Sushi Bar

Pull up a seat and relax. Tonight we are proud to offer some of the freshest data around, expertly crafted by our master analysts. For your first course this evening, we have a refreshing maki roll featuring your dining preferences, lifetime value, and demographic data.  Please enjoy...

Like chefs at a sushi bar, restaurateurs can slice, dice, and roll data in a variety of ways in order to deliver value to guests and increase profitability at the same time. In this post, I will examine one of the most basic yet powerful types of data analysis - customer segmentation - and explain how it can be applied within the context of the restaurant industry.

Customer segmentation provides business owners with a means of better understanding their customer base in order to develop targeted products and services for them. Of course, such an undertaking relies heavily upon data analysis, which is perhaps one of the reasons why it is so prevalent in the consumer packaged goods industry. Yet despite what restaurateurs may believe, they too possess the data to conduct such an analysis. Demographic and preference data for guests can easily be compiled from internal databases or reservation agents such as Opentable. Spend data, contained within POS systems such as Micros, can be linked to particular guests through the use of unique identification numbers. By fostering communication between customer databases and POS systems, restaurateurs can not only understand who is patronizing their establishments, but also how much they are spending.  

The information gleaned from a customer segmentation analysis can be used in a variety of ways. For instance, by conducting a statistical analysis of guest preferences, restaurateurs may be better able to develop products and services to meet guest needs. By understanding the lifetime value of guests, promotional offers can be developed to encourage additional consumption. Clearly, the data housed in restaurants' walk-ins has great potential. Yet it is up to the master chef, the analyst, to turn it into a delicious dish.    

Caviar in the Walk-In

For those of you for whom my last post piqued your interest, here's an article that you might find particularly interesting.  Writing for the Harvard Business Review, Gary Loveman, CEO of Harrah's Entertainment, describes how investing in data mining produced dividends for his company far beyond that which could have been generated through elaborate casino design a la Las Vegas.  Using a variety of analytical techniques, Harrah's was able to determine who its most profitable customers truly were and how they might be able to better target and serve those individuals.  Although Harrah's initial investment in technology was large (but probably nothing compared to building a replica of Venice's canals), the knowledge gained from its implementation is without measure.  

And so I ask you this - If gaming companies have found data mining to be a profitable endeavor, why doesn't the restaurant industry give it a try? 

The Walk-In

So where is all that fresh, nutritious data sashimi kept? Why in the walk-in of course!  For those in the restaurant industry, you know this feature well -  a cold metal box in which all items requiring controlled temperatures are held. For those who are not in the industry, I'll cut to the chase - it's a big refrigerator. And regardless of how many actual walk-ins a restaurant may have, there is always one that management forgets - the data walk-in.

In my previous discussion of raw data, I noted that restaurateurs have myriad opportunities to collect data on customers and their preferences. Yet far too many simply stop there, gathering data and letting it spoil on the shelves of the walk-in. Why is it the case that so few restaurants fully exploit the power of their data? In this post, I'd like to explore that question and offer some practical suggestions to restaurateurs who are scared to open that heavy, metal door.

The very nature of the restaurant industry makes data mining a difficult task. During the course of a typical day, managers are inundated with paperwork, preparing for service, or facilitating operations on the floor. Thus, there is little time for data analysis, despite the fact that it would likely contribute to the bottom line. And even if time were not of the essence, training most certainly would be. As digital divide exercises have demonstrated, it is not sufficient to simply provide individuals with IT; to truly benefit from such an investment, users need to receive both adequate training and support. 

So what are restaurateurs to do? In my opinion, the answer is fairly simple - hire an office assistant. Managers should be focused on creating value for the company; therefore, they must concentrate on strategic, as opposed to administrative, issues. Yet in order for them to sufficiently attend to these issues, they need both time and training. By hiring an office assistant, a restaurateur demonstrates his or her commitment to spending management's time wisely.  Of course, hiring a new employee is a costly endeavor, especially in this economy. But not hiring an additional employee might cost even more if only restaurateurs considered the value of data that had spoiled under their noses, wasting away, on their walk-in's shelves.

Data Sashimi

Despite the abundance of data sashimi in restaurants, few establishments harness the power of raw data effectively.  Failure in this regard can be attributed to a number of causes; ineffective collection mechanisms and inappropriate analytic methodologies provide but two examples. Because the process of data analysis involves several steps, it is far too broad to investigate in a single post.  So let's start at the beginning -- data collection at the individual restaurant level.

From the moment a guest enters a restaurant, the data collection process begins.  Formalized collection may occur by requiring walk-in guests to provide their full names and informal collection may take place through observations of a guest's behavior.  Further data becomes available once guests are seated and have ordered their meals, which are typically entered into POS systems such as Micros. Throughout the dining experience, severs and managers may speak with guests and inquire about the quality of their experience, providing additional data pertaining to a number of critical metrics (e.g. food quality, service quality, atmosphere...).  At the conclusion of the meal, guests may have the opportunity to complete a comment card, enabling the restaurant to capture key insights into meal quality as well as contact information that can assist with targeted marketing efforts.  

Clearly, there is plenty of data to be captured from a single dining experience.  And fortunately for restaurateurs, much of it is automatically collected through systems such as Micros.  Yet opportunities exist to further refine collection processes, particularly in terms of observational data and contact information.  Throughout the course of a given service, both servers and managers will likely observe a number of issues related to both food and service quality. Instead of simply taking note of these issues, staff should formally record, code, and track them through a database.  Furthermore, individual guest preferences (an issue in of itself) that are observed by staff should be recorded and included in guest notes.  While tempting to ask for upfront, contact information should be obtained at the end of the meal; walk-in guests are likely to be irritated that they need to provide personal information before even being sat for dinner.  True, response rates might be lower at the end of the meal but at least you don't risk souring the diner's experience before it has even begun.

The very nature of service industries make data collection tricky. Since customers act as co-producers in restaurants, the potential to negatively impact their experience by forcibly extracting data from them is omnipresent.  Thus, restaurateurs must carefully balance their desire to obtain useful data with their need to provide an excellent experience for their guests. By effectively utilizing all resources at their disposal (e.g. systems and personnel), restaurateurs can ensure that their data sashimi is as fresh as can be.       

Tasting Menu

When I am lucky enough to frequent a high-end restaurant, I always opt for the tasting menu. My fellow diners are often quick to point out the consequences of such a decision -- the necessity of full table participation, the inability to select specific dishes, and the inevitable high price point.  Yet despite the accuracy of these criticisms, I am rarely swayed in my conviction. Why might you ask?  When I am lucky enough to frequent a high-end restaurant, I want to try as much as humanly possible.

Consider this blog to be your tasting menu.  Throughout the course of this semester, I will offer my insights into the future of the restaurant industry with a particular focus on issues related to the collection and analysis of data. Participation is not required but certainly encouraged and yes, substitutions are available.  On behalf of all of the wonderful people who have helped to shape my thinking, welcome to my kitchen.

And for your amuse-bouche this evening...