How to get value from your restaurant data warehouse

Here at Tenzo we think a lot about data, how to create value from data, and what that means for the IT architecture of our different clients.

3As of Restaurant Data

We use our “3A” framework to think about a broad data approach:

  • Absorb: This is the process of getting all of your data into one place. It may include POS data, labor data, social data, inventory data, customer data, compliance data, IoT data, the list goes on. Importantly, you need to have both a process for loading the data, and then somewhere to put it.
  • Analyze: Now you’ve got your data, you need to extract insights. This ranges from simple alerts and exception reporting, to advanced analytical topics that might involve machine learning and A.I.
  • Act: Finally — the hard part — now you have to get someone to do something with the insights you have.

Let’s talk through each in more detail.

1. Absorb

In today’s world, we’re going to assume that you are comfortable working in the cloud. Of course, you could opt to store your data on premise — but you don’t need the hassle of maintaining architecture, and with AWS, Google Cloud and Microsoft Azure so prevalent — we’d recommend you start there.

Then you need to decide exactly to store your databases, as an example, you could choose:

  • Traditional SQL database e.g., MySQL, PostgreSQL, Microsoft SQL Server
  • NoSQL e.g., MongoDB, Cassandra etc.
  • Some hybrid approach e.g., Google BigQuery, or a combination of SQL and NoSQL

Our advice would be to choose a data store to match the kind of data you’re importing. For example, transaction and labor data is inherently very transactional (and thus lends itself to SQL), whereas IoT or customer feedback data may lend itself more towards a NoSQL type approach.

Having chosen somewhere to put the data — you then have to think about how to ingest it. For this, you’re going to have to build relationships with all of the people who store your data and then figure out how to get the data. Typically, this can be a combination of:

  • Using a public API
  • Streaming data live from stores; using custom code if needed
  • Daily dumps of data from vendors’ servers

Importantly, you have to build an understanding of the data you’re ingesting to make sure it’s accurate.

Now you have a choice: build vs. buy?

As a small player, the answer is easy… you won’t have the scale to cover the cost of building yourself. However — we also think that even at larger scales you should buy as long as your partner is open. It can be considerable effort an expense to own and maintain a data warehouse, and of course this doesn’t include the tremendous cost of creating that infrastructure.

Note: a common misconception is that you need to own the data warehouse to give you the depth of analysis you need. This just isn’t true if you have an open provider (yes — at Tenzo, we are!)

Analysis time!

2. Analyze

Ok — so now you’ve gotten all of your data in one place, what on earth do you do with it?

We like to categorize this in to 3 key areas:

a) Use alerts and exception reporting to catch the low-hanging fruit

First, you need to identify places that you want to catch obvious problems e.g.,

  • A significant year-on-year drop for a given location
  • Low inventory for a specific item
  • Potential incidents of fraud at the employee level
  • Respond to poor customer feedback and reviews

b) Dive one level deeper to fine tune the machine

Now it’s time to think about fine tuning your operating machine e.g.,

  • Optimizing daily labor schedules to match to demand
  • Trimming opening hours when needed
  • De-listing low performing items
  • Building team schedules that work well together
  • Identify the meaning behind customer feedback (understand sentiment around specific issues etc.)
What is A.I. and how is it relevant to me?

c) Now what on earth is “A.I.” and how is that relevant to me?

So, we all hear about A.I. and machine learning — but isn’t that just relevant at Google (playing Go) or for Uber and driverless cars ?

Well — actually, it can be used in restaurants too. In simple terms, A.I. allows computers to learn. That means they can recognize patterns outside of normal statistics (e.g., correlations and regressions), and ultimately start making decisions.

Some examples of where we see the potential for A.I. to be used in restaurants include:

  • Advanced forecasting (e.g., including weather and events) to aid prep, procurement and staffing
  • Shift planning and team selection to optimize sales
  • Fraud detection
  • Optimized digital signage and improved kiosk up-sell
  • Predictive maintenance and compliance schedules
  • Real-estate purchase and location selection
  • Dynamic promotion and pricing decisions
  • Talent identification and on-boarding

So— should you build this yourself, or look to a partner? At a very small level (1–2 locations) you may do much of this yourself, but as you hit 2–100 locations you’re going to start to want something that thinks about this on your behalf.

Above 100 locations and, while you might have an in-house capability for basic business insight, you need to assess whether you’ll have a leading data-science capability. As already discussed — incase you still want to the ability to run custom analytics, it helps to connect to an open platform— you need to be able to get your data out to talk to other systems.

At Tenzo, we’ll help you connect to other systems, like TableauLooker etc., so you can see data the way you want.

3. Act

Now the trickiest of all of the “3As” — you need to get managers in stores to do something with business insight.

How do you drive action?

The nice thing here is that today you have a powerful tool to do that — the cell phone.

We think all insights need to be:

  • Actionable: something the person can do e.g., change this shift, order this item, talk to this employee
  • Available: delivered to the person in a way they can digest e.g., email, mobile app, push notification etc.
  • Targeted: tailored to the right person e.g., sentiment to the CMO, menu insights to a COO and a forecast to the store manager

Our findings here are that you can so-far on your own (e.g., static dashboards and daily reports), but to get this seamless and tailored it’s much better to go to someone with platform expertise. What that means is you need a web app, and iOS app and an Android app.

Of course, at Tenzo we can do all of the “3As” or even just some of them if you’d prefer. Reach out to us to understand more.

Thanks for reading — reach out if you’d like to talk through in more detail.

How does weather affect restaurant sales?

This is the first of what is intended to be a 3 part series on how to get quality forecasts. We’d love your feedback!

At Tenzo we’ve spent a lot of time thinking about how to forecast accurately and wanted to share a couple of the key insights. Typically we have found:

  1. A smart forecasting algorithm can out-perform a store manager in the long run by 25–50%, but it might miss short term events (e.g., roadworks, staff shortage) that only a manager may know about
  2. Weather and events are a critical element in improving a typical forecast
  3. Rain affects sales, but after a certain amount of rain the impact diminishes. Extreme temperatures (vs. normal for the season) are what cause significant deviations in sales.

How do we think about the impact of machine learning?

The below chart compares a 4-week rolling average (e.g., the last 4 Mondays) to a machine learning generated forecast. We typically find a 4-week average this is the best a good manager can do given their memory for events.

MAPE, for a 4-week average forecast vs. a machine learning generated forecast


As you can see — the computer wins overall. There may be days when a manager knows something the computer does not, but overall results tend to this.

Now, let’s look at a chart showing how rain impacts sales for a given location.:

Daily sales variance per mm of rain


The result is clear — when it start to rain, sales drop-off, but beyond a certain point — people are no longer driven by the rain.

Now, let’s look at temperature:

Daily sales variance per degree of temperature (celsius)


Interestingly — this chart is looking at a day in July. A big portion of temperature will be captured in the normal seasonality (which any computer based forecasting system should capture). However, what becomes apparent is how it’s all about extremes — if the day is unseasonably warm or cold it will dramatically affect sales up to a point.

Note: importantly all of these results will be dependent on the specific location, brand and type of business. That’s why you need a machine!

Thanks for reading, we hope we’ve shown:

  1. How weather can be an important factor for your business
  2. The kind of dramatic improvement you can get by looking at it
  3. How a computer can outperform a typical location manager

Let us know your thoughts!

To arrange a demo of Tenzo, please visit

Identifying insights – Areas data will give your business competitive advantage

Data is a gold mine of insights, which can dramatically add value to your business across the board and give a significant competitive advantage. But how is it that most businesses fail to use their own data (sales, reviews, etc) and miss out on the opportunity to gain insights, make better decisions and ultimately grow?

The aim of this article is to show you that clear data will always triumph over ‘gut’ led decision making. Businesses that use their data properly will always have a competitive edge as they can react faster, forecast better and gain real insight about their business activity.

Here are four benefits of using data in your business.

  1. Use social data to increase sales

Did you know that one star social media rating has been shown to drive 7% of additional revenue? By continuously monitoring the data from customer reviews on social sites like Yelp, Google Places, Facebook, Tripadvisor, getting alerted of bad reviews and reacting quickly, you will have a direct impact on sales.

Furthermore, focus on using your social data to raise your customer loyalty and engage more new customers instantly.

2. Use data to reduce your COGS

Data can add value by helping you accurately forecast your future sales. By analysing many factors such as weather, events and past sales performance it is possible to get an accurate forecast which in turn can help you adjust staffing levels, optimise opening hours and reduce wastage.

3. Data will highlight your top staff performers

In hospitality, there is a massive variability in staff performance — 150% variability in check size dependent on employee and a staggering 800% in speed of service. Analysing transactional data can help identify the top performers, ensuring that the best staff are scheduled at the right place at the right time.

4. Data will train better staff

By showing your front line team members data on average customer spend and speed of service you can train staff to perform to a higher level. Data analytics can help you give employees real time feedback on their performance. Furthermore, incentivising staff to outperform the benchmark, will increase sales.

In conclusion, the more data you collect from customers, from your sales and from your employees, the more actionable insights you will receive, which will significantly add value to your business. Developing a data analytics capability by using the best tools such as Tenzo is essential.

Tenzo is a platform that gives hospitality and retail businesses actionable insights from their real time data.

The power of data in restaurant chains

Managing a chain of restaurants is very challenging, and in order to get the best results the team in each restaurant needs to have access to the right information in order to make the right decisions.

This is becoming ever more complex as restaurants are collecting an increasingly large amount of data.

In this article we will set out how technologies that have been available to Google and Amazon are now set to revolutionize the restaurant industry.

We see the approach in 3 key steps:

1)Data collection: you must gathering data from all facets of your business. We like to break it down as follows:

  • “In-store” data e.g., POS, inventory, employee data
  • “Near-store” data e.g., social media reviews and other 3rd party content
  • “External data” e.g., weather, traffic etc.

2)Insight generation: then turning the data into actionable insights — here it’s important that the steps taken by each staff member must be clear, and ideally you can quantify the result

3)Insight delivery: finally , you must deliver them to the right person (e.g. a store manager) without having to wait for the insight to be passed down the management chain.

You need to ensure ease of access to relevant and reliable information, while decentralizing decision making ability away from the boardroom, or headquarters.

These insights will drive decision-making and and help better manage restaurant chains. Actually, the faster and more accurately you can access and review information about your restaurant, the better you can manage, control and improve your operation.

The use of big data in your chain should increase your productivity and maximize your marketing ROI. For example, based on the analysis of your sales you could adjust staffing and procurement levels based on demand or you could reduce food cost by reducing wastage. With the collection of data from social media and review sites you are able to see how well your sites and staff are performing.

Here are five ways you can get value from your data:

  • Raise customer satisfaction to drive additional traffic

Improve your overall customer reviews and get alerted of bad reviews immediately, so they can be actioned in real time. The store managers will receive alerts if something needs attention to engage your most valuable customers.

  • Improve staff performance: increase speed and upsell

Increase your speed of service, your average check size and give staff real time feedback on their performance and incentivise to sell more. We’ve seen more than 150% variability in up-sell across staff members, and even up to 800% in speed of service!

  • Optimize your menu

Analyze menus to find the most popular dish. Menu analytics can have far-reaching benefits, whether in identifying complementary menu pairings, creating discounts for winning combinations of such items, or identifying non-performing items and removing them.

  • Reduce wastage of food and labour cost

Increase procurement efficiency with automated forecasting and find the right balance of delivery and in-store resources — more accurate ordering and staff scheduling.

  • Test and learn: bring software development practices to your restaurant!

A restaurant can test a program in one location and then, depending on its success, choose to apply the program at other locations and across various levels. Having access to the data enables you to quantity an initiative’s success.

At Tenzo we can offer all these insights in one place, on mobile and web. All the insights are delivered in real time to the right person in order to improve decision making and your bottom line!