you collect in-store, near-store and above-store data, and then connect it all together in the cloud (i.e. on powerful computers located outside your restaurant), you see problems and opportunities that have gone unnoticed. You can begin to change conventional processes that have been killing your profit margins and losing you customers.
In-store data is all the information that comes from your restaurant. Your POS devices, fryers, refrigerators, temperature sensors and labor scheduling system can all communicate useful data. Combine them in the cloud, and you can detect patterns.
For example, one global restaurant brand learned that its fryers were a huge source of inefficiency. Five times per year, when they added new menu items, all 100,000 fryers had to be reconfigured and each required 30 minutes of labor. So, the company developed a way to push new instructions to fryers via the cloud. Now, an IT guy clicks one button, and all 100,000 fryers know how to cook the new menu item. It’s similar to the way Keanu Reeves learns Kung Fu in The Matrix.
By comparison, near-store and above-store data is all the information that originates outside the restaurant and above the restaurants in the company hierarchies. Near-store data includes weather, Yelp reviews, sports calendars, school holidays, special events and any other external data that could affect revenue and therefore the inventory and labor.
Normally, a good manager keeps an eye on the near-store data and adjusts inventory and labor based on experience or gut feel. When you instead connect all this data in the cloud and compare it against sales, both real time and historical, you can build much more efficient labor and inventory models for your restaurant. Instead of guessing, your managers forecast inventory and labor needs with fewer errors, all on their smartphones.
- Untangling skill and luck in sports and business
- The greatest comeback ever and the limits of decision models
- The super-rotation rivalry