5 steps to turn data you already have into actionable business intelligence

Understanding what happens in a business is important. For a small business going with their gut is often the only option for a business owner. Data takes time to collect, and time to convert into meaningful information.

The goal is to maximize the value of the information already being gathered and convert it effectively into meaningful information to make decisions with. One way to do this is to understand the questions that are important to the business, and understand the places where data may already be gathered as a part of normal processes to ensure this data is consolidated and converted with the lowest impact on everyone within the business.

Follow these 5 simple steps:

  1. Identify the problem
  2. Find the right question
  3. Gather the data
  4. Analyze the data
  5. Convert the data into actionable business intelligence

1. Identify the problem

Start by looking at what don’t you know, but do want to know. Or consider a problem/concern you have.

For a restaurant owner, they may simply want to provide the best quality service to their customers.

2. Find the right question

You can start by looking at who you already have on your staff.

Who is your most effective server, what might you consider as the best indicator?

  • Time guests spend at their table?
  • Size of tip?
  • Additional items sold?

3. Gather the data

How do you gather that information? Start with your register, or Point of Sale system. It is already gathering data on every transaction that runs through your restaurant.

4. Analyze the data

Now we understand the questions and the source of the data we can begin to analyze the data.

  • Table time
    • First, in a basic system the original order may be entered in as the guests first place their order. The system will capture the time when a server first enters the order, until the time the server finally clears out the table’s check. The difference is an approximate amount of time each table spends sitting. Is there a limitation? Yes, if the waiter takes forever to enter the order, and is quick on the check the turn around time will be very low, but that isn’t really what happened, and your guests may be very unhappy. So, it is important to understand the limitations to keep a watchful eye on your servers.
    • What if your system is based upon handwritten checks during the meal and a final receipt at the end? Then look at how many receipts the cashier processed during a shift. You have their time cards. 16 tables in 8 hours, is about 2 tables per hour, or 30 minutes per table. Is this perfect? No, but it can start to give you a better idea. If you notice one cashier has a consistent volume than you can start asking more questions, about their behavior and learn if there is something to either improve on with them, or a lesson to be taught to the other servers.
  • Tip Size
    • Size of Tip is another decent measure of quality of service. Total tips may not be the best indicator either, a $100 tip on a $5,000 table is only a 2% tip. Where a $20 tip on an $80 bill is a 25% tip. The guests may not leave a comment card, but built into your accounting system you can see if there is a pattern emerging.
  • Upselling superstar
    • Does one server consistently sell more? If your system isn’t detailed enough to show individual items the size of each check is a simple measure, but if your system can show the items on each check, look for drinks, appetizers and desserts. These are the items that a server will have to hustle more to move, and if one moves more than another there may be something to learn.

5. Convert the data

We talked briefly about it above, but it is more than just to learn about learning who is best and who isn’t. Make sure you have a clear picture of the reality. There may be more to the story than what is on the spreadsheets, a single behavior difference can affect how data is inputted. Consistency is key, when data is inputted, and how can affect data significantly. Also, definitional changes can affect it (what each person believes each item or behavior represents). In a restaurant situation there may be less room for ambiguity, but a small difference on when they ring up the check could be huge. Because if they are quick to get drink orders, and food orders, but slow to get it into the system, there may be no actual difference between how long the guest is at their table, but the perceptual difference from the data will be different. By clearly communicating when and how to perform certain tasks that ambiguity is reduced.

If the data is consistent, and there are noticed trends, understand that this isn’t the time to start slapping gold stars on your high performers and dunce caps on your low performers. Learn what behavior differences impact these metrics and use training to modify behaviors. Understand your staff and how they will behave when they know the data and how they are being measured.

A word of caution

Everyone will try to game the system, if they know what behaviors to adjust to improve the perception of their performance they will do their best. It is your job as a business owner to communicate the real message you want communicated. If you want faster turnover on tables, train the behavior for that, don’t tell your servers this is how you analyzed the data, then they will have the keys to the castle, and will start adjusting their behavior to affect the data not the turnover on tables.

Summary

It started with some simple questions, and can turn into a full dashboard and process for identifying high and low performers. High performers should be praised, and retained, low performers should be retrained or replaced. But if you don’t know who is a high or low performer, you may be running on your gut, and the cool bartender may be fun to talk to but his performance may be lacking in performance.

This doesn’t just apply to servers, within your own business consider what questions you have, or even problem. Follow the 5 steps:

  1. Identify the problem
  2. Find the right question
  3. Gather the data
  4. Analyze the data
  5. Convert the data into actionable business intelligence

Best of luck.

Disclaimer: The information contained in this document is provided for informational purposes only and should not be construed as financial or tax advice. It is not intended to be a substitute for obtaining legal, accounting, or other financial advice from an appropriate legal professional, financial adviser or for the purpose of avoiding U.S. Federal, state or local tax payments and penalties.

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