Further complicating matters is the fact that most foodservice operators feel they constantly swim through a sea of data that’s supposed to help them better manage their business. But making heads or tails of this information can be a full-time job. Focusing on just one or two metrics might not paint an accurate picture regarding business performance. But looking at too many data points can become a full time job, too. So what to do?
Operators today need to take a step back to not only understand what’s important to their business but also determine which tools can help them develop a better picture. And using analytical techniques such as triangulation can be very insightful. And that’s not the old way of running restaurants.
In most restaurants, all the data is connected in one way or another.
Labor as a percent of sales in the restaurant industry represents a staple metric. Everyone at a restaurant company knows what their target levels are and yet, using labor as a percent of sales to measure success is far less effective than it has been. That’s because it hides a lot of sins.
For example, it is common to view labor and food costs independently. But operators who buy a lot of food intend to cook a lot of food and that requires labor. So, in theory, if your restaurant is buying a lot of food then you should have higher labor costs. But is this really true?
If it’s right after a distributor food show and food purchases may be higher than normal, this may not be an accurate measure at times during the year. Evaluating hourly sales against labor may be more accurate. This will lead to better understanding of when waitstaff is not waiting on tables because they’re empty or not being able to service tables at a fast enough rate during dinner, for example.
This is only one example of an analytical approach that will allow you to get a better picture of what’s going on within a restaurant using data the operation already has. Creating parameters of what’s acceptable and what’s not will lead the general manager to be alerted to what falls outside the range and better manage their labor.
If you try to look at all of your data every day, there’s just not enough time. By closely studying the exceptions, or those data points outside the norm, you look for the action items. This will quickly tell you what’s working and what needs work, thus providing a clearer path to success.