Gastronomy is at the doorstep of strong data analytics.
Every business owner who has an intention to compete must be very cautious with how he or she gathers and treats relative business data. Reasons for doing this are simple yet there is no simple way around – or hasn’t been one until recently.
Strong data analytics is driving many business sectors today to advance product development and to meet customer needs in ways unknown even a few years ago. Nevertheless, only 35% of businesses pay attention to their profit generation metrics and only 10% analyse customer behaviour. Therefore, the possibility to objectively evaluate one’s own performance is ignored by the vast majority. Whereas all they need to do is take their phone out and have a complete overlook in real time or for the upcoming period.
In the gastronomy industry chef creativity in conjunction with progressive and data-driven management is the recipe for success. While the biggest gastro giants have used this technology and data science to run their operations for years, such methods are now more affordable and accessible. As a result, smaller, family-owned gastro chains now have a much better chance to stay competitive.
Regardless of the time spent on the market, here are some things to keep an eye on:
- Time-framed revenue metrics;
- Employee monitoring
- Sales analytics
Being close to your customer
New systems allow businesses to better understand their final customer organising data such as: age, demographics, bestsellers and their popular combinations at popular times. This helps shape marketing campaigns and general understanding of your business concept. For instance, a live music venue must be renowned for its atmosphere and liveliness or else losing acts and patrons to better venues.
Restaurants can identify the exact duration of peak and off-peak periods, popular days and in-demand meals. Do you have the lower sales at 3pm on Tuesday? It may be a good time for a happy hour.
Data processing makes it easy to monitor the productivity of your waiters, chefs, cleaning staff etc and understand their workload during peak and off-peak times, and thus use this information to design effective PRP (performance-related pay) schemes. By using such data, restaurant managers can proactively remove shifts during specific time periods estimated to be more quiet or, conversely, add shifts when it is predicted to be busier. Consequently, better estimation of staff requirements saves a large chunk of business spending.
ABC analysis is used to categorise meals based on their sales frequency, profit and revenue margins. Hence, restaurants can optimise their menu by repositioning particular items in their menu cards, or to completely replace it with another dish. There may be anomalies of low profits during peak times; perhaps it is needed to increase the margin of top-sellers. Or, if a product is sold only once a day and the retail margin is less than 150% it should be left out from the menu.
Technology already plays a huge part in the day-to-day operations of businesses and people. With the ever-increasing threats SMEs face today, they must be ready for anything to avoid losing customer trust; harming revenue growth; or in the worst case, putting the future of the company in jeopardy. Looking ahead, sustainable and profitable businesses will be the ones who analyse and care about the data that they produce.