Big data is on everyone’s lips these days, and every conference has a track or two dedicated to it. As a restaurant owner, you know you probably should pay attention and even do something with it, but where do you start or how do you make sense of it?
This is a short guide to give you some pointers and hopefully get you started on this data journey.
You have two types of data:
Structured Data: This type of data comes from the different systems you use internally. If you haven’t already explored the systems, most will provide ready-to-consume analytics and reports. Check with your vendors if you are unsure.
The most common sources of structured data in your restaurant are:
- Your POS: What menu items are selling, who is buying them and how much they are spending
- Your accounting software: How much you spend on food, on rent, on electricity, on labor
- Your suppliers: How much you spend on every item offered in your menu
- Your reservation system: Repeat customers, customer preferences, reservation trends and projected traffic
- Your kitchen system: What are the most commonly ordered dishes, menu trends, labor cost per menu items
Unstructured Data: This type of data comes in many forms and is far more difficult to interpret and work with. The common sources for
this data are:
- Social Media: Likes, comments and feedback from guests, Tweets, Instagram and Facebook posts
- Customer profiles: These would probably come from your reservation management system. You can get an understanding of the profile of your typical guest
- Weather, season, traffic patterns
While unstructured data is not as clear-cut, making it more complex to interpret than structured data, you will still need both. Mostly because structured data will help you identify what is problematic, while unstructured data will tell you why you may have a problem. So for instance, your sales seem to drop every once in a while for no apparent reason, but once you start tracking weather, it seems like it rained on those days. If half of your restaurant consists of outdoor seating, it would be pretty obvious since rain can encourage customers to stay home and order food instead. Track and understand both types of data.
Each data source comes with its own characteristic and – yes – sometimes flaws. While it shouldn’t deter you from using them, it’s good to
aware of these seven data characteristics:
- Volume: Getting data is great; getting too much data can be overwhelming. Learn how to attain value from your data and aggregate
at a level that makes sense. For instance, you can get a better understanding of patterns from weekly reports than daily, since daily can
greatly day by day.
- Velocity: Circumstances change and what was true yesterday might not be tomorrow. Also, there are ever-increasing sources of data. As a result, new data are created at an exponential speed, and it is important to be able to process them in a timely manner or they quickly become obsolete.
- Variety: Data come from many sources, in many shapes and forms. This is especially true when it comes to unstructured data, and 90% of data generated today is unstructured. Being able to interpret and integrate data is a challenge that shouldn’t be underestimated.
- Variability: Meaning changes depending on context, and that is also true for data. A poor sale day on a sunny day may be a good day on a rainy day. Data can take different meanings based on outside context.
- Veracity: Data has value only if it is accurate. Make sure you are working with valid data.
- Visualization: The human brain is built to detect visual patterns. A bunch of numbers on a spreadsheet is harder to decipher. Put the data on a graph to be able to interpret it faster.
- Value: The value of data is largely underestimated until you figure out how to make it work for you so you can gather incredible insight about your business.
Predict demand and plan accordingly: Based on historical data, stock perishables based on what customers will order as influenced by
weather, outdoor temperature, season, holiday.
Drive thru: Change the digital menu items depending on the line. When the lines are long, foods that are quick to prepare are displayed first. When lines are shorter, it high margin items are displayed first.
Wow your guests: Know who they are so that the next time they come, they won’t have to remind you of their allergies or of their table preference.
Server data: Find out which servers are pushing high margin items, which server is always late, which server has lower tips, etc.
POS Data: Find out which item is not selling and replace it.
Social media: Get raw feedback about the whole customer experience.
The list can go on and on, but this should show you the importance of data for your business.
Big data is a big word and you should start small (pun intended). But by progressively becoming more familiar with the data available to you, you can unlock many opportunities, discover small changes with larger impacts, and learn more about how to make your restaurant a great success story.
by Marylise Fabro
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